Cytokine production of RSV/PHA‐stimulated tonsillar mononuclear cells: influences of age and atopy
Bibliographic record
Abstract
Links between immune responses to respiratory syncytial virus (RSV), age and atopic sensitisation are poorly understood. This study investigated the induction of target organ type-1, type-2 and proinflammatory cytokine responses to RSV and/or phytohaemagglutinin (PHA) in tonsillar mononuclear cells from children, in relation to age and atopic status. In comparison with the control medium, RSV induced production of the type-1 cytokines interferon (IFN)-gamma and interleukin (IL)-18, the pro-inflammatory cytokines IL-6, -8 and RANTES (regulated on activation, normal T-cell expressed and secreted), but not any of the type-2 cytokines IL-4, -5, -10 and -13. Induction of IL-6, -8 and RANTES, but not IFN-gamma or IL-18, were shown to be dependent on virus replication. PHA induced all except IL-12, -13, and -15. Induction of IFN-gamma, IL-6, -8, and RANTES was significantly increased in atopic children. Induction of both IFN-7 and IL-4 increased in parallel in relation to age, with no change in the IFN-gamma:IL-4 ratio. These data are compatible with the hypothesis that immature type-1 immunity during early childhood plays a role in both respiratory syncytial virus bronchiolitis and in its relationship with atopy.
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 | 0.000 |
| 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".