Mast cells impact the acute innate immune response to RSV by reducing viral load and promoting eosinophil recruitment 2952
Bibliographic record
Abstract
Abstract Description Respiratory viral infections, including Respiratory Syncytial Virus (RSV) are major health threats. Mast cells are resident innate immune effector cells which produce multiple mediators in response to viral infections. This study determined the role of mast cells in responses to early RSV infection. Mast cell-deficient Cpa3-Cre; Mcl-1fl/fl mice exhibited significantly higher viral loads, greater weight loss, and more tissue damage compared to wild type mice two days post infection. This was associated with increased inflammatory monocyte influx and elevated immune mediators CXCL10, CCL4 and TNF in the lung following RSV infection. Mast cell deficiency was also associated with reduced and phenotypically distinct eosinophil populations in lung tissue in the absence of infection. Mice selectively reconstituted with mast cells exhibited similar lung eosinophil populations and responses to RSV as wild types. These studies reveal the protective role of mast cells during RSV infection, offering valuable insight to enhance future treatment strategies. Funding Sources This work was funded by CIHR (grant no. MOP10966 and PJT 173350) to JSM, with additional support from the Dalhousie Medical Research Foundation (DMRF) and an American Association for Immunology fellowship awarded to RHN. Topic Categories Immune Response Regulation: Cellular Mechanisms (IRC)
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".