Engineered Cellular Uptake and Controlled Drug Delivery Using Two Dimensional Nanoparticle and Polymer for Cancer Treatment
Bibliographic record
Abstract
Two major problems in chemotherapy, poor bioavailability of hydrophobic anticancer drug and its adverse side effects causing nausea, are taken into account by developing a sustained drug release vehicle along with enhanced bioavailability using two-dimensional layered double hydroxides (LDHs) with appropriate surface charge and its subsequent embedment in polymer matrix. A model hydrophobic anticancer drug, raloxifene hydrochloride (RH), is intercalated into a series of zinc iron LDHs with varying anion charge densities using an ion exchange technique. To achieve significant sustained delivery, drug-intercalated LDH is embedded in poly(ε-caprolactone) (PCL) matrix to develop intravenous administration and to improve the therapeutic index of the drug. The cause of sustained release is visualized from the strong interaction between LDH and drug, as measured through spectroscopic techniques, like X-ray photoelectron spectroscopy, infrared, UV-visible spectroscopy, and thermal measurement (depression of melting temperature and considerable reduction in heat of fusion), using differential scanning calorimeter, followed by delayed diffusion of drug from polymer matrix. Interestingly, polymer nanohybrid exhibits long-term and excellent in vitro antitumor efficacy as opposed to pure drug or drug-intercalated LDH or only drug embedded PCL (conventional drug delivery vehicle) as evident from cell viability and cell adhesion experiments prompting a model depicting greater killing efficiency (cellular uptake) of the delivery vehicle (polymer nanohybrid) controlled by its better cell adhesion as noticed through cellular uptake after tagging of fluorescence rhodamine B separately to drug and LDH. In vivo studies also confirm the sustained release of drug in the bloodstream of albino rats using polymer nanohybrid (novel drug delivery vehicle) along with a healthy liver vis-à-vis burst release using pure drug/drug-intercalated LDHs with considerable damaged liver.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".