<i>In vivo</i>pharmacological evaluation of compound 48/80‐induced airways oedema by MRI
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Allergen-induced airways oedema in actively sensitized rats has been studied earlier by magnetic resonance imaging (MRI). We used MRI to follow the consequences of non-immunological mast cell activation induced by compound 48/80 in the rat lungs in vivo. EXPERIMENTAL APPROACH: Male naïve rats were scanned by MRI prior to and at several time points following intratracheal administration of the mast cell secretagogue, compound 48/80. The effects of a range of drugs on the response induced by compound 48/80 were studied. KEY RESULTS: Strong fluid signals were detected by MRI in the lungs at 24 h after compound 48/80, correlating with increased protein concentration and inflammatory cell infiltration in bronchoalveolar lavage, and with perivascular oedema observed histologically. Pharmacological intervention demonstrated that the increase in MRI signal volume induced by compound 48/80 24 h after challenge was blocked by disodium cromoglycate and the glucocorticoid, budesonide. Pretreatment with wortmannin, capsazepine, DNK333 (a dual neurokinin (NK) 1 and NK2 antagonist) or the anti-allergy drug CGS8515, but not indomethacin, resulted in partial inhibition. CONCLUSIONS AND IMPLICATIONS: Compound 48/80 induced a complex inflammatory reaction which did not solely involve mast cell degranulation but also activation of sensory nerves and was qualitatively similar to allergen challenge. Changes observed by MRI correlated with decreases in protein concentration in BAL fluid. However, the magnitude of the changes detected was greater using MRI. Our results demonstrate that MRI is a sensitive and efficient tool to assess the effects of drugs on lung inflammation.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".