The inhibition of NOS down regulates adenosine production in the interstitial space of rat skeletal muscle
Bibliographic record
Abstract
It is generally accepted that vasodilatation in skeletal muscle is regulated in part by both adenosine (Ado) and nitric oxide (NO). It has previously been shown by our laboratory that perfusion of 60 μM of ATP into the interstitial space (via microdialysis) more than doubled the interstitial Ado concentration (0.15±0.02 to 0.33±0.04 μM), mediated predominantly by the 5′‐ectonucleotidase. However, a thorough examination of the relationship between NO and Ado production in the interstitial space has yet to be examined. Anesthetized Sprague Dawley rats had microdialysis fibers inserted into the gastrocnemius muscle of each leg and perfused with saline (baseline control) and then with either 10 mM L‐NAME (NOS inhibitor, n = 8 rats, n = 31 probes) or 10 mM L‐NAME + 60 μM ATP (n = 6 rats, n = 14 probes) for 20 minutes at a rate of 5 μl/min. Interestingly, during L‐NAME perfusion interstitial Ado levels were decreased (P<0.05) from baseline levels (0.20±0.01 μM) to below HPLC detection limits. The addition of ATP to the perfusate in an effort to promote Ado production via the 5′‐ectonucleotidase did not restore interstitial Ado concentrations. These data clearly show that the inhibition of NOS dramatically attenuates Ado production, which cannot be reversed by the addition of ATP. These finding strongly suggest that skeletal muscle interstitial Ado production is regulated by NO and/or NOS activity. Supported by NSERC
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".