Ex vivo T-lymphopoiesis assays assisting corrective treatment choice for genetically undefined T-lymphocytopenia
Bibliographic record
Abstract
Persistent selective T-lymphocytopenia is found both in SCID and congenital athymia. Without molecular diagnosis, it is challenging to determine whether HCT or thymus transplantation ought to be performed. Ex vivo T-lymphopoiesis assays have been proposed to assist clinical decision-making for genetically undefined patients. We investigated 20 T-lymphocytopenic patients, including 13 patients awaiting first-line treatment and 7 patients with failed immune reconstitution after previous HCT or thymus transplantation. Whilst developmental blocks in ex vivo T-lymphopoiesis indicated hematopoietic cell-intrinsic defects, successful T-lymphocyte differentiation required careful interpretation, in conjunction with clinical status, immunophenotyping, and genetic investigations. Of the 20 patients, 13 proceeded to treatment, with successful immune reconstitution observed in 4 of the 6 patients post-HCT and 4 of the 7 patients after thymus transplantation, the latter including two patients who had previously undergone HCT. Whilst further validation and standardization are required, we conclude that assessing ex vivo T-lymphopoiesis during the diagnostic pathway for genetically undefined T-lymphocytopenia improves patient outcomes by facilitating corrective treatment choice.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".