Opposing Effects of Short- and Long-term Stress on Airway Inflammation
Bibliographic record
Abstract
Between 20% and 35% of subjects with asthma experience asthma exacerbations during periods of stress. The biological mechanisms underlying these exacerbations are not clearly understood, and the role of psychologic factors in the pathophysiology of asthma remains controversial. We investigated the ability of psychologic stress to modulate airway inflammation and airway hyperresponsiveness (AHR) to methacholine in a murine model of asthma. Animals were exposed to a stressor daily for 3 (short-term stress) or 7 (long-term stress) days. After allergen challenge, AHR was assessed through plethysmography, and bronchoalveolar lavage cells were counted as a measure of inflammation. After short-term stress, inflammatory cell number was decreased compared with unstressed animals, whereas levels of interleukin (IL)-6, IL-9, and IL-13 were increased. Administration of a corticosteroid receptor antagonist, before stress, prevented the decrease in inflammatory cell numbers. In contrast, animals stressed for 7 consecutive days showed a significant increase in inflammatory cell numbers, which was independent of the glucocorticoid response, but no change in cytokine levels. AHR was not altered in stressed animals. Our results indicate that repeated exposure to stress over the long term engages different mechanisms than short-term stress and can exacerbate the chronic inflammatory responses of the airway.
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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) | 0.001 | 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".