The Neurod1/4-Ntrk3-Src pathway regulates gonadotrope cell adhesion and motility
Bibliographic record
Abstract
Pituitary gonadotrope cells are essential for the endocrine regulation of reproduction in vertebrates. These cells emerge early during embryogenesis, colonize the pituitary glands and organize in tridimensional networks, which are believed to be crucial to ensure proper regulation of fertility. However, the molecular mechanisms regulating the organization of gonadotrope cell population during embryogenesis remain poorly understood. In this work, we characterized the target genes of NEUROD1 and NEUROD4 transcription factors in the immature gonadotrope αT3-1 cell model by in silico functional genomic analyses. We demonstrated that NEUROD1/4 regulate genes belonging to the focal adhesion pathway. Using CRISPR/Cas9 knock-out approaches, we established a double NEUROD1/4 knock-out αT3-1 cell model and demonstrated that NEUROD1/4 regulate cell adhesion and cell motility. We then characterized, by immuno-fluorescence, focal adhesion number and signaling in the context of NEUROD1/4 insufficiency. We demonstrated that NEUROD1/4 knock-out leads to an increase in the number of focal adhesions associated with signaling abnormalities implicating the c-Src kinase. We further showed that the neurotrophin tyrosine kinase receptor 3 NTRK3, a target of NEUROD1/4, interacts physically with c-Src. Furthermore, using motility rescue experiments and time-lapse video microscopy, we demonstrated that NTRK3 is a major regulator of gonadotrope cell motility. Finally, using a Ntrk3 knock-out mouse model, we showed that NTRK3 regulates gonadotrope cells positioning in the developing pituitary, in vivo. Altogether our study demonstrates that the Neurod1/4-Ntrk3-cSrc pathway is a major actor of gonadotrope cell mobility, and thus provides new insights in the regulation of gonadotrope cell organization within the pituitary gland.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".