ArticleCurrent opinion in biomedical engineering2023
Label-free optical imaging and sensing for quality control of stem cell manufacturing.
Article in Current opinion in biomedical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Coarse-graining analysis for non-invasive, label-free, and quantitative evaluation of undulating motion in cultured oral mucosa epithelial cell sheets.Regenerative therapy · 2026Article
- AI-Driven Innovations for Quality Control and Standardization: Future Strategies in Adipose-Derived Stem Cell Manufacturing.International journal of molecular sciences · 2026Review
- Exploring In Vitro Mesenchymal Stem Cell Osteodifferentiation via Vibrational Microspectroscopy: A Review.Stem cell reviews and reports · 2025Review
- Pericellular oxygen dynamics in human cardiac fibroblasts and iPSC-cardiomyocytes in high-throughput plates: insights from experiments and modeling.Journal of molecular and cellular cardiology plus · 2025Article
- Hyperspectral Imaging Techniques for Lyophilization: Advances in Data-Driven Modeling Strategies and Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Integrating ChromaLIVE™ dye with an AI-powered image analysis for real-time monitoring of human mesenchymal stem cells differentiation.Biochemistry and biophysics reports · 2025Article
- Optical redox imaging to screen synthetic hydrogels for stem cell-derived cardiomyocyte differentiation and maturation.Biophotonics discovery · 2024Article
- Probing organoid metabolism using fluorescence lifetime imaging microscopy (FLIM): The next frontier of drug discovery and disease understanding.Advanced drug delivery reviews · 2023Review
- Assessing Tumorigenicity in Stem Cell-Derived Therapeutic Products: A Critical Step in Safeguarding Regenerative Medicine.Bioengineering (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Human stem cells provide emerging methods for drug screening, disease modeling, and personalized patient therapies. To meet this growing demand for scale-up, stem cell manufacturing methods must be streamlined with continuous monitoring technologies and automated feedback to optimize growth conditions for high production and consistency. Label-free optical imaging and sensing, including multiphoton microscopy, Raman spectroscopy, and low-cost methods such as phase and transmitted light microscopy, can provide rapid, repeatable, and non-invasive monitoring of stem cells throughout cell differentiation and maturation. Machine learning algorithms trained on label-free optical imaging and sensing features could identify viable cells and predict optimal manufacturing conditions. These techniques have the potential to streamline stem cell manufacturing and accelerate their use in regenerative medicine.
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.