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Robotic High Thoroughput Multiplex PCR Single-Nucleotide Polymorphism Genotyping of Apheresis Platelet Donors.

2009· article· en· W2594914094 on OpenAlexaffabout
Nadine Shehata, Barbara Hannach, Nancy Banning, John Freedman, Gregory A. Denomme

Bibliographic record

VenueBlood · 2009
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of TorontoCanadian Blood ServicesSt. Michael's Hospital
Fundersnot available
KeywordsGenotypingSingle-nucleotide polymorphismSNPMultiplexGenotypeSNP genotypingMultiplex polymerase chain reactionPolymerase chain reactionImmunologyTypingAntigenMedicineBiologyGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Abstract 2106 Poster Board II-83 Background Phenotyping blood donors for human platelet antigens (HPAs) can be limited by the availability of antibodies and methodologies. Robotic high throughput multiplex polymerase chain reaction (PCR) single-nucleotide polymorphism (SNP) technology provides the opportunity to perform mass genotyping for HPAs to screen apheresis donors who are negative for antigens implicated in alloimmune thrombocytopenia. This technology needs to be validated by standard polymerase chain reaction-SSP to establish a repository of platelet donors to allow for timely and adequate platelet support for patients requiring HPA-matched platelets. The objective of this study is to validate the use of high throughput SNP technology. Methods This is a prospective cohort study of 750 regular apheresis donors. Platelet apheresis donors were identified from Canadian Blood Services' Toronto Centre and genotyped for HPA 1-5 and 15 using high throughput SNP (SNPStream®) technology. HPAs were genotyped using both the sense and antisense DNA strands of each polymorphism to ensure maximum specificity. The genotypes identified by SNP were confirmed by standard methods thus all donors found to be negative for antigens implicated in alloimmune thrombocytopenia were retested using manual (sequence specific SSP-PCR at Canadian Blood Services' Platelet Immunology Laboratory and at the Toronto Centre. Results Of the 750 donors that were screened, 130 donors were found to be negative for antigens implicated in alloimmune thrombocytopenia based on SNP technology. The table illustrates genotyping results using SNP technology and SSP-PCR confirmation to date. In some instances, donors were homozygous for two low frequency HPA genotypes: 2 donors were homozygous for both HPA-1b/b and -2b/b, 6 donors for HPA-1b/b and -3b/b, 1 donor for HPA-2b/b and -3b/b, 1 donor for HPA-1b/b and -5b/b, 10 donors for HPA-1b/b and -15b/b, 4 donors for HPA-5b/b and -15b/b and 1 donor for HPA-2b/b and 15-b/b. HPA System Number of Genotypes Identified by SNP Technology Discrepant results Identified by SSP HPA-1 b/b 15 2 (13%) HPA-2 b/b 8 3 (27%) HPA-3 b/b 25 1 (4%) HPA-5 b/b 1 0 HPA-15 b/b 9 1 (11%) Conclusions: Robotic high throughput multiplex PCR SNP is potentially useful for mass genotyping of apheresis platelet donors and can identify both low frequency antigen-negative donors and combinations of these genotypes. This technology needs to be further developed. Disclosures: No relevant conflicts of interest to declare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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.

Opus teacher head0.018
GPT teacher head0.235
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes2
Has abstractyes

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