Role of endothelin ET<sub>A</sub>‐ and ET<sub>B</sub>‐receptors in haemodynamic compensation following haemorrhage in anaesthetized rats
Bibliographic record
Abstract
1. This study examined the role of endothelin ET(A) and ET(B) receptors on haemodynamic compensation following haemorrhage (-17.5 ml kg(-1)) in thiobutabarbitone-anaesthetized rats. Rats were divided into four groups (n=6 each): time-control, haemorrhage-control, haemorrhage after treatment with FR 139317 (ET(A)-receptor antagonist), and haemorrhage after treatment with BQ-788 (ET(B)-receptor antagonist). 2. In the time-control rats, there were no significant changes in any haemodynamics for the duration of the experiments. Relative to the time-control rats, rats given haemorrhage had reduced mean arterial pressure (MAP), cardiac output (CO) and mean circulatory filling pressure (MCFP), but increased systemic vascular resistance (R(SV)). Venous resistance (R(V)) was slightly (but insignificantly) reduced by haemorrhage. MAP, however, gradually returned towards baseline (-17+/-4 and -3+/-2 mmHg at 10 and 60 min after haemorrhage, respectively) as a result of a further increase in R(SV). 3. Pre-treatment with FR 139317 (i.v. 1 mg kg(-1), followed by 1 mg kg(-1) h(-1)) accentuated haemorrhage-induced hypotension through abolition of the increase in R(SV). FR 139317 did not modify haemorrhage-induced changes in CO, MCFP and R(V). 4. Pre-treatment of BQ-788 (3 mg kg(-1)) did not affect MAP or MCFP following haemorrhage; however, CO was lower, and R(SV) as well as R(V) were higher relative to the readings in the haemorrhaged-control rats. 5. These results show that following compensated haemorrhage, ET maintains arterial resistance and blood pressure via the activation of ET(A) but not ET(B) receptors.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".