BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.2.3.1//EN TZID:Asia/Kolkata X-WR-TIMEZONE:Asia/Kolkata BEGIN:VEVENT UID:5@cds.iisc.ac.in DTSTART;TZID=Asia/Kolkata:20230811T110000 DTEND;TZID=Asia/Kolkata:20230811T120000 DTSTAMP:20231102T045245Z URL:https://cds.iisc.ac.in/events/ph-d-thesis-colloquium-cds-modeling-phys iological-transport-at-scales-connecting-cells-to-organs/ SUMMARY:Ph.D. Thesis {Colloquium}: CDS : “Modeling physiological transpor t at scales: connecting cells to organs.” DESCRIPTION:DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES\nPh.D. Thesis Col loquium\n\n_______________________________________________________________ ___________________________\n\nSpeaker : Ms. Deepa Maheshvare\n\nS.R. Numb er : 06-18-01-10-12-16-1-14025\n\nTitle : “Modeling physiological transp ort at scales: connecting cells to organs.”\n\nResearch Supervisor: Prof . Debnath Pal\n\nDate &\; Time : August 11\, 2023 (Friday) at 11:00 AM\ n\nVenue : Room No. 102 (CDS Seminar Hall)\n\n____________________________ ______________________________________________________________\nAbstract\n The physiological system is a complex network in which each organ forms a subsystem\, and different subsystems interact to maintain the body’s ove rall homeostasis. Within each subsystem\, functional networks exist at dif ferent levels of complexity. The vessels that perfuse the cells within a t issue mediate short- and long-distance communication. The ability to simul taneously capture local and global dynamics by hierarchically bridging com munication networks at different scales is a key challenge in holistic phy siology modeling.\n\nWe present a scalable hierarchical framework that all ows us to bridge diverse scales to model biochemicals’ production\, cons umption\, and distribution in a tissue microenvironment. We developed a di screte modeling framework to simulate the gradient-driven advection–disp ersion-reaction physics of multispecies transport in multiscale systems. B iochemical drift in the capillary network\, transcapillary exchange\, and cellular reactions were modeled by translating physical space into a metam odel with functional units. We define graph operators on the finite connec ted network representation of the discrete functional units embedded in th e metamodel. The governing differential equations are modeled to study the inter-compartment dynamics of the well-mixed nodal volumes by formulating the transport dynamics in the vascular domain and the transcapillary exch ange as a ‘tank-in-series’ model. This allows our framework to scale t o large networks and provides the flexibility to fuse multiscale models by encoding imaging data of vascular topology and omics data of cellular rea ctions to enhance systems-level understanding. Our framework is suitable f or reducing the computational cost of spatially discretizing large tissue volumes and for probing the effect of flow topology on biochemical transpo rt to study structure-function relationships in tissues.\n\nNext\, we deve loped a comprehensive and standardized data-driven modeling workflow to bu ild kinetic models of cellular metabolism. There are significant challenge s in developing computational models at the cellular level due to the subs tantial variation in data across different experimental systems\, animal s pecies\, and cell lines. We have created open\, free\, and FAIR (findable\ , accessible\, interoperable\, and reusable) assets that can be used to st udy pancreatic physiology and glucose-stimulated insulin secretion (GSIS). The data curation\, integration\, normalization and data fitting workflow \, and a large database of metabolic data of the pancreatic beta-cell base d on experimental and clinical data from 39 studies spanning 50 years of p ancreatic\, islet\, and beta-cell research in humans\, rats\, mice\, and c ell lines were used to construct a novel data-driven kinetic SBML (Systems Biology Markup Language) model of GSIS in the pancreatic beta-cell. The m odel consists of detailed glycolysis and phenomenological equations for bi phasic insulin secretion coupled to cellular energy state\, ATP dynamics\, and (ATP/ADP ratio). The predicted glucose-dependent response of glycolyt ic intermediates and biphasic insulin secretion are in good agreement with experimental measurements\, and our model predicts that the factors affec ting ATP consumption\, ATP formation\, hexokinase\, phosphofructokinase\, and ATP/ADP-dependent insulin secretion have a major effect on GSIS.\n\nFi nally\, we present KiPhyNet\, an online network simulation tool connecting cellular kinetics and physiological transport. The tool allows users to s imulate and interactively visualize pressure\, velocity\, and concentratio n fields for applications such as flow distribution\, glucose transport\, and glucose-lactate exchange in microvascular networks.\n\nWhen extended f or translational purposes in clinical settings\, the framework and pipelin e developed in this work can advance the simulation of whole-body models a nd are expected to have major applications in personalized medicine and dr ug discovery.\n\n========================================================= ======================\n\nALL ARE WELCOME CATEGORIES:Events,Ph.D. Thesis Colloquium END:VEVENT BEGIN:VTIMEZONE TZID:Asia/Kolkata X-LIC-LOCATION:Asia/Kolkata BEGIN:STANDARD DTSTART:20220811T110000 TZOFFSETFROM:+0530 TZOFFSETTO:+0530 TZNAME:IST END:STANDARD END:VTIMEZONE END:VCALENDAR