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Record W2012392954 · doi:10.1002/mds.22212

Elevated serotonin transporter binding in depressed patients with Parkinson's disease: A preliminary PET study with [<sup>11</sup>C]DASB

2008· article· en· W2012392954 on OpenAlexaff
Isabelle Boileau, Jerry J. Warsh, Mark Guttman, Jean A. Saint‐Cyr, Tina McCluskey, Pablo Rusjan, Sylvain Houle, Alan A. Wilson, Jeffrey H. Meyer, Stephen J. Kish

Bibliographic record

VenueMovement Disorders · 2008
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsCentre for Movement DisordersUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsSerotonin transporterPsychologyInternal medicineSerotoninParkinson's diseaseEndocrinologyMedicineDiseaseReceptor

Abstract

fetched live from OpenAlex

This study investigated whether abnormalities in serotonin transporter binding occur in Parkinson's disease (PD) patients with concurrent depression. We estimated serotonin transporter levels in seven clinically depressed early-stage PD patients and in seven healthy matched-control subjects during a single positron emission tomography (PET) scan with the serotonin transporter radioligand, [(11)C]DASB. Depressed PD patients displayed a wide-spread increase (8-68%) in [(11)C]DASB specific binding outside of the striatum, which was significant in dorsolateral (37%) and prefrontal (68%) cortices. Elevated [(11)C]DASB binding was positively correlated with depressive symptoms but not with disease severity or duration. Compatible with recent PET/[(11)C]DASB findings in major depression, the present preliminary data suggest that increased [(11)C]DASB binding, possibly reflecting greater serotonin transporter density (up-regulation), might be a pathological feature of depression in Parkinson's disease-and possibly a characteristic of depressive illness in general.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.009
GPT teacher head0.217
Teacher spread0.208 · 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 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

Citations170
Published2008
Admission routes1
Has abstractyes

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