Multimodal cell atlas of the ageing human skeletal muscle

United Kingdom News News

Multimodal cell atlas of the ageing human skeletal muscle
United Kingdom Latest News,United Kingdom Headlines
  • 📰 Nature
  • ⏱ Reading Time:
  • 91 sec. here
  • 3 min. at publisher
  • 📊 Quality Score:
  • News: 40%
  • Publisher: 68%

Muscle atrophy and functional decline (sarcopenia) are common manifestations of frailty and are critical contributors to morbidity and mortality in older people1. Deciphering the molecular mechanisms underlying sarcopenia has major implications for understanding human ageing2.

Muscle atrophy and functional decline are common manifestations of frailty and are critical contributors to morbidity and mortality in older people. Yet, progress has been slow, partly due to the difficulties of characterizing skeletal muscle niche heterogeneity and obtaining well-characterized human samples.

Skeletal muscle comprises large multinucleated myofibres with distinct contractile and metabolic activities controlled by the activity of motoneurons that contact the myofibres at the neuromuscular junction . Muscles also contain a variety of less abundant mononucleated cells, including muscle stem cells , fibro-adipogenic progenitors , adipocytes, fibroblast-like cells, immune cells, vascular cells and Schwann cells.

Here we aimed to generate a comprehensive transcriptomic and epigenomic cell atlas of the human locomotor skeletal muscle across different age groups and sexes, including individuals aged ≥84 years with signs of sarcopenia.To investigate the molecular changes that occur in the human skeletal muscle with ageing, we obtained hindlimb muscle biopsies from 31 participants from Spain and China, who were divided into two age groups: adults .

Gonzalez‐Freire, M. et al. Skeletal muscle ex vivo mitochondrial respiration parallels decline in vivo oxidative capacity, cardiorespiratory fitness, and muscle strength: The Baltimore Longitudinal Study of Aging.MacQuarrie, K. L. et al. Comparison of genome-wide binding of MyoD in normal human myogenic cells and rhabdomyosarcomas identifies regional and local suppression of promyogenic transcription factors.Rigillo, G. et al.

P.M.-C. and M.A.E. supervised the study. Y.L., I.R.-P., J.I., E.P., A.L.S., P.M.-C. and M.A.E. conceptualized the study and wrote the manuscript. Y.L., I.R.-P., J.A., A.L.S., J.S., P.G., V.L. and E.A. performed the experiments. Y.L., I.R.-P., J.A. and J.L. analysed the data. E.G.-D., J.V., J.D.-F, M.C.G.-C. and Y.S. collected the muscle biopsies. J.Z., Y.Y. and C.L. provided technical support. L.L. and X.X. gave relevant advice. I.R.-P., J.I. and Y.L. drew the schematic. J.L.

We have summarized this news so that you can read it quickly. If you are interested in the news, you can read the full text here. Read more:

Nature /  🏆 64. in US

United Kingdom Latest News, United Kingdom Headlines

Similar News:You can also read news stories similar to this one that we have collected from other news sources.

Unimodal Intermediate Training for Multimodal Meme Sentiment ClassificationUnimodal Intermediate Training for Multimodal Meme Sentiment ClassificationExplore a novel approach to improve multimodal meme sentiment classification by supplementing training with unimodal sentiment data.
Read more »

Unimodal Intermediate Training for Multimodal Meme Sentiment Classification: Architectural DetailsUnimodal Intermediate Training for Multimodal Meme Sentiment Classification: Architectural DetailsExplore the impact of unimodal training on enhancing meme sentiment analysis and strategies in multimodal meme classifiers for improved performance.
Read more »

Unimodal Training for Multimodal Meme Sentiment Classification—Metric: Weighted F1-ScoreUnimodal Training for Multimodal Meme Sentiment Classification—Metric: Weighted F1-ScoreExplore the impact of unimodal training on enhancing meme sentiment analysis and strategies in multimodal meme classifiers for improved performance.
Read more »

Text-STILT, Meme Sentiment Analysis, Limitations, Future Works, Multimodal ClassifiersText-STILT, Meme Sentiment Analysis, Limitations, Future Works, Multimodal ClassifiersDiscover the limitations and future prospects of Text-STILT in meme sentiment analysis, exploring challenges, opportunities, and the future of meme classifiers.
Read more »

Exploring Multimodal Meme Sentiment Analysis: Architectural Comparisons and Training StrategiesExploring Multimodal Meme Sentiment Analysis: Architectural Comparisons and Training StrategiesDiscover the latest strategies and comparative insights into optimizing meme sentiment analysis through multimodal classifiers.
Read more »

'Multimodal is the most unappreciated AI breakthrough' says DoNotPay CEO Joshua Browder'Multimodal is the most unappreciated AI breakthrough' says DoNotPay CEO Joshua BrowderJoshua Browder, Founder/CEO of DoNotPay, joined the HackerNoon community to discuss AI agents, dividends, and what's next for DoNotPay.
Read more »



Render Time: 2025-04-06 17:35:10