Impaired proteostasis in obese skeletal muscle relates to altered immunoproteasome activity
Bibliographic record
Abstract
Obesity-associated inflammation and/or oxidative stress can damage intramuscular proteins and jeopardize muscle integrity. The immunoproteasome (iProt) is vital to remove oxidatively modified proteins, but this function may be compromised with obesity. We sought to elucidate whether diet-induced obesity alters intramuscular iProt content and activity in mice to identify a possible mechanism for impaired muscle proteostasis in the obese state. Total proteasome content and activity and estimates of muscle oxidative damage, inflammation, muscle mass and strength were also assessed. Twenty-three male, 5-week-old C57BL/6J mice were fed a high-fat, high-sucrose (HFS; 45% kcal fat, 17% sucrose, n = 12) or low-fat, low-sucrose (LFS; 10% kcal fat, 0% sucrose, n = 11) diet for 12 weeks. Strength was assessed via a weightlifting test. Despite no change in pro-inflammatory cytokines (P > 0.05), oxidative protein damage was elevated within the gastrocnemius (P = 0.036) and tibialis anterior (P = 0.033) muscles of HFS-fed mice. Intramuscular protein damage coincided with reduced iProt and total proteasome activity (P < 0.05), and reductions in relative muscle mass (P < 0.001). Therefore, proteasome dysregulation occurs in obese muscle and may be a critical link in muscle oxidative stress. Novelty: Our results show for the first time that immunoproteasome and total proteasome function is significantly reduced within obese muscle. Visceral fat mass is a significant predictor of diminished proteasome activity in skeletal muscle. Proteasome function is inversely correlated with an intramuscular accumulation of oxidatively damaged proteins.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".