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Record W4385718734 · doi:10.1055/s-0043-1771468

The Role of Helicobacter pylori and Small Intestinal Bacterial Overgrowth in Parkinson's Disease

2023· review· en· W4385718734 on OpenAlexaff
Maria Belen Justich, Olga L. Rojas, Alfonso Fasano

Bibliographic record

VenueSeminars in Neurology · 2023
Typereview
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsOntario Brain InstituteToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsSmall intestinal bacterial overgrowthMedicineHelicobacter pyloriParkinson's diseaseDiseaseEtiologyPathogenesisProinflammatory cytokineGastroenterologyGastrointestinal tractHelicobacterInternal medicineInflammationIrritable bowel syndrome

Abstract

fetched live from OpenAlex

Abstract Parkinson's disease (PD) is a common neurodegenerative disorder whose etiology remains largely unexplained. Several studies have aimed to describe a causative effect in the interactions between the gastrointestinal tract and the brain, for both PD pathogenesis and disease course. However, the results have been controversial. Helicobacter pylori and small intestinal bacterial overgrowth (SIBO) are theorized to be agents capable of triggering chronic proinflammatory changes with a possible neurotoxic effect, as well as a cause of erratic L-dopa response in PD patients. This review evaluates the individual and possibly synergistic influence of H. pylori and SIBO on PD, to provide an opportunity to consider prospective therapeutic approaches.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.047
GPT teacher head0.378
Teacher spread0.330 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2023
Admission routes1
Has abstractyes

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