New Insight into an Old Concept: Role of Immature Erythroid Cells in Immune Pathogenesis of Neonatal Infection
Bibliographic record
Abstract
Newborns are exceedingly susceptible to infection. However, very little is known about what governs the immunological differences seen in early life that result in extreme vulnerability to infection, nor how this changes during infancy. Herein, I provide evidence that the reduced ability to mount a protective immune response to pathogens is not due to an inherent immaturity of neonatal immune cells but instead the functions of these immune cells are actively suppressed by CD71(+) erythroid cells. Furthermore, the role of CD71(+) erythroid cells in host defense against infection is examined. CD71(+) erythroid cells are enriched in newborns and have distinctive immunosuppressive properties that leave them vulnerable to infection. Moreover, immature erythroid cells possess exclusive immunomodulatory properties and may play a role in immune ontogeny. In addition to these distinct features, CD71(+) erythroid cells impact digestive health by preventing excessive inflammation following the sudden transition from a sterile in utero setting to excessive colonization with commensals in the external environment. Ongoing research in identifying the beneficial and/or detrimental effects of immature erythrocytes on immune responses may serve to enhance protective newborn immune responses to infection and enable better vaccination strategies for the young to be designed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".