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Record W2165987803 · doi:10.1093/brain/awh229

Reply to: PET studies and physiopathology of motor fluctuations in Parkinson's disease

2004· article· en· W2165987803 on OpenAlexaffabout
C. S. Lee

Bibliographic record

VenueBrain · 2004
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsTRIUMFUniversity of British Columbia
Fundersnot available
KeywordsPavilionResearch centreWatsonParkinson's diseaseUniversity hospitalBrain researchGerontologyLibrary scienceArt historyPsychologyMedicineNeuroscienceArtHistoryDiseaseFamily medicinePathologyArchaeology

Abstract

fetched live from OpenAlex

1Pacific Parkinson's Research Centre, Vancouver Hospital and Health Sciences Centre, 2Departments of Physics and Astronomy and 3TRIUMF, University of British Columbia, Vancouver, BC, Canada We agree that the most interesting and unexpected finding in this study is the shorter latency to the onset of levodopa response on the less affected side than on the more affected side. This shorter latency to the onset on the less affected side reflects our consistent observations that the time–response curve of tapping rates on the more affected side appears as a down-shift of the curve on the less affected side, accounting for later onset and earlier offset on the more affected side. The most characteristic changes in response fluctuations to levodopa are the greater magnitude and further left-shift of the time-response curve (with earlier onset, peak response time and decay) (Nutt, 1990). Although mechanisms of these response changes are not clearly understood, current evidence suggests that response fluctuations can be attributed to both presynaptic and postsynaptic factors. However, interpretation of data from clinical and pharmacological studies exploring mechanisms of response fluctuations is notoriously complicated, largely because of the difficulty in (i) separating the effects of dopamine (DA) terminal loss and drug treatment, and (ii) separating presynaptic and postsynaptic effects. For instance, since Parkinson's disease is a slowly progressive degenerative disorder, a strong correlation exists between the duration of disease and the duration of drug treatment. Thus, longitudinal study does not solve the problem in delineating the effects of DA terminal loss from the effects of drug treatment. Furthermore, both presynaptic and postsynaptic factors are influenced by either DA terminal loss or drug treatment (Gerfen et al., 1990; Lee et al., 2000; Guttman et al., 2001). Therefore, comparisons of pharmacodynamic parameters of levodopa and in vivo [11C]dihydrotetrabenazine (DTBZ) PET measures between the two sides in patients with asymmetrical Parkinson's disease provide a unique opportunity to gain insight into the role of DA terminal loss in the development of response fluctuations. This is because DTBZ is a presynaptic marker for in vivo PET studies, which is relatively resistant to regulatory changes (Vander Borght et al., 1995), and the drug treatment is not a variable in side-to-side comparisons of patients with asymmetrical Parkinson's disease.

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)0.003
metaresearch head score (Gemma)0.018
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.025
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.004
Open science0.0020.001
Research integrity0.0250.021
Insufficient payload (model declined to judge)0.0060.005

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 head0.309
Teacher spread0.286 · 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
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

Citations1
Published2004
Admission routes2
Has abstractyes

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