Early Recovery of CD4 T Cell Receptor Diversity after “Lymphoablative” Conditioning and Autologous CD34 Cell Transplantation
Bibliographic record
Abstract
T cell diversity posttransplantation is thought to be severely restricted, based on T cell receptor beta-chain immunophenotyping or spectratyping. Using beta-chain sequencing, we studied CD4 T cell diversity in 2 adult patients undergoing "lymphoablative" conditioning with cyclophosphamide (Cy), total body irradiation (TBI), and antithymocyte globulin (ATG) and autologous transplantation of hematopoietic cells depleted of T cells by enrichment for CD34 cells. The indication for the transplantation was systemic sclerosis (SSc) or multiple sclerosis (MS). Pretransplantation, the estimated number of distinct beta chains (the minimum number of CD4 T cell clones) in the 2 patients was 600,000 to 700,000, similar to the number in a healthy control. This number was 200,000 to 500,000 at 1 month posttransplantation and 400,000 to 1,600,000 at 12 months posttransplantation. In conclusion, the number of T cells early after lymphoablative conditioning and autologous CD34 cell transplantation may be more diverse than previously appreciated, possibly because many T cell clones survive the conditioning or are reinfused with the graft. Thus, the therapy may not be completely T cell lymphoablative.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".