Étude de la différenciation des lymphocytes B mémoires en milieu sans sérum
Bibliographic record
Abstract
Les infections opportunistes sont l’une des principales causes de mortalité associées à la greffe de cellules souches. Afin d’aider à reconstituer le système immunitaire des patients greffés, nous proposons d’exploiter les plasmocytes autologues générés in vitro dans notre modèle de culture basé sur l’interaction CD40-CD154. Pour ce faire, les milieux de culture doivent être exempts de protéines animales. Deux milieux sans sérum ont été préalablement développés à Héma-Québec. Notre hypothèse est qu’il serait maintenant possible de promouvoir la différenciation des lymphocytes B et de maintenir la survie des plasmocytes en modifiant la composition de ces milieux sans sérum. Nos résultats montrent que notre milieu sans protéines animales permet de générer un grand nombre de plasmocytes et que ceux-ci ont un profil d’expression de CD38 qui est stabilisé par la vitamine A. En conclusion, la formulation de ce milieu représente un progrès quant à la possibilité d’utiliser ces plasmocytes en immunothérapie.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".