MétaCan
Menu
Back to cohort

Steroid Biosynthesis within the Frog Brain

2009· review· en· W2135800518 on OpenAlexaff
Jean‐Luc do Rego, Jae Young Seong, Delphine Burel, Dan Larhammar, Kazuyoshi Tsutsui, Georges Pelletier, Marie‐Christine Tonon, Hubert Vaudry

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2009
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversité Laval
FundersInstitut National de la Santé et de la Recherche Médicale
KeywordsNeuroactive steroidPregnenoloneReceptorGABAA receptorNeuropeptideInternal medicineEndocrinologyBiologygamma-Aminobutyric acidChemistrySteroidHormoneMedicine

Abstract

fetched live from OpenAlex

There is now clear evidence that the brain, similar to the adrenal gland, gonads, and placenta, is a steroidogenic organ. Notably in the frog brain, the presence of various steroidogenic enzymes has been detected by immunohistochemistry in specific populations of neurons and/or glial cells. These steroidogenic enzymes are biologically active, as shown by the ability of brain tissue explants to convert [(3)H]pregnenolone into various radiolabeled steroids. The frog brain has also been extensively used as a model to study the mechanism of regulation of neurosteroidogenesis by neurotransmitters and neuropeptides. It has been demonstrated that the biosynthesis of neurosteroids is inhibited by gamma-aminobutyric acid (GABA), acting through GABA(A) receptors, and neuropeptide Y, acting through Y1 receptors, and is stimulated by the octadecaneuropeptide (ODN), acting through central-type benzodiazepine receptors, triakontatetraneuropeptide (TTN), acting through peripheral-type benzodiazepine receptors, and vasotocin, acting through V1a-like receptors. These data indicate that some of the neurophysiological effects of neurotransmitters and neuropeptides may be mediated through modulation of neurosteroid biosynthesis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.198
GPT teacher head0.384
Teacher spread0.186 · 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
GenreReview

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
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of the New York Academy of SciencesSame topicRegulation of Appetite and ObesityFrench-language works237,207