Prevention of cancer recurrence in tumor margins by stopping microcirculation in the tumor and tumor–host interface
Bibliographic record
Abstract
Combretastatins interrupt blood flow of solid tumor vascular networks and lead to necrosis by blocking nutrients. However, tumors recover from tumor blood flow interruption-induced damage and develop viable rims. To investigate why cancer recurs and its prevention, we used a combretastatin derivative, Cderiv (=AC7700), and analyzed changes in tumor-host interface (T-HI) vessels, which were closest to cancer cells in the tumor margin after tumor vessel disruption, and the microenvironment surrounding them. Treatment with Cderiv (10 mg/kg) interrupted tumor blood flow in all regions of LY80 (a variant of Yoshida sarcoma) tumor, but not T-HI vessel blood flow. The same Cderiv dose given 72 h after 5 Gy irradiation stopped T-HI vessel blood flow and prevented cancer recurrence. Treatment in the reverse order, however, did not affect T-HI vessel blood flow. The greatest difference between the two treatments was the occurrence of gradual T-HI edema with the former. Severe T-HI edema compressed T-HI blood vessels, so that circulation stopped. Thus, the distance between a tumor margin and its nearest functioning host vessel became much larger, and the tumor marginal region became a microenvironment that lacked a nutritional supply. Cancer cells in tumor margins received nutrients through two circulation routes: tumor vessels and T-HI vessels. Our starvation methods, which involved treatment with Cderiv 72 h after 5 Gy irradiation, blocked both circulation routes and may have great potential as a clinical strategy to prevent cancer recurrence.
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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 | 0.000 | 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".