Traditional and nontraditional risk factors for cardiovascular disease in special populations.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{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"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"3101",leadTitle:null,fullTitle:"Research on Soil Erosion",title:"Research on Soil Erosion",subtitle:null,reviewType:"peer-reviewed",abstract:'Soil loss for erosion is a natural phenomenon in soil dynamics, influenced by climate, soil intrinsic properties, and morphology, that can both trigger and enhance the process. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"2270",title:"Fourier Transform",subtitle:"Materials Analysis",isOpenForSubmission:!1,hash:"5e094b066da527193e878e160b4772af",slug:"fourier-transform-materials-analysis",bookSignature:"Salih Mohammed Salih",coverURL:"https://cdn.intechopen.com/books/images_new/2270.jpg",editedByType:"Edited by",editors:[{id:"111691",title:"Dr.Ing.",name:"Salih",surname:"Salih",slug:"salih-salih",fullName:"Salih Salih"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"117",title:"Artificial Neural Networks",subtitle:"Methodological Advances and Biomedical Applications",isOpenForSubmission:!1,hash:null,slug:"artificial-neural-networks-methodological-advances-and-biomedical-applications",bookSignature:"Kenji Suzuki",coverURL:"https://cdn.intechopen.com/books/images_new/117.jpg",editedByType:"Edited by",editors:[{id:"3095",title:"Prof.",name:"Kenji",surname:"Suzuki",slug:"kenji-suzuki",fullName:"Kenji Suzuki"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3828",title:"Application of Nanotechnology in Drug Delivery",subtitle:null,isOpenForSubmission:!1,hash:"51a27e7adbfafcfedb6e9683f209cba4",slug:"application-of-nanotechnology-in-drug-delivery",bookSignature:"Ali Demir Sezer",coverURL:"https://cdn.intechopen.com/books/images_new/3828.jpg",editedByType:"Edited by",editors:[{id:"62389",title:"PhD.",name:"Ali Demir",surname:"Sezer",slug:"ali-demir-sezer",fullName:"Ali Demir Sezer"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"64903",title:"Dyslipidemia in Special Populations, the Elderly, Women, HIV, Chronic Kidney Disease and ESRD, and Minority Groups",doi:"10.5772/intechopen.82831",slug:"dyslipidemia-in-special-populations-the-elderly-women-hiv-chronic-kidney-disease-and-esrd-and-minori",body:'Dyslipidemia, defined as high levels of low-density lipoprotein cholesterol (LDL-C) (≥130 mg/dl), total cholesterol (≥200 mg/dl), and triglycerides (TG) (≥150 mg/dl), or low levels of high-density lipoprotein cholesterol (HDL-C) [<40 (men) and < 50 (women) mg/dl], is a major risk factor for cardiovascular disease (CVD). Significant heterogeneity in patterns of dyslipidemia exists in these special populations. There is confusion among health-care providers regarding selection and implementation of appropriate guidelines, particularly for special patient populations. Patients in special populations may not clearly fall into one of the four statin-benefit groups identified by the ACC/AHA cholesterol guidelines [1].
In this chapter, we review the evidence in patterns of dyslipidemia and management in the elderly, women and pregnancy, CKD, ESRD, HIV, and different racial/ethnic groups.
According to census projections, the population age 65 and older is expected to double between 2012 and 2060, from 43.1 to 92.0 million [2]. CVD is the main cause of mortality in this age group. Lipid-lowering pharmacological intervention is one of the most successful cardiovascular preventative interventions. Concerns about its safety and efficacy in this age group have led different countries to adopt different strategies concerning the use of lipid-lowering drugs in the elderly [3]. In US population as reported in the National Health and Nutrition Examination Survey (NHANES) publications, across all age groups, triglyceride levels increase with age and reach a peak in men aged 50–59 years and in women aged 60–69 years. Apolipoprotein B (Apo B) and small dense LDLc also increase with age, while HDL-c does not seem to vary with age [4].
Lifestyle modification including adhering to a heart healthy diet, regular exercise, avoidance of tobacco products, and maintenance of a healthy weight remains a critical component of ASCVD risk reduction.
In general, the elderly are usually underrepresented in published clinical trials. The only large randomized statin trials that focused on older patients are the Prospective Study of Pravastatin in the Elderly at Risk (PROSPER) and the Study Assessing Goals in the Elderly (SAGE) trial.
PROSPER is a randomized controlled trial in which 5804 patients aged 70–82 years with a history of, or risk factors for, vascular disease were randomized to receive pravastatin (40 mg/day; n = 2891) or placebo (n = 2913). Follow-up was 3.2 years. Pravastatin was found to reduce the incidence of coronary death, nonfatal myocardial infarction, and fatal or nonfatal stroke. Suggesting pravastatin may be utilized to manage dyslipidemia in the elderly and be prescribed to [5]. Later, the Study Assessing Goals in the Elderly (SAGE) compared the effect of intensive (atorvastatin 80 mg/day) with moderate (pravastatin 40 mg/day) cholesterol lowering with statins in a cohort of 893 patients, 65–85 years of age with coronary artery disease (CAD), and follow-up for 12 months. Atorvastatin-treated patients experienced greater LDL-C reductions than did pravastatin-treated patients, a trend toward fewer major acute cardiovascular events and a significantly greater reduction (77%) in all-cause death [6].
British Heart Foundation Heart Protection Study evaluated the role of simvastatin 40 mg/day versus placebo in 20,536 patients with coronary atherosclerosis and diabetics with coronary heart disease (CHD) risk equivalence. About 28% of randomized patients were ≥70 years of age. Among the 1263 individuals with 75–80 years of age at study entry, the rate of major coronary events in the simvastatin group was significantly lower than placebo group [7]. The long-term intervention with pravastatin in ischemic disease (LIPID) trial randomized patients with prior myocardial infarction or unstable angina to receive pravastatin 40 mg/day versus placebo, of which 39% (3514) were of age 65–75 years. Here, pravastatin reduced the risk for all CVD events, and similar adverse effects were observed in older and younger patients [8].
Other major secondary prevention trials, which included large numbers of elderly patients, are cholesterol and recurrent events (CARE) and Scandinavian simvastatin survival study (4S). In subgroup analyses of both studies, the absolute benefit of treatment was significantly greater in older patients as compared to younger patients for cardiovascular events [9, 10]. The 2013 ACC/AHA guidelines on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults recommended high-intensity statin therapy should be initiated or continued as first-line therapy in women and men ≤75 years of age who have clinical atherosclerotic cardiovascular disease (ASCVD), unless contraindicated. A larger amount of data supports the use of moderate-intensity statin therapy for secondary prevention in individuals with clinical ASCVD who are >75 years of age. However, the limited information available did not clearly support initiation of high-intensity statin therapy for secondary prevention in individuals >75 years of age [1]. Statin therapy to higher risk elderly patients is appropriate. In individuals with clinical ASCVD >75 years of age, practitioners should evaluate the potential for ASCVD risk-reduction benefits, adverse effects, drug-drug interactions and consider patient preferences when initiating a moderate- or high-intensity statin. It is reasonable to continue statin therapy in those who are tolerating it [1, 11]. Physicians treating the elderly must also consider the functional age of the patient and the impact of long-term drug therapy on safety and quality of life. Caution is recommended when statins are used in frail elderly patients, who may be more susceptible to drug-related myopathy and other side effects [12].
The Anglo-Scandinavian Cardiac Outcomes trial randomized 19,342 hypertensive patients (aged 40–79 years with at least three other cardiovascular risk factors) to be assigned to atorvastatin 10 mg or placebo. Nonfatal myocardial infarction and fatal cardiovascular disease were significantly lower in the statin group [13]. In a post hoc analysis, efficacy and safety of atorvastatin in 1129 patients aged 65–75 years at randomization was compared with 1709 younger patients in the Collaborative Atorvastatin Diabetes Study (CARDS). Primary end point of time to first occurrence of acute coronary heart disease events, coronary revascularizations, or stroke was similar in both groups. The overall safety profile of atorvastatin was similar between age groups [14]. Justification for the Use of statins in Prevention: An Intervention Trial Evaluating Rosuvastatin (JUPITER) is a randomized, double-blind, placebo-controlled trial with 17,802 participants of which 5695 were 70 years or older with LDL-C levels <130 mg/dl and high-sensitivity C-reactive protein levels of 2.0 mg/L or more without cardiovascular disease and were randomly assigned in a 1:1 ratio to receive 20 mg of rosuvastatin daily or placebo. In secondary analysis of this trial, no significant heterogeneity was found in treatment effects by age, absolute reductions in event rates associated with rosuvastatin were greater in elderly. The relative rate of any serious adverse event among older patients in the rosuvastatin versus placebo group was 1.05 (CI, 0.93–1.17) [15, 16].
As per 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults; four statin benefit groups are individuals with ASCVD, individuals with primary elevations of LDL-C ≥ 190 mg/day, individuals 40–75 years of age with diabetes and LDL-C 70 to 189 mg/dl without clinical ASCVD, and individuals without clinical ASCVD or diabetes who are 40–75 years of age and have LDL-C 70–189 mg/dl and an estimated 10-year ASCVD risk of ≥7.5%. This requires a clinician-patient discussion. Few data are available to indicate an ASCVD event reduction benefit in primary prevention among individuals >75 years of age who do not have clinical ASCVD. Therefore, initiation of statins for primary prevention of ASCVD in individuals >75 years of age requires consideration of additional factors, including increasing comorbidities, safety considerations, and priorities of care. The Pooled Cohort Equations can also provide information on expected 10-year ASCVD risk for those 76–79 years of age that may inform the treatment decision. A discussion of the potential ASCVD risk-reduction benefits, risk of adverse effects, drug-drug interactions, and consideration of patient preferences should precede the initiation of statin therapy for primary prevention in older individuals [1].
In the PROSPER study, no rhabdomyolysis or serum CK concentration > 10 times the upper limit of normal was reported. There was no statistically significant difference in the incidence of reported myalgia between the pravastatin and placebo groups (1.2 and 1.1%, respectively). In the SAGE study, incidence of myalgia was also not different between the atorvastatin and pravastatin treatment groups (3.1% versus 2.7%) with only one individual found to have CK level > 10 times the upper limit of normal in the pravastatin treatment group but none in the atorvastatin group [5, 6]. In a retrospective study, Graham et al. reported rhabdomyolysis risk was similar and low for monotherapy with atorvastatin, pravastatin, and simvastatin. Combined statin-fibrate use was associated with increased risk, especially in older patients with diabetes mellitus [17].
All of the available statins, with the exception of pravastatin and rosuvastatin, are metabolized by the cytochrome P450 (CYP) system. Serum concentrations of these statins can potentially be increased when other medications competing for the CYP system or CYP isoenzyme inhibitors are prescribed and can lead to increased risk of myositis and rhabdomyolysis. There is an age-related decrease in glomerular filtration rate, decrease in hepatic blood flow, decrease in drug clearance, and increased expression of P-glycoproteins resulting in alterations in the rate of drug transport across cellular membranes [18, 19, 20].
Improved Reduction of Outcomes: Vytorin Efficacy International Trial (IMPROVE-IT) evaluated the effect of ezetimibe combined with simvastatin, as compared to simvastatin alone in 18,144 patients with acute coronary syndrome. Subgroup analysis showed a benefit of ezetimibe in the 7971 patients’ over 65 years and 2798 patients’ over 75 years of age [21].
The first large cardiovascular outcome study using PCSK9 inhibitor therapy (FOURIER) was a randomized, double-blind placebo-controlled trial of 27,564 subjects with 12,254 patients over the age 65 years with ASCVD and LDL-C levels ≥70 mg/dl while on maximally tolerated statin therapy, randomly assigned to receive evolocumab or placebo. In these patients, there was a significant decrease in composite outcome of cardiovascular death, myocardial infarction (MI), stroke, hospitalization for unstable angina, or coronary revascularization. However, cost is prohibitive for generalized use [22].
No data are available for fibrates in patients over 75 years of age. World Health Organization Clofibrate Study, Helsinki Heart Study (HHS), Bezafibrate Infarction Prevention (BIP), and Veterans Affairs Program High-Density Lipoprotein Cholesterol Intervention Trial (VA-HIT) showed reduction in the risk of myocardial infraction. Fenofibrate is considered the preferred agent, due to once-daily dosing and a favorable adverse reactions profile. Caution is needed in elderly patients with reduced renal function [23, 24, 25, 26].
In conclusion, cardiovascular prevention clinical trial evidence for the patients over age 75 years is very limited. Management of dyslipidemia in the elderly requires consideration of comorbidities, safety considerations, polypharmacy, and priorities of care.
CVD is a major cause of death in women. While the risk of CVD in men increases after age 40 years, risk develops 7–10 years later in women. Incidence of CAD in premenopausal women is 3–4 times lower than in men [27, 28]. After menopause due to loss of vasodilating property of estrogen and increased sympathetic activity, the risk of CAD is increased and is similar to men [29, 30, 31]. Risk factors unique to women are use of oral contraceptives, menopause, hormone replacement therapy, gestational hypertension, and diabetes. Obesity and metabolic syndrome are also more prevalent in women [32].
Plasma cholesterol levels and LDL-C levels are similar in both sexes during the infancy and adolescence. LDL levels increase progressively in both men and women after the age of 20, but more rapidly in men. Size of the LDL particles reduces as men age, while it remains stable in women until menopause then becomes smaller [33].
In 1999, American heart association (AHA) developed the first women-specific clinical report regarding recommendations for CVD prevention [34]. In the 2011 AHA update, effectiveness-based guidelines for the prevention of CVD in women recommended lifestyle approaches for LDL-C < 100 mg/dl, HDL-C > 50 mg/dl, triglycerides <150 mg/dl, and non-HDL-C (total cholesterol minus HDL) <130 mg/dl (class I recommendation; level of evidence B). LDL-C-lowering drug therapy with lifestyle therapy in women with coronary heart disease (CHD) to achieve an LDL-C < 100 mg/dl (class I; level of evidence A) and is also indicated in women with other atherosclerotic CHD or diabetes mellitus or 10-year absolute risk 20% (class I; level of evidence B). A reduction to <70 mg/dl is reasonable in very-high-risk women like those with recent acute coronary syndrome (ACS) or multiple cardiovascular risk factors with CHD and may require an LDL-lowering drug combination (class IIa; level of evidence B). In women >60 years of age and with an estimated CHD risk >10%, statins could be considered if hsCRP is >2 mg/dl after lifestyle modification and no acute inflammatory process is present (class IIb; level of evidence B). Niacin or fibrate therapy can be useful when HDL-C is low (<50 mg/dl) or non-HDL-C is elevated (>130 mg/dl) in high-risk women after LDL-C goal is reached (class IIb; level of evidence B) [35].
In 2013 ACC/AHA guidelines added, treatment decisions for women should be based on the level of ASCVD risk. Statin treatment based on estimated 10-year ASCVD risk avoids the overtreatment of lower risk groups, such as younger, non-Hispanic white women who, despite moderate elevations in LDL-C, are typically not at significantly increased risk for ASCVD in the absence of other substantial risk factors [1]. The European Atherosclerosis Society (ESC/EAS) recommends that assessment of CV risk should be gender specific and recommended statin therapy be initiated as primary and secondary prevention for women at high risk [36].
Women have been underrepresented in many primary and secondary prevention trials. In major primary prevention trials, the number of women varied from 15 to 49%. In AFCAPS (15%), HPS (30%), ALLHAT-LLT (49%), and in ASCOT-LLA trial (19%) were women [37, 38]. In a prospective, randomized, open-labeled, blinded Japanese primary prevention trial of patients with hypercholesterolemia, 5547 (68%) were women randomly assigned to diet alone or diet with pravastatin daily. Treatment with a low dose of pravastatin reduced the risk of CHD but subgroup analysis of CHD risk in women was not statistically significant [39]. JUPITER trial participants included 6801 women ≥60 years of age and 11,001 men ≥50 years of age with high-sensitivity C-reactive protein ≥2 mg/L and LDL-C < 130 mg/dl, randomized to rosuvastatin versus placebo. JUPITER demonstrated that for primary prevention, rosuvastatin reduced CVD events in women with a relative risk reduction similar to that in men, a finding supported by meta-analysis of primary prevention statin trials [40].
In major secondary prevention trials, 4S included 827 (19% woman), CARE 576 (14%), LIPID 1516 (17%), TNT 1902 (19%), and SEARCH trial included 2052 (17%) women [41, 42, 43, 44]. Cholesterol lowering with simvastatin produced similar reductions in relative risk for major coronary events in women compared with men. There were too few female deaths to assess the effects on mortality in women [41]. A meta-analysis of 13 large trials for a total of 11,435 women in primary prevention and 8272 in secondary prevention concluded that lipid lowering does not affect CHD mortality in women for primary prevention, but it is effective for secondary prevention [27].
Women are more likely to have poor lipid control. There have been conflicting results regarding gender differences in benefit of statins in women with CVD. However, in a meta-analysis performed on data from 22 trials of statin therapy versus control (n = 134,537) and five trials of more intensive versus less intensive statin therapy, 27% of 174,149 randomized participants were women. In men and women at an equivalent risk of cardiovascular disease, statin therapy was equally effective for the prevention of major vascular events. Kostis et al. performed a meta-analysis consisting of 18 randomized clinical trials of statins with gender-specific outcomes and found statin therapy was associated with significant decreases in cardiovascular events and in all-cause mortality in women and men [45].
There is a gender-specific impact of transporter polymorphisms on statin pharmacokinetics. Estrogen-induced water and sodium retention, increased volume for lipophilic drugs, higher protein-binding globulins, higher CYP3A4 activity, lower body mass index, and lower renal clearance in women may affect absorption of different statins. Women seem to be at greater risk of statin-induced rhabdomyolysis. In a US case-control study of 252,460 users of lipid-lowering therapy, there was trend for increased risk of rhabdomyolysis [46]. In the JUPITER study, the occurrence of serious adverse events was similar in both men and women [40].
Metabolic adaptations during pregnancy are essential to meet the physiological demands of pregnancy as well as development of the fetus. An increase in insulin resistance results in increases in maternal glucose and free fatty acid concentrations, allowing for greater substrate availability for fetal growth. Production of progesterone leads to lipogenesis, lipids are transported across the placenta and metabolized; this signifies the essential role of lipids to normal fetal development [47, 48]. Within 6 weeks of gestation, lipid levels drop slightly followed by rise in both total cholesterol and marked increase in triglycerides (TG). HDL-C levels and apolipoprotein A-I levels also increase during normal gestation, with peak levels during the second trimester. As TG levels rise, there is a decrease in low-density lipoprotein (LDL) size with an increased proportion of atherogenic small-dense LDL. Both cholesterol and triglyceride concentrations decrease significantly within 24 h of delivery. However, while TG levels continued to decrease rapidly returning to nonpregnant levels during the puerperium, LDL-C remained elevated for at least 6–7 weeks postpartum [49, 50]. During pregnancy, lipoprotein Lp(a) levels increase with gestational age and fall to prepregnancy levels within 6 months postpartum [51, 52].
Preeclamptic women exhibit higher mean serum TG levels, elevated LDL-C fractions, increased levels of Lp(a), and lower HDL cholesterol levels compared with healthy pregnant women [49]. Amsterdam Born Children and Their Development (ABCD) cohort study showed that every unit increase in TG was linearly associated with an increased risk of preeclampsia, pregnancy-induced hypertension, and preterm delivery. Total cholesterol was not associated with any of the outcome measures [53]. Women who have higher concentrations of small-dense LDL fractions during pregnancy tend to have increased risk of cardiovascular disease later in life [53, 54].
In the multicenter, prospective Coronary Artery Risk Development in Young Adults study, 1010 women of which 49% identified as black with at least one singleton birth with 20 years of follow-up were evaluated. There was a U-shaped relationship between prepregnancy cholesterol concentrations and preterm birth risk with both low ((<156 mg/dl) and high cholesterol (>195 mg/dl) related to preterm birth risk [55]. Observational and experimental evidence increasingly supports a relation between growth and development during fetal and infant life and health in later years. Additionally, preterm newborns have been found to be at an increased risk of CVD later in life [56].
Pregnant women are generally excluded from clinic trials, thus the data are limited. HMG-CoA reductase inhibitors have been associated with teratogenicity and congenital malformation and are not recommended. Fibrates and nicotinic acid have not been well studied and are not recommended. Omega fatty acids, on the other hand, can be safely used as monotherapy to decrease TG levels.
Patients with CKD and ESRD are at an increased risk of CVD, and are more likely to die because of adverse cardiovascular events [57]. In addition to traditional risk factors like hypertension, diabetes mellitus, dyslipidemia, and a family history of CAD, patients with CKD are plagued by nontraditional risk factors like homocysteinemia, mineral bone disease, carbamylation, and chronic inflammation [58, 59]). As CKD progresses, an unstable vascular environment ensues which threatens endothelial function and lipoprotein integrity and thus potentiating adverse cardiovascular outcomes. Figure 1 shows mechanism of dyslipidemia in this population.
Mechanism of dyslipidemia in chronic kidney disease (CKD), end stage renal disease (ESRD), and human immunodeficiency virus (HIV) patients.
Dyslipidemia in these patients is undoubtedly one of the strongest risk factors for these adverse cardiovascular outcomes. Despite these data, however, CVD remains underdiagnosed and undertreated in patients with CKD. Dyslipidemia has been found to be distinctly different from the general population and variable depending on the stage of CKD [60]. The lipid profile of patients with nondialysis-dependent CKD is usually composed of low HDL-C and high triglycerides with normal to low total cholesterol and low-density lipoprotein cholesterol [61]. In fact, plasma triglycerides start to increase in early stages of CKD and show the highest concentrations in nephrotic syndrome and in dialysis patients, especially those who are treated with peritoneal dialysis [60]. In patients with nondialysis-dependent CKD, the hypertriglyceridemia has been attributed to delayed catabolism and increased hepatic production of triglyceride-rich lipoproteins, and to a smaller extent by the presence of lipase inhibitors [62]. This altered catabolism in turn results in the accumulation of triglyceride-rich lipoproteins, like IDL and small-dense LDL (sdLDL) which are highly atherogenic [63, 64].
Though elevated LDL-C is not a typical feature of these patients, sdLDL, an LDL subtype, is increased and carries the ability to penetrate the vessel wall, becomes oxidized, and triggers the atherosclerotic process. The subfractions of HDL in CKD and ESRD are also different than that of the general population. In uremia [65], LDL and HDL, their subfractions, lipidomes, and proteomes, gradually become more susceptible to structural modifications such as carbamylation, oxidation, glycation, nitration, and homocysteinylation [66, 67]. Most of these effectors are irreversible and amplify the uptake by the scavenger receptors on the surface of macrophages [60]. HDL’s vital components like ApoA-I, PON-1, and LCAT are altered, ultimately attenuating HDL’s cyto- and vascular-protective properties [68] . The reduced PON-1 activity further predisposes LDL and HDL to more oxidation and, in turn, dysfunction and enhanced atherogenic potential [69]. In fact, it has been found that increasing serum HDL-C over time is paradoxically associated with significantly higher all-cause and cardiovascular mortality [70].
Recent studies show that statin therapy can decrease cardiovascular mortality in CKD population. Heart Protection Study and Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT) demonstrated that CKD patients treated with simvastatin exhibited a reduction of cardiovascular morbidity and mortality [71, 13]. Results from the Pravastatin Pooling Project showed similar cardioprotective effects [72]. Atorvastatin and rosuvastatin also reduced the relative risk of cardiovascular events in CKD patients and improved outcomes were found with higher atorvastatin doses [73, 74, 75]. Study of Heart and Renal Protection (SHARP) trial randomized 9270 patients with CKD with no prior history of CAD and found that simvastatin 20 mg plus ezetimibe 10 mg daily safely reduced the incidence of major atherosclerotic events in CKD patients [76].
KDIGO panel provides recommendations for dyslipidemia in patients at all stages of CKD based on a few large, randomized controlled trials and post hoc analyses of the subgroup of CKD patients from statin trials in the general population [76, 77]. In adult CKD patients ≥50 years age, statin therapy alone is recommended for those with GFR ≥ 60 ml/min and statin or statin/ezetimibe therapy is recommended for GFR < 60 ml/min. In adults aged 18–49 years with CKD, statin treatment is recommended in patients with known coronary disease, diabetes mellitus, prior ischemic stroke or estimated 10-year incidence of coronary death or nonfatal myocardial infarction >10%. Neither ACC/AHA nor KDIGO guidelines recommend initiation of statin therapy or combination treatment with statin and ezetimibe in dialysis-dependent patients on the basis of results from the AURORA (A Study to Evaluate the Use of Rosuvastatin in Subjects on Regular Hemodialysis: An Assessment of Survival and Cardiovascular Events) and Deutsche Diabetes Dialyse Studie (4-D) trials. However, patients already on lipid-lowering therapy at the time of progression to dialysis may continue treatment [76, 78, 79, 80].
Novel and innovative therapies are needed to address the multiple lipid/lipoprotein abnormalities that facilitate high cardiovascular risk and mortality in patients with dialysis-dependent CKD.
Risk of cardiovascular events in kidney transplant recipients is markedly elevated as compared to people without CKD. Prevalence of hyperlipidemia ranges from 16 to 78% in kidney transplant recipients. Hypercholesterolemia has peak incidence at 12 months posttransplant and correlates with excessive body weight. After transplantation, increases in total cholesterol, LDL-C, very-low-density lipoprotein (VLDL)-cholesterol, and TG have been noted. In addition, LDL-C may be more susceptible to oxidation, making the particle more atherogenic. HDL-C levels may be normal or even high although the composition of HDL may not be normal [81].
Immunosuppressive agents contribute significantly to hyperlipidemia in renal transplant recipients. Corticosteroids induce insulin resistance. Hyperinsulinemia leads to increased hepatic uptake of free fatty acids (FFA) which constitute the main substrate for VLDL cholesterol synthesis. There is increased conversion of VLDL to LDL cholesterol, leading to a rise in LDL cholesterol levels and downregulation of LDL receptors [81, 82, 83]. Calcineurin inhibitors interfere with binding of LDL-to-LDL receptor leading to increase in LDL-C, interfere with bile acid synthesis and lead to LDL receptor downregulation. Cyclosporine is highly lipophilic. Tacrolimus is associated with less hyperlipidemia [84]. Rapamycin inhibits lipoprotein lipase, associated with decrease in apolipoprotein-B 100 catabolism, and increases secretion of VLDL cholesterol [85]. Other secondary causes include nephrotic syndrome, hypothyroidism, diabetes mellitus, excessive alcohol intake, obesity, chronic liver disease, and genetic predisposition.
Lipid profile evaluation including total cholesterol, LDL, HDL, and triglyceride levels is recommended. Kidney Disease Improving Global Outcomes (KDIGO) suggest treatment with statins in adult kidney transplant recipients [77]. Assessment of Lescol in Renal Transplantation (ALERT) trial is the only multicenter, randomized, double-blind, placebo-controlled trial in renal transplant recipients. In this study, 2102 renal transplant recipients with total cholesterol 4·0–9 mmol/l were randomized to receive fluvastatin (n = 1050) or placebo (n = 1052). After a mean follow-up of 5 years, fluvastatin lowered LDL cholesterol concentrations by 32%. Although cardiac deaths and nonfatal myocardial infarction seemed to be reduced, fluvastatin did not reduce rates of coronary intervention procedures or mortality [86]. Of 1787 patients who completed ALERT, 1652 (92%) were followed in the extension trial with mean follow-up of 6.7 years which showed 29% reduction in cardiac death or definite nonfatal myocardial infarction in the fluvastatin arm [87]. Due to the known interaction of calcineurin inhibitors through CYP3A isoenzyme system, lower doses of statins are generally used as compared to general population. Among fibrates, fenofibrate is less myotoxic than gemfibrozil when combined with statin but fenofibrate should be avoided in advanced CKD. Bile acid sequesterants are not widely used due to gastrointestinal side effects and can also interfere with absorption of immunosuppressants. Ezetimibe is considered safe in renal transplant recipients.
Antiretroviral therapy (ART) has prolonged the survival of HIV-infected individuals, which, in effect, has increased the prevalence of comorbidities, like coronary heart disease. Studies have shown that HIV-infected individuals have higher cardiovascular disease (CVD) risk than uninfected persons in the United States [88, 89, 90]. Paisible et al. reported a 1.5–2-fold increased risk of incident myocardial infarction compared with uninfected subjects [91]. Among HIV patients, women have been found to have higher CVD risk than men [92]. Risk, however, cannot be attributed to HIV alone as traditional CVD risk factors like smoking [93], dyslipidemia, diabetes mellitus, and hypertension [92] have been found to be more common among those infected. Table 1 summarizes the traditional and nontraditional risk factors for cardiovascular disease in special populations.
Traditional | Non-traditional | ||
---|---|---|---|
CKD | HIV | Renal transplant | |
Diabetes mellitus and insulin resistance | Hyperhomocysteinemia | Antiretroviral therapy | Immunosuppressive therapy: Glucocorticoids Calcineurin inhibitor Rapamycin |
Hypertension | Hypercalcemia and hyperphosphatemia | ||
Dyslipidemia | Chronic inflammation and oxidative stress | ||
Obesity and physical inactivity | Anemia of chronic disease | ||
Smoking | Microalbuminuria | ||
Family history of atherosclerosis | Nephrotic syndrome | ||
Age | |||
Gender |
Traditional and nontraditional risk factors for cardiovascular disease in special populations.
CKD, chronic kidney disease; HIV, human immunodeficiency virus.
Their lipid profile is comprised of hypertriglyceridemia, increased sdLDL, and low HDL-C levels [94, 95]. Atheromas have been found to have larger lipid pools with dystrophic calcifications [96]. Consequently, the coronary arteries have a higher burden of coronary plaque and prevalence of detectable calcium [97, 98, 99]. These plaques are rupture-prone and associated with inflammation [100] and monocyte activation [101]. As a result, patients tend to have higher rates of subclinical vascular disease [102, 103]. ART-associated lipodystrophy has been linked with these cardiac and metabolic complications [104]. However, newer ART medications have had less effect on dyslipidemia and related myocardial events [105]. Still, CD4 cell depletion and immune dysfunction perpetuates HIV-related atherosclerosis, irrespective of ART [106]. Silverberg et al. reported that CD4 counts <200 cells/mm3 were significantly associated with increased risk of MI [105]. While viral load and prior ART use were not associated with MI, unsuppressed HIV viremia was associated with MI [89] and stroke [107]. Dyslipidemia and its effects on the cardiovascular system in HIV are dynamic and multimodal. In these states of chronic inflammation, it is difficult to associate quantities of cholesterol types with outcomes. That is, in these special populations, there may not be a “good” or “bad” cholesterol, but rather dysfunctional lipoprotein atherosclerosis.
Studies have shown that statins are safe and beneficial in those infected with HIV; however, the use of statins remains relatively low [89, 108, 109]. Reasons include (1) the low prevalence of elevated LDL-C, (2) their uncertain efficacy for CVD prevention, and (3) the potential to adverse side effects and negative drug-drug interactions [80]. National Lipid Association (NLA) recommends that all HIV-infected patients be first assessed for cardiovascular risk and counseled about lifestyle interventions like diet, exercise, and smoking for the prevention of atherosclerotic cardiovascular disease. In addition, a fasting lipid panel should be obtained in all newly identified HIV-infected patients before and after starting antiretroviral therapy. TG >500 mg/dl that are refractory to lifestyle modification or changes in ART (if an option) should be treated with either a fibrate (fenofibrate preferred) or prescription omega-3 fatty acids to lower TG to <500 mg/dl. Non-HDL-C and LDL-C should be reassessed for appropriate management with statin therapy with caution of drug-drug interactions and side effects. To this end, the NLA Expert Panel recommends clinicians to prescribe pitavastatin as the generally preferred agent in HIV-infected patients [80].
National Health and Nutrition Examination Survey (NHANES) is the primary data source for national prevalence rates of dyslipidemia in the US with data on Whites, black/African Americans, and Hispanics/Latinos but is limited in data on Asian subgroups [110]. NHANES data in 2013 showed that the prevalence rate of high LDL-C was highest among Mexican men (40%) and women (30%), followed by non-Hispanic black men (33%) and women (31%). Non-Hispanic white men (30%) and women (29%) had the lowest prevalence of high LDL-C. The prevalence rates of low HDL were 20% in black men and 10% in black women as compared to prevalence rates among non-Hispanic white men (33%) and women (12%) and Hispanic American men (34%) and women (15%). NHANES data in 2008 reported prevalence of high TG in 35% of Hispanic Americans, 33% among non-Hispanic whites, and 16% among non-Hispanic blacks [111]. American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, and the National Institutes of Health reported prevalence of hyperlipidemia in non-Hispanic black men (32.6%) and non-Hispanic black women (36.1%), Hispanic men (43.1%), Hispanic women (41.2%), non-Hispanic white men (37%) and in women (43.4%) and for non-Hispanic Asians, prevalence was 39.9% in men and 40.5% in women [112]. Data from outpatient cohort of adults 35 years or older from 2008 to 2011 in northern California found that compared with non-Hispanic whites, every minority subgroup had an increased prevalence of high triglycerides except blacks. Most minority groups had an increased prevalence of low HDL-C, except for Japanese and blacks. The prevalence of HDL-C was increased among Asian Indians, Filipinos, Japanese, and Vietnamese compared with non-Hispanic whites [113]. Table 2 shows cholesterol levels in minority populations compared to non-Hispanic Whites in the United States.
Percent of population | Total cholesterol | HDL | LDL | TGs | Lp(a) | ASCVD | |
---|---|---|---|---|---|---|---|
Hispanics | |||||||
Men | 17% | ↑ | ↓ | ↑ | ↑ | ↔ | ↑ |
Women | ↓ | ||||||
African Americans | |||||||
Men | 13% | ↔ | ↑ | ↓ | ↓ | ↑ | ↑ |
Women | ↔ | ↔ | |||||
Asians | 6% | ↑ | ↓ | ↑ | ↑ | – | ↑ |
American Indians/Alaska Natives | 2% | – | ↑ | – | – | – | ↑ |
Cholesterol levels in minority populations compared to non-Hispanic Whites in the United States.
HDL, high-density lipoprotein; LDL, low-density lipoprotein; Lp(a), lipoprotein (a), ASCVD, atherosclerotic cardiovascular disease.
The Study of Health Assessment and Risk in Ethnic groups (SHARE), a prospective Canadian trial, showed that South Asians including Asian Indians had an increased prevalence of total cholesterol, high LDL-C, low HDL-C, and high TG compared to European and Chinese cohort [114]. The Multi-Ethnic Study of Atherosclerosis (MESA), a multicenter cohort study of 6814 adults aged 45 to 84 years who were free of clinical CVD at baseline were evaluated for CVD risk and self-reported use of lipid-lowering therapy. Black and Hispanic Americans had prevalence of dyslipidemia that was comparable to that of non-Hispanic whites but were less likely to be treated and controlled. Ethnic disparities were attenuated substantially by adjustment for health-care access variables [115]. Data from the Hispanic Community Health Study (HCHS)/Study of Latinos (SOL), an observational study, showed high prevalence of dyslipidemia among Central American men and Puerto Rican women [116].
In the US, cardiovascular mortality rates are highest in blacks as compared to Hispanics [117]. An early study of CHD among Japanese migrants compared with Japanese living in Japan showed higher rates of CAD in Japanese immigrants in America [118]. In a study of immigrant Asian Indian men in US, Enas et al. reported high prevalence of CAD, low HDL-C levels, and hypertriglyceridemia. Authors suggested “insulin resistance” as a common pathogenetic mechanism [119]. Increased risk of CAD in south Asian community was seen in data from other studies as well [114, 120, 121].
The 2013 ACC-AHA guidelines for the treatment of cholesterol expand the indications for statin therapy for the prevention of CVD. Ten-year ASCVD risk assessment calculator has been added to determine statin use [122]. ASCVD risk calculator is derived from cohorts that included African-American or white participants with at least 12 years of follow-up. Data from other racial/ethnic groups were insufficient, precluding their inclusion in the final analyses. The equations were also assessed in external validation studies with data from other available cohorts [123]. For other ethnic groups, ACC/AHA recommends use of the equations for non-Hispanic whites, though it acknowledges that estimates may underestimate the risk for American Indians, some Asian Americans (e.g., of south Asian ancestry), and some Hispanics (e.g., Puerto Ricans), and may overestimate the risk for others, including some Asian Americans (e.g., of east Asian ancestry) and some Hispanics (e.g., Mexican Americans) [124].
There are several genetic variants associated with altered statin metabolism. Single-nucleotide polymorphisms in the genes that encode the organic anion-transporting polypeptide (OATP) 1B1 (521 T > C), which regulates hepatic uptake of statins, and the adenosine triphosphate-binding cassette G2 (ABCG2) transporter (421C > A), which regulates hepatic efflux, have been reported [125, 126, 127]. Plasma exposure to rosuvastatin and its metabolites was significantly higher in Chinese, Malay, and Asian-Indian subjects compared with white subjects living in Singapore [128]. Rosuvastatin, a HMG-CoA reductase inhibitor, is excreted into bile mediated by breast cancer resistance protein (BCRP). BCRP 421C > A polymorphism may play an important role in the pharmacokinetics of rosuvastatin in healthy Chinese males [129]. In a Japanese study, single-nucleotide polymorphisms in OATP-C, such as T521C (Val174Ala), has been reported to be associated with altered pharmacokinetics of pravastatin [125]. In a US-based study cohort of 69 European-Americans and 38 African-Americans, SLCO1B1 genotype, in particular, the 521C allele, had a significant effect on the pharmacokinetics of pravastatin. European-Americans demonstrated significantly higher pravastatin levels as compared to African-Americans [130]. There is less information on statin metabolism in other racial/ethnic minority groups. In a randomized placebo-controlled trial of 25,673 patients, the absolute risk of myopathy with adding niacin-laropiprant to statin-based LDL cholesterol-lowering therapy was more than 10 times as great among Chinese as compared to their European counterparts [131]. The relative risk of myopathy with niacin-laropiprant versus placebo was also higher in Chinese patients [132].
Lifestyle risk factors include unhealthy diet, obesity, and physical inactivity. Racial/ethnic disparities also exist in these lifestyle risk factors. According to the National Health Interview Survey (NHIS) 2008–2010, Asian adults were less likely to be current smokers or to be obese. Black adults were more likely to be physically inactive, to be obese, and to get insufficient sleep. Hispanics were less likely than non-Hispanic adults to smoke cigarettes, get insufficient sleep, but were more likely to be inactive in terms of aerobic and muscle-strengthening leisure time. Immigration and acculturation have a profound impact on lifestyle in both Hispanics and Asians in the US [133]. Asian Indian, Filipino, Vietnamese women, and Asian Indian men have increased risk dyslipidemias as compared to non-Hispanic whites. Further research is needed to determine the role of dyslipidemia subtypes and other risk factors in explaining the higher risk of CVD in minority subgroups. By understanding these differences, clinicians will be able to provide more culturally competent recommendations on prevention and management of dyslipidemia.
In conclusion, differences in dyslipidemia patterns, risk factors, and management exist in the elderly, women and pregnancy, CKD, ESRD, HIV, and different racial ethnic groups. Nevertheless, they are frequently underrepresented in clinical trials, which calls for more inclusive research that will develop stronger recommendations of daily practice.
Calculation of turbulent flows is one of the most challenging problems in all of science and mathematics. Exact solutions of turbulence have bedeviled researchers for many decades and it is generally appreciated that there is no closed form solution of any fluid flow problem except the most simple laminar situations. Despite this fact, there are ways to complete calculations with sufficient accuracy so that engineering and design decisions can be made. The accuracy of turbulent calculations has gradually improved with more powerful computational resources and with improvements to numerical modeling. Here we discuss the most commonly used methods to simulate turbulent flow and discuss the strengths and weaknesses of each approach. The authors believe that particular methods are more or less appropriate for a particular situation, depending on the characteristics of the system, the computational resources available and the accuracy requirements. In this chapter, we pay particular attention to turbulence models that are most commonly used by scientists and researchers; we also provide guidance to researchers who are pondering different turbulent-modeling approaches.
The first problems handled by CFD were relatively simple, two-dimensional, incompressible, steady state situations that often were limited to laminar flows. To our best knowledge, the first three-dimensional CFD simulation was not completed until 1967 [1]. Around the same time, the very first climate models were being constructed, for modeling the circulation of fluids around the globe. Shortly thereafter, progress became much more rapid as both computational power and modeling approaches advanced. A key development was the incorporation of turbulence modeling into the CFD solutions. The first turbulence models accounted for turbulence effects through a concept termed the “eddy viscosity”. Essentially, the eddy viscosity (or turbulent viscosity) reflects an apparent increase in viscosity caused by small-scale chaotic motions in a fluid. The simulations do not attempt to actually capture small scale turbulent motions, rather they approximate their effect with an increase in the fluid viscosity. As we will discuss, the concept of turbulence viscosity plays a central role in Reynolds Averaged Navier Stokes (RANS) models. As we will also show, other approaches do not rely extensively on the turbulent viscosity concept.
The first turbulent viscosity “eddy viscosity” models were developed in the 1960s and are classified as algebraic [2, 3], one-Equation [4], or two-Equation [5, 6, 7]. The basis for two equation models was the relationship between the turbulent viscosity and local values of the turbulent kinetic energy k and turbulent dissipation, ε. Since this approach soon became the dominant method (even for today), it is worthwhile to discuss it in some detail. In essence, this group of turbulence models neglect small scale and rapid turbulent motions and use an average flow field (timewise average values in the velocities and pressure values) to estimate the effects of turbulence.
The first major effort to simulate turbulence in the context of CFD was the so-called k-ε model [5, 6]. This approach utilizes the fluctuating components of the turbulent velocity in the three coordinate directions to obtain a turbulent kinetic energy, from:
That is, k is the additional turbulent energy that results from the time-fluctuating turbulent motions. Accompanying the turbulent kinetic energy is a turbulent dissipation ε which can be calculated as
for flows in pipes with diameter D [7, 8]. The connection of turbulence kinetic energy and turbulent dissipation will be provided, following the equations of motion. In essence, the governing equations of motion are conservation of mass, which under steady conditions is:
conservation of momentum, written as:
and the closure equations for turbulence:
The turbulent viscosity is calculated from
The Pk is the production of turbulent kinetic energy from the shear strain rate and Pb is the production of turbulent kinetic energy from buoyancy effects. The production of turbulent kinetic energy is obtained from the time-averaged velocity field from:
The σ terms are corresponding Prandtl numbers for the transported variables. The values of the constants and turbulent Prandtl numbers are specific to a particular k-ε model. The k-ε approach is likely the most widely used turbulent model, even today. It is generally sufficient for flows that are wall bounded, with limited adverse pressure gradients or separation.
Traditionally, the elements are not used to capture steep velocity and temperature gradients near the wall. Rather, wall functions are employed to interpolate to the wall. Of course, the accuracy of this approach depends on the suitability of a particular wall function to a problem. For example, wall functions often fail when the flow experiences adverse pressure gradients and/or separation. On the other hand, when small elements are deployed near the wall and/or when damping equations are used to limit fluid motion in the boundary layer, integration can be performed up to the wall. In our experience, if integration is to be performed up to the wall (and wall function interpolation is avoided), the near-wall element should have a size of y+∼1 for models that resolve the boundary layer. This guidance is not used for models that use the law-of-the-wall to interpolate to the wall.
A popular modification of the traditional k-ε model is the RNG (Renormalization Group) model. It was developed by [9] in an effort to handle small flow phenomenon. The mechanism of multiple scale motions is achieved by modifying the turbulent dissipation equation production term. In our experience, it has somewhat better performance than the standard k-ε particularly for rotating flows. The differences between the RNG and standard models is in the relationship between the turbulent kinetic energy, turbulent dissipation, and turbulent viscosity. With the RNG approach the turbulent viscosity is found from:
and the new turbulent dissipation transport equation becomes:
With the following inputs
While the k-ε model has experienced success in computational modeling, it has deficiencies in some situations. In particular, the k-ε model performs suitably away from walls, in the main flow. However, it has issues in the boundary layer zone, particularly with low Reynolds numbers. Here, Reynolds numbers refer to local Reynolds numbers that decrease as one moves closer to the wall and the no-slip condition exerts its influence (rather than to the Reynolds number based on macroscopic dimensions such a pipe diameter or plate length).
A significant development in CFD was brought forward by the development of k-ω model that replaced the transport equation for ε with a specific rate of turbulence dissipation, ω [10]. The new equations are:
With a turbulent viscosity calculated as:
Recognizing that the k-ε and k-ω model each have strengths and weaknesses, a new model was proposed that uses both of these approaches in a way that harnesses their strengths [11]. This new approach, termed the Shear Stress Transport model (SST), smoothly transitions from the k-ω model near the wall to the k-ε model in the main flow. With the SST model, the governing equation for turbulent dissipation is recast into an ω form. The governing equations are:
and the turbulent viscosity is found from
As before, Pk is the production of turbulent kinetic energy and ω reflects the specific rate of turbulent destruction. As noted earlier, the σ terms are turbulent Prandtl numbers associated with their subscript. The function F1 is the aforementioned blending function that transfers the k-ω model near the wall to the k-ε model away from the wall from the wall. The S term is the magnitude of the shear strain rate.
While ostensibly, the SST model is used for fully turbulent flows, it has shown ability to capture both laminar and turbulent flow regimes [12]. However, in the next section we discuss a set of modifications to the SST models that are specifically designed to handled laminar/transitional/turbulent flow regimes that are recommended.
The already discussed turbulent models were largely developed based on correlations of canonical fully turbulent flow situations (such as flows over flat plates, airfoils, Falkner-Skans flows, and flows in tubes and ducts). Of course, researchers and engineers often experience situations where the flow is partially turbulent or other situations where the flow changes so that for part of the time it is laminar and other times turbulent. Consider for example pulsatile flow wherein the fluid velocity changes sufficiently so that for parts of the flow period, different flow regimes occur. There are a number of approaches to handle these situations but with respect to the RANS models, the approaches generally utilize the concept of turbulent intermittency. Intermittency was originally defined as the percentage of time that a flow was turbulent. However, more recently, turbulent intermittency has been used as a multiplier on the rate of turbulent kinetic production [13, 14, 15].
Here we will set forth two current transitional models, both based on the SST turbulence approach. The first method involves two extra transport equations. One for the intermittency, γ, which is a multiplier to the turbulent production. The transport equation for turbulent intermittency is:
The P and E terms are, respectively, production and dissipation of intermittency. An additional transport equation is required for the transitional momentum thickness Reynolds number. This added equation is:
Together, solution to Eqs. (19) and (20) determine the local state of turbulence. They result in an intermittency that takes values between 0 and 1. For fully laminar flow, γ = 0 and the model reverts to a laminar solver. When γ = 1, the flow is fully turbulent. The turbulent production then is then multiplied by the local value of the intermittency, γ. Interested readers are invited to review the development of this model, including implementation for problems that involve heat transfer [16, 17, 18, 19, 20, 21, 22].
Recently, the above two-equation model was modified to reduce the two transitional transport equations to a single Equation [23] and that approach was later adapted by [24] to accurately solve for situations in confined pipe/duct/tube flows. Essentially, Eqs. (19) and (20) are replaced by a single intermittency equation which is:
As with the two-equation approach, the intermittency factor γ will take on values between 0 and 1. Also, as before, The P and E terms represent, respectively, the production and destruction in local value of intermittency.
For these intermittency models, the onset of turbulence is calculated by a series of correlation functions. In particular, a local value of the critical Reynolds number is determined from
Eq. (22) is used to identify the location of laminar-turbulent transition. It is based on the local value of the momentum layer thickness. The C terms are correlation constants and are based on comparison of numerically simulated results with experimentation. An important term in Eq. (22) is the local value of the mid-boundary-layer turbulence intensity (TuL). This value is attained at the midpoint of the boundary layer as an output from an empirical formulation based on experimentation.
Local production of intermittency is calculated from:
As we have already noted, the term S is the shear strain rate. A new term that appears in Eq. (23) is the so-called onset transition term (Fonset) which is calculated using the following set of equations.
Similarly, the local rate of destruction of intermittency is found by:
We have already noted that these transitional turbulence models were initially developed for external boundary layer flows (flat plate boundary layers, airfoil flows, Falkner-Skans flows, etc.). Insofar as we have adopted them for internal flow, some modification was required. We recommend, at least for flows through pipes, tubes, and ducts, that the initial constants determined in [23] be replaced by alternative values from [24].
While we recommend the above approach for solving transitional flow problems, this area of research is also heavily studied by other researchers who have provided alternative approaches to handle such flows. We cite them here for readers who are interested in those alternative but complementary viewpoints [25, 26, 27, 28, 29, 30, 31, 32, 33].
Reynolds stress models (RSM) are quite different from the RANS approach that was just discussed. For RSMs, transport equations are used for all components of the Reynolds stress tensor and an eddy viscosity is not utilized. These models are expected to be superior for situations with non-isotropic turbulence and flows with significant components of transport in three directions. There are a number of RSM versions, some of which will be discussed here. The so-called SSG-RSM model employed here utilizes the following momentum transport equation:
The second-to-last term on the right-hand side represents the Reynolds stresses. There is a pseudo-pressure term p’ that is calculated from the local static pressure p and local velocity gradient from the following expression.
The Reynolds stresses are calculated by a collection of six equations for all directional possibilities. The transport equations for Reynolds stresses are:
We note that a turbulence dissipation term, ε, appears in Eq. (32) and it has to be solved from its own transport equation. We refer readers to [34, 35] for more details.
A modification to the above is realized from the Baseline RSM (BSL RSM) model. It differs from the SSG RSM in that the transport equation for ε is replaced by a transport equation for ω. The new equation is:
This approach blends between two different models that are used near the wall and alternatively away from the wall. The modeling is accomplished using a weighting function, similar to the SST:
Where the symbols ϕ correspond to any particular transport variable in the near wall and far wall regions. Various constants change their values in the two regions, so that:
The constants near the wall:
The constants away from the wall:
The last RSM version to be discussed is the Explicit Algebraic RSM (EARSM). This approach includes a non-linear relationship between the local values of the Reynolds stresses and the vorticity tensors. It is focused on flows with secondary motions and curvature [36]. The local values of the Reynolds stresses are calculated using an anisotropy tensor which is based on algebraic equations [36]. This is contrasted with RSM approaches that solve for the Reynolds stress components using differential transport equations. The approach is to use higher order terms for many of the flow phenomena. It was designed to handle secondary flow situations and flows with extensive curvature and rotation. The governing equations are complex and lengthy and for brevity sake, we refer interested readers to [36].
So far, we have presented RANS-based models that perform conservation calculations at each grid element. If turbulence is present, the impact of turbulence appears via the eddy viscosity. Traditionally users either
Regardless of the method that is selected, the coupled equations are solved for each computational element and the turbulent viscosity is applied to the fluid in the element under consideration.
In contrast to this approach, there is another major group of computational techniques that are termed “scale adaptive models”. These are models that resolve part of the turbulent motions but model flow features that are smaller than the element size. Since there is less modeling and more actual resolution of fluid motion, one might expect the scale-adaptive models to be more accurate than RANS; and there are cases where that is so (particularly for free shear flows, swirling flows, boundary layer separation, and jets). However, the RANS approach can be more accurate than scale-adaptive methods in some situations, including wall bounded flows. Also, RANS is less computationally expensive because the eddy viscosity provides the link to the time-averaged flow field and the local turbulence with a very simple calculation. In fact, for even problems of modest complexity, scale adaptive models are more time consuming.
There are a number of established and new Scale-Adaptive Models that are used in CFD simulations. We will not be exhaustive in this section by covering all the existing models, rather we will focus on some of the models we think are most useful and representative. Interested readers are directed to an excellent comprehensive discussion provided by [34, 37].
One of the primary decisions that models are faced with is whether to perform calculations in steady or unsteady mode. Typically with numerical simulation, unsteadiness is driven by either timewise changes in boundary conditions or it is related to unsteady phenomena that occur in an otherwise steady scenario. A classic example is the Karmen Vortex Street that occurs in a wake region of a blunt object. Figure 1, shown below, illustrates this phenomenon.
Unsteady wake region, even though oncoming flow is steady state.
Researchers have often conjectured that if a RANS model is performed with sufficiently small elements and time steps, the unsteady features of the flow would naturally be resolved. But in fact, this is not true. It is important to note that steady state calculations using RANS models will often provide very accurate information about averaged quantities (like drag), these simulations will miss details in the rapidly fluctuating downstream wake region. This issue was explored in depth in [35] where time-averaged results of drag obtained from unsteady RANS simulations were compared with calculations from steady RANS calculations (using the SST transitional model that was previously described). It was found that the steady state calculations were able to accurately capture drag forces but were only partially adept at capturing vortex movement in the downstream wake region.
With this discussion as background, it is now time to turn attention to the governing equations of scale-adaptive RANS models. The model to be discussed here uses the SST approach for the underlying governing equations (in the literature it is often termed the SAS-SST model). The scale-adaptive approach modifies the ω transport equation based on [37]. In particular, a new transport equation is presented that incorporates the turbulent length scale L and is set forth here:
and
Values of the various constants can be found in [34, 37] and are not repeated here for brevity. The term Lt is a novel modification; it refers to the von Karmen length scale. Figures 2 and 3 are provided that show a comparison of downstream wake regions for an unsteady RANS calculation using the SST model (Figure 2) and a simulation using the scale-adaptive SST modification. Results are obtained from [34]. It can be seen that the standard SST model does capture a periodic release of eddies from the downstream side of a circular cylinder (shown in blue). In both images, the flow is left-to-right. The color legend is keyed to the local values of the turbulent length scale. Clearly the scale-adaptive approach provides a much wider range of turbulent eddy sizes.
Calculations of turbulent length scale for flow over a circular cylinder, based on an unsteady SST model.
Calculations of turbulent length scale for flow over a circular cylinder, based on a scale-adaptive unsteady SST model.
Another common approach to dealing with these types of problems is based on the so-called “large eddy simulation”. To the best knowledge of the authors, the first articulation of a LES model was [38] and the models have been updated in the intervening decades. Here we focus on one popular and current LES method (the Wall-Adaptive Local Eddy, or WALE LES model). The general processes of LES modeling are the same, regardless of which variant is used. LES models involve the filtering of eddies that are smaller than the size of the computational elements. The algorithm incorporates an eddy viscosity for flow scales that are not resolved.
For this model, the tensor-form of the Navier Stokes equations is:
where
And the
The term Cw is a constant and the symbol ∆ = (element volume)1/3. The tensor Sijd is calculated from the strain-rate and vorticity tensors, as shown here
And the vorticity tensor
Now that the main CFD models have been presented, we turn attention to comparisons of the results from different models. There are comparisons available in [7, 8, 34, 35, 37, 39, 40, 41, 42, 43, 44, 45, 46] and a very small subset of those comparisons will be provided here. We have selected the classic problem of flow over a square blockage. This canonical problem has the features that elucidate the strengths and weaknesses of the particular models. For instance, some important parameters relate to the time-averaged interactions between the fluid and the solid structure (drag force). Also, there are significant unsteady phenomena, particularly in the wake region that provide a challenging test for the models. In addition, this is a problem with extensive experimental work that will serve as the basis for evaluating the results. To begin we refer to Figure 4 which shows the solution domain (similar to [35]).
Geometry for flow over a square cylinder.
A number of computational meshes were used and an example mesh is shown in Figure 5. The images are provided in a series of increasing magnification. Image (a) is the most global view, part (b) is focused on the square obstruction, and image (c) reveals details of the elements in the near-wall region, near a corner of the cylinder.
Computational mesh used for square cylinder simulation.
With this mesh, we present results for a large number of computational methods. We note here that in reality appropriate meshes may differ depending on the turbulence model that is used. For instance, a mesh that is suitable for a k-w simulation may not be appropriate for SST, and vice versa. We recommend that mesh independent studies be carried out for each turbulence mode that is employed. The results, set forth in Figures 6 and 7, provide the drag coefficient on the square cylinder (large aspect ratio). Each model has its own color. Literature-based values from experiments are also included (shown as gray x symbols).
Drag coefficients for flow over a square cylinder and comparison with experiments. Reynolds numbers range from 1 to 10,000,000.
Drag coefficients for flow over a square cylinder and comparison with experiments, Reynolds numbers ranging between 10 and 10,000.
In the above calculations, which were first set forth in [35], the SST and transitional-SST models were most accurate (when compared with existing experiments) for calculating the drag coefficient. On the other hand, since these approaches were RANS, they lose some local detail and flow structure. For example, in Figure 8 which is provided below, we show velocity vectors, overlaid atop a velocity contour image. It is evident from the upper part of the figure that there are the expected stagnation locations at the leading edge, and in the wake region. There is also a slow-moving recirculation zone above and below the cylinder that are a result of flow separation at the leading corners. However, the lower images show a focus on the flow patterns at the leading edge. It is seen that with the SST RANS model, there are no small-scale eddies at this location. But for the LES model, there are two LES results that are obtained at two different instances in time. These sequential images show the time-varying flow field. While a RANS model like the SST is excellent for full-body drag, it does not capture some small flow structures. Researchers thus need to consider their computational needs before selecting a CFD model.
(upper image) velocity contour and vectors for SST model and (lower image) side-by-side comparison of leading-edge flow for SST and WALE LES models.
The last result to be presented is shown in Figure 9. There, instantaneous results are displayed for the SST model. There, clearly, the unsteady nature of flow in the downstream wake region are evident. If the simulation of Figure 9 was carried out with a steady state SST solver, there would still be timewise changes in the flow field but they would have a different frequency than the unsteady calculations.
Streamline patterns and velocity contours for Re = 100,000 flow over a square cylinder. Images at a sequence of time instances, using SST model.
In order to elucidate the iteration-by-iteration fluctuations in drag that result from a steady state solver (compared to an unsteady simulation), Figure 10 is prepared. This figure shows the timewise (iteration wise) fluctuations in drag force on the square cylinder first with a steady state SST solution and then with a truly unsteady solution. The steady state results are calculated using a “false transient” approach wherein the algorithm steps forward to new iterations using a non-physical time. The figure has two call outs that provide focus on different parts of the graph. The important conclusion is that the average value of unsteady fluctuations of drag obtained by the steady state algorithm are an excellent match that that attained from the unsteady calculations. On the other hand, the period is very different between the two.
SST solution that began as steady state and then was changed to unsteady.
This chapter has presented a brief overview of a large number of turbulence models. While there is no “correct” turbulence model, there are models that are better suited for particular situations.
For flows that are truly laminar with no regions of intermittency or turbulence, a laminar solver can be used. However, if there is a potential for any turbulent flow, caution is warranted. For flows that are fully turbulent, particularly wall bounded flows, the SST model is recommended. In our experience it is more able to capture flow phenomena compared to other RANS models. It also has excellent performance for a wide range of thermal-transport situations.
If regions of mixed flows (laminar/transitional/turbulent) are expected, of if the flows might change in time (pulsatile flows for example), the SST transitional model is recommended. This new approach is rapidly becoming more common in the CFD community and could replace fully turbulent models in the future.
For situations where small scale and short-lived flow must be captured, we recommend the scale-adaptive SST model or the LES model. They are more computationally expensive but the scale adaption enables small features to be calculated. We also direct readers to two further excellent resources [47, 48] for more in depth discussion.
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Radiotherapy and Nuclear Medicine Technology has always been my aspiration and my life. As years passed I accumulated a tremendous amount of skills and knowledge in Radiotherapy and Nuclear Medicine, Conventional Radiology, Radiation Protection, Bioinformatics Technology, PACS, Image processing, clinically and lecturing that will enable me to provide a valuable service to the community as a Researcher and Consultant in this field. My method of translating this into day to day in clinical practice is non-exhaustible and my habit of exchanging knowledge and expertise with others in those fields is the code and secret of success.",institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"313277",title:"Dr.",name:"Bartłomiej",middleName:null,surname:"Płaczek",slug:"bartlomiej-placzek",fullName:"Bartłomiej Płaczek",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/313277/images/system/313277.jpg",biography:"Bartłomiej Płaczek, MSc (2002), Ph.D. (2005), Habilitation (2016), is a professor at the University of Silesia, Institute of Computer Science, Poland, and an expert from the National Centre for Research and Development. His research interests include sensor networks, smart sensors, intelligent systems, and image processing with applications in healthcare and medicine. He is the author or co-author of more than seventy papers in peer-reviewed journals and conferences as well as the co-author of several books. He serves as a reviewer for many scientific journals, international conferences, and research foundations. Since 2010, Dr. Placzek has been a reviewer of grants and projects (including EU projects) in the field of information technologies.",institutionString:"University of Silesia",institution:{name:"University of Silesia",country:{name:"Poland"}}},{id:"35000",title:"Prof.",name:"Ulrich H.P",middleName:"H.P.",surname:"Fischer",slug:"ulrich-h.p-fischer",fullName:"Ulrich H.P Fischer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/35000/images/3052_n.jpg",biography:"Academic and Professional Background\nUlrich H. P. has Diploma and PhD degrees in Physics from the Free University Berlin, Germany. He has been working on research positions in the Heinrich-Hertz-Institute in Germany. Several international research projects has been performed with European partners from France, Netherlands, Norway and the UK. He is currently Professor of Communications Systems at the Harz University of Applied Sciences, Germany.\n\nPublications and Publishing\nHe has edited one book, a special interest book about ‘Optoelectronic Packaging’ (VDE, Berlin, Germany), and has published over 100 papers and is owner of several international patents for WDM over POF key elements.\n\nKey Research and Consulting Interests\nUlrich’s research activity has always been related to Spectroscopy and Optical Communications Technology. Specific current interests include the validation of complex instruments, and the application of VR technology to the development and testing of measurement systems. He has been reviewer for several publications of the Optical Society of America\\'s including Photonics Technology Letters and Applied Optics.\n\nPersonal Interests\nThese include motor cycling in a very relaxed manner and performing martial arts.",institutionString:null,institution:{name:"Charité",country:{name:"Germany"}}},{id:"341622",title:"Ph.D.",name:"Eduardo",middleName:null,surname:"Rojas Alvarez",slug:"eduardo-rojas-alvarez",fullName:"Eduardo Rojas Alvarez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/341622/images/15892_n.jpg",biography:null,institutionString:null,institution:{name:"University of Cuenca",country:{name:"Ecuador"}}},{id:"215610",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sarfraz",slug:"muhammad-sarfraz",fullName:"Muhammad Sarfraz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/215610/images/system/215610.jpeg",biography:"Muhammad Sarfraz is a professor in the Department of Information Science, Kuwait University, Kuwait. His research interests include optimization, computer graphics, computer vision, image processing, machine learning, pattern recognition, soft computing, data science, and intelligent systems. Prof. Sarfraz has been a keynote/invited speaker at various platforms around the globe. He has advised/supervised more than 110 students for their MSc and Ph.D. theses. He has published more than 400 publications as books, journal articles, and conference papers. He has authored and/or edited around seventy books. Prof. Sarfraz is a member of various professional societies. He is a chair and member of international advisory committees and organizing committees of numerous international conferences. He is also an editor and editor in chief for various international journals.",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"32650",title:"Prof.",name:"Lukas",middleName:"Willem",surname:"Snyman",slug:"lukas-snyman",fullName:"Lukas Snyman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/32650/images/4136_n.jpg",biography:"Lukas Willem Snyman received his basic education at primary and high schools in South Africa, Eastern Cape. He enrolled at today's Nelson Metropolitan University and graduated from this university with a BSc in Physics and Mathematics, B.Sc Honors in Physics, MSc in Semiconductor Physics, and a Ph.D. in Semiconductor Physics in 1987. After his studies, he chose an academic career and devoted his energy to the teaching of physics to first, second, and third-year students. After positions as a lecturer at the University of Port Elizabeth, he accepted a position as Associate Professor at the University of Pretoria, South Africa.\r\n\r\nIn 1992, he motivates the concept of 'television and computer-based education” as means to reach large student numbers with only the best of teaching expertise and publishes an article on the concept in the SA Journal of Higher Education of 1993 (and later in 2003). The University of Pretoria subsequently approved a series of test projects on the concept with outreach to Mamelodi and Eerste Rust in 1993. In 1994, the University established a 'Unit for Telematic Education ' as a support section for multiple faculties at the University of Pretoria. In subsequent years, the concept of 'telematic education” subsequently becomes well established in academic circles in South Africa, grew in popularity, and is adopted by many universities and colleges throughout South Africa as a medium of enhancing education and training, as a method to reaching out to far out communities, and as a means to enhance study from the home environment.\r\n\r\nProfessor Snyman in subsequent years pursued research in semiconductor physics, semiconductor devices, microelectronics, and optoelectronics.\r\n\r\nIn 2000 he joined the TUT as a full professor. Here served for a period as head of the Department of Electronic Engineering. Here he makes contributions to solar energy development, microwave and optoelectronic device development, silicon photonics, as well as contributions to new mobile telecommunication systems and network planning in SA.\r\n\r\nCurrently, he teaches electronics and telecommunications at the TUT to audiences ranging from first-year students to Ph.D. level.\r\n\r\nFor his research in the field of 'Silicon Photonics” since 1990, he has published (as author and co-author) about thirty internationally reviewed articles in scientific journals, contributed to more than forty international conferences, about 25 South African provisional patents (as inventor and co-inventor), 8 PCT international patent applications until now. Of these, two USA patents applications, two European Patents, two Korean patents, and ten SA patents have been granted. A further 4 USA patents, 5 European patents, 3 Korean patents, 3 Chinese patents, and 3 Japanese patents are currently under consideration.\r\n\r\nRecently he has also published an extensive scholarly chapter in an internet open access book on 'Integrating Microphotonic Systems and MOEMS into standard Silicon CMOS Integrated circuitry”.\r\n\r\nFurthermore, Professor Snyman recently steered a new initiative at the TUT by introducing a 'Laboratory for Innovative Electronic Systems ' at the Department of Electrical Engineering. The model of this laboratory or center is to primarily combine outputs as achieved by high-level research with lower-level system development and entrepreneurship in a technical university environment. Students are allocated to projects at different levels with PhDs and Master students allocated to the generation of new knowledge and new technologies, while students at the diploma and Baccalaureus level are allocated to electronic systems development with a direct and a near application for application in industry or the commercial and public sectors in South Africa.\r\n\r\nProfessor Snyman received the WIRSAM Award of 1983 and the WIRSAM Award in 1985 in South Africa for best research papers by a young scientist at two international conferences on electron microscopy in South Africa. He subsequently received the SA Microelectronics Award for the best dissertation emanating from studies executed at a South African university in the field of Physics and Microelectronics in South Africa in 1987. In October of 2011, Professor Snyman received the prestigious Institutional Award for 'Innovator of the Year” for 2010 at the Tshwane University of Technology, South Africa. This award was based on the number of patents recognized and granted by local and international institutions as well as for his contributions concerning innovation at the TUT.",institutionString:null,institution:{name:"University of South Africa",country:{name:"South Africa"}}},{id:"317279",title:"Mr.",name:"Ali",middleName:"Usama",surname:"Syed",slug:"ali-syed",fullName:"Ali Syed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/317279/images/16024_n.png",biography:"A creative, talented, and innovative young professional who is dedicated, well organized, and capable research fellow with two years of experience in graduate-level research, published in engineering journals and book, with related expertise in Bio-robotics, equally passionate about the aesthetics of the mechanical and electronic system, obtained expertise in the use of MS Office, MATLAB, SolidWorks, LabVIEW, Proteus, Fusion 360, having a grasp on python, C++ and assembly language, possess proven ability in acquiring research grants, previous appointments with social and educational societies with experience in administration, current affiliations with IEEE and Web of Science, a confident presenter at conferences and teacher in classrooms, able to explain complex information to audiences of all levels.",institutionString:null,institution:{name:"Air University",country:{name:"Pakistan"}}},{id:"75526",title:"Ph.D.",name:"Zihni Onur",middleName:null,surname:"Uygun",slug:"zihni-onur-uygun",fullName:"Zihni Onur Uygun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/75526/images/12_n.jpg",biography:"My undergraduate education and my Master of Science educations at Ege University and at Çanakkale Onsekiz Mart University have given me a firm foundation in Biochemistry, Analytical Chemistry, Biosensors, Bioelectronics, Physical Chemistry and Medicine. After obtaining my degree as a MSc in analytical chemistry, I started working as a research assistant in Ege University Medical Faculty in 2014. In parallel, I enrolled to the MSc program at the Department of Medical Biochemistry at Ege University to gain deeper knowledge on medical and biochemical sciences as well as clinical chemistry in 2014. In my PhD I deeply researched on biosensors and bioelectronics and finished in 2020. Now I have eleven SCI-Expanded Index published papers, 6 international book chapters, referee assignments for different SCIE journals, one international patent pending, several international awards, projects and bursaries. In parallel to my research assistant position at Ege University Medical Faculty, Department of Medical Biochemistry, in April 2016, I also founded a Start-Up Company (Denosens Biotechnology LTD) by the support of The Scientific and Technological Research Council of Turkey. Currently, I am also working as a CEO in Denosens Biotechnology. The main purposes of the company, which carries out R&D as a research center, are to develop new generation biosensors and sensors for both point-of-care diagnostics; such as glucose, lactate, cholesterol and cancer biomarker detections. My specific experimental and instrumental skills are Biochemistry, Biosensor, Analytical Chemistry, Electrochemistry, Mobile phone based point-of-care diagnostic device, POCTs and Patient interface designs, HPLC, Tandem Mass Spectrometry, Spectrophotometry, ELISA.",institutionString:null,institution:{name:"Ege University",country:{name:"Turkey"}}},{id:"246502",title:"Dr.",name:"Jaya T.",middleName:"T",surname:"Varkey",slug:"jaya-t.-varkey",fullName:"Jaya T. Varkey",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/246502/images/11160_n.jpg",biography:"Jaya T. Varkey, PhD, graduated with a degree in Chemistry from Cochin University of Science and Technology, Kerala, India. She obtained a PhD in Chemistry from the School of Chemical Sciences, Mahatma Gandhi University, Kerala, India, and completed a post-doctoral fellowship at the University of Minnesota, USA. She is a research guide at Mahatma Gandhi University and Associate Professor in Chemistry, St. Teresa’s College, Kochi, Kerala, India.\nDr. Varkey received a National Young Scientist award from the Indian Science Congress (1995), a UGC Research award (2016–2018), an Indian National Science Academy (INSA) Visiting Scientist award (2018–2019), and a Best Innovative Faculty award from the All India Association for Christian Higher Education (AIACHE) (2019). She Hashas received the Sr. Mary Cecil prize for best research paper three times. She was also awarded a start-up to develop a tea bag water filter. \nDr. Varkey has published two international books and twenty-seven international journal publications. She is an editorial board member for five international journals.",institutionString:"St. Teresa’s College",institution:null},{id:"250668",title:"Dr.",name:"Ali",middleName:null,surname:"Nabipour Chakoli",slug:"ali-nabipour-chakoli",fullName:"Ali Nabipour Chakoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/250668/images/system/250668.jpg",biography:"Academic Qualification:\r\n•\tPhD in Materials Physics and Chemistry, From: Sep. 2006, to: Sep. 2010, School of Materials Science and Engineering, Harbin Institute of Technology, Thesis: Structure and Shape Memory Effect of Functionalized MWCNTs/poly (L-lactide-co-ε-caprolactone) Nanocomposites. Supervisor: Prof. Wei Cai,\r\n•\tM.Sc in Applied Physics, From: 1996, to: 1998, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Determination of Boron in Micro alloy Steels with solid state nuclear track detectors by neutron induced auto radiography, Supervisors: Dr. M. Hosseini Ashrafi and Dr. A. Hosseini.\r\n•\tB.Sc. in Applied Physics, From: 1991, to: 1996, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Design of shielding for Am-Be neutron sources for In Vivo neutron activation analysis, Supervisor: Dr. M. Hosseini Ashrafi.\r\n\r\nResearch Experiences:\r\n1.\tNanomaterials, Carbon Nanotubes, Graphene: Synthesis, Functionalization and Characterization,\r\n2.\tMWCNTs/Polymer Composites: Fabrication and Characterization, \r\n3.\tShape Memory Polymers, Biodegradable Polymers, ORC, Collagen,\r\n4.\tMaterials Analysis and Characterizations: TEM, SEM, XPS, FT-IR, Raman, DSC, DMA, TGA, XRD, GPC, Fluoroscopy, \r\n5.\tInteraction of Radiation with Mater, Nuclear Safety and Security, NDT(RT),\r\n6.\tRadiation Detectors, Calibration (SSDL),\r\n7.\tCompleted IAEA e-learning Courses:\r\nNuclear Security (15 Modules),\r\nNuclear Safety:\r\nTSA 2: Regulatory Protection in Occupational Exposure,\r\nTips & Tricks: Radiation Protection in Radiography,\r\nSafety and Quality in Radiotherapy,\r\nCourse on Sealed Radioactive Sources,\r\nCourse on Fundamentals of Environmental Remediation,\r\nCourse on Planning for Environmental Remediation,\r\nKnowledge Management Orientation Course,\r\nFood Irradiation - Technology, Applications and Good Practices,\r\nEmployment:\r\nFrom 2010 to now: Academic staff, Nuclear Science and Technology Research Institute, Kargar Shomali, Tehran, Iran, P.O. Box: 14395-836.\r\nFrom 1997 to 2006: Expert of Materials Analysis and Characterization. Research Center of Agriculture and Medicine. Rajaeeshahr, Karaj, Iran, P. O. Box: 31585-498.",institutionString:"Atomic Energy Organization of Iran",institution:{name:"Atomic Energy Organization of Iran",country:{name:"Iran"}}},{id:"248279",title:"Dr.",name:"Monika",middleName:"Elzbieta",surname:"Machoy",slug:"monika-machoy",fullName:"Monika Machoy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248279/images/system/248279.jpeg",biography:"Monika Elżbieta Machoy, MD, graduated with distinction from the Faculty of Medicine and Dentistry at the Pomeranian Medical University in 2009, defended her PhD thesis with summa cum laude in 2016 and is currently employed as a researcher at the Department of Orthodontics of the Pomeranian Medical University. She expanded her professional knowledge during a one-year scholarship program at the Ernst Moritz Arndt University in Greifswald, Germany and during a three-year internship at the Technical University in Dresden, Germany. She has been a speaker at numerous orthodontic conferences, among others, American Association of Orthodontics, European Orthodontic Symposium and numerous conferences of the Polish Orthodontic Society. She conducts research focusing on the effect of orthodontic treatment on dental and periodontal tissues and the causes of pain in orthodontic patients.",institutionString:"Pomeranian Medical University",institution:{name:"Pomeranian Medical University",country:{name:"Poland"}}},{id:"252743",title:"Prof.",name:"Aswini",middleName:"Kumar",surname:"Kar",slug:"aswini-kar",fullName:"Aswini Kar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252743/images/10381_n.jpg",biography:"uploaded in cv",institutionString:null,institution:{name:"KIIT University",country:{name:"India"}}},{id:"204256",title:"Dr.",name:"Anil",middleName:"Kumar",surname:"Kumar Sahu",slug:"anil-kumar-sahu",fullName:"Anil Kumar Sahu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204256/images/14201_n.jpg",biography:"I have nearly 11 years of research and teaching experience. I have done my master degree from University Institute of Pharmacy, Pt. Ravi Shankar Shukla University, Raipur, Chhattisgarh India. I have published 16 review and research articles in international and national journals and published 4 chapters in IntechOpen, the world’s leading publisher of Open access books. I have presented many papers at national and international conferences. I have received research award from Indian Drug Manufacturers Association in year 2015. My research interest extends from novel lymphatic drug delivery systems, oral delivery system for herbal bioactive to formulation optimization.",institutionString:null,institution:{name:"Chhattisgarh Swami Vivekanand Technical University",country:{name:"India"}}},{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/253468/images/system/253468.png",biography:"An assistant professor at Department of Biomedical Computer Systems, at Institute of Computer Science, Silesian University in Katowice. Scientific interests: computer analysis and processing of images, biomedical images, databases and programming languages. He is an author and co-author of scientific publications covering analysis and processing of biomedical images and development of database systems.",institutionString:"University of Silesia",institution:null},{id:"212432",title:"Prof.",name:"Hadi",middleName:null,surname:"Mohammadi",slug:"hadi-mohammadi",fullName:"Hadi Mohammadi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/212432/images/system/212432.jpeg",biography:"Dr. Hadi Mohammadi is a biomedical engineer with hands-on experience in the design and development of many engineering structures and medical devices through various projects that he has been involved in over the past twenty years. Dr. Mohammadi received his BSc. and MSc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, and his PhD. degree in Biomedical Engineering (biomaterials) from the University of Western Ontario. He was a postdoctoral trainee for almost four years at University of Calgary and Harvard Medical School. He is an industry innovator having created the technology to produce lifelike synthetic platforms that can be used for the simulation of almost all cardiovascular reconstructive surgeries. He’s been heavily involved in the design and development of cardiovascular devices and technology for the past 10 years. He is currently an Assistant Professor with the University of British Colombia, Canada.",institutionString:"University of British Columbia",institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"254463",title:"Prof.",name:"Haisheng",middleName:null,surname:"Yang",slug:"haisheng-yang",fullName:"Haisheng Yang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/254463/images/system/254463.jpeg",biography:"Haisheng Yang, Ph.D., Professor and Director of the Department of Biomedical Engineering, College of Life Science and Bioengineering, Beijing University of Technology. He received his Ph.D. degree in Mechanics/Biomechanics from Harbin Institute of Technology (jointly with University of California, Berkeley). Afterwards, he worked as a Postdoctoral Research Associate in the Purdue Musculoskeletal Biology and Mechanics Lab at the Department of Basic Medical Sciences, Purdue University, USA. He also conducted research in the Research Centre of Shriners Hospitals for Children-Canada at McGill University, Canada. Dr. Yang has over 10 years research experience in orthopaedic biomechanics and mechanobiology of bone adaptation and regeneration. He earned an award from Beijing Overseas Talents Aggregation program in 2017 and serves as Beijing Distinguished Professor.",institutionString:"Beijing University of Technology",institution:null},{id:"255757",title:"Dr.",name:"Igor",middleName:"Victorovich",surname:"Lakhno",slug:"igor-lakhno",fullName:"Igor Lakhno",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255757/images/system/255757.jpg",biography:"Lakhno Igor Victorovich was born in 1971 in Kharkiv (Ukraine). \nMD – 1994, Kharkiv National Medical Univesity.\nOb&Gyn; – 1997, master courses in Kharkiv Medical Academy of Postgraduate Education.\nPhD – 1999, Kharkiv National Medical Univesity.\nDSc – 2019, PL Shupik National Academy of Postgraduate Education \nLakhno Igor has been graduated from an international training courses on reproductive medicine and family planning held in Debrecen University (Hungary) in 1997. Since 1998 Lakhno Igor has worked as an associate professor of the department of obstetrics and gynecology of VN Karazin National University and an associate professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education. Since June 2019 he’s a professor of the department of obstetrics and gynecology of VN Karazin National University and a professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education . He’s an author of about 200 printed works and there are 17 of them in Scopus or Web of Science databases. Lakhno Igor is a rewiever of Journal of Obstetrics and Gynaecology (Taylor and Francis), Informatics in Medicine Unlocked (Elsevier), The Journal of Obstetrics and Gynecology Research (Wiley), Endocrine, Metabolic & Immune Disorders-Drug Targets (Bentham Open), The Open Biomedical Engineering Journal (Bentham Open), etc. He’s defended a dissertation for DSc degree \\'Pre-eclampsia: prediction, prevention and treatment”. Lakhno Igor has participated as a speaker in several international conferences and congresses (International Conference on Biological Oscillations April 10th-14th 2016, Lancaster, UK, The 9th conference of the European Study Group on Cardiovascular Oscillations). His main scientific interests: obstetrics, women’s health, fetal medicine, cardiovascular medicine.",institutionString:"V.N. Karazin Kharkiv National University",institution:{name:"Kharkiv Medical Academy of Postgraduate Education",country:{name:"Ukraine"}}},{id:"89721",title:"Dr.",name:"Mehmet",middleName:"Cuneyt",surname:"Ozmen",slug:"mehmet-ozmen",fullName:"Mehmet Ozmen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/89721/images/7289_n.jpg",biography:null,institutionString:null,institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"243698",title:"M.D.",name:"Xiaogang",middleName:null,surname:"Wang",slug:"xiaogang-wang",fullName:"Xiaogang Wang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243698/images/system/243698.png",biography:"Dr. Xiaogang Wang, a faculty member of Shanxi Eye Hospital specializing in the treatment of cataract and retinal disease and a tutor for postgraduate students of Shanxi Medical University, worked in the COOL Lab as an international visiting scholar under the supervision of Dr. David Huang and Yali Jia from October 2012 through November 2013. Dr. Wang earned an MD from Shanxi Medical University and a Ph.D. from Shanghai Jiao Tong University. Dr. Wang was awarded two research project grants focused on multimodal optical coherence tomography imaging and deep learning in cataract and retinal disease, from the National Natural Science Foundation of China. He has published around 30 peer-reviewed journal papers and four book chapters and co-edited one book.",institutionString:"Shanxi Eye Hospital",institution:{name:"Shanxi Eye Hospital",country:{name:"China"}}},{id:"242893",title:"Ph.D. Student",name:"Joaquim",middleName:null,surname:"De Moura",slug:"joaquim-de-moura",fullName:"Joaquim De Moura",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/242893/images/7133_n.jpg",biography:"Joaquim de Moura received his degree in Computer Engineering in 2014 from the University of A Coruña (Spain). In 2016, he received his M.Sc degree in Computer Engineering from the same university. He is currently pursuing his Ph.D degree in Computer Science in a collaborative project between ophthalmology centers in Galicia and the University of A Coruña. His research interests include computer vision, machine learning algorithms and analysis and medical imaging processing of various kinds.",institutionString:null,institution:{name:"University of A Coruña",country:{name:"Spain"}}},{id:"267434",title:"Dr.",name:"Rohit",middleName:null,surname:"Raja",slug:"rohit-raja",fullName:"Rohit Raja",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRZkkQAG/Profile_Picture_2022-05-09T12:55:18.jpg",biography:null,institutionString:null,institution:null},{id:"294334",title:"B.Sc.",name:"Marc",middleName:null,surname:"Bruggeman",slug:"marc-bruggeman",fullName:"Marc Bruggeman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/294334/images/8242_n.jpg",biography:"Chemical engineer graduate, with a passion for material science and specific interest in polymers - their near infinite applications intrigue me. \n\nI plan to continue my scientific career in the field of polymeric biomaterials as I am fascinated by intelligent, bioactive and biomimetic materials for use in both consumer and medical applications.",institutionString:null,institution:null},{id:"244950",title:"Dr.",name:"Salvatore",middleName:null,surname:"Di Lauro",slug:"salvatore-di-lauro",fullName:"Salvatore Di Lauro",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0030O00002bSF1HQAW/ProfilePicture%202021-12-20%2014%3A54%3A14.482",biography:"Name:\n\tSALVATORE DI LAURO\nAddress:\n\tHospital Clínico Universitario Valladolid\nAvda Ramón y Cajal 3\n47005, Valladolid\nSpain\nPhone number: \nFax\nE-mail:\n\t+34 983420000 ext 292\n+34 983420084\nsadilauro@live.it\nDate and place of Birth:\nID Number\nMedical Licence \nLanguages\t09-05-1985. Villaricca (Italy)\n\nY1281863H\n474707061\nItalian (native language)\nSpanish (read, written, spoken)\nEnglish (read, written, spoken)\nPortuguese (read, spoken)\nFrench (read)\n\t\t\nCurrent position (title and company)\tDate (Year)\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. Private practise.\t2017-today\n\n2019-today\n\t\n\t\nEducation (High school, university and postgraduate training > 3 months)\tDate (Year)\nDegree in Medicine and Surgery. University of Neaples 'Federico II”\nResident in Opthalmology. Hospital Clinico Universitario Valladolid\nMaster in Vitreo-Retina. IOBA. University of Valladolid\nFellow of the European Board of Ophthalmology. Paris\nMaster in Research in Ophthalmology. University of Valladolid\t2003-2009\n2012-2016\n2016-2017\n2016\n2012-2013\n\t\nEmployments (company and positions)\tDate (Year)\nResident in Ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl.\nFellow in Vitreo-Retina. IOBA. University of Valladolid\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. \n\t2012-2016\n2016-2017\n2017-today\n\n2019-Today\n\n\n\t\nClinical Research Experience (tasks and role)\tDate (Year)\nAssociated investigator\n\n' FIS PI20/00740: DESARROLLO DE UNA CALCULADORA DE RIESGO DE\nAPARICION DE RETINOPATIA DIABETICA BASADA EN TECNICAS DE IMAGEN MULTIMODAL EN PACIENTES DIABETICOS TIPO 1. Grant by: Ministerio de Ciencia e Innovacion \n\n' (BIO/VA23/14) Estudio clínico multicéntrico y prospectivo para validar dos\nbiomarcadores ubicados en los genes p53 y MDM2 en la predicción de los resultados funcionales de la cirugía del desprendimiento de retina regmatógeno. Grant by: Gerencia Regional de Salud de la Junta de Castilla y León.\n' Estudio multicéntrico, aleatorizado, con enmascaramiento doble, en 2 grupos\nparalelos y de 52 semanas de duración para comparar la eficacia, seguridad e inmunogenicidad de SOK583A1 respecto a Eylea® en pacientes con degeneración macular neovascular asociada a la edad' (CSOK583A12301; N.EUDRA: 2019-004838-41; FASE III). Grant by Hexal AG\n\n' Estudio de fase III, aleatorizado, doble ciego, con grupos paralelos, multicéntrico para comparar la eficacia y la seguridad de QL1205 frente a Lucentis® en pacientes con degeneración macular neovascular asociada a la edad. (EUDRACT: 2018-004486-13). Grant by Qilu Pharmaceutical Co\n\n' Estudio NEUTON: Ensayo clinico en fase IV para evaluar la eficacia de aflibercept en pacientes Naive con Edema MacUlar secundario a Oclusion de Vena CenTral de la Retina (OVCR) en regimen de tratamientO iNdividualizado Treat and Extend (TAE)”, (2014-000975-21). Grant by Fundacion Retinaplus\n\n' Evaluación de la seguridad y bioactividad de anillos de tensión capsular en conejo. Proyecto Procusens. Grant by AJL, S.A.\n\n'Estudio epidemiológico, prospectivo, multicéntrico y abierto\\npara valorar la frecuencia de la conjuntivitis adenovírica diagnosticada mediante el test AdenoPlus®\\nTest en pacientes enfermos de conjuntivitis aguda”\\n. National, multicenter study. Grant by: NICOX.\n\nEuropean multicentric trial: 'Evaluation of clinical outcomes following the use of Systane Hydration in patients with dry eye”. Study Phase 4. Grant by: Alcon Labs'\n\nVLPs Injection and Activation in a Rabbit Model of Uveal Melanoma. Grant by Aura Bioscience\n\nUpdating and characterization of a rabbit model of uveal melanoma. Grant by Aura Bioscience\n\nEnsayo clínico en fase IV para evaluar las variantes genéticas de la vía del VEGF como biomarcadores de eficacia del tratamiento con aflibercept en pacientes con degeneración macular asociada a la edad (DMAE) neovascular. Estudio BIOIMAGE. IMO-AFLI-2013-01\n\nEstudio In-Eye:Ensayo clínico en fase IV, abierto, aleatorizado, de 2 brazos,\nmulticçentrico y de 12 meses de duración, para evaluar la eficacia y seguridad de un régimen de PRN flexible individualizado de 'esperar y extender' versus un régimen PRN según criterios de estabilización mediante evaluaciones mensuales de inyecciones intravítreas de ranibizumab 0,5 mg en pacientes naive con neovascularización coriodea secunaria a la degeneración macular relacionada con la edad. CP: CRFB002AES03T\n\nTREND: Estudio Fase IIIb multicéntrico, randomizado, de 12 meses de\nseguimiento con evaluador de la agudeza visual enmascarado, para evaluar la eficacia y la seguridad de ranibizumab 0.5mg en un régimen de tratar y extender comparado con un régimen mensual, en pacientes con degeneración macular neovascular asociada a la edad. CP: CRFB002A2411 Código Eudra CT:\n2013-002626-23\n\n\n\nPublications\t\n\n2021\n\n\n\n\n2015\n\n\n\n\n2021\n\n\n\n\n\n2021\n\n\n\n\n2015\n\n\n\n\n2015\n\n\n2014\n\n\n\n\n2015-16\n\n\n\n2015\n\n\n2014\n\n\n2014\n\n\n\n\n2014\n\n\n\n\n\n\n\n2014\n\nJose Carlos Pastor; Jimena Rojas; Salvador Pastor-Idoate; Salvatore Di Lauro; Lucia Gonzalez-Buendia; Santiago Delgado-Tirado. Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical\nconsequences. Progress in Retinal and Eye Research. 51, pp. 125 - 155. 03/2016. DOI: 10.1016/j.preteyeres.2015.07.005\n\n\nLabrador-Velandia S; Alonso-Alonso ML; Di Lauro S; García-Gutierrez MT; Srivastava GK; Pastor JC; Fernandez-Bueno I. Mesenchymal stem cells provide paracrine neuroprotective resources that delay degeneration of co-cultured organotypic neuroretinal cultures.Experimental Eye Research. 185, 17/05/2019. DOI: 10.1016/j.exer.2019.05.011\n\nSalvatore Di Lauro; Maria Teresa Garcia Gutierrez; Ivan Fernandez Bueno. Quantification of pigment epithelium-derived factor (PEDF) in an ex vivo coculture of retinal pigment epithelium cells and neuroretina.\nJournal of Allbiosolution. 2019. ISSN 2605-3535\n\nSonia Labrador Velandia; Salvatore Di Lauro; Alonso-Alonso ML; Tabera Bartolomé S; Srivastava GK; Pastor JC; Fernandez-Bueno I. Biocompatibility of intravitreal injection of human mesenchymal stem cells in immunocompetent rabbits. Graefe's archive for clinical and experimental ophthalmology. 256 - 1, pp. 125 - 134. 01/2018. DOI: 10.1007/s00417-017-3842-3\n\n\nSalvatore Di Lauro, David Rodriguez-Crespo, Manuel J Gayoso, Maria T Garcia-Gutierrez, J Carlos Pastor, Girish K Srivastava, Ivan Fernandez-Bueno. A novel coculture model of porcine central neuroretina explants and retinal pigment epithelium cells. Molecular Vision. 2016 - 22, pp. 243 - 253. 01/2016.\n\nSalvatore Di Lauro. Classifications for Proliferative Vitreoretinopathy ({PVR}): An Analysis of Their Use in Publications over the Last 15 Years. Journal of Ophthalmology. 2016, pp. 1 - 6. 01/2016. DOI: 10.1155/2016/7807596\n\nSalvatore Di Lauro; Rosa Maria Coco; Rosa Maria Sanabria; Enrique Rodriguez de la Rua; Jose Carlos Pastor. Loss of Visual Acuity after Successful Surgery for Macula-On Rhegmatogenous Retinal Detachment in a Prospective Multicentre Study. Journal of Ophthalmology. 2015:821864, 2015. DOI: 10.1155/2015/821864\n\nIvan Fernandez-Bueno; Salvatore Di Lauro; Ivan Alvarez; Jose Carlos Lopez; Maria Teresa Garcia-Gutierrez; Itziar Fernandez; Eva Larra; Jose Carlos Pastor. Safety and Biocompatibility of a New High-Density Polyethylene-Based\nSpherical Integrated Porous Orbital Implant: An Experimental Study in Rabbits. Journal of Ophthalmology. 2015:904096, 2015. DOI: 10.1155/2015/904096\n\nPastor JC; Pastor-Idoate S; Rodríguez-Hernandez I; Rojas J; Fernandez I; Gonzalez-Buendia L; Di Lauro S; Gonzalez-Sarmiento R. Genetics of PVR and RD. Ophthalmologica. 232 - Suppl 1, pp. 28 - 29. 2014\n\nRodriguez-Crespo D; Di Lauro S; Singh AK; Garcia-Gutierrez MT; Garrosa M; Pastor JC; Fernandez-Bueno I; Srivastava GK. Triple-layered mixed co-culture model of RPE cells with neuroretina for evaluating the neuroprotective effects of adipose-MSCs. Cell Tissue Res. 358 - 3, pp. 705 - 716. 2014.\nDOI: 10.1007/s00441-014-1987-5\n\nCarlo De Werra; Salvatore Condurro; Salvatore Tramontano; Mario Perone; Ivana Donzelli; Salvatore Di Lauro; Massimo Di Giuseppe; Rosa Di Micco; Annalisa Pascariello; Antonio Pastore; Giorgio Diamantis; Giuseppe Galloro. Hydatid disease of the liver: thirty years of surgical experience.Chirurgia italiana. 59 - 5, pp. 611 - 636.\n(Italia): 2007. ISSN 0009-4773\n\nChapters in books\n\t\n' Salvador Pastor Idoate; Salvatore Di Lauro; Jose Carlos Pastor Jimeno. PVR: Pathogenesis, Histopathology and Classification. Proliferative Vitreoretinopathy with Small Gauge Vitrectomy. Springer, 2018. ISBN 978-3-319-78445-8\nDOI: 10.1007/978-3-319-78446-5_2. \n\n' Salvatore Di Lauro; Maria Isabel Lopez Galvez. Quistes vítreos en una mujer joven. Problemas diagnósticos en patología retinocoroidea. Sociedad Española de Retina-Vitreo. 2018.\n\n' Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor Jimeno. iOCT in PVR management. OCT Applications in Opthalmology. pp. 1 - 8. INTECH, 2018. DOI: 10.5772/intechopen.78774.\n\n' Rosa Coco Martin; Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor. amponadores, manipuladores y tinciones en la cirugía del traumatismo ocular.Trauma Ocular. Ponencia de la SEO 2018..\n\n' LOPEZ GALVEZ; DI LAURO; CRESPO. OCT angiografia y complicaciones retinianas de la diabetes. PONENCIA SEO 2021, CAPITULO 20. (España): 2021.\n\n' Múltiples desprendimientos neurosensoriales bilaterales en paciente joven. Enfermedades Degenerativas De Retina Y Coroides. SERV 04/2016. \n' González-Buendía L; Di Lauro S; Pastor-Idoate S; Pastor Jimeno JC. Vitreorretinopatía proliferante (VRP) e inflamación: LA INFLAMACIÓN in «INMUNOMODULADORES Y ANTIINFLAMATORIOS: MÁS ALLÁ DE LOS CORTICOIDES. RELACION DE PONENCIAS DE LA SOCIEDAD ESPAÑOLA DE OFTALMOLOGIA. 10/2014.",institutionString:null,institution:null},{id:"265335",title:"Mr.",name:"Stefan",middleName:"Radnev",surname:"Stefanov",slug:"stefan-stefanov",fullName:"Stefan Stefanov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/265335/images/7562_n.jpg",biography:null,institutionString:null,institution:null},{id:"318905",title:"Prof.",name:"Elvis",middleName:"Kwason",surname:"Tiburu",slug:"elvis-tiburu",fullName:"Elvis Tiburu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Ghana",country:{name:"Ghana"}}},{id:"336193",title:"Dr.",name:"Abdullah",middleName:null,surname:"Alamoudi",slug:"abdullah-alamoudi",fullName:"Abdullah Alamoudi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"318657",title:"MSc.",name:"Isabell",middleName:null,surname:"Steuding",slug:"isabell-steuding",fullName:"Isabell Steuding",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"318656",title:"BSc.",name:"Peter",middleName:null,surname:"Kußmann",slug:"peter-kussmann",fullName:"Peter Kußmann",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"338222",title:"Mrs.",name:"María José",middleName:null,surname:"Lucía Mudas",slug:"maria-jose-lucia-mudas",fullName:"María José Lucía Mudas",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}},{id:"147824",title:"Mr.",name:"Pablo",middleName:null,surname:"Revuelta Sanz",slug:"pablo-revuelta-sanz",fullName:"Pablo Revuelta Sanz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}}]}},subseries:{item:{id:"12",type:"subseries",title:"Human Physiology",keywords:"Anatomy, Cells, Organs, Systems, Homeostasis, Functions",scope:"Human physiology is the scientific exploration of the various functions (physical, biochemical, and mechanical properties) of humans, their organs, and their constituent cells. 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