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Record W2550711879 · doi:10.1101/088724

Sexually satiated male uses gustatory-to-neuropeptide integrative circuits to reduce time investment for mating

2016· preprint· en· W2550711879 on OpenAlexaff
Woo Jae Kim, Seung Gee Lee, Anne-Christine Auge, Lily Yeh Jan, Yuh Nung Jan

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2016
Typepreprint
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsUniversity of Ottawa
FundersNational Institutes of HealthUniversity of California, San FranciscoKorea Research Institute of Bioscience and Biotechnology
KeywordsMushroom bodiesTimelessMatingBiologyCircadian clockNeuroscienceNeuropeptideSex pheromonePeriod (music)Circadian rhythmGeneZoologyGenetics

Abstract

fetched live from OpenAlex

ABSTRACT Males rely on a ‘time investment strategy’ to maximize reproductive success. Here we report a novel behavioral plasticity whereby male fruit flies exhibit a shortened mating duration when sexually satiated, which we named ‘Shorter-Mating-Duration (SMD)’. SMD requires the sexually dimorphic Gr5a-positive neurons for detecting female body pheromones. The memory circuitry within the ellipsoid body (EB) and mushroom body (MB) brain regions is crucial for SMD, which depends on the circadian clock genes Clock and cycle , but not timeless or period . SMD also relies on signaling via the neuropeptide sNPF, but not PDF or NPF. Sexual experience modifies the neuronal activity of a subset of sNPF-positive neurons involved in neuropeptide signaling, which modulates SMD. Thus, our study delineates the molecular and cellular basis for SMD – a plastic social behavior that serves as a model system to study how the brain switches the internal states between sexual drive and satiety.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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)0.0040.000

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 head0.040
GPT teacher head0.286
Teacher spread0.246 · 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 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

Citations22
Published2016
Admission routes1
Has abstractyes

Explore more

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