FGF Receptor Signaling at the Crossroads of Endocrine Homeostasis and Tumorigenesis
Bibliographic record
Abstract
Multiple endocrine neoplasia (MEN) syndromes represent familial disorders characterized by endocrine cell growth and hormone production dysregulation. For several decades, the fibroblast growth factor (FGF) system has been suspected of playing a unique function in MEN-type I (MEN I). However, specific elucidation of these actions has been hampered by the overwhelming redundancy of this complex system. The human FGF family is composed of 22 members organized into 6 groups based on phylogenetic relationships. Signaling is mediated through membrane-spanning tyrosine kinase receptors encoded by four independent genes, some of which generate multiple products via alternative splicing or transcription initiation. High-affinity interaction between an FGF and its cognate receptor induces receptor dimerization and activation. Many FGFs display high-affinity interactions with multiple FGFRs, while some activate unique receptors or receptor isoforms. Most FGFs have demonstrated mitogenic activity in a variety of systems; however, a growing number display predominantly metabolic actions. This review will examine the evidence that FGF/FGFRs play a role in sporadic endocrine neoplasia and the pathways in which these molecules may be selectively targeted for therapeutic purposes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".