AIMC Topic: Cell Adhesion

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

eLife Nov 22, 2024
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...
Humans Machine Learning Leukemia, Myeloid, Acute Automation Cell Cycle Cell Adhesion Cell Line, Tumor Image Processing, Computer-Assisted Workflow
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Machine learning interpretable models of cell mechanics from protein images.

Cell Jan 8, 2024
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...
Cytoplasm Machine Learning Cell Adhesion Models, Biological Focal Adhesions Cytoskeletal Proteins
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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 Dec 15, 2023
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...
Graphite Cell Adhesion Mechanotransduction, Cellular Deep Learning Proteins Cell Communication
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Topological data analysis of spatial patterning in heterogeneous cell populations: clustering and sorting with varying cell-cell adhesion.

NPJ systems biology and applications Sep 14, 2023
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. ...
Data Analysis Animals Cell Movement Machine Learning Cluster Analysis Cell Adhesion
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White blood cell detection using saliency detection and CenterNet: A two-stage approach.

Journal of biophotonics Sep 29, 2022
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...
Neural Networks, Computer Leukocytes Cell Adhesion
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Engineered Extracellular Matrices with Integrated Wireless Microactuators to Study Mechanobiology.

Advanced materials (Deerfield Beach, Fla.) Aug 7, 2021
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...
Finite Element Analysis Wireless Technology Oligopeptides Cell Adhesion Animals Mice Cell Movement Robotics Extracellular Matrix NIH 3T3 Cells
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Machine learning reveals mesenchymal breast carcinoma cell adaptation in response to matrix stiffness.

PLoS computational biology Jul 23, 2021
Epithelial-mesenchymal transition (EMT) and its reverse process, mesenchymal-epithelial transition (MET), are believed to play key roles in facilitating the metastatic cascade. Metastatic lesions often exhibit a similar epithelial-like state to that ...
Humans Machine Learning Cell Adhesion Cell Count Female Cell Shape Epithelial-Mesenchymal Transition Tumor Microenvironment Adaptation, Physiological Cadherins Biomarkers, Tumor Extracellular Matrix Models, Biological Biophysical Phenomena Vimentin Triple Negative Breast Neoplasms Neoplasm Metastasis Cell Line, Tumor Cell Proliferation Computational Biology Antigens, CD
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Modeling adult skeletal stem cell response to laser-machined topographies through deep learning.

Tissue & cell Sep 15, 2020
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...
Adult Stem Cells Lasers Bone and Bones Cell Adhesion Deep Learning Humans Time Factors Neural Networks, Computer Reproducibility of Results
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LeukocyteMask: An automated localization and segmentation method for leukocyte in blood smear images using deep neural networks.

Journal of biophotonics Apr 10, 2019
Digital pathology and microscope image analysis is widely used in comprehensive studies of cell morphology. Identification and analysis of leukocytes in blood smear images, acquired from bright field microscope, are vital for diagnosing many diseases...
Deep Learning Image Processing, Computer-Assisted Leukocytes Humans Molecular Imaging Automation Cell Adhesion
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Quantitative assessment of cancer cell morphology and motility using telecentric digital holographic microscopy and machine learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Dec 28, 2017
The noninvasive, fast acquisition of quantitative phase maps using digital holographic microscopy (DHM) allows tracking of rapid cellular motility on transparent substrates. On two-dimensional surfaces in vitro, MDA-MB-231 cancer cells assume several...
Neoplasm Invasiveness Holography Breast Neoplasms Actins Cell Line, Tumor Microscopy, Fluorescence Humans Cell Cycle Cell Movement Cell Nucleus Machine Learning Cell Adhesion
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