Role of bradykinin B2-receptor in the sympathoadrenal effects of ???new pressor protein??? related to human blood coagulation factor XII fragment
Bibliographic record
Abstract
BACKGROUND: Human plasma new pressor protein (NPP) increases blood pressure, heart rate and plasma adrenal medullary catecholamines in bioassay rats - all potentiated by angiotensin-converting enzyme (ACE) inhibition. High plasma NPP activity has been found in haemodialysis patients with hypertension. OBJECTIVE: To investigate whether the bradykinin B2-receptor mediates the effects of NPP. METHODS AND RESULTS: Male Wistar bioassay rats were anaesthetized with inactin, ganglion blocked with pentolinium and injected intravenously (i.v.) with human NPP (20 microl plasma equivalent) or bradykinin (100 ng/kg). Both NPP and bradykinin increased systolic (SBP) and diastolic (DBP) blood pressures, heart rate and plasma adrenaline and noradrenaline concentrations. All these responses were potentiated by the ACE inhibitor, captopril (10 mg/kg i.v.), but not by antagonism of the angiotensin II type 1 receptor with losartan (10 mg/kg i.v.). Administration of the bradykinin B2-receptor antagonist, HOE-140 (20 microg/kg i.v.), significantly attenuated the peak NPP responses as follows: SBP from 58 +/- 3 to 40 +/- 4 mmHg (decrease of 30%; P < 0.05); DBP from 22 +/- 4 to 10 +/- 1 mmHg (decrease of 55%; P < 0.05); heart rate from 124 +/- 8 to 28 +/-6 beats/min (decrease of 77%; P < 0.05); plasma adrenaline from 14297 +/- 2477 to 3318 +/- 1105 pg/ml (decrease of 77%; P < 0.05) and noradrenaline from 505 +/- 66 to 77 +/-29 pg/ml (decrease of 85%; P < 0.05). CONCLUSIONS: The haemodynamic and sympathoadrenal effects of NPP involve substantial mediation by the bradykinin B2-receptor, in addition to other mechanisms.
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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) | 0.002 | 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".