Investigating The Effect Of Chronic Muscle Use And Disuse On Innate Immune Signaling In Skeletal Muscle
Bibliographic record
Abstract
Skeletal muscle health is highly dependent on the intricate mitochondrial reticulum that exhibits high levels of adaptability. It is now recognized that mitochondrial perturbations can activate innate immune pathways, such as the NLRP3 inflammasome complex, by augmenting the response against damage-associated molecular patterns (DAMPs). The objective of this study was to investigate how various metabolic conditions affect innate immune activation and mitochondrial health within skeletal muscle, which has not been fully elucidated. To investigate this, we assessed innate immune signaling pathways and mitochondrial parameters within a model of muscle denervation and an aging model combined with endurance training. Our results suggest that NLRP3 inflammasome signaling is responsive to alterations in skeletal muscle activity and can be attenuated with chronic endurance training. Furthermore, we highlight a differential response to exercise with aged muscle in innate immune signaling. This work aims to further the understanding of innate immune signaling pathways within skeletal muscle, which can potentially highlight therapeutic targets to regulate its activation under divergent metabolic conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".