The role of ILC2s in neonatal type 2 immunity bias and allergen sensitization
Bibliographic record
Abstract
Abstract Neonatal immunity is largely type 2, potentially dampening damaging inflammatory type 1 immunity. Without early correction from gradual microbial type 1 stimulation, type 2 immunity may become overactive, resulting in allergic disease. Exposure to inhaled allergens during the neonatal period may sensitize individuals resulting in the development of allergic lung disease. Our lab has characterized group 2 innate lymphoid cells (ILC2s) in mouse lungs, which upon exposure to inhaled allergens, produce IL-5 and IL-13 and drive type 2 lung inflammation. We investigated whether ILC2s play a role in neonatal type 2 bias and allergen sensitization. Mouse lung ILC2s rapidly develop and 10 day old (D10) pups had more ILC2s than adults. D10 ILC2s appeared to be activated due to intracellular IL-13 and IL-5 expression and eosinophil lung infiltration, not observed in ILC2-deficient pups. ILC2 numbers are high in D10 lung-draining lymph nodes but not in the spleen or liver. ILC2s may be driving Th2-biased cell differentiation, as intranasal (IN) OVA-antigen treatment into D10 OTII pups results in significantly more IL-4+IL-13+ CD4+ T cells in the lung-draining LN after 6 days compared to adult OTII mice. Moreover, upon IN protease-allergen papain treatment at D10 and then again 4 weeks later, higher numbers of LN Th2 cells were present compared to similarly treated adults. Importantly, IL-33-deficient D10 pups, had fewer activated ILC2s and little eosinophil lung infiltration, suggesting that neonatal ILC2s activated by endogenous IL-33, produce type 2 cytokines resulting in type 2-biased lung immunity. Therefore, ILC2s may play a role in the neonatal sensitization of individuals, causing the development of allergic lung inflammation in adults.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".