Bibliographic record
Abstract
Abstract The development of immunity in humans starts within a few days of conception and proceeds over a few years before it reaches full maturity. Maturation of the immune system during gestation occurs through waves of cellular production and turnover. Unlike the adult immune system, the foetal one shows reduced antigenic diversity and attenuated pathogen recognition receptor function. Current models suggest that this state is well adapted to the foetal environment. However, this physiological state can prove to be detrimental for infants born prematurely. Consequently, given the high burden of neonatal morbidity and mortality due to infections, understanding of the foetal and neonatal immune system is important to improving health outcomes in this age group. In this article, we review the developmental changes in the immune system during human gestation and highlight its impact on the risk of neonatal infections. Key Concepts The development of the immune system takes place in sequential waves during gestation. The foetal immune system is biased towards immunological tolerance to the mother. Macrophages play a broad role in embryonic organ development. Foetal lymphoid cells show more limited antigenic diversity and an increased proportion of innate‐like lymphoid cells. This developmental immaturity of the immune system is responsible for a high health burden, especially in neonates born prematurely.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".