Irinophore C, a Novel Nanoformulation of Irinotecan, Alters Tumor Vascular Function and Enhances the Distribution of 5-Fluorouracil and Doxorubicin
Bibliographic record
Abstract
PURPOSE: To examine the antitumor effects of Irinophore C, a nanopharmaceutical formulation of irinotecan, on the tissue morphology and function of tumor vasculature in HT-29 human colorectal tumors. EXPERIMENTAL DESIGN: Fluorescence microscopy was used to map and quantify changes in tissue density, tumor vasculature, hypoxia, and the distribution of Hoechst 33342, a perfusion marker, and the anticancer drug, doxorubicin. Noninvasive magnetic resonance imaging was used to quantify Ktrans, the volume transfer constant of a solute between the blood vessels and extracellular tissue compartment of the tumor, as a measure of vascular function. Following treatment with Irinophore C, 19F magnetic resonance spectroscopy was used to monitor the delivery of 5-fluorouracil (5-FU) to the tumor tissue, whereas scintigraphy was used to quantify the presence of bound [14C]5-FU. RESULTS: Irinophore C decreased cell density (P = 8.42 x 10(-5)), the overall number of endothelial cells in the entire section (P = 0.014), tumor hypoxia (P = 5.32 x 10(-9)), and K(trans) (P = 0.050). However, treatment increased the ratio of endothelial cells to cell density (P = 0.00024) and the accumulation of Hoechst 33342 (P = 0.022), doxorubicin (P = 0.243 x 10(-5)), and 5-FU (P = 0.0002) in the tumor. Vascular endothelial growth factor and interleukin-8, two proangiogenic factors, were down-regulated, whereas the antiangiogenic factor TIMP-1 was up-regulated in Irinophore C-treated tumors. CONCLUSIONS: Irinophore C treatment improves the vascular function of the tumor, thereby reducing tumor hypoxia and increasing the delivery and accumulation of a second drug. Reducing hypoxia would enhance radiotherapy, whereas improving delivery of a second drug to the tumor should result in higher cell kill.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".