Colloidal Gold-Mediated Delivery of Bleomycin for Improved Outcome in Chemotherapy
Bibliographic record
Abstract
Nanoparticles (NPs) can be used to overcome the side effects of poor distribution of anticancer drugs. Among other NPs, colloidal gold nanoparticles (GNPs) offer the possibility of transporting major quantities of drugs due to their large surface-to-volume ratio. This is while confining these anticancer drugs as closely as possible to their biological targets through passive and active targeting, thus ensuring limited harmful systemic distribution. In this study, we chose to use bleomycin (BLM) as the anticancer drug due to its limited therapeutic efficiency (harmful side effects). BLM was conjugated onto GNPs through a thiol bond. The effectiveness of the chemotherapeutic drug, BLM, is observed by visualizing DNA double strand breaks and by calculating the survival fraction. The action of the drug (where the drug takes effect) is known to be in the nucleus, and our experiments have shown that some of the GNPs carrying BLM were present in the nucleus. The use of GNPs to deliver BLM increased the delivery and therapeutic efficacy of the drug. Having a better control over delivery of anticancer drugs using GNPs will establish a more successful NP-based platform for a combined therapeutic approach. This is due to the fact that GNPs can also be used as radiation dose enhancers in cancer research.
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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) | 0.001 | 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".