Mouse FLRT2 Interacts with the Extracellular and Intracellular Regions of FGFR2
Bibliographic record
Abstract
Fibroblast Growth Factor (FGF) signaling is known to be critical in mediating key developmental events during craniofacial development. Recent evidence suggests that members of the Fibronectin (F) Leucine (L) Rich (R) Transmembrane (T), FLRT, family modulate FGF signaling. FLRT2 has a highly specific pattern of expression during craniofacial development, in close relationship with FGFR2. We therefore characterized FLRT2/FGFR2 interactions in the context of craniofacial development and showed, by co-immunoprecipitation and GST pulldown assays with embryonic craniofacial tissue lysates, that FLRT2 interacted with FGFR2. Yeast two-hybrid assays further showed that the intracellular regions of both proteins interacted in addition to the interactions in the extracellular portions. The extracellular Leucine Rich Repeats domain of FLRT2 contributed to the interactions with the extracellular regions of FGFR2. Interactions in the intracellular regions of the 2 proteins were mediated by the C-tail domain in FLRT2. Furthermore, cells stably transfected with FLRT2 shRNAs or FLRT2 cDNA exhibited a concomitant decrease and increase, respectively, in FGFR2 protein, mRNA, and ERK phosphorylation levels, suggesting a positive feedback regulatory loop of FLRT2 on FGF signaling in craniofacial tissues. We propose that FLRT2-FGFR2 interactions represent a potential mechanism for regulation of FGF signaling by FLRT2 during craniofacial development.
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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) | 0.001 | 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) | 0.002 | 0.001 |
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.
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".