The phenotype and function of preterm infant monocytes: implications for susceptibility to infection
Bibliographic record
Abstract
The extreme vulnerability of preterm infants to invasive microbial infections has been attributed to "immature" innate immune defenses. Monocytes are important innate immune sentinel cells critical in the defense against infection in blood. They achieve this via diverse mechanisms that include pathogen recognition receptor- and inflammasome-mediated detection of microbes, migration into infected tissues, and differentiation into Mϕs and dendritic cells, initiation of the inflammatory cascade by free radicals and cytokine/chemokine production, pathogen clearance by phagocytosis and intracellular killing, and the removal of apoptotic cells. Relatively little is known about these cells in preterm infants, especially about how their phenotype adapts to changes in the microbial environment during the immediate postnatal period. Overall, preterm monocytes exhibit attenuated proinflammatory cytokine responses following stimulation by whole bacterial or specific microbial components in vitro. These attenuated cytokine responses cannot be explained by a lack of intracellular signaling events downstream of pattern recognition receptors. This hyporesponsiveness also contrasts with mature, term-like phagocytosis capabilities detectable even in the most premature infant. Finally, human data on the effects of fetal chorioamnionitis on monocyte biology are incomplete and inconsistent. In this review, we present an integrated view of human studies focused on monocyte functions in preterm infants. We discuss how a developmental immaturity of these cells may contribute to preterm infants' susceptibility to infections.
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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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".