Melan‐A‐specific T cells derived from A2+ or A2‐umbilical cord blood (UCB) units proliferate and exhibit specific cytolytic function following in vitro stimulation
Bibliographic record
Abstract
UCB is increasingly used as a source of haematopoietic progenitors to treat a variety of blood disorders requiring bone marrow transplantation. Advantages of UCB include availability and reduced HLA matching requirements as compared with bone marrow. To characterize functional properties of UCB T cells in the context of allogeneic UCB transplant, naïve CD8+ T cells specific for the HLA‐A2‐restricted Melan‐A‐derived peptide ELAGIGILTV were sorted from A2+ and A2− UCB units using A2/Melan‐A tetramers and were cultured in the presence of IL‐2, IL‐7, PHA, and peptide. Microcultures were phenotyped and tested for Melan‐A‐specific cytotoxicity by 51Cr‐release assay. Clonal diversity was estimated by T cell receptor (TCR) β chain sequencing. 83.3% (15/18) of clinical units tested were positively stained by tetramers (median frequency of 0.11% regardless of HLA type). Following in vitro stimulation, the median frequency of tetramer+ T cells was increased (p<0.0001), T cell microcultures exhibited Melan‐A‐specific cytolytic activity (median = 11.98% of positive cultures at an input of 1000 cells/well), and the TCR β chain repertoire showed evidence of oligoclonality consistent with antigen‐driven expansion. This study will bring new light on the ability of the preimmune T cell repertoire to participate in antitumoral and antiviral activity following UCB transplantation. Supported by FRSQ/Héma‐Québec.
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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 | 0.000 |
| 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 | 0.001 |
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".