Severe Muscle Deconditioning Triggers Early Extracellular Matrix Remodeling and Resident Stem Cell Differentiation into Adipocytes in Healthy Men
Bibliographic record
Abstract
Besides the loss of muscle mass and strength, increased intermuscular adipose tissue (IMAT) is now a well-recognized consequence of muscle deconditioning as experienced in prolonged microgravity. IMAT content may alter the muscle stem cell microenvironment. We hypothesized that extracellular matrix structure alterations and microenvironment remodeling induced by fast and severe muscle disuse could modulate fibro-adipogenic progenitor fate and behavior. We used the dry immersion (DI) model that rapidly leads to severe muscle deconditioning due to drastic hypoactivity. We randomly assigned healthy volunteers (n = 18 men) to the control group (only DI, n = 9; age = 33.8 ± 4) or to the DI + thigh cuff group (n = 9; age = 33.4 ± 7). Participants remained immersed in the supine position in a thermo-neutral water bath for 5 days. We collected vastus lateralis biopsies before (baseline) and after DI. 5 days of DI are sufficient to reduce muscle mass significantly, as indicated by the decreased myofiber cross-sectional area in vastus lateralis samples (−18% vs. baseline, p < 0.05). Early and late adipogenic differentiation transcription factors protein levels were upregulated. Platelet-derived growth Factors alpha (PDGFR⍺) protein level and PDGFR⍺-positive cells were increased after 5 days of DI. Extracellular matrix structure was prone to remodeling with an altered ECM composition with 4 major collagens, fibronectin, and Connective Tissue Growth Factor mRNA decreases (p < 0.001 vs. baseline). Wearing thigh cuffs did not have any preventive effect on the measured variable. Our results show that altered extracellular matrix structure and signaling pathways occur early during DI, a severe muscle wasting model, favoring fibro-adipogenic progenitor differentiation into adipocytes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".