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Record W2101957987 · doi:10.1096/fj.14-249532

Follicle‐stimulating hormone synthesis and fertility depend on SMAD4 and FOXL2

2014· article· en· W2101957987 on OpenAlexafffund
Jérôme Fortin, Ulrich Boehm, Chu‐Xia Deng, Mathias Treier, Daniel J. Bernard

Bibliographic record

VenueThe FASEB Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsMcGill University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentCanadian Institutes of Health ResearchNational Institutes of HealthCalifornia Department of Fish and Game
KeywordsBiologyFollicle-stimulating hormoneHypogonadotropic hypogonadismConditional gene knockoutEndocrinologyInternal medicineRegulatorTranscription factorHormoneGonadotropin-releasing hormoneGeneLuteinizing hormonePhenotypeCell biologyGeneticsMedicine

Abstract

fetched live from OpenAlex

Follicle-stimulating hormone (FSH) is an essential regulator of gonadal function and fertility. Loss-of-function mutations in the FSHB/Fshb gene cause hypogonadotropic hypogonadism in humans and mice. Both gonadotropin-releasing hormone (GnRH) and activins, members of the transforming growth factor β (TGFβ) superfamily, stimulate FSH synthesis; yet, their relative roles and mechanisms of action in vivo are unknown. Here, using conditional gene-targeting, we show that the canonical mediator of TGFβ superfamily signaling, SMAD4, is absolutely required for normal FSH synthesis in both male and female mice. Moreover, when the Smad4 gene is ablated in combination with its DNA binding cofactor Foxl2 in gonadotrope cells, mice make essentially no FSH and females are sterile. Indeed, the phenotype of these animals is remarkably similar to that of Fshb-knockout mice. Not only do these results establish SMAD4 and FOXL2 as essential master regulators of Fshb transcription in vivo, they also suggest that activins, or related ligands, could play more important roles in FSH synthesis than GnRH.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.027
GPT teacher head0.271
Teacher spread0.243 · 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 designObservational
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

Citations83
Published2014
Admission routes2
Has abstractyes

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