Enhanced drug delivery in rabbit VX2 tumours using thermosensitive liposomes and MRI-controlled focused ultrasound hyperthermia
Bibliographic record
Abstract
PURPOSE: The efficacy of anticancer drugs in solid tumours is impaired by their inability to reach all cancer cells in sufficient concentration to cause cytotoxicity. Hyperthermia-triggered release of drugs from thermosensitive liposomes can increase tumour drug concentration, but tumour-specific drug delivery requires precise temperature control, and effects on microregional distribution of anticancer drugs in tumours are unknown. Here we evaluate thermally triggered release of doxorubicin in a rabbit tumour model by comparing free versus thermosensitive liposomal doxorubicin administered systemically during magnetic resonance imaging (MRI)-controlled focused ultrasound hyperthermia. MATERIALS AND METHODS: Twelve rabbits with a transplanted VX2 tumour in each thigh had a 10 mm diameter region in one tumour heated to 43°C using focused ultrasound with temperature control by MRI thermometry. Delivery of doxorubicin to tumours and normal tissues was quantified by fluorescence in tissue homogenates, and by fluorescence microscopy. RESULTS: Using thermosensitive liposomal doxorubicin (2.5 mg/kg), doxorubicin concentrations in heated tumours were 26.7 times higher than in unheated tumours (n = 7, p = 0.017, two-sided Wilcoxon signed-rank test). There was no significant enhancement with free doxorubicin in heated versus unheated tumours (n = 3, p = 0.5). With thermosensitive liposomes (8.3 mg/kg), fluorescence microscopy demonstrated increased doxorubicin fluorescence in heated versus unheated tumours, co-localised with nuclear staining throughout the tumour. CONCLUSIONS: Localised image-guided delivery of high concentrations of doxorubicin to cancer cells was achieved non-invasively in implanted tumours with temperature-sensitive drug carriers and a preclinical MRI-controlled focused ultrasound hyperthermia system.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".