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Record W4402832381 · doi:10.1073/pnas.2410269121

Paracrine FGF1 signaling directs pituitary architecture and size

2024· article· en· W4402832381 on OpenAlexafffund
Konstantin Khetchoumian, Kevin Sochodolsky, Chrystel Lafont, Arthur Gouhier, Amandine Bemmo, Yacine Kherdjemil, Marie Kmita, Paul Le Tissier, Patrice Mollard, Helen Christian, Jacques Drouin

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFibroblast Growth Factor Research
Canadian institutionsMontreal Clinical Research Institute
FundersCanadian Institutes of Health ResearchAgence Nationale de la Recherche
KeywordsParacrine signallingFGF1Cell biologyBiologyNeuroscienceChemistryInternal medicineFibroblast growth factorMedicineGeneticsReceptorFibroblast growth factor receptor

Abstract

fetched live from OpenAlex

Organ architecture is established during development through intricate cell–cell communication mechanisms, yet the specific signals mediating these communications often remain elusive. Here, we used the anterior pituitary gland that harbors different interdigitated hormone-secreting homotypic cell networks to dissect cell–cell communication mechanisms operating during late development. We show that blocking differentiation of corticotrope cells leads to pituitary hypoplasia with a major effect on somatotrope cells that directly contact corticotropes. Gene knockout of the corticotrope-restricted transcription factor Tpit results in fewer somatotropes, with less secretory granules and a loss of cell polarity, resulting in systemic growth retardation. Single-cell transcriptomic analyses identified FGF1 as a corticotrope-specific Tpit dosage-dependent target gene responsible for these phenotypes. Consistently, genetic ablation of FGF1 in mice phenocopies pituitary hypoplasia and growth impairment observed in Tpit -deficient mice. These findings reveal FGF1 produced by the corticotrope cell network as an essential paracrine signaling molecule participating in pituitary architecture and size.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.195

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.022
GPT teacher head0.309
Teacher spread0.287 · 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

Citations6
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicFibroblast Growth Factor ResearchFrench-language works237,207