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Neuroendocrine Control of Reproduction in Teleost Fish: Concepts and Controversies

2021· review· en· W3212640275 on OpenAlexaff
Vance L. Trudeau

Bibliographic record

VenueAnnual Review of Animal Biosciences · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReproductive biology and impacts on aquatic species
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBiologyZebrafishNeuropeptideVertebrateHormoneLuteinizing hormoneReproductionMedian eminenceGonadotropin-releasing hormoneInternal medicineEndocrinologyGeneReceptorGenetics

Abstract

fetched live from OpenAlex

During the teleost radiation, extensive development of the direct innervation mode of hypothalamo-pituitary communication was accompanied by loss of the median eminence typical of mammals. Cells secreting follicle-stimulating hormone and luteinizing hormone cells are directly innervated, distinct populations in the anterior pituitary. So far, ∼20 stimulatory and ∼10 inhibitory neuropeptides, 3 amines, and 3 amino acid neurotransmitters are implicated in the control of reproduction. Positive and negative sex steroid feedback loops operate in both sexes. Gene mutation models in zebrafish and medaka now challenge our general understanding of vertebrate neuropeptidergic control. New reproductive neuropeptides are emerging. These include but are not limited to nesfatin 1, neurokinin B, and the secretoneurins. A generalized model for the neuroendocrine control of reproduction is proposed. Hopefully, this will serve as a research framework on diverse species to help explain the evolution of neuroendocrine control and lead to the discovery of new hormones with novel applications.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.353
Teacher spread0.332 · 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

Citations60
Published2021
Admission routes1
Has abstractyes

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