ArticleCurrent research in biotechnology2023
Phenotyping senescent mesenchymal stromal cells using AI image translation.
Article in Current research in biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Cell-based therapies of autoimmune diseases in the context of artificial intelligence development.Clinical and experimental medicine · 2026Review
- Senomorphic Small Extracellular Vesicles Delivered by a Tissue-Adhesive α-Lipoic-Acid Hydrogel Enable Immuno-Rejuvenation for Bone-Tendon Interface Regeneration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Artificial Intelligence Driven Innovation: Advancing Mesenchymal Stem Cell Therapies and Intelligent Biomaterials for Regenerative Medicine.Bioengineering (Basel, Switzerland) · 2025Review
- Article
- Current Trends and Future Opportunities of AI-Based Analysis in Mesenchymal Stem Cell Imaging: A Scoping Review.Journal of imaging · 2025Review
- Cell condensation initiates organogenesis: the role of actin dynamics in supracellular self-organizing process.Cell & bioscience · 2025Review
- Extensible Immunofluorescence (ExIF) accessibly generates high-plexity datasets by integrating standard 4-plex imaging data.Nature communications · 2025Article
- How artificial intelligence can enable personalized mesenchymal stem cell-based therapeutic strategies in systemic lupus erythematosus.Frontiers in immunology · 2025Review
- Measurable Metrics of Mesenchymal Stem Cell Aging.Sovremennye tekhnologii v meditsine · 2025Article
- Towards Healthy Longevity: Comprehensive Insights from Molecular Targets and Biomarkers to Biological Clocks.International journal of molecular sciences · 2024Review
- Applications of artificial intelligence in regenerative dentistry: promoting stem cell therapy and the scaffold development.Frontiers in cell and developmental biology · 2024Review
- Trustworthy in silico cell labeling via ensemble-based image translation.Biophysical reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Mesenchymal stromal cells (MSCs) offer promising potential in biomedical research, clinical therapeutics, and immunomodulatory therapies due to their ease of isolation and multipotent, immunoprivileged, and immunosuppersive properties. Extensive efforts have focused on optimizing the cell isolation and culture methods to generate scalable, therapeutically-relevant MSCs for clinical applications. However, MSC-based therapies are often hindered by cell heterogeneity and inconsistency of therapeutic function caused, in part, by MSC senescence. As such, noninvasive and molecular-based MSC characterizations play an essential role in assuring the consistency of MSC functions. Here, we demonstrated that AI image translation algorithms can effectively predict immunofluorescence images of MSC senescence markers from phase contrast images. We showed that the expression level of senescence markers including senescence-associated beta-galactosidase (SABG), p16, p21, and p38 are accurately predicted by deep-learning models for Doxorubicin-induced MSC senescence, irradiation-induced MSC senescence, and replicative MSC senescence. Our AI model distinguished the non-senescent and senescent MSC populations and simultaneously captured the cell-to-cell variability within a population. Our microscopy-based phenotyping platform can be integrated with cell culture routines making it an easily accessible tool for MSC engineering and manufacturing.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.