Optimized Photoactivatable Lipid Nanoparticles Enable Red Light Triggered Drug Release
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
Encapsulation of small molecule drugs in long-circulating lipid nanoparticles (LNPs) can reduce toxic side effects and enhance accumulation at tumor sites. A fundamental problem, however, is the slow release of encapsulated drugs from these liposomal systems at the disease site resulting in limited therapeutic benefit. Methods to trigger release at specific sites are highly warranted. Here, it is demonstrated that incorporation of ultraviolet (UV-A) or red-light photoswitchable-phosphatidylcholine analogs (AzoPC and redAzoPC) in conventional LNPs generates photoactivatable LNPs (paLNPs) having comparable structural integrity, drug loading capacity, and size distribution to the parent DSPC-cholesterol liposomes. It is shown that 65-70% drug release (doxorubicin) can be induced from these systems by irradiation with pulsed light based on trans-to-cis azobenzene isomerization. In vitro it is confirmed that paLNPs are non-toxic in the dark but convey cytotoxicity upon irradiation in a human cancer cell line. In vivo studies in zebrafish embryos demonstrate prolonged blood circulation and extravasation of paLNPs comparable to clinically approved formulations, with enhanced drug release following irradiation with pulsed light. Conclusively, paLNPs closely mimic the properties of clinically approved LNPs with the added benefit of light-induced drug release making them promising candidates for clinical development.
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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 | 0.000 | 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) | 0.004 | 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