H
Hirenkumar K. Makadia
Researcher at Thomas Jefferson University
Publications - 6
Citations - 3441
Hirenkumar K. Makadia is an academic researcher from Thomas Jefferson University. The author has contributed to research in topics: Signal transduction & Phosphorylation. The author has an hindex of 5, co-authored 6 publications receiving 2787 citations. Previous affiliations of Hirenkumar K. Makadia include University of Pennsylvania.
Papers
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Journal ArticleDOI
Poly Lactic-co-Glycolic Acid (PLGA) as Biodegradable Controlled Drug Delivery Carrier
TL;DR: This manuscript describes the various fabrication techniques for these devices and the factors affecting their degradation and drug release.
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Computational modeling of cytokine signaling in microglia
Warren D. Anderson,Hirenkumar K. Makadia,Andrew D. Greenhalgh,James S. Schwaber,Samuel David,Rajanikanth Vadigepalli +5 more
TL;DR: It is proposed that differential kinetics in parallel negative feedback loops constitute a novel mechanism underlying the complex and non-intuitive pro- versus anti-inflammatory effects of individual cytokine perturbations.
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Intracellular Information Processing through Encoding and Decoding of Dynamic Signaling Features.
TL;DR: This work develops novel sensitivity and information transfer maps to unravel the dynamic multiplexing of signaling features at each of these network components and identifies downstream snapshot measures required for inferring specific dynamical features of upstream signals involved in the regulation of cellular responses.
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Multiscale Model of Dynamic Neuromodulation Integrating Neuropeptide-Induced Signaling Pathway Activity with Membrane Electrophysiology
Hirenkumar K. Makadia,Warren D. Anderson,Dirk Fey,Thomas Sauter,James S. Schwaber,Rajanikanth Vadigepalli +5 more
TL;DR: The integrated multiscale model provides a new approach for quantitative investigation of neuromodulatory effects on signaling and electrophysiology and revealed that the kinetics emerging from neurommodulatory activation of the signaling network were required to account for the dynamical changes in excitability.
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Molecular variability elicits a tunable switch with discrete neuromodulatory response phenotypes
TL;DR: The study showed that receptor expression and biophysical state interact with distinct relative contributions to neuronal excitability, and found that receptor and channel expression levels influence the neuromodulation response phenotype through a complex though systematic mapping.