Immunohistochemical localization of fibroblast growth factors FGF‐1 and FGF‐2, and receptors FGFR2 and FGFR3 in the epithelium of human odontogenic cysts and tumors
Bibliographic record
Abstract
Acidic (FGF-1) and basic (FGF-2) fibroblast growth factors are members of a family of growth factors that function in growth, differentiation and regeneration of a variety of tissues. Their presence in human odontogenic cysts and tumors has not been previously investigated. This study was designed to detect immunohistochemically the presence of these factors and two fibroblast growth factor receptors (FGFR2 and FGFR3) in a cross section of odontogenic cysts and tumors, to determine if they may be involved in the differentiation of odontogenic epithelium or, more specifically, in the development of particular cysts or tumors. Archival formalin-fixed paraffin-embedded tissues were used. With some exceptions, FGF-2 and the receptor FGFR2, were found in the cytoplasm and occasionally in the nuclei of cells of odontogenic epithelium, while FGF-1 and the receptor FGFR3, were absent or only focally or weakly detected, using standard immunohistochemical techniques. The data are similar to those published for normal murine odontogenesis, suggesting that these factors are associated with odontogenic differentiation rather than pathogenesis. The presence of significant nuclear staining in odontogenic epithelium associated with embryonic mesenchyme in ameloblastic fibromas and ameloblastic fibro-odontomas suggests that FGF-2 may be involved in directing nuclear activity at the histodifferentiation stage of odontogenesis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".