Vascular normalisation as the stepping stone into tumour microenvironment transformation
Bibliographic record
Abstract
A functional vascular system is indispensable for drug delivery and fundamental for responsiveness of the tumour microenvironment to such medication. At the same time, the progression of a tumour is defined by the interactions of the cancer cells with their surrounding environment, including neovessels, and the vascular network continues to be the major route for the dissemination of tumour cells in cancer, facilitating metastasis. So how can this apparent conflict be reconciled? Vessel normalisation-in which redundant structures are pruned and the abnormal vasculature is stabilised and remodelled-is generally considered to be beneficial in the course of anti-cancer treatments. A causality between normalised vasculature and improved response to medication and treatment is observed. For this reason, it is important to discern the consequence of vessel normalisation on the tumour microenvironment and to modulate the vasculature advantageously. This article will highlight the challenges of controlled neovascular remodelling and outline how vascular normalisation can shape disease management.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".