Characterization of Myogenic Factors in Normal Rat Mesenteric Veins
Bibliographic record
Abstract
Vascular tone is maintained by the sympathetics, other neurohormones and myogenic factors. Myogenic factors have been characterized in arteries; however limited studies have been completed in veins. The objective of this study was to evaluate the contribution of myogenic factors to vascular tone in a large capacitance bed, the mesenteric veins, of normal male rats. Pressure myography was used to study isolated cannulated third order mesenteric venules (2‐12 mmHg) and arterioles (20‐140 mmHg). Arterioles showed myogenic contractions to pressure increases beginning at 60 mmHg, while venules showed evidence of myogenic tone (resistance to stretch) but not myogenic contractions. The contribution of endothelial dilators (N‐nitro‐L‐argentine, 100 µM) to net tone with increasing luminal pressure was minimal in both vessel types. The L‐type calcium channel blocker, Nifedipine (1 µM), abolished myogenic contributions to net tone in arterioles while only partially reducing responses in venules. The protein kinase C inhibitor (PKC), Chelerythrine (2.5 µM), also abolished myogenic contributions to net tone in arterioles; however, responses in venules were only substantially reduced. These findings suggest that in mesenteric venules (1) myogenic factors contribute to net venous tone and (2) myogenic tone is due in part to extracellular calcium and PKC activation and not altered by endothelial nitric oxide release. Grant Funding Source 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) | 0.000 | 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".