Notch-1/2 receptors and Jagged-1 ligand, but not HERP-1 transcription factor, are immunohistochemically expressed in the epithelial lining of periapical cysts
Bibliographic record
Abstract
Background: To further understand the involvement of Notch pathway signaling in the pathogenesis of periapical cyst the immunohistochemical expression of Notch-1 and Notch-2 receptors, Jagged-1 ligand, and HERP-1 transcription factor in the lining epithelium of periapical cysts was investigated.Material and Methods: Thirty human periapical cysts were immunohistochemically stained with antibodies against Notch-1, Notch-2, Jagged-1, and HERP-1.Epithelial expression of each antibody was correlated with the presence of inflammation in the connective tissue of the cystic wall.Results: Notch-1 was identified in the basal and suprabasal epithelial cells of 30/30, Notch-2 in 19/24, and Jagged-1 in 27/30 cysts.HERP-1 was detected in scattered subepithelial inflammatory cells, but not in the lining epithelium of cysts.There was no significant correlation between the immunohistochemical expression of each antibody and the presence of inflammation in the connective tissue of the cystic wall.Conclusions: This immunohistochemical study showed expression of Notch-1/2 and Jagged-1 in periapical cysts that combined with the expression of HES1/5 found in a previous report, are indicative of the activation of Notch an endocrine-paracrine mechanism.Further research on the activity of Notch and other pathways in periapical cysts may contribute both to elucidate their pathogenesis and select molecular targets for future novel treatments.
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 | 0.001 |
| 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 | 0.001 |
| 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".