Self‐Assembled Nanoparticles from Phenolic Derivatives for Cancer Therapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Therapeutic nanoparticles hold clinical promise for cancer treatment by avoiding limitations of conventional pharmaceuticals. Herein, a facile and rapid method is introduced to assemble poly(ethylene glycol) (PEG)-modified Pt prodrug nanocomplexes through metal-polyphenol complexation and combined with emulsification, which results in ≈100 nm diameter nanoparticles (PtP NPs) that exhibit high drug loading (0.15 fg Pt per nanoparticle) and low fouling properties. The PtP NPs are characterized for potential use as cancer therapeutics. Mass cytometry is used to quantify uptake of the nanoparticles and the drug concentration in individual cells in vitro. The PtP NPs have long circulation times, with an elimination half-life of ≈18 h in healthy mice. The in vivo antitumor activity of the PtP NPs is systematically investigated in a human prostate cancer xenograft mouse model. Mice treated with the PtP NPs demonstrate four times better inhibition of tumor growth than either free prodrug or cisplatin. This study presents a promising strategy to prepare therapeutic nanoparticles for biomedical applications.
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.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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