Discordant gene expression in subcutaneous adipose and skeletal muscle tissues in response to exercise training
Bibliographic record
Abstract
Exercise has different effects on different tissues in the body, the sum of which may determine the response to exercise and the health benefits. In the present study, we aimed to investigate whether physical training regulates transcriptional network communites common to both skeletal muscle (SM) and subcutaneous adipose tissue (SAT). Eight such shared transcriptional communities were found in both tissues. Eighteen young overweight adults voluntarily participated in 7 weeks of combined strength and endurance training (five training sessions per week). Biopsies were taken from SM and SAT before and after training. Five of the network communities were regulated by training in SM but showed no change in SAT. One community involved in insulin- AMPK signaling and glucose utilization was upregulated in SM but downregulated in SAT. This diverging exercise regulation was confirmed in two independent studies and was also associated with BMI and diabetes in an independent cohort. Thus, the current finding is consistent with the differential responses of different tissues and suggests that body composition may influence the observed individual whole-body metabolic response to exercise training and help explain the observed attenuated whole-body insulin sensitivity after exercise training, even if it has significant effects on the exercising muscle.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".