Mass‐scale high‐throughput multiplex polymerase chain reaction for human platelet antigen single‐nucleotide polymorphisms screening of apheresis platelet donors
Bibliographic record
Abstract
BACKGROUND: Treatment with human platelet antigen (HPA)-matched platelets (PLTs) is the optimal therapy for bleeding secondary to neonatal alloimmune thrombocytopenia. Recent advances in high-throughput DNA-based blood group and PLT antigen genotyping have made it possible to screen plateletpheresis donors for potential HPA-matched PLT transfusion. STUDY DESIGN AND METHODS: This prospective study evaluated genomic DNA from plateletpheresis donors for single-nucleotide polymorphisms (SNPs) associated with HPA-1, -2, -3, -4, -5, and -15 to determine whether high-throughput multiplex genomic DNA PCR and oligonucleotide extension technology can be used for mass-scale PLT antigen genotyping. Genotyping using SNP technology was confirmed using sequence-specific polymerase chain reaction (SSP-PCR). RESULTS: Of the 748 donors screened, 277 were found to be negative for antigens implicated in alloimmune thrombocytopenia. In addition, two donors were homozygous for HPA-1b/b and -2b/b, six donors for HPA-1b/b and -3b/b, one for HPA-2b/b and -3b/b, one for HPA-1b/b and -5b/b, 10 for HPA-1b/b and -15 b/b, four for HPA-5b/b and -15b/b, and one for HPA-2b/b and -15b/b. Retesting using SSP-PCR was conducted for 60 donors. Discrepant results occurred between SNP and SSP-PCR in less than 20% of samples for HPA-1b/1b/HPA-3b/3b, HPA-5b/5b, and HPA-15b/b. DISCUSSION: High-throughput multiplex PCR SNP and confirmatory molecular genotyping are useful for mass-scale screening of apheresis PLT donors to provide antigen-negative genotypes. Refinements to mass-scale multiplex analysis technology would reduce further the confirmatory testing needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".