AIMC Topic: Cell Adhesion

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Deep learning reveals how cells pull, buckle, and navigate fibrous environments.

Proceedings of the National Academy of Sciences of the United States of America
Cells in tissues navigate fibrous environments fundamentally differently than they do on flat substrates, but the establishment of cell forces in physiological fibrous settings remains poorly understood. Although factors such as the stiffness of the ...

Recellularization of scaffolds derived from precision-cut kidney slices.

Biomedical materials (Bristol, England)
The global rise in chronic kidney disease necessitates innovative solutions for end-stage renal disease that can help to overcome the limitations of the only available treatment options, transplantation and dialysis. Tissue engineering presents a pro...

Automated workflow for the cell cycle analysis of (non-)adherent cells using a machine learning approach.

eLife
Understanding the cell cycle at the single-cell level is crucial for cellular biology and cancer research. While current methods using fluorescent markers have improved the study of adherent cells, non-adherent cells remain challenging. In this study...

Machine learning interpretable models of cell mechanics from protein images.

Cell
Cellular form and function emerge from complex mechanochemical systems within the cytoplasm. Currently, no systematic strategy exists to infer large-scale physical properties of a cell from its molecular components. This is an obstacle to understandi...

Regulated Behavior in Living Cells with Highly Aligned Configurations on Nanowrinkled Graphene Oxide Substrates: Deep Learning Based on Interplay of Cellular Contact Guidance.

ACS nano
Micro-/nanotopographical cues have emerged as a practical and promising strategy for controlling cell fate and reprogramming, which play a key role as biophysical regulators in diverse cellular processes and behaviors. Extracellular biophysical facto...

Topological data analysis of spatial patterning in heterogeneous cell populations: clustering and sorting with varying cell-cell adhesion.

NPJ systems biology and applications
Different cell types aggregate and sort into hierarchical architectures during the formation of animal tissues. The resulting spatial organization depends (in part) on the strength of adhesion of one cell type to itself relative to other cell types. ...

White blood cell detection using saliency detection and CenterNet: A two-stage approach.

Journal of biophotonics
White blood cell (WBC) detection plays a vital role in peripheral blood smear analysis. However, cell detection remains a challenging task due to multi-cell adhesion, different staining and imaging conditions. Owing to the powerful feature extraction...

Engineered Extracellular Matrices with Integrated Wireless Microactuators to Study Mechanobiology.

Advanced materials (Deerfield Beach, Fla.)
Mechanobiology explores how forces regulate cell behaviors and what molecular machinery are responsible for the sensing, transduction, and modulation of mechanical cues. To this end, probing of cells cultured on planar substrates has served as a prim...

Modeling adult skeletal stem cell response to laser-machined topographies through deep learning.

Tissue & cell
The response of adult human bone marrow stromal stem cells to surface topographies generated through femtosecond laser machining can be predicted by a deep neural network. The network is capable of predicting cell response to a statistically signific...