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Record W4409967934 · doi:10.1002/mdc3.70111

Tics and Parkinson's Disease: Clinical and Pathophysiological Insights from a Rare Syndromic Association

2025· article· en· W4409967934 on OpenAlexaff
Tarig Mohammed Abkur, Alexandra Boogers, Talyta Grippe, David A. Isaacs, Irene A. Malaty, Renato P. Munhoz, Kailash P. Bhatia, Lauren A. Hart, Alfonso Fasano, Suneil K. Kalia, Anthony E. Lang, Christos Ganos

Bibliographic record

VenueMovement Disorders Clinical Practice · 2025
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsOccupational Cancer Research CentreToronto Western HospitalKrembil FoundationUniversity of TorontoUniversity Health Network
FundersNational Institute of Neurological Disorders and Stroke
KeywordsTicsDeep brain stimulationDopaminergicNeuroscienceSubthalamic nucleusParkinson's diseaseParkinsonismPathophysiologyDegenerative diseasePsychologyDopamineDiseaseMedicineMovement disordersCentral nervous system diseaseInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The coexistence of tics with Parkinson's disease (PD) is rare, as they often emerge at different ages, follow different trajectories and involve contrasting pathophysiological mechanisms related to dopamine availability and function in the brain. CASES: We present 10 individuals with primary tic disorders who later developed PD. Tic severity remained unchanged with the onset of parkinsonism or dopaminergic treatment. Peak-dose dyskinesias in two cases did not affect tics, and deep brain stimulation of the subthalamic nucleus transiently induced tics in one individual with PD. CONCLUSIONS: The evidence drawn from this case series does not support a linear relation between nigrostriatal dopaminergic availability and tics. It suggests that tics may instead arise from a more complex interplay between multiple neurotransmitter systems acting on several networks within the cortico-striatal-thalamic circuits.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
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 head0.019
GPT teacher head0.370
Teacher spread0.351 · 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 designCase report
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

Citations3
Published2025
Admission routes1
Has abstractyes

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