# TRANSFER GRANT: Systems Biophysics of Multiscale State Transitions in Cells and Tissues

> **NIH NIH R35** · STATE UNIVERSITY NEW YORK STONY BROOK · 2024 · $110,004

## Abstract

Project Summary
 Our lab develops and applies integrated experimental and computational methods to elucidate the impact
of mechanics on biology at multiple scales. Our goal for the next few years is to uncover how the interplay of
complex biophysical factors in the tissue microenvironment drives structural and functional state transitions at
the cytoskeletal, cellular, and tissue levels. In particular, we will focus on the interplay between osmotic pressure,
extracellular matrix (ECM) crosslinking, and mesoscale ECM architectures. These factors are prominent in
tissues and often simultaneously present, but their fundamental integrated impact on cellular systems is not well
understood. We will investigate how together they act as inputs that program local molecular and cellular
interactions. We will extract the critical input parameter values that induce drastic mode switching, especially in
cytoskeletal organization and function, cell migration, cell-matrix interactions, and collective cell dissemination.
We will determine the mechanisms and consequences of biophysical transitions at different scales and how they
function as on and off switches for global tissue phenotypes.

## Key facts

- **NIH application ID:** 11261386
- **Project number:** 7R35GM142875-05
- **Recipient organization:** STATE UNIVERSITY NEW YORK STONY BROOK
- **Principal Investigator:** Michael MAK
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $110,004
- **Award type:** 7
- **Project period:** 2021-08-06 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11261386

## Citation

> US National Institutes of Health, RePORTER application 11261386, TRANSFER GRANT: Systems Biophysics of Multiscale State Transitions in Cells and Tissues (7R35GM142875-05). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/11261386. Licensed CC0.

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