Barely three months into the new year and we are happy to announce a monumental milestone reached - 150 million downloads.
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This achievement solidifies IntechOpen’s place as a pioneer in Open Access publishing and the home to some of the most relevant scientific research available through Open Access.
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We are so proud to have worked with so many bright minds throughout the years who have helped us spread knowledge through the power of Open Access and we look forward to continuing to support some of the greatest thinkers of our day.
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Thank you for making IntechOpen your place of learning, sharing, and discovery, and here’s to 150 million more!
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\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:"7518",leadTitle:null,fullTitle:"Medicinal Chemistry",title:"Medicinal Chemistry",subtitle:null,reviewType:"peer-reviewed",abstract:"The area covered by this book undoubtedly includes a multidisciplinary approach. It combines and uses the wide range of methods and knowledge from a variety of disciplines in chemistry, pharmacology, and biology to synthesize new or extracted natural substances and their characterization, in terms of bioefficiency in different systems, pharmacokinetics, and pharmacodynamics. Importance is placed on revealing the interactions and effects on organisms. The process is long term, ranging from synthesis to potential testing of substances in animal studies, followed by monitoring effects on patients. The purpose is to define molecular targets of the highest efficacy of the prepared drugs, minimizing the undesirable effects. The content of this book is conceived with these intentions.",isbn:"978-1-78985-174-8",printIsbn:"978-1-78985-173-1",pdfIsbn:"978-1-83962-077-5",doi:"10.5772/intechopen.76494",price:119,priceEur:129,priceUsd:155,slug:"medicinal-chemistry",numberOfPages:168,isOpenForSubmission:!1,isInWos:1,isInBkci:!1,hash:"944740b06e48079bae2b7dd7b28940a1",bookSignature:"Janka Vašková and Ladislav Vaško",publishedDate:"March 13th 2019",coverURL:"https://cdn.intechopen.com/books/images_new/7518.jpg",numberOfDownloads:13553,numberOfWosCitations:2,numberOfCrossrefCitations:8,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:24,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:34,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 21st 2018",dateEndSecondStepPublish:"April 11th 2018",dateEndThirdStepPublish:"June 10th 2018",dateEndFourthStepPublish:"August 29th 2018",dateEndFifthStepPublish:"October 28th 2018",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"140747",title:"Associate Prof.",name:"Janka",middleName:null,surname:"Vašková",slug:"janka-vaskova",fullName:"Janka Vašková",profilePictureURL:"https://mts.intechopen.com/storage/users/140747/images/system/140747.jpeg",biography:"Janka Vašková, assoc. prof. Dr. PhD is working as research scientist at the Department of Medical and Clinical Biochemistry, Faculty of Medicine, Pavol Jozef Šafárik University in Košice. She studied at the University of Pavol Jozef Šafárik (1993-1998) with specialisation in Anthropology. She began with internal doctoral studies completed by dissertation thesis in Anthropology in 2003 (PhD.). She was appointed associated professor in Anthropology in 2016, and received scientific qualification level senior researcher in Clinical Biochemistry. She is the author of 2 monographs, 4 textbooks and more than 280 original scientific and conference papers. Currently deals with detection of pro- and antioxidant properties of natural and synthetic substances, their effect on the antioxidant status of the organism, as well as assessment of treatment success and patient prognosis by detecting the changes in selected antioxidant markers.",institutionString:"Pavol Jozef Safarik University in Kosice",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"3",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"University of Pavol Jozef Šafárik",institutionURL:null,country:{name:"Slovakia"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"207199",title:"Prof.",name:"Ladislav",middleName:null,surname:"Vaško",slug:"ladislav-vasko",fullName:"Ladislav Vaško",profilePictureURL:"https://mts.intechopen.com/storage/users/207199/images/7406_n.jpg",biography:"Ladislav Vaško, assoc. prof. DVM., PhD is working as associate professor at the Department of Medical and Clinical Biochemistry, Faculty of Medicine, Pavol Jozef Šafárik University in Košice. Since graduation at the University of Veterinary Medicine in Košice in 1974, he had been working on the Clinic of Internal Diseases. He completed doctoral studies by dissertation thesis in 1979. From 1980 to 2008 he taught chemistry at the Department of Biochemistry and Toxicology. In 1989, the Ministry of Education of the Slovak Republic appointed him associated professor in Biochemistry, in 2006 habilitated to associate professor in Physiology and Morphology. Since March 2008 he has been working at the Faculty of Medicine in Košice. He is the author of 3 monographs, 9 textbooks, and more than 400 scientific and conference papers. Currently deals with the effects of humic acids on organisms with simultaneous intake of toxic substances.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:null},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1190",title:"Pharmaceutical Chemistry",slug:"pharmaceutical-chemistry"}],chapters:[{id:"64761",title:"Introductory Chapter: Unregulated Mitochondrial Production of Reactive Oxygen Species in Testing the Biological Activity of Compounds",doi:"10.5772/intechopen.82514",slug:"introductory-chapter-unregulated-mitochondrial-production-of-reactive-oxygen-species-in-testing-the-",totalDownloads:978,totalCrossrefCites:0,totalDimensionsCites:1,hasAltmetrics:0,abstract:null,signatures:"Janka Vašková and Ladislav Vaško",downloadPdfUrl:"/chapter/pdf-download/64761",previewPdfUrl:"/chapter/pdf-preview/64761",authors:[{id:"140747",title:"Associate Prof.",name:"Janka",surname:"Vašková",slug:"janka-vaskova",fullName:"Janka Vašková"},{id:"207199",title:"Prof.",name:"Ladislav",surname:"Vaško",slug:"ladislav-vasko",fullName:"Ladislav Vaško"}],corrections:null},{id:"64453",title:"Determination of In Vitro Cytotoxicity and Anti-Angiogenesis for a Bioactive Compound from Aspergillus terreus FC36AY1 Isolated from Aegle marmelos around Western Ghats, India",doi:"10.5772/intechopen.81046",slug:"determination-of-in-vitro-cytotoxicity-and-anti-angiogenesis-for-a-bioactive-compound-from-aspergill",totalDownloads:1260,totalCrossrefCites:0,totalDimensionsCites:6,hasAltmetrics:0,abstract:"The biotechnological research mainly emphasis its investigation on searching new natural drugs at economical to human welfare. With this view in mind, this research has focused to develop a prospective bioactive compound isolating from an efficient endophytic fungus isolated from potential medicinal tree Aegle marmelos. The endophytic fungus was isolated from the medicinal tree and identified as Aspergillus terreus FC36AY1. This fungus produced maximum of crude metabolites and this was produced in Sabouraud’s Dextrose Broth. The produced metabolites were extracted using acetone as a sole solvent and it was taken for the assessment of antimicrobial and antioxidant analysis. The crude metabolites exhibited maximum activity at least concentration and further the crude extract were taken for purification processes through chromatographic techniques. Through purification, five different fractions were eluted and those five different fractions were also assessed for antimicrobial and antioxidant analysis. From these analysis results, TA4 was found to be efficient fraction and it was characterized through FT-IR, GC-MS and UV-VIS analysis. The compound was taken for cytotoxicity determination in HT-29 cancer cells and anti-angiogenesis analysis was assessed through HET-CAM testing. The bio-activities study revealed that the compound TA4 has the ability to target the cancer cells in an efficient manner.",signatures:"Vellingiri Manon Mani, Arockiam Jeyasundar Parimala Gnana\nSoundari and Selvam Tamilarasi",downloadPdfUrl:"/chapter/pdf-download/64453",previewPdfUrl:"/chapter/pdf-preview/64453",authors:[{id:"250724",title:"Dr.",name:"Parimala Gnana Soundari",surname:"A",slug:"parimala-gnana-soundari-a",fullName:"Parimala Gnana Soundari A"},{id:"258274",title:"Dr.",name:"Manon Mani",surname:"Vellingiri",slug:"manon-mani-vellingiri",fullName:"Manon Mani Vellingiri"},{id:"268822",title:"Ms.",name:"Tamilarasi",surname:"S",slug:"tamilarasi-s",fullName:"Tamilarasi S"}],corrections:null},{id:"62012",title:"The Apoptotic Effects of Methylparaben and Ultraviolet B Light on M624 Human Melanoma Cells",doi:"10.5772/intechopen.78575",slug:"the-apoptotic-effects-of-methylparaben-and-ultraviolet-b-light-on-m624-human-melanoma-cells",totalDownloads:925,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Methylparaben is a commonly used antimicrobial in cosmetics that has been shown to have negative effects on mammalian cells. Human melanoma M624 cells were treated with 1 and 5 mM methylparaben in the presence and absence of 25 mJ/cm2 ultraviolet B (UV-B) light. Cell proliferation assays showed that 5 mM methylparaben was toxic to M624 cells after 24 hours. Apoptotic signaling pathways were analyzed via isolation of separate cellular compartments and protein analysis via western blot. Upon 5 mM methylparaben treatment, PARP I was cleaved indicating apoptosis, which was mediated by the TNF-α receptor activated in the lipid rafts of the M624 cells. Upon 25 mJ/cm2 UV-B radiation, PARP II was activated indicating cellular damage, cytochrome c was released from the mitochondria, and caspase-3 was expressed. Upon combinatory treatment with 5 mM methylparaben and 25 mJ/cm2 UV-B, apoptosis was induced through mitochondrial release of cytochrome c, expression of caspase-3 and cleavage of PARP I, while methylparaben-induced TNF-α receptor activation and UV-B-induced PARP II activation was inhibited., demonstrating that antimicrobial methylparaben in cosmetics can cause damage to cells.",signatures:"Rebekah S. Wood, Rebecca S. Greenstein, Isabella M. Hildebrandt\nand Kimberly S. George Parsons",downloadPdfUrl:"/chapter/pdf-download/62012",previewPdfUrl:"/chapter/pdf-preview/62012",authors:[{id:"210771",title:"Dr.",name:"Kimberly Suzanne",surname:"George Parsons",slug:"kimberly-suzanne-george-parsons",fullName:"Kimberly Suzanne George Parsons"},{id:"210773",title:"Ms.",name:"Rebekah",surname:"Wood",slug:"rebekah-wood",fullName:"Rebekah Wood"},{id:"210774",title:"Ms.",name:"Rebecca",surname:"Greenstein",slug:"rebecca-greenstein",fullName:"Rebecca Greenstein"},{id:"210775",title:"Ms.",name:"Isabella",surname:"Hildebrandt",slug:"isabella-hildebrandt",fullName:"Isabella Hildebrandt"}],corrections:null},{id:"62647",title:"Indomethacin from Anti-Inflammatory to Anticancer Agent",doi:"10.5772/intechopen.79677",slug:"indomethacin-from-anti-inflammatory-to-anticancer-agent",totalDownloads:1316,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"The chapter “Indomethacin from Anti-inflammatory to Anticancer Agent” covers the recent reports regarding the implication of COX-2/PGE2 in multiple cancer cell proliferation to emphasize the anticancer potential of COX-inhibitors including indomethacin and to reveal that the reduction of PGE2 production interferes with the cancer cell proliferation belongs to multiple cancer cell types. Impressively, indomethacin is involved in antiproliferative and apoptotic actions against cancer cell types via COX-2-independent mechanisms to highlight indomethacin as promising anticancer agent with dual actions to control the cancer cell proliferation. The cardiovascular complications result from diaryl heterocycle sulfonamide/methylsulfone selective COX-2 inhibitors upon reduction in PGE2 and PGI2 production that affects the vascular tone limits the use of Celecoxib as chemopreventive agent against recurrence of colorectal carcinoma cells. Kinetic profile of indomethacin against COX-2 showed obvious difference from that of selective COX-2 inhibitors in which it recovered completely from the enzyme after long time of incubation while COX-2 inhibitors did not recover to impress that this might be implicated in the cardiovascular toxicity of the selective inhibitors. This raised the concern to develop the indomethacin from nonselective COX- to selective COX-2-inhibitors and to assert whether the cardiac complications are from pharmacological class effect or chemical class effect.",signatures:"Shaymaa Emam Kassab",downloadPdfUrl:"/chapter/pdf-download/62647",previewPdfUrl:"/chapter/pdf-preview/62647",authors:[{id:"251335",title:"Dr.",name:"Shaymaa",surname:"Kassab",slug:"shaymaa-kassab",fullName:"Shaymaa Kassab"}],corrections:null},{id:"63768",title:"1,4-Benzodiazepines and New Derivatives: Description, Analysis, and Organic Synthesis",doi:"10.5772/intechopen.79879",slug:"1-4-benzodiazepines-and-new-derivatives-description-analysis-and-organic-synthesis",totalDownloads:4405,totalCrossrefCites:3,totalDimensionsCites:8,hasAltmetrics:0,abstract:"Benzodiazepines are widely used drugs for several indications. This study provides, on the other hand, a global vision of the family starting for their fortuitous discovery, the synthesis of their derivatives, their mechanism of action widely known nowadays, the actual classification according to the chemical structure and pharmacokinetic properties, and their uses and indications, the traditional and the new ones. On the other hand,the study is focused in the mainly problems of benzodiazepines, depedence, and tolerance, many times led by a misuse of the patient, wrong prescriptions, or extended treatments. A withdrawal program is proposed that includes the important factors or criteria to success, with a slow and gradual reduction of these drugs, avoiding relapse or severe adverse effects. New lines of research related to benzodiazepines are taken into account, which not only include the new therapeutic uses but also the adverse effects in short and long term. They are also analyzed the new discoveries concerning the nonbenzodiazepine drugs due to the close relation they have with benzodiazepines.",signatures:"Elisabet Batlle, Enric Lizano, Miquel Viñas and Maria Dolors Pujol",downloadPdfUrl:"/chapter/pdf-download/63768",previewPdfUrl:"/chapter/pdf-preview/63768",authors:[{id:"252409",title:"Prof.",name:"Maria Dolors",surname:"Pujol",slug:"maria-dolors-pujol",fullName:"Maria Dolors Pujol"},{id:"262535",title:"Dr.",name:"Elisabet",surname:"Batlle",slug:"elisabet-batlle",fullName:"Elisabet Batlle"},{id:"262756",title:"Mr.",name:"Enric",surname:"Lizano",slug:"enric-lizano",fullName:"Enric Lizano"},{id:"274188",title:"Dr.",name:"Miquel",surname:"Viñas",slug:"miquel-vinas",fullName:"Miquel Viñas"}],corrections:null},{id:"63789",title:"Clinical Pharmacokinetics of Clavulanic Acid, a Novel β- Lactamase Isolated from Streptomyces clavuligerus and Its Variability",doi:"10.5772/intechopen.79409",slug:"clinical-pharmacokinetics-of-clavulanic-acid-a-novel-lactamase-isolated-from-streptomyces-clavuliger",totalDownloads:1100,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:1,abstract:"The clavulanic acid derived by fermentation of Streptomyces clavuligerus and possessed the capability to inactivate a broad range of β-lactamase enzymes. A complex physicochemical process involves the binding of clavulanic acid to β-lactamases in which clavulanic acid itself deplete irreversibly along with β-lactamase enzyme rendering amoxicillin spared which otherwise would hydrolyze by an enzyme. It is therefore termed as ‘suicide ‘inhibitor for β-lactamases. We discussed here pharmacokinetic parameters and identified factors responsible for the variability of absorption of clavulanic acid. The results based on individual plasma concentration-time curve of amoxicillin and clavulanic acid in an open, randomized, two-way crossover study involving 10 healthy male subjects administered with two amoxiclav formulations.",signatures:"Anab Fatima, Mohammad Jiyad Shaikh, Hina Zahid, Ishart Younus,\nSheikh Abdul Khaliq and Farah Khalid",downloadPdfUrl:"/chapter/pdf-download/63789",previewPdfUrl:"/chapter/pdf-preview/63789",authors:[{id:"225358",title:"Dr.",name:"Muhammad Jiyad",surname:"Shaikh",slug:"muhammad-jiyad-shaikh",fullName:"Muhammad Jiyad Shaikh"},{id:"231412",title:"Dr.",name:"Anab",surname:"Fatima",slug:"anab-fatima",fullName:"Anab Fatima"},{id:"243371",title:"Dr.",name:"Hina",surname:"Zahid",slug:"hina-zahid",fullName:"Hina Zahid"},{id:"243372",title:"Dr.",name:"Ishart",surname:"Younus",slug:"ishart-younus",fullName:"Ishart Younus"},{id:"243373",title:"Dr.",name:"Sheikh Abdul",surname:"Khaliq",slug:"sheikh-abdul-khaliq",fullName:"Sheikh Abdul Khaliq"},{id:"243374",title:"Dr.",name:"Farah",surname:"Khalid",slug:"farah-khalid",fullName:"Farah Khalid"}],corrections:null},{id:"63353",title:"New Antituberculosis Drug FS-1",doi:"10.5772/intechopen.80795",slug:"new-antituberculosis-drug-fs-1",totalDownloads:1464,totalCrossrefCites:2,totalDimensionsCites:5,hasAltmetrics:0,abstract:"The new iodine complex (FS-1), including molecular iodine, which is coordinated by lithium, magnesium halides, and bioorganic ligands, possesses high bactericidal activity against various microorganisms, including Mycobacterium sp., Staphylococcus aureus MRSA and MSSA, Escherichia coli, Pseudomonas aeruginosa, etc. FS-1 has synergistic properties with a broad class of antibiotics. The experimental model of tuberculosis in guinea pigs caused by clinical multidrug-resistant strains of Mycobacterium tuberculosis shows antituberculosis, immunomodulatory, and anti-inflammatory activity. FS-1 is characterized by low acute toxicity and lack of genotoxicity and mutagenicity. FS-1 is well distributed to organs and tissues; its pharmacokinetics is linear. The maximum nontoxic dose is 100 mg/kg for rats after 28-day oral administration and 30 mg/kg for rabbits after 180-day oral administration.",signatures:"Rinat Islamov, Bahkytzhan Kerimzhanova and Alexander Ilin",downloadPdfUrl:"/chapter/pdf-download/63353",previewPdfUrl:"/chapter/pdf-preview/63353",authors:[{id:"109493",title:"Dr.",name:"Rinat",surname:"Islamov",slug:"rinat-islamov",fullName:"Rinat Islamov"},{id:"136527",title:"Dr.",name:"Alexander",surname:"Ilin",slug:"alexander-ilin",fullName:"Alexander Ilin"},{id:"261645",title:"Prof.",name:"Bahyitzhan",surname:"Kerimzhanova",slug:"bahyitzhan-kerimzhanova",fullName:"Bahyitzhan Kerimzhanova"}],corrections:null},{id:"62975",title:"Clinical Relevance of Medicinal Plants and Foods of Vegetal Origin on the Activity of Cytochrome P450",doi:"10.5772/intechopen.79971",slug:"clinical-relevance-of-medicinal-plants-and-foods-of-vegetal-origin-on-the-activity-of-cytochrome-p45",totalDownloads:1113,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Drug metabolism is a pharmacokinetic process whose main objective is to modify the chemical structure of drugs to easily excretable compounds. This process is carried out through phase I and phase II reactions. The enzymes of cytochrome P450 (CYP450) participate in phase I reactions, and their activity can be inhibited or induced by xenobiotics. The aim of this chapter is to study the clinical relevance of the induction and inhibition of CYP450, by describing the effect that some bioactive compounds present in medicinal plants or foods can modify, either increasing or decreasing the activity of CYP450 enzymes and with it modify the bioavailability and depuration of drugs. Examples will be described on the interaction of medicinal plants and foods of vegetal origin that when combined with some drugs can generate toxicity or therapeutic failure; this will allow gathering relevant information on the adequate pharmacological management in different clinical situations.",signatures:"Xóchitl S. Ramírez-Gómez, Sandra N. Jiménez-García, Vicente\nBeltrán Campos, Esmeralda Rodríguez Miranda, Gabriel Herrera\nPérez and Rafael Vargas-Bernal",downloadPdfUrl:"/chapter/pdf-download/62975",previewPdfUrl:"/chapter/pdf-preview/62975",authors:[{id:"141347",title:"Dr.",name:"Sandra Neli",surname:"Jimenez Garcia",slug:"sandra-neli-jimenez-garcia",fullName:"Sandra Neli Jimenez Garcia"},{id:"152334",title:"Dr.",name:"Gabriel",surname:"Herrera-Pérez",slug:"gabriel-herrera-perez",fullName:"Gabriel Herrera-Pérez"},{id:"152335",title:"Dr.",name:"Esmeralda",surname:"Rodríguez-Miranda",slug:"esmeralda-rodriguez-miranda",fullName:"Esmeralda Rodríguez-Miranda"},{id:"182114",title:"D.Sc.",name:"Rafael",surname:"Vargas-Bernal",slug:"rafael-vargas-bernal",fullName:"Rafael Vargas-Bernal"},{id:"212575",title:"Dr.",name:"Xochitl Sofia",surname:"Ramirez Gomez",slug:"xochitl-sofia-ramirez-gomez",fullName:"Xochitl Sofia Ramirez Gomez"},{id:"255064",title:"Dr.",name:"Vicente",surname:"Beltran Campos",slug:"vicente-beltran-campos",fullName:"Vicente Beltran Campos"}],corrections:null},{id:"63990",title:"The Pragmatic Strategy to Detect Endocrine-Disrupting Activity of Xenobiotics in Food",doi:"10.5772/intechopen.81030",slug:"the-pragmatic-strategy-to-detect-endocrine-disrupting-activity-of-xenobiotics-in-food",totalDownloads:994,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Endocrine-disrupting activity induced by xenobiotics might pose a possible health threat. Facing so many chemicals, there is an issue on how we detect them precisely and effectively. The whole embryo culture (WEC) test, an ex vivo exposure lasting 48 hours with rat embryos of 10.5 days old, is used to detect prenatal developmental toxicity. We extended the WEC function to detect the endocrine-disrupting activity induced by environmental chemicals. Results showed that in the development of rat embryo, basically 17ß-estradiol, triiodothyronine, triadimefon, penconazole, and propiconazole exhibited no significant effect on yolk sac circulatory system, allantois, flexion, heart caudal neural tube, hindbrain, midbrain, forebrain, otic system, optic system, olfactory system, maxillary process, forelimb, hind limb, yolk sac diameter, crown-rump length, head length, and developmental score. In the immunohistochemistry, the positive control of 17ß-estradiol showed positive effect for its receptor expressions. These three triazoles induced expressions of ERα and ERß in WEC. This result basically meets the mode of action that triazoles were designed to disrupt the synthesis of steroid hormone. Here we gave a strategy to detect possible endocrine-disrupting activity induced by xenobiotics in food. 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\r\n\tThe transformation of the world into the digital era has made almost everything in the world change drastically. It's not just the economic life as most people tend to focus on, but also the political life. Democracy as a regime of almost the entire world has become a way of life for the majority of people. However, like anything else, it has been affected by this major shift and has been driven towards digitalization. The understanding of this political science keyword that most people used to think they understood very well is now in a situation where it is no longer certain. The asymmetrical changes of countries in the world in terms of economic, social, and political development in terms of digitization of democracy are inevitable. Understanding the status, challenges, and trends of this world's mainstream is therefore imperative and helpful. This book will therefore be an endeavor to gather the results of studies on the situations, challenges, and trends of democracy, including elections, which are the foundation of democracy, of countries in the world today.
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\n
1. Introduction
\n
The attraction or the motivation by which individuals decide to go to certain destinations or others, has inspired the study of tourism competitiveness. Among the theoretical studies, it is possible to highlight the models of [1–4]. The studies of [5–9] can be mentioned among the empirical. In these studies, it is shown that there is no single determining factor of tourism attraction, but that tourism competitiveness is related to the sum of many factors. Consequently, various indicators have been developed that attempt to summarise the competitiveness of the destination by a number. Basically, several elements are included in these indicators, which are found with various methodologies [10]. Among them are those related to the provision of physical resources or those inherited from the past.
\n
The interest of these analyses is focused on determining which factors influence the growth of tourism. Concurrently to these studies, other economists have focused their interest on the empirical analysis of the relationship between tourism and growth. Initially, these analyses were focused on the empirical confirmation of the so-called tourism-led growth (TLG) hypothesis, since [11] made the first empirical study on the causal relationships between both variables. Other, more recent, studies put emphasis on knowing through what mechanism, or how or in what quantity, tourism generates economic growth, and they empirically analyse the relationship between tourism and economic growth, including tourism demand variables in the production functions, because as [12] affirms, it is necessary to consider other productive factors when the relationship between tourism activity and economic growth is analysed.
\n
This study reviews the theories relating to competitiveness and the indicators used for its measurement on the one hand, and the studies that relate tourism and growth on the other, with the purpose of establishing the links that exist between both concepts. This enables a model to be defined in which some factors that affect tourism competitiveness, combine with capital and labour to determine economic growth. Those factors are included in this study, under the name of inherited tourism resources.
\n
With this objective, the present study is structured as follows. After this introduction, the competitiveness models are reviewed in Section 2, including tourism competitiveness. In Section 3, a review is made of the international indicators used to make estimations of tourism competitiveness. In Section 4, a review is made of the studies that analyse economic growth and tourism, putting emphasis on the limitations or difficulties of these models and their relationship to tourism competitiveness. This analysis allows the definition of an alternative model of study, which includes the concept of inherited tourism resource. Finally, conclusions are made in Section 5.
Since the last decade of the twentieth century, an increasing number of researchers have focused on knowing the causes that make a geographical enclave become a preferred tourist destination above others, and the reasons for their greater or lesser tourist attraction potential. In the past decade of the present century, the proposals have been focused on producing models that measure, by means of a specific empirical methodology, the competitiveness of the tourism destinations [1–4].
\n
In agreement with [5], there are three main reasons why the mentioned scientific interest has been inspired: firstly, the increasing importance that the tourism sector has in the regional, national and global economies; secondly, the increasing competition between tourism destinations, although they have hardly changed over the years [13,14]; and finally, the benefits of tourism for the economies seem to be clear in the short term, but their effects in the long term do not appear to be as great, or at least there is insufficient empirical evidence that supports it [15–17].
\n
The first section of this chapter reviews the conceptual models of tourism competitiveness. This is followed with an examination of the empirical studies developed to date, highlighting the main existing indicators on tourism competitiveness that have come to be used at the international level, putting emphasis on the applied methodology.
\n
\n
2.1. The conceptual framework of tourism competitiveness
\n
The conceptual framework of tourism competitiveness is based on the pioneering studies that began to be published at the end of the twentieth century and the start of the twenty-first, fruit of the scientific activity of [2,18–20], among others. In [19], the competitiveness of one tourism destination with respect to another is defined as its increasing capacity to attract visitors, together with the increase in total tourist spending, offering them rewarding, satisfactory experiences. These authors also specify that an improvement must be produced in the well-being of the residents of the tourism destination, as well as continuity in the growth of the natural capital of the destination for future generations.
\n
However, and despite the ease there may be a priori when exploring the registry of data that allow the determination of the degree of attraction of a geographical location, the measurement of tourism competitiveness is a complex task, as, in agreement with [21], it is an abstract concept, not directly observable and with a multidimensional character resulting from the sum of variables, many of them compared to those of another tourist destination that is taken as a reference. Therefore the measurement of competitiveness can be subjective and depend on factors such as the approach of the researcher, the aim of the research, etc., thereby enabling the existence of diverse models of competitiveness. In agreement with [2], to suitably measure the competitiveness of tourism destinations, it is advisable to distinguish between the comparative and competitive advantages of a tourism destination. In [22] the comparative advantages are defined as the tourism heritage of the destination, as opposed to the competitive advantages which are those that arise when planning, management and marketing policies are applied to the comparative advantages.
\n
From this differentiation between comparative and competitive advantages, different authors have proposed several models to explain tourism competitiveness. In [22], the competitiveness model of [1–4] is indicated as being among the most significant. A commonality of these models is an interrelated set of diverse elements that influence tourism competitiveness, thus recognising that competitiveness is a clearly multidimensional fact, which can be characterised by indicators of both an objective and subjective nature, as stated in [23].
\n
\n
2.1.1. Porter’s model
\n
Porter’s [1] model of competitive advantage, also called “Porter’s Diamond”, presents a methodology for establishing enterprise strategies to achieve greater competitiveness in a globalised economy. In this model, the competitiveness of the companies of a country does not depend only on the natural and favourable factors that the country may have a priori, but also on those that can doubtlessly be generated by positive or negative synergies and which have the ultimate goal of productivity growth. Thus, the competitiveness model of [1] establishes that the competitive position of the companies is very much influenced by their surroundings, which in turn depend on certain “primary factors”, these being understood as the state of the productive factors; the existence of qualified human resources; the conditions of the demand, such as tastes and their variations; the characteristics, existence and development of the associated sectors; as well as the enterprise strategies. There are also “secondary factors”, which influence the primary factors, which are the actions of local government and fortuitous events.
\n
\n
\n
2.1.2. The Crouch-Ritchie model
\n
The Crouch-Ritchie competitiveness model [2] was the first of the models presented to evaluate the tourism competitiveness of the ‘long-haul’ destinations. It can be considered, in agreement with [8], to be the main reference model on tourism competitiveness made to date. This claim is based on the fact that the model includes all the important factors that may determine the competitiveness of a tourism destination. In [8], it is considered that this model is neither predictive nor causal, but simply a conceptual model, as its intention is nothing more than to explain the determining factors of tourism competitiveness, by using abstract concepts and relationships.
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The authors of this model consider that the competitiveness of the destination is primarily conditioned by both the competitive environment (micro) and by the global environment (macro). With the first concept, the authors refer to the immediate environment to which the destination has to adapt to compete, and which is composed of the different agents which operate in the tourism sector. The second concept is shaped by those global forces which change the composition and nature of tourism practice in the destination.
\n
The main resources and attractions of the local geographical enclave are established as the third theoretical element of the model. This component includes all the assets that motivate the visit to the tourism destination. These resources are grouped into six large categories: the physiography; the culture and history; the market restrictions; the range of leisure activities; special events; and, the tourism superstructure.
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The fourth element is made up of the so-called complementary factors and resources, which form the base on which the tourism industry must develop. They include the general infrastructure of the destination, the enabling resources, the vitality and the enterprise sense, as well as the accessibility of the destination.
\n
The fifth element of the model refers to the management of the destination. This includes those activities which increase the interest in the main resources. Among these activities can be mentioned the marketing actions, such as promotions or the marketing of package tourism. Lastly, local endogenous determinants are established as elements of the model.
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\n
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2.1.3. Kim’s model
\n
The third of the basic models of tourism competitiveness is that of Kim [3], which considers four sources of tourism competitiveness:
The economic agents that are involved in the tourism process, the environment and tourism resources which make the place attractive to the tourist.
The tourism policies: the planning, management, investments made in the sector, taxes applied to tourism activities and the prices of the services of the sector or the prices of other sectors directly related to it.
The tourism infrastructure, the system of accommodation of the visitors, the publicity and the qualification of the human resources.
The tourism demand itself, the employment generated by the sector, the tourism behaviour and the tourism export, which are the result of the three first sources of competitiveness.
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\n
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2.1.4. The Dywer-Kim model
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The model proposed by Dywer and Kim [4] is a comprehensive model, which suggests an outline for determining the competitiveness of a country as a tourism destination. This model has many points in common with the model of [2], although some important new features are introduced:
Firstly, it establishes that the base of the tourism competitiveness is supported by three elements: the inherited resources, the created resources and the complementary resources, in turn grouping these into one superior structure because they provide the characteristics that make a tourism destination attractive to the visitors.
Secondly, governmental management of the destination is an important point to consider in its competitiveness. Therefore, all those factors are included which, in one way or another, strengthen the attractiveness of the local tourism resources and which adapt to their particular conditions. Although the model of [2] already made reference to these questions, the model of [4] introduces questions relating to the conditions of demand as a determinant of the competitiveness.
Thirdly, the model considers that although the competitiveness of the destination depends on the previously mentioned determinants, these also influence socioeconomic prosperity in the sense that the competitiveness of the destination is, in itself, also an intermediate objective towards the socioeconomic well-being of the residents. Table 1 contains a summary of the main components of each of the mentioned models of competitiveness.
\n
\n\n
\n
Porter
\n
1990
\n
Elements of the model
\n
\n
\n
\n
Conditions of the productive factors
\n
\n
\n
Conditions of the demand
\n
\n
\n
Related and support industries
\n
\n
\n
Rival strategies, structures and companies
\n
\n
\n
\nCrouch-Ritchie\n
\n
1999
\n
\nElements of the model\n
\n
\n
\n
\n
Competitive environment (microeconomic)
\n
\n
\n
Competitive environment (macroeconomic)
\n
\n
\n
Main factors and resources
\n
\n
\n
Complementary factors and resources
\n
\n
\n
Management of the destination
\n
\n
\n
Local determinants
\n
\n
\n
\nKim\n
\n
2001
\n
\nElements of the model: competitiveness sources\n
\n
\n
\n
\n
Primary sources: agents (politicians, employees, travel agents, etc.), environment and resources (historical, cultural and natural)
\n
\n
\n
Secondary sources: tourism policy, planning and management of the destination, investments, tourism taxes and prices
\n
\n
\n
Tertiary sources: tourism infrastructures, system of accommodation of the visitors, attraction of the resources, publicity and qualification of the human resources
\n
\n
\n
Quaternary sources (resulting from the previous ones): tourism demand, employment generated by the sector, tourism behaviour (growth rates, balance of payments of the sector, participation of the sector in the GNP of the country or region, etc.) and tourism export
\n
\n
\n
\nDywer-Kim\n
\n
2003
\n
\nKim’smodel + New features\n
\n
\n
\n
\n
Factors that influence the competitiveness of the destination:
\n
\n
\n
Basis of the competitiveness of the tourism destination
\n
Inherited resources
\n
Competitiveness of the destination: intermediate objective
\n
\n
\n
Created resources
\n
\n
\n
Complementary resources
\n
\n
\n
Local conditions
\n
Management of the destination
\n
\n
\n
Conditions of the demand
\n
\n
\n
Factors influenced by the competitiveness of the destination:
\n
\n
\n
Socioeconomic prosperity: productivity levels of the economy, added levels of employment, income per capita,rate of economic growth, etc.
\n
Socioeconomic well-being of the residents: final objective
\n
\n\n
Table 1.
Summary of the main elements of the Porter, Crouch and Ritchie, Kim and Dywer-Kim competitiveness models.
3. Empirical advances of tourism competitiveness: international indicators
\n
Those theoretical or conceptual models of tourism competitiveness have also brought about a very considerable empirical advance [5–9,20,24–28]. The models proposed in those works have emphasised the need to define tourism competitiveness by means of a set of interrelated variables, which necessarily have to be measurable to be able to assess that competitiveness. This has led to interest in a large variety of indicators that are being proposed in the economics literature. These indicators are those that make reference to inputs and other results, or outputs and other instruments [6], those that are directly linked to competitiveness with other tourism areas, and those that are related to more general elements that can affect this competition. There are authors who offer a list of indicators of competitiveness of tourism destinations [26,29].
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The case study of [29] lists more than 150 indicators of competitiveness of tourism destinations, grouped into different categories (inherent resources, 11; created resources, 21; complementary factors and resources, 28; management of the destination, 34; local conditions, 25; conditions of the demand, 4; and other indicators of a macroeconomic nature and of socioeconomic prosperity, 32). Also, the study of [26] lists a lower number of indicators (68), although it is sometimes difficult to find the value of those indicators in all the analysed destinations.
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Along this line, some institutions have echoed the need to provide data for the construction of tourism competitiveness indicators, and it is possible, above all, to highlight the World Travel and Tourism Council (WTTC) and the World Economic Forum (WEF).
\n
\n
\n
3.1. Indicators of the World Travel and Tourism Council
\n
In 2001, the WTTC, in collaboration with the Christel DeHaan Tourism and Travel Research Institute (TTRI) of the University of Nottingham, put into practice a Competitiveness Monitor (CM), with 65 tourism competitiveness indicators classified into eight dimensions (competitiveness in prices, human tourism, infrastructure, environment, technology, opening tourism, social development and human resources), to measure the degree of tourism competitiveness of almost 200 countries, by means of the production of multi-variant reference indicators [10]. The methodology used began with the standardisation of 23 previously selected indicators, calculating the standardised value (yij) for each of them.\n
The indicators vary between 0 and 1; with the 1 value corresponding to countries with the maximum value of the indicator, and 0 to the countries with the minimum value. In the case that the relationship between the indicator and the degree of competitiveness is inverse, a procedure of inverse standardisation is applied.
Once the indicators are standardised, an aggregate index of the eight dimensions of the previously defined competitiveness is defined. This index is an arithmetic mean of the standardised values of the indicators of each dimension:
where Sik is the value taken in country i with aggregate indicator from the group k, which is made up of m simple indicators; that is, superscript k (k = 1, 2,…, 8) reflects eight dimensions and m the number of indicators necessary to measure them.
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The simple indicators that comprise each aggregated indicator are shown in Table 2.
\n
\n\n
\n
\n
\nIndicators\n
\n
\n\n\n
\n
\nCompetitiveness of prices\n
\n
Hotel price index PPP (Purchasing Power Parity Index)
\n
\n
\n
\nHuman factor\n
\n
Participation index Tourism impact index
\n
\n
\n
\nDevelopment Infrastructures\n
\n
Highway Index Health facilities Drinkable water facilities
\n
\n
\n
\nEnvironment\n
\n
Population density CO2 issues International Treaty relations
\n
\n
\n
\nTechnological development\n
\n
Internet terminals Telephone and mobile lines High technology exports
\n
\n
\n
\nHuman resources\n
\n
Education index
\n
\n
\n
\nOpening tourism\n
\n
Visas Opening tourism Opening trade Rates of international trade
\n
\n
\n
\nSocial development\n
\n
Human development index Newspapers Personal computers Television sets
\n
\n\n
Table 2.
WTTC indicators of competitiveness.
\n
This methodology, in spite of obtaining eight aggregate indices, does not synthesise all the information in a single competitiveness index, because each of the eight aggregate indices corresponds to a different competitive dimension. In general, two disadvantages are attributed to it: i) the index Sikdoes not use all the indicators available due to the deficit of statistical information on them, many countries being excluded from the global calculation; and ii), each Sikis obtained as a simple sum of the standardised indicators, without the indicators having been weighted in the calculation of the aggregate indices.
\n
With the aim of constructing a weighted aggregate index of tourism competitiveness, in [30] a definition is given for the aggregate index Zi for each dimension (I), from the weighted average of the indicators proposed by the WTTC. The weight (ω)of each of these is obtained by means of a confirmatory factor analysis, with those weights or weightings being the slopes of the confirmatory factor analysis: Zi=∑k=18ωkIik.
\n
It is possible to say that, in [30], the simple arithmetic mean is used in the construction of the indicators of the groups, where as for the construction of the synthetic indicator, they use the weighted mean, where the weightings are constructed from the value of the slopes of the confirming factorial analysis. The weights or weightings of the indicators obtained in [30] were as follows: Technology (0.220), Social Indicator (0.217), Human Resources (0.153), Price (0.147), Opening (0.126), Infrastructure (0.101), Human Factor (0.033) and Environment (0.003). From this synthetic indicator, in [30] it was concluded that the more competitive tourism destinations were, in sequence, the following: The United States, Sweden, Norway, Finland and Australia.
\n
This proposal, although allowing a comparison to be made between a large number of countries, presents the following two main disadvantages: one resides in the results themselves, because, with the exception of the United States, none of the other countries indicated as the most competitive from the tourism point of view, appear in the list of the most visited countries of the world; the other is that it grants a very secondary role to the environmental factor [25]. Nevertheless, numerous studies, such as those of [2,31], indicate natural and environmental resources as one of the main attractions of a destination.
\n
\n
\n
3.2. Indicators of the World Economic Forum
\n
The other competitiveness model initiative, relatively accepted throughout the world since 2007 [6], is the Global Travel and Tourism Competitiveness Index (TTCI) proposed by the WEF. This index appears structured into three sub-indices. Each sub-index is composed of a series of pillars composed of variables, which measure the competitiveness of each of those three blocks.
Sub-index A. Regulatory Framework. Pillar 1. Regulation. Pillar 2. Environmental sustainability. Pillar 3. Security and protection. Pillar 4. Health and hygiene. Pillar 5. Prioritisation of the tourism activity.
Sub-index B. Business and infrastructure environment: Pillar 6. Ait transport infrastructure. Pillar 7. Terrestrial rail and road transport infrastructure. Pillar 8. Tourism infrastructure. Pillar 9. CIT infrastructure. Pillar 10. Competitiveness of prices in the tourism sector.
Sub-index C. Human, cultural and natural resources: Pillar 11. Human resources. Pillar 12. Compatibility of the tourism activity. Pillar 13. Natural resources. Pillar 14. Cultural resources.
\n
The indicators result from the combination of hard data from various official data sources, and soft data or “survey data”, which come from opinion surveys of executives from leading companies in each country. These data are included in the Executive Opinion Survey of the World Economic Forum.
\n
The hard data are rescaled between one and seven, directly or inversely based on the influence that the variable exerts on the competitiveness of the tourism destination, increasing it or reducing it.
\n
The numeration of the rescaling is identical for the surveys. The value of the index is from one to seven, calculated as the arithmetic mean of the three sub-indices, where the value of each of these sub-indices is calculated as the arithmetic mean of each one of the pillars, and these also, as the arithmetic mean of each of the individual variables of which it is composed (a total of 73 variables), all rescaled from one to seven. Among the main disadvantages of this proposal is that it always uses the simple arithmetic mean, which is why all the individual indicators (pillars) take part with the same weighting in the production of the sub-index, and all the sub-indices with the same weighting in the construction of the index.
\n
In agreement with the latest Global Competitive Report [32], Switzerland takes first place in the ranking of countries with greater tourism competitiveness, followed by Singapore, Finland, Germany and the United States.
\n
\n
\n
4. Tourism competitiveness and economic growth
\n
As previously stated, the importance of tourism activity as a source of development and growth has been highlighted by numerous institutions at global level [33,34]. Nevertheless, this visibility has not rested there, as a strong scientific interest has arisen in the academic sphere regarding the study of this subject. Thus, some economists, such as [35], and more recently [36], suggest that tourism activity can promote the growth and development of countries, especially because international tourism can bring in foreign currencies that are used for the financing of capital assets, which allow improvements to be made in the production of goods and services. In that sense, in 2013, the international income through tourism represented 30% of global export services, and 6% of the total global exports of goods and services [37].
\n
For other economists, however, tourism activity can generate growth simply because it is a “large industry”. It is more — it can be considered the largest industry at global level [38]. As such, in agreement with [34], in 2013, the total contribution of tourism to the global economy reached 9.5% of global GDP (7 trillion U.S. $), generating a total of almost 22 million jobs, which represents one in ten jobs on the planet, of which 9 million jobs, 4.1% of the total global employment, can be considered jobs directly related to tourism.
\n
Therefore, the sector has a large capacity to generate employment and to increase the value of its production and tax revenue, as stated by different authors [39–45]. These tax revenues, can promote economic development policies, by seeking efficiency through greater competition between the local companies and others of different tourism destinations [46,47], thereby facilitating the use of economies of scale [48].
\n
In many studies, the role of tourism activity is recognised as a driving force of economic development [14,15,49–52]. However, most of these studies do not analyse whether this growth is later translated into an improvement of the economic progress or the well-being of the population. They do agree, however, that the growth of the well-being is noticeably inferior to the growth of the GDP, admitting that the increase of tourism production contributes to development, at least up to a certain level of income, to which very few countries could have arrived without the tourism activity [53]. Therefore, these scientific shortcomings suppose a broad and important field for analysis and study.
\n
In other more recent studies, tourism competitiveness is linked with growth in certain economic areas [2,4,54–57]. This has generated new research giving rise to an academic debate about the manner of measuring this competitiveness [9,58]. Beyond these measurements, a number of emerging studies emphasise the role of some factors, generally linked to economic growth, as determinants of a greater tourism competitiveness, and therefore of the improvement or growth of the tourism sector [59,60]
\n
All this seems to highlight that tourism competitiveness, the growth of tourism activity, the economic growth and the production factors are variables that can be related.
\n
\n
4.1. Tourism activity and economic growth
\n
Ever since [11] originally analysed the hypothesis known as tourism-led growth (TLG), i.e., tourism generates economic growth, studies have proliferated which, although agreeing in linking tourism activity and economic growth, present clear differences in the scale of this link. The scale seems to be related to the methodology used, the temporal and territorial framework of study, and the form of measuring the tourism activity in each case [61].
\n
In [61], it was shown that most of the studies are based on the use of time series [62–70], other studies were based on a cross section analysis [49,71–73], and finally some studies used panel techniques, such as those of [12,74–77]. In the afore-mentioned study [61], it was shown that, up to the start of 2013, 87 studies that empirically analysed the relationship between tourism activity and economic growth had been published . Of those, 55 showed the existence of a causality relationship that runs from tourism activity to economic growth, whereby the TLG hypothesis is verified or supported. Of the other published works, 16 identified a two-way relationship between the variables, 9 found a causality relationship between economic growth and tourism activity, and 4 did not find any type of relationship between both variables.
\n
However, the authors state that, even though most of these studies show that there is a link between tourism activity and economic growth, there are clear, simultaneous, differences between the different studies in the magnitude of this link. This magnitude variation seems to be associated with the methodology used, the temporal and territorial framework referred to in each study, and the form of measuring the tourism activity in each case
\n
In a similar direction, the methodological strategies used in the studies that analyse the TLG hypothesis have recently been reviewed, also showing differences in the magnitude of this link based on the methodologies used, as well as on the variable used to measure tourism activity [78]. These conclusions have been ratified by the meta-analysis made in [79]. In that study, important differences are demonstrated referring to the short or long term, the use of additional variables of economic growth in the explanation of the model and the use of different methodologies to measure the tourism activity.
\n
In this regard, the study significantly shows that the value of the effect of tourism on economic growth in the long term, depends on whether the effect of other economic variables on growth is also taken into account, such as physical or human capital, in which case, the effect of tourism activity on growth diminishes remarkably. Thus, these variables should not be excluded from the analysis, if it is required to adequately show in which way tourism activity contributes to economic growth.
\n
\n
4.1.1. The measurement of tourism activity in studies of economic growth
\n
Tourism activity has been measured in various ways to be able to make econometric estimates that serve as the basis for the study of the relationship of that activity with economic growth. There are researchers who use the income obtained by international tourism as a measure of tourism activity [62,65,80–83]. Others use the number of non-resident tourists who visit the country [84–86]. The choice of indicator is of special importance, because, as stated in [79], the way in which tourism activity is evaluated will also affect its elasticity of productivity. Thus, if tourism activity is measured by the income that it generates, then the elasticity will tend to be greater than if it is measured based on visitor numbers.
\n
Additionally, other studies use the people registered in hotels [87], the number of overnight stays of foreigners in hotels [88], the income obtained by the hotel industry [89], the sales income in hotels and restaurants [90], or the cost in tourism [91]. All these ways of measuring tourism activity have the commonality that they are measured from the point of view of demand, which supposes that economic growth is linked to demand. A perspective that has been criticised by several economists, as it does not allow the contribution of tourism to economic growth to be suitably demarcated [92].
\n
In this regard, new approaches [93] have recently appeared that use the TTCI to measure the contribution of tourism activity to economic growth, analysing if this activity stimulates economic growth in the most competitive destinations. However, this study does not consider the role that other productive factors, such as capital investments, have in economic growth.
\n
\n
\n
4.1.2. Tourism activity, economic growth and other productive factors
\n
The need to consider other productive factors when analysing the relationship between tourism activity and economic growth has been demonstrated by [12]. Despite this, there has been little inclusion of additional factors in the study of the contribution of tourism activity to growth. Thus, of the 87 studies reviewed in [61], only 16 include other determining factors of economic growth, with only 5 studies incorporating these variables when the analysis is made using a time series [12,63,68,94,95]. The economic factors that are included refer to private or public (infrastructures) capital stock, human capital and technological capital. There are only a few studies that also include other factors, such as the indicators of freedom [96] or life expectancy [97].
\n
In spite of the small number of studies that introduce these factors into the analysis, in [79] the importance of their inclusion is shown for suitably measuring the contribution of tourism to growth. Thus, these authors indicate that the inclusion of additional variables tends to diminish the value of the elasticity of productivity with respect to tourism activity.
\n
\n
\n
\n
4.2. Competitiveness, tourism and economic growth
\n
From the previous analysis, it is deduced that the increase of tourism activity seems to contribute positively to economic growth, although the way in which it does so, its magnitude, as well as the generalisation of this contribution to the growth of all the countries or time periods, are questions that remain open today. It is possible that this is because the factors that favour economic growth and the relationships among them are not always suitably taken into account.
\n
Tourism is usually seen as an element that favours the economic growth and development of countries and regions [98]. It is assumed in the extensive literature on competitiveness and tourism, as affirmed in [93], that the more competitive a tourist destination is, the more tourists it will attract, bringing an increase in income through this sector, which will lead to an increase of production and economic growth. However, this link does not seem to be so clear for some other economists, for whom a greater number of tourists also supposes greater imports of goods to satisfy their needs, the repatriation of profits to other countries when the tourism companies have foreign capital, or the sale of tourist objects at very inferior prices to those of the market or under very favourable conditions [99–101].
\n
In this regard, recent studies do not find empirical evidence in favour of the argument that a greater tourism competitiveness generates a greater contribution to economic growth [93], which seems to suggest that, by not assessing the relationship between tourism and other productive factors, their conclusions may be biased. Several aspects can be taken into account when analysing these relationships.
\n
Firstly, the indicators of tourism competitiveness include a wide number of economic variables that form part of the public capital, private capital, and human capital. This is why those competitiveness indicators are influenced by productive factors that determine economic growth. Secondly, the relationship between tourism and growth also involves some difficulties in its study. These occur when tourism is measured by income or by number of tourists, thus making reference to demand variables, or when physical and human capital and infrastructure are used to explain the effects of tourism and economic growth, when the studies seem to suggest that tourism depends on competitiveness, which in turn depends on productive factors.
\n
Also, and in relation to this question, it is possible to say that the study of these effects of tourism on economic growth are affected by other essential variables to explain the growth, such as the physical and human capital, and the infrastructure. Therefore, if they are not included to explain the growth, the study will be biased, but if they are included it will also be biased if it is thought that tourism depends on competitiveness, and this on the productive factors.
\n
\nFigure 1 shows the relationships between competitiveness, tourism and growth, where competitiveness depends on tourism, tourism generates growth and the growth depends on the productive factors which affect tourism competitiveness.
\n
Figure 1.
Relationships between competitiveness, tourism and growth in previous studies. (Source: Own production).
\n
Alternatively, in this study, a new conception of those relationships between competitiveness, tourism and growth is proposed, where the provision of those inherited resources, together with the provision of productive resources and the links between them are the determining elements of the capacity of an economy to produce, and therefore to grow. Figure 2 presents this new conception of the relationships between competitiveness, tourism and growth. The analysis of this new conceptual framework involves the need to determine or to evaluate the productive factors, on the one hand, and on the other to determine those tourism resources, by means of some type of indicator, which can be called inherited, and which are not directly affected by the productive factors. This analysis can be based on the methodologies that have previously been developed to define tourism competitiveness.
\n
Figure 2.
Relationships between competitiveness, tourism and growth: New conceptual framework. (Source: Own production).
\n
The tourism variable that is included in the model does not depend on demand factors, as in the previous models in which tourism is measured by tourism derived income or number of tourists [62,65,80–86]. Neither does it depend directly on productive factors, such as physical and human capital. This variable refers to the conditions of the territory that motivate the tourism offer of a geographic zone. However, what should be included in the concept of inherent tourism resources is an undefined question, as has been shown in the measurement of tourism competitiveness in previous studies. Thus, the Crouch and Ritchie [2] model of competitiveness refers to the main resources and attractions of the local geographic enclave, which include landscape and climatic characteristics and the monumental and historical-artistic heritage. The model of Kim [3] refers to the tourism resources which make the place attractive to the tourist. The model that Dywer and Kim [4] propose establishes the term of inherited resources. Dywer et al. [55] highlight the so-called inherent resources among the tourism resources. The WEF Indicator includes factors such as environmental sustainability and natural and cultural resources [34].
\n
In general, it seems that in certain territories a series of elements exist that make those places interesting for the tourist, and which seem to be related to the culture, the environment and the climatic situation. These resources are numerous, and some of them have been protected throughout the last century, for their interest, showing that they are recognised as elements of attraction for some of the reasons indicated previously. Therefore, from the measurement of those elements, it can be possible to produce an indicator, with the tourism competitiveness measurement techniques indicated previously, such as those applied in the TTCI or CM, including only the elements related to culture, environment and climatic situation.
\n
Additionally, the proposed model of study includes other productive variables, such as human and physical capital. In this model, these variables interact with the tourism variable, in such a way that relationships of complementariness or substitutability can be defined among them. All these variables and their relationships finally affect the economic growth. Thus, the definition of this model includes other productive factors for analysing the effect of the elements relating to tourism on economic activity, following the studies of [12] and [79]. Although, the inclusion of these other productive factors in this model does not generate biased results, as the definition of the tourism variable in this case does not include, nor depend upon, those same productive factors.
\n
Therefore, this model considers that the territories have a series of resources that are attractive for tourists, and which, based on their interaction with the physical and human capital existing or developed in the territory, can positively affect the economic growth. These tourism variables thus have an effect on the economic growth, although that effect would additionally depend on the relationships with the other productive variables of the territory.
\n
\n
\n
\n
5. Conclusions
\n
From the start of the present millennium, an increasing number of studies have been analysing the causes that determine the competitiveness of tourism destinations, this being understood as the capacity of certain territories to attract visitors.
\n
However, the measurement of competitiveness and its analysis are not simple, as it is a concept that is not directly observable and has a multidimensional character. In order to suitably measure the competitiveness of tourism destinations, the comparative and competitive advantages of a tourism destination are distinguished, thus differentiating between the factors and resources which a destination has and the measures implemented by the destination to efficiently manage its resources. From this differentiation between comparative and competitive advantages, several models have set out to explain tourism competitiveness. Among them are highlighted Porter’s model of competitiveness, the Crouch and Ritchie model of competitiveness, Kim’s model of competitiveness and the Dwyer-Kim model of competitiveness. All these models have an interrelated set of diverse elements or factors that influence tourism competitiveness.
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These conceptual models have brought about a very considerable empirical advance in recent years. These applied models have the commonality of the need to define competitiveness by means of a set of interrelated variables, which are to be measured in some way to be able to evaluate this competitiveness. Thus, a large variety of indicators have been used as a means to measure competitiveness. From different spheres, numerous institutions have been offering data which allow the production of these indicators; along this line can be highlighted mainly the WTTC and the WEF at international level.
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The most commonly used methodology for the production of the different indices of competitiveness can be synthesised in two stages. In a first stage, the indicators are selected and usually ordered into groups, they are typified and directly or inversely standardised. In a second stage, an aggregate index is calculated for each of the previously defined groups. Later, another aggregate index is calculated from the indices calculated for each group. There are two main procedures for calculating the aggregate indices. The simplest one is calculated as the arithmetic mean of the standardised indicators. Alternatively, this aggregate indicator can be calculated from a weighted mean of the proposed indicators, where the weight of each of these is obtained by means of a confirming factorial analysis.
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The interest shown in measuring tourism competitiveness is related to the economic income that tourism can generate and, with it, the boost to the economic growth of its territories. Thus, there are many scientific studies which recognise the role of tourism activity as a driving force of growth and economic development. An important and increasing number of scientific studies have been made on this subject since 2002, showing that there is a link between tourism activity and economic growth, although a clear differences exists between the different studies in the magnitude of this link. In this sense, there are two key elements. Firstly, that the different ways to measure tourism activity play a key role when determining the magnitude of its relationship to economic growth, and, secondly, that the results of the analyses that study the relationship between both variables depend on the consideration of other variables or factors that affect economic growth.
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In these studies, all these forms of measuring tourism activity have the commonality of measuring from the point of view of demand, which supposes linking economic growth to demand, a perspective that has been criticised by several economists. On the other hand, if it is required to suitably measure the way in which tourism contributes to economic growth, it is considered necessary to observe other productive factors when analysing the relationship between tourism activity and economic growth. However, there has been scarce inclusion of additional factors in the study of the contribution of tourism activity to growth.
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Thus, the increase of tourism activity seems to contribute positively to economic growth, although the way in which it does so, its magnitude, as well as the generalisation of this contribution to the growth of all the countries or time periods, are questions that remain open today. Therefore, it seems that a relationship can be defined that links greater tourism competitiveness with an increase of tourism activity, and another that relates an increase of tourism activity to greater economic growth.
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However, several aspects have to be considered when analysing these relationships. Firstly, the indicators of tourism competitiveness of the destinations include abroad number of economic variables that are comprised of the public, the private and the human capital of the territory. Thus, the competitiveness indicators are influenced by productive factors that directly affect economic growth. Secondly, tourism is usually measured by income or number of tourists, which involves linking a demand variable with economic growth. In addition, this relationship between tourism and economic growth is affected by other variables, such as physical and human capital and infrastructure again. Therefore, if these variables are not included to explain the growth, the study will be biased, but if they are included it will also be biased if it is thought that tourism depends on competitiveness, and this on these productive factors.
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In these chapter, it is considered that these relationships can be seen from an alternative point of view, in which the territory has a series of qualities or resource provisions that make it especially attractive to tourists, and which are not themselves affected by the productive factors, which are called inherited resources. The provision of those resources in a territory, together with the provision of productive resources, such as private or public capital and human capital, and their linking together, that is to say, the relationships of complementarity or substitutability that exist between them, are the elements which determine the capacity of an economy to produce, and therefore to grow.
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Acknowledgments
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The authors wish to express their gratitude for the funding provided by the SEJ-132 project
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\n',keywords:"Tourism, Economic Growth, Competitiveness, Model, Review",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/50140.pdf",chapterXML:"https://mts.intechopen.com/source/xml/50140.xml",downloadPdfUrl:"/chapter/pdf-download/50140",previewPdfUrl:"/chapter/pdf-preview/50140",totalDownloads:2846,totalViews:934,totalCrossrefCites:2,totalDimensionsCites:5,totalAltmetricsMentions:0,impactScore:5,impactScorePercentile:92,impactScoreQuartile:4,hasAltmetrics:0,dateSubmitted:"September 24th 2015",dateReviewed:"January 22nd 2016",datePrePublished:null,datePublished:"May 4th 2016",dateFinished:"March 21st 2016",readingETA:"0",abstract:"This study reviews the theories relating to competitiveness and the indicators used for its measurement on the one hand and the studies that relate tourism and growth on the other, with the purpose of establishing the links that exist between both concepts. This enables a model to be defined in which some factors that affect tourism competitiveness combine with capital and work to determine economic growth. The provision of inherited tourism resources, together with the provision of productive resources, and the links between them are the determining elements of the capacity of an economy to produce and therefore to grow.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/50140",risUrl:"/chapter/ris/50140",book:{id:"5140",slug:"tourism-from-empirical-research-towards-practical-application"},signatures:"María del P. Pablo-Romero, Palma Gómez-Calero and Javier\nSánchez-Rivas",authors:[{id:"72663",title:"Dr.",name:"Maria Del",middleName:null,surname:"Pablo-Romero",fullName:"Maria Del Pablo-Romero",slug:"maria-del-pablo-romero",email:"mpablorom@us.es",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Seville",institutionURL:null,country:{name:"Spain"}}},{id:"184221",title:"Dr.",name:"Palma",middleName:null,surname:"Gómez-Calero",fullName:"Palma Gómez-Calero",slug:"palma-gomez-calero",email:"mdepalma@us.es",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"184222",title:"Prof.",name:"Javier",middleName:null,surname:"Sanchez-Rivas",fullName:"Javier Sanchez-Rivas",slug:"javier-sanchez-rivas",email:"sanchezrivas@us.es",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Tourism competitiveness: measurement indicators",level:"1"},{id:"sec_2_2",title:"2.1. The conceptual framework of tourism competitiveness",level:"2"},{id:"sec_2_3",title:"2.1.1. Porter’s model",level:"3"},{id:"sec_3_3",title:"2.1.2. The Crouch-Ritchie model",level:"3"},{id:"sec_4_3",title:"2.1.3. Kim’s model",level:"3"},{id:"sec_5_3",title:"Table 1.",level:"3"},{id:"sec_8",title:"3. Empirical advances of tourism competitiveness: international indicators",level:"1"},{id:"sec_9",title:"3.1. Indicators of the World Travel and Tourism Council",level:"1"},{id:"sec_10",title:"3.2. Indicators of the World Economic Forum",level:"1"},{id:"sec_11",title:"4. Tourism competitiveness and economic growth",level:"1"},{id:"sec_11_2",title:"4.1. Tourism activity and economic growth",level:"2"},{id:"sec_11_3",title:"4.1.1. The measurement of tourism activity in studies of economic growth",level:"3"},{id:"sec_12_3",title:"4.1.2. Tourism activity, economic growth and other productive factors",level:"3"},{id:"sec_14_2",title:"4.2. Competitiveness, tourism and economic growth",level:"2"},{id:"sec_16",title:"5. Conclusions",level:"1"},{id:"sec_17",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'\nPorter M. (1990). The Competitive Advantage of Nations. The Free Press: New York.\n'},{id:"B2",body:'\nCrouch G.I. and Ritchie J.B. (1999). Tourism, competitiveness, and societal prosperity. Journal of Business Research, 44, 137-152.\n'},{id:"B3",body:'\nKim C.H. (2001). Destination Competitiveness: Development of a Model with Application to Australia and the Republic of Korea. Korea Tourism Research Institute: Korea.\n'},{id:"B4",body:'\nDwyer L. and Kim C. (2003). Destination competitiveness. Determinants and indicators. Current Issues in Tourism, 6, 369-414.\n'},{id:"B5",body:'\nCroes R. (2011). Measuring and explaining competitiveness in the context of small island destinations. 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1. Introduction
Pneumonia is an acute lower respiratory tract infection caused by bacteria, viruses, or fungi. Groups of patients at high risk of getting pneumonia include children under 5 years old, people over 65 years old, and people with comorbidities. Pneumonia is the leading cause of death in children, and among the top four causes of death globally [1]. Each year, pneumonia kills more than 800,000 children under the age of 5, equivalent to about 2,200 children every day [2]. In the United States, the annual incidence of community-acquired pneumonia (CAP) was 248 cases per 100,000 persons [3]. A study in central Vietnam reported that the incidence of CAP in subjects aged ≥ 65 years was 4.6 per 1,000 person-years (95% CI, 3.8–5.5) [4]. Hospitalized patients diagnosed with pneumonia accounted for 19.9%, 6.4%, and 1.5% in the Philippines, Malaysia, and Indonesia, respectively. The total estimated costs incurred for pneumonia patients were in Malaysia 4.1 million USD, in Indonesia 2.6 million USD, and in the Philippines 2.6 million USD [5].
Drug-related problems are defined as ‘events or circumstances involving drug therapy that actually or potentially interfere with desired health outcomes’ [6]. Causes of DRPs can be related to inappropriate drug selection, inappropriate dosage, duration of use of medication longer or shorter than recommended, incorrect drug use processes, or poor compliance, all resulting in decreased treatment effectiveness and increased morbidity and mortality [7, 8, 9]. In Ethiopia, the proportion of patients hospitalized for infectious diseases, and who also had DRPs, was 71.51% (123/172); of these, the unnecessary broad-spectrum antibiotic option ceftriaxone accounted for 44.77% [10]. Similarly, in a study in Spain, almost half (45.1%) of hospitalized patients suffered from DRPs [11]. Common DRPs associated with pneumonia include inappropriate antibiotic indications, prolonged antibiotic treatment, and overtreatment, which may lead to potential drug–drug interactions [12, 13, 14, 15]. In the context of increasing antibiotic resistance, prescribing doctors, often concerned about possibly missing pathogenic bacteria, tend to prescribe broad-spectrum antibiotics over a longer treatment time to avoid recurrence of the disease. Fear, rather than lack of knowledge, is a major barrier to preventing overtreatment with antibiotics [16]. Therefore, a new method being considered for improving empirical antibiotic selection is the community-acquired pneumonia score. This score can be used in a prediction model of clinical data, enabling more accurate application of empirical antibiotics [17]. In addition, many intervention tools need to be applied, such as antibiotic management programs, biomarkers, and computerized physician order entries (CPOE), to ensure the effectiveness and safety of guideline compliance. The computerized physician order entry (CPOE) and clinical decision support systems (CDSS) are valuable technological tools for use in interventions to prevent adverse drug events (ADEs). However, in the healthcare system, the role of the clinical pharmacist in minimizing DRPs remains crucial [14]. The chapter is, therefore, to summarize an overview of DRPs in pneumonia and recommend some strategies for reducing these DRPs.
2. Drug-related problems in pneumonia
2.1 Improper drug selection and dose selection
Prescribing inappropriate antibiotics leads to increased mortality, the development of antimicrobial resistance, and added treatment costs [18, 19]. Meta-analysis of 7401 patients with ventilator-associated pneumonia (VAP), using unadjusted data, revealed that inappropriate antibiotic therapy significantly increased the mortality of patients (odds ratio [OR], 2.34; 95% CI, 1.51–3.63; P = 0.0001, I2 = 28.5%) [8]. A retrospective cohort study of bacteremic pneumonia, conducted in Barnes-Jewish Hospital in Missouri, USA (2008–2015) using multivariable logistic regression analysis for hospital mortality, indicated that inappropriate initial antibiotic treatment had the greatest odds ratio with mortality (OR 2.2, 95% CI 1.5–3.2, P < 0.001). The rate of inappropriate antibiotic initiation was significantly higher in patients with ceftriaxone-resistant pathogens than with ceftriaxone-susceptible pathogens (27.9% vs. 7.1%, P < 0.001), and the associated hospital mortality rates were respectively 41.5% vs. 32.0% (P = 0.001) [9].
Inappropriate antibiotic selection is one of the most common DRPs in patients with pneumonia, and particularly community-acquired pneumonia (CAP). Antibiotic prescriptions collected from 22 pharmacies in Mongolia indicated that inappropriate drug selection affected both adults (57.7%) and children (56.6%) [20]. A study among 518 outpatients with CAP in the Veterans Affairs Western New York Healthcare System indicated that 69% of patients received an inappropriate antibiotic; for 76.7% of them an incorrect drug had been prescribed, based on the patient’s comorbidities [21]. In Thailand, a prospective observational study of severe CAP in general medical wards showed that 52% of patients received initial antibiotic regimens that were discordant with IDSA/ATS guidelines [22].
The increase in resistance rates of bacteria to antibiotics leads to inappropriate selection of initial antibiotics. Due to an “encirclement” mentality, doctors often tend to choose empiric broad-spectrum antibiotics; this invisible cause increases antibiotic resistance, resulting in a “vicious circle” that increasingly burdens patients and society [23, 24, 25]. In particular, prescribing broad-spectrum antibiotics for a low-risk group increases the risk of unwanted effects rather than making treatment beneficial. According to current guidelines for the treatment of community-acquired pneumonia, an outpatient should receive beta-lactam or a macrolide or doxycycline [26, 27]. A retrospective chart review at a large hospital indicated that fluoroquinolones were antibiotics overprescribed for 71% of patients in the low-risk group [28]. Another retrospective chart review among 156 adult patients with a diagnosis of CAP, admitted to a community hospital emergency department in Canada, found that physicians overprescribed fluoroquinolones for 80.8% of patients who did not need them [29]. Over-prescribing of fluoroquinolones for outpatients with pneumonia increases the risk of side effects: tendon rupture, tendonitis, feeling shaky, unusual hunger, serious events of aortic ruptures or tears, and development of antibiotic resistance [30, 31, 32].
For this reason, antibiotic stewardship programs (ASPs) and clinical pharmacists play an important role in promoting the appropriate prescribing of empiric antibiotics. A retrospective cohort study of patients with CAP indicated a significant reduction in fluoroquinolone prescribing over time following intervention involving ASPs and clinical pharmacists [33]. An additional new method for improving empirical antibiotic selection is the community-acquired pneumonia score. This score provides a model of clinical data, thereby enabling the proper use of empirical antibiotics [17]. Implementation of an empiric therapy guide is important to minimize DRPs in the initial selection of antibiotics for pneumonia, as the causative organism and the patient’s susceptibility to it are often unknown at the time of prescription. Galanter KM et al. demonstrated that after intervention in accordance with the empiric therapy guide, the rate of broad-spectrum antibiotic indication for CAP decreased significantly, by 17.0% [34].
In Canada, a study on pneumonia showed that prescribed antibiotic doses tended to be higher than recommended [29]. In contrast, a prospective multinational study involving 68 ICUs across 10 countries confirmed that 20% of patients received less than the most conservative PK/PD target (50% f T > MIC), and fewer than 50% of patients received a preferred PK/PD target (100% f T > MIC) [13]. Such insufficient antibiotic exposure can also facilitate antibiotic resistance. For the treatment of CAP, especially critical patients require individualized dosing based on the severity of disease, local documented pathogen susceptibilities, and causal bacteria. Patient characteristics also play an important role in reducing mortality.
2.2 Drug interactions
Pneumonia patients often have not just one diagnosis but suffer from comorbid conditions. Frequent comorbidities are diabetes mellitus, cerebrovascular disease, chronic lung disease, chronic kidney disease, and dementia [15, 35, 36]. Common medication classes used for the management of comorbid conditions are cardiovascular agents, alimentary tract and metabolism agents, nervous system agents, respiratory agents, blood-forming agents, and general anti-infective agents for systemic use. The potential of drug–drug interactions in cases of pneumonia is more prevalent in older patients, possibly leading to chronic diseases and polypharmacy; some drugs even increase the risks of pneumonia [37]. In pneumonia patients, comorbidities have been strongly associated with long-term mortality [36], and concurrent use of multiple drugs can lead to an increased risk of drug–drug interactions (DDIs) [15, 35, 38]. Results of a study in a population, most of whom were concurrently using >10 drugs, revealed that 73.1% of these patients faced potential DDIs. Indeed, more than half of the patients presented with major potential DDIs [15]. Furthermore, nearly 75% of patients with community-acquired pneumonia (CAP) were subjected to polypharmacy [35].
Some clinical consequences of DDIs included increased or decreased therapeutic effectiveness, adverse drug reactions (ADRs), and toxicity (nephrotoxicity, hepatotoxicity) [15, 38]. DDIs can take place between different antibiotics, and between antibiotics and other medications. For treating pneumonia many guidelines recommend using β-lactams, macrolides, and fluoroquinolones. This may cause a prolonged QT interval (when fluoroquinolones or macrolides are administered) or a prolonged Prothrombin Time and International Normalized Ratio (INR) (if fluoroquinolones and warfarin are administered concurrently) [37]. Therefore, to prevent the negative effects of polypharmacy, consultations should be held to identify potential DDIs and alert physicians. Moreover, medical staff should refer to more than one drug interaction checker tool -- like Lexi-Interact, Micromedex, Medscape, Drugs.com. -- as well as adhere to guidelines for optimizing the use of prescribed drugs and discontinuing the use of unnecessary drugs.
2.3 Initiation and duration of administration antibiotic treatment
Patients whose initial appropriate antibiotics therapy is delayed may have increased morbidity rates compared to those receiving appropriately prescribed therapy on time. A systematic review in patients hospitalized with infections due to Klebsiella pneumoniae or Escherichia coli found that a delay in appropriate antibiotic therapy of more than 24 hours and 48 hours after culture collection, or in culture and susceptibility reporting, can increase the risk of mortality: OR 1.60 (95% CI, 1.25–2.50) and OR 1.76 (95% CI, 1.27–2.44) respectively [39]. A prospective cohort study in patients with VAP showed that for thirty-three patients (30.8%) the appropriate antibiotic treatment was delayed for >24 hours after they first met the diagnostic criteria for VAP; this initially delayed appropriate antibiotic treatment was a risk factor for increasing the hospital mortality rate (adjusted odds ratio, 7.68; 95% CI 4.50 to 13.09; p < 0.001) [40].
The British Thoracic Society Guidelines for the Management of Community-Acquired Pneumonia in Adults recommends the administration of antibiotics within four hours of admission to hospital for adults with radiologically confirmed CAP [41]. A large study (n = 13,725 from 188 institutions) conducted among adults hospitalized with CAP indicated that 37% of patients failed to receive antibiotics within four hours of admission. Delay time of the first antibiotic was associated with a greater OR of 30-day inpatient mortality. The adjusted 30-day inpatient mortality was lower for adults who received their initial antibiotic within four hours, compared with >4 hours (adjusted OR 0.84, 95% CI 0.74 to 0.94; p = 0.003) [42]. A retrospective study (n = 18,209) of Medicare patients older than 65 years who were hospitalized with CAP revealed that 39.1% did not receive antibiotics within four hours of admission. Initial administration of antibiotics within four hours, versus more than four hours, after arrival at the hospital was associated with reduced in-hospital mortality (6.8% vs. 7.4%; adjusted odds ratio (AOR)), 0.85; 95% CI, 0.74–0.98), versus mortality within 30 days of admission (11.6% vs. 12.7%; AOR, 0.85; 95% CI, 0.76–0.95), and length of stay exceeding the 5-day median (42.1% vs. 45.1%; AOR, 0.90; 95% CI, 0.83–0.96) [43].
For a long time, a seven-day application of antibiotic therapy to treat infectious diseases was standard procedure [44]. However, the duration of antibiotic treatment should be based on the severity of the disease, patient characteristics, patients’ clinical stability, and the causative organisms [45]. Long-term antibiotic treatment is associated with increased side- effects, antibiotic-resistant organisms, and C. difficile diarrhea [46, 47]. Unfortunately, a large study in 66,901 long-term care residents showed that 44.9% of patients were prescribed antibiotic treatment lasting longer than 7 days, and prescriptions tended not to be based on patient characteristics and comorbidities [14]. Furthermore, a retrospective cohort of 152,874 patients hospitalized for CAP found that more than 70% were prescribed antibiotics in excess of recommendations [48]. A large US study found that for 93% and 71% of patients with uncomplicated CAP and healthcare-associated pneumonia, respectively, lengthy durations of antibiotic treatment were indicated [49].
In addition, a systematic review of HAP in critically ill adults (including VAP) manifested that a short duration of antibiotic therapy (7 to 8 days) versus conventional antibiotic therapy (10 to 15 days) did not increase mortality rate, duration of mechanical ventilation, and length of hospital stay; however, a rise in recurrence was discovered in the subgroup of patients with VAP, caused by non-fermenting Gram-negative bacilli [50]. An RCT study in neonatal pneumonia conducted to compare the efficacy of a short course (4 days, intervention group) with a traditional antibiotic regimen (7 days, control group) demonstrated that treatment in the intervention group had the same success rate as in the control group, but the group intervention significantly reduced the length of the hospital stay, as well as antibiotic use and treatment costs [51].
For adults with CAP, although more relevant antibiotic studies are needed in the future to support a short-term therapy, clinicians should always be aware that the duration of antibiotic treatment should be based on the clinical improvement of the patient rather than mechanical practice. ATS/IDSA guidelines recommend a total duration of antibiotic therapy of 5 days for most outpatients and inpatients with CAP, except for cases of suspected MRSA or P. aeruginosa. According to the guidelines, the patient will achieve clinical improvement after the first 48–72 hours, after which antibiotics should be continued for 2–3 days [45]. Pending further studies, adherence to guidelines is one of the keys to limiting DRPs in treatment.
For pediatric patients with CAP, according to the 2011 PIDS/IDSA guidelines, which are still applicable today, the duration of treatment depends upon the severity. Treatment courses of 10 days are recommended, although the guidelines suggest that shorter courses may be just as effective, especially in mild patients. CA-MRSA patients may need a longer treatment period [26].
For adults with HAP/VAP, although the duration of antibiotic use is determined based on patients’ conditions like a clinical improvement, as well as radiological and laboratory parameters, the current recommendation for most patients is a 7-day course of antimicrobial therapy rather than longer treatment [52].
In conclusion, the high rate of prolongation of antibiotic treatment and inappropriate initiation of therapy in patients with pneumonia indicates the great need for improvement to reduce drug-related problems. Antimicrobial stewardship, biomarkers, and clinical stability scores should be applied to decrease the duration of antibiotic therapy [53, 54].
2.4 Comorbidities
Respiratory diseases have been found to be associated with multi-morbidity patterns [55]. Patients with pneumonia often have a broad range of comorbid conditions [37, 56]. While short-term mortality is directly associated with the severity of pneumonia, long-term mortality is associated with comorbid conditions [56]. Most patients who die from pneumonia have one or more severe chronic diseases, such as cerebrovascular disease, chronic cardiac or renal disease, dementia, cachexia, mobility impairment, neoplastic metastatic disease, or sepsis. Patients with either MRSA or Pseudomonas were found to have an increased risk of dying of pneumonia [57]. In patients with pneumonia, comorbidities are also associated with poor response to treatment. Moreover, patients older than 80 years with comorbidities also have a higher mortality rate than patients from other age groups [58].
All-cause mortality has been found to increase in relation to the number of comorbid conditions. Every comorbid condition has been found to correlate with a 9% higher risk of death [56]. Some comorbid conditions that influence mortality (cardiovascular and lung diseases, diabetes, etc.) are also particular risk factors for pneumonia [37].
The Charlson Comorbidity Index measures comorbidity. Patients with a higher Charlson pathology index score were found to have a higher risk of death due to hospitalization (OR 1.28; 95% CI 1.07–1.53). These findings indicate a relationship between a patient’s comorbid burden and the consequences of community-acquired pneumonia [59]. Results of a study among 108 patients by Franzen et al. indicated that the death risk of hospitalized pneumonia patients tended to increase with a higher CCI [58].
Children with comorbidities were more likely to be hospitalized for community-acquired pneumonia, compared to those without comorbidities. Approximately 50% of children and adolescents with community-acquired pneumonia had comorbidities related to malnutrition, as well as the use of antibiotics and hospitalization for community-acquired pneumonia during the previous 24 months. Bivariate analysis showed that patients with comorbidities demonstrated higher chances of malnutrition (p = 0.002), previous use of antibiotics (p = 0.008), and previous hospitalization for community-acquired pneumonia in the last 24 months (p = 0.004). In multivariate analysis, the following variables were independent predictors of community-acquired pneumonia in patients with comorbidities: malnutrition (p = 0.008; RR = 1.75; 95%CI 1.75–44.60); previous use of antibiotics (p = 0.0013; RR = 3.03; 95%CI 1.27–7.20); and previous hospitalization for community-acquired pneumonia (p = 0.035; RR = 2.91; 95%CI 1.08–7.90) [60].
In addition, pneumonia influenced concurrent comorbid conditions, resulting in a subsequent impact on the incidence of events like acute myocardial infarction, heart failure, stroke, venous thromboembolism, and cancer [56]. Recognition of the mutual relationship between pneumonia and comorbidities will help to identify patients at high risk. Though no specific guideline for multi-morbidities currently exists, close monitoring of patients during hospitalization and long-term follow-up may result in better outcomes.
2.5 Risk factors for DRP-readmission and pneumonia re-hospitalization
According to a review on drug-related hospital readmissions, an average of 21% of such readmissions were drug-related, and 69% were considered preventable [61]. Some predictive factors that can be considered to avoid hospital readmissions due to DRPs include limiting the number of drugs prescribed on a particular day, and the number of drug classifications according to the day of hospitalization [62]. Healthcare professionals should focus more on identifying risk factors related to drug-related readmissions, and on finding appropriate interventions.
Among the known risk factors for DRPs is non-adherence to medication, which may be aggravated by the complexity of the medication regimen. The medication regimen complexity index (MRCI) is a tool that assesses the complexity of a medication list in terms of dosage form, dosing frequency, and additional directions required for administration. Higher MRCI scores indicate greater regimen complexity. MRCI scores were significantly higher in patients readmitted (within 30 days) than those not readmitted [63, 64]. The MRCI can thus be used as a predictor of drug-related readmissions.
Another risk factor associated with 30-day readmission rates was the presence of comorbidities [65]. Comorbidities weaken the immune system and worsen a patient’s condition. The Charlson Comorbidity Index (CCI) is a tool that adds weighted scores to each illness predictive of mortality. Some studies have reported a higher mean CCI in patients who were re-admitted [62, 65]. As the CCI apparently has a strong potential to be a readmission predictor, it has been recommended for inclusion in readmission prediction tools [63].
Risk factors for pneumonia re-hospitalization are currently among the most important problems to be dealt with. Possible risk factors for early re-hospitalizations include male gender, age ≥70 years, the longer length of stay during the first admission, and a Multisource Comorbidity Score (MCS) ≥10. As for therapy, for readmitted CAP patients whose underlying respiratory disease has not yet been determined, the value of inhaled therapy has not definitely been decided. “Inhaled steroids may favor CAP in COPD patients, whereas anticholinergics may favor CAP in asthma patients. It is difficult to differentiate the effect of inhaled therapy from the effect of COPD or asthma severity on the risk of CAP, and these relationships may not be causal, but could call attention to inhaled therapy in COPD and asthma patients.” [66]. In pediatric patients infected with Mycoplasma pneumonia, readmission before 90 days after discharge is influenced by age, body temperature, and influenza A co-infection during hospitalization [67]. However, in adult patients, risk factors for readmission within 30 days after hospital discharge include the person’s age, hospitalization frequency during 3 months, chronic respiratory failure, heart failure, chronic liver disease, and the (non)availability of home healthcare [68].
A post-discharge study was performed in which researchers phoned every patient within 48–96 hours after they left the hospital to ask about their medication adherence, any adverse drug events (ADEs), and their use of medication. The process of medication reconciliation identified 103 errors, or 2.4 errors per patient, especially errors related to inaccurate doses, frequency, or medications not included on the list of home medications (Table 1) [69].
Interventions (n = 186)
n (%)
Medication reconciliation (n = 103)
Incorrect dose or frequency
49 (48)
Medication omitted
33 (32)
Medication added
14 (14)
Duplicate therapy
4 (4)
Counseled in nonadherence
3 (3)
Mean errors per patienta
2.4
Therapeutic recommendations (n = 38)
Change route
29 (76)
Optimize therapy
7 (18)
De-escalate therapy
2 (5)
Discharge counseling (n = 45)
Counseling on antibioticsb
33 (73)
Counseling on chronic medication changes
12 (27)
Table 1.
Medication errors identified, and pharmacist interventions.
n = 43 patients.
n = 39 patients were prescribed discharge antibiotics.
Note: All data are given as n (%) unless otherwise specified, and all percentages are rounded to the nearest whole number.
Multivariable analysis showed pneumonia-related readmission to be connected to para/hemiplegia, malignancy, pneumonia severity index class ≥4, and clinical instability ≥1 upon hospital discharge. Comorbidities such as chronic lung disease and chronic kidney disease, treatment failure, and decompensation of comorbidities were correlated with the pneumonia-unrelated 30-day re-hospitalization rate [65].
3. Strategies for reducing DRPs in pneumonia
3.1 Role of a clinical hospital pharmacist in patient care
Various interventions are needed, focused on reducing the risk of hospital readmissions by choosing transitional and territorial care and synchronizing post-discharge care [66]. Pharmacist-bundled interference was associated with a decline in the 30-day readmission rate for high-risk patients with pneumonia. Consequently, reducing hospital readmissions by supplying the greatest possible quality of health care is now becoming an essential consideration, also for the institutions themselves [69]. Also, identifying drug-resistant pathogens in pneumonia patients may help to determine the appropriate choice of empirical antibiotics. Further, building a model to define the patient’s risk factors may help with the prescription of broad-spectrum antibiotics [70]. Antibiotic administration for outpatients can be improved by predicting factors related to inappropriate antibiotic regimens. Patients at risk of drug resistance are now among the predictors of unsuitable antibiotic regimens [21].
The outcomes of this pilot research show that a pharmacist-specific bundled intervention, involving medication reconciliation, curative advice, patient discharge direction, and a research phone call, was associated with a decreased 30-day readmission rate for high-risk patients with pneumonia. The more than 200 total interventions reported suggest countless promising opportunities for increased pharmacist participation in care. Permitting pharmacists to devote time and effort to high-risk patient populations could confirm their value in supporting and expanding services to other people in the future, as well as reduce health care prices, and eventually the extent of welfare patient care [69].
Modifying the route of administration (ex- or intravenous to oral) was the most popular intervention, second to optimizing therapy. Optimizing therapy included making suitable renal doses and suggesting substitute regimens, especially if a patient’s inpatient antibiotic regimen was the same as an outpatient regimen that had failed, or if he or she had risk factors for a healthcare-associated infection. Regarding the element of discharge counseling in the intervention, 91% of patients chosen prospectively for a pilot study received such counseling. This single-center pilot research concentrated on the influence pharmacists can have on transitions of care and readmission rates, using interventions like medication reconciliation, therapeutic recommendations, discharge instructions, and follow-up [66].
3.2 Antibiotic stewardship programs
J.E. McGowan Jr. and D.N. Gerding were the first to create the term “antimicrobial stewardship” in an article published in 1996. They wanted to emphasize the need for appropriate antibiotic prescription in order to prevent resistance [71]. IDSA defined these as “antibiotic stewardship programs referring to coordinated interventions designed to improve and measure the appropriate use of antimicrobial agents” [72]. The 5 “Rs” of anti-microbial stewardship are: “the right drug at the right time with the right dose for the right bug for the right duration” [16]. The goals of ASP increase treatment effectiveness while reducing C. difficile infections, adverse effects, antibiotic resistance, hospital costs, and lengths of stay. Some activities related to antibiotic stewardship in CAP include monitoring the de-escalation and duration of antibiotic treatment, complying with treatment guidelines, switching from intravenous to oral antibiotic treatments, prospective auditing, and developing the multidisciplinary team [73]. Antibiotic stewardship contributes to rational prescription of antibiotics, increases treatment effectiveness, and reduces side-effects and antibiotic resistance. A multi-center, pre-empirical, quasi-experimental study including 600 CAP patients (307 in the historical control group and 293 in the stewardship intervention group) showed that antibiotic stewardship helped to increase guideline-concordance to the duration of antibiotic therapy from 5.6% in the historical group to 42% in the intervention group (P = 0.001). The intervention group received a significantly shorter mean duration of treatment than the historical group (6 (5–7) versus 9 (7–10) days, P = 0.001). Antibiotic stewardship helped to avoid a total of 586 days of unnecessary antibiotics during the 6-month intervention period, while incidence of readmission for CAP, mortality rate within 30 days post-discharge were similar in both groups [54]. A multicenter randomized trial including 312 hospitalized CAP patients found that the duration of antibiotic therapy as determined by the physician (control group) was longer than in the guideline-concordant group (intervention group): (median, 10 days [interquartile range, 10–11]) versus 5 days (interquartile range, 5–6.5), respectively; P < .001). Clinical success was similar between both groups, at both 10 days (48.6% versus 56.3%) and 30 days (88.6% versus 91.9%) after admission [73].
The major activities and elements of ASPs include [74]:
Hospital Leadership Commitment
Accountability
Pharmacy Expertise
Action
Tracking
Reporting
Education
Hospital Leadership Commitment: The senior leadership of the hospital, especially the chief medical officer, plays an important role in the success of ASPs. Hospital leadership helps to provide ASPs with the resources needed to achieve their goals.
Accountability: ASPs must have a designated leader or co-leaders, such as a physician and pharmacist, who have effective leadership, management, and communication skills, and are responsible for program management and outcomes.
Pharmacy Expertise: The participation of pharmacists, ideally as co-leaders of ASPs, will help to make ASPs highly effective. In large hospitals, pharmacists with infectious disease training are designated, but in hospitals without infectious disease trained pharmacists, general clinical pharmacists are appointed to help lead implementation efforts to improve antibiotic use.
Action: Antibiotic stewardship interventions are initiated to improve antibiotic use. Some activities related to antibiotic stewardship in CAP include prospective audit and feedback, such as monitoring the de-escalation and duration of antibiotic treatment, complying with treatment guidelines, switching from intravenous to oral antibiotic treatments, and preauthorization. The three priority interventions are: prospective audit and feedback, preauthorization, and facility-specific treatment guidelines.
Preauthorization: This requires prescribers to gain approval prior to the use of certain antibiotics. This can help to optimize initial empiric therapy. The development of preauthorization for necessary antibiotics can be based on standard guidelines; limited antibiotics can be prescribed based on consultation, or more easily, referring to the WHO antibiotic classification. In 2017, WHO proposed categorizing antibiotics into three groups: ACCESS, WATCH, and RESERVE groups [75]. For the WATCH group, antibiotics with a high risk of resistance, such as 3rd-generation cephalosporins, carbapenems, and fluoroquinolones, should be preauthorized; for the RESERVE group, antibiotics such as colistin, ceftaroline, tigecycline, and aztreonam are indicated when other prescribed antibiotics have failed or are inadequate (e.g., serious life-threatening infections due to multidrug-resistant bacteria), and must be authorized and discussed before prescribing.
Prospective audit and feedback: This is an external assessment of antibiotic therapy by ASP experts at some point after the agent has been prescribed. The ASP prospective audit and feedback team usually consists of a physician (an infectious disease specialist or a clinical microbiologist) and a clinical pharmacist. Prospective audit and feedback are performed as follows: On the first day of prescribed antibiotics, the team audits the suitability of doses and the routes of empirical antibiotic therapy. After 72 hours, the team reviews the patient’s response (clinical stability, biomarkers, renal function), along with microbiological culture results, to give feedback to the treating physician in case a need to change the therapy is indicated: change of antibiotic, the addition of antibiotic, de-escalation of antibiotic treatment, dose adjustment. The cycle of audit and feedback is performed continuously. On day 7, the team evaluates the duration of antibiotic treatment (Figure 1) [76]. Preauthorization and prospective audit and feedback are complementary processes that optimize antibiotic therapy. Preauthorization resembles an antibiotic input “filter” that improves initiation of antibiotics, and prospective audit and feedback help to optimize continued therapy.
Facility-specific treatment guidelines: A clear guideline on antibiotic use will help to make prospective audit and feedback easier and more effective. Recommendations should be developed based on national and international guidelines, local susceptibilities, and hospital antibiotic management policies.
Figure 1.
Schema for prospective audit and feedback, and formulary restriction and preauthorization, for ASPs.
Tracking: Measurement is crucial to identify opportunities for improvement and to assess the impact of interventions. Measurement of antibiotic stewardship interventions may include measures of antibiotic use, and measures of outcomes like C. difficile infections, antibiotic resistance, and financial impact.
Reporting: A comprehensive picture of antibiotic use and antibiotic resistance, along with the work of the antibiotic stewardship program, should be provided in regular updates to prescribers, pharmacists, nurses, and leadership. This helps make medical staff aware of the situation of antibiotic use and antibiotic resistance at their facility, thereby promoting rational use of antibiotics.
Education: Interventions (preauthorization, prospective audit, and feedback) and measurement of antibiotic use and outcomes, can reveal gaps in antibiotic prescribing in hospitals. This helps to make the education of medical professionals realistic and effective, thereby gradually improving the effectiveness of antibiotic treatment, reducing adverse effects, antibiotic resistance, and treatment costs. There are many ways to provide education regarding antibiotic use, such as presentations; posters, flyers, and newsletters; and/or electronic communication to staff groups.
In summary, ASP interventions applied in hospitals, such as audit and feedback, updating of treatment guidelines along with local susceptibility patterns, and training of medical staff, can reveal individual or departmental cases of high antibiotic use by infectious disease specialists, clinical pharmacists, and microbiologists in order to promote rational antibiotic use [77].
3.3 Technological tools
3.3.1 Biomarkers
Among the oldest and most frequently used biomarkers for predicting a patient’s response to antibiotic therapy are fever and leukocytosis. A decline in both indicates that an infectious disease has been adequately treated with a chosen course of antibiotics. More recently, studies have shown that another biomarker, procalcitonin (PCT), can be combined with clinical criteria to help physicians to decide whether to de-escalate or discontinue antibiotic therapy, without affecting outcomes [78]. A systematic review of 26 RCTs involving 6708 participants (acute respiratory infections) from 12 countries found that the duration of antibiotic therapy using PCT concentration reduced mortality, decreased antibiotic consumption, and lowered the risk of antibiotic side-effects. The length of hospital stay and ICU stay were similar in both groups [79]. A randomized trial of 621 patients with suspected community or hospital infection showed that the intervention group (using PCT) had a significantly shorter duration of antibiotic treatment than the control group (14.3 days (SD 9.1) vs. 11.6 days (SD 8.2); absolute difference 2.7 days, 95% CI 1.4 to 4.1, p < 0.0001) [80]. Similarly, an RCT of 101 patients with VAP indicated that antibiotic discontinuation based on serum PCT decreased their duration of antibiotic use compared with the control group (p = 0.038) [81]. A novel multicenter quality control survey study, including 1759 patients from Switzerland, France, and the United States who had respiratory tract infections, revealed that antibiotic therapy duration based on PCT concentration was shorter than without PCT concentration (5.9 vs. 7.4 days; the absolute difference in days (95% CI), −1.51 (−2.04 to −0.98); P < 0.001) [82]. The Infectious Diseases Society of America (IDSA) and the American Thoracic Society (ATS) suggest using PCT levels plus clinical criteria, rather than clinical criteria alone (weak recommendation, low-quality evidence), to guide discontinuation of antibiotic therapy [52].
Besides PCT, another biomarker useful in the management of pneumonia is C-reactive protein (CRP). Together with clinical criteria, low levels of CRP and PCT at 72 h of CAP treatment may improve the prognosis of an absence of severe complications [83]. In a study by Shuren Guo et al., performed on 350 hospitalized CAP patients, CRT and PCT levels on day 3 were statistically lower in the survivors compared to non-survivors [84]. The European Respiratory Society recommended that for patients with suspected pneumonia, along with observing clinical signs and symptoms, a CRP test may be indicated. A CRP level of >100 mg/L, with symptoms for >24 hours makes pneumonia likely; a CRP level < 20 mg/L at presentation, with symptoms for >24 hours, is possibly caused by another respiratory tract infection [85].
Antibiotic resistance is one of the greatest threats to global health, and pneumonia is one of several infections that are becoming less responsive to antibiotic treatment. Antibiotic resistance increases the risk of mortality, prolongs hospital stays, and increases treatment costs. The unnecessary and prolonged use of antibiotics is an important cause contributing to the growth of multidrug-resistant bacteria [86]. This “one size fits all” approach can result in overtreatment, increased side effects, and antibiotic resistance. Therefore, individualization in treatment is important. In addition to clinical assessment, the physician may further consider assessing serum PCT and CRP levels to guide clinical decision-making.
3.3.2 Computerized provider order entry (CPOE) and clinical decision support system (CDSS)
Two useful tools which help in the prevention of ADEs are the computerized physician order entry (CPOE) and clinical decision support systems (CDSS). Compared with conventional medication control, the computerized alert system ADEAS selected different patients based on the risk of an ADE. For the hospital pharmacist, this makes ADEAS a valuable and appropriate tool in reducing the number of preventable ADEs [87].
The implementation of CPOE and advanced CDSS tools substantially increases the number of possible ADE alerts for pharmacist review, and the number of true-positive ADE alerts per 1000 admissions [88].
In a statistical study involving 592 patients during the paper-based prescribing period and 603 patients in the CPOE/CDSS period, the total cost of the paper-based system was €12.37 per patient/day, and of CPOE/CDSS was €14.91 per patient/day. Incremental Cost-Effectiveness Ratios (ICER) for medication errors and for preventable adverse drug events were 3.54 and 322.70, respectively; this indicates the additional amount (€) necessary to prevent a medication error or an ADE. CPOE with primary CDSS contributes to the reduction of the risk of preventable harm. Overall, the additional CPOE/CDSS costs required to prevent medication errors or ADEs appear to be acceptable [89].
However, another study indicated a need to optimize the sensitivity of CPOE/CDSS to detect certain classes of problems, because most DRPs identified by clinical pharmacists were not detected in daily clinical practice by CPOE/CDSS. This underlines the importance of the clinical pharmacist’s involvement to reduce DRPs [90].
4. Conclusion
Pneumonia is one of the respiratory diseases causing the highest mortality rate in children and the elderly. As the elderly often have many comorbidities, DRPs also greatly affect their condition and ability to recover.
DRPs in pneumonia are a very complex issue, requiring great attention from healthcare professionals and patients in prescribing, dispensing, and administering medications. Moreover, the rate of hospital readmissions for pneumonia is also a challenging burden, for the health system in general and for patients in particular. The application of technological tools such as CPOE and CDSS to prescribing and ordering can reduce the occurrence of DRPs, but it is physicians, clinical pharmacists and health professionals who play the most important role in reducing DRPs and hospital readmissions in pneumonia.
\n',keywords:"Pneumonia, drug-related problems, re-hospitalization, prescriptions, interventions",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/78526.pdf",chapterXML:"https://mts.intechopen.com/source/xml/78526.xml",downloadPdfUrl:"/chapter/pdf-download/78526",previewPdfUrl:"/chapter/pdf-preview/78526",totalDownloads:236,totalViews:0,totalCrossrefCites:0,dateSubmitted:"August 20th 2021",dateReviewed:"August 25th 2021",datePrePublished:"September 10th 2021",datePublished:"May 11th 2022",dateFinished:"September 10th 2021",readingETA:"0",abstract:"Pneumonia is one of the most common infectious diseases and the fourth leading cause of death globally. According to US statistics in 2019, pneumonia is the most common cause of sepsis and septic shock. In the US, inpatient pneumonia hospitalizations account for the top 10 highest medical costs, totaling $9.5 billion for 960,000 hospital stays. The emergence of antibiotic resistance in the treatment of infectious diseases, including the treatment of pneumonia, is a globally alarming problem. Antibiotic resistance increases the risk of death and re-hospitalization, prolongs hospital stays, and increases treatment costs, and is one of the greatest threats in modern medicine. Drug-related problems (DRPs) in pneumonia - such as suboptimal antibiotic indications, prolonged treatment duration, and drug interactions - increase the rate of antibiotic resistance and adverse effects, thereby leading to an increased burden in treatment. In a context in which novel and effective antibiotics are scarce, mitigating DRPs in order to reduce antibiotic resistance is currently a prime concern. A variety of interventions proven useful in reducing DRPs are antibiotic stewardship programs, the use of biomarkers, computerized physician order entries and clinical decision support systems, and community-acquired pneumonia scores.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/78526",risUrl:"/chapter/ris/78526",signatures:"Kien T. Nguyen, Suol T. Pham, Thu P.M. Vo, Chu X. Duong, Dyah A. Perwitasari, Ngoc H.K. Truong, Dung T.H. Quach, Thao N.P. Nguyen, Van T.T. Duong, Phuong M. Nguyen, Thao H. Nguyen, Katja Taxis and Thang Nguyen",book:{id:"7102",type:"book",title:"Pneumonia",subtitle:null,fullTitle:"Pneumonia",slug:"pneumonia",publishedDate:"May 11th 2022",bookSignature:"Nima Rezaei",coverURL:"https://cdn.intechopen.com/books/images_new/7102.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-83968-639-9",printIsbn:"978-1-83968-638-2",pdfIsbn:"978-1-83968-640-5",isAvailableForWebshopOrdering:!0,editors:[{id:"116250",title:"Dr.",name:"Nima",middleName:null,surname:"Rezaei",slug:"nima-rezaei",fullName:"Nima Rezaei"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"84603",title:"Dr.",name:"Dyah A.",middleName:null,surname:"Perwitasari",fullName:"Dyah A. 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Duong",slug:"van-t.t.-duong",email:"dttvan@ctump.edu.vn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"429460",title:"Dr.",name:"Phuong M.",middleName:null,surname:"Nguyen",fullName:"Phuong M. Nguyen",slug:"phuong-m.-nguyen",email:"nmphuong@ctump.edu.vn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"429461",title:"Prof.",name:"Thao H.",middleName:null,surname:"Nguyen",fullName:"Thao H. Nguyen",slug:"thao-h.-nguyen",email:"huongthao0508@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Ho Chi Minh City Medicine and Pharmacy University",institutionURL:null,country:{name:"Vietnam"}}},{id:"429462",title:"Prof.",name:"Katja",middleName:null,surname:"Taxis",fullName:"Katja Taxis",slug:"katja-taxis",email:"k.taxis@rug.nl",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"University of Groningen",institutionURL:null,country:{name:"Netherlands"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Drug-related problems in pneumonia",level:"1"},{id:"sec_2_2",title:"2.1 Improper drug selection and dose selection",level:"2"},{id:"sec_3_2",title:"2.2 Drug interactions",level:"2"},{id:"sec_4_2",title:"2.3 Initiation and duration of administration antibiotic treatment",level:"2"},{id:"sec_5_2",title:"2.4 Comorbidities",level:"2"},{id:"sec_6_2",title:"2.5 Risk factors for DRP-readmission and pneumonia re-hospitalization",level:"2"},{id:"sec_8",title:"3. Strategies for reducing DRPs in pneumonia",level:"1"},{id:"sec_8_2",title:"3.1 Role of a clinical hospital pharmacist in patient care",level:"2"},{id:"sec_9_2",title:"3.2 Antibiotic stewardship programs",level:"2"},{id:"sec_10_2",title:"3.3 Technological tools",level:"2"},{id:"sec_10_3",title:"3.3.1 Biomarkers",level:"3"},{id:"sec_11_3",title:"3.3.2 Computerized provider order entry (CPOE) and clinical decision support system (CDSS)",level:"3"},{id:"sec_14",title:"4. 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\r\n\tTransforming our World: the 2030 Agenda for Sustainable Development endorsed by United Nations and 193 Member States, came into effect on Jan 1, 2016, to guide decision making and actions to the year 2030 and beyond. Central to this Agenda are 17 Goals, 169 associated targets and over 230 indicators that are reviewed annually. The vision envisaged in the implementation of the SDGs is centered on the five Ps: People, Planet, Prosperity, Peace and Partnership. This call for renewed focused efforts ensure we have a safe and healthy planet for current and future generations.
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\r\n\t
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\r\n\tThis Series focuses on covering research and applied research involving the five Ps through the following topics:
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\r\n\t1. Sustainable Economy and Fair Society that relates to SDG 1 on No Poverty, SDG 2 on Zero Hunger, SDG 8 on Decent Work and Economic Growth, SDG 10 on Reduced Inequalities, SDG 12 on Responsible Consumption and Production, and SDG 17 Partnership for the Goals
\r\n
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\r\n\t2. Health and Wellbeing focusing on SDG 3 on Good Health and Wellbeing and SDG 6 on Clean Water and Sanitation
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\r\n\t
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\r\n\t3. Inclusivity and Social Equality involving SDG 4 on Quality Education, SDG 5 on Gender Equality, and SDG 16 on Peace, Justice and Strong Institutions
\r\n
\r\n\t
\r\n
\r\n\t4. Climate Change and Environmental Sustainability comprising SDG 13 on Climate Action, SDG 14 on Life Below Water, and SDG 15 on Life on Land
\r\n
\r\n\t
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\r\n\t5. Urban Planning and Environmental Management embracing SDG 7 on Affordable Clean Energy, SDG 9 on Industry, Innovation and Infrastructure, and SDG 11 on Sustainable Cities and Communities.
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\r\n\tThe series also seeks to support the use of cross cutting SDGs, as many of the goals listed above, targets and indicators are all interconnected to impact our lives and the decisions we make on a daily basis, making them impossible to tie to a single topic.
",coverUrl:"https://cdn.intechopen.com/series/covers/24.jpg",latestPublicationDate:"May 19th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:0,editor:{id:"262440",title:"Prof.",name:"Usha",middleName:null,surname:"Iyer-Raniga",slug:"usha-iyer-raniga",fullName:"Usha Iyer-Raniga",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRYSXQA4/Profile_Picture_2022-02-28T13:55:36.jpeg",biography:"Usha Iyer-Raniga is a professor in the School of Property and Construction Management at RMIT University. Usha co-leads the One Planet Network’s Sustainable Buildings and Construction Programme (SBC), a United Nations 10 Year Framework of Programmes on Sustainable Consumption and Production (UN 10FYP SCP) aligned with Sustainable Development Goal 12. The work also directly impacts SDG 11 on Sustainable Cities and Communities. She completed her undergraduate degree as an architect before obtaining her Masters degree from Canada and her Doctorate in Australia. 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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:"15",type:"subseries",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. 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Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. Dr. Beydemir is also Rector of Bilecik Şeyh Edebali University, Turkey.",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",slug:"deniz-ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",biography:"Dr. Deniz Ekinci obtained a BSc in Chemistry in 2004, MSc in Biochemistry in 2006, and PhD in Biochemistry in 2009 from Atatürk University, Turkey. He studied at Stetson University, USA, in 2007-2008 and at the Max Planck Institute of Molecular Cell Biology and Genetics, Germany, in 2009-2010. Dr. Ekinci currently works as a Full Professor of Biochemistry in the Faculty of Agriculture and is the Head of the Enzyme and Microbial Biotechnology Division, Ondokuz Mayıs University, Turkey. He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. 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