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Record W2903411193 · doi:10.1371/journal.ppat.1007414

Soil humic acids degrade CWD prions and reduce infectivity

2018· article· en· W2903411193 on OpenAlexafffund
Alsu Kuznetsova, Catherine I. Cullingham, Debbie McKenzie, Judd M. Aiken

Bibliographic record

VenuePLoS Pathogens · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsUniversity of Alberta
FundersNational Institute on Alcohol Abuse and AlcoholismAlberta Prion Research InstituteAlberta Agriculture and ForestryGenome AlbertaAlberta InnovatesGenome Canada
KeywordsChronic wasting diseaseInfectivityIncubationSoil waterIncubation periodOrganic matterPrion proteinBiologyEnvironmental chemistryEcologyChemistryVirologyDiseaseBiochemistryVirusInternal medicine

Abstract

fetched live from OpenAlex

Chronic wasting disease (CWD), an environmentally transmissible, fatal prion disease is endemic in North America, present in South Korea and has recently been confirmed in northern Europe. The expanding geographic range of this contagious disease of free-ranging deer, moose, elk and reindeer has resulted in increasing levels of prion infectivity in the environment. Soils are involved in CWD horizontal transmission, acting as an environmental reservoir, and soil mineral and organic compounds have the ability to bind prions. Upper horizons of soils are usually enriched with soil organic matter (SOM), however, the role of SOM in prion conservation and mobility remains unclear. In this study, we show that incubation of PrPCWD with humic acids (HA), a major SOM compound, affects both the molecular weight and recovery of PrPCWD. Detection of PrPCWD is reduced as HA concentration increases. Native HA extracted from pristine soils also reduces or entirely eliminates PrPCWD signal. Incubation of CWD prions with HA significantly increased incubation periods in tgElk mice demonstrating that HA can reduce CWD infectivity.

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 score0.022
Threshold uncertainty score0.517

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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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

Citations33
Published2018
Admission routes2
Has abstractyes

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