Nanocomplexes of Photolabile Polyelectrolyte and Upconversion Nanoparticles for Near-Infrared Light-Triggered Payload Release
Bibliographic record
Abstract
A new approach to encapsulating charged cargo molecules into a nanovector and subsequently using near-infrared (NIR) light to trigger the release is demonstrated. NIR light-responsive nanovector was prepared through electrostatic interaction-driven complexation between negatively charged silica-coated upconversion nanoparticles (UCNP@silica, 87 nm hydrodynamic diameter, polydispersity index ∼0.05) and a positively charged UV-labile polyelectrolyte bearing pendants of poly(ethylene glycol) and o-nitrobenzyl side groups; whereas charged fluorescein (FLU) was loaded through a co-complexation process. By controlling the amount of polyelectrolyte, UCNP@silica can be covered by the polymer, whereas remaining dispersed in aqueous solution. Under 980 nm laser excitation, UV light emitted by UCNP is absorbed by photolytic side groups within polyelectrolyte, which results in cleavage of o-nitrobenzyl groups and formation of carboxylic acid groups. Such NIR light-induced partial reversal of positive charge to negative charge on the polyelectrolyte layer disrupts the equilibrium among UCNP@silica, polyelectrolyte, and FLU and, consequently, leads to release of FLU molecules.
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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".