MétaCan
Menu
Back to cohort
Record W2116058026 · doi:10.1073/pnas.0400491101

Selective facilitation of sexual solicitation in the female rat by a melanocortin receptor agonist

2004· article· en· W2116058026 on OpenAlexaff
James G. Pfaus, Annette M. Shadiack, Tanya Van Soest, Maric Tse, Perry B. Molinoff

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2004
Typearticle
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsConcordia University
Fundersnot available
KeywordsMelanocortinMelanocortin 4 receptorFacilitationAgonistSexual desireAffect (linguistics)LordosisPsychologyEndocrinologyInternal medicineMelanocortin receptorSexual behaviorProceptive phaseReceptorHormoneDevelopmental psychologyNeuroscienceBiologyMedicineHuman sexualityCommunication

Abstract

fetched live from OpenAlex

Disorders of sexual desire affect an estimated 30% of women in North America and Europe, with etiologies based on interpersonal, personal, and physiological factors. There are currently no pharmacological agents approved for use in the treatment of female sexual dysfunction. This is due, in part, to a focus on the effects of experimental drugs on reflexive components of sexual behavior, such as lordosis, in animal models. Here we report that PT-141, a peptide analogue of alpha-melanocyte-stimulating hormone that binds to central melanocortin receptors, selectively stimulates solicitational behaviors in the female rat. This occurs without affecting lordosis, pacing, or other sexual behaviors. PT-141 did not cause generalized motor activation, nor did it affect the perception of sexual reward. A selective pharmacological effect on appetitive sexual behavior in female rats has not been reported previously, and indicates that central melanocortin systems are important in the regulation of female sexual desire. Accordingly, PT-141 may be the first identified pharmacological agent with the capability to treat female sexual desire disorders.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.046
GPT teacher head0.313
Teacher spread0.267 · 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 designBench or experimental
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

Citations128
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicRegulation of Appetite and ObesityFrench-language works237,207