Nano-Encapsulation of Arsenic Trioxide Enhances Efficacy against Murine Lymphoma Model while Minimizing Its Impact on Ovarian Reserve In Vitro and In Vivo
Bibliographic record
Abstract
Advances in cancer therapy have increased the rate of survival of young cancer patients; however, female lymphoma patients frequently face a temporary or permanent loss of fertility when treated with traditional cytotoxic agents. The potential loss of fertility is an important concern that can influence treatment decisions for many premenopausal cancer patients. The negative effect of chemotherapeutic agents and treatment protocols to patients' fertility-referred to as fertotoxicity-are thus an increasingly important cancer survivorship issue. We have developed a novel nanoscale formulation of arsenic trioxide, a potent drug for treatment of hematological malignancies, and demonstrate that it has significantly better activity in a murine lymphoma model than the free drug. In parallel, we have developed a novel in vitro assay of ovarian follicle function that predicts in vivo ovarian toxicity of therapeutic agents. Our results reveal that the nanotherapeutic agent is not only more active against lymphoma, but is fertoprotective, i.e., it is much less deleterious to ovarian function than the parent drug. Thus, our in vitro assay allows rapid evaluation of both established and experimental anticancer drugs on ovarian reserve and can inform the selection of efficacious and fertility-sparing treatment regimens for reproductive-age women diagnosed with cancer.
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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 | 0.001 |
| 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) | 0.000 | 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".