Effects of moderate electrical stimulation on reactive species production by primary rat skeletal muscle cells: Cross talk between superoxide and nitric oxide production
Bibliographic record
Abstract
The effects of a moderate electrical stimulation on superoxide and nitric oxide production by primary cultured skeletal muscle cells were evaluated. The involvement of the main sites of these reactive species production and the relationship between superoxide and nitric oxide production were also examined. Production of superoxide was evaluated by cytochrome c reduction and dihydroethidium oxidation assays. Electrical stimulation increased superoxide production after 1 h incubation. A xanthine oxidase inhibitor caused a partial decrease of superoxide generation and a significant amount of mitochondria-derived superoxide was also observed. Nitric oxide production was assessed by nitrite measurement and by using 4,5-diaminofluorescein diacetate (DAF-2-DA) assay. Using both methods an increased production of nitric oxide was obtained after electrical stimulation, which was also able to induce an increase of iNOS content and NF-κB activation. The participation of superoxide in nitric oxide production was investigated by incubating cells with DAF-2-DA in the presence or absence of electrical stimulation, a superoxide generator system (xanthine-xanthine oxidase), a mixture of NOS inhibitors and SOD-PEG. Our data show that the induction of muscle contraction by a moderate electrical stimulation protocol led to an increased nitric oxide production that can be controlled by superoxide generation. The cross talk between these reactive species likely plays a role in exercise-induced maintenance and adaptation by regulating muscular glucose metabolism, force of contraction, fatigue, and antioxidant systems activities.
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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) | 0.001 | 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".