AIMC Topic: Mesenchymal Stem Cells

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Machine learning aided single cell image analysis improves understanding of morphometric heterogeneity of human mesenchymal stem cells.

Methods (San Diego, Calif.)
The multipotent stem cells of our body have been largely harnessed in biotherapeutics. However, as they are derived from multiple anatomical sources, from different tissues, human mesenchymal stem cells (hMSCs) are a heterogeneous population showing ...

Uncovering hidden treasures: Mapping morphological changes in the differentiation of human mesenchymal stem cells to osteoblasts using deep learning.

Micron (Oxford, England : 1993)
Deep Learning (DL) is becoming an increasingly popular technology being employed in life sciences research due to its ability to perform complex and time-consuming tasks with significantly greater speed, accuracy, and reproducibility than human resea...

Morphology-based deep learning enables accurate detection of senescence in mesenchymal stem cell cultures.

BMC biology
BACKGROUND: Cell senescence is a sign of aging and plays a significant role in the pathogenesis of age-related disorders. For cell therapy, senescence may compromise the quality and efficacy of cells, posing potential safety risks. Mesenchymal stem c...

Implementation of transfer learning for the segmentation of human mesenchymal stem cells-A validation study.

Tissue & cell
INTRODUCTION: Stem cell therapy has been gaining interest in the regeneration rather than repair of lost human tissues. However, the manual analysis of stem cells prior to implantation is a cumbersome task that can be automated to improve the efficie...

High throughput screening of mesenchymal stem cell lines using deep learning.

Scientific reports
Mesenchymal stem cells (MSCs) are increasingly used as regenerative therapies for patients in the preclinical and clinical phases of various diseases. However, the main limitations of such therapies include functional heterogeneity and the lack of ap...

Optimizing Lipofectamine LTX Complex and G-418 Concentration for Improvement of Transfection Efficiency in Human Mesenchymal Stem Cells.

Archives of Razi Institute
Conventional cancer therapies, including surgery, radiotherapy, and chemotherapy, are not tumor site-specific and have cytotoxic and harmful side effects for normal cells. Mesenchymal stem cells (MSCs), due to their tumor-tropism migration property, ...

Demystifying the long noncoding RNA landscape of small EVs derived from human mesenchymal stromal cells.

Journal of advanced research
INTRODUCTION: The regenerative capacity of mesenchymal stromal cells or medicinal signaling cells (MSCs) is largely mediated by their secreted small extracellular vesicles (sEVs), and the therapeutic efficacy of sEVs can be enhanced by licensing appr...

Investigating heterogeneities of live mesenchymal stromal cells using AI-based label-free imaging.

Scientific reports
Mesenchymal stromal cells (MSCs) are multipotent cells that have great potential for regenerative medicine, tissue repair, and immunotherapy. Unfortunately, the outcomes of MSC-based research and therapies can be highly inconsistent and difficult to ...

Supervised machine learning for automated classification of human Wharton's Jelly cells and mechanosensory hair cells.

PloS one
Tissue engineering and gene therapy strategies offer new ways to repair permanent damage to mechanosensory hair cells (MHCs) by differentiating human Wharton's Jelly cells (HWJCs). Conventionally, these strategies require the classification of each c...

Machine learning to predict mesenchymal stem cell efficacy for cartilage repair.

PLoS computational biology
Inconsistent therapeutic efficacy of mesenchymal stem cells (MSCs) in regenerative medicine has been documented in many clinical trials. Precise prediction on the therapeutic outcome of a MSC therapy based on the patient's conditions would provide va...