Metabolic Reprogramming in Prostate Cancer: Impact of TP53 Gain-of-Function Mutations on Tumor Progression and Therapeutic Vulnerabilities | Chapter 12 | Achievements and Challenges of Medicine and Medical Science Vol. 13

Prostate cancer (PC) is one of the most common malignancies affecting men worldwide, and androgen hormone deprivation therapy (ADT) serves as an effective first-line treatment, inducing favorable responses in advanced PC patients. Despite advancements in the treatment of advanced prostate cancer, including metastatic castration-resistant prostate cancer (mCRPC), the disease remains lethal, often developing resistance to conventional therapies such as androgen deprivation therapy (ADT) and chemotherapy. Therapy resistance poses a significant challenge, particularly in aggressive forms of prostate cancer. Data on TP53 mutations, especially gain-of-function (GOF) mutations, and their specific impact on prostate cancer metabolism remain limited, underscoring the need for a deeper understanding to uncover new therapeutic avenues. This study aimed to explore the metabolic consequences of TP53 GOF mutations (R175H and R273H) in prostate cancer progression using metabolomics analysis. Approximately 300 metabolites were significantly altered across PC3-GFP (KO), PC3-TP53WT (WT), and PC3-TP53 mutant (R175H & R273H) models. Key findings revealed dysregulation of essential metabolites, such as α-ketoglutarate and spermidine, which support cancer cell survival and progression. These insights not only enhance the understanding of the interplay between TP53 mutations and metabolic alterations but also identify potential biomarkers for prognosis and therapeutic targeting in therapy-resistant prostate cancer. In the TP53-R175H mutant, numerous essential metabolites were dysregulated (downregulated: glutamine, GAP/DHAP, and α-ketoglutarate; Upregulated: deoxyuridine, spermidine, and pseudouridine) when compared with the control (KO), thereby causing metabolic shifts that favor cancer cell survival. Conversely, metabolites such as GlaNAC/GlcNAC, adenosine, acetoacetic acid, acetylcholine, octopamine, itaconic acid, lactic acid, and NADP+ are all downregulated in the R273H mutant. While spermine, spermidine, N-acetyl-DL-serine, pseudouridine, deoxyguanosine, sucrose, and AMP/dGMP are upregulated by the R273H mutant but downregulated in GFP (KO). These findings showed that TP53 GOF mutations (R175H & R273H) cause metabolic alterations in numerous metabolites essential for tumor survival and progression. Furthermore, it may provide therapeutic benefits by identifying appropriate biomarkers that could be used as diagnostic and/or prognostic tools for prostate cancer. Future studies should focus on elucidating the distinct metabolic roles of each TP53 mutant, employing advanced techniques such as isotope tracing to track metabolic fluxes in real time. Additionally, therapeutic strategies targeting polyamine metabolism, redox imbalance, and TCA cycle disruptions could provide novel avenues for treatment, particularly for therapy-resistant prostate cancers.

 

Author (s) Details

Farida Jazuli Usman
Department of Biochemistry, Faculty of Basic Medical Sciences, Bayero University Kano, Nigeria.

 

Dikshat Gopal Gupta
Department of Urology and Pathology, The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, 60611, USA, The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA and Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.

 

Sarki A Abdulkadir
Department of Urology and Pathology, The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, 60611, USA, The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA and Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.

 

Ibrahim Muhammad Usman
Department of Biochemistry, Faculty of Basic Medical Sciences, Bayero University Kano, Nigeria.

 

Adamu Jibrin Alhassan
Department of Biochemistry, Faculty of Basic Medical Sciences, Bayero University Kano, Nigeria.

 

Young A Yoo
Department of Urology and Pathology, The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, 60611, USA and The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.

 

Haris Jaafar Bello
Department of Biochemistry, Aliko Dangote University of Science and Technology, Wudil, Kano, Nigeria.

 

Binta G. Kurfi
Department of Biochemistry, Faculty of Basic Medical Sciences, Bayero University Kano, Nigeria.

 

Kamaluddeen Babagana
Department of Biochemistry, Faculty of Basic Medical Sciences, Bayero University Kano, Nigeria.

 

Please see the book here:- https://doi.org/10.9734/bpi/acmms/v13/4559

A Primer to Nutrigenomics | Book Publisher International

Nutrigenomics is an interdisciplinary field that explores the relationship between nutrition and genetics, focusing on how individual genetic variations influence responses to nutrients and dietary patterns. This field combines aspects of molecular biology, genomics, and nutrition to understand how nutrients and bioactive food compounds interact with our genes to affect health outcomes and disease risk. The book "“A Primer to Nutrigenomics” provides an accessible overview of the principles, methodologies, and applications of nutrigenomics, exploring key concepts such as gene-environment interactions, epigenetics, and personalized nutrition. It discusses the role of genetic variation in determining nutrient metabolism, absorption, and utilization, and highlights how understanding these interactions can lead to more effective dietary recommendations tailored to individual genetic profiles. Additionally, the book examines the impact of diet on gene expression and disease prevention, offering insights into the potential of nutrigenomics for advancing personalized medicine, public health, and chronic disease management. Through the integration of cutting-edge research and practical examples, this book serves as a foundational resource for students, professionals, and researchers interested in the evolving field of nutrigenomics.

 

Author (s) Details

Dr. D. Udaya Kumar
Department of Human Genetics, Andhra University, Visakhapatnam, Andhra Pradesh, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-48859-39-6

A Primer to Nutrigenomics | Book Publisher International

Nutrigenomics is an interdisciplinary field that explores the relationship between nutrition and genetics, focusing on how individual genetic variations influence responses to nutrients and dietary patterns. This field combines aspects of molecular biology, genomics, and nutrition to understand how nutrients and bioactive food compounds interact with our genes to affect health outcomes and disease risk. The book "“A Primer to Nutrigenomics” provides an accessible overview of the principles, methodologies, and applications of nutrigenomics, exploring key concepts such as gene-environment interactions, epigenetics, and personalized nutrition. It discusses the role of genetic variation in determining nutrient metabolism, absorption, and utilization, and highlights how understanding these interactions can lead to more effective dietary recommendations tailored to individual genetic profiles. Additionally, the book examines the impact of diet on gene expression and disease prevention, offering insights into the potential of nutrigenomics for advancing personalized medicine, public health, and chronic disease management. Through the integration of cutting-edge research and practical examples, this book serves as a foundational resource for students, professionals, and researchers interested in the evolving field of nutrigenomics.

 

Author (s) Details

Dr. D. Udaya Kumar
Department of Human Genetics, Andhra University, Visakhapatnam, Andhra Pradesh, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-48859-39-6

Metabolomics and Metabolic Pathway Analysis: Decoding Cellular Biochemistry | Chapter 2 | Innovations in Biological Science Vol. 6

 Metabolomics is the systematic study of small molecule metabolites found within cells, tissues, or biofluids. It aims to provide a functional readout of biochemical activities and hence can provide an integrated view of the biochemical status of living systems. Metabolomic studies have been used to better understand various disease states, identify biomarkers, and study the effects of drug treatments or toxic exposures. This chapter will introduce the concepts and technologies behind metabolomics experiments including mass spectrometry and nuclear magnetic resonance spectroscopy. Methods for metabolite identification, quantification and data analysis will be discussed. A key application of metabolomics data is in mapping metabolites to biochemical pathways and constructing metabolic networks. Various bioinformatics resources for pathway mapping and analysis will be presented such as KEGG, Reactome and WikiPathways. Computational approaches for metabolic modeling and simulation will also be covered. Case studies demonstrating how integrated metabolomic and pathway analysis has provided novel insights into cancer metabolism, drug toxicity and personalized medicine will be reviewed. The chapter will conclude by discussing current challenges and future opportunities in metabolomics and metabolic pathway analysis, such as integrating ‘omics data and applying network-based approaches for systems-level understanding of metabolism.

Author(s) Details:

Ebenezer Morayo Ale,
Department of Biochemistry, Faculty of Pure and Applied Sciences, Federal University Wukari, Taraba State, Nigeria.

Olanrewaju Roland Akinseye,
HAT Unit, Nigerian Institute for Trypanosomiasis & Onchocerciasis Research, Ibadan, Nigeria.

Richard-Harris Nsenreuti Boyi
Department of Biochemistry, Faculty of Pure and Applied Sciences, Federal University Wukari, Taraba State, Nigeria.

Victoria Ifeoluwa Ayo
Department of Biochemistry, Faculty of Pure and Applied Sciences, Federal University Wukari, Taraba State, Nigeria.

 

Mgbede Joy Timothy
Department of Biochemistry, Faculty of Pure and Applied Sciences, Federal University Wukari, Taraba State, Nigeria.

 

Steve Osagie Asuelimen
Department of Biochemistry, Faculty of Pure and Applied Sciences, Federal University Wukari, Taraba State, Nigeria.

 

Please see the link here: https://stm.bookpi.org/IBS-V6/article/view/14924

Glucocorticoid Ablation Attenuates Insulin Resistance and Improves Glucose Tolerance in the Obese LA/Ntul//-cp RAT | Chapter 10 | New Advances in Medicine and Medical Science Vol. 2

 The counterregulatory belongings of glucocorticoids and insulin that commonly happen in obesity result in the growth of insulin resistance and injured glycemic responses to dietary carbohydrates. Two together adipose fabric and skeletal power are dependent on insulin actions to cause success glucose rude answer, and the combined hormonal effects enhance disordered processes of minimum energy requirement in insulin dependent tissues that mainly correspond to the magnitude of insulin fighting. To determine the belongings of glucocorticoid inhibition on usual insulin-mediated glycemic processes in obese rats, groups (n=6 -12 rats/phenotype) of usually reared durability-prone congenic lean and obese mammals were fed a Purina food diet from 6 to 9 weeks of age, and overfill with the Chow diet plus a very palatable restaurant diet from 9 to 12 weeks of age. The congenic LA/Ntul//-cp rat strain articulates the obese characteristic soon after detaching but remains glucose prejudiced but non-diabetic thereafter. Subgroups of corpulent animals were subjected to reciprocal adrenalectomy (ADX) at 6 weeks of age to away glucocorticoid contributions to glycemic limits. At 6, 9, and 12 weeks of age, each treatment group realized weight gain (WG) and sweet liquid tolerance (OGT). At 6 and 9 weeks of age on the food diet, WG on ADX-obese rats was equivalent to that of their lean littermates, but was doubly that of their lean littermates from 9 to 12 weeks of age. following 30 to 60 record, OGT responses and the area under the OGT curve were injured but not diabetic in obese mammals of all ages, and reverted to those of lean rats following ADX. At 12 weeks of age, the insulin to sweet liquid ratio (I:G) was logical with insulin opposition in obese rats but not in ADX-obesity or lean rats. At 9 and 12 weeks adult, ADX led to the normalization of OGT and glycemic indications in the obese phenotype. These verdicts support normalizationof typical insulin-mediated parts of glycemic parameters and sweet substance uptake in peripheral tissues following glucocorticoid devaluation due to use of congenic obese rats, and plan that the counterregulatory effects of insulin and glucocorticoid hormones can be contributory to the impaired glycemic reactions in the obese phenotype of the LA/N//-cp (fat) rat and are consistent accompanying a receptor-mediated aspect in the development of insulin fighting and glucose uptake in minor tissues commonly guide the early development of obesity in this place strain.

Author(s) Details:

Orien L. Tulp,
University of Science Arts and Technology, Montserrat, BWI, University of Health and Humanities, Virgin (BVI) and the Einstein Medical Institute, Florida USA.

Aftab R. Awan,
University of Science Arts and Technology, Montserrat, BWI, University of Health and Humanities, Virgin (BVI) and the Einstein Medical Institute, Florida USA.

George P. Einstein,
University of Science Arts and Technology, Montserrat, BWI, University of Health and Humanities, Virgin (BVI) and the Einstein Medical Institute, Florida USA.

Please see the link here: https://stm.bookpi.org/NAMMS-V2/article/view/10628

Characteristics of Gut Microbiota and Metabolomics Associated with Disorders of Lipid Metabolism in Thyroid Cancer | Chapter 2 | Perspective of Recent Advances in Medical Research Vol. 4

 The study's aim search out research the connection between the gut microbiota society, metabolites, and the growth of changed thyroid tumor (TC). The parts and characteristics of the polluted microbiota and metabolites from 50 inmates accompanying TC and 58 active controls(HCs) were driven utilizing 16S rRNA deoxyribonucleic acid sequencing and an joined LC-MS-located metabolomics means.  In the TC inmates, skilled was a important decline in the sort and copiousness of the gut microbiota. The gut microbiota's composition had sustained a large change, and the Bacteroides enterotype ruled it in TC cases. Furthermore, the demonstrative genuineness of the linked model (three type and eight metabolites) and the metabolite model (six metabolites) for changing TC cases from HCs were particularly degree those of the microbial model (seven type). LEfSe reasoning illustrated that type (g_Christensenellaceae_R-7_group, g_Eubacterium_coprostanoligenes_group) and metabolites [27-hydroxycholesterol (27HC), cholesterol] approximately had connection with lipid absorption were considerably lowered in the TC group. In addition, a dispassionate antitoxin sign (total cholesterol) and metabolites (27HC and cholesterol) had the most powerful influence on the sample disposal. Additionally, in the TC group, working pathways complicated in steroid result and lipid digesting were restrained. 27HC was really equated accompanying bacteria that were complicated in absorption in the microbiota-metabolite network (g Christensenellaceae R-7 group). Our study look at the traits of TC victims' gut microbiota. The results concerning this study will aid in recognizing risk variables that impact TC establishment and occurrence in the stomach microecology.

Author(s) Details:

Ganghua Lu,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.

Xiaqing Yu,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.

Wen Jiang,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.

Qiong Luo,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China and Clinical Nuclear Medicine Center, Tongji University School of Medicine, Shanghai, 200072, China.

Junyu Tong,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China and Clinical Nuclear Medicine Center, Tongji University School of Medicine, Shanghai, 200072, China.

Suyun Fan,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China and Clinical Nuclear Medicine Center, Tongji University School of Medicine, Shanghai, 200072, China.

Li Chai,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China and Clinical Nuclear Medicine Center, Tongji University School of Medicine, Shanghai, 200072, China.

Dingwei Gao,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.

Tingting Qiao,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.

Ru Wang,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.

Chengwen Deng,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.

Zhongwei Lv,
Department of Nuclear Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200092, China, Clinical Nuclear Medicine Center, Tongji University School of Medicine, Shanghai, 200072, China, Imaging Clinical Medical Center, Tongji University School of Medicine, Shanghai, 200072, China and Institute of Nuclear Medicine, Tongji University School of Medicine, Shanghai, 200072, China.

Dan Li,
Department of Nuclear Medicine, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510289, China.

Please see the link here: https://stm.bookpi.org/PRAMR-V4/article/view/9127

Integration of Omics in Mental Disorders: Understanding Molecular Connectivity from Prediction to Prevention | Chapter 14 | Current Practice in Medical Science Vol. 4

Stressors are one of several environmental variables, which lead to mental illness. The adoption of sensitivity related with important biomarkers in the detection, assessment, and validation procedures is now necessary due to unmet medical outcomes and monitoring platforms in the field of mental diseases. By validating the functional efficacy of medications or the state of brain function recovery using behavioural assessment and metabolomics, which includes a neuro-pharmacogenomics study, the use of omics in mental disorders and in a health care assessment platform based on macromolecule-dependent data analysis, such as bioinformatics, has the potential to increase the identification of risk genes and treatment options. Though it might seem futuristic, this idea is excellent. Health professionals like clinicians and lab scientists will be able to forecast the likelihood of a disease outbreak, drug addiction, and synaptic malfunction, as well as the likelihood that a treatment will be effective, if numerous databases around the world continue to expand, increasing the likelihood of identifying a strand. The therapeutic alternative, which consists of biological and synthetic components, will be well worth the wait even though practical acceptance would take some time. In this article, we provide a brief overview of mental disorders with unclear etiologies through the visualisation of risk genes and functional vulnerability in the creation of molecular diagnostics using the Omics platform. The Omics platform's potential uses in the future illuminated the space for biomarker discovery, innovation, and the evaluation of assessment techniques for the treatment of mental health illnesses in a clinical context appears promise.

Author(s) Details:

Elizabeth Heroux,

Department of Public Health, Division of Environmental Health Science, New York Medical College, USA.

Aminata Musa,

Department of Public Health, Division of Environmental Health Science, New York Medical College, USA.

Jae-Hyeon Cho,

Institute of Animal Medicine, College of Veterinary Medicine, Gyeongsang National University, Korea.

Diane E. Heck,

Department of Public Health, Division of Environmental Health Science, New York Medical College, USA.

Hong-Duck Kim,

Department of Public Health, Division of Environmental Health Science, New York Medical College, USA.

Please see the link here: https://stm.bookpi.org/CPMS-V4/article/view/7369

Empowering Molecular Network in the Pathogenesis of Obesity with Omics Architecture | Chapter 6 | Emerging Trends in Disease and Health Research Vol.4.

 Obesity is regarded as a major public health concern, owing to the multifaceted factors involved in metabolic complications rooted in multifactorial causes (e.g., environmental toxicity or genetic abnormality), as well as the unmet landscape of the health-care system in search of therapeutic or prevention methods. Evidence that supports Omics as a strategic tool of systemic biology is being used to define the wiring of the molecular circuit in metabolic malfunctions, as well as the evaluation of metabolic modulators such as synthetic drugs, stem cell replacement, and natural secondary metabolites derived from various sources. The link between the nutritional environment and cellular/genetic processes is referred to as nutritional genomics or Nutrigenomics. Its goal is to figure out how nutrition affects a person's genes and health. Nutrigenomics strives to give a genetic understanding of how common food ingredients (i.e., nutrition) modify the expression or structure of an individual's genetic makeup, hence affecting the balance of health and sickness. Furthermore, enhancing detection capabilities from patient clinical samples and monitoring illness progression in reserve populations, who may be at a higher risk of disease susceptibility due to numerous micro- and macro-environmental variables, remains a preventative thread in public health informatics. By utilising the omics platform, which includes epigenetics, metabolomics, nutrigenomics, transcriptomics, pharmacogenomics, and genomics, molecular-based detection systems can forecast evolving disease in terms of key molecule modifications that may contribute to disease pathogenesis and reflect heredity, such as quantitative trait loci, polymorphism, and epigenetic modification. Furthermore, a customised or personalised approach to treating metabolic disease could be applied by building a person's health algorithm in conjunction with a molecular chain-based surveillance and prevention system. To encourage effective biomarker discoveries in the field of molecular therapy and early detection target molecules in obesity, early diagnostic tools as a potential strategy has inspired us in clinical validation and assessment to improve prevention/treatment outcomes for a better translation medicine process. In this short review, we aim to better understand the interaction and connectivity between risks and metabolic disorders like obesity by utilising the molecular drive platform that OMICS technologies are worthy of developing a clinical assessment with regard to diagnosing, predicting, and treating metabolic disease chains (i.e., initiation, progress, and determination) and defining causative molecule-based wiring on host defence machinery after exposure to various unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown unknown Nutrigenomics, as a crucial strategical method to detecting genetic variation or disclosing faults of the host defence system in metabolic disorders, can be used not only to assess one's risk for obesity, but also to treat obesity through the creation of individualised diet regimens.

Author(s) Details:

S. Bartley
Department of Public Health, Division of Environmental Health Science, New York Medical College, Valhalla NY 10595, USA.

H. H. Cho,
College of Veterinary Medicine, Gyeongsang National University, Jiju Daero 501, Jinju-City, Gyeongsangnamdo, 660-701, Korea.


D. E. Heck,
Department of Public Health, Division of Environmental Health Science, New York Medical College, Valhalla NY 10595, USA.


J. H. Cho,
College of Veterinary Medicine, Gyeongsang National University, Jiju Daero 501, Jinju-City, Gyeongsangnamdo, 660-701, Korea.


H. D. Kim,
Department of Public Health, Division of Environmental Health Science, New York Medical College, Valhalla NY 10595, USA.

Please see the link here: https://stm.bookpi.org/ETDHR-V4/article/view/6049 

Integrated Risk Assessment Coupled with Molecular Detection Platform Enhance Personalized Health Care in Metabolic Disorders | Chapter 13 | Emerging Trends in Disease and Health Research Vol. 3

 Type 2 diabetes mellitus (T2DM) is characterised by multidimensional metabolic dysfunction caused by endothelium and beta cell malfunction, as well as regulatory molecular dysfunction caused by stress, lifestyle, food, and physical inactivity anchored in the insulin signalling network. It is caused by both environmental and genetic changes, which may play a role in the development of secondary disease as a risk barrier for microvascular disorders such coronary artery disease, hypertension, obesity, stroke, and dyslipidemia. It's also worth noting that T2DM is a risk factor for mental illness accompanied by cognitive impairment, such as Alzheimer's disease (AD). Using integrated multi-omics techniques, new evidence suggests that the interrelationship between metabolic syndrome and mental disorders involves multiple biological interfaces and connectivity. This review summarises that these categories include core omics strategy, genomics, transcriptomic, and proteomics; advanced omics applications, such as nutrigenomics, and metabolomics, to better understand pathobiology in metabolic illness and improve prediction skill set of T2DM with complicated genetic background and heterogeneity traits. Diagnostic indicators such as glucose concentrations and haemoglobin A1c are being employed in the blood to predict the state of metabolic surveillance. The human whole genome sequencing project ushered in the post-genomic era. Diet and lifestyle have exhibited dual qualities to be employed in customised dietary medicine as treatment guidance and precision medicine for health surveillance, both of which are dependent on genetic diversity as illustrated by gene-diet interaction. Molecular-based risk assessment using Omics methods such as nutrigenomics and metabolomics can help forecast and prevent health difficulties caused by environmental risk and exposure in people who have adapted to the new post-industrialized niche.

Author(S) Details

Sylvester Ndimele
Department of Environmental Health Science, School of Health Sciences and Practice, New York Medical College, Valhalla, NY, 10595, USA.

Miranda L. Carpenter
Department of Environmental Health Science, School of Health Sciences and Practice, New York Medical College, Valhalla, NY, 10595, USA.

Jae-Hyeon Cho
Institute of Agriculture and Life Science, Collegeof Veterinary Medicine, Gyeongsang National University, Jinju, 660-701, Korea.

Diane E. Heck
Department of Environmental Health Science, School of Health Sciences and Practice, New York Medical College, Valhalla, NY, 10595, USA.

Hong Duck Kim
Department of Environmental Health Science, School of Health Sciences and Practice, New York Medical College, Valhalla, NY, 10595, USA.

View Book:- https://stm.bookpi.org/ETDHR-V3/article/view/5889