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Record W3095092551 · doi:10.3233/jpd-202237

The Gut Mycobiome in Parkinson’s Disease

2020· letter· en· W3095092551 on OpenAlexafffund
Mihai Cîrstea, Kristen Sundvick, Ella Golz, Adam C. Yu, Rozlyn C. T. Boutin, Daniel Kliger, B. Brett Finlay, Silke Appel‐Cresswell

Bibliographic record

VenueJournal of Parkinson s Disease · 2020
Typeletter
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsCanadian Sport Centre PacificUniversity of British Columbia HospitalCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsDiseaseParkinson's diseaseMedicinePathology

Abstract

fetched live from OpenAlex

The gut microbiome has been increasingly implicated in Parkinson's disease (PD); however, most existing studies employ bacterial-specific sequencing, and have not investigated non-bacterial microbiome constituents. Here, we use fungal-specific internal transcribed spacer (ITS)-2 amplicon sequencing in a cross-sectional PD cohort to investigate associations between the fungal gut microbiome and PD. Fungal load among participants was extremely low, and genera identified were almost exclusively of proposed dietary or environmental origin. We observed significantly lower fungal DNA relative to bacterial DNA among PD patients. No fungi differed in abundance between patients and controls, nor were any associated with motor, cognitive, or gastrointestinal features among patients.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.451
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.023
GPT teacher head0.275
Teacher spread0.252 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations31
Published2020
Admission routes2
Has abstractyes

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