Electromyostimulation with blood flow restriction enhances activation of mTOR and MAPK signaling pathways in rat gastrocnemius muscles
Bibliographic record
Abstract
Neuromuscular electrical stimulation (NMES) combined with blood flow restriction (BFR) induces muscle hypertrophy. However, cellular mechanisms underlying the muscle hypertrophy induced by NMES combined with BFR remain unclear. We tested the hypothesis that NMES combined with BFR would enhance the mechanistic target of rapamycin (mTOR) and mitogen-activated protein kinase (MAPK) signaling pathways. Age-matched male Wistar rats (6 months old, n = 7 per group) were assigned randomly to control, BFR alone (BFR), NMES alone (NMES), and NMES combined with BFR (NMES/BFR) groups. NMES induced 25 isometric contractions lasting 8 s with 4-s resting periods between contractions in the gastrocnemius muscle. Four sets in total were performed, with 1-min intervals between sets. A latex cuff was placed on the proximal portion of the hind limb and BFR at 200 mm Hg was conducted in 4 sets (each set 5 min) with 1-min rest intervals between sets. Venous blood was collected from the lateral tail vein to determine pH, H+ concentration, and lactate concentration before and immediately after the treatments. Expression levels of proteins related to muscle hypertrophy were determined by Western blot analysis. The application of NMES/BFR promoted muscle fatigue more than NMES alone. NMES/BFR induced greater changes in accumulation of metabolites and increase in gastrocnemius muscle weight. The phosphorylation of mTOR and MAPK signaling-related proteins was also enhanced following NMES/BFR, compared with other conditions. Thus, NMES enhanced the activation of mTOR and MAPK signaling pathways when combined with BFR.
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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) | 0.000 | 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) | 0.001 | 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".