Paradoxical effects of acidosis on the noradrenaline-induced and neurogenic constriction of the rat tail artery at low temperatures
Bibliographic record
Abstract
Although vasodilatation evoked by acidosis at normal body temperature is well known, the reports regarding effect of acidosis on the reactivity of the isolated arteries at low temperatures are nonexistent. This study tested the hypothesis that the inhibitory effect of acidosis on the neurogenic vasoconstriction may be increased by cooling. Using wire myography, we recorded the neurogenic contraction of the rat tail artery segments to the electrical field stimulation in the absence and in the presence of 0.03–10.0 µmol/L noradrenaline. The experiments were conducted at 37 °C or 25 °C and pH 7.4 or 6.6 which was decreased by means of CO2. Noradrenaline at concentration of 0.03–0.1 µmol/L significantly potentiated the neurogenic vasoconstriction at 25 °C, and the potentiation was not inhibited by acidosis. Contrary to our hypothesis, acidosis at a low temperature did not affect the noradrenaline-induced tone and significantly increased the neurogenic contraction of the artery segments in the absence and presence of noradrenaline. These effects of acidosis were partly dependent on the endothelium and L-type Ca2+ channels activation. The phenomenon described for the first time might be of importance for the reduction in the heat loss by virtue of decrease in the subcutaneous blood flow at low ambient temperatures.
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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".