Implication of the bradykinin receptors in antigen‐induced pulmonary inflammation in mice
Bibliographic record
Abstract
1. The involvement of bradykinin (BK) receptors in the allergic inflammation associated with airway hyper-reactivity (AHR) was evaluated by means of the selective bradykinin B(1) receptor (BKB(1)-R) antagonists R-715 (Ac-Lys-[D-betaNal(7), Ile(8)]desArg(9)-BK) and R-954 (Ac-Orn[Oic(2), alpha-MePhe(5), D-betaNal(7), Ile(8)]desArg(9)-BK) or the selective bradykinin B(2) receptor (BKB(2)-R) antagonist HOE-140 (D-Arg(0)-Hyp(3)-Thi(5)-D-Tic(7)-Oic(8)-BK). Cellular migration and AHR were examined 24 h after the second ovalbumin (OA) challenge. 2. R-715 (10-500 microg kg(-1)) and R-954 (1-100 microg kg(-1)) injected intravenously (i.v.), 5 min prior to aerosol OA challenges, decreased by approximately 50% the induced lung eosinophilia in OA-sensitized mice but did not reduce AHR. 3. HOE-140 (1 microg kg(-1)) administered in the same manner, decreased mononuclear cell and eosinophil infiltration in the bronchoalveolar lavage fluid (BALF) of OA-sensitized mice. Moreover, treatment of OA-sensitized mice with HOE-140 (100 microg kg(-1)) completely abolished the AHR to carbachol. 4. The BKB(1)-R agonist desArg(9)-BK (DBK; 10-1000 microg kg(-1)) administered intratrachealy to normal mice had no effect on the basal cell counts recovered in BALF nor on the plasma extravasation, while the BKB(2)-R selective agonist BK (20 microg kg(-1)) stimulated mononuclear cell migration, neutrophilia and plasma extravasation in normal mouse lungs. Such effects were inhibited by HOE-140 (10 microg kg(-1)). 5. Our results suggest that the airway inflammatory response induced by antigen challenge in mice is mediated by stimulation of both BKB(1)-R and BKB(2)-R.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".