Macromolecule Extravasation—Xenograft Size Matters: A Systematic Study Using Probe-Based Confocal Laser Endomicroscopy (pCLE)
Bibliographic record
Abstract
PURPOSE: Profound changes of the vasculature in tumors critically impact drug delivery and therapy response. We aimed at developing a procedure to monitor morphological and functional parameters of the vasculature in subcutaneous xenograft models commonly applied for therapy testing by using probe-based confocal laser endomicroscopy. PROCEDURES: By monitoring various normal and diseased tissues, we established an experimental and analytical set-up to systematically analyze tracer extravasation from the microvasculature. Application of the approach in two xenograft models (HCT-116 and SW620) was realized consecutively throughout tumor growth. RESULTS: The incidence of dilated vessels increased with xenograft size in both models while macromolecule extravasation and tracer accumulation in the tumor tissue, respectively, was significantly reduced throughout growth. The development of dilated/ultradilated vessels correlated with tracer extravasation only in the HCT-116 but not the SW620 model. The underlying mechanisms are still ambiguous and discussed. CONCLUSIONS: Our findings clearly indicate that both xenograft type and size matter for drug delivery and therapy testing.
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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 | 0.002 | 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 | 0.001 |
| 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".