Smart Self-Assembled Nanosystem Based on Water-Soluble Pillararene and Rare-Earth-Doped Upconversion Nanoparticles for pH-Responsive Drug Delivery
Bibliographic record
Abstract
Exploring novel drug delivery systems with good stability and new structure to integrate pillararene and upconversion nanoparticles (UCNPs) into one system continues to be an important challenge. Herein, we report a novel preparation of a supramolecular upconversion nanosystem via the host-guest complexation based on carboxylate-based pillar[5]arene (WP5) and 15-carboxy-N,N,N-trialkylpentadecan-1-ammonium bromide (1)-functionalized UCNPs to produce WP5⊃1-UCNPs that can be loaded with the chemotherapeutic drug doxorubicin (DOX). Importantly, the WP5 on the surface of the drug-loaded nanosystem can be efficiently protonated under acidic conditions, resulting in the collapse of the nanosystem and drug release. Moreover, cellular uptake confirms that the nanosystem can enter human cervical cancer (HeLa) cells, resulting in drug accumulation in the cells. More importantly, cytotoxicity experiments demonstrated the excellent biocompatibility of WP5⊃1-UCNPs without loading DOX and that the nanosystem DOX-WP5⊃1-UCNPs exhibited an ability of killing HeLa cells effectively. We also investigated magnetic resonance imaging and upconversion luminescence imaging, which may be employed as visual imaging agents in cancer diagnosis and treatment. Thus, in the present work, we show a simple yet powerful strategy to combine UCNPs and pillar[5]arene to produce a unified nanosystem for dual-mode bioimaging-guided therapeutic applications.
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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".