Lymphangiogenesis in Esophageal Adenocarcinomas--Lymphatic Vessel Density as Prognostic Marker in Esophageal Adenocarcinoma
Bibliographic record
Abstract
We studied tumor lymphatic vascular density (LVD) as a predictive marker for the risk of lymph node (LN) metastasis and its relationship to other prognostic parameters and survival in 75 patients with esophageal adenocarcinoma. Samples were immunostained for D2-40, CD31, and vascular endothelial growth factor (VEGF). Microvessels were counted in densely vascular/lymphatic foci (hot spots) at x400 field (0.17 mm2). Intensity of staining for VEGF was scored on a 2-tiered scale. CD31 microvessel counts showed significant correlation with tumor stage and patient survival (P < .01). D2-40 LVD demonstrated a significant correlation with LN metastases, lymphovascular invasion, and tumor stage (r = 0.45, r = 0.47, and r = 0.37, respectively) and with shorter disease-free survival. D2-40 detected lymphovascular invasion in 29 of 75 cases, more than with CD31 (23/75) and H&E (18/75). VEGF was expressed in 48 (64%) of 75 cases and was significantly correlated with lymphovascular invasion, LN metastases, and overall survival. Our study showed that angiogenesis and lymphangiogenesis have important roles in the progression of esophageal adenocarcinoma.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".