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Techniques for following the differentiation of human mesenchymal stem cells (hMSCs) in laboratory settings prior to their transplantation into living organisms are essential for progress in tissue engineering and regenerative medicine. In this study, we have used a non-toxic fluorescent dye (ChromaLIVE™) coupled with an artificial intelligence (AutoHCS™) powered image analysis system for real-time monitoring of the differentiation of hMSCs. To validate the performance of this novel Live-Cell Imaging assay, its accuracy was benchmarked to a well-established immunocytochemistry method for studying MSC differentiation into osteoblasts. This innovative method utilizes the distinctive phenotypic signature detected by the non-toxic dye to identify and measure differentiation phenotypes, which were found to align with the expression of osteogenic markers. As a highly sensitive, affordable, non-destructive and scalable kinetic assay, this new technology offers promise as a dependable tool for monitoring stem cell differentiation. By delivering real-time insights into the quality of cell batches, it facilitates prompt adjustments and optimization of culture conditions.
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http://dx.doi.org/10.1016/j.bbrep.2025.102174 | DOI Listing |
J Sep Sci
September 2025
Department of Analytical Chemistry, Faculty of Science, Palacký University Olomouc, Olomouc, Czech Republic.
The increasing use of engineered nanoparticles (NPs) in consumer and biomedical products has raised concern over their potential accumulation, transformation, and toxicity in biological systems. Accurate analytical methods are essential to detect, characterize, and quantify NPs in complex biological matrices. Inductively coupled plasma mass spectrometry (ICP-MS) has emerged as a leading technique due to its high sensitivity, elemental selectivity, and quantitative capabilities.
View Article and Find Full Text PDFBMC Nurs
September 2025
Institute of Business Administration and Business Informatics, IT for the Caring Society, University of Hildesheim, Hildesheim, Germany.
Background: As populations age, informal caregivers play an increasingly vital role in long-term care, with 80% of care provided by family members in Europe. However, many individuals do not immediately recognize themselves as caregivers, especially in the early stages. This lack of awareness can increase physical and emotional stress and delay access to support services.
View Article and Find Full Text PDFCell Commun Signal
September 2025
Department of Cytology, Institute of Anatomy, Medical Faculty, Ruhr-University Bochum, Universitätsstr. 150, Building MA 5/52, Bochum, 44801, Germany.
Background: Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease characterized by oxidative stress and progressive motor neuron degeneration. This study evaluates the potential neuroprotective effects of caffeine in the Wobbler mouse, an established model of ALS.
Methods: Wobbler mice received caffeine supplementation (60 mg/kg/day) via drinking water, and key parameters, including muscle strength, NAD metabolism, oxidative stress, and motor neuron morphology, were assessed at critical disease stages.
J Assist Reprod Genet
September 2025
Department of Gynecology, Pingxiang Maternal and Child Health Hospital, PingXiang, Jiangxi, China.
Objective: This study aimed to identify key predictors of uterine fibroid (UF) recurrence following laparoscopic myomectomy (LM) in reproductive-age women and to construct a predictive nomogram to support individualized clinical decision-making.
Methods: This retrospective cohort study included 459 women who underwent LM. Recurrence of UFs and risk of recurrence were analyzed.
Behav Res Methods
September 2025
Czech Technical University in Prague, Faculty of Electrical Engineering, Department of Cybernetics, Prague, Czech Republic.
Automatic markerless estimation of infant posture and motion from ordinary videos carries great potential for movement studies "in the wild", facilitating understanding of motor development and massively increasing the chances of early diagnosis of disorders. There has been a rapid development of human pose estimation methods in computer vision, thanks to advances in deep learning and machine learning. However, these methods are trained on datasets that feature adults in different contexts.
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