Cord blood–derived V <sub>δ</sub> 2 <sup>+</sup> and V <sub>δ</sub> 2 <sup>−</sup> T cells acquire differential cell state compositions upon in vitro expansion
Bibliographic record
Abstract
Human cord blood–derived γδ T cells (CB γδ ) display a highly diverse TCR γδ repertoire and have a unique subtype composition different from fetal or adult peripheral blood counterparts. We expanded CB γδ in vitro using an irradiated Epstein-Barr virus–transformed feeder cell–based modified rapid expansion protocol (REP). Single-cell RNA sequencing tracked progressive differentiation of naïve CB γδ into cells expressing neoantigen-reactive tumor-infiltrating lymphocyte as well as tissue-resident memory precursor–like and antigen-presenting cell–like gene signatures. TCR γδ clonal tracing revealed a bias toward cytotoxic effector differentiation in a much larger proportion of V δ 2 − clones compared to V δ 2 + clones, resulting in the former being more cytotoxic at the population level. These clonotype-specific differentiation dynamics were not restricted to REP and were recapitulated upon secondary nonviral antigen stimulations. Thus, our data showed intrinsic cellular differences between major subtypes of human γδ T cells already in operation at early postnatal stage and highlighted key areas of consideration in optimizing cell manufacturing processes.
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) | 0.001 | 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".