Alveolar macrophages reduce airway hyperresponsiveness and modulate cytokine levels
Bibliographic record
Abstract
The authors have recently demonstrated that alveolar macrophages (AMs) are important in protecting against early phase reactions and airway hyperresponsiveness following allergen challenge. To further understand the mechanisms involved, the authors investigated the capacity of AMs to modulate airway inflammation and cytokine levels in bronchoalveolar lavage (BAL). AMs from allergy-susceptible Brown Norway (BN) rats or allergy-resistant Sprague-Dawley (SD) rats were transferred into AM-depleted BN rats 24 hours prior to allergen challenge. Methacholine-induced airway hyperresponsiveness was examined 24 hours following ovalbumin challenge. Total cells, cell types, and cytokine levels (tumor necrosis factor [TNF], interleukin [IL]-4, IL-10, IL-12 and IL-13) in BAL were measured 24 hours after allergen challenge. The transfer of AMs from SD rats into AM-depleted BN rats 24 hours before allergen challenge eliminated methacholine-induced airway hyperresponsiveness, but did not modify the number and the type of inflammatory cells in BAL. Levels of IL-13 and TNF were significantly higher in BAL of BN rats compared with SD rats. Interestingly, IL-13 and TNF levels were significantly increased and inhibited, respectively, in BN rats that received AMs from SD rats compared with BN rats. Our data suggest that AM modulation of cytokine milieu is involved in the reduction of airway hyperresponsiveness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".