Risk Factors for Osteoporosis
\\n\\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"IntechOpen Maintains",originalUrl:"/media/original/113"}},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
\n'}],latestNews:[{slug:"intechopen-supports-asapbio-s-new-initiative-publish-your-reviews-20220729",title:"IntechOpen Supports ASAPbio’s New Initiative Publish Your Reviews"},{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"}]},book:{item:{type:"book",id:"268",leadTitle:null,fullTitle:"Glaucoma - Basic and Clinical Concepts",title:"Glaucoma",subtitle:"Basic and Clinical Concepts",reviewType:"peer-reviewed",abstract:"This book addresses the basic and clinical science of glaucomas, a group of diseases that affect the optic nerve and visual fields and is usually accompanied by increased intraocular pressure. The book incorporates the latest development as well as future perspectives in glaucoma, since it has expedited publication. It is aimed for specialists in glaucoma, researchers, general ophthalmologists and trainees to increase knowledge and encourage further progress in understanding and managing these complicated diseases.",isbn:null,printIsbn:"978-953-307-591-4",pdfIsbn:"978-953-51-6568-2",doi:"10.5772/792",price:159,priceEur:175,priceUsd:205,slug:"glaucoma-basic-and-clinical-concepts",numberOfPages:604,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"b9a66374f7429cc798c56e9e8149a1aa",bookSignature:"Shimon Rumelt",publishedDate:"November 11th 2011",coverURL:"https://cdn.intechopen.com/books/images_new/268.jpg",numberOfDownloads:166797,numberOfWosCitations:50,numberOfCrossrefCitations:30,numberOfCrossrefCitationsByBook:2,numberOfDimensionsCitations:64,numberOfDimensionsCitationsByBook:3,hasAltmetrics:1,numberOfTotalCitations:144,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 27th 2010",dateEndSecondStepPublish:"November 24th 2010",dateEndThirdStepPublish:"March 31st 2011",dateEndFourthStepPublish:"April 30th 2011",dateEndFifthStepPublish:"June 29th 2011",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"54335",title:"Dr.",name:"Shimon",middleName:null,surname:"Rumelt",slug:"shimon-rumelt",fullName:"Shimon Rumelt",profilePictureURL:"https://mts.intechopen.com/storage/users/54335/images/system/54335.jpg",biography:"Prof. Shimon Rumelt received his medical degree and diploma in ophthalmology from Tel Aviv University, Israel. 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\r\n\tMale circumcision is a procedure that has been practiced since the dawn of human culture more than six thousand years ago. It is performed for both medical and non-medical reasons. Despite being a simple procedure, it may lead to a myriad of minor and even crippling complications, if not done properly, such as iatrogenic injury of the glans or the urethra. Several techniques have been used to perform circumcision including the classic open technique, clamp technique, and laser /electrocautery technique with various safety outcomes. Overtime time, there has been an ongoing debate over the pros and cons of cultural circumcision with a significant dichotomy between the opinions of the experts in the field.
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Although most statistics on the prevalence of osteoporosis quoted in the literature are from those published in 1991 to 2004 [2,3] the projection is nevertheless very consistent. Thus, osteoporosis is estimated to affect over 200 million people worldwide and 75 million people in Europe, the United States, and Japan [4]. Approximately 1 in 2 women and 1 in 5 men older than 50 years will eventually experience osteoporotic fractures [5] An increase in the worldwide incidence of hip fracture by 240% in women and 310% in men is projected by the year 2050 [6]. Osteoporosis is “a major public health threat” that is projected to results to 8.1 million fractures (78 % women, 22 % men) during the period between 2010 and 2050 [7]. The condition costs our healthcare system $18 billion per year [8]. Records show that Osteoporosis has been known to exist since the Egyptian mummies have been found with suspected dowager’s hump [9]. Newer findings on all aspects of osteoporosis have increased exponentially. The more importantly ones are the introduction and improvement in more sensitive diagnostic instruments, discovering an ever increasing number of risk factors including oxidative stress, opening up new knowledge on the involvement of the bone forming cells osteoblasts and the bone resorbing cells osteoclasts in the development of osteoporosis and finding new drugs and the nutritional alternatives for the prevention and treatment of osteoporosis. Advances in knowledge on osteoporosis is not without pitfalls. Hormone Replacement Therapy (HRT), once a first line of treatment for osteoporosis has been discontinued due to side effects [10]. It is becoming more evident that the drugs known as bisphosphonates, although effective in stopping the resoption of bone and preventing osteoporosis in women, are associated with a number of side effects [11,12]. The side effects have been alarming a number of women with osteoporosis in such a way that they are now resorting to other mode of treatment, including that from natural food components. Our laboratory has carried out studies on the use of antioxidants such as lycopene and polyphenols as possible alternatives and/or complementaries to drugs in the treatment and prevention of osteoporosis. This chapter will include an overview on osteoporosis, the role of oxidative stress in bone cells osteoclasts and osteoblasts, oxidative stress as a risk factor in the development of osteoporosis and a review of studies on the use of antioxidants in counteracting oxidative stress in the prevention of osteoporosis. These topics should put our research in perspective and offer a rationale to our study approaches. Finally we will highlight our pioneering studies on the effects of the lipid-soluble antioxidant lycopene and the water-soluble antioxidant polyphenols present in a nutritional supplement in an
Bone as a dynamic tissue continuously renews itself throughout life by the process of bone remodeling carried out by a functional and anatomic structure known as the basic multicellular unit (BMU) that requires the coordinated action of three major types of bone cells: osteoclasts, osteoblasts and osteocytes [13,14]. The remodeling process is the result of interactions between these cells and multiple molecular agents, including hormones, growth factors, and cytokines. Bone remodeling is a physiological process that follows a time sequence lasting approximately six months wherein osteoclasts eliminate old or damaged bone which is subsequently replaced with new bone formed by osteoblasts, while the osteocytes functions in the transduction of signals necessary to sustain mechanical loads. The coupled process of bone formation and bone resorption in mature, healthy bone is tightly regulated and maintained in order to prevent a significant alterations in bone mass or mechanical strength after each remodeling cycle [14,15]. At menopause when estrogen production is decreased, the increase in resorption cavities due to increased bone resorption, but insufficient increase in bone formation, results to incomplete filling of resorption cavities with new bone leading to a permanent loss of bone mass. Disturbances in the remodeling process of this nature can lead to metabolic bone diseases. One such disturbance caused by oxidative stress, shown to control the functions of both osteoclasts and osteoblasts, may contribute to the pathogenesis of skeletal system including osteoporosis, the most prevalent metabolic bone disease [16].
Women over the age of 50 become susceptible to osteoporosis because of the loss of estrogen at menopause [17]. As well, men’s susceptibility to osteoporosis is due to low levels of the sex hormone testosterone [18-20]. In the past, a majority of men view osteoporosis as solely a “woman’s disease.” This is because men in their fifties do not experience the rapid loss of bone mass that women do in the years following menopause, and therefore men osteoporosis does not set in until later in life [21,22]. However, by age 65 to 70, men and women are losing bone mass at the same rate [23]. The World Health Organization (WHO) aptly defined osteoporosis as a systemic disease that is characterized by low bone mass and deterioration of the microarchitecture of bone, resulting in an increased risk of fracture. Bone mass or bone mineral density (BMD) is measured using a dual-energy x-ray absorptiometry, or DXA, at various skeletal sites, including the spine, hip and wrist [24].
BMD is expressed as T-score which is a value compared to the expected value for young adults of the same sex and race. WHO has established that for normal BMD, the T-score is between standard deviation of +2.5 and -1.0; for osteopenia/low BMD, T-score is between -1.0 and -2.5, inclusive; for osteoporosis, T-score is lower than -2.5 and for severe osteoporosis,T-score is lower than -2.5 with the presence of one or more fragility fractures [25]. Thus BMD values can identify osteoporosis, determine the risk for fractures (broken bones), and measure the response to osteoporosis treatment [26]. In the case of severe osteoporosis, minimal trauma such as a minor fall or just a hug from a loved one can result to fragility fracture. Fragility fracture is defined by WHO as “a fracture caused by injury that would be insufficient to cause fracture normally. The spine, hip and distal forearm are the most common sites of fragility fracture [27]. Some doctors recommend that people be tested on a regular basis for bone loss. For women, those tests should begin after menopause. For men, they should begin after the age of sixty-five. Such tests are important since there are seldom other signs of osteoporosis. Therefore, those who have a higher rate of bone loss and are at higher risk for a fracture need a better diagnostic tool. Recently, the WHO introduced a prognostic tool to evaluate fracture risk of patients called the FRAX® [28]. The FRAX tool takes into account country, bone mineral density of the hip (when available), age, sex, and 8 clinical risk factors to calculate the 10-year probability of a major osteoporotic fracture and the 10-year probability of a hip fracture [29]. It assesses the 10-year risk of osteoporosis based on individual patient models that combines clinical risk factors (CRF) as well as BMD at the femoral neck [30].
During bone remodeling in healthy young adult, bone formation by osteoblasts equals bone resorption by osteoclasts. However In postmenopausal bone loss, the remodeling process becomes significantly more active with a primary increase in bone resorption and a corresponding, but an insufficient increase in bone formation [31]. Enzymes and/or other proteins are released into the blood that are considered to reflect either bone formation or bone resorption [32] and are termed as bone turnover markers. Molecular markers of bone turnover have been developed as a product of bone remodeling [31] in the diagnostic and therapeutic assessment of metabolic bone disease [33]. They are now used for the individual monitoring of osteoporotic patients treated with antiresorptive agents [34]. Specific and sensitive assessment of the rate of bone formation and bone resorption and prediction of fracture [35] can now be possible using commercially available biochemical markers [36]. It remained to be seen whether bone turnover markers might contribute a useful independent risk factor for inclusion in FRAX [30]. The bone turnover markers we used for our clinical studies were crosslinked N-telopeptide of type I collagen (NTx) [37-39] and crosslinked C-telopeptide of type I collagen (CTx) [40,41] as bone resorption markers and bone alkaline phosphatase (BAP) [37-39] and Procollagen type I N-terminal propeptide (PINP) [40,41] for a measure of bone formation in the serum of participants.
Although BMD is considered the best parameter for determining the osteoporotic status of men and women, BMD is static and cannot predict changes that may occur post-measurement [42]. As well, changes in BMD occur slowly and can take up to one to two years to be detected during the course of therapy [43,44]. An alternative or additional parameters now measured clinically as either formation or resorption markers in the urine or serum of participants are bone turnover markers which can reveal changes much earlier in the course of therapy compared to changes in BMD [34]. When combined with BMD measurement, changes in bone turnover markers have been significantly linked to fracture risk due to a significant positive correlation between high bone turnover markers and loss of BMD [35]. Bone turnover markers are therefore very useful in assessing treatment protocol for a short duration period, e.g., 3 to 6 months. Measurement of bone turnover markers was therefore utilized in our clinical study during which postmenopausal women were given the antioxidant lycopene for 3 months [37-39] and in another study during which nutritional supplement greens+bone builderTM were administered for a period of eight weeks [40,41]. As will be reviewed in later sections, during the short period of treatment, positive changes were measured that correlated decreased bone resorption markers with decreases in oxidative stress parameters and thereby to decrease of risk for osteoporosis in postmenopausal women.
Some of the risk factors for osteoporosis [45,46] are presented in Table 1 [47]. The risk factors that are of interest in our studies are oxidative stress-generating factors, including smoking, alcohol intake, low antioxidant status, nutrition deficiency, excessive sports activity and excessive caffeine intake. Oxidative stress will be reviewed in detail below.
Up until 10 years ago, the first line of treatment for women who have gone through menopause and was diagnosed with osteoporosis was hormone replacement therapy (HRT). However, results of the Women’s Health Initiative (WHI) warned women that HRT leads to higher risks for breast cancer, cardiovascular events, blood clots, cognitive decline, and more [10]. This treatment for osteoporosis has since been discontinued and is prescribed only for a short period of time to alleviate hot flashes in menopausal women [48]. A wide range of pharmaceuticals are available for the treatment of osteoporosis. The current antiresorptive treatments approved by the Food and Drug Administration (FDA) include a number of bisphosphonates under specific trademarks which inhibit bone resorption [49]. Some are taken daily while others are formulated for weekly, monthly or intermittent oral use [50,51]. The newer bisphophonates are injectables such as ibandronate and Zoledronate [51] Other drugs available include calcitonin, strontium renalate and the Selective Estrogen Receptor Modulator (SERM), Raloxifene (Evista) [52]. Parathyroid hormone, PTH1-34 or teriparatide (Forteo), is the only anabolic agent currently approved for use by the FDA [24,53]. The new class of osteoporosis medications now approved for use is a fully human monoclonal antibody (Denosumab) which bind to RANKL, imitating the effects of OPG and acting as an inhibitor of RANKL [54]. A number of other drugs are being tested clinically for osteoporotic treatment and prevention.[24].
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t||
Race Sex Age Genetics Body size Family History Previous Fractures | \n\t\t\t\n\t\t\t | Chronic inactivity Low body weight Low lifetime calcium intake Medication used Oxidative stress-related factors | \n\t\t|
\n\t\t\t | Smoking Alcohol intake Low antioxidant status Nutrition deficiency Excessive sports activity Excessive caffeine intake | \n\t\t
Risk Factors for Osteoporosis
None of the drugs are without side effects. Side effects that emerged in clinical trials include esophageal irritation with oral administration and acute phase response with iv treatment or high-dose oral therapy. Uncommon side effects that have been noted with wide clinical use include osteonecrosis of the jaw, musculoskeletal complaints, and atypical fractures. The numbers of events are small, and a clear cause-and-effect relationship between these events and bisphosphonate treatment has not been established. Because Bisphosphonates accumulate in the bone, they create a reservoir leading to continued release from bone for months or years and provide some residual antifracture reduction when treatment is stopped. For this reason, there is a recommendation for a drug holiday after 5 –10 yr of bisphosphonate treatment [12,55]. The length of the holiday is based on fracture risk and previous duration of treatment and BMD status. Studies with risedronate and alendronate suggest that if treatment is stopped after 3–5 yr, there is persisting antifracture efficacy, at least for 1–2 yr. For those who are not on holiday, the consensus from expert panels [12] suggest not stopping the use of drug since the side effects are often rare, and that the benefits outweigh the side effects. In the balance, most individuals who have osteoporosis are much better taking an osteoporosis medication [11].
Considering the possible adverse side effects of HRT and the ever increasing reports on the side effects of bisphosphonates in the management of postmenopausal osteoporosis, there is an increasing demand for complementary and alternative medicine (CAM) for the prevention and treatment of osteoporosis [56]. CAM is the term for medical practices, services and products that are not a part of standard care. Some of the approaches include exercise, acupuncture, diet, herbs rich in polyphenols and nutritional supplements including calcium, zinc, magnesium boron and other vitamins and minerals. Recent dietary guidelines for the prevention of chronic diseases have recommended an increase in the consumption of fruits and vegetables worldwide [57] that are good sources of dietary antioxidants [58]. The beneficial effects of antioxidants in bone health and osteoporosis are demonstrated epidemiologically and through clinical intervention. Given that many nutrients have been identified as being beneficial to bone health [59,60], there is strong scientific support for the potential benefits of incorporating therapeutic nutritional interventions with contemporary pharmaceutical treatments [61]. Diet is now recognized as an important life-style factor in the management of bone health [62]. As will be reviewed in this chapter, our clinical studies on lycopene treatment and nutritional supplements containing polyphenols and other nutritional components showed positive results on bone health.
Oxidative stress is caused by reactive oxygen species (ROS) which are the main by-products formed in the cells of aerobic organisms that can initiate autocatalytic reactions in such a way that the target molecules gets converted into free radicals causing a chain of damage [63]. There is ample evidence to show that oxidative stress induced by ROS increases the rate of bone loss and is therefore a risk factor for osteoporosis. Epidemiological evidence in humans and studies in animals indicate that aging and the associated increase in ROS are responsible for bone loss [64]. As will be reviewed in later sections, oxidative stress is associated with the activity and function of both the osteoblasts and osteoclasts cells, the two major bone cells involved in the pathogenesis of osteoporosis.
Oxidative stress results from the weakening of antioxidant defense or an over production of ROS in the body. ROS contains one or more unpaired electrons, a state that makes them highly reactive as they seek out another electron to fill their orbital and stabilize their electron balance [65]. Therefore, ROS are a family of highly reactive, oxygen-containing molecules and free radicals, including hydroxyl (OH –), superoxide radicals (O2 –), hydrogen peroxide (H2O2), singlet oxygen, and lipid peroxides [66]. ROS have an extremely short half-life and are difficult to measure in humans, but it is possible to measure the damage they cause to protein, lipids, and DNA and the damage is manifested as chronic diseases including osteoporosis [67]. This can occur by the induction of apoptosis, reduction of cellular proliferation, cell cycle arrest and modulation of cellular differentiation [68]. The major intracellular sites for the generation of ROS are via electron transport chains in the mitochondria, endoplasmic reticulum and nuclear membranes [69]. Oxidative stress may result from normal metabolic activity [70]; during acute or chronic immune responses [71]; lifestyle factors such as cigarette smoke [72,73], high alcohol intake [74,75], low antioxidant status [76], nutrition deficiency [74] excessive sports activity [77], excessive caffeine [78]; and environmental factors such as ultraviolet radiation, chemicals, pollution and toxins [79]. ROS production increases with age [80,81] and is associated with several chronic diseases including osteoporosis.
Under normal physiological conditions, the cells can fight free radical attack or oxidative stress by promoting antioxidant defenses. A number of endogenous defense mechanisms are present in the body, including the metal chelating proteins and the endogenous antioxidant enzymes catalase (CAT), glutathione peroxidase (GPx) and superoxide dismutase (SOD). [82]. Exogenous antioxidants come from dietary sources present in fruits and vegetables containing several phytonutrient antioxidants such as the carotinoids potent antioxidant lipid-soluble lycopene; the water-soluble antioxidant polyphenols; and vitamins such as C and E [83]. In cases where the endogenous antioxidants or antioxidants from diet fail to prevent oxidative damage, the repair antioxidants come into play which include DNA repair enzymes, lipase, protease and transferase [69]. When antioxidants loses its fight with oxidative stress, diseases associated with oxidative stress develop, which include cardiovascular disease, cancer, diabetes, neurological diseases and osteoporosis [84].
The phytochemical antioxidants that are naturally present in plant- and animal-derived foods include the carotenoids, which are lipid-soluble, to which the potent antioxidant lycopene belongs and the water-soluble antioxidants such as polyphenols [85]. Figure 1 is a cartoon depicting the production of oxidative stress from ROS, the damaging effects they exert on DNA, lipid and protein which subsequently leads to chronic diseases and the protection afforded by antioxidants.
Oxidative Stress/Antioxidants & Chronic Diseases
Lycopene is a potent antioxidant that is not synthesized in the body. It is a carotenoid acyclic isomer of ß-carotene, with no vitamin A activity [86]. It is a highly unsaturated, straight-chained hydrocarbon containing a total of 13 double bonds, of which 11 are conjugated, making it one of the most potent antioxidants [84,87]. The singlet oxygen-quenching ability of lycopene is twice that of ß-carotene and 10 times that of α-tocopherol [88]. The chemistry and antioxidant properties of lycopene have been comprehensively reviewed [87]. Other than from tomatoes and processed tomato, the dietary lycopene source of 85% of North Americans, lycopene can also be obtained from watermelon, pink guavas, and pink grapefruit [85]. Lycopene in an all-trans configuration such as that found in raw tomatoes, is not readily absorbed. Lycopene is absorbed more efficiently from processed tomato products than from raw tomatoes because it is converted from the all-trans to the cis-isomeric configuration with heat processing [89,90]. Since lycopene is a lipid-soluble compound that is absorbed via a chylomicron-mediated mechanism [91], the presence of small amounts of lipids further enhance its absorption [92]. The health benefits of lycopene may be due to its potent antioxidant property, although there is evidence for other mechanisms such as its effects on gap junction communication [93] and cell cycling [94]. The reported average daily intake levels of lycopene vary considerably from country to country, from 0.7 mg per day in Finland to 25 mg per day in Canada. However, a generally accepted universal level of daily intake is 2.5 mg. There is no official recommended daily intake of lycopene, but based on published research, a daily intake of 7 mg is suggested [95].
The role of lycopene in the prevention of human diseases is supported by a number of evidence [96]. Giovannicci was the first to publish the initial epidemiological observations suggesting an inverse relationship between the intake of tomatoes and lycopene and the incidence of prostate cancer [97]. Since then, there have been several epidemiological as well as clinical intervention studies showing the relationship between lycopene intake and the prevention of cancers at other sites, as well as coronary heart disease, hypertension, diabetes, macular degenerative disease, male infertility, and neurodegenerative disease [84]. The role of lycopene in bone health has so far been based on its potent antioxidant properties, the well known role of oxidative stress in bone health, and the limited studies on the effects of lycopene in bone cells in culture (see below) and more recently, the results of epidemiological studies [39,98]. To date our clinical intervention studies at St. Michael’s Hospital on the role of lycopene and elucidation of its mechanism in lowering the risk for osteoporosis in postmenopausal women (aged 50 to 60 years) are so far the only studies reported in the literature.
Polyphenols are a class of water-soluble molecules naturally found in plants. They are defined as compounds having molecular masses ranging from 500 to 3000–4000 Da and possessing 12 to 16 phenolic hydroxy groups on five to seven aromatic rings per 1000 Da of relative molecular mass [99]. It is estimated that there are 10,000 different phytonutrients (phyto, meaning from plants). To date, over 8000 polyphenols have been identified [100]. Polyphenols can be divided into 2 main groups: flavonoids and non-flavonoids [101-103]. The health benefits associated with fruits, vegetables, red wine, tea, and Mediterranean diets are probably linked to the polyphenol antioxidants they contain [59,104,105]. The polyphenols of interest in our study are a mixture of flavonoids such as quercetin, apigenin, kaempferol and luteolin present in the supplement greens+TM [106]. greens+TM in combination with another supplement, bone builderTM, were used in our study on osteoblasts cells and in clinical intervention studies on the prevention of risk of osteoporosis in postmenopausal women. Studies on polyphenols and bone will be reviewed in later sections.
(Studies involving lycopene and polyphenols will be reviewed at a later section)
The evidence being reported on the role of oxidative stress in osteoblasts has increased exponentially. Up until 2002, only a few studies were reported. Thus, it was reported that treatment of rat osteosarcoma ROS 17/2.8 cells with tumor necrosis factor-alpha (TNF-a) suppressed bone sialoprotein (BSP) gene transcription through a tyrosine kinase-dependent pathway that generates ROS [107]. Osteoblasts can be induced to produce intracellular ROS [108,109], which can cause a decrease in alkaline phosphatase (ALP) activity that is partially inhibited by vitamin E and cause cell death [108,109]. The intracellular calcium (Ca++) activity in osteoblasts is modulated by H2O2 by increasing Ca++ release from the intracellular Ca++ stores [110]. High concentrations of ROS can damage osteoblast cells to prevent normal growth and development [111] and have been shown to induce osteoblast death [112]. In osteoblasts, H2O2 has been shown to decrease cell growth, ALP activity, calcification, mineralization and gene expression of osteogenic markers such as ALP, bone sailoprotein (BSP) and runt-related transcription factor 2 (Runx2) [113,114]. More recently, Ueno et al induced oxidative stress by adding 100 microM H2O2 to osteoblasts cultured from rat bone marrow, and showed that this treatment substantially impaired the proliferation, differentiation, and mineralization and that addition of the antioxidant N-acetyl cysteine into the culture restored these damages to a near normal level [115]]. With their study on hydrogen sulphide, Xu et al concluded that hydrogen sulfide (H2S) protected MC3T3-E1 osteoblastic cells via a MAPK (p38 and ERK1/2)-dependent mechanism against hydrogen peroxide (H2O2)-induced oxidative injury that cause the suppression of proliferation and differentiation of the cells [116].
More recently reported inducers of oxidative stress include Arsenic trioxide [117], Cobalt and Chromium ion [118] and Vanadium Compounds [119].
In recent years, the number of antioxidants reported to prevent oxidative stress in osteoblasts are as follows: Tetrahydrostibene [125,126], Curculigoside [127], Green tea [128], Simvastatin [129], N-acetylcysteine [115], flavonoids from parsimmon [130], prevastatin [131], Linarin [132], Panaxnotaginseng saponin [133], crysoeriol from surya cilliata leaves [134], quercetin [135] Drynaria fortunei [136], cathamus tinctorium flower extract [137], estrogen [138], diazoxide, atractylodes japonica root extract [139]. and Myrcetin, a naturally occurring flavonoid [140]. The mechanism of osteblastic defense against oxidative stress was shown to involve β-Catenin which serves as a cofactor of the forkhead box O (FOXO) transcription factors [121].
The mechanisms involved in the differentiation of osteoclasts and their ability to resorb bone is beginning to be unraveled, and evidence shows that ROS may be involved in this process [141]. Superoxide was detected both at the osteoclast-bone interface and intracellularly using nitroblue tetrazolium (NBT), which is reduced to purple-colored formazan by ROS, suggesting the participation of superoxide in bone resorption [142]. Both the H2O2 produced by endothelial cells [143] intimately associated with osteoclasts and the H2O2 that is produced by osteoclasts [144] increase osteoclastic activity and bone resorption. H2O2 may also be involved in osteoclast motility [144], differentiation of osteoclast precursors [145] and the regulation of osteoclast formation [146]. Osteoclastic superoxide is produced by NADPH oxidase [147]. The degradation of collagen and other proteins is caused by highly destructive ROS as a result of the reaction of H2O2 with tartrate-resistant acid phosphatase (TRAP), found on the surface of osteoclasts [148]. 1,25-Dihydroxyvitamin D3 had a direct nongenomic effect on the generation of superoxide anion (O2_), which was inhibited by estrogen [149]. Estrogen has been reported to have an antioxidant property [150]. Hormones known to stimulate bone resorption, such as parathyroid hormone (PTH) [151] and 1,25(OH)2D3, have stimulatory effects on ROS production in osteoclasts [149] and hormones known to have inhibitory effects on bone resorption, such as calcitonin, inhibit ROS production [151].
Antioxidants also play a role in osteoclast activity. Osteoclasts produce the antioxidant enzyme SOD in the plasma membrane [152]. ROS production in osteoclasts was inhibited after treating the cells with antioxidant enzymes such as SOD [142] and catalase [146]. ROS production in osteoclasts was also inhibited by estrogen [149], the superoxide scavenger deferoxamine mesylatemanganese complex [153], pyrrolidine dithiocarbamate (PDTC), and N-acetyl cysteine (NAC) [154].
Other more recent antioxidant shown to affect osteoclasts include polyphenol extracts from dried plums [155], curcumerin [156], ascorbic acid [157], salvia miltorrhiza [158], coffee diterpene Kahweol [159], delthametrin [160], to name a few. The use of antioxidants from natural sources, such as fruits and vegetables, could be another way of inhibiting ROS. The use of lycopene and polyphenols in this regard is reviewed in a later section.
OVXed rats were treated with Strontium ranelate and at the end of the treatment, oxidative parameters including malondialdehyde (MDA) level, superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) and catalase (CAT) activities were determined by biochemical analysis methods. Their results showed that Sr has preventive effect on oxidative damage in ovariectomized rats [161]. Yin et al showed that protection against osteoporosis by statins is linked to a reduction of oxidative stress and restoration of NO formation in aged and ovariectomized rats [162]. To investigate the anti-osteoporosis effect of Rhizoma Drynariae (RD), an effectively traditional Chinese medicine and its action mechanism, Liu et al administered with or without RD extract at a therapeutic dose to a group of rats for 12 weeks and showed that the anti-osteoporosis effect of RD has been reliably confirmed by the metabonomics method and that the osteoporosis might be prevented by RD via, among other things, through intervening antioxidant-oxidation balance in vivo in rats [163]. Treatment of OVXed rats with Salvia miltiorrhiza ethanol extract significantly ameliorated the decrease in BMD and trabecular bone mass according to DEXA and trabecular bone architecture analysis of trabecular bone structural parameters by μ-CT scanning. As well, SM decreased the released TRAP-5b, an osteoclast activation marker and oxidative stress parameters including MDA and NO induced by OVX [164]. Oxidative stress (OS) was assessed 100 days postovariectomy by measuring the activity of several enzymes, including catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase, as well as the concentrations of malondialdehyde (MDA), nitric oxide (NO), and total sulfhydryl groups in plasma and bone homogenates of OVXed rats treated with or without vitamin C. Their results suggest that ovariectomy may produce osteoporosis and oxidative stress in females, and vitamin C supplementation may provide alterations regarding improvement in OS and BMD values [165]. Curcumin was shown to inhibit OVX-induced bone loss, at least in part by reducing osteoclastogenesis as a result of increased antioxidant activity and impaired RANKL signaling [166]. In order to investigate the pathologic significance of oxidative stress in bones, Nojiri et al showed that mice deficient in cytoplasmic copper/zinc superoxide dismutase exhibited a distinct weakness in bone stiffness and decreased BMD, aging-like changes in collagen cross-linking, and transcriptional alterations in the genes associated with osteogenesis. They further demonstrated that intracellular oxidative resulted in the decrease in osteoblast number and accompanied by suppression of RANKL/M-CSF osteoclastogenic signaling in bone; treatment with an antioxidant, vitamin C, effectively improved bone fragility and osteoblastic survival [167].
The detrimental effect of oxidative stress and the beneficial role of antioxidant in osteoporosis have been reviewed [58,83,168,169]. There is now ample evidence to suggest that ROS-induced oxidative stress is associated with the pathogenesis of osteoporosis. Thus, epidemiological studies demonstrated the adverse effect on bone of oxidative stress produced during strenuous exercise [170]; among heavy smokers [171] and that antioxidants including vitamin C, E and β-carotene may counteract these adverse effects and reduce the risk of osteoporosis [170-173]. A study of severe osteoporotic syndrome in relatively young males showed evidence linking osteoporosis to an increase in oxidative stress [174]. Maggio et al [175] demonstrated that women with osteoporosis had markedly decreased plasma antioxidants. A biochemical link between reduced bone density and increased oxidative stress biomarker 8-iso-prostaglandin F alpha (8-iso-PGF) has been reported [176,177]. Positive correlation was found between the severity of osteoporosis and the level of oxidative stress marker lactic acid in 2 men with mitochondrial deletion (mtDNA) [178].
Evidence points to the fact that Postmenopausal women are more prone to osteoporosis due to reduction in estrogen, but there is also ample evidence to support the theory that oxidative stress which accompanies the reduction in estrogen level may be the cause of osteoporosis [179]. Indeed, estrogen has been shown to have antioxidant properties [150]. Earlier reports on the association of oxidative stress with osteoporosis were confined mainly to epidemiological studies. Vitamins C, E, and A, uric acid, the antioxidant enzymes SOD in plasma and erythrocytes and GPx in plasma were consistently lower in osteoporotic than in control subjects. An epidemiological study by Hahn
Postmenopausal women with osteoporosis have been shown to have markedly reduced serum concentrations of retinol, β-cryptoxanthin, zeaxanthin and α- and β-carotene, compared to healthy postmenopausal women [175]. Overall carotenoid intake has been found to be inversely associated with risk of fracture [184]. Sadly, the effect of β-carotene on the risk of osteoporosis is still controversial. There are studies which suggest that β-carotene has beneficial effect on bone [98,185,186], while other studies suggest a null or even detrimental effect, most probably due to its association with vitamin A [187].
In summary, the studies presented above provide evidence of the detrimental effects of oxidative stress and beneficial effects of antioxidants on the risk of osteoporosis.
The direct role of lycopene in osteoblasts and osteoclasts, the cells involved in the pathogenesis of osteoporosis is now being unraveled. This involvement is further supported by both epidemiological and clinical intervention with lycopene in postmenopausal women men who are at risk of osteoporosis.
Only few studies on the effects of lycopene in osteoblasts have been reported. This is most likely because lycopene is not soluble in the culture medium and needed to be solubilized in organic solvent before it can be added to the cell culture. In our study, we used lyc-o-mato preparation that is partially dispersed in micelle form in water. When added to the human osteoblast-like SaOS-2 cells, lycopene had a stimulatory effect on cell proliferation as well as a stimulatory effect on alkaline phosphatase activity, a marker of osteoblastic differentiation in more mature cells but, depending on the time of addition, it had an inhibitory or no effect on younger SaOS-Dex cells. These findings comprised the first report on the effect of lycopene on human osteoblasts [188]. In another study, the effect of lycopene on MC3T3 cells (the osteoblastic cells of mice) was contrary to the findings of Kim et al. [188] in that lycopene had an inhibitory effect on cell proliferation [189]. The discrepancy in the effects of lycopene on cell proliferation could be a result of species differences, age of the cells when lycopene was added or experimental conditions. Both studies, however, reported an effect of lycopene on the differentiation of the cells by stimulating the alkaline phosphatase activity [188,189] and gene expression of BSP [189]. The lycopene used in our study is the trans-configuration (95% trans, 5% cis). Subsequently, we studied which configuration of lycopene will prevent the damaging effect of oxidative stress as well as repair this damage in human osteoblast cultures. Lycopene with varying content of cis- and trans- configuration (45:55, 28:72 or 5:95
To date, there have been only 2 studies on the effects of lycopene in osteoclasts [191,192]. Rao et al. cultured cells from bone marrow prepared from rat femur in 16 well, calcium phosphate-coated OsteologicTM multi-test slides. Lycopene was added to the cells in the absence or presence of the resorbing agent parathyroid hormone (PTH) (1-34) and mineral resorption, TRAP+ multinucleated osteoclast formation, and NBT-staining were measured. Lycopene inhibited TRAP+ multinucleated cell formation in both vehicle- and PTH-treated cultures. The cells that were stained with the NBT reduction product formazan were decreased in number after treatment with lycopene, indicating that lycopene inhibited the formation of ROS-secreting osteoclasts [192]. The effect of lycopene on osteoclast formation and bone resorption was also reported by Ishimi et al in murine osteoclasts formed in co-culture with calvarial osteoblasts [191]. Their results differed from those of Rao et al [192] in that they found that lycopene inhibited PTH-induced, but not basal, TRAP+ multinucleated cell formation. Furthermore, they could not demonstrate any effect of lycopene on bone resorption. They also did not study the effect of lycopene on ROS production.
Other than our intervention studies to be discussed in the next section, most of the intervention studies with lycopene were carried out in animals. Liang et al investigated the beneficial effect of lycopene on bone biomarkers in ovariectomized (OVX) rats. Their results showed that administration of lycopene (20, 30 and 40 mg/kg b.w.) for 8 weeks to OVXed rats significantly enhanced BMD, concluding that the consumption of lycopene may have the most protective effect on bone in OVX [193]. Ke et al fed OVXed rats for 3 months with EM-X, an antioxidant beverage derived from ferment of unpolished rice, sea weeds and papaya with combinations of microorganisms and contains, among other things, lycopene. Results showed that rats receiving EM-X for 3 months after sham operation or ovariectomy had increased bone density of the middle of femur that was statistically significantly different from unreated rats [194].
A systematic review of the experimental studies on Mediterranean diet and disease prevention was made and analyzed [195]. Although the Mediterrenean diet comprised of many different food components, it is striking that one of the components is abundance of plant foods including fruits, vegetables [195]. The two possible active components in its properties to prevent diseases are lycopene [196] and polypenols [197]. Epidemiological evidence support the beneficial effects of tomatoes and tomato products in the prevention of osteoporosis in the Mediterranean population [104].
The role of lycopene in the prevention of risk for osteoporosis has recently been reviewed [58,83,168,169]. Maggio et al [175] and Yang et al [198] both demonstrated that serum lycopene concentrations are lower in women with osteoporosis than in healthy women of the same age. The antioxidant mechanistic effect of lycopene is demonstrated by Misra
We carried out a cross-sectional study in which 33 postmenopausal women aged 50–60 years provided seven-day dietary records and blood samples for analysis of oxidative stress parameters and bone turnover markers. Our results showed that postmenopausal women who consumed an average of 7.4 mg of lycopene per day had significantly higher serum lycopene. Our finding that the estimated dietary lycopene had a significant and direct correlation with serum lycopene suggests that lycopene from the diet is bioavailable. Our finding that a higher serum lycopene was associated with a low NTx (
The overrall conclusions from the epidemiological studies support the beneficial role of lycopene in the prevention of risk for osteoporosis. Further clinical studies described below support this conclusion.
Since our laboratory is the only one to this date that reported clinical intervention studies with lycopene, this section will focus on reviewing our studies on the role of lycopene in the prevention of risk for osteoporosis in postmenopausal women.
We carried out 4 different clinical studies. In the first study, the objective was to determine the effects of a lycopene-restricted diet on oxidative stress parameters and bone turnover markers in postmenopausal women [38]. To avoid the effects of compounding factors with antioxidants, women who smoked or were on medications which may affect bone metabolism or have antioxidant properties were excluded from participating. Twenty-three healthy postmenopausal women, 50-60 years old, provided blood samples at baseline and after a one-month lycopene-depletion period. Serum samples were analyzed for carotenoids; the oxidative stress parameters protein thiols and lipid peroxidation TBARS; the antioxidant enzymes SOD, CAT and GPx, and the bone turnover markers BAP and NTX. Results revealed that lycopene restriction resulted in significant decrease in serum lycopene, lutein/zeaxanthin and α-/β-carotene as shown in Table 2, However, the overall percent change in these serum carotenoids was not as high as that seen for lycopene. Figure 2 demonstrates that all configurations of lycopene (all trans, 5-cis- and other cis lycopene) were all decreased after lycopene restriction. The antioxidant enzymes CAT and SOD were significantly depressed (data not shown). These changes were accompanied by a significant increase in the bone resorption marker NTx [Figure 3].
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t||
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t|||
α-carotene | \n\t\t\t408.4 ± 131.4 | \n\t\t\t334.4 ± 110.6 | \n\t\t\tp<0.05 | \n\t\t\t-13.03 ± 6.88 | \n\t\t
β-carotene | \n\t\t\t1443.0 ± 278.9 | \n\t\t\t1035.0 ± 221.7 | \n\t\t\tp<0.0005 | \n\t\t\t-22.84 ± 5.09 | \n\t\t
β-cryptoxanthin | \n\t\t\t403.2 ± 58.4 | \n\t\t\t367.6 ± 47.3 | \n\t\t\tp = 0.229 | \n\t\t\t-1.29 ± 8.21 | \n\t\t
Lycopene | \n\t\t\t1171.0 ± 111.1 | \n\t\t\t494.9 ± 48.46 | \n\t\t\tp<0.0001 | \n\t\t\t-54.86 ± 3.59a\n\t\t\t | \n\t\t
Lutein/zeaxanthin | \n\t\t\t516.4 ± 49.57 | \n\t\t\t443.0 ± 47.04 | \n\t\t\tp<0.01 | \n\t\t\t-12.77 ± 5.03 | \n\t\t
Change in serum carotenoid concentrations after postmenopausal women were assigned to Lycopene-restricted diet for a period of 1 month.
1 Wilcoxon matched pairs test used for these non-normally distributed data sets.
a Average percent change in lycopene was significantly higher than that seen for all the other carotenoids (p<0.0001), as determined by unpaired t-test or Mann-Whitney test.
Decrease in all configurations of lycopene (all trans, 5-cis- and other cis lycopene) in the serum of postmenopausal women after lycopene restriction.
Increase in the concentrations of the bone resorption marker, NTx, in the serum of postmenopausal women after lycopene restriction.
To our knowledge, this is the first study on the effects of dietary lycopene restriction on increasing the risk for osteoporosis in postmenopausal women which proves that lycopene may be beneficial in reducing this risk. It can be speculated that this significant increase in the bone resorption marker NTx may lead to a long-term decrease in BMD and increased fracture risk as was observed by Brown et al [42], and that a longer restriction period may be detrimental to a group of postmenopausal women who were already at high risk for osteoporosis. It can also mean that shorter wash-out periods of no lycopene consumption is all that is needed in clinical trials examining the effects of lycopene on bone health. In addition, lycopene is present in a select number of foods; therefore not consuming these products as a part of the regular daily diet may result in negative health consequences to bone health.
In a second study [37], clinical intervention was carried out to investigate directly the effects of supplementation with lycopene on decreasing the risk for osteoporosis. Sixty postmenopausal women, 50-60 years old, were recruited for a fully randomized controlled intervention. Following a one-month washout without lycopene consumption, participants consumed either (N=15/group): (1) regular tomato juice, (2) lycopene-rich tomato juice, (3) tomato lycopene capsules or (4) placebo capsules, twice daily for total lycopene intakes of 30, 70, 30 and 0 mg/day, respectively for 4 months. Serum collected was assayed for oxidative stress parameters and bone turnover markers. Lycopene-supplementation for 4 months significantly increased serum lycopene compared to placebo (p<0.001). Since the increase in serum lycopene was similar for all three supplements, the participants were pooled into a “LYCOPENE-supplemented” and PLACEBO-supplement group for further statistical analyses. LYCOPENE-supplementation for 4 months resulted in significant increase in total antioxidant capacity as shown in Figure 4, decreased in oxidative stress parameters protein oxidation [Figure 5] and lipid peroxidation [Figure 6] which correlated to a decrease in NTx [Figure 7] in the LYCOPENE-supplemented group; all changes were significantly different from the PLACEBO group. These findings suggest that it did not matter whether lycopene was in the form of tomato juice or capsule to exert its potent antioxidant properties beneficial in reducing the risk of osteoporosis in postmenopausal women [37].
In a third study [169]. Serum lycopene, bone turnover markers and oxidative stress parameter data were compared between postmenopausal women who were supplemented with lycopene and those who obtained lycopene from both a low and high daily food intake of lycopene to determine whether the elevated dose obtained through supplementation was more beneficial in reducing bone turnover markers than intakes typically obtained from the usual daily diet. Table 3 showed that women supplemented with lycopene had significantly lower TBARS and marginally significant lower NTx values than participants who obtained a low intake (or high intake lycopene, data not show) through their usual daily diets. These differences in NTx and TBARS may be attributed to a significantly higher concentration of serum 5-
Increase in the serum total antioxidant capacity of postmenopausal women supplemented with LYCOPENE compared to placebo capsules for 4 months. Values are mean ± SEM. Values compared within supplement group was determined to be statistically significant using repeated-measures ANOVA (*p<0.05).
Increase the serum concentration of thiol (meaning decreased protein oxidation) in postmenopausal women supplemented with LYCOPENE compared to placebo capsules for a period of 4 months. Values are mean ± SEM. Values compared within supplement group was determined to be statistically significant using repeated-measures ANOVA (*p<0.001).
Decrease in the serum concentration of TBARS or lipid peroxidation in postmenopausal women supplemented with LYCOPENE compared to placebo capsules for a period of 4 months. Values are mean ± SEM. Values compared within supplement group was determined to be statistically significant using repeated-measures ANOVA (*p<0.001).
Decrease in the serum concentration of bone resorption marker NTx in postmenopausal women supplemented with LYCOPENE compared to placebo capsules for a period of 4 months. Values are mean ± SEM. Values compared within supplement group was determined to be statistically significant at 2 and 4 months using repeated-measures ANOVA (*p<0.01 and **p<0.001).
In a fourth study, we investigated whether the 172T→A or 584A→G polymorphisms of the paraoxonase 1 (PON 1) modulated the effects of serum lycopene on bone turnover markers, oxidative stress parameters and antioxidant capacity in women between the ages of 25-70 years. We showed that the PON1 polymorphism modified the association between lycopene and NTx and BAP (p<0.02 and p<0.05 for interaction). In the combined 172TT and 584G genotype, high serum lycopene was associated with decreased BAP (p<0.01) and NTx (p<0.05). Among those with the combined 172A and 584G genotype, however, increased serum lycopene was associated with increased BAP (p<0.05) and NTx (p<0.05). These findings show that PON1 polymorphisms modified the association between serum concentrations of lycopene and oxidative stress parameters and bone turnover markers and may, therefore, moderate the risk of osteoporosis [201].
\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t\t\n\t\t\t\t | \n\t\t||
\n\t\t\t\t | \n\t\t\t2.59 ± 0.32a\n\t\t\t | \n\t\t\t43.33 ± 2.84 | \n\t\t\t<0.0001 | \n\t\t|
\n\t\t\t\t | \n\t\t\tTotal | \n\t\t\t1094 ± 80.24 | \n\t\t\t2012 ± 88.56 | \n\t\t\t<0.0001 | \n\t\t
all- | \n\t\t\t539.0 ± 40.07 | \n\t\t\t979.0 ± 48.48 | \n\t\t\t<0.0001 | \n\t\t|
5- | \n\t\t\t342.4 ± 26.13 | \n\t\t\t685.0 ± 30.22 | \n\t\t\t<0.0001 | \n\t\t|
other- | \n\t\t\t212.6 ± 15.96 | \n\t\t\t347.7 ± 17.36 | \n\t\t\t<0.0001 | \n\t\t|
\n\t\t\t\t | \n\t\t\t1.65 ± 0.03 | \n\t\t\t1.66 ± 0.05 | \n\t\t\t0.190 | \n\t\t|
\n\t\t\t\t | \n\t\t\tNTx (nM BCE) | \n\t\t\t21.97 ± 1.11 | \n\t\t\t19.19 ± 0.79 | \n\t\t\t0.047 | \n\t\t
BAP (U/L) | \n\t\t\t24.42 ± 1.40 | \n\t\t\t23.56 ± 1.02 | \n\t\t\t0.900 | \n\t\t|
\n\t\t\t\t | \n\t\t\tProtein thiols (μM) | \n\t\t\t454.7 ± 15.37 | \n\t\t\t455.2 ± 15.50 | \n\t\t\t0.982 | \n\t\t
TBARS (nmol/mL) | \n\t\t\t9.06 ± 0.35 | \n\t\t\t6.80 ± 0.35 | \n\t\t\t<0.0001 | \n\t\t|
\n\t\t\t\t | \n\t\t\tCAT (K/g Hb) | \n\t\t\t81.50 ± 4.13 | \n\t\t\t58.59 ± 2.06 | \n\t\t\t<0.0001 | \n\t\t
SOD (U/mg Hb) | \n\t\t\t47.60 ± 2.44 | \n\t\t\t39.22 ± 4.72 | \n\t\t\t0.001 | \n\t\t|
GPx (U/g Hb) | \n\t\t\t15.44 ± 1.40 | \n\t\t\t32.82 ± 2.85 | \n\t\t\t<0.0001 | \n\t\t
Comparison of lycopene values, oxidative stress parameters and bone turnover markers between women who were supplemented with lycopene with those who obtained a low lycopene (not shown) intake from their usual daily diet (unpaired t-test).
1 Data that were not normally distributed were compared using the Mann-Whitney test
a The range of lycopene intake for the low usual daily intake group is 0.0-6.07 mg/day.
A similar investigation was carried out in a fifth study to assesses whether the PON1 172T→A polymorphism affects the response to dietary intervention with lycopene. We showed that supplementation in the TT genotype and carriers of the A allele significantly increased serum lycopene (both: p<0.0001) while decreasing protein oxidation (p<0.005 and p<0.05, respectively) and lipid peroxidation (p<0.005 and p<0.0005). However, participants with the TT genotype responded more favourably to lycopene, with corresponding significant increase in total antioxidant capacity (TAC) (p<0.01) and significant decrease in NTx (p<0.001); this effect was not significant in carriers of the A allele. Further analyses showed that there was a significant interaction between PON1 genotype and change in TBARS (p<0.05) suggesting that supplementation with lycopene resulted in decreased lipid peroxidation, which interacted with the PON1 genotype to decrease bone resorption markers in postmenopausal women. These findings provide mechanistic evidence of how intervention with lycopene may act to decrease lipid peroxidation and thus the risk of osteoporosis in postmenopausal women [169,202].
There is now ample evidence to show that oxidative stress brought about by the accumulation of ROS in the body is one of the causes of the development of several chronic diseases including osteoporosis and that antioxidants such as lycopene can counteract this damaging effect. The evidence includes studies on their role in osteoclastic resorption and osteoblastic bone formation, animal intervention studies, epidemiological studies and, more recently, clinical intervention studies. Considering the possible adverse side effects of the conventional therapy (eg, HRT and bisphosphonates) in the management of postmenopausal osteoporosis, there is an increasing demand for the use of antioxidants naturally present in foods. The results of these studies indicate that lycopene maybe useful either as a dietary alternative to drug therapy or as a complement to the drugs presently used by women at risk for osteoporosis.
Polyphenols have long been known to have a role in the prevention of chronic diseases such as cardiovascular diseases, cancers, neurodegenerative diseases, diabetes, or osteoporosis. Only in the last 10 years has there been an increase in the interest on polyphenols and bone health [203-206]. Horcajada [204] has recently reviewed the anabolic role of phytonutrients and especially polyphenols in bone while Trzeciakiewicz [205] reviewed the mechanisms of action of polyphenol in osteoblast function and its interaction with osteoclasts. The beneficial effects of green tea polyphenols has been reviewed [207,208].
Currently, most of the research on polyphenols and their effects have emerged from
The most commonly studied polyphenol abundant in green tea is epigallocatechin-3-Gallate (EGCG). We have shown that epigallocathechin-3-gallate (EGCG) increased the formation of mineralized bone nodules by human osteoblast-like cells [210]. EGCG has been shown to inhibit the expression of matrix metalloproteinase 9 (MMP-9) and the formation of osteoclasts [211]. H2O2-induced alterations of osteoblast viability and reduction in alkaline phosphatase activity were prevented by pre-incubating the osteoblasts with green tea polyphenol [212]. Green tea was shown to protect human osteoblasts from cigarette smoke-induced injury [128]. EGCG was shown to inhibit thyroid hormone-stimulated osteocalcin synthesis in osteoblasts [213], suppressed the differentiation of murine osteoblastic MC3T3-E1 cells [214], inhibit rat osteoclast formation and differentiation [215] and induces apoptosis via caspase activation in osteoclasts differentiated from RAW 264.7 cells [216]. Horcajada suggested that most studies investigating the effects of polyphenols on osteoblast cells have reported involvement of complex networks of anabolic signaling pathways such as BMPs or estrogen receptor mediated pathways [204]. Trzeciakiewicz describing a more detailed mechanisms, suggested that polyphenols modulate the expression of transcription factors in osteoblasts such as runt-related transcription factor-2 (Runx2) and Osterix, NFkappaB and activator protein-1 (AP-1) [205]. In agreement with Hocajada (2012), Trzeciakiewicz (2009) stated in his review that polyphenol may act on cellular signaling such as mitogen-activated protein kinase (MAPK), bone morphogenetic protein (BMP), oestrogen receptor and osteoprotegerin/receptor activator of NF-kappaB ligand (OPG/RANKL) and thus may affect osteoblast functions. The two reviews complement each other and paint a better understanding of the mechanisms of action of polyphenols in bone cells, with the warning that it is also important to take into account the possible interaction of these compounds on osteoblasts metabolism.
Other polyphenols/sources of polyphenols which were found to have beneficial effects on bone cells include the dried plum polyphenols found to attenuate the detrimental effects of TNFalpha on osteoblast function coincident with up-regulation of Runx2, Osterix and IGF-I and increasing lysyl oxidase expression, and at the same time attenuate osteoclastogenesis signalling [217]; black tea polyphenol which affects the MMP activity and osteoclast formation and differentiation in vitro [215]; phenolic leaf extract of Heimia myrtifolia (Lythraceae) found to stimulate mineralization of SaOS-2 osteosarcoma cells) [218]; Oleuropein which enhances osteoblastogenesis and inhibits adipogenesis and the effects on differentiation in stem cells derived from bone marrow [219] and the polyphenol component of red wine resveratrol which promotes osteogenic differentiation and protects against dexamethasone damage in murine-induced pluripotent stem cells [220] and facilitates in vitro mineralization and in vivo bone regeneration [221]. A number of animal studies have been reported and this was reviewed by Rao et al [209].
Other good sources of polyphenols that are frequently studied are extracts containing combinations of polyphenols. One such source is the nutritional supplement greens+TM, a blend of several herbal and botanical products containing a substantial amount of polyphenols including quercetin, apigenin and luteolin [106] which act as antioxidants and therefore should be able to counteract oxidative stress. Our laboratory has shown that the polyphenolic extracts from greens+TM have stimulatory effect on mineralized bone nodule formation in human osteoblast cells in a dose- and time- dependent manner and is more effective than epicatechin (EC) as shown in Figure 8 [222]. We have further shown that this stimulatory effect is accompanied by decreases in the reactive oxygen species H2O2 shown in Figure 9 [223], thus proving that greens+TM is able to counteract oxidative stress in human osteoblastic cells and may therefore be a good candidate as a nutritional supplement to prevent the risk of osteoporosis.
Two additional nutritional supplements have since been formulated which may prove to be good for bone health. These are the bone builderTM and the greens+bone builderTM ; the latter is the original greens+TM product that has been supplemented with the bone builderTM formula containing several compounds including vitamins, minerals, and antioxidants. These various components have been separately shown to have some beneficial effect on bone [224]. Using the human osteoblast SaOS-2 cells, we showed that similarly to the greens+
Effect of continuous addition of greens+TM extract on the number of SaOS-2 cells cultured in the presence of EC, or varying dilutions of greens+TM at an early time points and number of nodules analyzed at the indicated time points. An asterix, *, on a bar indicates statistical significance (p
Dose-dependent inhibitory effects of phenolic extracts of greens+TM on intracellular ROS levels stimulated by 20 uM H2O2 in SaOS-2 cells. Data are mean ± SEM of 6 replicates. *p = < 0.05.
Time and Dose-dependent Effects of bone builderTM on mineralized bone nodule area in SaOS-2 cells. indicates significant difference from vehicle: p<0.0001; p<0.0005; p<0.005, #, p<0.01 and ##, p< 0.05. There is a significant dose-dependent effect both at day 17 and day 20, according to One-way ANOVA; p<0.0001.
Dose dependent effect of greens + (g+) with and without 0.5 mg/ml of bone builder (bb) on the area of mineralized bone nodules in osteoblasts SaOS-2 Cells. Significant differences were found compared to respective controls. g+bb was more effective than either g+ or bb alone.
We have recently reviewed earlier clinical studies on polyphenols and osteoporosis [209]. Only the more recent reports, as well as our own clinical studies will be reviewed here. Shen et al [227] have extended their studies in osteopenic women and showed that dietary supplement in the form of green tea combined with tai-chi, a mind-body exercise, can alleviating bone loss in osteopenic women. The effect of catechin was studied in perimenopausal Scottish women and it was found that catechin was negatively associated with bone-resorption markers, association between energy-adjusted total flavonoid intakes and BMD at the femoreal neck and lumbar spine while annual percent change in BMD was associated with intakes of procyanidins and catechins [228].
Other than these clinical studies in the last two years, there has not been not been anymore reported clinical studies on polyphenols in human subjects except our studies.
Our results on the in vitro effects of greens+TM, bone builderTM and greens+bone builderTM on bone formation in osteoblasts encouraged us formed the rationale for our clinical studies to test whether these products can prevent the risk of osteoporosis in postmenopausal women. We chose to study the greens+bone builderTM since of the three products, it gave the greatest stimulatory effect on bone formation, being six times more effective than the other two. The first randomized cross-sectional clinical intervention study was carried out to test whether a daily supplementation with greens+ bone builderTM may be important in reducing oxidative damage in postmenopausal women at risk for osteoporosis. [40]. Forty-seven postmenopausal women, 50-60 years old were randomized to either Treatment group consuming 1 scoop (equivalent to ¼ cup) daily of greens+ bone builder
Change relative to baseline in serum concentrations of trolox, a measure of total antioxidant capacity, in greens+bone builderTM-treated postmenopausal women was significantly increased after 4 and 8 weeks while that in the placebo-treated control was marginally decreased. Treated values were also higher than the placebo [unpaired t-test (*p<0.01, **p<0.0001)]. Values are mean ± SEM.
Change relative to baseline in serum concentrations of thiol in greens+bone builder-treated postmenopausal women was significantly increased after 4 and 8 weeks (meaning decreased protein oxidation) while that in the placebo-treated control was unchanged; treated values were also higher than the placebo. Mann-Whitney test (*p<0.05, **p<0.001). Values are mean ± SEM.
Change relative to baseline in serum concentrations of TBARS in greens+bone builderTM-treated postmenopausal women was significantly decreased after 4 and 8 weeks (meaning decreased lipid peroxidation) while that in the placebo-treated control was unchanged; treated values were also lower than the placebo. Mann-Whitney test (*p<0.05, **p<0.001). Values are mean ± SEM.
In order to test whether the antioxidant properties of greens+bone builderTM can prevent the risk of osteoporosis in postmenopausal women, we also measured the serum bone turnover markers, C-terminal telopeptide of type I collagen (CTX) as indicator of bone resorption, and procollagen type I N-terminal propeptide (PINP) as indicator of bone formation, in addition to the serum antioxidant capacity, and the oxidative stress parameters lipid peroxidation, protein oxidation. As shown in Figure 15, statistical analysis showed that at 8 weeks, the greens+bone builderTM supplement group significantly decreased the bone resorption marker CTX, while the Placebo group showed no significant changes. The supplement group was also significantly different from that of the Placebo group in all parameters measured. This decrease in CTX correlated to the increase in their serum total antioxidant capacity [Figure 12] and decreases in oxidative parameters protein oxidation [Figure 13] lipid peroxidation [Figure 14]. These results suggest that a daily supplementation with polyphenols and micronutrients may be important in reducing oxidative damage by reducing bone resorption, thereby reducing the risk of osteoporosis in postmenopausal women [41].
Change relative to baseline in serum concentrations of CTX in greens+bone builderTM-treated postmenopausal women was significantly decreased after 8 weeks (meaning decreased bone resorption marker) compared to that of the placebo-treated control (a paired t-test (*p<0.05).. Values are mean ± SEM.
Studies reported in the literature on the role of polyphenols in bone health have exploded in the last 10 years, but most of the reports involved in vitro studies in osteoclasts and osteoblasts, animal studies and epidemiologicai studies. There is little doubt from the excellent studies reported that oxidative stress is one of the primary culprits responsible for the pathogenesis of osteoporosis via its role in osteoclastic resoption and the detrimental effects on the bone-forming osteoblasts. To date, only four clinical intervention studies have been reported, including ours. It is easy to see why it is very difficult to evaluate the role of polyphenols since, as we learned from this review, there are at least 8,000 different polyphenols identified to date, and each one probably having different effects on humans. Additionally, polyphenols are present in food with other constituents that may also be beneficial to bone health. In our clinical study, we combined the effects of a combination of polyphenols present in the nutritional supplement from greens+TM with the nutritional components present in bone builderTM such as minerals, vitamins and other nutrients. It is possible that the effects of greens+bone buildertm in increasing total antioxidant capacity, decreasing the oxidative stress markers protein oxidation and lipid peroxidation which correlated to the decrease in bone turnover marker for bone resorption is a result of the combined effects of the different polyphenols it contained with those of the other nutritional components present in the bone builderTM. It remained for future studies to zero in on specific component that is responsible for its beneficial effect.
In conclusion, we showed that oxidative stress due to ROS that are shown to cause the development of osteoporosis may be prevented by supplementation with the antioxidants lycopene and polyphenols. Results of in vitro studies in osteoblasts and osteoclasts, animal intervention studies, epidemiological studies and clinical intervention studies on lycopene and polyphenols are evidence for their potential use as alternative or complementary agent with other established drugs approved for the prevention or treatment of osteoporosis in postmenopausal women.
Funding for this research into Oxidative Stress, Antioxidants and Bone Health is shared by Genuine Health Ltd (Canada), the H.J. Heinz Co (Canada), Millenium Biologix Inc. (Canada), Kagome Co. (Japan) and LycoRed Natural Product Industries, Ltd. (Israel) and matched by the Canadian Institutes of Health Research (CIHR). We sincerely thanked the valuable contributions to this research by the following students/graduate students and staff at the Calcium Research Laboratory, Department of Medicine at St Michael’s Hospital and the University of Toronto and Department of Nutritional Sciences, University of Toronto: Dr. Bala Balachandran, Jaclyn Beca, Dawn Snyder, Loren Chan, Honglei Shen, Salva Sadeghi, Ayesha Quireshi, Dr. Erin Mackinnon and Nancy Kang. Their contributions were based on their experimental data, written reports published/in press manuscripts. We would also like to thank to Dr. R.G. Josse for providing us with his medical expertice as well as allowing us access to his list of patients we were able to recruit. Special thanks to Dr. H. Vandenberghe for carrying out the CTX assay and for her valuable suggestions.
Pain management is increasingly recognised as a formal medical subspecialty worldwide [1]. Optimal sedation and analgesic strategies, combined with delirium management, are a challenge when caring for critically ill patients. Sedation in ICU aims to provide patient pain reflief, comfort and safety. For sedation monitoring, the most extensively used tools are RASS (Richmond Agitation and Sedation Scale) [2] and SAS (Sedation Agitation Scale) [3]. Despite extensive improvements in analgesia medication there are still barriers to nurses’ assessment, management, documentation, and reassessment of pain [4, 5, 6].
Pain is the most common reason that patients come to the emergency department. Emergency nurses have an indispensable role in the management of this pain [7, 8]. Sedation in the intensive care unit (ICU) is challenging, as both over- and under-sedation are detrimental. Current methods of assessment, such as the Richmond Agitation Sedation Scale (RASS), are measured intermittently and invariable depend on patients’ behavioural response to stimulation, as such may interrupt sleep and rest. A non-stimulating method for continuous sedation monitoring may be beneficial and allow more frequent assessment., noting that appropriate sedation cycling has to accommodate patients’ oscillations between states of agitation and over-sedation, which are detrimental to patient health and increases hospital length of stay [9, 10, 11, 12, 13, 14].
As such there also have been recent studies exploring the impact of augmenting sedation assessment with physiologic monitors [15] and studying the correlation between observational scales of sedation and bispectral index scores [16]. Recently the feasibility of continuous sedation monitoring of ICU patients using the NeuroSENSE was studied and suggested that such a non-stimulating method for continuous sedation monitoring may benefit patient care and allow increased A-S assessment [17]. The authors advocated use of incorporating some degree of automation into sedative drug administration, e.g. closed-loop control based on feedback from a processed EEG monitor, and various studies have suggested the limitations of RASS as a stand-alone measure of sedation levels, and pointed to benefit of adjunct continuous e.g., brain monitoring [17].
Earlier, Rudge, Chase, Shaw, Lee [12] discussed target controlled infusion (TCI) systems to deliver drugs to maintain target plasma concentrations, using a pharmacokinetic model, shown to be feasible when anaesthesia is given over short periods of reduced consciousness and well-known pharmacology is invoked. Infusion systems that regulate the infusion rate to maintain target agitation levels, to regulate the primary metric for longterm sedation, are one approach to improving care in the ICU. The data analysed in this chapter pertains to the scenario and data type studied earlier by [9, 10, 11, 12, 13, 14].
Assessing the severity of agitation is a challenging clinical problem as variability related to drug metabolism for each individual is often subjective. A multitude of previous studies suggest that the assessment accuracy of the sedation quality conducted by nurses tend to suffer from subjectivity and lead to sub-optimal sedation [14, 15, 18]. For example, [19] strongly recommend lighter than deeper levels of sedations. Moreover, [20, 21] argue that sedation should be reviewed and adjusted regularly. Whilst agitation management methods frequently rely on subjective agitation assessment [2, 3] the carers then select an appropriate infusion rate based upon their evaluation of these scales, experience, and intuition [21]. This approach usually leads to largely continuous infusions which lack a bolus-focused approach, commonly resulting in over or under-sedation. The work of [11, 12, 13] aimed to enhance feedback protocols for medical decision support systems and eventually automated sedation administration. A minimal differential equation model to predict or simulate each patient’s agitation-sedation status over time was presented in [12] for 37 ICU patients and was shown to capture patient A-S dynamics. The use of quantitative modelling to enhance understanding of the agitation-sedation (A-S) system and provision of an A-S simulation platform are one of the key tools in this area of patient critical care. A more refined A-S model, which utilised regression with an Epanechnikov kernel was formulated by [12]. A Bayesian approach using densities and wavelet shrinkage methods was later suggested by [9] to assess a previously derived deterministic, parametric A-S model [10, 11, 12, 13, 14], thus successfully challenging the practice of sedating ICU patients using continuous infusions. Wavelets approaches [9, 10] were shown to provide reliable diagnostics and visualisation tools to assess A-S models, giving alternative metrics of A-S control to assess validity of the earlier A-S deterministic models (Table 1 in [10]).
V1 | V2 | V3 | Total V’s | Time in ICU | WPB% | |
---|---|---|---|---|---|---|
P18/Good | 2 | 24 | 26 | 20 | 64 | 93.8% |
P28/Poor | 1 | 5 | 12 | 114 | 203 | 50.8% |
Time to the patient-specific 1st violation V1, second violation V2 and third violation V3, total number of violations, total ICU time and WPB% values.
This suite of wavelet metrics based on the discrete wavelet transform (DWT) were able to establish the value of earlier deterministic agitation-sedation (A-S) models against empirical (recorded) dynamic A-S infusion profiles, providing robust performance metrics of A-S control and excellent tools, as based on the classification of patients into poor and good trackers based on Wavelet Probability Bands (WPBs). Importantly, the WPBs were shown as a useful patient-specific method by which to identify and detect regions in the patient’s A-S profile i.e., times whilst in ICU, where the simulated infusion rate performs poorly, thus providing visual and quantified ways to help improve and distil the deterministic A-S model and in practice be a guage to alert carers.
In this chapter Empirical Transition Matrix (ETM) approach of multi-state counting process (survival analytic) models of Allignol and coauthors [22, 23], aligned with the counting process/event history work in [24, 25, 26], which use the times patients transition to varying states of violations (a violation being an A-S measure outside the 90% WPB bands), confirm the utility of defining trackers and non-trackers according to these control limits and wavelet diagnostic rules of Kang et al., [9, 10]. In this chapter ETM and multi-state modelling are found to be valuable for developing advanced optimal infusion controllers and also to assist coding of nurses A-S scores, which potentially offer significant clinical potential of improved agitation management and reduced length of stay, as an augmented approach to also using RASS and SAS. Establishing patient-specific thresholds of poor A-S management and control has significant implications for the effective administration of sedatives, as improved management of A-S states will allow clinicians to improve the efficacy of care and reduce healthcare costs [27, 28, 29].
This chapter models the agitation-sedation profiles of Agitation and Sedation (A-S) profiles of 37 patients were collected at the Christchurch Hospital, Christchurch School of Medicine and Health Sciences, NZ. Two measures were recorded for each patient: (1) the nurses’ ratings of a patient’s agitation level and (2) an automated sedation dose (see Figure 1). Infusion data were recorded using an electronic drug infusion device for all admitted ICU patients during a nine-month observation period and required more than 24 hours of sedation. Infusion data containing less than 48 hours of continuous data, or data from patients whose sedation requirements were extreme, such as those with severe head injuries, were excluded [9, 10]. A total of 37 ICU patients met these requirements and were enrolled in the study. Classification of patients into poor and good trackers, as based on the Wavelet Probability Bands (WPB) are given in Table 2. The so-called good tracker delineates the scenario where the nurse’s rating scores remains within the (time based) 90% coverage of wavelet probability band (WPB) based on the simulated dose profiles [9, 10]. Poor tracking delineates the scenario where the nurses rating scores remain outside the (time based) 90% coverage of wavelet probability band (WPB) for a significant portion of time based on the simulated dose profiles [13, 14].
Diagram of the feedback loop employing nursing staff’s feedback of subjectively assessed patient agitation through the infusion controller (diagram is sourced from Chase et al. [
By way of illustration we consider four patients from the pool of 37 patients.Tables 1 and 3 summarise each of these four patients’ WPB tracker status, time to first, second and third violation outside the WPB bands [9], their total number of violations over ICU stay and patient’s time in ICU, along with their specific WPB% value. Display of their line profiles of
V1 | V2 | V3 | Total V’s | Time in ICU | WPB% | |
---|---|---|---|---|---|---|
P8/Good | 1 | 2 | 3 | 46 | 128 | 87.5% |
P27/Poor | 1 | 4 | 5 | 89 | 225 | 43.7% |
Time to the patient-specific 1st violation V1, second violation V2 and third violation V3, total number of violations, total ICU time and WPB% values.
Line plot of nurses’ rating of patient agitation and the automated sedation dose for patient 8 (good tracker).
Line plot of nurses’ rating of patient agitation and the automated sedation dose for patient 27 (good tracker).
Line plot and WPB% band for patient 18 (LHS) and 28 (RHS, poor tracker).
The first patient (patient 8) in Table 3 is a good WPB tracker and the second a poor WPB tracker (patient 27), studied in depth in [28], for which upper tail thresholds of the nurses’ scores using copulas were established. We also refer the reader also to Hudson & Tursunalieva’s chapter in this book entitled “Copula thresholds and modelling Agitation-Sedation (A-S) in ICU: analysis of nurses scores of A-S and automated drug infusions by protocol” [27]. The corresponding WPB% values for patient 8 and patient 27 are 87.5% and 43.7%, respectively (Table 3). Overall, the minimum, median and maximum WPB% values for the 24 good trackers is (58.8%, 87.5%, 96.9%) and (47.3%, 64.8%, 77.3%) for the 13 poor trackers (Table 2). Noteworthy also is that the A-S time series of these two patients examined (P8 and P27) were of disparate lengths - patient eight had 10,561 time points and patient 27, 13,441 time points. The full 37 patients studied had a range of [3001–25,261] time points.
Patient 18 (good tracker) with a WPB% of 93.8% and patient 28 (poor tracker) with WPB% of 50.8% (Table 1) were studied in detail in [28], for which both upper and lower tails/thresholds of over or under-estimation of agitation levels by the nurses rating were established using copula dependence analytics [29], refer also to [27].
Patients vary according to their length of stay in ICU and consequently differ in their opportunity for violations to occur. The good trackers generally have shorter ICU time and thus less chance to exibit an increased total number of violations. An indication of how the strata (good versus poor tracker), the patient’s total number of violations and a patient’s time in ICU interact, can be visualied in Figure 5. The total number of WPB based violations is clearly greater for the poor trackers than for the good trackers, and it is the poor trackers that tend to have longer ICU times. Also from the scatterplot in Figure 5 there seems to be three approximate categories of patient ICU time: 50–64, 113–128 and 205–256. The majority of patients (28 (76%)) have ≤40 violations (RHS of Figure 5), 19 (51%) patients have an ICU time of ≤64 (Table 4).
Total number of violations by WPB tracking status [
ICU category | |||
---|---|---|---|
WPB tracker | 0 | 1 | 2 |
Good | 15 | 7 | 2 |
Poor | 4 | 4 | 5 |
Patient tracker status by ICU time: 0 = 50–64, 1 = 113–128, 2 = 205–256.
Accordingly, for ICU time categorised and coded as: 0 = [50,64], 1 = [113,128], and 2 = [205,256], the total violations profile according to tracking status, displayed in Figure 6, shows that the total number of violations is significantly higher for the poor trackers, particularly when ICU time > 205. Noteworthy, is that the majority of patients 28 (76%) have ≤40 violations (RHS of Figure 6), whereas 19 (51%) patients have an ICU time ≤ 64 (Table 4). Figure 7 displays the histogram of the number of violations where a violation is defined as a nurse’s A-S rating outside the patient’s WPB control band. We note that the majority of the time, in excess of >75% of the 370 violation counts are below a count of five violations (Figure 7).
Total number of violations by 3 levels of ICU time (LHS) and boxplot of poor good tracker time to 3rd violation by ICU time: 0 = [50,64], 1 = [113,128], 2 = [205,256].
Violation counts in bins across all patients.
For the state-space analysis described in Section 3 each patient’s total ICU time is broken into 10 bins, where each bin represents 10% of the patients’ total time in ICU; i.e., Bin 1: 0–10%, Bin 2: 11–20% etc. For the 37 patients, we thus have 370 bins, i.e. 370 counts of violations. The 10% interval approach is used due to the large variation in time in ICU between the WPB-based good versus poor strata [9] - noting that some poor trackers have times up to 256, whereas good trackers are mostly limited to 64–128. Given these bins, patients’ A-S states can then be defined in terms of the total number of violations or jumps outside the WPB bands that occur during each 10% interval of a patient’s total ICU time. The randon, outcome event of A-S status is then the number of violations that over time.
Multi-state models are known to provide a relevant framework for modelling complex event histories. Quantities of interest are mainly the transition probabilities that can be estimated by the empirical transition matrix, that is also referred to as the Aalen-Johansen estimator [30, 31]. Such multi-state models have had a wide range of applications for modelling complex courses of a disease over the course of time and across applications in medical research (Beyersmann et al., 2011 [32], Munoz-Price et al., 2016, [33], Andersen & Keiding 2002 [34]). We now utilise the Empirical Transition Matrix (etm) approach to model multi-state models of [22] and derive inference tests for such models using the approach of Commenges [25, 35, 36] with a particular focus on Commenges’ test derived in earlier work [25].
Define patient states as follows, any state can transition into any other state (Figure 8).
State-space system.
• State 1: 0 or 1 violations
• State 2: 2 or 3 violations
• State 3: > 3 violations
A number of different approaches (etm on ICU time, etm on bin time, and log-rank type tests as in Commenges [25], will be used to investigate the difference between good and poor trackers in terms of a devised a 3 state transition formulation as defined below. Differences between transition probabilities between states for the good and poor trackers will be evaluated using Commenges’ [25] chi square test.
The mathematics is well described in the work of Allignol [22], adapted to more complex scenarios in [23]; and in Commenges’ approach [25, 35, 36]. The mathematical formulation of the ETM state-space approach and Commenges’ test are given for general frameworks as follows.
Consider a stochastic process
The cumulative hazard transitions are defined as,
Define
as the probability that an individual who is in state
The (K + 1)x(K + 1) probability transition matrix with elements
and the diagonal elements
where the product is taken over all possible transition times in time interval (s,t].
An estimator for the covariance of the empirical transition matrix is given by,
which is a (K + 1)2 x (K + 1)2 matrix, with number or rows and columns equal (K + 1)2.
We now utilise the framework of the generalised Cochran–Mantel–Haenszel (CMH) test for (I x J x K) tables. The CMH test is based on the hypergeometric distribution. The CMH and the test of Commenges’ for the specific case here, where we have three states (of violations) and two strata (good versus poor trackers) is now described.
In our application then we have 2 × 3 × 3 tables. For each k = 1, 2, 3 we have a 2 × 3 table, where the elements are counts nijk (k denotes the departure state j, so the rows, I, are the WPB strata, the columns, J, are the entry states I and the slices, K, are the departure states j), as tabulated below.
I = 0 | I = 1 | I = 2 | Row total | |
---|---|---|---|---|
Good | n11k | n12k | n13k | n1 + k |
Poor | n21k | n22k | n23k | n2 + k |
Total | n+1k | n+2k | n+3k | n++k |
Assume that the row and column marginals are fixed. This implies that there are (I-1) by (J-1) values that are free to vary. For the cell nijk the expected value is then given by ni + k x n+jk. We are able to express all cell counts by the vector
where
The generalised CMH statistic is then given by,
which follows a chi square distribution with (I-1) by (J-1) degrees of freedom. This test is implemented in R via the mantelhaen.test function. Commenges [25] adapts this concept, with a test which differs to the generalised CMH test in that it does not sum over the K strata, before calculating the relevant chi squared test statistic.
Commenges’ test [25] is as follows,
where
The required total chi squared statistic is then simply obtained by taking
Conditionally on the number of patients in each state at each step we have 3 x 9 = 27 independent contingency tables (i.e., number of departure states j by the number of time points k–1, recall we have 10, 10% bins for a patient’s time in ICU) and each of these tables has dimension 2 × 3 (good/poor tracker by the number of states i).
The corresponding three specific strata tables are given in Tables 5–7. For example, for departure state j = 0 and time point k = 2 we have a two by three contingency table with an overall total of 7ϕ violations (labelled ϕ in Table 5); the latter informs that, at time k = 2 there are 5
Strata | I = 0 | I = 1 | I = 2 | Total | |
---|---|---|---|---|---|
k = 2 | Good | 5ϕ | 0 | 0 | 5 |
Poor | 0 | 2ϕ | 0 | 2 | |
Total | 5 | 2 | 0 | 7ϕ | |
k = 3 | Good | 10 | 5 | 1 | 16 |
Poor | 0 | 1 | 0 | 1 | |
Total | 10 | 6 | 1 | 17 | |
k = 4 | Good | 10 | 1 | 0 | 11 |
Poor | 2 | 0 | 0 | 2 | |
Total | 12 | 1 | 0 | 13 | |
k = 5 | Good | 9 | 2 | 2 | 13 |
Poor | 0 | 3 | 1 | 4 | |
Total | 9 | 5 | 3 | 17 | |
k = 6 | Good | 9 | 3 | 2 | 14 |
Poor | 0 | 0 | 0 | 0 | |
Total | 9 | 3 | 2 | 14 | |
k = 7 | Good | 9 | 2 | 2 | 13 |
Poor | 1 | 1 | 0 | 2 | |
Total | 10 | 3 | 2 | 15 | |
k = 8 | Good | 5 | 4 | 2 | 11 |
Poor | 2 | 0 | 2 | 4 | |
Total | 7 | 4 | 4 | 15 | |
k = 9 | Good | 5 | 2 | 0 | 7 |
Poor | 3 | 0 | 0 | 3 | |
Total | 8 | 2 | 0 | 10 | |
k = 10 | Good | 9 | 1 | 1 | 11 |
Poor | 2 | 1 | 2 | 5 | |
Total | 11 | 2 | 3 | 16 |
Departure state j = 0: WPB strata [9].
Strata | I = 0 | I = 1 | I = 2 | Total | |
---|---|---|---|---|---|
k = 2 | Good | 6 | 1 | 1 | 8 |
Poor | 1 | 1 | 0 | 2 | |
Total | 7 | 2 | 1 | 10 | |
k = 3 | Good | 1 | 2 | 0 | 3 |
Poor | 2 | 2 | 2 | 6 | |
Total | 3 | 4 | 2 | 9 | |
k = 4 | Good | 2 | 2 | 3 | 7 |
Poor | 2 | 2 | 0 | 4 | |
Total | 4 | 4 | 3 | 11 | |
k = 5 | Good | 3 | 1 | 1 | 5 |
Poor | 0 | 1 | 2 | 3 | |
Total | 3 | 2 | 3 | 8 | |
k = 6 | Good | 3 | 1 | 0 | 4 |
Poor | 1 | 3 | 1 | 5 | |
Total | 4 | 4 | 1 | 9 | |
k = 7 | Good | 2 | 3 | 1 | 6 |
Poor | 3 | 2 | 0 | 5 | |
Total | 5 | 5 | 1 | 11 | |
k = 8 | Good | 2 | 2 | 3 | 7 |
Poor | 1 | 1 | 2 | 4 | |
Total | 3 | 3 | 5 | 11 | |
k = 9 | Good | 4 | 3 | 2 | 9 |
Poor | 0 | 1 | 0 | 1 | |
Total | 4 | 4 | 2 | 10 | |
k = 10 | Good | 4 | 1 | 2 | 7 |
Poor | 1 | 1 | 0 | 2 | |
Total | 5 | 2 | 2 | 9 |
Departure state j = 1: WPB strata [9].
Strata | I = 0 | I = 1 | I = 2 | Total | |
---|---|---|---|---|---|
k = 2 | Good | 5 | 2 | 4 | 11 |
Poor | 0 | 3 | 6 | 9 | |
Total | 5 | 5 | 10 | 20 | |
k = 3 | Good | 0 | 0 | 5 | 5 |
Poor | 0 | 1 | 5 | 6 | |
Total | 0 | 1 | 10 | 11 | |
k = 4 | Good | 1 | 2 | 3 | 6 |
Poor | 0 | 1 | 6 | 7 | |
Total | 1 | 3 | 9 | 13 | |
k = 5 | Good | 2 | 1 | 3 | 6 |
Poor | 0 | 1 | 5 | 6 | |
Total | 2 | 2 | 8 | 12 | |
k = 6 | Good | 1 | 2 | 3 | 6 |
Poor | 1 | 2 | 5 | 8 | |
Total | 2 | 4 | 8 | 14 | |
k = 7 | Good | 0 | 2 | 3 | 5 |
Poor | 0 | 1 | 5 | 6 | |
Total | 0 | 3 | 8 | 11 | |
k = 8 | Good | 0 | 3 | 3 | 6 |
Poor | 0 | 0 | 5 | 5 | |
Total | 0 | 3 | 8 | 11 | |
k = 9 | Good | 2 | 2 | 4 | 8 |
Poor | 2 | 1 | 6 | 9 | |
Total | 4 | 3 | 10 | 17 | |
k = 10 | Good | 2 | 1 | 3 | 6 |
Poor | 1 | 0 | 5 | 6 | |
Total | 3 | 1 | 8 | 12 |
Departure state j = 2: WPB strata [9].
Three 2 x 3 contingency tables (one for each departure state j) are thus created.
Estimated transition probabilities for the 3 state process are then plotted using the ‘xyplot’ function from the lattice package in R. In the resultant plots (Figures 9–11), the vertical y-axis represents the transition probability value, which is represented by the solid line in each plot region. The numbers in the coloured bar above each plot defines the transition (e.g., 1 2 means transition probability from state 1 to state 2). The dotted lines around the solid line represent the confidence bands based on the covariance as calculated by the etm function. The horizontal x-axis shows the the time i.e., 10% bins (i.e. 2–10, because no transitions occur at time one being the initial state). For each tracker status and possible piairs of state transitions there are three plots, given in the following order, good trackers, poor trackers. Figure 11 displays the probability of being in each of the 3 states (0, 1, 2) given the initial state is state 0.
Transition probability profiles for
Transition probability profiles for
Probability of being in each state as time progresses given start state 0. Top is good trackers, bottom is poor trackers:
Our procedure results in three 2 x 3 contingency tables (one for each departure state j), see Tables 8–10. The chi squared statistic as derived in [25] can now be calculated in that for the Commenges test the same chi squared calculation is made for each state specific table separately (i.e., without summing over k). The results in this case are χ2(1) = 6.046, χ2 (2) = 2.269 and χ2(3) = 9.280. Each of these follows a chi square distribution with 2 degrees of freedom with associated p-values of 0.049, 0.322 and 0.010 (Table 11). Kang WPB (2013) [9].
Tracker strata | I = 0 | I = 1 | I = 2 | Total |
---|---|---|---|---|
Good | 71 | 20 | 10 | 101 |
Poor | 10 | 8 | 5 | 23 |
Total | 81 | 28 | 15 | 124 |
Departure state j = 0 summed over all time points k, k = 2, …,10.
Tracker strata | I = 0 | I = 1 | I = 2 | Total |
---|---|---|---|---|
Good | 27 | 16 | 13 | 56 |
Poor | 11 | 14 | 7 | 32 |
Total | 38 | 30 | 20 | 88 |
Departure state j = 1 summed over all time points k, k = 2, …,10.
Tracker strata | I = 0 | I = 1 | I = 2 | Total |
---|---|---|---|---|
Good | 13 | 15 | 31 | 59 |
Poor | 4 | 10 | 48 | 62 |
Total | 17 | 25 | 79 | 121 |
Departure state j = 2 summed over all time points k, k = 2, …,10.
State | χ2 | p-value |
---|---|---|
J = 0 | 6.046 | |
J = 1 | 2.269 | 0.322 |
J = 2 | 9.280 | |
Total |
Computation of Commenges’ test for the WPB strata [9].
Summing these threeχ 2 (j), j = 1,2,3 statistics gives a value of χ2 =17.59 with 6 degrees of freedom and an associated p-value of 0.007 (Table 11). The underlying null hypothesis is that the two nominal variables (strata: good or poor tracker and entry state: 0, 1, or 2) are conditionally independent in each stratum (departure state j; 0, 1 or 2), assuming no three-way interaction. The low p-value of 0.007 suggests that this hypothesis be rejected, i.e., the two variables are not conditionally independent. Thus the Commenges test shows that there is a statistically significant difference between the good versus poor tracker WPB strata, and that this difference is mainly due to transitions out of states 0 and 2, which agrees with the trends based on a graphical inspection of Figures 9–11.
The same procedure and related Commenges’ test is then applied to each of the 3 remaining good/poor tracker definitions of Kang [10, 11, 14] for the three-state context studied in this chapter. These results are reported in Table 12.
State | χ2 | p-value |
---|---|---|
J = 0 | 1.724 | 0.422 |
J = 1 | 0.911 | 0.634 |
J = 2 | 7.123 | |
Total | 0.135 |
Computation of Commenges’ test for the remaining A-S studies.
Kang et al., WCORR [10].
Chase et al. [14].
State | χ2 | p-value |
---|---|---|
J = 0 | 5.669 | 0.059 |
J = 1 | 6.406 | |
J = 2 | 3.097 | 0.213 |
Total |
Rudge et al. [11].
State | χ2 | p-value |
---|---|---|
J = 0 | 0.367 | 0.832 |
J = 1 | 2.951 | 0.229 |
J = 2 | 5.466 | 0.065* |
Total | 0.186 |
Transition probability profiles of being in each state as time progresses, given start state 0, for the remaining 3 studies of [10, 14, 11] are given in Figures 12–14. In summary, Figures 9–14 illustrate the trend that good trackers tend to have higher probability of transitioning into state 0 than poor trackers, and the good trackers tend to have lower probability of transitioning into state two than poor trackers, where state two indicates that more violations (>3 violations) are occurring, and state 0 indicates few violations are occurring.
Probability of being in each state as time progresses given start state 0. Top is good trackers; bottom is poor trackers: WCORR of [
Probability of being in each state as time progresses given start state 0. Top is good trackers; bottom is poor trackers according to Chase et al. [
Probability of being in each state as time progresses given start state 0. Top is good trackers; bottom is poor trackers according to Rudge et al. [
Notably also, the probability of transitioning into state 2 overall appears to increase as ICU time increases. This is most likely because poor tracking patients tend to have longer ICU times, and so, as time goes on, it is only poor trackers transitions that are being estimated. By categorising patients according to total ICU time (≤64, >64) as discussed earlier (Figures 5 and 6, Table 4) some of this could be accounted for. The results obtained are still consistent, as shown in the etm profiles using ICU time (≤64, >64) in Figures 15 and 16, respectively. The corresponding ETM probabilities are determined according to etm in R [21] and associated state and strata specific plots given in Figures 15 and 16.
Transition probability profiles for patients with ICU time ≤ 64. Top panel are the WPB good trackers, and bottom panel the poor trackers.
Transition probability profiles for patients with ICU time > 64. Top panel are the WPB good trackers, and bottom panel the poor trackers.
The different approaches in Section 3 led to the sasimilar conclusions that there is a difference in the way good trackers and poor trackers transition between states. Most of this difference occurs in states 0 and states 2, as defined. Good trackers tend to have higher probability of transitioning into state 0 than poor trackers, and good trackers tend to have lower probability of transitioning into state 2 than poor trackers, noting that state 2 indicates more violations are occurring, and state 0 indicates fewer violations. The probability of transitioning into state 2 overall appears to increase as ICU time increases. This is most likely due to the fact that poor tracking patients have longer ICU times, and so, as time goes on, it is only the poor trackers’ transitions that are being estimated.
By categorising patients according to their total ICU time (≤64, >64) similar trends were found. The Commenges’ test established a statistically significant difference between the two tracking strata (p = 0.007), and that this difference was mainly due to transitions out of states 0 and 2. For the tracking metric of Chase et al. [14], the Commenges test demonstrated a statistically significant difference between the two good versus poor strata (p = 0.019), with this difference mainly due to transitions out of states 0 and 1. Overall, the WCORR [10] and Rudge [11] classifications of tracking/strata, the transision probability profiles for the 3 state process, good and poor trackers are not significantly different, but exhibited some difference mainly due to transitions out of state 2.
In this section we analyse the WPB violation data and investigate the times to the third violation given times to second violation for both poor trackers and good trackers where tracking status is defined by WPB diagnostics. The process can be thought to have three states. State 1 corresponds to less than two violations, state 2 means two violations and if a patient is in state 3 then three violations have occurred. This is a sequential three state process shown schematically in Figure 17. Events of interest are a transition from state 2 to state 3, i.e. the occurrence of a third violation.
States of a patient’s agitation (violations) defined by certain levels of violations or jumps outside of the patient’s WPB bands - a 3 state process.
Time one is the patient’s entry time into state 2 and time two is the patients exit time from state 2 (i.e., entry time to state 3, so-called ‘death’ state). Time one is the patient’s entry time into state 2 and time two is the patient’s exit time from state 2 (i.e., entry time to state 3, so-called ‘death’ state).
In the case of multiple events of interest, the process can be treated as a Markov chain. Let Nij (t) be the process counting the number of observed transitions from state i to state j in the interval [0, t]. The transition intensity from state i to state j at time t is then λij (t) and gives the instantaneous risk of transition from state i to j.
Nij (t) has intensity process of the form λij(t)Ni(t) where Yi(t) is the number of individuals in state i just before time t. This is the setup of Simon and Makuch [37] who considered 4 states and two transitions of interest.
The concept of time in our ICU application represents time on-study (i.e. time at ICU) rather than calendar time. In the case of our 3 state process (Figure 8) the hazard functions of the two transitions of interest are λ13(t) and λ23(t) and the number of individuals in the states just before t are N1(t) and N2 (t), respectively. A chi squared test is conducted to test for independence between response and non-response as in the development formulated in [37].
This same test can be conducted to assess the association between strata and hazard rate. If λ23(0)(t) is the hazard rate (from state 2 to 3) for the good trackers and λ23(1) is the hazard rate (from state 2 to 3) for the poor tackers. Since the focus here is to test the effect of response (prior 2nd violation) on the hazard function, the null hypothesis of interest is H0: λ23(0) (t) = λ23(1). The hypothesis is tested via a log-rank type test following [37] which tests for the time-to-response bias. Now the equivalent of Table 2 in Simon and Makuch [37] can be constructed for both the good trackers and the poor trackers. Let N1(t) be the number of patients in state 1 at time t, and let N2 (t) denote the number of patients in state 2 at time t in Table 13.
Table 13 presents the WPB data as state-specific patient counts for each event time t.
Time | Events | ||
---|---|---|---|
3 | 12 | 12 | 7 |
4 | 7 | 10 | 5 |
6 | 6 | 6 | 2 |
9 | 5 | 5 | 1 |
12 | 4 | 5 | 1 |
18 | 2 | 6 | 1 |
19 | 2 | 5 | 1 |
26 | 0 | 6 | 1 |
27 | 0 | 5 | 1 |
28 | 0 | 4 | 1 |
33 | 0 | 3 | 1 |
36 | 0 | 2 | 1 |
43 | 0 | 1 | 1 |
(a) Good trackers. |
Time | Events | ||
---|---|---|---|
3 | 9 | 4 | 3 |
4 | 8 | 2 | 1 |
5 | 5 | 4 | 2 |
6 | 3 | 4 | 2 |
8 | 1 | 4 | 2 |
9 | 1 | 2 | 1 |
12 | 1 | 1 | 1 |
23 | 0 | 1 | 1 |
(b) Poor trackers |
Simon and Makuch’s [37] represeantation and formulation of the WPB data.
Mathematically the cumulative hazard function is conventionally estimated instead of the hazard function λ(t), as the latter is difficult to estimate. The cumulative hazard function and survival function is then given as,
Note that dij(u) above are the so-called end-state “deaths” i.e., third violations, the number of transitions from state i to state j in time interval [x, t]. The estimated survival and cumulative hazard curves are shown as in Figure 18.
Survival function of time to 3rd violation given the 2nd violation for good tracker and poor (non-)trackers (LHS) and cumulative hazard functions (RHS).
Survival curves and cumulative hazard functions were calculated according to Simon and Makuch’s method [37]. In essence, this counting process formulation keeps track of the number of patients in state 1 and 2 and event times (i.e., transitions into state 3). The survival package is used for estimation, where two times are used. Time one is the patients entry time into state 2 and time two is the patients exit time from state 2 (i.e. entry time to state 3, ‘death’).
The log rank test for H0: λ23(0) (t) = λ23(1), based on the counting process which utilises the number of individuals in the states just before t, these are, N1(t) and N2 (t), was performed. Accordingly, it is shown that the good tracker and poor tracker hazard rates/ (survival curves) time to the 3rd violation, given a 2nd violation has occurred, are statistically significantly different (p-value = 0.044), see left hand side of Figure 18. Notably, the hazard rate for the poor trackers is 2.1 times that of good trackers, 95% confidence interval (CI) [1.01, 4.38].
Further interpretation of the hazard function can be made by assessing the slope of the cumulative hazard function. Figure 18 (RHS), shows that the cumulative hazard increases faster for the poor trackers than the good trackers indicated by a much steeper slope. This suggests it takes less time for the poor trackers to reach their third violation than for the good trackers, this is also confirmed by the 95% confidence bands for the survival curves shown in Figure 19 for the good tracker and poor trackers. Note that the interpretation of Kaplan–Meier curves here is not as straight-forward as for conventional survival analysis. In our ICU A-S process formulation the curves do not correspond to fixed cohorts, as patients can contribute to different states/curves at different times (Table 13). Thereby the curves may be considered to represent hypothetical cohorts whose values remain constant after follow-up [38, 39].
Survival curves (95% CIs) for good (left) and poor (right) (non-)trackers.
A Cox proportional hazards model (CPHM) was then fitted with tracking status and a patient’s number of violations as covariates. The general CPHM hazard function is,
In our application we model two covariates: X1 (0 for a good tracker, 1 for a poor tracker), and X2 being the patient’s total number of violations in the CPHM. The log rank test associated with the CPHM confirmed that the good tracker and poor tracker hazard rates, and the survival curves were significantly different (p-value = 0.0496), with the hazard rate for the poor trackers being 2.1 times that of good trackers, with a 95% confidence interval of [1.01, 4.38]. The associated hazard rate for poor trackers is shown to be 1.87 times that of good trackers, with a 95% confidence interval [0.75, 4.70]. By inclusion of the total number of second time violations the effect of tracking status has only reduced slightly, and it remains significant (1.87 versus 2.1).
Log-rank tests were likewise conducted to assess times to different violation counts. Let VX denote the violation times for the Xth violation and the DX’s the associated event indicators (0 censored, 1 event of interest). Log rank tests for the two WPB tracking strata for selected violation times (X = 5, 10, 15, 20, 25, 30) showed significant differences between good and poor WPB trackers regarding the time to the patient’s time to 10th violation (p = 0.027), their 15th (p = 0.025) and their 25th violation (p = 0.011). Likewise, significance at the 10% level was demonstrated for times to the patient’s 5th, 20th and 30th violation (non-violatory lifetimes). All survival curves (not shown here) are significantly different or are close to being significant at the 5% level of significance. This confirms that the difference in time to violations between the good and poor trackers are consistently different, for these varying number of violations (VX, for X = 5, 10, 15, 20, 25, 30).
The time to a patient’s last violation event was also investigated using log-rank tests and Kaplan–Meier curves. We examined nine levels of the effect of the following covariate, which categorises the counts the patient levels of violations as follows: 0–5 violations, 5–10, 10–15, 15–20, 20–25, 25–30, 30–40, 40–50 and >50 violations. A histogram of the time to a patient’s last violation with boxplots of the times for each of these nine levels of categorisation shown is given in Figure 20 (the number above the boxplots gives the number of patients in each of the nine categories).
Histogram and boxplots of time to last violation. The numbers above the boxplot (RHS) specify the number of patients in each violation level.
Using the patient’s time to their final violation/jump, as the event of interest, and implementing log-rank based tests using this covariate adjustment, the log rank test demonstrated a statistically significant difference between the survival curves of time to last violation (p-value <0.000001) across the above nine different total number of violation levels, {0–5, 5–10, 10–15, 15–20, 20–25, 25–30, 30–40, 40–50, >50 violations}.
Notably, the levels that most contribute to the difference between trackers and non-trackers are those patients who have a total number of violations between 10 and 15, between 20 and 25 and >50, in that order. A log rank test on time to last violation (time of last jump outside the WPB bands) as the outcome of interest by tracking status, also establishes that there is a difference between the two survival curves (p-value = 0.045) (Figure 21). Clearly the WPB-based poor trackers tend to take longer to reach their last violation than good trackers. Corresponding Kaplan–Meier estimated curves are given in Figure 21. We note that up to ICU time 64 (≤64), 40% of the good versus 70% of the poor trackers are still violating, whereas after time point, 130, the corresponding percentages violating are 15% versus 40%, of the good versus poor trackers (Figure 21).
Estimated survival curves for time to last violation by tracking status.
A log-rank test from the counting process formulation [37, 38, 39] established a significant difference between the hazard curves of the WPB-based good and poor trackers (p-value = 0.044). Similarly log-rank tests performed for a variety of violation numbers to test for differences between good and poor trackers times to their 5th, 10th, 15th, 20th, 25th and 30th violation, showed evidence of a significant difference between good and poor trackers for a selection of these violation times (namely patient’s time to their 10th, 15th and 25th violation). In regard to analysing the patients time to their last recorded violation, log-rank tests and Kaplan–Meier curves showed that poor trackers tend to have a higher probability of still violating as time progresses in ICU compared to good trackers (p-value = 0.045).
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\n'}]},successStories:{items:[]},authorsAndEditors:{filterParams:{},profiles:[{id:"396",title:"Dr.",name:"Vedran",middleName:null,surname:"Kordic",slug:"vedran-kordic",fullName:"Vedran Kordic",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/396/images/7281_n.png",biography:"After obtaining his Master's degree in Mechanical Engineering he continued his education at the Vienna University of Technology where he obtained his PhD degree in 2004. He worked as a researcher at the Automation and Control Institute, Faculty of Electrical Engineering, Vienna University of Technology until 2008. His studies in robotics lead him not only to a PhD degree but also inspired him to co-found and build the International Journal of Advanced Robotic Systems - world's first Open Access journal in the field of robotics.",institutionString:null,institution:{name:"TU Wien",country:{name:"Austria"}}},{id:"441",title:"Ph.D.",name:"Jaekyu",middleName:null,surname:"Park",slug:"jaekyu-park",fullName:"Jaekyu Park",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/441/images/1881_n.jpg",biography:null,institutionString:null,institution:{name:"LG Corporation (South Korea)",country:{name:"Korea, South"}}},{id:"465",title:"Dr.",name:"Christian",middleName:null,surname:"Martens",slug:"christian-martens",fullName:"Christian Martens",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Rheinmetall (Germany)",country:{name:"Germany"}}},{id:"479",title:"Dr.",name:"Valentina",middleName:null,surname:"Colla",slug:"valentina-colla",fullName:"Valentina Colla",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/479/images/358_n.jpg",biography:null,institutionString:null,institution:{name:"Sant'Anna School of Advanced Studies",country:{name:"Italy"}}},{id:"494",title:"PhD",name:"Loris",middleName:null,surname:"Nanni",slug:"loris-nanni",fullName:"Loris Nanni",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/494/images/system/494.jpg",biography:"Loris Nanni received his Master Degree cum laude on June-2002 from the University of Bologna, and the April 26th 2006 he received his Ph.D. in Computer Engineering at DEIS, University of Bologna. On September, 29th 2006 he has won a post PhD fellowship from the university of Bologna (from October 2006 to October 2008), at the competitive examination he was ranked first in the industrial engineering area. He extensively served as referee for several international journals. He is author/coauthor of more than 100 research papers. He has been involved in some projects supported by MURST and European Community. His research interests include pattern recognition, bioinformatics, and biometric systems (fingerprint classification and recognition, signature verification, face recognition).",institutionString:null,institution:null},{id:"496",title:"Dr.",name:"Carlos",middleName:null,surname:"Leon",slug:"carlos-leon",fullName:"Carlos Leon",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Seville",country:{name:"Spain"}}},{id:"512",title:"Dr.",name:"Dayang",middleName:null,surname:"Jawawi",slug:"dayang-jawawi",fullName:"Dayang Jawawi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Technology Malaysia",country:{name:"Malaysia"}}},{id:"528",title:"Dr.",name:"Kresimir",middleName:null,surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/528/images/system/528.jpg",biography:"K. Delac received his B.Sc.E.E. degree in 2003 and is currentlypursuing a Ph.D. degree at the University of Zagreb, Faculty of Electrical Engineering andComputing. His current research interests are digital image analysis, pattern recognition andbiometrics.",institutionString:null,institution:{name:"University of Zagreb",country:{name:"Croatia"}}},{id:"557",title:"Dr.",name:"Andon",middleName:"Venelinov",surname:"Topalov",slug:"andon-topalov",fullName:"Andon Topalov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/557/images/1927_n.jpg",biography:"Dr. Andon V. Topalov received the MSc degree in Control Engineering from the Faculty of Information Systems, Technologies, and Automation at Moscow State University of Civil Engineering (MGGU) in 1979. He then received his PhD degree in Control Engineering from the Department of Automation and Remote Control at Moscow State Mining University (MGSU), Moscow, in 1984. From 1985 to 1986, he was a Research Fellow in the Research Institute for Electronic Equipment, ZZU AD, Plovdiv, Bulgaria. In 1986, he joined the Department of Control Systems, Technical University of Sofia at the Plovdiv campus, where he is presently a Full Professor. He has held long-term visiting Professor/Scholar positions at various institutions in South Korea, Turkey, Mexico, Greece, Belgium, UK, and Germany. And he has coauthored one book and authored or coauthored more than 80 research papers in conference proceedings and journals. His current research interests are in the fields of intelligent control and robotics.",institutionString:null,institution:{name:"Technical University of Sofia",country:{name:"Bulgaria"}}},{id:"585",title:"Prof.",name:"Munir",middleName:null,surname:"Merdan",slug:"munir-merdan",fullName:"Munir Merdan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/585/images/system/585.jpg",biography:"Munir Merdan received the M.Sc. degree in mechanical engineering from the Technical University of Sarajevo, Bosnia and Herzegovina, in 2001, and the Ph.D. degree in electrical engineering from the Vienna University of Technology, Vienna, Austria, in 2009.Since 2005, he has been at the Automation and Control Institute, Vienna University of Technology, where he is currently a Senior Researcher. His research interests include the application of agent technology for achieving agile control in the manufacturing environment.",institutionString:null,institution:null},{id:"605",title:"Prof",name:"Dil",middleName:null,surname:"Hussain",slug:"dil-hussain",fullName:"Dil Hussain",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/605/images/system/605.jpg",biography:"Dr. Dil Muhammad Akbar Hussain is a professor of Electronics Engineering & Computer Science at the Department of Energy Technology, Aalborg University Denmark. Professor Akbar has a Master degree in Digital Electronics from Govt. College University, Lahore Pakistan and a P-hD degree in Control Engineering from the School of Engineering and Applied Sciences, University of Sussex United Kingdom. Aalborg University has Two Satellite Campuses, one in Copenhagen (Aalborg University Copenhagen) and the other in Esbjerg (Aalborg University Esbjerg).\n· He is a member of prestigious IEEE (Institute of Electrical and Electronics Engineers), and IAENG (International Association of Engineers) organizations. \n· He is the chief Editor of the Journal of Software Engineering.\n· He is the member of the Editorial Board of International Journal of Computer Science and Software Technology (IJCSST) and International Journal of Computer Engineering and Information Technology. \n· He is also the Editor of Communication in Computer and Information Science CCIS-20 by Springer.\n· Reviewer For Many Conferences\nHe is the lead person in making collaboration agreements between Aalborg University and many universities of Pakistan, for which the MOU’s (Memorandum of Understanding) have been signed.\nProfessor Akbar is working in Academia since 1990, he started his career as a Lab demonstrator/TA at the University of Sussex. After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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Accordingly, 80 medicinal plant species were reviewed; leaves and roots are the main parts of the plants used for preparation of traditional medicines. The local practitioners provided various traditional medications to their patients’ diseases such as stomachaches, asthma, dysentery, malaria, evil eyes, cancer, skin diseases, and headaches. The uses of medicinal plants for human and animal treatments are practiced from time immemorial. Stream/riverbanks, cultivated lands, disturbed sites, bushlands, forested areas and their margins, woodlands, grasslands, and home gardens are major habitats of medicinal plants. Generally, medicinal plants used for traditional medicine play a significant role in the healthcare of the majority of the people in Ethiopia. The major threats to medicinal plants are habitat destruction, urbanization, agricultural expansion, investment, road construction, and deforestation. Because of these, medicinal plants are being declined and lost with their habitats. Community- and research-based conservation mechanisms could be an appropriate approach for mitigating the problems pertinent to the loss of medicinal plants and their habitats and for documenting medicinal plants. Chromatography; electrophoretic, macroscopic, and microscopic techniques; and pharmaceutical practice are mainly used for quality control of herbal medicines.",book:{id:"8502",slug:"plant-science-structure-anatomy-and-physiology-in-plants-cultured-in-vivo-and-in-vitro",title:"Plant Science",fullTitle:"Plant Science - Structure, Anatomy and Physiology in Plants Cultured in Vivo and in Vitro"},signatures:"Admasu Moges and Yohannes Moges",authors:[{id:"249746",title:"Ph.D.",name:"Admasu",middleName:null,surname:"Moges",slug:"admasu-moges",fullName:"Admasu Moges"},{id:"297761",title:"MSc.",name:"Yohannes",middleName:null,surname:"Moges",slug:"yohannes-moges",fullName:"Yohannes Moges"}]},{id:"70658",title:"Factors Affecting Yield of Crops",slug:"factors-affecting-yield-of-crops",totalDownloads:4179,totalCrossrefCites:31,totalDimensionsCites:46,abstract:"A good understanding of dynamics involved in food production is critical for the improvement of food security. It has been demonstrated that an increase in crop yields significantly reduces poverty. Yield, the mass of harvest crop product in a specific area, is influenced by several factors. These factors are grouped in three basic categories known as technological (agricultural practices, managerial decision, etc.), biological (diseases, insects, pests, weeds) and environmental (climatic condition, soil fertility, topography, water quality, etc.). These factors account for yield differences from one region to another worldwide. The current chapter will discuss each of these three basic factors as well as providing some recommendations for overcoming them. In addition, it will provide the importance of climate-smart agriculture in the increase of crop yields while facilitating the achievement of crop production in safe environment. This goes in line with the second goal of 2030 Agenda for Sustainable Development of United Nations in transforming our world formulated as end hunger, achieve food security, improve nutrition and promote sustainable agriculture.",book:{id:"8153",slug:"agronomy-climate-change-food-security",title:"Agronomy",fullTitle:"Agronomy - Climate Change & Food Security"},signatures:"Tandzi Ngoune Liliane and Mutengwa Shelton Charles",authors:[{id:"313819",title:"Dr.",name:"Liliane",middleName:null,surname:"Tandzi",slug:"liliane-tandzi",fullName:"Liliane Tandzi"},{id:"314316",title:"Prof.",name:"Charles Shelton",middleName:null,surname:"Mutengwa",slug:"charles-shelton-mutengwa",fullName:"Charles Shelton Mutengwa"}]},{id:"59402",title:"Robotic Harvesting of Fruiting Vegetables: A Simulation Approach in V-REP, ROS and MATLAB",slug:"robotic-harvesting-of-fruiting-vegetables-a-simulation-approach-in-v-rep-ros-and-matlab",totalDownloads:2820,totalCrossrefCites:8,totalDimensionsCites:9,abstract:"In modern agriculture, there is a high demand to move from tedious manual harvesting to a continuously automated operation. This chapter reports on designing a simulation and control platform in V-REP, ROS, and MATLAB for experimenting with sensors and manipulators in robotic harvesting of sweet pepper. The objective was to provide a completely simulated environment for improvement of visual servoing task through easy testing and debugging of control algorithms with zero damage risk to the real robot and to the actual equipment. A simulated workspace, including an exact replica of different robot manipulators, sensing mechanisms, and sweet pepper plant, and fruit system was created in V-REP. Image moment method visual servoing with eye-in-hand configuration was implemented in MATLAB, and was tested on four robotic platforms including Fanuc LR Mate 200iD, NOVABOT, multiple linear actuators, and multiple SCARA arms. Data from simulation experiments were used as inputs of the control algorithm in MATLAB, whose outputs were sent back to the simulated workspace and to the actual robots. ROS was used for exchanging data between the simulated environment and the real workspace via its publish-and-subscribe architecture. Results provided a framework for experimenting with different sensing and acting scenarios, and verified the performance functionality of the simulator.",book:{id:"6265",slug:"automation-in-agriculture-securing-food-supplies-for-future-generations",title:"Automation in Agriculture",fullTitle:"Automation in Agriculture - Securing Food Supplies for Future Generations"},signatures:"Redmond R. Shamshiri, Ibrahim A. Hameed, Manoj Karkee and\nCornelia Weltzien",authors:[{id:"182449",title:"Prof.",name:"Ibrahim",middleName:"A.",surname:"Hameed",slug:"ibrahim-hameed",fullName:"Ibrahim Hameed"},{id:"203413",title:"Dr.",name:"Redmond R.",middleName:null,surname:"Shamshiri",slug:"redmond-r.-shamshiri",fullName:"Redmond R. Shamshiri"},{id:"241193",title:"Dr.",name:"Manoj",middleName:null,surname:"Karkee",slug:"manoj-karkee",fullName:"Manoj Karkee"},{id:"241194",title:"Dr.",name:"Cornelia",middleName:null,surname:"Weltzien",slug:"cornelia-weltzien",fullName:"Cornelia Weltzien"}]}],onlineFirstChaptersFilter:{topicId:"5",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"83156",title:"Biomimetic and Hemisynthetic Pesticides",slug:"biomimetic-and-hemisynthetic-pesticides",totalDownloads:2,totalDimensionsCites:0,doi:"10.5772/intechopen.105158",abstract:"Pests are responsible for most losses associated with agricultural crops. In addition, due to the indiscriminate use of synthetic pesticides, several problems have arisen over the years, such as pest resistance and contamination of important planetary sources such as water, air and soil. This awareness regarding pest problems and environment has led to the search for powerful and eco-friendly pesticides that degrade after some time, avoiding pest persistence resistance, which is also pest-specific, non-phytotoxic, nontoxic to mammals, and relatively less expensive in order to obtain a sustainable crop production Biodegradable biomimetic pesticides can be a potential green alternative to the pest industry.",book:{id:"11318",title:"Pesticides",coverURL:"https://cdn.intechopen.com/books/images_new/11318.jpg"},signatures:"Ahissan Innocent Adou, Garrick Bibian, Odile Bordelais, Léa Farouil, Muriel Sylvestre, Sarra Gaspard, Marie-Noëlle Sylvestre and Gerardo Cebrián-Torrejón"},{id:"83167",title:"Physiological Mechanisms of Tolerance to Drought and Heat in Major Pulses for Improving Yield under Stress Environments",slug:"physiological-mechanisms-of-tolerance-to-drought-and-heat-in-major-pulses-for-improving-yield-under-",totalDownloads:6,totalDimensionsCites:null,doi:"10.5772/intechopen.106054",abstract:"Reduction in biomass and pollen fertility are the two major constraints resulting in poor grain yield in major pulses grown under rainfed agrosystem. Generally, pulses are encountered into both heat and drought stresses during terminal reproductive stages. Though pulses have many adaptive features to counter the adverse effects of various abiotic stresses but yield is substantially reduced when the magnitude of these stresses is very high. The factors have been identified to enhance grain yield under stress environments which include promotion of biomass in the above ground part enabling crops to reserve a maximum amount of photosynthesis and water in the plant system itself before the onset of drought and heat stresses during reproductive stages. Various physiological mechanisms and fertility enhancement components including genetic diversity in key traits have been discussed here to improve yield of pulses under stressed conditions.",book:{id:"11330",title:"Plant Response Mechanisms to Abiotic Stresses",coverURL:"https://cdn.intechopen.com/books/images_new/11330.jpg"},signatures:"Partha S. Basu, Sushil Kumar Chaturvedi, Pooran Mall Gaur, Biswajit Mondal, Surendra Kumar Meena, Krishnashis Das, Vaibhav Kumar, Kalpana Tewari and Kusum Sharma"},{id:"83160",title:"State of the Art of Yam Production",slug:"state-of-the-art-of-yam-production",totalDownloads:7,totalDimensionsCites:null,doi:"10.5772/intechopen.106504",abstract:"Yam is a labor-intensive and weed-sensitive food crop. The labor-intensive nature of the yam means that the production process requires the attention of the farmer all year round. However, the dwindling labor situation and the proliferation of weeds have forced farmers to think of modern ways of controlling weeds on their farms, that is, the adoption of chemical (herbicides) weed control. Even though the adoption of these chemicals has no doubt brought relief to the farmers and has resulted in increased yam production over the years, it has also brought in its wake, negative externalities of environmental pollution, human health effects, and food quality issues. The study was thus designed to investigate how yam is produced, the human and environmental health effects of how yam is produced, and food quality effects of how yam is produced. This was done through literature review, and field and laboratory experiments. It was revealed that, in recent years, new innovations have been introduced in yam production, the manner in which farmers handle herbicides in their yam production process exposes them to high doses of pesticides, thereby endangering their lives. The study findings also suggest that the use of herbicides in yam production does not affect the quality of the yam.",book:{id:"11619",title:"Root Vegetables",coverURL:"https://cdn.intechopen.com/books/images_new/11619.jpg"},signatures:"Abukari Wumbei, Sopkoutie Kengni Nerlus Gautier, Joseph Kwowura Kwodaga, Djeugap Fovo Joseph and Yamdeu Joseph Hubert Galani"},{id:"83168",title:"Improvement of Tertiary Irrigation Networks, Changes in Cropping Patterns, and Increasing Cropping Index at Kendal Indonesia",slug:"improvement-of-tertiary-irrigation-networks-changes-in-cropping-patterns-and-increasing-cropping-ind",totalDownloads:1,totalDimensionsCites:null,doi:"10.5772/intechopen.106266",abstract:"Increasing food crop production remains a top priority for the Indonesian government, as demand increases as the population grows. One of the obstacles faced in increasing production is climate change. One of the adaptations to climate change in agriculture is to establish policies for the development and modification of infrastructure that can save water resources management and establish institutions involved in the planning and implementation of water resources management. Kendal Regency, Central Java Province, is one of the regions that contributes to food availability in Indonesia. These conditions support the development of food crops, especially rice, corn, and soybeans. Since 2015, the government and farmers have made improvements to the tertiary irrigation network in paddy fields. This activity aims to increase the cropping index and achieve cropping patterns for one year. In the implementation of irrigation network improvement activities, the community of farmers using water usually works together in determining the location for repairs and making suggestions for improvements to the government. Improvements to irrigation networks were able to increase the cropping index by 0.37 from 1.85 in 2015 to 2.22 in 2016 or equivalent to an area of 8,880 ha (standard area ±24,000 ha).",book:{id:"11623",title:"Irrigation and Drainage - Recent Advances",coverURL:"https://cdn.intechopen.com/books/images_new/11623.jpg"},signatures:"Meinarti Norma Setiapermas, Anggi Sahru Romdon and Yulis Hindarwati"},{id:"82580",title:"Predicting Trends, Seasonal Effects, and Future Yields in Cow’s Milk through Time Series Analysis",slug:"predicting-trends-seasonal-effects-and-future-yields-in-cow-s-milk-through-time-series-analysis",totalDownloads:1,totalDimensionsCites:0,doi:"10.5772/intechopen.105704",abstract:"A dairy is a place that is used for handling milk and milk products. Dairy products are basically based on milk. Milk is used to prepare dairy products, such as butter, cheese, and milk powder. There is always a great demand for milk and milk products among people. This study attempted to investigate the trends in the actual yield of cow’s milk production at Andassa dairy farm. We used secondary data for the study of the daily milk production of cows at Andassa dairy farm. The specific objectives of the study were—to identify whether the milk production is time-dependent or not; to predict in which season the milk production is high or low; to examine the daily trend analysis of milk production; to fit the appropriate model; and to forecast the milk production for the future. The study was conducted based on quantitative variables. So, the dependent variable is the average daily milk, and the independent variable is the time measure at which milk production is measured each day. The study used both descriptive and inferential statistics to analyze the data that were collected from the dairy farms in the sector. This study covered a total of 179 days of milk production. The results reveal that the milk yield of cows is declining, and that milk output is time-dependent, according to the time series plot, and that the model is ARIMA.",book:{id:"10887",title:"New Advances in the Dairy Industry",coverURL:"https://cdn.intechopen.com/books/images_new/10887.jpg"},signatures:"Birhan Ambachew Taye, Alemayehu Amsalu Alen, Ashenafi Kalayu Nega and Bantie Getnet Yirsaw"},{id:"81881",title:"Cassava Production Enterprise in the Tropics",slug:"cassava-production-enterprise-in-the-tropics",totalDownloads:11,totalDimensionsCites:0,doi:"10.5772/intechopen.104677",abstract:"Cassava, a tropical root crop, provides the staple food for millions of people around the world. It is one of the tuber crops that could be cultivated on a small scale in an environment with erratic rainfall, and without necessarily needing heavy equipment and machineries. Cassava could be successfully cultivated by resource-poor farm family. Farmers’ productivity could be as much as 70 tonnes per hectares under favourable conditions. However, smallholder farmers do among other things improve productivity through proven cultural practices and a mix of organic and inorganic measures. Irrigation is very necessary for achieving bumper harvest in areas with shortage of rainfall and insufficient soil moisture content. The concept of sustainability in the practice of agriculture has been on the front burner world over in recent time. Therefore, the cultivation of cassava with the aim of increased productivity without jeopardising the factors of production meant for future time is encouraged. Practices that combine traditional knowledge with modern technologies that are adapted to the needs of small-scale farmers are on the increase around the world. Depending on the purpose, cassava could be harvested anytime from eight month. Cassava leaves could serve as vegetable and the stems use as fire wood.",book:{id:"11311",title:"Tropical Plant Species",coverURL:"https://cdn.intechopen.com/books/images_new/11311.jpg"},signatures:"Raufu Olusola Sanusi, Deola-Tayo Lordbanjou, Azeez Olalekan Ibrahim, Mohammad Babakatcha Abubakar and Oluwole Olalekan Oke"}],onlineFirstChaptersTotal:331},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:11,numberOfPublishedChapters:91,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:333,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:11,numberOfPublishedChapters:144,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:126,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:23,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:13,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"6",title:"Infectious Diseases",doi:"10.5772/intechopen.71852",issn:"2631-6188",scope:"This series will provide a comprehensive overview of recent research trends in various Infectious Diseases (as per the most recent Baltimore classification). Topics will include general overviews of infections, immunopathology, diagnosis, treatment, epidemiology, etiology, and current clinical recommendations for managing infectious diseases. Ongoing issues, recent advances, and future diagnostic approaches and therapeutic strategies will also be discussed. This book series will focus on various aspects and properties of infectious diseases whose deep understanding is essential for safeguarding the human race from losing resources and economies due to pathogens.",coverUrl:"https://cdn.intechopen.com/series/covers/6.jpg",latestPublicationDate:"August 18th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:13,editor:{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",slug:"alfonso-j.-rodriguez-morales",fullName:"Alfonso J. Rodriguez-Morales",profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},editorTwo:null,editorThree:null},subseries:{paginationCount:5,paginationItems:[{id:"91",title:"Sustainable Economy and Fair Society",coverUrl:"https://cdn.intechopen.com/series_topics/covers/91.jpg",isOpenForSubmission:!0,annualVolume:11975,editor:{id:"181603",title:"Dr.",name:"Antonella",middleName:null,surname:"Petrillo",slug:"antonella-petrillo",fullName:"Antonella Petrillo",profilePictureURL:"https://mts.intechopen.com/storage/users/181603/images/system/181603.jpg",biography:"Antonella Petrillo, Ph.D., is a professor in the Department of Engineering, University of Naples “Parthenope,” Italy. She received her Ph.D. in Mechanical Engineering from the University of Cassino and Southern Lazio, Italy. Her research interests include multi-criteria decision analysis, industrial plants, logistics, manufacturing, and safety. She serves as an associate editor for the International Journal of the Analytic Hierarchy Process and is an editorial board member for several other journals. She is also a member of the Analytic Hierarchy Process (AHP) Academy.",institutionString:"Parthenope University of Naples, Italy",institution:{name:"Parthenope University of Naples",institutionURL:null,country:{name:"Italy"}}},editorTwo:null,editorThree:null},{id:"92",title:"Health and Wellbeing",coverUrl:"https://cdn.intechopen.com/series_topics/covers/92.jpg",isOpenForSubmission:!0,annualVolume:11976,editor:{id:"348225",title:"Prof.",name:"Ann",middleName:null,surname:"Hemingway",slug:"ann-hemingway",fullName:"Ann Hemingway",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035LZFoQAO/Profile_Picture_2022-04-11T14:55:40.jpg",biography:"Professor Hemingway is a public health researcher, Bournemouth University, undertaking international and UK research focused on reducing inequalities in health outcomes for marginalised and excluded populations and more recently focused on equine assisted interventions.",institutionString:null,institution:{name:"Bournemouth University",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null},{id:"93",title:"Inclusivity and Social Equity",coverUrl:"https://cdn.intechopen.com/series_topics/covers/93.jpg",isOpenForSubmission:!0,annualVolume:11977,editor:{id:"210060",title:"Prof. Dr.",name:"Ebba",middleName:null,surname:"Ossiannilsson",slug:"ebba-ossiannilsson",fullName:"Ebba Ossiannilsson",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6LkBQAU/Profile_Picture_2022-02-28T13:31:48.png",biography:"Professor Dr. Ebba Ossiannilsson is an independent researcher, expert, consultant, quality auditor and influencer in the fields of open, flexible online and distance learning (OFDL) and the 'new normal'. Her focus is on quality, innovation, leadership, and personalised learning. She works primarily at the strategic and policy levels, both nationally and internationally, and with key international organisations. She is committed to promoting and improving OFDL in the context of SDG4 and the future of education. Ossiannilsson has more than 20 years of experience in her current field, but more than 40 years in the education sector. She works as a reviewer and expert for the European Commission and collaborates with the Joint Research Centre for Quality in Open Education. Ossiannilsson also collaborates with ITCILO and ICoBC (International Council on Badges and Credentials). She is a member of the ICDE Board of Directors and has previously served on the boards of EDEN and EUCEN. Ossiannilsson is a quality expert and reviewer for ICDE, EDEN and the EADTU. She chairs the ICDE OER Advocacy Committee and is a member of the ICDE Quality Network. She is regularly invited as a keynote speaker at conferences. She is a guest editor for several special issues and a member of the editorial board of several scientific journals. She has published more than 200 articles and is currently working on book projects in the field of OFDL. Ossiannilsson is a visiting professor at several international universities and was recently appointed Professor and Research Fellow at Victoria University of Wellington, NZ. Ossiannilsson has been awarded the following fellowships: EDEN Fellows, EDEN Council of Fellows, and Open Education Europe. She is a ICDE OER Ambassador, Open Education Europe Ambassador, GIZ Ambassador for Quality in Digital Learning, and part of the Globe-Community of Digital Learning and Champion of SPARC Europe. On a national level, she is a quality developer at the Swedish Institute for Standards (SIS) and for ISO. She is a member of the Digital Skills and Jobs Coalition Sweden and Vice President of the Swedish Association for Distance Education. She is currently working on a government initiative on quality in distance education at the National Council for Higher Education. She holds a Ph.D. from the University of Oulu, Finland.",institutionString:"Swedish Association for Distance Education, Sweden",institution:null},editorTwo:null,editorThree:null},{id:"94",title:"Climate Change and Environmental Sustainability",coverUrl:"https://cdn.intechopen.com/series_topics/covers/94.jpg",isOpenForSubmission:!0,annualVolume:11978,editor:{id:"61855",title:"Dr.",name:"Yixin",middleName:null,surname:"Zhang",slug:"yixin-zhang",fullName:"Yixin Zhang",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYWJgQAO/Profile_Picture_2022-06-09T11:36:35.jpg",biography:"Professor Yixin Zhang is an aquatic ecologist with over 30 years of research and teaching experience in three continents (Asia, Europe, and North America) in Stream Ecology, Riparian Ecology, Urban Ecology, and Ecosystem Restoration and Aquatic Conservation, Human-Nature Interactions and Sustainability, Urbanization Impact on Aquatic Ecosystems. He got his Ph.D. in Animal Ecology at Umeå University in Sweden in 1998. He conducted postdoc research in stream ecology at the University of California at Santa Barbara in the USA. After that, he was a postdoc research fellow at the University of British Columbia in Canada to do research on large-scale stream experimental manipulation and watershed ecological survey in temperate rainforests of BC. He was a faculty member at the University of Hong Kong to run ecological research projects on aquatic insects, fishes, and newts in Tropical Asian streams. He also conducted research in streams, rivers, and caves in Texas, USA, to study the ecology of macroinvertebrates, big-claw river shrimp, fish, turtles, and bats. Current research interests include trophic flows across ecosystems; watershed impacts of land-use change on biodiversity and ecosystem functioning; ecological civilization and water resource management; urban ecology and urban/rural sustainable development.",institutionString:null,institution:{name:"Soochow University",institutionURL:null,country:{name:"China"}}},editorTwo:null,editorThree:null},{id:"95",title:"Urban Planning and Environmental Management",coverUrl:"https://cdn.intechopen.com/series_topics/covers/95.jpg",isOpenForSubmission:!0,annualVolume:11979,editor:{id:"181079",title:"Dr.",name:"Christoph",middleName:null,surname:"Lüthi",slug:"christoph-luthi",fullName:"Christoph Lüthi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRHSqQAO/Profile_Picture_2022-04-12T15:51:33.png",biography:"Dr. Christoph Lüthi is an urban infrastructure planner with over 25 years of experience in planning and design of urban infrastructure in middle and low-income countries. He holds a Master’s Degree in Urban Development Planning from the University College of London (UCL), and a Ph.D. in Urban Planning & Engineering from TU Berlin. He has conducted applied research on urban planning and infrastructure issues in over 20 countries in Africa and Asia. In 2005 he joined Eawag-Sandec as Leader of the Strategic Environmental Sanitation Planning Group. 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Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Bacterial Infectious Diseases",value:3,count:2},{group:"subseries",caption:"Parasitic Infectious Diseases",value:5,count:4},{group:"subseries",caption:"Viral Infectious Diseases",value:6,count:7}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:2},{group:"publicationYear",caption:"2021",value:2021,count:4},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:3},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:189,paginationItems:[{id:"221831",title:"Prof.",name:"Niansheng",middleName:null,surname:"Tang",slug:"niansheng-tang",fullName:"Niansheng Tang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221831/images/system/221831.jpeg",biography:"Niansheng Tang is a Professor of Statistics and Dean of the School of Mathematics and Statistics, Yunnan University, China. He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. As a professor, Dr. Neves has supervised several Ph.D. and master’s students and was involved in more than twenty-five different courses.",institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"11317",title:"Dr.",name:"Francisco",middleName:null,surname:"Javier Gallegos-Funes",slug:"francisco-javier-gallegos-funes",fullName:"Francisco Javier Gallegos-Funes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/11317/images/system/11317.png",biography:"Francisco J. Gallegos-Funes received his Ph.D. in Communications and Electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. He is currently an associate professor in the Escuela Superior de Ingeniería Mecánica y Eléctrica (Mechanical and Electrical Engineering Higher School) at the same institute. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. 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He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:null,institution:null},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. 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He is currently a rated researcher by the National Research Foundation of South Africa at category C2. He has published widely in the field of infectious diseases and has overseen several MSc’s and PhDs. His research activities mostly cover topics on infectious diseases from epidemiology to control. His particular interest lies in the study of intestinal protozoan parasites and opportunistic infections among HIV patients as well as the potential impact of childhood diarrhoea on growth and child development. He also conducts research on water-borne diseases and water quality and is involved in the evaluation of point-of-use water treatment technologies using silver and copper nanoparticles in collaboration with the University of Virginia, USA. 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