Cooling is a potent vasodilator of deep vessels in the rat
Bibliographic record
Abstract
The objectives of this study were to determine the effect of cooling on smooth muscle tone of the pulmonary artery and aorta and to clarify the basic mechanism of these responses. We recorded isometric tension in smooth muscle strips of rat pulmonary artery and aorta in organ baths during stepwise cooling. Cooling responses were tested before and after the addition of various standard agents that interfere with known neurogenic (autonomic blockers, tetrodotoxin) and myogenic mechanisms (calcium channel blockers) of relaxation. We also examined the hypothesis of the presence of a cooling-released substance. Stepwise cooling (37degrees C to 4 degrees C) of aortic smooth muscle induced reproducible graded relaxations that were inversely proportional to temperature. Cooling-induced relaxation was not dependent on a neural mechanism nor the release of neurotransmitters or a cooling-released substance such as NO or CO. Cooling of pulmonary arterial and aortic smooth muscle preparations induced a graded myogenic relaxation inversely proportional to the cooling temperature. The mechanism is not dependent on local nervous or known mediators but related to a direct physico-chemical effect of cooling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.002 | 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".