Immunologie néonatale et greffe de sang de cordon
Bibliographic record
Abstract
The increased susceptibility of human newborns to infections is usually ascribed to the immaturity of the neonatal immune system. The neonatal immune system has never met microbial antigens, and thus the repertoire of its adaptative arm (T and B cells) is entirely pre-immune, or "naïve". However this neonatal pre-immune repertoire is similar to the adult pre-immune repertoire, and cord blood natural killer cells studies show that the innate immunity cells harbor the full killing machinery that characterize mature cells. Moreover, human neonates are able to show an adult-like allogeneic response. Taken together, several lines of evidence suggest that the neonatal immune system, although naïve, is fully mature. However, newborns display phenotypic and functional differences with adults in both adaptative and innate arms. Specific properties may explain these differences, as high number of regulatory T cells, low plasmacytoid dendritic cell response to stimuli and high IL-10 production. These properties are in line with the high susceptibility of newborns to infections and the low incidence of graft-versus-host-disease after cord blood transplantation. To explain these differences, we introduce a new model. Although naive, the neonatal immune system is mature, and these functional differences are due to a message originating from the placenta and aimed at inducing the foetus tolerance to its mother. Full understanding of the involved mechanisms will help to protect the newborn against infections and to improve cord blood transplantation outcome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".