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Extended blood grouping of blood donors with automatable PCR‐ELISA genotyping

2003· article· en· W1848678194 on OpenAlexaff
Maryse St‐Louis, Josée Perreault, Réal Lemieux

Bibliographic record

VenueTransfusion · 2003
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsUniversité LavalHéma-QuébecCegep de Sainte Foy
Fundersnot available
KeywordsGenotypingAmpliconMultiplexConcordanceTypingGenotypeSerologyBiologyAntigenMultiplex polymerase chain reactionSubtypingMolecular biologyPolymerase chain reactionVirologyGeneGeneticsAntibody

Abstract

fetched live from OpenAlex

BACKGROUND: In the past 10 years, PCR-based methods have been described to allow the detection of gene polymorphisms responsible for many blood group antigens. These methods are routinely used to test samples of fetal origin and to resolve serologic discrepancies. Another interesting application of blood group genotyping could be the extended typing of blood donors for minor antigens to facilitate the procurement of compatible blood for alloimmunized patients. STUDY DESIGN AND METHODS: PCR-based tests have been modified to allow multiplex amplification of specific fragments of blood group genes and the convenient detection of hybridized amplicons by ELISA in a microplate format. RESULTS: The results obtained show that fragments of the Rh (D, c, C, e, E), Kell (K, k), Duffy (Fya, Fyb), and Kidd (Jka, Jkb) genes could be amplified along with controls in multiplex PCR reactions. Labeling of amplicons with digoxigenin allowed their solid-phase detection in microplate wells previously coated with individual blood group-specific oligonucleotides. A comparative study performed with 100 individuals showed a 99.7 percent concordance between genotypes and phenotypes for the 11 antigens assayed, with only three discrepant Fyb genotypes. CONCLUSION: Extended genotyping could be performed once on regular donors and confirmed when needed by standard serologic RBC assays. The format of these tests will allow easy automation of the procedure including the interpretation and downloading of the results with existing ELISA software.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.037
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.221
Teacher spread0.211 · 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 teacher head, 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

Citations15
Published2003
Admission routes1
Has abstractyes

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