AIMC Topic: Cellular Microenvironment
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Molecular features and diagnostic modeling of synovium- and IPFP-derived OA macrophages in the inflammatory microenvironment via scRNA-seq and machine learning.
Journal of orthopaedic surgery and research
Apr 17, 2025
BACKGROUND: Osteoarthritis (OA) is the leading cause of degenerative joint disease, with total joint replacement as the only definitive cure. However, no disease-modifying therapy is currently available. Inflammation and fibrosis in the infrapatellar...
Spatiotemporal feature learning for actin dynamics.
PloS one
Mar 5, 2025
The social amoeba Dictyostelium discoideum is a standard model system for studying cell motility and formation of biological patterns. D. discoideum cells form protrusions and migrate via cytoskeletal reorganization driven by coordinated waves of act...
Robotic Microcapsule Assemblies with Adaptive Mobility for Targeted Treatment of Rugged Biological Microenvironments.
ACS nano
Jan 13, 2025
Microrobots are poised to transform biomedicine by enabling precise, noninvasive procedures. However, current magnetic microrobots, composed of solid monolithic particles, present fundamental challenges in engineering intersubunit interactions, limit...
Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment.
Frontiers in immunology
Jun 24, 2024
Monocytes are pivotal immune cells in eliciting specific immune responses and can exert a significant impact on the progression, prognosis, and immunotherapy of intracranial aneurysms (IAs). The objective of this study was to identify monocyte/macrop...
Fisheye transformation enhances deep-learning-based single-cell phenotyping by including cellular microenvironment.
Cell reports methods
Nov 21, 2022
Incorporating information about the surroundings can have a significant impact on successfully determining the class of an object. This is of particular interest when determining the phenotypes of cells, for example, in the context of high-throughput...
Machine learning-based inverse design for electrochemically controlled microscopic gradients of O and HO.
Proceedings of the National Academy of Sciences of the United States of America
Aug 1, 2022
A fundamental understanding of extracellular microenvironments of O and reactive oxygen species (ROS) such as HO, ubiquitous in microbiology, demands high-throughput methods of mimicking, controlling, and perturbing gradients of O and HO at microscop...
Microfluidic Tissue Engineering and Bio-Actuation.
Advanced materials (Deerfield Beach, Fla.)
Mar 29, 2022
Bio-hybrid technologies aim to replicate the unique capabilities of biological systems that could surpass advanced artificial technologies. Soft bio-hybrid robots consist of synthetic and living materials and have the potential to self-assemble, rege...
Environmental properties of cells improve machine learning-based phenotype recognition accuracy.
Scientific reports
Jul 4, 2018
To answer major questions of cell biology, it is often essential to understand the complex phenotypic composition of cellular systems precisely. Modern automated microscopes produce vast amounts of images routinely, making manual analysis nearly impo...
Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach.
Scientific reports
Apr 25, 2017
Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differ...
Machine learning based methodology to identify cell shape phenotypes associated with microenvironmental cues.
Biomaterials
Jun 25, 2016
Cell morphology has been identified as a potential indicator of stem cell response to biomaterials. However, determination of cell shape phenotype in biomaterials is complicated by heterogeneous cell populations, microenvironment heterogeneity, and m...
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