Higher viscosity participates in the regulation of coronary flow via nitric oxide and indomethacin-sensitive contracting factor
Bibliographic record
Abstract
Few studies have reported on the association of viscosity with coronary circulation. We evaluated the change in coronary flow after dextran was added to a perfusion solution to increase viscosity in isolated rat hearts. We also measured NOx- production induced by the change in shear stress in the coronary effluent, as a marker of NO synthesis. The baseline coronary flow was not influenced by the presence of either the cyclooxygenase inhibitor indomethacin, the thromboxane A2 (TXA2)-prostaglandin H2 (PGH2) receptor antagonist ONO-3708, or the TXA2 synthase inhibitor OKY-046. After exposure to solution containing 0.5% dextran, the coronary flow first decreased and then gradually increased until 10 min. The initial decrease in coronary flow was inhibited by indomethacin, ONO-3708, and OKY-046 individually. The gradual increase was completely inhibited by the NO inhibitor L-NAME, but not by indomethacin or ONO-3708. OKY-046 partially inhibited the increase. NOx- levels in the effluent were higher after the dextran solution was administered, and the increased NOx- levels were inhibited by L-NAME. The increased NOx- levels were not inhibited by inhibitors of the cyclooxygenase pathway. It appears that a higher viscosity of perfusion solution induced a gradual increase in NO production and was associated with increased production of indomethacin-sensitive contracting factor.
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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 | 0.001 | 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".