Diversity and fate of pre-immune anti-tumor T cells after umbilical cord blood transplantation (102.28)
Bibliographic record
Abstract
Abstract Umbilical cord blood (UCB) has been used successfully as a source of progenitor cells to treat a variety of haematological and immune disorders in children. Donor-derived T cells play a key role in antitumoral and antiviral immunity and contribute to the survival of the graft recipient. Here we studied the diversity, persistence, fate and antitumoral function of UCB-derived T cells and characterized their persistence and function in the graft recipient. Naïve CD8+ T cells specific for the Melan-A26-35 peptide were isolated from UCB and UCB recipients at 1, 3, and 6 months post-transplant using Melan-A26-35-HLA-A2 tetramers and cell sorting, and were cultured in the presence of IL-2, IL-7, PHA and peptide. Melan-A-specific cytotoxicity was tested in 51Cr-release assays, and the clonal diversity of the pre-immune Melan-A-specific repertoire was determined by sequencing of the T cell receptor β chain CDR3 region. 14 UCB recipients were enrolled. Melan-A-specific CD8+ T cells were detected at a median frequency of 2.28% (range=0.0–8.18%) in 4 of 6 UCB samples initially analyzed. These cells proliferated in the presence of Melan-A peptide in 4 of 6 cases, and showed cognate cytotoxicity in 2 of 6 cases. Finally, tetramer-positive cells were detected in UCB recipients as early as 1 month post-transplant. This study will lead to a better understanding of the fate of the pre-immune T cell repertoire in UCB recipients.
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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) | 0.001 | 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".