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Record W2571180541 · doi:10.1093/jnen/nlw103

The Search for a Peripheral Biopsy Indicator of α-Synuclein Pathology for Parkinson Disease

2017· review· en· W2571180541 on OpenAlexaff
John M. Lee, Pascal Derkinderen, Jeffrey H. Kordower, Roy Freeman, David G. Muñoz, Thomas Kremer, Wagner Zago, Samantha J. Hutten, Charles H. Adler, Geidy E. Serrano, Thomas G. Beach

Bibliographic record

VenueJournal of Neuropathology & Experimental Neurology · 2017
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsPathologicalPathologyParkinson's diseaseMedicineBiopsyDiseaseHistologyAnatomical pathologyImmunohistochemistry

Abstract

fetched live from OpenAlex

The neuropathological hallmark of Parkinson disease (PD) is abnormal accumulation of α-synuclein (α-syn). Demonstrating pathological α-syn in live patients would be useful for identifying and monitoring PD patients. To date, however, imaging and biofluid approaches have not permitted premortem assessment of pathological α-syn. α-syn pathology in the peripheral nervous system of patients with PD has been demonstrated in studies dating back more than 40 years. More recent work suggests that colon, submandibular gland and skin biopsies could be useful as expedient biomarkers but histological differentiation of pathological and normal peripheral α-syn has been challenging and multiple research groups have reported variable results. A variety of immunohistochemical methods have been employed but almost all studies to date originated at single centers with no independent, blinded replication. To address these issues, the Michael J. Fox Foundation for Parkinson's Research sponsored a series of meetings and investigations by several research groups with relevant experience. The major finding reported herein was that biopsies can be used to distinguish PD patients from normal subjects. However, full assessment of the clinical potential of biopsy will only be achieved through large, multicenter trials in which both the initial detection methodology and histology have been assessed by blinded panels of pathologists.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.082
GPT teacher head0.394
Teacher spread0.312 · 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
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

Citations72
Published2017
Admission routes1
Has abstractyes

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