Award Abstract # 2224708
Study of Dynamical Mechanical Properties of Pericellular Layer

NSF Org: CMMI
Division of Civil, Mechanical, and Manufacturing Innovation
Recipient: TRUSTEES OF TUFTS COLLEGE
Initial Amendment Date: July 12, 2022
Latest Amendment Date: May 31, 2024
Award Number: 2224708
Award Instrument: Standard Grant
Program Manager: Shivani Sharma
shisharm@nsf.gov
 (703)292-4204
CMMI
 Division of Civil, Mechanical, and Manufacturing Innovation
ENG
 Directorate for Engineering
Start Date: August 1, 2022
End Date: July 31, 2025 (Estimated)
Total Intended Award Amount: $648,721.00
Total Awarded Amount to Date: $656,721.00
Funds Obligated to Date: FY 2022 = $648,721.00
FY 2024 = $8,000.00
History of Investigator:
  • Igor Sokolov (Principal Investigator)
    Igor.Sokolov@tufts.edu
  • Vera Gorbunova (Co-Principal Investigator)
  • Mojtaba Azadi Sohi (Co-Principal Investigator)
Recipient Sponsored Research Office: Tufts University
80 GEORGE ST
MEDFORD
MA  US  02155-5519
(617)627-3696
Sponsor Congressional District: 05
Primary Place of Performance: Tufts University
169 HOLLAND ST FL 3
SOMERVILLE
MA  US  02144-2401
Primary Place of Performance
Congressional District:
07
Unique Entity Identifier (UEI): WL9FLBRVPJJ7
Parent UEI: WL9FLBRVPJJ7
NSF Program(s): BMMB-Biomech & Mechanobiology
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01002425DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 028E, 070Z, 116E, 9178, 9231, 9251
Program Element Code(s): 747900
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

This project will develop novel tools to study physical properties of individual biological cells at the nanoscale. The properties of a brush-like part of cells that covers the cell body of most cells have remained unknown. This is interesting because it is known that the biological changes in this brush layer are correlated with many human diseases, like cancer, cardiovascular diseases, and even aging. This work will support the development of experimental and theoretical methods to study the physical properties of this brush layer on individual cells. The developed methods will be applied to study cells of one of the most puzzling creatures, naked mole rats, which are long-lived and highly resistant to cancer. This study of age-related changes in the brush layer may eventually shed light on the mechanisms responsible for the exponential increase in the prevalence of certain diseases (including cancer) associated with aging. This multidisciplinary work will combine expertise from physics, engineering, and biology of researchers from three different institutions. This multi-university project will help broaden participation of underrepresented groups in research and have a positive impact on engineering education.

Atomic force microscopy will be used to develop a novel high-resolution experimental method to measure the dynamical mechanical properties of the pericellular layer surrounding cells. The project's approach arises from a novel technique, Fourier-transform dynamical mechanical analysis, a fast high-resolution quantitative method will allow for measuring frequency-dependent storage and loss moduli at the subcellular level. These mechanical properties are expected to be highly nontrivial. Therefore, it is expected that advanced mechanical models, such as various viscoelastic and poroelastic contact models, will be necessary. These models will be investigated and compared with the experimental results to understand the physical and mechanical nature of the pericellular brush layer. The research team will apply the developed methods to study the mechanics of the pericellular layer of fibroblasts of naked mole rats. The difference between these animals and other rodents like the guinea pig, rats, mice will be investigated to learn the aging-related changes in naked mole rats in comparison with regular aging rodents. The importance of particular polysaccharides, such as hyaluronic acid, for the mechanics of the pericellular layer will be studied. It will fill the gap in our knowledge on the specific features of mechanics of the pericellular layer of naked mole rats and contribute to the physics of cancer and longevity.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

Note:  When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

Iraniparast, Mahshid and Peng, Berney and Sokolov, Igor "Towards the Use of Individual Fluorescent Nanoparticles as Ratiometric Sensors: Spectral Robustness of Ultrabright Nanoporous Silica Nanoparticles" Sensors , v.23 , 2023 https://doi.org/10.3390/s23073471 Citation Details
Makarova, Nadezda and Lekka, Magorzata and Gnanachandran, Kajangi and Sokolov, Igor "Mechanical Way To Study Molecular Structure of Pericellular Layer" ACS Applied Materials & Interfaces , v.15 , 2023 https://doi.org/10.1021/acsami.3c06341 Citation Details
Petrov, Mikhail and Sokolov, Igor "Identification of Geometrical Features of Cell Surface Responsible for Cancer Aggressiveness: Machine Learning Analysis of Atomic Force Microscopy Images of Human Colorectal Epithelial Cells" Biomedicines , v.11 , 2023 https://doi.org/10.3390/biomedicines11010191 Citation Details
Petrov, Mikhail and Sokolov, Igor "Machine Learning Allows for Distinguishing Precancerous and Cancerous Human Epithelial Cervical Cells Using High-Resolution AFM Imaging of Adhesion Maps" Cells , v.12 , 2023 https://doi.org/10.3390/cells12212536 Citation Details
Sokolov, I "On machine learning analysis of atomic force microscopy images for image classification, sample surface recognition" Physical Chemistry Chemical Physics , v.26 , 2024 https://doi.org/10.1039/D3CP05673B Citation Details

Please report errors in award information by writing to: awardsearch@nsf.gov.

Print this page

Back to Top of page