Exercise training impacts skeletal muscle gene expression related to the kynurenine pathway
Bibliographic record
Abstract
Exercise positively impacts mood and symptoms of depression; however, the mechanisms underlying these effects are not fully understood. Recent evidence highlights a potential role for skeletal muscle-derived transcription factors to influence tryptophan metabolism, along the kynurenine pathway, which has important implications in depression. This has important consequences for older adults, whose age-related muscle deterioration may influence this pathway and may increase their risk for depression. Although exercise training has been shown to improve skeletal muscle mass in older adults, whether this also translates into improvements in transcription factors and metabolites related to the kynurenine pathway has yet to be examined. The aim of the present study was to examine the influence of a 12-wk exercise program on skeletal muscle gene expression of transcription factors, kynurenine aminotransferase (KAT) gene expression, and plasma concentrations of tryptophan metabolites (kynurenines) in healthy older men over 65 yr of age. Exercise training significantly increased skeletal muscle gene expression of transcription factors (peroxisome proliferator-activated receptor-γ coactivator 1α, peroxisome proliferator-activated receptor-α, and peroxisome proliferator-activated receptor-δ: 1.77, 1.99, 2.18-fold increases, respectively, P < 0.01] and KAT isoforms 1-4 (6.5, 2.1, 2.2, and 2.6-fold increases, respectively, P ≤ 0.01). Concentrations of plasma kynurenines were not altered. These results demonstrate that 12 wk of exercise training significantly altered skeletal muscle gene expression of transcription factors and gene expression related to the kynurenine pathway, but not circulating kynurenine metabolites in older men. These findings warrant future research to determine whether distinct exercise modalities or varying intensities could induce a shift in the kynurenine pathway in depressed older adults.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".