Endothelial modulation of skeletal muscle blood flow andV˙<scp>o</scp><sub>2</sub>during low- and high-intensity contractions
Bibliographic record
Abstract
In the present study, we determined whether endothelin (ET)-1 contributed to the observed reduction in muscle blood flow (Q) during contractions with nitric oxide synthase (NOS) inhibition and whether muscle O(2) uptake (VO(2)) would be affected by the decrease in muscle Q with NOS inhibition at different contraction intensities. Muscle Q, VO(2), O(2) extraction ratio (OER), and tension development (TD) were studied in the in situ gastrocnemius muscle preparation in anesthetized dogs. A decrease in the VO(2)-to-TD ratio (VO(2)/TD) was used as an indicator of O(2) limitation. Three contraction protocols were used: 1) isometric twitch contractions at 2 twitches (tw)/s, 2) the same contractions at 4 tw/s, and 3) pretreatment with an ET(A)-receptor antagonist (BQ-123) before 2 tw/s contractions. The muscle was stimulated to contract, and measures were obtained at steady state (approximately 5-8 min). NOS inhibition (N(omega)-nitro-L-arginine methyl ester) was then induced, and measures were repeated at 2, 5, 10, and 15 min. During 2 tw/s contractions, NOS inhibition reduced Q with and without ET(A)-receptor blockade. In both groups, OER increased in response to the fall in Q, with the result being no change in VO(2)/TD. NOS inhibition also decreased Q during 4 tw/s contractions, but OER did not increase, resulting in a reduction in VO(2)/TD 5 and 15 min after N(omega)-nitro-L-arginine methyl ester. These data indicated that 1) a reciprocal increase in ET-1 during NOS inhibition does not influence active hyperemia in skeletal muscle, and 2) during 4 tw/s contractions, the ischemia with NOS inhibition was associated with either an O(2) limitation or an alteration in the efficiency of muscle contractions.
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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) | 0.001 | 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".