Novel Nanoparticle-Based Cancer Treatment, Effectively Inhibits Lung Metastases and Improves Survival in a Murine Breast Cancer Model
Bibliographic record
Abstract
Sarah Nanoparticles (SaNPs) are unique multicore iron oxide-based nanoparticles, developed for the treatment of advanced cancer, following standard care, through the selective delivery of thermal energy to malignant cells upon exposure to an alternating magnetic field. For their therapeutic effect, SaNPs need to accumulate in the tumor. Since the potential accumulation and associated toxicity in normal tissues are an important risk consideration, biodistribution and toxicity were assessed in naïve BALB/c mice. Therapeutic efficacy and the effect on survival were investigated in the 4T1 murine model of metastatic breast cancer. Toxicity evaluation at various timepoints did not reveal any abnormal clinical signs, evidence of alterations in organ function, nor histopathologic adverse target organ toxicity, even after a follow up period of 25 weeks, confirming the safety of SaNP use. The biodistribution evaluation, following SaNP administration, indicated that SaNPs accumulate mainly in the liver and spleen. A comprehensive pharmacokinetics evaluation, demonstrated that the total percentage of SaNPs that accumulated in the blood and vital organs was ~78%, 46%, and 36% after 4, 13, and 25 weeks, respectively, suggesting a time-dependent clearance from the body. Efficacy studies in mice bearing 4T1 metastatic tumors revealed a 49.6% and 70% reduction in the number of lung metastases and their relative size, respectively, in treated vs . control mice, accompanied by a decrease in tumor cell viability in response to treatment. Moreover, SaNP treatment followed by alternating magnetic field exposure significantly improved the survival rate of treated mice compared to the controls. The median survival time was 29 ± 3.8 days in the treated group vs . 21.6 ± 4.9 days in the control, p -value 0.029. These assessments open new avenues for generating SaNPs and alternating magnetic field application as a potential novel therapeutic modality for metastatic cancer patients.
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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 | 0.001 |
| 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) | 0.000 | 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".