HLA-C expression levels define permissible mismatches in hematopoietic cell transplantation
Bibliographic record
Abstract
Life-threatening graft-versus-host disease (GVHD) limits the use of HLA-C-mismatched unrelated donors in transplantation. Clinicians lack criteria for donor selection when HLA-C-mismatched donors are a patient's only option for cure. We examined the role for HLA-C expression levels to identify permissible HLA-C mismatches. The median fluorescence intensity, a proxy of HLA-C expression, was assigned to each HLA-C allotype in 1975 patients and their HLA-C-mismatched unrelated transplant donors. The association of outcome with the level of expression of patients' and donors' HLA-C allotypes was evaluated in multivariable models. Increasing expression level of the patient's mismatched HLA-C allotype was associated with increased risks of grades III to IV acute GVHD, nonrelapse mortality, and mortality. Increasing expression level among HLA-C mismatches with residue 116 or residue 77/80 mismatching was associated with increased nonrelapse mortality. The immunogenicity of HLA-C mismatches in unrelated donor transplantation is influenced by the expression level of the patient's mismatched HLA-C allotype. HLA-C expression levels provide new information on mismatches that should be avoided and extend understanding of HLA-C-mediated immune responses in human disease.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".