Cross-talk between skeletal muscle and immune cells: muscle-derived mediators and metabolic implications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Skeletal muscles contain resident immune cell populations and their abundance and type is altered in inflammatory myopathies, endotoxemia or different types of muscle injury/insult. Within tissues, monocytes differentiate into macrophages and polarize to acquire pro- or anti-inflammatory phenotypes. Skeletal muscle macrophages play a fundamental role in repair and pathogen clearance. These events require a precisely regulated cross-talk between myofibers and immune cells, involving paracrine/autocrine and contact interactions. Skeletal muscle also undergoes continuous repair as a result of contractile activity that involves participation of myokines and anti-inflammatory input. Finally, skeletal muscle is the major site of dietary glucose disposal; therefore, muscle insulin resistance is essential to the development of whole body insulin resistance. Notably, muscle inflammation is emerging as a potential contributor to insulin resistance. Recent reports show that inflammatory macrophage numbers within muscle are elevated during obesity and that muscle cells in vitro can mount autonomous inflammatory responses under metabolic challenge. Here, we review the nature of skeletal muscle inflammation associated with muscle exercise, damage, and regeneration, endotoxin presence, and myopathies, as well as the new evidence of local inflammation arising with obesity that potentially contributes to insulin resistance.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it