Fine‐Tuning Photochemical Immunogenic Cell Death by a Panel of Verteporfin‐Lipid Nanoparticles: A Data‐Driven Approach
Why this work is in the frame
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Bibliographic record
Abstract
Immunogenic cell death (ICD) is an immunostimulatory process that can be induced by light-activated photosensitizers, but its mechanisms remain unclear, especially with lipid nanoparticle (LNP) formulations. In this study, a multivariate, data-driven analysis was conducted using a panel of five verteporfin(V)-LNPs to identify the attributes that lead to the greatest photochemically-induced exposure of ICD markers in pancreatic cancer cells. These attributes include varying production of Type I (radicals) or Type II (singlet oxygen) reactive oxygen species (ROS) upon 690 nm activation, localization in different organelles, variable cellular uptake efficiencies, and different phototoxicity levels. Using principal component analysis, we identified that, unexpectedly, Type I ROS is most strongly associated with ICD marker exposure, which leads to dendritic cell activation ex vivo, while Type II ROS shows the weakest association. Furthermore, V-LNP localization in the endoplasmic reticulum and mitochondria is most strongly associated with exposure of ICD markers, while lysosomal localization shows the weakest association. ICD marker exposure is proportional to the degree of phototoxicity and cellular uptake efficiency for all V-LNPs. These findings provide critical insights into the multiparametric mechanism underlying photochemical ICD induced by V-LNPs and can inform the rational design of photochemical LNP constructs for augmenting anticancer immune responses.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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