Dysembryoplastic neuroepithelial tumours: clinical, proliferative and apoptotic features
Bibliographic record
Abstract
AIMS: Dysembryoplastic neuroepithelial tumours (DNTs) have been considered benign lesions characterised by a chronic, indolent clinical course. Previous studies have suggested that increased proliferation rates may be balanced by corresponding rates of apoptosis. The objective of this study was to determine whether a correlation exists between histological features and indices of proliferation/apoptosis. METHODS: Fourteen consecutive surgical specimens meeting the histological criteria for DNT were retrospectively reviewed for evidence of aggressive histological features, including anaplasia, mitotic activity, and Ki67 labelling. Immunohistochemistry was performed semiquantitatively to evaluate and compare proliferation (Ki76) and apoptosis (TUNEL). The clinical course of the patients was also reviewed. RESULTS: Atypical histological features were demonstrated in the glial component of select complex DNTs. TUNEL indices, however, had negligible correlation with proliferative indices. A balance between cell proliferation and apoptosis was not evident particularly in those cases displaying aggressive histological features. CONCLUSIONS: While there is no clearly defined clinical or pathological pattern to indicate aggressive growth of DNTs, elevated proliferative indices coupled with atypical histological features in complex DNTs should be taken into consideration in determining the aggressiveness of surgical extirpation and follow-up until experience with these uncommon tumours is greater.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".