Molecular design of upconversion nanoparticles for gene delivery
Bibliographic record
Abstract
Due to their large anti-Stokes shifts, sharp emission spectra and long excited-state lifetimes, upconversion nanoparticles (UCNPs) have attracted an increasing amount of research interests, and have shown great potential for enhancing the practical utility of gene therapy, whose versatility has been limited by existing gene delivery technologies that are basically mono-functional in nature. Despite this, up to now in-depth analysis of the development of UCNPs for gene delivery has been scant in the literature, even though there has been an upsurge of reviews on the chemistry of UCNPs and their applications in bioimaging and drug delivery. To fill this gap, this review aims to present the latest advances in the development and applications of UCNPs as gene carriers. Prior to describing the prominent works published in the field, a critical view on the properties, chemistry and molecular design of UCNPs for gene delivery is provided. With a synopsis of the recent advances in UCNP-mediated gene delivery, challenges and opportunities could be illuminated for clinical translation of works in this nascent field of research.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".