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Record W2106499597 · doi:10.1038/clpt.2011.20

Evaluation of the Abuse Potential of Lorcaserin, a Serotonin 2C (5-HT2C) Receptor Agonist, in Recreational Polydrug Users

2011· article· en· W2106499597 on OpenAlexaff
M.J. Shram, K A Schoedel, Cynthia Huang Bartlett, R L Shazer, C.M. Anderson, Edward M. Sellers

Bibliographic record

VenueClinical Pharmacology & Therapeutics · 2011
Typearticle
Languageen
FieldMedicine
TopicPharmacology and Obesity Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsZolpidemPlaceboPharmacologyAgonistKetamineCrossover studyMedicinePsychologyAnesthesiaInternal medicineReceptorInsomnia

Abstract

fetched live from OpenAlex

Lorcaserin is a selective and potent serotonin 2C receptor subtype (5-HT(2C)) agonist under development for the treatment of obesity. This study assessed the drug's abuse potential on the basis of its pharmacological profile. For this purpose, a double-blind, double-dummy, placebo-controlled, randomized seven-way crossover study with single oral doses of lorcaserin (20, 40, and 60 mg), zolpidem (15 and 30 mg), ketamine (100 mg), and placebo was conducted in recreational polydrug users (N = 35). Subjective and objective measures were assessed up to 24 h after the dose. We found that zolpidem and ketamine had significantly higher peak scores relative to placebo on the primary measures as well as on most of the secondary measures. The subjective effects of a 20-mg dose of lorcaserin were similar to those of placebo, whereas supratherapeutic doses of lorcaserin were associated with significant levels of dislike by users as compared with placebo, zolpidem, and ketamine. Perceptual effects were minimal after administration of lorcaserin and significantly lower than after administration of either ketamine or zolpidem. The findings suggest that, at supratherapeutic doses, lorcaserin is associated with distinct, primarily negative, subjective effects and has low abuse potential.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.193
GPT teacher head0.438
Teacher spread0.245 · 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 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

Citations63
Published2011
Admission routes1
Has abstractyes

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