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Record W2083384059 · doi:10.1002/mds.10542

Novel antiepileptic drug levetiracetam decreases dyskinesia elicited by <scp>L</scp>‐dopa and ropinirole in the MPTP‐lesioned marmoset

2003· article· en· W2083384059 on OpenAlexaff
Michael P. Hill, Erwan Bézard, Steven G. McGuire, Alan R. Crossman, Jonathan M. Brotchie, Ann Michel, R. Grimée, Henrik Klitgaard

Bibliographic record

VenueMovement Disorders · 2003
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsRopiniroleDyskinesiaLevetiracetamLevodopaParkinson's diseaseMPTPBasal gangliaMedicinePharmacologyDopamineStriatumEpilepsyPsychologyDopaminergicAnesthesiaNeuroscienceInternal medicineDiseaseCentral nervous system

Abstract

fetched live from OpenAlex

Long-term dopamine replacement therapy of Parkinson's disease leads to the occurrence of dyskinesias. Altered firing patterns of neurons of the internal globus pallidus, involving a pathological synchronization/desynchronization process, may contribute significantly to the genesis of dyskinesia. Levetiracetam, an antiepileptic drug that counteracts neuronal (hyper)synchronization in animal models of epilepsy, was assessed in the MPTP-lesioned marmoset model of Parkinson's disease, after coadministration with (1) levodopa (L-dopa) or (2) ropinirole/L-dopa combination. Oral administration of levetiracetam (13-60 mg/kg) in combination with either L-dopa (12 mg/kg) alone or L-dopa (8 mg/kg)/ropinirole (1.25 mg/kg) treatments was associated with significantly less dyskinesia, in comparison to L-dopa monotherapy during the first hour after administration. Thus, new nondopaminergic treatment strategies targeting normalization of abnormal firing patterns in basal ganglia structures may prove useful as an adjunct to reduce dyskinesia induced by dopamine replacement therapy without affecting its antiparkinsonian action.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.889

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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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 designObservational
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

Citations55
Published2003
Admission routes1
Has abstractyes

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