MétaCan
Menu
Back to cohort
Record W2060490218 · doi:10.1242/dev.095992

Regeneration of breeding tubercles on zebrafish pectoral fins requires androgens and two waves of revascularization

2013· article· en· W2060490218 on OpenAlexafffund
Stephanie C. McMillan, Zhe Xu, Jing Zhang, Cathleen Teh, Vladimir Korzh, Vance L. Trudeau, Marie‐Andrée Akimenko

Bibliographic record

VenueDevelopment · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicZebrafish Biomedical Research Applications
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsBiologyZebrafishRegeneration (biology)AngiogenesisAndrogenAnatomyRevascularizationFish finEndocrinologyInternal medicineCell biologyHormoneCancer researchGenetics

Abstract

fetched live from OpenAlex

Sexually dimorphic breeding tubercles (BTs) are keratinized epidermal structures that form clusters on the dorsal surface of the anterior rays of zebrafish male pectoral fins. BTs appear during sexual maturation and are maintained through regular shedding and renewal of the keratinized surface. Following pectoral fin amputation, BT clusters regenerate after the initiation of revascularization, but concomitantly with a second wave of angiogenesis. This second wave of regeneration forms a web-like blood vessel network that penetrates the supportive epidermis of BTs. Upon analyzing the effects of sex steroids and their inhibitors, we show that androgens induce and estrogens inhibit BT cluster formation in intact and regenerating pectoral fins. Androgen-induced BT formation in females is accompanied by the formation of a male-like blood vessel network. Treatment of females with both androgens and an angiogenesis inhibitor results in the formation of undersized BT clusters when compared with females treated with androgens alone. Overall, the growth and regeneration of large BTs requires a hormonal stimulus and the presence of an additional blood vessel network that is naturally found in males.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.047
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.016
GPT teacher head0.268
Teacher spread0.253 · 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

Citations34
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueDevelopmentSame topicZebrafish Biomedical Research ApplicationsFrench-language works237,207