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Feasibility study of a screening assay that identifies the abnormal prion protein PrP<sup>TSE</sup> in plasma: initial results with 20,000 samples

2010· article· en· W2101726394 on OpenAlexfundno aff
Philippe Guntz, Christine Walter, Patricia Schosseler, Pascal Morel, Joliette Coste, Jean‐Pierre Cazenave

Bibliographic record

VenueTransfusion · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsnot available
FundersEtablissement Français du SangAmorfix Life Sciences
KeywordsPrion proteinVirologyMedicineChemistryPathologyDisease

Abstract

fetched live from OpenAlex

BACKGROUND: It is likely that transmission of variant Creutzfeldt-Jakob disease (vCJD) occurs by transfusion and that the candidate infectious agent (PrP(TSE)) is present in small concentrations in the blood of infected donors in the asymptomatic phase of the disease. A new blood screening assay has been developed to detect PrP(TSE) in citrated plasma samples. STUDY DESIGN AND METHODS: Three regional Blood Transfusion Establishments (ETS) in France (ETS Alsace, ETS Bourgogne Franche-Comté, and ETS Pyrénées-Méditerranée) will screen 60,000 plasma samples (20,000 in each ETS) over a time period of approximately 9 to 12 months. RESULTS: Results provided in this report are those of the first testing site in Strasbourg, Alsace. The preliminary results have demonstrated an initial specificity of 97.60%. Upon repeat testing the specificity rate achieved 99.90% (20 repeat-positive samples). Based on the known epidemiology of vCJD in France, it is likely that the repeat-reactive samples are not true-positives. CONCLUSION: The screening assay was studied in terms of specificity and practicality and was found to be suitable for use in routine testing of blood donations. However, throughput must be enhanced by automation of the assay, and traceability would be improved if automated systems were used to distribute and identify samples.

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)0.001
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 score0.150
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.026
GPT teacher head0.276
Teacher spread0.250 · 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

Citations9
Published2010
Admission routes1
Has abstractyes

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