Basic operational and financial risk measures in the examined enterprises: average values for 5 subsequent years.
\\n\\n
IntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\\n\\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\\n\\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\\n\\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\\n\\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\\n\\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\\n\\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\\n\\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\\n\\nFeel free to share this news on social media and help us mark this memorable moment!
\\n\\n\\n"}]',published:!0,mainMedia:{caption:"",originalUrl:"/media/original/237"}},components:[{type:"htmlEditorComponent",content:'
After years of being acknowledged as the world's leading publisher of Open Access books, today, we are proud to announce we’ve successfully launched a portfolio of Open Science journals covering rapidly expanding areas of interdisciplinary research.
\n\n\n\nIntechOpen was founded by scientists, for scientists, in order to make book publishing accessible around the globe. Over the last two decades, this has driven Open Access (OA) book publishing whilst levelling the playing field for global academics. Through our innovative publishing model and the support of the research community, we have now published over 5,700 Open Access books and are visited online by over three million academics every month. These researchers are increasingly working in broad technology-based subjects, driving multidisciplinary academic endeavours into human health, environment, and technology.
\n\nBy listening to our community, and in order to serve these rapidly growing areas which lie at the core of IntechOpen's expertise, we are launching a portfolio of Open Science journals:
\n\nAll three journals will publish under an Open Access model and embrace Open Science policies to help support the changing needs of academics in these fast-moving research areas. There will be direct links to preprint servers and data repositories, allowing full reproducibility and rapid dissemination of published papers to help accelerate the pace of research. Each journal has renowned Editors in Chief who will work alongside a global Editorial Board, delivering robust single-blind peer review. Supported by our internal editorial teams, this will ensure our authors will receive a quick, user-friendly, and personalised publishing experience.
\n\n"By launching our journals portfolio we are introducing new, dedicated homes for interdisciplinary technology-focused researchers to publish their work, whilst embracing Open Science and creating a unique global home for academics to disseminate their work. We are taking a leap toward Open Science continuing and expanding our fundamental commitment to openly sharing scientific research across the world, making it available for the benefit of all." Dr. Sara Uhac, IntechOpen CEO
\n\n"Our aim is to promote and create better science for a better world by increasing access to information and the latest scientific developments to all scientists, innovators, entrepreneurs and students and give them the opportunity to learn, observe and contribute to knowledge creation. Open Science promotes a swifter path from research to innovation to produce new products and services." Alex Lazinica, IntechOpen founder
\n\nIn conclusion, Natalia Reinic Babic, Head of Journal Publishing and Open Science at IntechOpen adds:
\n\n“On behalf of the journal team I’d like to thank all our Editors in Chief, Editorial Boards, internal supporting teams, and our scientific community for their continuous support in making this portfolio a reality - we couldn’t have done it without you! With your support in place, we are confident these journals will become as impactful and successful as our book publishing program and bring us closer to a more open (science) future.”
\n\nWe invite you to visit the journals homepage and learn more about the journal’s Editorial Boards, scope and vision as all three journals are now open for submissions.
\n\nFeel free to share this news on social media and help us mark this memorable moment!
\n\n\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:"5976",leadTitle:null,fullTitle:"Drosophila melanogaster - Model for Recent Advances in Genetics and Therapeutics",title:"Drosophila melanogaster",subtitle:"Model for Recent Advances in Genetics and Therapeutics",reviewType:"peer-reviewed",abstract:'This book contains 12 chapters divided into two sections. Section 1 is "Drosophila - Model for Genetics." It covers introduction, chromosomal polymorphism, polytene chromosomes, chromosomal inversion, chromosomal evolution, cell cycle regulators in meiosis and nongenetic transgenerational inheritance in Drosophila. It also includes ecological genetics, wild-type strains, morphometric analysis, cytostatics, frequencies of early and late embryonic lethals (EEL and LEL) and mosaic imaginal discs of Drosophila for genetic analysis in biomedical research. Section 2 is "Drosophila - Model for Therapeutics." It explains Drosophila as model for human diseases, neurodegeneration, heart-kidney metabolic disorders, cancer, pathophysiology of Parkinson\'s disease, dopamine, neuroprotective therapeutics, mitochondrial dysfunction and translational research. It also covers Drosophila role in ubiquitin-carboxyl-terminal hydrolase-L1 (UCH-L1) protein, eye development, anti-dUCH antibody, neuropathy target esterase (NTE), organophosphorous compound-induced delayed neuropathy (OPIDN) and hereditary spastic paraplegia (HSP). It also includes substrate specificities, kinetic parameters of recombinant glutathione S-transferases E6 and E7 (DmGSTE6 and DmGSTE7), detoxification and insecticidal resistance and antiviral immunity in Drosophila.',isbn:"978-953-51-3854-9",printIsbn:"978-953-51-3853-2",pdfIsbn:"978-953-51-4011-5",doi:"10.5772/66545",price:119,priceEur:129,priceUsd:155,slug:"drosophila-melanogaster-model-for-recent-advances-in-genetics-and-therapeutics",numberOfPages:268,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"46ff086c2ae55b49970a648d604634cc",bookSignature:"Farzana Khan Perveen",publishedDate:"February 28th 2018",coverURL:"https://cdn.intechopen.com/books/images_new/5976.jpg",numberOfDownloads:28962,numberOfWosCitations:27,numberOfCrossrefCitations:30,numberOfCrossrefCitationsByBook:1,numberOfDimensionsCitations:46,numberOfDimensionsCitationsByBook:1,hasAltmetrics:1,numberOfTotalCitations:103,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"December 7th 2016",dateEndSecondStepPublish:"December 21st 2016",dateEndThirdStepPublish:"September 16th 2017",dateEndFourthStepPublish:"October 16th 2017",dateEndFifthStepPublish:"December 16th 2017",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"75563",title:"Dr.",name:"Farzana Khan",middleName:null,surname:"Perveen",slug:"farzana-khan-perveen",fullName:"Farzana Khan Perveen",profilePictureURL:"https://mts.intechopen.com/storage/users/75563/images/system/75563.jpg",biography:"Dr. Farzana Khan Perveen (FLS; Gold Medalist) obtained her BSc (Hons) and MSc in Entomology from the University of Karachi, Pakistan, and MAS (Monbusho Scholarship) in Agronomy from Nagoya University, Japan, and a Ph.D. in Toxicology from the University of Karachi. She is the founder of the Department of Zoology and former controller of examinations at Shaheed Benazir Bhutto University, Hazara University, and Kohat University of Science and Technology. She is the author of 150 high-impact research papers, 135 abstracts, 40 authored books, 9 chapters, and 9 edited books. She is also a student supervisor. Her fields of interest are entomology, toxicology, forensic entomology.",institutionString:"Classes et Events in Sciences (C.E.S.)",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"6",totalChapterViews:"0",totalEditedBooks:"7",institution:null}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"347",title:"Pestology",slug:"insectology-pestology"}],chapters:[{id:"54451",title:"Introduction to Drosophila",doi:"10.5772/67731",slug:"introduction-to-drosophila",totalDownloads:12248,totalCrossrefCites:1,totalDimensionsCites:4,hasAltmetrics:1,abstract:null,signatures:"Farzana Khan Perveen",downloadPdfUrl:"/chapter/pdf-download/54451",previewPdfUrl:"/chapter/pdf-preview/54451",authors:[{id:"75563",title:"Dr.",name:"Farzana Khan",surname:"Perveen",slug:"farzana-khan-perveen",fullName:"Farzana Khan Perveen"}],corrections:null},{id:"59005",title:"Drosophila Chromosomal Polymorphism: From Population Aspects to Origin Mechanisms of Inversions",doi:"10.5772/intechopen.73246",slug:"drosophila-chromosomal-polymorphism-from-population-aspects-to-origin-mechanisms-of-inversions",totalDownloads:1264,totalCrossrefCites:4,totalDimensionsCites:5,hasAltmetrics:0,abstract:"High rates of chromosomal rearrangements are remarkably abundant in Drosophila Fallén, 1832 (Insecta, Diptera) genus, highlighting the paracentric inversions. Since different species of this genus are paradigms for genetics, evolutionary, and population studies, polymorphism analyses for chromosomal inversions have provided basic knowledge for beautiful biological questions. Chromosomal inversions suppress meiotic recombination and thus, natural selection can act to preserve favorable gene complexes. Analyses of natural and laboratory populations show that these polymorphisms provide adaptive advantages to their carriers in relation to diverse factors, such as niche exploration and climatic factors. In addition, due to their monophyletic origin, they also serve as genetic markers for the construction of unrooted phylogenies. With the increasing domain of molecular techniques and genome sequencing, factors such as the reuse of breakpoints by different inversions and the mechanisms that give rise to these polymorphisms have been exploited with scientific refinement. These analyses show the presence of regions that are hot spots for breakpoints, fitting the fragile breakage chromosomal evolution model, as well as the involvement of transposition elements at the origin of chromosomal inversions.",signatures:"Carolina Garcia and Vera L. S. Valente",downloadPdfUrl:"/chapter/pdf-download/59005",previewPdfUrl:"/chapter/pdf-preview/59005",authors:[{id:"204362",title:"Dr.",name:"Carolina",surname:"Garcia",slug:"carolina-garcia",fullName:"Carolina Garcia"},{id:"204415",title:"Dr.",name:"Vera",surname:"L. S. Valente",slug:"vera-l.-s.-valente",fullName:"Vera L. S. Valente"}],corrections:null},{id:"57519",title:"Cell Cycle Regulators in Female Meiosis of Drosophila melanogaster",doi:"10.5772/intechopen.70671",slug:"cell-cycle-regulators-in-female-meiosis-of-drosophila-melanogaster",totalDownloads:1313,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Meiosis is a highly regulated and complex variation on the canonical cell cycle. It depends on the activity of most of the known mitotic cell cycle regulators, as well as many meiosis-specific factors that interact with and modify the activities of this core cell cycle machinery. This review will examine the roles of known mitotic cell cycle regulators and meiosis-specific factors in Drosophila female meiosis, focusing on three important meiotic events: nuclear envelope breakdown or maturation, establishment of the meiosis I spindle, and release from metaphase I arrest at ovulation. Many meiotic processes are controlled by the mitotic kinase, Cdk1 with its cyclin partners, cyclins A, B, and B3. Other major mitotic kinases, including Polo and Aurora B have been found to play multiple roles in Drosophila meiosis. The Anaphase Promoting Complex or Cyclosome (APC/C) controls many meiotic processes through regulation of Cdk1, the sister chromatid cohesion regulator, Separase and other targets. This review will focus on these and other meiotic regulators, emphasizing some of the technical advances that have driven the field forward in recent years, and highlighting gaps that need to be filled to achieve a more complete picture of how meiosis is regulated in Drosophila.",signatures:"Mohammed Bourouh and Andrew Swan",downloadPdfUrl:"/chapter/pdf-download/57519",previewPdfUrl:"/chapter/pdf-preview/57519",authors:[{id:"119027",title:"Dr.",name:"Andrew",surname:"Swan",slug:"andrew-swan",fullName:"Andrew Swan"},{id:"203182",title:"BSc.",name:"Mohammed",surname:"Bourouh",slug:"mohammed-bourouh",fullName:"Mohammed Bourouh"}],corrections:null},{id:"57586",title:"Non-genetic Transgenerational Inheritance of Acquired Traits in Drosophila",doi:"10.5772/intechopen.71643",slug:"non-genetic-transgenerational-inheritance-of-acquired-traits-in-drosophila",totalDownloads:1324,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"It is increasingly recognized that acquired traits may be transgenerationally transmitted through non-DNA sequence-based elements, with epigenetics as perhaps the most important mechanism. Here we review examples of non-genetic transgenerational inheritance in Drosophila, highlighting transgenerational programming of metabolic status and longevity, one particular histone modification as an evolutionarily conserved underlying mechanism, and important implications of such studies in understanding health and diseases.",signatures:"Brian Xia and J. Steven de Belle",downloadPdfUrl:"/chapter/pdf-download/57586",previewPdfUrl:"/chapter/pdf-preview/57586",authors:[{id:"218815",title:"Mr.",name:"Brian",surname:"Xia",slug:"brian-xia",fullName:"Brian Xia"},{id:"221917",title:"Dr.",name:"Steven",surname:"De Belle",slug:"steven-de-belle",fullName:"Steven De Belle"}],corrections:null},{id:"58489",title:"Drosophila Imaginal Discs as a Playground for Genetic Analysis: Concepts, Techniques and Expectations for Biomedical Research",doi:"10.5772/intechopen.72758",slug:"drosophila-imaginal-discs-as-a-playground-for-genetic-analysis-concepts-techniques-and-expectations-",totalDownloads:1510,totalCrossrefCites:1,totalDimensionsCites:4,hasAltmetrics:1,abstract:"Drosophila imaginal discs are epithelial tissues perfectly suited to use them as a playground to define the functional contribution of genes to epithelial development and organ morphogenesis. The more we know about the discs and the mechanisms directing their development, the best prepared we are to assign specific “functions” to individual genes based on phenotypic observations. Conversely, and thinking from the perspective of the gene, the more we know about its function, the best inferences we could make about the mechanisms underlying imaginal disc development. This reciprocal relationship, coupled to the arsenal of possible experimental approaches available in Drosophila genetics, genomics and cellular biology, makes these tissues excellent systems to address biological problems with biomedical relevance. In this review, an overview of three interconnected aspects related to the use of Drosophila imaginal discs as an experimental system to analyze gene function is given: (i) imaginal discs biology, with a focus in the genetic mechanisms involved in pattern formation; (ii) concepts and available experimental tools for the analyses of gene function and (iii) uses of Drosophila and the imaginal discs for addressing biomedical problems.",signatures:"Cristina M. Ostalé, Ana Ruiz-Gómez, Patricia Vega, Mireya Ruiz-\nLosada, Carlos Estella and Jose F. de Celis",downloadPdfUrl:"/chapter/pdf-download/58489",previewPdfUrl:"/chapter/pdf-preview/58489",authors:[{id:"201401",title:"Prof.",name:"Jose F.",surname:"De Celis",slug:"jose-f.-de-celis",fullName:"Jose F. De Celis"},{id:"201405",title:"BSc.",name:"Cristina",surname:"Martínez-Ostalé",slug:"cristina-martinez-ostale",fullName:"Cristina Martínez-Ostalé"},{id:"227839",title:"Prof.",name:"Ana",surname:"Ruiz-Gómez",slug:"ana-ruiz-gomez",fullName:"Ana Ruiz-Gómez"},{id:"227840",title:"MSc.",name:"Patricia",surname:"Vega",slug:"patricia-vega",fullName:"Patricia Vega"},{id:"227842",title:"MSc.",name:"Mireya",surname:"Ruiz-Losada",slug:"mireya-ruiz-losada",fullName:"Mireya Ruiz-Losada"},{id:"227844",title:"Dr.",name:"Carlos",surname:"Estella",slug:"carlos-estella",fullName:"Carlos Estella"}],corrections:null},{id:"58694",title:"The Fruit Fly, Drosophila melanogaster: The Making of a Model (Part I)",doi:"10.5772/intechopen.72832",slug:"the-fruit-fly-drosophila-melanogaster-the-making-of-a-model-part-i-",totalDownloads:2493,totalCrossrefCites:5,totalDimensionsCites:6,hasAltmetrics:1,abstract:"The fruit fly, Drosophila melanogaster (Meigen, 1830) has been established as a cornerstone for research into a wide array of subjects including diseases, development, physiology, and genetics. Thanks to an abundance of genetic tools, publicly available fly stocks, and databases, as well as their considerable biological similarity to mammalian systems, Drosophila has been solidified as a key model organism for elucidating many aspects of human disease. Herein is presented an overview of what makes Drosophila such an appealing model organism. In Part I of this chapter, basic Drosophila biology is reviewed and the most relevant genetic tools available to Drosophila researchers are covered. Then in part II, we outline the use of Drosophila as a model organism to study a wide array of pathologies in which Drosophila has been used, along with key advances made in the specific field using the fly as a model organism.",signatures:"Mariateresa Allocca, Sheri Zola and Paola Bellosta",downloadPdfUrl:"/chapter/pdf-download/58694",previewPdfUrl:"/chapter/pdf-preview/58694",authors:[{id:"219543",title:"Associate Prof.",name:"Paola",surname:"Bellosta",slug:"paola-bellosta",fullName:"Paola Bellosta"},{id:"233005",title:"MSc.",name:"Mariateresa",surname:"Allocca",slug:"mariateresa-allocca",fullName:"Mariateresa Allocca"},{id:"233006",title:"MSc.",name:"Sheri",surname:"Zola",slug:"sheri-zola",fullName:"Sheri Zola"}],corrections:null},{id:"58858",title:"The Fruit Fly, Drosophila melanogaster: Modeling of Human Diseases (Part II)",doi:"10.5772/intechopen.73199",slug:"the-fruit-fly-drosophila-melanogaster-modeling-of-human-diseases-part-ii-",totalDownloads:2438,totalCrossrefCites:8,totalDimensionsCites:14,hasAltmetrics:1,abstract:"The fruit fly, Drosophila melanogaster (Meigen, 1830) has been established as a key model organism thanks in part to their considerable biological similarity to mammals and an abundance of available genetic tools. Drosophila have been used to model many human disease states and have been critical in elucidating the genetic mechanisms contributing to them. Part I of this chapter covered basic Drosophila biology and relevant genetic tools available to Drosophila researchers. Here in part II, we review the use of Drosophila as a model organism to study neurodegenerative disorders, cardiovascular diseases, kidney diseases, cancer, metabolic disorders, and immune disorders, as well as key findings made in those fields thanks to Drosophila research.",signatures:"Mariateresa Allocca, Sheri Zola and Paola Bellosta",downloadPdfUrl:"/chapter/pdf-download/58858",previewPdfUrl:"/chapter/pdf-preview/58858",authors:[{id:"219543",title:"Associate Prof.",name:"Paola",surname:"Bellosta",slug:"paola-bellosta",fullName:"Paola Bellosta"}],corrections:null},{id:"57879",title:"Parkinson’s Disease: Insights from Drosophila Model",doi:"10.5772/intechopen.72021",slug:"parkinson-s-disease-insights-from-drosophila-model",totalDownloads:1401,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Parkinson’s disease (PD) is a medical condition that has been known since ancient times. It is the second most common neurodegenerative disorder affecting approximately 1% of the population over 50 years. It is characterized by both motor and non-motor symptoms. Most of PD cases are sporadic while 5–10% cases are familial. Environment factors such as exposure to pesticides, herbicides and other heavy metals are expected to be the main cause of sporadic form of the disease. Mutation of the susceptible genes such as SNCA, PINK1, PARKIN, DJ1, and others are considered to be the main cause of the familial form of disease. Drosophila offers many advantages for studying human neurodegenerative diseases and their underlying molecular and cellular pathology. Shorter life span; large number of progeny; conserved molecular mechanism(s) among fly, mice and human; availability of many techniques, and tools to manipulate gene expression makes drosophila a potential model system to understand the pathology associated with PD and to unravel underlying molecular mechanism(s) responsible for dopaminergic neurodegeneration in PD—understanding of which will be of potential assistance to develop therapeutic strategies to PD. In the present review, we made an effort to discuss the contribution of fly model to understand pathophysiology of PD, in understanding the biological functions of genes implicated in PD; to understand the gene-environment interaction in PD; and validation of clues that are generated through genome-wide association studies (GWAS) in human through fly; further to screen and develop potential therapeutic molecules for PD. In nutshell, fly has been a great model system which has immensely contributed to the biomedical research relating to understand and addressing the pathology of human neurological diseases in general and PD in particular.",signatures:"Mohamad Ayajuddin, Abhik Das, Limamanen Phom, Priyanka Modi,\nRahul Chaurasia, Zevelou Koza, Abuno Thepa, Nukshimenla Jamir,\nPukhrambam Rajesh Singh, Sentinungla Longkumer, Pardeshi Lal\nand Sarat Chandra Yenisetti",downloadPdfUrl:"/chapter/pdf-download/57879",previewPdfUrl:"/chapter/pdf-preview/57879",authors:[{id:"181774",title:"Prof.",name:"Sarat Chandra",surname:"Yenisetti",slug:"sarat-chandra-yenisetti",fullName:"Sarat Chandra Yenisetti"}],corrections:null},{id:"59235",title:"Drosophila Model in the Study Role of UCH-L1",doi:"10.5772/intechopen.73578",slug:"drosophila-model-in-the-study-role-of-uch-l1",totalDownloads:1346,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"UCH-L1 (ubiquitin carboxyl-terminal hydrolase L1) is a protein, which plays an important role in ubiquitin-proteasome system. Many previous reports showed the relation between UCH-L1 and neurodegenerative diseases, diabetes, as well as cancer. However, the mechanism still remains unclear. In the aim to investigate the functions and regulatory mechanism of UCH-L1 in living organism, Drosophila melanogaster model was utilized to examine the role of UCH-L1. This chapter provides a summary on recent findings related to the roles of UCH-L1 based on the model. First, abnormal expression of Drosophila ubiquitin carboxyl-terminal hydrolase (dUCH) leads to the defects on fly tissue development and function. Gain function of dUCH in the eye imaginal discs induced a rough eye phenotype in the adult, partly resulting from induction of caspase-dependent apoptosis, upset of photoreceptor cell distribution and ommatidium apical mispatterning. Interestingly, the dUCH overexpression of induced rough eye phenotype was completely recused by co-expression either Sevenless or Draf of the mitogen-activated protein kinase pathway. Besides, knockdown dUCH in dopaminergic neurons resulted in some Parkinson’s disease—like phenotypes in fly. Taken together, those findings in Drosophila model contributed a significant dUCH in tissue development and function.",signatures:"Dang Thi Phuong Thao",downloadPdfUrl:"/chapter/pdf-download/59235",previewPdfUrl:"/chapter/pdf-preview/59235",authors:[{id:"202162",title:"Prof.",name:"Thao",surname:"Dang",slug:"thao-dang",fullName:"Thao Dang"}],corrections:null},{id:"58710",title:"Swiss Cheese, Drosophila Ortholog of Hereditary Spastic Paraplegia Gene NTE, Maintains Neuromuscular Junction Development and Microtubule Network",doi:"10.5772/intechopen.73077",slug:"swiss-cheese-drosophila-ortholog-of-hereditary-spastic-paraplegia-gene-nte-maintains-neuromuscular-j",totalDownloads:1285,totalCrossrefCites:7,totalDimensionsCites:8,hasAltmetrics:0,abstract:"Neuropathy target esterase (NTE) is a molecular target for the organophosphorus compound-induced delayed neuropathy (OPIDN) and also one of the genetic factors responsible for the development of the hereditary spastic paraplegia (HSP), characterized by axon degeneration of motoneurons causing progressive lower-limb spastic paralysis. Both HSP and OPIDN are characterized by the distal axonopathy. The molecular mechanisms underlying the axonopathy involved in HSP and OPIDN are poorly understood. In order to have a better understanding of the mechanisms that NTE is involved in, we used one of the homologs, human NTE. Swiss cheese (sws) is a Drosophila melanogaster ortholog of NTE with 39% homology. Mutations in sws as it was shown before lead to age-dependent neurodegeneration, structure alteration of glia cells, and reduced insect life span. To study SWS functions, we used the system of the third-instar larval neuromuscular junctions of D. melanogaster. In this study, we show that mutations in sws (sws1\n and sws76−1\n) and SWS knockdown alter neuromuscular junction’s morphology and synaptic microtubules organization.",signatures:"Elena Ryabova, Nataliya Matiytsiv, Olena Trush, Iryna Mohylyak,\nGalina Kislik, Pavel Melentev and Svetlana Sarantseva",downloadPdfUrl:"/chapter/pdf-download/58710",previewPdfUrl:"/chapter/pdf-preview/58710",authors:[{id:"219724",title:"Dr.",name:"Svetlana",surname:"Sarantseva",slug:"svetlana-sarantseva",fullName:"Svetlana Sarantseva"},{id:"228876",title:"Ms.",name:"Elena",surname:"Ryabova",slug:"elena-ryabova",fullName:"Elena Ryabova"},{id:"228877",title:"Dr.",name:"Nataliya",surname:"Matiytsiv",slug:"nataliya-matiytsiv",fullName:"Nataliya Matiytsiv"},{id:"228879",title:"Ms.",name:"Olena",surname:"Trush",slug:"olena-trush",fullName:"Olena Trush"},{id:"228880",title:"Dr.",name:"Iryna",surname:"Mohylyak",slug:"iryna-mohylyak",fullName:"Iryna Mohylyak"},{id:"228881",title:"Ms.",name:"Galina",surname:"Kislik",slug:"galina-kislik",fullName:"Galina Kislik"},{id:"228883",title:"Dr.",name:"Pavel",surname:"Melentev",slug:"pavel-melentev",fullName:"Pavel Melentev"}],corrections:null},{id:"58828",title:"Substrate Specificities and Kinetic Parameters of Recombinant Drosophila melanogaster Glutathione S-Transferases E6 and E7",doi:"10.5772/intechopen.72970",slug:"substrate-specificities-and-kinetic-parameters-of-recombinant-drosophila-melanogaster-glutathione-s-",totalDownloads:992,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"D. melanogaster glutathione transferases E6 and E7 (DmGSTE6 and DmGSTE7) were successfully cloned, purified, and biochemically characterized. The recombinant proteins were readily purified using the combination of both anionic and BSP/GSH-agarose affinity chromatography. Although both GSTs have significant identity in their amino acid sequence, each enzyme displayed unique biochemical characteristics. Both recombinant proteins were only active toward 1-chloro-2,4-dinitrobenzene (CDNB), 1,2-dichloro-4-nitrobenzene (DCNB), and p-nitrobenzyl chloride (p-NBC) with significant difference in catalytic activities. The findings have shown that neither GSTE6 nor GSTE7 was able to counter oxidative stress. Comparatively, GSTE7 was a more efficient enzyme at turning over DCNB and p-NBC, based on its kcat/Km values which were of 0.183 and 2.25 min−1 mM−1, respectively. Thin-layer chromatography analysis showed that both isoforms were not able to conjugate several tested insecticides. The inhibition kinetics of natural products and dyes toward GSTs in vitro revealed that phenol red possessed inhibition effects only on GSTE6 while rose bengal and cardiogreen inhibit significantly on both GSTE6 and GSTE7. In contrast, methylene blue dye and trans-chalcone have been shown to stimulate GSTE7 activity toward CDNB.",signatures:"Vennobaashini Venu and Zazali Alias",downloadPdfUrl:"/chapter/pdf-download/58828",previewPdfUrl:"/chapter/pdf-preview/58828",authors:[{id:"176212",title:"Dr.",name:"Zazali",surname:"Alias",slug:"zazali-alias",fullName:"Zazali Alias"},{id:"230983",title:"Ms.",name:"Vennobaashini",surname:"Venu",slug:"vennobaashini-venu",fullName:"Vennobaashini Venu"}],corrections:null},{id:"55560",title:"Antiviral Immunity in the Fruit Fly, Drosophila melanogaster",doi:"10.5772/intechopen.69293",slug:"antiviral-immunity-in-the-fruit-fly-drosophila-melanogaster",totalDownloads:1348,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,abstract:"The fruit fly, Drosophila melanogaster, is an extremely useful model to study innate immunity mechanisms. A fundamental understanding of these mechanisms as they relate to various pathogens has come to light over the past 30 years. The discovery of Toll‐like receptors and their recognition of shared molecules (pathogen‐associated molecular patterns or PAMPs) among pathogenic bacteria were the first detailed set of receptors to be described that act in innate immunity. The immune deficiency pathway (Imd) described in D. melanogaster functions in a very similar way to the Toll pathway in recognizing PAMPs primarily from Gram‐negative bacteria. The discovery of small interfering RNAs (RNAi) provided a means by which antiviral immunity was accomplished in invertebrates. Another related pathway, the JAK/STAT pathway, functions in a similar manner to the interferon pathways described in vertebrates, also providing antiviral defense. Recently, autophagy was also shown to function as a protective pathway against virus infection in D. melanogaster. At least three of these pathways (Imd, JAK/STAT, and RNAi) show signal integration in response to viral infection, demonstrating a coordinated immune response against viral infection. The number of pathways and the integration of them reflect the diversity of pathogens to which innate immune mechanisms must be able to respond. The viral pathogens that infect invertebrates have developed countermeasures to some of these pathways, in particular to RNAi. The evolutionary arms race of pathogen vs. host is ever ongoing.",signatures:"Wilfredo A. Lopez, Alexis M. Page, Brad L. Ericson, Darby J. Carlson\nand Kimberly A. Carlson",downloadPdfUrl:"/chapter/pdf-download/55560",previewPdfUrl:"/chapter/pdf-preview/55560",authors:[{id:"202812",title:"Dr.",name:"Kimberly",surname:"Carlson",slug:"kimberly-carlson",fullName:"Kimberly Carlson"},{id:"202815",title:"Mr.",name:"Wilfredo",surname:"Lopez",slug:"wilfredo-lopez",fullName:"Wilfredo Lopez"},{id:"202817",title:"Ms.",name:"Alexis",surname:"Page",slug:"alexis-page",fullName:"Alexis Page"},{id:"202818",title:"Dr.",name:"Brad",surname:"Ericson",slug:"brad-ericson",fullName:"Brad Ericson"},{id:"202819",title:"Mr.",name:"Darby",surname:"Carlson",slug:"darby-carlson",fullName:"Darby Carlson"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"843",title:"Insecticides",subtitle:"Pest Engineering",isOpenForSubmission:!1,hash:"88f3cc3c937f853057f544c152ef7491",slug:"insecticides-pest-engineering",bookSignature:"Farzana 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The contents of the book will be written by multiple authors and edited by experts in the field.",isbn:null,printIsbn:null,pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"a97becd6aa14a480ce28c05a3116f639",bookSignature:"",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/12156.jpg",keywords:null,numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 4th 2022",dateEndSecondStepPublish:"March 25th 2022",dateEndThirdStepPublish:"May 24th 2022",dateEndFourthStepPublish:"August 12th 2022",dateEndFifthStepPublish:"October 11th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"3 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:1,editedByType:null,kuFlag:!1,biosketch:null,coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"5",title:"Agricultural and Biological Sciences",slug:"agricultural-and-biological-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:null},relatedBooks:[{type:"book",id:"6418",title:"Hyperspectral Imaging in Agriculture, Food and Environment",subtitle:null,isOpenForSubmission:!1,hash:"9005c36534a5dc065577a011aea13d4d",slug:"hyperspectral-imaging-in-agriculture-food-and-environment",bookSignature:"Alejandro Isabel Luna Maldonado, Humberto Rodríguez Fuentes and Juan Antonio Vidales Contreras",coverURL:"https://cdn.intechopen.com/books/images_new/6418.jpg",editedByType:"Edited by",editors:[{id:"105774",title:"Prof.",name:"Alejandro Isabel",surname:"Luna Maldonado",slug:"alejandro-isabel-luna-maldonado",fullName:"Alejandro Isabel Luna Maldonado"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"10359",title:"Landraces",subtitle:"Traditional Variety and Natural Breed",isOpenForSubmission:!1,hash:"0600836fb2c422f7b624363d1e854f68",slug:"landraces-traditional-variety-and-natural-breed",bookSignature:"Amr Elkelish",coverURL:"https://cdn.intechopen.com/books/images_new/10359.jpg",editedByType:"Edited by",editors:[{id:"231337",title:"Dr.",name:"Amr",surname:"Elkelish",slug:"amr-elkelish",fullName:"Amr Elkelish"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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Capital is a necessary element of each economic activity. Its significance is increasing along with the increase of capital consumption in the activity. In the enterprises functioning in capital-consuming industries, such as mining industry, the problem of capital becomes more complex, which is followed by a number of problems that do not emerge in the enterprises functioning in other industries. Taking the size of capital used in mining industry into account and the problems linked to its management, the measurement of the return on capital expected by investors became the objective of this research. The problem of how to calculate the expected return rate is known, both in scientific circles and business practice. However, the universal calculation methods in use are difficult to be applied in the enterprises from mining industry due to a specific character of risk occurring in such enterprises, unique type of activity, and high capital consumption. In order to meet such a goal, diagnostic and conceptual research was conducted. As a part of diagnostic research, the method, often used, of estimating the return rate on capital called capital asset pricing model (CAPM) was analyzed and verified, but that does not fully resolve the problem. Therefore, it was used as the grounds for conceptual research, as a part of which an attempt was made to design a new method including the conditions of mining industry. The suggested solutions, to a great extent, facilitate the process of calculation of the expected return on capital used to finance mining activity; even in cases when such calculation was not possible or did not provide rational results, they make this process possible and give measurable results. The solutions presented allow a more realistic look on the issue of financing mining activity. They may find use in the efficiency calculus of mining enterprises, value pricing of mining enterprises, in the area of development of optimal structure of financing sources, when obtaining capital through shares or bonds issuance, etc.
\nIn order to define the expected return rate on capital, firstly, one should refer to the definition of capital. Capital is one of the most often used notions in economic sciences and many others. At the same time, it is interpreted in various ways, both in theory and economic practice. For this reason, some kind of theoretical pluralism appeared, where the proper essence is sought for the particular area of knowledge. For example, one may talk about real capital, tangible, operating, money, human, intellectual, social capital, etc.
\nThe definition of capital started to be used in the Middle Ages, although there is a proof that the foundation for the conception of capital has already appeared in prehistoric times, several thousands of years BC. The conceptions linking capital with a corresponding return rate have been developed as the definition of capital was shaping. Capital was initially defined as the monetary value being able to earn interest [1]. The notion of capital also referred to all the goods possessed [2], and as the time went by, it encompassed a wider range of possessions, going beyond a traditional understanding of assets and including other, even intangible values. At present “capital” is a wide and equivocal category. Various ways of approach to defining and interpreting this definition appear in both theory and economic practice. Capital is perceived as strength, which is the basis for progress; it increases work efficiency and creates the wealth of nations [3]. Capital is at the same time noticed as a category responding to goods (resources) possessed, used to run and develop economic activity (tangible or resource conceptions) or responding to savings gathered (monetary conceptions). Its basic feature is the ability to grow (see more in [4]). Such growth may take a form of income, financial revenue (percentage), value added, and others. However, a fact is emphasized that the growth occurring as a result of capital use takes place after a particular amount of time (compare with [5]). These are only some of the conceptions of capital appearing in the history.
\nIn the process of enterprise management, capital may also be analyzed in the forms of existence as
Despite a great variety of approaches to defining capital, it should be noticed that in most conceptions of capital there is one inherent feature, namely, the ability to generate profit. Some people identify this profit with income (most often in asset, production approach to capital) [10]. However, the most common understanding of capital profits is interest, which mainly relates to capital in value depiction, that is, money. In this work it is assumed that the return on invested capital consists of the
The significance of risk should be emphasized when defining the expected return rate. Investments of the same risk level have the same return rate. Consequently, the return rate expected by investors, in case of investing capital in a particular undertaking, should be at least equal to the highest total return that the investors could expect if they invested in an alternative portfolio of securities with a comparable risk [12]. According to this approach, the more risky the enterprise’s activity is, the higher return rate should be generated (compare with [13]). The expected return rate defined in this way has its interpretation in the price that the enterprise pays for the possibility of using capital. This price is expressed in a form of interest rate, reflecting the relation of expenses borne by the capital provider in a yearly scale due to putting capital at someone’s disposal and the value of this capital. In this depiction the expected return rate is strictly connected with the source of capital’s origin and accompanies capital coming from any source. It may be described as interest, dividends, other benefits, or even opportunity cost for capital providers. In subject literature the division emerged into the expected return rate on equity and debt capital. Individual financing sources, being the components of these groups, are characterized by a different return rate for capital providers. Usually, the return rate even on the same type of capital is different. For example, a different interest rate is assigned to the investment loan in different banks. It results from the contents of particular agreements.
\nThe expected return rate may be understood in a different way from the point of view of capital provider and recipient. For capital recipient the desired return rate at a given risk level is the cost of capital. However, some circumstances should be taken into account, when the return rate may be higher or lower than the cost of capital. For capital recipient the cost of capital is lower than the return rate expected by capital provider, when tax benefits emerge thanks to decreasing the taxable amount by the interest on capital. It consists in the fact that the interest paid by the enterprise decreases gross financial result, lowering at the same time taxable amount. This phenomenon is called
Risk is considered to be one of the most important indicators of the expected return rate, especially in mining industry, due to the capital-consuming character of this industry and long period of return for the outlays put.
Risk generated inside the enterprise may be generally divided into operational and financial risk.
where EBIT0 is the earnings before deducting interest and taxes, ∆EBIT is the change in EBIT, S0 is the sales revenues, ∆S is the change in sales revenues, and Cv is the variable operating cost.
\n\n
where D is the debt burdened with interest and E is the equity.
\nIf the financial leverage ratio in the enterprise is higher than 0 (only when the enterprise is financed by debt capital), the effect of financial leverage appears. It consists in a situation when, due to financial costs resulting from interest on debt, possible fluctuations of earnings per share are more than proportional to fluctuation of operating income. The higher the financial cost, the stronger the effect of financial leverage. It may be positive when it translates into increase of earnings per share or negative when such earnings decrease. The degree of this effect depends on the share of fixed financial cost in total cost of the enterprise [20].
\nThe effect of financial leverage is measured using the
where EBIT is the earnings before deducting interest and taxes, EPS is the earnings per share, \n
The indicator of the degree of financial leverage is calculated for the particular value of EBIT. If EBIT is close to the cost of servicing debt, which means net income is close to zero, then the level of DFL is high. Along with EBIT rise, the level of DFL decreases (the share of fixed cost of servicing debt falls in relation with operating income), which proves that financial risk decreases. The higher the share of debt in the enterprise’s capital structure and the higher the cost of servicing debt representing the return rate expected by capital providers, the higher the effect of financial leverage and the higher the value of DFL. When the enterprise is financed by equity only (I = 0), the effect of financial leverage does not occur and DFL = 1. The effects of financial leverage are different for various variants of corporate capital structure, however, the effects (positive or negative) are stronger when the share of debt capital increases in financing structure and the expected return rate on capital is higher.
\nIn practice, based on DFL indicator expressing the relation of operating income and cost of debt servicing, ratings are assigned for enterprise’s debt. Then, a corresponding financial risk premium resulting from debt is determined. The indicator showing the ability of servicing debt is used here—times interest earned (TIE) (used by renowned rating agencies, such as Standard & Poor’s and Moody’s Investors Service)—which measures the relation of operating income and cost of servicing debt capital [22]:
\n\n
Financial risk in the enterprise may be additionally pictured in practice using other indicators characterizing the financial structure of the enterprise. These include the share of equity in total capital (
The first ratio informs about the level at which the enterprise is able to finance itself in the activity conducted. A high value of this ratio means solid financial grounds of the enterprise and ensures the creditors that in case of failure, the enterprise will be able to settle the debt incurred using equity. Debt to capital ratio informs about the level of enterprise’s debt, that is, what part of corporate capital is debt [24].
\nFurthermore, when examining the corporate capital structure, also the level of assets coverage by equity (
When the value of this ratio is equal to or more than 100%, it means that the balance sheet’s golden rule has been fulfilled. It says that fixed assets, which are engaged in conducting economic activity for a longer time, should be fully financed by equity as they are at enterprise’s disposal in a long term.
\nThe next variable considered to be an important indicator of financial risk is the level of net
An important problem during analysis of this area of the enterprise is determination of the limit of debt capital engagement. It may be identified using dependency analysis between the return on equity (ROE) indicator and return on net operating assets (RNOA) indicator. ROE informs about the value of net profit ascribed to one unit of employed equity. This indicator alone may serve as an estimator of specific risk premium. Nevertheless, it is not a perfect measurement method as it only bases on book value. The current financial reports do not include intellectual capital of the enterprise, which may lead to extremely high values of this ratio caused by decreasing the actual value of denominator in the formula [26].
Theoretically, the higher the value of this indicator, the more favorable the corporate financial situation. However, in each case, ROE indicator should be confronted with other measures of financial risk, for example,
where T is the income tax, NOA is the
Positive assessment is noted for the relation
\n\n
In practice, the value of β coefficient may be calculated according to the formula [11]
\nwhere
The calculation of β coefficient is connected with numerous problems that need to be resolved. One of the most important issues is to indicate the duration of estimation period, so-called estimation window. It is assumed at that time that based on daily return rates a shorter estimation window may be chosen (e.g., 2 years) and based on monthly return rates this period should be accordingly extended to several years [32]. In this area it is important to comply with the requirement of normal distribution of return rates on stock and benchmark index [33].
\nIn practice the estimation of the expected return rate is most often based on CAPM method. CAPM is a part of greater theory called
In general, there is no agreement in literature concerning the type of explanatory variables or the ways of determining the basic parameters, etc. Nevertheless, CAPM constitutes the basis for further attempts of searching for an optimal method of estimating the expected return rate. In most methods the attention is paid to risk pricing; however, only systematic risk is usually included, omitting specific risk of the enterprise. Within the frames of the actions taken in this area, it is necessary to add the specific features of the analyzed sector.
\nCapital asset pricing model assumes that a part of risk premium for the expected return on investment in securities is a function of market risk of these securities (more in [36]). The expected return rate in this approach is a function of individual risk index, describing the volatility of return on stock of the particular enterprise in relation with return on the whole economy (usually represented by a certain market index) [34, 35]. Return on capital invested in stock of the particular enterprise is connected with the market, which may be presented in the following formula:
\nwhere Re is the expected return on equity,
\n
In some situation the assessment of market risk premium is especially difficult, for example, on emerging markets, where capital market does not provide sufficient data (not enough data or they are characterized by too high volatility, and they cannot be a source of reliable estimation of risk premium). Thus, in order to avoid complications in terms of
A response to CAPM limitations mentioned in the previous part can be alternative estimation methods of expected return rate. These include dividend growth model (DGM), Fama–French model, and arbitrage pricing model (APM).
\n\n
where VE is the equity market value (stock market price x number of stock), DIVt is the dividend paid in t period, where t = 1,2,…n, and rw is the expected return rate on equity.
\nSuch construction in a simplified way brings the estimation of equity down to examining two factors: expected dividend growth in the future and return rate that reflects systematic risk of the growth. However, it does not contradict the portfolio theory, which assumes that the return rate consists of dividend and capital profit or loss per share.
\nDividend growth model has not found many supporters in literature or practice. The use of this model in its basic form, that is, with the assumption that the dividend growth is unlimited in time, requires developing the forecast of dividend growth from present up to unlimited yearly periods, which is very time-consuming. The difficulty of this model may also come from the necessity of determining the dividend level and its growth rate, which limits its application only to the enterprises characterized by stable growth and dividend policy aimed at regular payoffs, proportionally to the corporate profits. Mining enterprises do not comply with such requirement. Most of them do not have a policy of regular dividend payoff due to huge capital needs, connected with investment.
\nThe model that constitutes a critical response to the standard version of CAPM is Fama and French three-factor model (Fama-French model), also called F-F model. Some researchers place this model among the nonstandard variations of CAPM. The authors of this model (E. Fama and K. French) proved in 1992 that the standard CAPM does not sufficiently explain the level of return rates on securities. Based on research conducted, they positively verified that the relationship between
APM is often called APT model (
After the analysis of the basic assumptions of the models above, it may be concluded that most of them cannot be directly used, without modification, in mining enterprises; furthermore, some of them should even be rejected. These models possess a number of limitations. The primary problem connected with their utilization is the fact that in many countries mining industry does not have many representatives; often the market is ruled by a few enterprises with very high production potential, which causes that this industry has a few representatives on capital market that provide statistical data for the most pricing models based on capital assets. Another problem related to the use of traditional calculation models of return rate is that they usually include systematic risk only and assume that the pricing of return rate is performed from the investor’s point of view, who possesses a well-diversified portfolio. Such investor, when calculating the expected return rate, pays attention to market (systematic) risk only. On the other hand, capital provider, who does not possess a diversified investment portfolio, invests a great share of assets in one enterprise; she or he is exposed to both market risk and specific risk of the enterprise. Stock of mining enterprises often, in majority shareholding, belongs to one strategic investor, who is strongly connected with mining industry and does not have a diversified portfolio. The necessity of modification of some models also comes from the issue that they include the elements of specific risk not compliant with the characteristics of mining enterprises or not occurring in the industry. Thus, many categories linked to the return rate calculation in mining enterprises require a new definition or better precision.
\nIn this point a modification is suggested regarding the existing method of the expected return rate calculation. An example of the selected mining enterprise—X—is used for that purpose. The expected return rate was calculated for that enterprise and compared with 19 mining enterprises listed on global stock exchanges. The basic subject of research is the mining enterprise from hard coal mining industry, conducting mining activity in Poland, listed on Warsaw Stock Exchange.
\nFor the purpose of research conducted, to enable comparison, the research sample encompassed the largest global mining enterprises in terms of hard coal excavation, comprising the so-called cluster. The parameters characterizing their financial situation are going to form, after an appropriate verification and modifications leading to comparability, benchmarks—reference points for the calculation of expected return rate in Polish mining industry. The selection of enterprises for the research sample was made on the basis of business homogeneity, that is, all the selected enterprises gain a great part of their revenues (over 50%) from hard coal mining activity. Among the benchmark of mining enterprises, the following ones can be mentioned: American corporations (Alpha Natural Resources, Arch Coal, Consol Energy, Peabody Energy Corp., Walter Energy, Inc., Westmoreland Coal Company), Chinese corporations (Inner Mongolia Yitai Coal Company, Ltd., Yanzhou Coal Mining Company, China Coal, Shenhua Group), Australian corporations (BHP Billiton Ltd., Coal of Africa, Coalspur Mines, New Hope Coal, Whitehaven Coal Ltd.), British corporations (Anglo American Coal, Glencore plc), and one Indian corporation (Coal India). They are listed on global stock exchanges such as the New York Stock Exchange (NYSE) in the USA, National Association of Securities Dealers Automated Quotations (NASDAQ)—over the counter, regulated stock market in the USA, Shanghai Stock Exchange (SSE) in China, Hong Kong Stock Exchange (HKSE) in Hong Kong, Australian Securities Exchange (ASX) in Australia, London Stock Exchange (LSE) in Great Britain, and National Stock Exchange of India (NSE) in India.
\nAs it was stated above, the expected return rate depends to a great extent on
No. | \nName | \nDOL | \nD/E | \nDFL | \nTIE | \nE/tot capital | \nD/tot capital | \nE/fix assets | \nOC | \nROE [%] | \nRNOA [%} | \nROE > RNOA | \n
---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | \nEnterprise X | \n1.73 | \n0.19 | \n1.03 | \n40.71 | \n0.68 | \n0.13 | \n0.84 | \n+ | \n12.4 | \n10.78 | \nYes | \n
2 | \nAlpha Natural Resources | \n−47.72 | \n0.95 | \n1.54 | \n−3.99 | \n0.44 | \n0.40 | \n0.55 | \n+ | \n−18.7 | \n−7.07 | \nNo | \n
3 | \nArch Coal | \n29.02 | \n1.77 | \n2.62 | \n−0.34 | \n0.36 | \n0.58 | \n0.42 | \n+ | \n−8.5 | \n−0.91 | \nNo | \n
4 | \nConsol Energy | \n0.72 | \n2.11 | \n2.21 | \n5.24 | \n0.30 | \n0.59 | \n0.35 | \n+ | \n14.7 | \n5.32 | \nYes | \n
5 | \nPeabody Energy Corp. | \n−0.15 | \n1.66 | \n0.83 | \n1.45 | \n0.34 | \n0.55 | \n0.42 | \n+ | \n3.7 | \n8.13 | \nNo | \n
6 | \nRio Tinto | \n−153.66 | \n0.94 | \n1.05 | \n5.31 | \n0.45 | \n0.41 | \n0.55 | \n+ | \n8.68 | \n7.61 | \nYes | \n
7 | \nWalter Energy, Inc. | \n12.40 | \n3.66 | \n0.92 | \n4.42 | \n0.22 | \n0.71 | \n0.28 | \n+ | \n−7.3 | \n6.80 | \nNo | \n
8 | \nWestmorel and Coal Company | \n13.07 | \n−4.89 | \n−2.42 | \n−0.29 | \n−0.24 | \n1.13 | \n−0.29 | \n— | \n1.35 | \n2.41 | \nNo | \n
9 | \nInner Mongolia Yitai Coal Company Ltd. | \n0.98 | \n2.14 | \n1.06 | \n20.83 | \n0.31 | \n0.57 | \n0.41 | \n— | \n53.1 | \n25.58 | \nYes | \n
10 | \nYanzhou Coal Mining Company | \n134.52 | \n0.97 | \n0.87 | \n24.38 | \n0.42 | \n0.38 | \n0.60 | \n+ | \n16.2 | \n9.93 | \nYes | \n
11 | \nChina Coal | \n3.81 | \n1.27 | \n1.11 | \n10.91 | \n0.46 | \n0.46 | \n0.69 | \n+ | \n12.0 | \n10.83 | \nYes | \n
12 | \nShenhua Group | \n0.25 | \n0.71 | \n1.04 | \n12.22 | \n0.61 | \n0.43 | \n0.84 | \n— | \n15.9 | \n20.61 | \nNo | \n
13 | \nBHP Billiton Ltd. | \n−4.54 | \n0.63 | \n1.06 | \n15.68 | \n0.53 | \n0.33 | \n0.68 | \n+ | \n28.6 | \n22.83 | \nYes | \n
14 | \nCoal of Africa | \n1.38 | \n0.22 | \n0.99 | \n−116.5 | \n0.79 | \n0.17 | \n0.98 | \n+ | \n−33.0 | \n−11.10 | \nNo | \n
15 | \nCoalspur Mines | \n0.48 | \n0.15 | \n0.96 | \n−19.99 | \n0.83 | \n0.12 | \n1.18 | \n+ | \n−23.0 | \n−27.40 | \nYes | \n
16 | \nNew Hope Coal | \n−1.83 | \n0.08 | \n1.02 | \n64.27 | \n0.86 | \n0.07 | \n2.96 | \n+ | \n9.83 | \n29.85 | \nNo | \n
17 | \nWhitehaven Coal Ltd. | \n−73.57 | \n0.29 | \n1.13 | \n5.59 | \n0.75 | \n0.22 | \n1.03 | \n+ | \n3.65 | \n2.95 | \nYes | \n
18 | \nAnglo American Coal | \n2.54 | \n1.24 | \n1.12 | \n4.77 | \n0.44 | \n0.50 | \n0.57 | \n+ | \n9.45 | \n11.29 | \nNo | \n
19 | \nGlencore plc | \n1.31 | \n5.06 | \n0.50 | \n0.47 | \n0.15 | \n0.62 | \n0.30 | \n— | \n8.90 | \n3.41 | \nYes | \n
20 | \nCoal India | \n−0.17 | \n1.05 | \n1.00 | \n291.99 | \n0.38 | \n0.39 | \n1.94 | \n+ | \n40.3 | \n63.10 | \nNo | \n
Basic operational and financial risk measures in the examined enterprises: average values for 5 subsequent years.
Source: own work.
Some indicators may serve themselves as the measures of specific risk premium of the enterprise. In this work it is assumed that this risk is determined by the whole set of indicators. The first one—degree of operating leverage—identifying the level of operational risk, shows very high fluctuations in the enterprises. DOL fluctuates in the range of over 134 to about 150. Such great volatility with positive or negative numbers appears only in single cases. In general, operating leverage is positive (almost 30% of the examined enterprises are characterized by negative average operating leverage in the examined period, which may mean sales below operational break-even point). In most cases yearly average operational leverage is lower than one, which means that the majority of mining enterprises possesses high vulnerability of operational income to changes in sales revenues. It is specific for hard coal mining industry, where fixed costs dominate. Their great share has an impact on high vulnerability of operating results and on changes in sales amount. The results obtained indicate a high level of operational risk in hard coal mining industry.
\nThe next indicator included in the listing presented in \nTable 1\n is financial leverage and degree (effect) of financial leverage. Financial leverage is used in most enterprises (apart from one enterprise, all of them use debt capital in financing their activity), and in most cases, we deal with a positive effect of financial leverage. The strongest effects appear in the enterprises with the highest level of debt. In order to determine whether the effect of financial leverage is positive or negative, it was examined whether debt of the enterprises increases or decreases the return on equity. It was observed that the financial leverage is not effectively used, though. It is supported by the fact that, in average, in about half of the enterprises the return on equity is lower than the return on net operating assets. In the majority of the examined enterprises, the cost of servicing debt (TIE) constitutes too big burden for operating income. These problems can be noticed, in particular, in the last 2 years of the analyzed period. Financial risk of the analyzed mining enterprises is growing as the time goes by. An additional risk factor is a low degree of financing fixed assets by equity. It can be seen that in six out of nineteen investigated enterprises equity dominates in their financing structure. These are all Australian enterprises and one Chinese enterprise. Fixed assets in these corporations are to a great extent (60% and more) or even fully covered by equity. In the other cases, it relates to about 2/3 of enterprises, and in their liabilities, structure debt capital dominates; furthermore, a great share of debt capital with interest is clearly outlined, and mostly this capital constitutes over 50% of all liabilities. In this group of enterprises, only about 50% of fixed assets is covered by equity. It means that mining industry, despite a high degree of assets immobilization, finances assets from external sources. Taking the character of fixed assets in mining industry into account, this state of things should be assessed as increasing the risk of financing, which may lead to losing liquidity.
\nThe next examined element is
Another element taken into account in effectiveness assessment of capital management is
In further analysis ROE is compared with RNOA. A positive evaluation occurs in case of the relation in which the return on equity is higher than the return on net operating assets. The verification of whether ROE > RNOA is made in \nTable 1\n. The relation of ROE to RNOA, according to the tendency in hard coal mining industry observed before, deteriorates year by year. At the beginning of the examined period only in 1/3 of corporations, the level of ROE is lower than RNOA. In the subsequent years, the number of enterprises characterized by unfavorable relation of these two indicators is increasing, and in the last analyzed year, such situation is noted in almost 80% of the examined enterprises. It means that at the beginning of the examined period in about 65% of the examined enterprises, capital management is effective, that is, the enterprises use a positive effect of financial leverage. However, this situation deteriorated, and, recently, positive assessment of the effects of capital management may obtain only 20% of the investigated corporations.
\nFor the purpose of calculation of the expected return rate in mining enterprises, a model is used in this work. Firstly, a decomposition and qualitative description were made for the most important variables affecting the expected return rate. These are variables representing specific and systematic risk of the enterprise. The next stage of model building is an attempt to parameterize the aforementioned variables.
\nOn the stage of variable selection in the process of model building, cluster analysis is used [58]. Its basis is a selection of research sample among the mining enterprises listed on stock exchanges. On the grounds of the features characterizing the researched areas of enterprise’s activity belonging to a particular cluster, the averaged levels of these features were calculated for the whole industry; next, the comparison of averaged values with their values was conducted for the enterprise that the expected return rate was calculated for (in case of this work for the enterprise X). Where necessary, the individual features were brought to comparability with the inclusion of external factors, specific for the enterprises representing different world markets.
\nNext to specific risk, an important indicator of expected return rate is systematic risk. A classic measure of systematic risk is β coefficient. In case when it cannot be calculated properly, only industry or sector average of β coefficient can be determined and used in CAPM. However, a problem appears that consists in the fact that all the assessed enterprises from the same industry have a common β coefficient, which may be connected with a possible, huge assessment mistake (averaging error).
\nIn some approach it is advised to include, beside systematic risk, the factors of specific risk in addition when calculating β coefficient. Such postulate is proposed by, for example, A. Damodaran, who uses the notion of total risk, marked as “total β,” explaining that [28]
\nConsidering the fact that the correlation cannot be higher than 1, total β cannot be lower than a regular one. It allows stating that the inclusion of specific risk always gives a result in a form of increasing the expected return rate [59, 60]. Nevertheless, a problem still remains unsolved concerning the differentiation of the expected return rate for different mining enterprises on the same market. In further analysis an attempt is made to solve this problem through specific risk modeling. It consists in appropriate transformation of β coefficient calculated for similar enterprises listed on stock exchange and adjusting it to the specificity of the investigated corporation. A starting point is a solution suggested in a model by
where βL is the β coefficient with financial leverage (levered β), βU is the β coefficient without financial leverage (unlevered β), and T is the income tax rate.
\nAfter transformation this formula takes the following form:
\nThe usefulness of both formulas consists in the possibility of making simulation how β is shaping, depending on changes in the level of financial leverage.
\nIn order to analyze systematic risk in the mining enterprise X, as its quotation history on Warsaw Stock Exchange is too short to use statistical methods, cluster analysis was applied. In the enterprises representing global mining industry, β coefficient was calculated. The condition for β determination is compliance of empirical distribution of return rates on stock and market index with normal distribution. In order to examine the empirical distribution of return rates on stock and market indexes, Shapiro–Wilk test and Kolmogorov–Smirnov test with Lilliefors significance correction were used. All the tests univocally indicate that this condition is fulfilled by monthly return rates on stock and market indexes calculated on the basis of 5-year estimation period. Thanks to the selection of enterprises subjected to business homogeneity, grounding on β coefficients calculated for the aforementioned enterprises, industry average β indexes were indicated for the researched market and for the whole research sample in the period of the past 5 years. Industry average β coefficients for the individual markets are included in \nTable 2\n.
\nNo. | \nName | \nAverage | \n
---|---|---|
1 | \nNYSE/NASDAQ (USA) | \n1.66 | \n
2 | \nSSE (China) | \n0.84 | \n
3 | \nHKSE (Hong Kong) | \n1.40 | \n
4 | \nASX (Australia) | \n1.43 | \n
5 | \nLSE (Great Britain) | \n1.84 | \n
\n | Total mining industry | \n1.43 | \n
Industry average β coefficient for individual markets with the assumption of 5-year estimation period.
Source: own work.
Industry average β for the cluster of hard coal mining in the examined period fluctuates in the range of 1.36–1.54. At the beginning of the analyzed period, the highest value of β is ascribed to the corporations listed in Great Britain (at the beginning this coefficient amounts to 1.92, and after 5 years, it goes down to 1.79). The lowest β coefficient is specific for Chinese enterprises in the whole examined period (average β of enterprises listed on this market equals 0.84). It means that the stock of Chinese mining enterprises is characterized by lower systematic risk than the whole market represented by SSE Composite Index. Beside China, on all the investigated markets, β is higher than 1, which means that the stock of mining enterprises is more risky than the average market portfolio. The stock of British enterprises is the most risky (average β = 1.84) and American ones (average β = 1.66). A bit lower risk is specific for the enterprises listed in Hong Kong (average β = 1.6640) and Australia (average β = 1.43).
\nIn order to include a wider dimension of risk in β coefficient, the correlation between the industry and the market was estimated using Pearson coefficient (the results are placed in \nTable 3\n). After dividing the industry average β by the correlation coefficient between the industry and the market, total β was obtained, which is shown in \nTable 4\n.
\nNo. | \nName | \nPearson correlation coefficient | \n
---|---|---|
1 | \nNYSE/NASDAQ (USA) | \n0.632 | \n
2 | \nSSE (China) | \n0.492 | \n
3 | \nHKSE (Hong Kong) | \n0.827 | \n
4 | \nASX (Australia) | \n0.447 | \n
5 | \nLSE (Great Britain) | \n0.712 | \n
Correlation between monthly return rates in the industry and the market.
Source: own work.
No. | \nName | \nTotal average β | \n
---|---|---|
1 | \nNYSE/NASDAQ (USA) | \n2.62 | \n
2 | \nSSE (China) | \n1.71 | \n
3 | \nHKSE (Hong Kong) | \n1.77 | \n
4 | \nASX (Australia) | \n2.97 | \n
5 | \nLSE (Great Britain) | \n4.12 | \n
6 | \nTotal hard coal mining industry | \n2.70 | \n
Total industry average β for individual markets.
Source: own work.
The highest correlation between the return rates on stock and the market is noticed in case of the enterprises listed in Hong Kong and Great Britain. The lowest one belongs to stock of Chinese and Australian corporations.
\nThe calculation of total β confirms that the highest risk is specific for stock of British mining enterprises. The lowest risk in the assessed group is characteristic for stock of enterprises listed in Hong Kong and China.
\nIn the area of systematic risk, the subject of analysis was another form of β coefficient. To be exact, β is transformed according to Hamada model, presenting it in an unlevered version for the particular markets (\nTable 5\n).
\nNo. | \nName | \nAverage unlevered β | \n
---|---|---|
1 | \nNYSE/NASDAQ (USA) | \n0.71 | \n
2 | \nSSE (China) | \n0.48 | \n
3 | \nHKSE (Hong Kong) | \n0.74 | \n
4 | \nASX (Australia) | \n1.20 | \n
5 | \nLSE (Great Britain) | \n0.99 | \n
\n | Total hard coal mining industry | \n0.84 | \n
Average industry unlevered β for individual markets.
Source: own work.
Unlevered β coefficient is considered to be a universal systematic risk measure of mining enterprises, and in this form, it is going to be used for modeling of the expected return rate for the enterprises not listed on a capital market or for the enterprises with too short quotation history, based on Polish mining enterprise X.
\nSpecific risk is parameterized based on scoring assessment that includes the operational and financial risk measures presented above. The parameterization of diagnostic features in the enterprise X consists in their comparison with the values of a given feature in the industry, represented by a certain cluster of enterprises and assigning a scoring value to them, corresponding to specific risk class. In \nTable 6\n there are diagnostic features from scoring model listed, showing at the same time a median of their value for hard coal mining industry (with tolerance level ± 10%), represented by the investigated cluster of enterprises. Median was used in the research as the distribution of the examined diagnostic features is usually asymmetric, which rules out using arithmetic mean.
\nNo. | \nAssessment criterion/diagnostic feature | \n−10% | \nMedian in global hard coal mining | \n+10% | \n
---|---|---|---|---|
1 | \nDOL | \n1.40 | \n1.55 | \n1.71 | \n
2 | \nD/E | \n0.63 | \n0.70 | \n0.77 | \n
3 | \nDFL | \n0.95 | \n1.05 | \n1.16 | \n
4 | \nTIE | \n4.51 | \n5.01 | \n5.51 | \n
5 | \nE/C total | \n0.40 | \n0.44 | \n0.48 | \n
6 | \nD/E total | \n0.35 | \n0.39 | \n0.43 | \n
7 | \nE/fixed assets | \n0.53 | \n0.59 | \n0.65 | \n
8 | \nOC | \n\n | + | \n\n |
9 | \nROE > RNOA | \n\n | Yes | \n\n |
Criteria of specific risk assessment with the reference point in a form of median of individual indicators in global hard coal mining.
Source: own work.
In the next step, it is suggested to list three specific risk classes, depending on the level of particular diagnostic indicators:
Class 0—low specific risk
Class 1—average specific risk
Class 2—high specific risk
Each of the accepted diagnostic features is assessed by having assigned the value of 0, 1, or 2, compliant with the specific risk class. The scale was constructed in a descending order, that is, class 0, and assessment 0 is ascribed to the indicators, the values of which is more favorable than the industry average level of a given diagnostic feature, class 1 and assessment 1 (level equal to industry average ± 10%) and class 2 and assessment 2 (unsatisfactory level), meaning a worse level than industry average. The average sum of scores for all diagnostic features is transformed into specific risk premium (SRP). The lower the scoring value, the lower the specific risk and in consequence lower risk premium, which is followed by lower expected return rate.
\nThe first diagnostic feature in a form of the degree of operating leverage informs about the operating risk level. The higher leverage the higher risk. The average industry level of operating leverage in the examined period amounts to 1.55. The enterprises in which the operating leverage is lower than 1.4 (average minus 10%) but higher than 0 are placed in risk class 0. The enterprises with DOL higher than 1.71 (average plus 10%) and a negative one are burdened with high operating risk (risk class 2). If the degree of operating leverage takes the value in the range [1.4; 1.71], the enterprise obtains risk class 1. The next diagnostic features are financial leverage and the degree of financial leverage, informing about the level of financial risk. In average, in the examined cluster of hard coal mining, financial leverage amounts to 0.7 and the degree of financial leverage to 1.05. The increase of these indicators triggers risk growth. When D/E ratio is lower than 0.63 and DFL lower than 0.95, risk class 0 is assigned. If these indicators have the values, D/E from 0.63 to 0.77 and DFL from 0.95 to 1.16, it is risk class 1. Furthermore, above these levels, we deal with risk class 2. Another diagnostic feature is the possibility of debt servicing (TIE). Its higher level is positively evaluated; therefore, the enterprises with the TIE level above 5.51 are in risk class 0, level from 4.51 to 5.51 is risk class 1, and below 4.51 means qualification to risk class 2. Equity to total capital (understood as equity and debt capital with interest) ratio is another criterion of ascribing the enterprise to the particular risk class. The lower the level of this ratio, the higher the risk. The share of equity in total capital below 0.4 is assessed as unsatisfactory and qualifies the particular enterprise to risk class 2. The level from 0.4 to 0.48 is risk class 1 and above 0.48 is class 0. In turn, the next feature—share of debt in total capital—is estimated as unsatisfactory in case of the level below 0.35 (risk class 0). The increase of debt capital in capital structure triggers risk increase. The level of the share of debt capital from 0.35 to 0.43 means risk class 1 and above 0.43 is class 2. The next diagnostic feature relates to the share of equity in financing fixed assets. The lower the scale of financing fixed assets by equity, the higher the risk; thus, the enterprises financing less than 53% of fixed assets by equity are ascribed to risk class 2. Risk class 0 appears in case of financing over 65% of fixed assets by equity. Between these ranges, we deal with, as in previous cases, risk class 1. Another criterion of specific risk assessment is the level of working (operating) capital. For this indicator, a positive level is considered to be satisfactory (risk class 0); indicator equal to zero is risk class 1, and negative working capital means qualifying the enterprise to risk class 2. The last examined criterion is the relation of ROE and RNOA indicators. If ROE > RNOA the corporation is in risk class 0. In adverse situation the relation is unfavorable, which indicates risk class 2. If ROE = RNOA it is risk class 1.
\nAccording to the guidelines above, an attempt of parameterization of the assessment criteria of specific risk was made for Polish mining enterprise X (\nTable 7\n).
\nNo. | \nIndicator | \nYear I | \nYear II | \nYear III | \nYear IV | \nYear V | \n
---|---|---|---|---|---|---|
1 | \nDOL | \n— | \n2 | \n0 | \n2 | \n2 | \n
2 | \nD/E | \n0 | \n0 | \n0 | \n0 | \n0 | \n
3 | \nDFL | \n0 | \n1 | \n1 | \n1 | \n2 | \n
4 | \nTIE | \n2 | \n0 | \n0 | \n0 | \n2 | \n
5 | \nE/C total | \n0 | \n0 | \n0 | \n0 | \n0 | \n
6 | \nD/E total | \n0 | \n0 | \n0 | \n0 | \n0 | \n
7 | \nE/fixed assets | \n0 | \n0 | \n0 | \n0 | \n0 | \n
8 | \nOC | \n2 | \n0 | \n0 | \n0 | \n0 | \n
9 | \nROE > RNOA | \n— | \n0 | \n0 | \n2 | \n2 | \n
\n | \n | \n0.57 | \n0.33 | \n0.11 | \n0.56 | \n0.89 | \n
Scoring assessment of diagnostic indicators in mining enterprise X.
Source: own work.
Specific risk of enterprise X amounts in the examined period to 0.49 in average. Operational risk increases the level of specific risk (in this area risk class 2 occurs in 3 years of the researched period). In terms of financial risk, the situation of the enterprise is generally more favorable than in the industry, which is confirmed by the domination of financial risk class 0 in the assessment made. However, attention should be paid to the fact that in the last year a rapid deterioration occurred concerning the level of many diagnostic features, which were previously at the more favorable level compared to the industry average. Above all, the ability of the enterprise to service debt is deteriorating, DFL level is increasing, and effectiveness of equity management is decreasing.
\nHaving qualified the individual diagnostic features to specific risk classes and performed their scoring assessment, one may start the calculation of specific risk premium. It is assumed that in each enterprise this premium consists of average score of specific risk multiplied by base premium, for which industry premium was adopted, known in practice as
Specific risk premium in scoring model may be written in the following way:
\nwhere SRP is the specific risk premium, ScoreSR is the arithmetic mean of scores resulting from scoring assessment of specific risk, and IRP is the industry risk premium.
\nSuch construction of specific risk premium means that, when all diagnostic features in the enterprise are in specific risk class 1, specific risk premium is equal to IRP. The enterprises, where the level of diagnostic features is more favorable than the industry average, are characterized by specific risk premium lower than IRP. In turn, the corporations, which have diagnostic features at a more risky level than the industry average, obtain specific risk premium higher than IRP. The listing of specific risk premium (SRP) is included in \nTable 8\n.
\nNo. | \nIndicator | \nYear I | \nYear II | \nYear III | \nYear IV | \nYear V | \n
---|---|---|---|---|---|---|
1. | \nIRP for hard coal mining [%] | \n6.00 | \n6.00 | \n6.00 | \n6.00 | \n6.00 | \n
2. | \nScoreSR\n | \n0.57 | \n0.33 | \n0.11 | \n0.56 | \n0.89 | \n
3. | \nSRP [%] | \n3.43 | \n2.00 | \n0.67 | \n3.33 | \n5.33 | \n
Calculation of specific risk premium (SRP) in mining enterprise X.
Source: own work.
After calculating specific risk premium, one can estimate the expected return rate according to the assumptions of modified CAPM. It may be written as the following formula:
\nThe calculation of the expected return rate in the Polish mining enterprise X requires the adoption of the following parameters: β coefficient, market risk premium and specific risk premium, and risk-free return rate. The basic parameters necessary for this calculation along with its results are presented in \nTable 9\n. Risk-free return rate was accepted as the return rate on 10-year Polish treasury bills. Market risk premium was adopted at the level recommended by A. Damodaran for the whole Polish economy [65]. Furthermore, specific risk premium was accepted at the level according to the calculation made on the basis of scoring model for specific risk parameterization.
\nNo. | \nIndicator | \nYear I | \nYear II | \nYear III | \nYear IV | \nYear V | \n
---|---|---|---|---|---|---|
1. | \nRisk-free rate (10-year treasury bills) [%] | \n6.17 | \n5.80 | \n5.98 | \n4.94 | \n4.10 | \n
2. | \nUnlevered industry average β | \n0.82 | \n0.91 | \n0.87 | \n0.85 | \n0.74 | \n
3. | \nMRP [%] | \n6.08 | \n6.5 | \n7.5 | \n7.3 | \n6.28 | \n
4. | \nSRP [%] | \n3.43 | \n2.00 | \n0.67 | \n3.33 | \n5.33 | \n
5. | \nExpected return rate [%] | \n13.97 | \n13.54 | \n13.09 | \n13.98 | \n12.69 | \n
Calculation of the cost of equity in Polish mining enterprise X according to the assumptions of modified CAPM.
Source: own work.
The activity of the examined enterprise is burdened with high risk. It is a corporation being in a difficult financial situation. The results obtained may be considered as adequate to risk that is connected with the engagement of capital in this enterprise. The enterprise is in debt and significantly burdened with the cost of debt capital and performs on the edge of financial liquidity. Another big problem is the influence of trade unions on corporate activity and low level of activity diversification. Taking the high risk into account, capital providers expect the return rate at the level of about 13%.
\nThe presented calculation model of the expected return rate does not lack limitations. In comparison with the traditional CAPM, it is better adjusted to the specificity of the activity of mining enterprises. Its limitation may be some kind of subjectivism, especially in relation with the specific risk factors that are difficult to measure. However, the solution proposed eliminates the basic defects of the existing calculation models of the expected return rate, which made it impossible to obtain a realistic pricing in mining enterprises. The models suggested constitute a significant help for the managers of mining enterprises.
\nJuvenile nasopharyngeal angiofibroma (JNA) is a benign, non-encapsulated, highly vascular tumor, occurring almost exclusively in adolescent males. Although JNAs comprise of less than 0.05% of all head and neck tumors, their tendency to bleed torrentially makes them an interesting disease entity to study and treat [1].
Development of other medical fields has been instrumental in studying the origin, growth and other characteristics of this disease entity. Advancements in radiology, histopathology and endoscopic nasal surgeries have been particularly useful. We can now better diagnoses, stage and treat JNA than the previous decade.
Earliest known documentation of juvenile nasopharyngeal angiofibroma is credited to Hippocrates in the 4th century BC [2]. The term “juvenile nasopharyngeal angiofibroma” was coined by Chaveau in 1906 and his works re-sparked the interest in JNA [3]. Shaheen et al. [4] reported the first female case of JNA (1930).
Harma et al. in 1959 gave a detailed clinico-pathological insight into this tumor [5]. Works of Bensch, Ewing, Som, Neffson, Moore, Handousa, Denker etc. have been vital in understanding the natural history of disease and its surgical management [6, 7, 8, 9].
Nasopharynx is a near-cuboidal shaped space with an approximate volume of 30cm3. It is located exactly below the middle cranial fossa.
Boundaries of Nasopharynx:
Posterior to the torus tuboris, lies a deep recess called
Endoscopic anatomy of nasopharynx as seen through right nasal cavity
Pterygopalatine fossa is a bilateral wedge-shaped space located below the orbital apex and behind the posterior wall of maxillary sinus. It communicates with other regions of skull through various canals and foramina.
Boundaries of Pterygopalatine Fossa:
I
Communications of Pterygopalatine Fossa:
Via
Via
Via
Via
Via
Via
Via
Contents of Pterygopalatine Fossa:
Pterygopalatine ganglion with its branches
Maxillary nerve (V2) and its branches
Vidian Nerve (carrying secretomotor fibers of facial nerve from superior salivatory nucleus and sympathetic fibers from internal carotid artery via deep petrosal nerve)
Third part of maxillary artery
Juvenile Nasopharyngeal Angiofibroma occurs almost exclusively in males and that too in adolescent period. Mean age of presentation is 14 years (range 7 years to 19 years) [10]. Isolated cases of JNAs in females or in younger/ older ages have been reported in literature [4, 11]. Exact etiology, although unknown, evidences point towards a hormonal influence on its occurrence and growth.
Juvenile nasopharyngeal angiofibroma can arise from any one of the following sites:
Scientists are still looking out for exact etiological factors and how these affect the growth of the tumor. Following factors should be considered:
The fibrous stroma has varying amounts of fine and coarse collagen fibers. Plump spindle, angular, or stellate-shaped cells are also seen. Rarely, mast cells may be present. The nuclei of stromal cells generally lack any characteristic features; although, multinucleated pleomorphic cells are not uncommon.
The vascular and fibrous elements vary in proportion within the same tumor and with the tumor age. While the fibrous component is more towards the centre of the tumor, peripheral areas have abundance of vascular elements. Also, newer lesions have predominantly vascular component while long standing tumors are enriched with fibrous tissue.
Embolised specimens show myxoid changes with areas of infarction. Embolic agent can be seen in the tumor vessels. Post flutamide therapy or radiotherapy specimens show a significant increase in fibrous component (Figure 2).
Histopathological section of JNA as seen under a microscope. Multiple blood vessels of varying diameters are seen in a fibrous stroma.
IMMUNOHISTOCHEMISTRY | |||
---|---|---|---|
TEST ANTIBODY | TUMOR COMPONENT | TUMOR CELLS | STAINING PATTERN |
1. Vimentin | Vascular & Fibrous | All tumor cells | Cytoplasmic |
2. Androgen receptor | Vascular & Fibrous | All stromal cells and endothelial cells | Nuclear |
3. VEGF | Vascular & Fibrous | Stromal and vascular cells | Cytoplasmic |
4. PDGF | Vascular & Fibrous | Stromal and vascular cells (+/−) | Cytoplasmic |
5. IGF-2 | Vascular & Fibrous | Stromal and vascular cells (+/−) | Cytoplasmic |
6. TGF- β | Vascular & Fibrous | Stromal and vascular cells (+/−) | Cytoplasmic |
7. SMA (Smooth Muscle Actin) | Vascular | Smooth muscle cells in blood vessels | Cytoplasmic |
8. Desmin | Vascular | Cells in walls of larger blood vessels | Cytoplasmic |
9. FVIIIRAg | Vascular | Endothelial cells | Cytoplasmic |
10. CD31 | Vascular | Endothelial cells | Cytoplasmic |
11. CD34 | Vascular | Endothelial cells | Cytoplasmic |
12. ER | Vascular | Vascular cell nuclei (+/−) | Nuclear |
13. PR | Vascular | Vascular cell nuclei (+/−) | Nuclear |
14. CD117 (c-kit) | Fibrous | Stromal cells | Cytoplasmic |
15. β Catenin | Fibrous | Stromal cells | Nuclear |
Immunohistochemistry (IHC) tests for JNA.
JNA arises at the upper lip of sphenopalatine foramen. As it grows further, it spreads along the path of least resistance to involve many vital structures.
From sphenopalatine foramen, it extends into the nasopharynx and grows submucosally. It can occupy the entire nasopharynx to produce bilateral nasal obstruction and nasal intonation of voice (rhinolalia clausa). Recurrent epistaxis often starts at this stage only. The tumor mass may depress the soft palate or hang in the oropharynx. Blockage of eustachian tube(s) results in conductive hearing loss (otitis media with effusion).
It enters the ipsilateral nasal cavity first to cause unilateral nasal obstruction and epistaxis. Here it may acquire secondary attachments.
As the tumor grows further within the ipsilateral nasal cavity, it pushes the nasal septum towards the opposite side to produce contralateral nasal obstruction as well.
Further tumor growth allows it to involve ethmoidal sinuses. This results in flattening of the nasal bridge and an increase in the intercanthal distance. An associated proptosis gives a classical ‘
The tumor may encroach upon and erode anterior wall of sphenoid sinus. It may further invade the sphenoid sinus.
Lateral growth of the tumor results in the involvement of pterygopalatine fossa. Pterygopalatine fossa is a small wedge-shaped cavity, which can be considered as a cross-section/ junction point of many important ‘highways’.
As the mass lesion fills the pterygopalatine fossa, it causes anterior bowing of the posterior wall of maxillary sinus
From pterygopalatine fossa, it can extend into the orbit via the inferior orbital fissure. This produces proptosis. Further involvement of orbital apex results in loss of vision. Involvement of extraocular muscles produces diplopia.
From pterygopalatine fossa, tumor grows laterally to invade infratemporal fossa via the pterygomaxillary fissure. This causes facial swelling and fullness in the cheek region. Erosion of the anterior face of greater wing of sphenoid causes entry of tumor into the middle cranial fossa.
From pterygopalatine fossa, it can grow along the vidian canal to reach foramen lacerum. Foramen lacerum opens in the middle cranial fossa, providing easy access to the tumor for intra cranial extension.
The tumor can erode the pterygoid process posteriorly and spread downwards into the pterygoid fossa. It can reach as far as the parapharyngeal space.
Tumor growth in the posterolateral part of nasopharynx can cause extension into the fossa of rosenmuller. Further posterolateral growth into the apex of this fossa results in intracranial extension by eroding the carotid canal and petrous apex.
The tumor can involve the orbit through the following routes-
Sphenopalatine foramen ➔ pterygopalatine fossa ➔ via inferior orbital fissure ➔ enters orbit.
Sphenopalatine foramen ➔ nasopharynx and nasal cavity ➔ erodes lamina papyracea ➔enters orbit.
The tumor can have intracranial extension through the following routes:
Sphenopalatine foramen ➔ pterygopalatine fossa ➔ infratemporal fossa ➔ erosion of anterior face of greater wing of sphenoid AND/ OR through foramen ovale causing its widening ➔ middle cranial fossa. The tumor lies lateral to Internal Carotid Artery (ICA) and Cavernous Sinus (CS) in such cases.
Sphenopalatine foramen ➔ pterygopalatine fossa ➔ via inferior orbital fissure ➔ orbit ➔ growth within orbit towards orbital apex and superior orbital fissure ➔ middle cranial fossa. The tumor lies anterolateral to ICA and lateral to CS.
Sphenopalatine foramen ➔ nasopharynx and nasal cavity ➔ erosion of floor and anterior wall of sphenoid sinus to invade sphenoid sinus ➔ erosion of roof of sphenoid sinus ➔ intracranial spread. The tumor lies medial to ICA and lateral to pituitary gland.
Sphenopalatine foramen ➔ pterygopalatine fossa ➔ pterygoid (vidian) canal ➔ foramen lacerum ➔ middle cranial fossa. Encasement of ICA is seen early.
Sphenopalatine foramen ➔ nasopharynx ➔ fossa of rosenmuller ➔ erodes carotid canal and petrous apex ➔ intracranial spread.
Sphenopalatine foramen ➔ nasopharynx ➔ nasal cavity ➔ through cribriform plate ➔ anterior cranial fossa (rare route for intracranial extension).
The patient is almost invariably male in his second decade of life. Mean age of presentation is 14 years (reference).
The patient may have one or more of the following symptoms
Mucopurulent discharge in the involved side is seen. Tumor mass may also be visualized. Septum is often deviated towards contralateral side.
Mass lesion is visualized in the nasopharynx.
Examination with a Hopkin’s rigid rod lens 0o endoscope reveals a fleshy mass lesion. It is usually covered in mucopurulent secretions which require gentle suctioning. Probing is avoided as it can complicate into profuse nasal bleed.
Though for any nasal mass, golden rule is that biopsy is preceded by radiological imaging to ascertain origin, extent, and nature of the disease; in vascular tumors such as JNAs, biopsy is contraindicated. Risk of bleeding during and/ or after the procedure outweighs any added advantage we may get out of preoperative biopsy.
Water’s view (Occipitomental view)/ Peer’s view (Occipitomental view with open mouth) shows haziness of the involved sinus. Lateral view shows anterior bowing of posterior wall of maxillary antrum (
Contrast enhanced computed tomographic imaging is the investigation of choice for JNA. Infact, the diagnosis of JNA is confirmed by presence of a mass in nasopharynx and pterygopalatine fossa that enhances after contrast administration on CECT. CECT is a non-invasive procedure that forms the basis for JNA diagnosis and staging.
mass lesion in the nasopharynx/ nasal cavity and pterygopalatine fossa
erosion of posterior bony margin of sphenopalatine foramen with extension to the upper medial pterygoid plate.
Contrast enhanced MRI (CE-MRI) is the investigation of choice for advanced JNA tumors, particularly those with intracranial, intra-orbital, or parapharyngeal space involvement. It can accurately determine the extent of the tumor. ‘Salt and pepper’ appearance on contrast MRI is characteristic to any vascular tumor, resulting due to flow-void areas (T2WI and contrast enhanced T1WI) [22, 34].
MRI is also the preferred modality for post-operative long-term surveillance because of its superior soft tissue differentiation quality without any radiation exposure.
CT angiography is useful to identify the feeder vessel(s) to the tumor. Internal maxillary artery is the most common feeder vessel for JNA. JNA may additionally acquire blood supply from ascending pharyngeal artery, contralateral external carotid artery branches, ipsilateral or contralateral internal carotid artery and its branches (ophthalmic, meningohypophyseal, vidian artery).
Knowledge about the feeding vessel and its site of entry into the tumor is absolutely critical to decide the surgical approach for JNA excision. For example, where feeder vessels are located posterior to the main tumor mass without direct access, open approach is preferred to endoscopic approach.
DSA is used in preoperative phase to identify the feeder vessel and its preoperative embolization. Selective vessel angiography in DSA allows to determine the exact branch(es) supplying the tumor and its selective embolization. JNA shows a characteristic
Various staging systems have been proposed over the years, each with its own merits and demerits.
SESSION’S STAGING SYSTEM | |
---|---|
STAGE | TUMOR EXTENSION |
IA | Involvement of the nose or nasopharyngeal vault |
IB | Extension into one or more sinuses |
IIA | Minimal extension into the pterygopalatine fossa |
IIB | Full occupation of the pterygopalatine fossa |
IIC | Infratemporal extension (± involvement of the cheek) |
III | Intracranial extension |
JNA staging system by Sessions, 1981 [36].
CHANDLER’S STAGING SYSTEM | |
---|---|
STAGE | TUMOR EXTENSION |
I | Involvement of the nasopharyngeal vault |
II | Extension into nasal cavity or sphenoid sinus |
III | Extension into maxillary sinus, ethmoid sinus, pterygopalatine fossa, infratemporal fossa, cheek, palate |
IV | Intracranial extension |
JNA staging system by Chandler, 1984 [37].
ANDREWS-FISCH’S STAGING SYSTEM | |
---|---|
STAGE | TUMOR EXTENSION |
I | Confined to nose or nasopharyngeal vault |
II | Invasion of the pterygopalatine fossa or maxillary/ ethmoid/ sphenoid sinuses with bone destruction |
IIIA | Extension into the infra- temporal fossa or orbit |
IIIB | Intracranial but extradural extension (parasellar area) |
IVA | Intracranial intradural extension |
IVB | Intracranial intradural extension involving |
JNA staging system by Andrew- Fisch, 1989 [38].
RADKOWSKI’S STAGING SYSTEM | |
---|---|
STAGE | TUMOR EXTENSION |
IA | Involvement of the nose or nasopharyngeal vault |
IB | Extension into one or more sinuses |
IIA | Minimal extension into pterygopalatine fossa |
IIB | Complete extension into pterygopalatine fossa |
IIC | Extension into infratemporal fossa/ posterior to pterygoid plates |
IIIA | Minimal skull base involvement (middle cranial fossa/ base of pterygoid plates) |
IIIB | Extensive intracranial involvement ± involvement of cavernous sinus |
JNA staging system by radkowski, 1996 [39].
Only valid for tumors which are preoperatively embolised (Table 6).
UPMC/ SNYDERMAN’S STAGING SYSTEM | |
---|---|
STAGE | TUMOR EXTENSION |
I | Nasal cavity, medial pterygopalatine fossa |
II | Paranasal sinuses and lateral pterygopalatine fossa, no residual vascularity |
III | Skull base erosion, orbit, infratemporal fossa, no residual vascularity |
IV | Skull base erosion, orbit, infratemporal fossa, with residual vascularity from ICA |
V | Intracranial extension with residual vascularity from ICA |
VM | Medial cavernous sinus |
VL | Middle cranial fossa |
JNA staging system by Snyderman/ UPMC, 2010 [40].
Choice of treatment depends on the size and extent of the tumor. Treatment modalities include surgical excision (open v/s endoscopic approach) and non-surgical adjuvant therapy (embolization/hormonal/ radiotherapy) or their combination(s).
Complete excision of the entire tumor mass should be the aim of any surgical procedure and the approach selected accordingly. Though the advancements in endoscopic surgery have minimized the need for open approaches, the surgeon should be well versed with all the techniques.
In general, open approaches have the advantage of providing a wide exposure. But this comes at the cost of higher morbidity, increased hospital stay, and some degree of cosmetic deformity.
This is the shortest and most direct approach for tumors limited to nasopharynx with/ without minimal extension into sphenoid sinus/ choana [41, 42].
A U-shaped incision (Wilson’s incision) is made 2.5 cm anterior to the junction of hard and soft palate. Submucoperiosteal flap is elevated posteriorly till the soft palate to bare the underlying horizontal plate of palatine bone. Soft palate and hard palate are separated. Bone is removed from the posterior part of hard palate to visualize the entire nasopharynx along with the tumor.
This approach has the advantage of good post-operative healing with no visible scar.
Lateral rhinotomy was first described by Irwin Moore in 1917 [43].
The incision is started 5 mm anterior and superior to the medial canthus and continued inferiorly along the deepest portion of the nasomaxillary groove. At its inferior end, it is curved medially in the crease beneath the ala. Skin flaps are elevated over the maxilla and nasal bones. Medial wall of maxillary antrum is removed.
This provides adequate exposure for tumors extending into the nasal cavity and/ or sinuses with minimal extension into the pterygopalatine fossa.
Adequate healing allows for an inconspicuous scar mark, well hidden within the facial creases.
The lateral rhinotomy incision is further extended inferiorly along the ipsilateral ridge of the philtrum and continued to split the upper lip in paramedian position. After dividing the upper lip, incision is continued laterally along the gingivobuccal sulcus upto the first molar. This approach is required in cases needing exposure beyond the infraorbital neurovascular bundle.
The main objective of this approach is to expose the maxillary antrum and remove its medial, anterior and posterolateral walls along with perpendicular plate of palatine bone. Orbital floor and alveolar arch are left intact. This converts the maxillary sinus, nasal cavity, nasopharynx, pterygopalatine fossa and infratemporal fossa into a single large accessible cavity.
This wide exposure is required for large tumors spilling in the infratemporal fossa. Lateral most aspect of these tumors is identified. Feeder vessel in the form of internal maxillary artery (most common feeder vessel) is identified as it enters the lateral aspect of the tumor in the infratemporal fossa and ligated before starting with the tumor dissection. Ascending pharyngeal artery maybe seen entering and supplying the tumor at its posterior aspect. It is also identified and ligated. This allows for minimal blood loss during the tumor dissection and delivery. Tumor delivery is done in-toto through transnasal/ transoral route or in a piecemeal fashion.
Two pathways for this approach have been described:
An incision is made in the gingivobuccal sulcus between the two upper second molars. Periosteum is elevated to expose maxilla in its anterior and lateral aspect. Horizontal osteotomies from pyriform aperture to pterygomaxillary fissure and from pyriform aperture to palatine canals are made. Nasal septum is freed from anterior nasal spine and maxillary crest. Pterygoid dysjuctioning allows easy down fracturing of maxilla to achieve a wide exposure of the tumor extending into multiple paranasal sinuses, infratemporal fossa or intracranial space. After tumor excision, fixation of mid facial skeleton is achieved using titanium plates. This approach provides the widest possible exposure without any external scar [44].
A Weber-Ferguson incision is combined with the splitting of the hard palate [45, 46]. Multiple osteotomies are done and maxilla is disarticulated. Overlying skin and muscles are NOT dissected. Rather they are raised as a single flap along with underlying maxillary and zygomatic bone (
This approach provides accessibility to nasopharynx, paranasal sinuses, infratemporal fossa, parapharyngeal space and intracranial space. Malocclusion of upper jaw and palatal fistula are some uncommon but difficult to manage complications associated with this procedure [47].
MRR starts as a midfacial degloving approach through a sublabial incision [48]. Partial osteotomy at nasofrontal angle allows extended degloving of midface. Multiple osteotomies are made to resect and remove the maxillary bone. Tumor is resected. Maxilla is repositioned at its original anatomical position and secured with titanium plates/ absorbable plates.
Wide exposure for tumor resection from infratemporal fossa, parapharyngeal space, and middle and anterior cranial fossa is achieved. Such extensive resections can cause malocclusions, visual disturbances and disruption of growth centres in the maxillary bone, resulting in future cosmetic deformities.
A combination of infratemporal fossa approach and transfacial approach is required in certain cases with advanced stage angiofibromas [52]. This approach allows access to the infratemporal fossa, middle and anterior cranial fossa, and entire cavernous sinus (both medial and lateral aspects). An added enhanced exposure to the nasopharynx, paranasal sinuses and pterygopalatine fossa facilitates complete tumor excision. Facial skeletal growth retardations and facial asymmetry is rare [53].
Large primary tumors or recurrent tumors may necessitate the need for using more than one open approach in the same sitting. These combinations can be tailor –made depending on size of the tumor, involvement of vital structures, and surgeon’s expertise in one or more approaches. Some commonly used combined approaches are-
Last decade has seen a paradigm shift from open approach to transnasal endoscopic approach. In today’s time, endoscopic surgery can be regarded as the most rapidly advancing surgical field. As the surgeon’s familiarity with the endoscopes is increasing, hard to reach anatomical regions are also becoming more accessible, thereby, widening the horizon for this approach. Tumors, which were earlier labeled as operable via an open approach only, can now be easily and completely resected using endoscopic approach.
Endoscopic surgery has the advantage of better illumination and magnification, lower morbidity, and shorter duration of hospital stay which ultimately leads to cost saving. Advantage of no visible facial scar adds to the cosmetic viability of this approach.
Tumor size and extent decides the exact endoscopic approach required. While smaller tumors are managed via an endonasal approach; medium to large sized tumors require an endoscopic Denker’s / Sturman- Canfield or a more extensive transpterygoid approach [57, 58].
Extended anterior skull base approaches are recommended for intracranial lesions [59].
Exposure is the key to a successful surgery. Adequate exposure allows identification of tumor limits, delineation of feeder vessels, and assessment of tumor’s relation with vital structures. Most of the surgical time is spent in achieving this exposure before starting off with the tumor resection.
It is always advisable to identify and ligate the feeding artery first (usually internal maxillary artery), before starting with tumor dissection.
Posterior septectomy, wherever required, is recommended. This greatly increases the access to the tumor.
Dissection is carried along the tumor pseudocapsule from lateral to medial direction. Any injury to tumor surface can provoke massive bleeding.
For larger tumors, a four-handed technique is recommended [22]. For large tumors with extensive lateral extension into infratemporal fossa/ parapharyngeal space, the four-port Bradoo’s technique is a worthy option [60].
Drilling of pterygoid base at the end of the procedure should be a routine practice, so as to minimize the recurrence rates (Figures 3–8).
The operative room should have the availability of hemostatic materials like SURGICEL, FLOSEAL, TIS SEEL and a functioning bipolar cautery. Access to a blood bank is recommended.
Coblation is a plasma based device that can be used for surface coagulation of the tumor without causing any collateral thermal damage. This shrinks the tumor and also greatly reduces intra-op bleeding.
During preoperative planning stage, it is imperative to discuss with the patient, the possibility to convert an endoscopic approach into an open approach at any given time during the surgery.
CE-MRI showing hyperintense tumor (*) with massive lateral extension into infratemporal fossa.
CE-MRI showing hyperintense tumor (*) in the infratemporal fossa.
CECT showing JNA occupying nasopharynx (1), pterygoid wedge (2), infratemporal fossa (3) and intracranial space (4). Notice the widening of left pterygoid wedge (red arrow) as compared to the right normal pterygoid wedge (green arrow)-
CT angiography showing a vascular tumor (*). Notice the internal maxillary artery supplying this tumor (orange arrow).
Endoscopic view through left nasal cavity: Medial and posterior walls of left maxillary sinus and left inferior turbinate have been removed. 1-nasopharyngeal component of JNA; 2- pterygopalatine fossa + infratemporal fossa component of JNA; 3- remnants of left inferior turbinate; R- right, L- left, S- superior, I- inferior.
Coblation wand being used in juvenile nasopharyngeal angiofibroma endoscopic surgery. 1- coblation wand, 2- tumor, R- right, L- left, S- superior, I- inferior.
Broad skull base infiltration
extensive blood supply from ICA
encasement of ICA
brain infiltration
Considering the pace of progress in endoscopic techniques, it would not be surprising if some more indications are added by the time this chapter reaches the readers.
Though Juvenile angiofibroma is now an established surgical entity, there has been an era when medical management alone was the rule for extensive tumors especially those with intracranial extension. With paradigm shift towards more aggressive surgical procedures for all stages of the tumor, other treatment modalities are now valued as adjuvant therapy only.
The procedure is usually done 24 to 48 hours before the scheduled surgery. Further surgical delay is not appreciated/recommended as tumor gains collateral blood supply through neoangiogenesis. A wide variety of materials are available as embolic agents: microspheres, gelatin sponge, Teflon particles, gel foam, poly-vinyl alcohol, polystyrene, silicone particles, silk, cyanoacrylate, sodium tetradacyl sulphate, autogenous clot, duramater, muscle fragments, etc. 300–500 micrometer spheres are preferred owing to greater blocking capacity of vascular lumen [62].
The procedure is not without complications. Cerebral ischemia and vision loss are known complications following embolic agent migrating to ICA system. Rare complications like cerebral edema, hemiplegia and aphasia have also been reported [63].
This results in almost complete filling of tumor microvasculature with irreversible occlusion of embolized vessels. Tumor gains a dark color (due to tungsten powder with blue dye) which helps to better distinguish it from surrounding normal tissue. Direct cytotoxicity of absolute ethanol has shown good therapeutic effects.
DPTE alone or in combination with TAE has shown to have better devascularisation effects than TAE alone [65, 66].
Hormonal influence on growth of JNA has been speculated since long. An interplay between estrogens and androgens has been associated with tumor proliferation and its spontaneous involution. Various hormonal therapies are recommended based on these concepts.
Flutamide therapy is recommended as a six week preoperative adjuvant therapy for intracranial and intraorbital lesions, recurrent lesions and those with their blood supply primarily from ICA.
Low dose radiotherapy is used for angiofibromas extending intracranially, not amenable to primary surgery. Typically, total radiation dose of 3,500 cGy is given over 3 weeks. A successful response in terms of decreased tumor size and vascularity is seen over several months in 80% of the patients [67, 68]. Those showing no response/incomplete response by 2 years post radiotherapy are deemed as failures and taken up for salvage surgery.
There are numerous side effects to use of radiotherapy at a young age. Posterior capsular opacities, glaucoma, optic nerve atrophy, xerostomia, hypopituitarism, cerebral necrosis, osteoradionecrosis of mandible, skull base osteomyelitis, risk of developing new head–neck tumors later in life, potential malignant transformation of angiofibromas are few of the complications associated with the use of radiotherapy in head and neck region.
Juvenile nasopharyngeal angiofibroma, although an old disease entity, is still fascinating medical experts all over the world. Although still largely unknown, with advanced genetic and molecular studies, we have moved a step closer to find the origin and etiology of this disease. At present, surgery is the mainstay of treatment with endoscopic approach replacing the conventional open approach. Future considerations can be focused on therapeutic embolisation, stereotactic radiotherapy and targeted molecular therapy for a non-surgical cure.
I wish to express my sincere gratitude towards Dr. Anupama Mahajan, Dr. Stuti Mahajan and Dr. Anugeet Sethi for their constant moral support. I am fortunate to have worked with Dr. Rajesh Choudhary and Dr. Bikramjeet Singh on numerous juvenile nasopharyngeal angiofibroma cases. A special vote of thanks to Dr. Rohan Sardana and Dr. Karamjeet Singh Gill for providing valuable insight into the pathology of this disease. I shall always be indebted to ENT Department of my alma mater VMMC & Safdarjung Hospital, New Delhi.
The authors declare no conflict of interest.
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Better integration may entail customizing operation of devices and training programs according to several user characteristics during execution of functional tasks. These characteristics may be physical dimensions, residual capabilities, restored sensory feedback, cognitive perception, or stereotypical actions.",book:{id:"5943",slug:"biomimetic-prosthetics",title:"Biomimetic Prosthetics",fullTitle:"Biomimetic Prosthetics"},signatures:"Raviraj Nataraj",authors:[{id:"203913",title:"Prof.",name:"Raviraj",middleName:null,surname:"Nataraj",slug:"raviraj-nataraj",fullName:"Raviraj Nataraj"}]},{id:"57587",title:"Sensory Feedback Device for Myoelectric Prosthetic Hand",slug:"sensory-feedback-device-for-myoelectric-prosthetic-hand",totalDownloads:1151,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"In this work, a sensory feedback device for myoelectric prosthetic hand was developed to enhance the quality of life (QOL) of myoelectric prosthetic hand users. 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\r\n\tThe four topics of this book series - Pollution; Environmental Resilience and Management; Ecosystems and Biodiversity; and Water Science - will address important areas of advancement in the environmental sciences. They will represent an excellent initial grouping of published works on these critical topics.
\r\n\tSustainable development focuses on linking economic development with environmental protection and social development to ensure future prosperity for people and the planet. To tackle global challenges of development and environment, the United Nations General Assembly in 2015 adopted the 17 Sustainable Development Goals. SDGs emphasize that environmental sustainability should be strongly linked to socio-economic development, which should be decoupled from escalating resource use and environmental degradation for the purpose of reducing environmental stress, enhancing human welfare, and improving regional equity. Moreover, sustainable development seeks a balance between human development and decrease in ecological/environmental marginal benefits. Under the increasing stress of climate change, many environmental problems have emerged causing severe impacts at both global and local scales, driving ecosystem service reduction and biodiversity loss. Humanity’s relationship with resource exploitation and environment protection is a major global concern, as new threats to human and environmental security emerge in the Anthropocene. Currently, the world is facing significant challenges in environmental sustainability to protect global environments and to restore degraded ecosystems, while maintaining human development with regional equality. Thus, environmental sustainability with healthy natural ecosystems is critical to maintaining human prosperity in our warming planet.
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