Day 1 :
Eclaire MD Foundation, USA
Time : 11:25-12:05
The author received an honorable PhD in mathematics and majored in engineering at MIT. He attended different universities over 17 years and studied seven academic disciplines. He has spent 20,000 hours in T2D research. First, he studied six metabolic diseases and food nutrition during 2010-2013, then conducted research during 2014-2018. His approach is “math-physics and quantitative medicine” based on mathematics, physics, engineering modeling, signal processing, computer science, big data analytics, statistics, machine learning, and AI. 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 8.5 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 99%).
Stanford University, USA
Keynote: Structural studies on Carbapenem-Hydrolyzing Class D serine β-lactamases from Acinetobacter baumannii
Time : 12:05-12:45
Clyde Smith has over 30 years’ experience in the determination of small molecule and protein structures using X-ray crystallography. Dr Smith gained his PhD in Protein Crystallography at Massey University (New Zealand) in 1993, where he studied the structure and metal binding properties of lactoferrin from human milk. He then undertook a two-year NIH-funded postdoctoral fellowship at the University of Wisconsin, working on the structure of the major skeletal muscle protein, myosin. He returned to New Zealand as a FRST postdoctoral fellow studying the structures of thermostable enzymes. In 1997 he was appointed as a Lecturer in Biochemistry in the School of Biological Sciences at the University of Auckland. In late 2003, he moved to the US to take up a Staff Scientist position in the Chemistry Department at Stanford University, working at the Stanford Synchrotron Radiation Lightsource (SSRL). He is currently a Senior Staff Scientist at SSRL. His scientific research in the field of structural biology includes work in antibiotic resistance, folate metabolism and vitamin B12 chemistry.
The class D serine β-lactamases comprise a superfamily of almost 800 enzymes capable of conferring high-level resistance to β-lactam antibiotics, predominantly the penicillin’s including oxacillin and cloxacillin. In recent years it has been discovered that some members of the class D superfamily have evolved the ability to deactivate carbapenems, “last resort” β-lactam antibiotics generally held in reserve for highly drug resistant bacterial infections. These enzymes are collectively known as Carbapenem-Hydrolyzing Class D serine β-Lactamases or CHDLs (1). The mechanism of β-lactam deactivation by the class D serine β-lactamases involves the covalent binding of the antibiotic to an active site serine to form an acyl-enzyme intermediate (acylation). This is followed by hydrolysis of the covalent bond (deacylation), catalyzed by a water molecule activated by a carboxylated lysine residue (2). It was initially thought that the carbapenems acted as potent inhibitors of the class D enzymes since the formation of the covalent acyl-enzyme intermediate effectively expelled all water molecules from the active site, thus preventing the deacylation step. Our structural studies on two CHDLs (3,4) have indicated that their carbapenem hydrolyzing ability may be due to two surface hydrophobic residues which allow for the transient opening and closing of a channel through which water molecules from the milieu can enter the binding site to facilitate the deacylation reaction (Figure). Although the hydrophobic residues responsible for the channel formation are present in all class D β-lactamases, sequence and structural differences nearby may be responsible for the evolution of carbapenemase activity in the CHDLs. These mechanisms will be presented, including some insights into the carbapenemase activity of non-Acinetobacter CHDLs which show a variation in how deacylation is activated. Future work aimed at improved inhibitor design will also be explored.
Stanford University School of Medicine USA
Time : 12:30-12:50
A.C. Matin got his PhD from University of California in Microbiology (1969). He is serving as the Chair of MS senate task force on postdoctoral affairs (2009- present), Member of MS senate steering committee (2008-present) & Senator of Medical School senate (2006-present). He is a Fellow of the American Academy of Microbiology. He got 16 Honors and Awards which are Star Award in Environmental Protection Agency (1991-1997), Review Committee Member in Accreditation Board for Engineering and Technology (1992) and Foundation for Microbiology Lecturer in American Society for Microbiology (1991-1993). He has authored about 37 Publications that include review articles. His Community & International Work involved in Bacterial antibiotic resistance in space flight, Stanford University; NASA Ames and Nuclear waste remediation.
Statement of the problem: Bacterial antibiotic resistance is a world-wide public health problem requiring and new approaches. Background: Sigma S (σs) controls the synthesis of proteins that contribute to the resistance of bacteria like uropathogenic Escherichia coli (UPEC) in the stationary phase of growth, where bacteria are most virulent; σs is encoded by the rpoS gene. Methodology: Colony forming unit formation was used to determine antibiotic sensitivity; a novel microfluidic device determined sensitivity at single-cell level. Results: Lack of rpoS increased UPEC sensitivity to bactericidal antibiotics: gentamicin (Gm), ampicillin and norfloxacin. Gm will be discussed to illustrate the findings with the three antibiotics. Global proteomic analysis implicated weakened antioxidant defense. Use of the psfiA genetic reporter, 3-(p-hydroxyphenyl) fluorescein (HPF) dye, and Amplex Red showed that Gm generated more oxidative stress in the mutant. Cell elongation can compromise the results of HPF, but the antibiotic treatment did not affect the dimensions of stationary phase bacteria. The antioxidant, N-acetyl cysteine (NAC), & anaerobiosis decreased drug lethality. Thus, greater oxidative stress caused by insufficient quenching of endogenous ROS and/or respiration-linked electron leakage contributed to the increased sensitivity of the mutant; this was confirmed also in vivo. Eliminating of quencher proteins, SodA/SodB and KatE/SodA, or the pentose phosphate pathway proteins, Zwf/Gnd and TalA, (source of NADPH required by the quenchers), also generated greater oxidative stress and killing by Gm. The results were confirmed at single-cell level, as well as under microgravity during space flight where astronaut immune response is compromised. Conclusion and Significance: Besides their established mode of action, bactericidal antibiotics also kill bacteria by oxidative stress. Targeting the antioxidant defense will therefore enhance their efficacy. Bioinformatic approaches have identified small molecules that inhibit these proteins and are under study.