Hierarchical Maturation of Innate Immune Defences in Very Preterm Neonates
Bibliographic record
Abstract
BACKGROUND: Preterm neonates are highly vulnerable to infection. OBJECTIVES: To investigate the developmental contribution of prematurity, chorioamnionitis and antenatal corticosteroids (ANS) on the maturation of neonatal microbial pathogen recognition responses. METHODS: Using standardized protocols, we assayed multiple inflammatory cytokine responses (IL-1β, IL-6, TNF-α and IL-12/23p40) to three prototypic Toll-like receptor (TLR) agonists, i.e. TLR4 (lipopolysaccharide), TLR5 (flagellin) and TLR7/8 (R848), and to the non-TLR retinoic acid-inducible gene I (RIG-I)-like receptor agonist, in cord blood mononuclear cells from neonates born before 33 weeks of gestation and at term. RESULTS: TLR responses develop asynchronously in preterm neonates, whereby responses to TLR7/8 were more mature and were followed by the development of TLR4 responses, which were also heterogeneous. Responses to TLR5 were weakest and most immature. Maturity in TLR responses was not influenced by sex. Overall, we detected no significant contribution of ANS and chorioamnionitis to the developmental attenuation of either TLR or RIG-I responses. CONCLUSIONS: The maturation of anti-microbial responses in neonates born early in gestation follows an asynchronous developmental hierarchy independently of an exposure to chorioamnionitis and ANS. Our data provide an immunological basis for the predominance of specific microbial infections in this age group.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".