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UID:57@cds.iisc.ac.in
DTSTART;TZID=Asia/Kolkata:20240621T110000
DTEND;TZID=Asia/Kolkata:20240621T120000
DTSTAMP:20240610T180046Z
URL:https://cds.iisc.ac.in/events/ph-d-thesis-defense-online-mode-cds-21-j
 une-2024modeling-physiological-transport-at-scales-connecting-cells-to-org
 ans/
SUMMARY:Ph.D: Thesis Defense: ONLINE MODE: CDS: 21\, June 2024"Modeling phy
 siological transport at scales: connecting cells to organs"
DESCRIPTION:DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES\nPh.D. Thesis Def
 ense\n\n\n\nSpeaker : Ms. Deepa Maheshvare M\nS.R. Number : 06-18-01-10-12
 -16-1-14025\nTitle : "Modeling physiological transport at scales: connecti
 ng cells to organs"\nResearch Supervisor : Prof. Debnath Pal\nDate &amp\; 
 Time : June 21\, 2024 (Friday)\, 11:00 AM\nVenue : The Thesis Defense will
  be held on MICROSOFT TEAMS\nPlease click on the following link to join th
 e Thesis Defense:\nMS Teams link\n\n\n\nABSTRACT\nThe physiological system
  is a complex network in which each organ forms a subsystem\, and the func
 tional networks in different subsystems communicate to maintain body's ove
 rall homeostasis. The ability to simultaneously capture local and global d
 ynamics by hierarchically bridging communication networks at different sca
 les is a key challenge in holistic physiology modeling.\nWe present a scal
 able hierarchical framework that allows us to bridge diverse scales to mod
 el biochemicals' production\, consumption\, and distribution in tissue mic
 roenvironments. We developed a discrete modeling framework to simulate the
  gradient-driven advection–dispersion-reaction physics of multispecies t
 ransport in multiscale systems. The physical space is translated into a me
 tamodel\, and we define graph operators on the finite connected network re
 presentation of the discrete functional units embedded in the metamodel. T
 he governing differential equations capture the inter-compartment dynamics
  of the well-mixed nodal volumes by formulating the transport dynamics in 
 the vascular domain\, transcapillary exchange\, and metabolism in the tiss
 ue domain as a 'tank-in-series' model. This allows our framework to scale 
 to large networks and provides the flexibility to fuse multiscale models b
 y encoding imaging data of vascular topology and omics data to enhance sys
 tems-level understanding. Our framework is suitable for reducing the compu
 tational cost of spatially discretizing large tissue volumes and for probi
 ng the effect of flow topology on biochemical transport to study structure
 -function relationships in tissues.\nNext\, we developed a comprehensive a
 nd standardized data-driven modeling workflow to address the challenges fa
 ced in developing kinetic models of metabolism in single cells. We have cr
 eated open\, free\, and FAIR (findable\, accessible\, interoperable\, and 
 reusable) assets to study pancreatic physiology and glucose-stimulated ins
 ulin secretion (GSIS). The data curation\, integration\, normalization and
  data fitting workflow\, and a large database of metabolic data from 39 st
 udies spanning 50 years of pancreatic\, islet\, and β-cell research in hu
 mans\, rats\, mice\, and cell lines were used to construct a novel data-dr
 iven kinetic SBML (Systems Biology Markup Language) model. The model consi
 sts of detailed glycolysis and phenomenological equations for biphasic ins
 ulin secretion coupled to ATP dynamics\, and (ATP/ADP ratio). The predicti
 ons of glycolytic intermediates and biphasic insulin secretion are in good
  agreement with experimental data\, and our model predicts the factors aff
 ecting ATP consumption\, ATP formation\, hexokinase\, phosphofructokinase\
 , and ATP/ADP-dependent insulin secretion influence GSIS.\nFinally\, we pr
 esent KiPhyNet\, an online network simulation tool connecting cellular kin
 etics and physiological transport. It allows users to simulate and interac
 tively visualize pressure\, velocity\, and concentration fields for applic
 ations such as flow distribution\, glucose transport\, and glucose-lactate
  exchange in microvascular networks. When extended for translational purpo
 ses in clinical settings\, the framework and pipeline developed in this wo
 rk can advance the simulation of whole-body models and are expected to hav
 e major applications in personalized medicine.\n\n\n\nALL ARE WELCOME
CATEGORIES:Events,Thesis Defense
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