Day 1 :
University of Babylon, Iraq
Keynote: Molecular interactions of polymethyl methacrylate, polyvinyl alcohol, polyethylene glycol, chitosan, cellulose and starch polymers with iodine
Time : 10:00-10:45
Jaleel Kareem Ahmed has completed his PhD from Baghdad University. He is the Dean of the Institute of Foundry and Hammering. He has registered 8 patents with 40 published papers and 3 books. He is a member in Who is Who network. He is a reviewer in Jon Wily and Sons and Editorial Board Member of Science Publishing Group and a member in Encyclopedia of Chemistry Scientists. He has got the Iraqi Scientist Medal. Currently, he is a Professor of physical chemistry in
the College of Materials Engineering , Babylon University, Iraq.
The interactions between Polymethyl Methacrylate (PMMA), Polyvinyl Alcohol (PVA) Polyethylene Glycol (PEG) as industrial biopolymers and chitosan, cellulose, starch as natural biopolymers with iodine mixed by diethyl ether for homogenous solid mixture show a clear depression in the glass Transition Temperature (Tg) for all polymers as well as new colors appear except cellulose unaffected. It appears that cellulose molecules coated with a film prevent iodine to diffuse through the network structure of cellulose thus no effected its color or its Tg which indicates that molecular structure of cellulose quite different from that of starch and for this fact cellulose not soluble by a solvent and undigested in the human
body. The depression in the Tg values of polymers indicate that iodine ruptures the engineering bonds of the polymers. The most effected Tg is of chitosan (lowered by 40.23˚C, this mean that iodine ruptures both hydrogen bonding through nitrogen and oxygen atoms in chitosan molecule. From Tg values it seems that iodine can acts as moderate plasticizer, by diffusing through the net of biopolymers and natural biopolymers ruptures their secondary bonds result in depression of their Tg except in case of cellulose. The order of Tg depressionchitosan>PMMA=starch>PVA>PEG>cellulose. From Tg values calculation of the energy given by the addition of iodine to the polymers was done. These energies are a function of iodine cause a depression in the original Tg of pure biopolymers 27.394>18.442=18.414>9.316>4.315>0 (kJ mol-1).
Sanford University and UC Berkeley University, USA
Time : 10:45-11:30
Over the past 40 years, He had worked for well-known American organizations such as world recognized institutions UC Berkeley University, Stanford University and ProQuest among others in Silicon Valley and the San Francisco bay area. He has diverse background in both academics and industries. As an e-book specialist and content editor he worked on a wide variety of e-books for well- known international universities, including Harvard, Princeton, Oxford, Cambridge, Stanford, Yale, MIT, and UC Berkeley universities among others educational institutions, and large publishers including Penguin Random House, Elsevier, McGraw-Hill, Wiley and Oxford University Press, As a keynote speaker, He had successfully delivered 45 conferences including 7 talks, presentations at Stanford University and continue sharing my knowledge and experience to help people around the world. Earned achievement and recognition awards, prizes and scholarship.
When you just think about it, The digital world has changed our lives in every way. Education - the days when teachers used chalk, dusters, and blackboards are almost at an end. Black has turned to white, in the form of interactive whiteboards. The white chalk is now digital ink. Digital technology and e-learning made it easier than ever to understand and analyze faster and more efficient about metabolomics and systems biology. It provides the most comprehensive and effective instruction of how metabolomics has the potential to serve an important role in diagnosis and management of human conditions. Digital content has revolutionized the way people in medical field distribute and access information on virtually every platform. How medical Students Benefit from Learning with interactive e-books? The interactive learning market is growing.
- Cancer Therapeutic Approaches
Tsinghua University, China
Time : 11:50-12:30
Zheng Shuo Jin study in Tsinghua University Beijing China since 2014 majoring in the 8-year MD program in School of medicine. Since 2015 I joined professor Dong Wang’s Lab at Tsinghua University, research in breast cancer and epigenetics.
Seoul National University, Republic of Korea
Title: Targeted toxicometabolomics of endosulfan sulfate in adult zebrafish (Danio rerio) using multiple reaction monitoring mode of GC-MS/MS
Time : 12:30-13:10
Jeong Han Kim and his laboratory have expertise in trace level analysis of pesticide residue, hazardous substances, bioactive compounds and primary/ secondary metabolites. His group carries out studies on food safety, environmental safety, pesticide operator exposure, toxic or bioactive metabolite profiling and toxicometabolomics of pesticide.
Endosulfan sulfate (6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9 methano-2,3,4-benzodioxathiepin-3,3-dioxide) is a major oxidized metabolite of endosulfan which is a broad-spectrum chlorinated cyclodiene insecticide. In this study, we used a GC-MS/MS based targeted metabolomic approach using MRM of metabolite to elucidate the toxicological effects of endosulfan sulfate in adult zebrafish. Zebrafish were exposed to endosulfan sulfate at concentrations of 1/10 LC50 and LC50 for 24 and 48 hours. After exposure, the fish was homogenized with liquid N2, extracted with 50% MeOH solution and dried before TMS derivatization (MSTFA+1% TMCS). On GC-MS/MS (Shimadzu TQ8040) MRM library of 381 metabolites were used for screening to detect overall 170 metabolites in zebrafish whole body. The PLS-DA score plot (SIMCA-P+) showed a good separation between the three experimental groups (control, 1/10 LC50, LC50) of 48 hours samples. Based on the VIP and
ANOVA results, 60 metabolites were identified for contributing significantly to the differences in the metabolic profile. Metabolic pathway analysis using MetaboAnalyst 4.0 revealed that those identified metabolites were important for the organism response to endosulfan sulfate. Several pathways were reported by metabolic pathway analysis included aminoacyl-tRNA biosynthesis, valine/leucine/isoleucine biosynthesis, alanine/aspartate/glutamate metabolism, glycerolipid metabolism, arginine/proline metabolism, citrate cycle (TCA cycle), glycine/serine/threonine metabolism, glyoxylate/dicarboxylate metabolism and pentose phosphate pathway. These results suggest that these pathways underwent significant perturbations over the exposure period. This study highlights the application of GC-MS/MS (MRM mode) based targeted metabolomics to understand molecularlevel toxicity of persistent organochlorine pesticides and the results will contributed to the environmental risk assessment of endosulfan sulfate in zebrafish.
Nueva Granada Military University, Colombia
Title: Metabolic profiling of hydroponics-growing mint (mentha x peppermint var. Piperita) leaves under supercritical fluid extraction
Time : 14:10-14:50
Laura Ceron Rincon has her expertise in evaluation in plant grow and development under different nutritional conditions and different stress conditions, this evaluation was based in plant secondary metabolism, because plants produce a great number and complexity of secondary metabolites, this phytochemicals possess a variety of bioactivities. In other hand has her expertise in evaluation of microbial population’s role to understand how they respond to environmental conditions.
Hydroponics consists of production of plants through the supply of required nutrients for their growth and development in the appropriate proportions and under controlled conditions, allowing the nutrients variation directly related to the production and metabolic composition. Recently metabolomics is used for the analysis of quality and searching of useful compounds in food and pharmaceutical industry. Medicinal plants are also known as functional foods due to its high content in secondary metabolites with important medicinal properties can be considered in the treatment of diseases. These compounds include the flavonoids and the isothiocyanates, the latter are synthesized as product of glucosinolates hydrolysis. Peppermint is an aromatic plant with high benefit due to its phytochemical content, so studying its metabolic production in hydroponic systems comprises great interest and applicability. The main objective was therefore to analyze the variation of volatile compound profiles (obtained from supercritical fluid extraction) for mint leaves in hydroponics growing. This research was conducted to design and construct six hydroponic system, they were divided into three systems with standard nutrient solution and other three with nutrient solution+foliar salicylic acid (2 mM). As results, particular changes were found in the profiles of mint-derived volatile metabolites. These changes were mediated by the selective occurrence and/or content of some monoterpenes such as L-menthone, pulegone and terpenes such as menthol. The profiling of volatile metabolites could be an excellent tool to evaluate the mint quality in hydroponics growing. This work was supported by Vicerrectoría de Investigaciones at UMNG Project INV-CIAS-2542.
Michele khoo has founder of COVERS, a paramedical micro-pigmentation service provider. COVERS are base in Singapore and is located at the Novena Medical Center. His profession involves using non-surgical medical tattooing to restore areolar and nipples after breast surgery. He hold an Australian certificate in paramedical micro-pigmentation and he has also certified in infection and disease control. In addition, he hold a certificate for semi-permanent cosmetics from Korea. He has been interviewed and published by reputable local newspaper, 5th May, 2019.
According to American Society of Plastic Surgery, over 106,000 breast reconstruction were performed in 2018. After Mastectomy, “body image altered is the most common psychosocial concern associated with breast cancer, (Mohammad, Khan, and Vanaki, 2018). However, very few people understand the effectiveness of a nipple-tattooing until they get one. Studies have shown that the nipple-areola complex has a high correlation with overall patient satisfaction and acceptance of body image, (Evans, Rasako and Lenert, 2005). Therefore, construction or recreation of a nipple –areola complex that matches the former state in terms of shape, size, and color enhances the effectiveness of the procedure in boosting the self-image of the mastectomy patient. 3D Areolar-nipple micro-pigmentation (tattooing) is safe, non-surgical, it has been endorsed and used for years by medical surgeons in the medical field. Areolar micro-pigmentation procedure is carried out by trained & certified personnel who works with micro-pigmentation (tattooing). Re-creates an illusion of 3D areola and nipples to make the surgical area look more realistic. To carry out the procedure, patients determine the size, shape and color of pigment which is introduced into the dermis layer of the skin with a medical-grade tattoo machine that penetrates slightly deeper. With the right technology, complete nipple areola-nipple complex can draw attention away from the reconstructed breast mound and boosts the confidence of the patient. Mastectomy scar’s appearance can be softened, blended or reduced by tattooing the areolar scar using corrective pigment camouflage techniques.
Gerald C Hsu has received an honorable PhD in Mathematics and majored in Engineering at MIT. He attended different universities over 17 years and studied seven academic disciplines. His main focus is on preventive medicine using prediction tools. He believes that the better the prediction, the more control you have.
Math-Physical Medicine approach (MPM) utilizes mathematics, physics, engineering models and computer science in medical research. Initially, the author spent four years of self-studying six chronic diseases and food nutrition to gain in-depth medical domain knowledge. During 2014, he defined metabolism as a nonlinear, dynamic and organic mathematical system having 10 categories with 500 elements. He then applied topology concept with partial differential equation and nonlinear algebra to construct a metabolism equation. He further defined and calculated two variables, metabolism index and general health status unit. During the past few years, he has collected and processed 1.5 million data. Since 2015, he developed prediction models, i.e. equations for both Postprandial Plasma Glucose (PPG) and Fasting Plasma Glucose (FPG).
He identified 19 influential factors for PPG and five factors for FPG. He developed the PPG model using optical physics and signal processing. Furthermore, by using both wave and energy theories, he extended his research into the risk probability of heart attack or stroke. In this risk assessment, he applied structural mechanics concepts, including elasticity, dynamic plastic and fracture mechanics, to simulate artery rupture and applied fluid dynamics concepts to simulate artery blockage. He further decomposed 12,000 glucose waveforms with 21,000 data and then re-integrated them into three distinctive PPG waveform types which revealed different personality traits and psychological behaviors of type-2 diabetes patients. Furthermore, he also applied fourier transform to conduct frequency domain analyses to discover some hidden characteristics of glucose waves. He then developed an AI Glucometer tool for patients to predict their weight, FPG, PPG and A1C. It uses various computer science tools, including big data analytics, machine learning and artificial intelligence to achieve very high accuracy (95% to
Latvijas Universitate, Latvia
Time : 16:30 - 17:00
University of Algarve, Portugal
Time : 16:30 - 17:00
Pedro M Rodrigues has completed his PhD in Chemistry from the Universidade Nova de Lisboa. He is currently working as a Professor at University of Algarve,
Portugal since 2000 and also a Member of the Center of Marine Science of the Algarce. He has published 44 papers in reputed journals, three book chapters and
has also been serving as an Editorial Board Member of Repute.
Fish is of increasing importance as a protein source in human diet. Farmed fish welfare is currently assessed using stress indicators such as the levels of cortisol, glucose and lactate in the blood plasma, but their reliability has been questioned due to high biological variability and fish adaptation processes. A multiomics approach can be a promisor strategy to discover reliable fish welfare biomarkers, since an integrated analysis can offer the possibility of understanding the complete flow of information in the fish biological system under stressful conditions. Our aim is to identify a restricted protein map as putative fish welfare biomarkers using proteomics, and integrate these results with complementary transcriptomics and metabolomics data, in order to validate these biomarkers as to achieve a global picture of the fish response to stress. Sparus aurata was reared under three different stressful conditions, in triplicate: overcrowding, repetitive net handling (air exposure) and hypoxia, using fish reared under optimal conditions as control.
Method: Fish were sampled after 45 days of trial and protein extracts were prepared from liver samples. Proteins were separated by 2D-DIGE and identified by MALDI-TOF/TOF MS. Putative welfare biomarkers were then chosen based on their stressrelated function, fold-change, score and other parameters and used for primer design. Total RNA was extracted from liver
samples using Trizol® reagent, with DNase treatment, and used for cDNA synthesis.
Results: The mRNA levels of the target genes were assessed by real-time PCR. Comparative proteomics show, in the liver, a total of 147 differentially expressed proteins among conditions, from which 24 were indicated as putative welfare biomarkers and chosen for their transcription level analysis.
Conclusion: This joint analysis provides a starter point for the development of more reliable fish welfare assessment measures
to improve aquaculture sustainability.
National University of Science and Technology, Pakistan
Title: Qualitative modeling of TGF beta-associated biological regulatory network: Insight into renal fibrosis
Time : 16:30 - 17:00
Ayesha Waqar Khan is currently a Researcher who works in collaboration with Jamil Ahmad to model biological regulatory networks of various signaling pathways. Her area of expertise is system biology at Research Centre for Modeling and Simulation (RCMS), NUST, Pakistan. She has supported numerous studies involving BRNs and predicted model verification. Kinetic logic used in this study is a qualitative modeling approach that is incredibly constructive in the study of biological feedback systems. It is an easily accessible method that considers time and thresholds of activity as a suitable method for building simplified models.
Kidney fibrosis is an anticipated outcome of possibly all types of progressive Chronic Kidney Disease (CKD). Epithelial- Mesenchymal Transition (EMT) signaling pathway is responsible for production of matrix-producing fibroblasts and myofibroblasts in diseased kidney. In this study, a discrete model of TGF-beta and CTGF was constructed using René Thomas formalism to investigate renal fibrosis turn over. The kinetic logic proposed by René Thomas is a renowned approach for modeling of Biological Regulatory Networks (BRNs). This modeling approach uses a set of constraints which represents the dynamics of the BRN thus analyzing the pathway and predicting critical trajectories that leads to a normal or diseased state. The molecular connection between TGF-beta, smad2/3 (transcription factor) phosphorylation and CTGF (Connective Tissue Growth Factor) is modeled using GenoTech. The order of BRN is CTGF, TGF-B and smad3 respectively. The predicted cycle depicts activation of TGF-B (TGF-β) via. cleavage of its own pro-domain (0, 1, 0) and presentation to TGFR-II receptor phosphorylating smad3 (smad2/3) in the state (0, 1, 1). Later TGF-B is turned off (0, 0, 1) thereby activating smad3 that
further stimulates the expression of CTGF in the state (1, 0, 1) and itself turns off in (1, 0, 0). Elevated CTGF expression reactivates TGF-B (1, 1, 0) and the cycle continues. The predicted model has generated one cycle and two steady states. Cyclic behavior in this study represents the diseased state in which all three proteins contribute to renal fibrosis. The proposed model is in accordance with the experimental findings of the existing diseased state. Extended cycle results in enhanced CTGF expression through smad2/3 and smad4 translocation in the nucleus. The results suggest that the system converges towards organ fibrogenesis if CTGF remains constructively active along with Smad2/3 and Smad4 that plays an important role in kidney fibrosis. Therefore, modeling regulatory pathways of kidney fibrosis will escort to the progress of therapeutic tools and real-world useful applications such as predictive and preventive medicine.