Tetramethylpyrazine ameliorated disuse-induced gastrocnemius muscle atrophy in hindlimb unloading rats through suppression of Ca<sup>2+</sup>/ROS-mediated apoptosis
Bibliographic record
Abstract
The purpose of this study was to examine the possible mechanism underlying the protective effect of tetramethylpyrazine (TMP) against disuse-induced muscle atrophy. Sprague−Dawley rats were randomly assigned to receive 14 days of hindlimb unloading (HLU, a model of disuse atrophy) or cage controls. The rats were given TMP (60 mg/kg body mass) or vehicle (water) by gavage. Compared with vehicle treatment, TMP significantly attenuated the loss of gastrocnemius muscle mass (−33.56%, P < 0.01), the decrease of cross-sectional area of slow fiber (−10.99%, P < 0.05) and fast fiber (−15.78%, P < 0.01) during HLU. Although TMP failed to further improve recovery of muscle function or fatigability compared with vehicle treatment, it can suppress the higher level of lactate (−22.71%, P < 0.01) induced by HLU. Besides, TMP could effectually reduce the increased protein expression of muscle RING-finger protein 1 induced by HLU (−14.52%, P < 0.01). Furthermore, TMP can ameliorate the calcium overload (−54.39%, P < 0.05), the increase of malondialdehyde content (−19.82%, P < 0.05), the decrease of superoxide dismutase activity (21.34%, P < 0.05), and myonuclear apoptosis (−78.22%, P < 0.01) induced by HLU. Moreover, TMP significantly reduced HLU-induced increase of Bax to B-cell lymphoma 2 (−36.36%, P < 0.01) and cytochrome c release (−36.16%, P < 0.05). In conclusion, TMP attenuated HLU-induced gastrocnemius muscle atrophy through suppression of Ca2+/reactive oxygen species increase and consequent proteolysis and apoptosis. Therefore, TMP might exhibit therapeutic effect against oxidative stress, cytosolic calcium overload, and mitochondrial damage in disuse-induced muscle atrophy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".