Mismatch for the Minor Histocompatibility Antigen HA-2 and GVHD Occurrence in HLA-A*0201-positive Tunisian Recipients of HSCs
Bibliographic record
Abstract
Graft-versus-Host disease (GVHD) has been widely linked to immunogenetic causes such as disparity between the recipient and its HLA geno-identical donor for some Non-HLA antigens called minor histocompatibility antigens (MiHAgs). HA-2 is one of potential human MiHAgs but its effect on the GVHD occurrence remains not clear. In order to examine such association in the Tunisian cohort of HSCs recipients, we performed a retrospective study on patients who received an HLA-identical HSCT between 2000 and 2009. The study was performed on 60 HLA-A2-positive patients who had received a haematopoietic stem cell transplant from an HLA-identical sibling. All patients received cyclosporine A and/or methotrexate for GVHD prophylaxis. HA-2 genotyping assay was performed with SSP-PCR method and HLA-A*0201 positive samples were identified mainly with Luminex HLA-Typing method. Luminex HLA-Typing assay showed that only 53 cases were positives for the HLA-A*0201 allele. Among these cases, only 3 pairs were mismatched for the MiHAg HA-2. Acute GVHD occurred in 01 HA-2-mismatched pair while chronic GVHD was detected in 02 disparate couples. Univariate and multivariate analyses showed that MiHAg HA-2 disparity does not have any significant effect on the occurrence of either acute or chronic GVHD. This last one appeared to be correlated only with the age of patient (adulthood) (p: 0.011, OR: 22.092). Our findings support the previously reported data denying the influence of the HA-2 disparity on the GVHD occurrence after HSCT.
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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 | 0.001 | 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) | 0.002 | 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".