Delivery of an anticancer drug and a chemosensitizer to murine breast sarcoma by intratumoral injection of sulfopropyl dextran microspheres
Bibliographic record
Abstract
Intratumoral injection of controlled-release microsphere formulations of anticancer compounds has the potential to selectively increase tumour exposure to drugs. This work aimed to evaluate the therapeutic effect and toxicity of microsphere formulations containing the anticancer drug, doxorubicin, in a murine tumour model. The effect of co-administration of verapamil, a P-glycoprotein modulator or chemosensitizer, was investigated. Initial in-vitro studies confirmed the ability of verapamil to enhance the accumulation of both doxorubicin and [(99mTc)]sestamibi, also a P-glycoprotein substrate, in EMT6 murine breast sarcoma cells and a doxorubicin-selected multidrug-resistant variant, EMT6/AR1.0. Ex-vivo studies using confocal microscopy demonstrated release of doxorubicin from microspheres and diffusion of the drug through tissue. For in-vivo studies, EMT6 and EMT6/AR1.0 cells were grown in BALB/c mice. Following intratumoral injection of doxorubicin-loaded microspheres, alone or in combination with verapamil-loaded microspheres, the tumour diameter was measured serially as an indication of therapeutic effect, while the weight, appearance, and behaviour of the mice were monitored as an indication of general toxicity. Intratumoral injections of doxorubicin-loaded microspheres were tolerated much better than systemic administration of equivalent drug concentrations. There was a modest (up to 34%) delay of tumour growth compared with groups receiving no treatment or blank microspheres. Co-injection of verapamil microspheres with doxorubicin microspheres produced a moderate increase in toxicity but no further delay in tumour growth. Controlled-release microsphere formulations of anticancer agents administered intratumorally were an efficient way to deliver high drug doses to the tumour with little systemic toxicity.
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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 | 0.000 |
| 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 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".