Preclinical Efficacy of Heat-Activated Drug Delivery and Radiotherapy in Breast Cancer
Bibliographic record
Abstract
Despite advancements in breast cancer management, treating disease recurrence remains clinically challenging. Existing therapies are often limited by their toxicities and the emergence of treatment-resistant tumors. Delivery of doxorubicin via thermosensitive liposomes has been shown to enhance drug accumulation in tumors through intravascular drug release triggered by localized mild hyperthermia, which makes it a promising treatment approach for local disease. Beyond drug delivery, mild hyperthermia can also potentiate the anti-tumor efficacy of radiotherapy. Therefore, this study harnesses the synergy among heat-activated liposomal doxorubicin, mild hyperthermia, and radiotherapy, aiming to enhance the inhibition of primary tumor growth and potentially expand the therapeutic effect to distant metastases, while minimizing the toxicity associated with monotherapy dosages. Initial findings present the potency of this trimodal regimen, emphasizing the advantages of employing advanced drug delivery systems and combination treatment strategies in overcoming the limitations of current treatment paradigms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".