Blended Nanoparticle System Based on Miscible Structurally Similar Polymers: A Safe, Simple, Targeted, and Surprisingly High Efficiency Vehicle for Cancer Therapy
Why this work is in the frame
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Bibliographic record
Abstract
A novel blended nanoparticle (NP) system for the delivery of anticancer drugs and its surprisingly high efficacy for cancer chemotherapy by blending a targeting polymer folic acid-poly(ethylene glycol)-b-poly(lactide-co-glycolide) (FA-PEG-b-PLGA) and a miscible structurally similar polymer D-α-tocopheryl polyethylene glycol 1000 succinate-poly(lactide-co-glycolide) (TPGS-PLGA) is reported. This blended NP system can be achieved through a simple and effective nanoprecipitation technique, and possesses unique properties: i) improved long-term compatibility brought by PEG-based polymers; ii) reduced multidrug resistance mediated by P-glycoprotein (P-gp) in tumor cells and increased bioavailability of anticancer drugs by incorporation of TPGS; iii) the regulation of controlled release through polymer ratios and active targeting by FA. Both in vitro cell experiments and in vivo antitumor assays demonstrated the reported blended NP system can achieve the best therapeutic efficiency in an extremely safe, simple and highly efficient process for cancer therapy. Moreover, this NP system is highly efficient in forming NPs with multiple functions, without repeated chemical modification of polymers, which is sometimes complex, inefficient and high cost. Therefore, the development of this novel blended NP concept is extremely meaningful for the application of pharmaceutical nanotechnology in recent studies.
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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) | 0.000 | 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 it