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Record W2887988214 · doi:10.1080/19336896.2018.1505399

Unexpected prion phenotypes in experimentally transfused animals: predictive models for humans?

2018· article· en· W2887988214 on OpenAlexfundno aff
Emmanuel Comoy, Jacqueline Mikol, Jean‐Philippe Deslys

Bibliographic record

VenuePrion · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsnot available
FundersFifth Framework ProgrammeAgence Nationale de la RechercheHealth CanadaEuropean Commission
KeywordsDiseaseSpinal cordVirologyPhenotypeBrainstemMedicineTransmissibility (structural dynamics)BiologyImmunologyPathologyNeuroscienceGeneticsGene

Abstract

fetched live from OpenAlex

The recently reevaluated high prevalence of healthy carriers (1/2,000 in UK) of variant Creutzfeldt-Jakob Disease (v-CJD), whose blood might be infectious, suggests that the evolution of this prion disease might not be under full control as expected. After experimental transfusion of macaques and conventional mice with blood derived from v-CJD exposed (human and animal) individuals, we confirmed in these both models the transmissibility of v-CJD, but we also observed unexpected neurological syndromes transmissible by transfusion: despite their prion etiology confirmed through transmission experiments, these original cases would escape classical prion diagnosis, notably in the absence of detectable abnormal PrP with current techniques. It is noteworthy that macaques developed an original, yet undescribed myelopathic syndrome associating demyelination and pseudo-necrotic lesions of spinal cord, brainstem and optical tract without affecting encephalon, which is rather evocative of spinal cord disease than prion disease in human medicine. These observations strongly suggest that the spectrum of human prion diseases may extend the current field restricted to the phenotypes associated to protease-resistant PrP, and may notably include spinal cord diseases.

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 score0.052
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.019
GPT teacher head0.288
Teacher spread0.269 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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