Neonatal antibody responses are attenuated by interferon-γ produced by NK and T cells during RSV infection
Bibliographic record
Abstract
Respiratory syncytial virus (RSV) infects most children in the first year of life and is a major single cause of hospitalization in infants and young children. There is no effective vaccine, and antibody generated by primary neonatal infection is poorly protective against reinfection even with antigenically homologous viral strains. Studying the immunological basis of these observations in neonatal mice, we found that antibody responses to infection were low and unaffected by CD4 depletion, in contrast with adult mice, which had stronger CD4-dependent antibody responses. Natural killer cell depletion or codepletion of CD4(+) and CD8(+) cells during neonatal RSV infection caused a striking increase in anti-RSV antibody titer. These cells are major sources of the cytokine IFN-γ, and blocking IFN-γ also enhanced RSV-specific antibody responses in neonates. In addition, infection with a recombinant RSV engineered to produce IFN-γ reduced antibody titer, confirming that IFN-γ plays a pivotal role in inhibition of antibody responses after neonatal infection. These unexpected findings show that the induction of a strong cellular immune response may limit antibody responses in early life and that vaccines that induce IFN-γ-secreting cells might, in some situations, be less protective than those that do not.
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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 | 0.001 |
| 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 | 0.000 |
| 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".