Single-treatment tumor ablation with photodynamic liposomal irinotecan sucrosulfate
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
Irinotecan (IRI) loaded actively into PEGylated liposomes via a sucrosulfate gradient has been approved recently to treat advanced pancreatic cancer. In this study, a similar liposomal composition was developed that includes a low mole fraction (1 mol.%) of porphyrin-phospholipid (PoP), a photosensitizer that stably incorporates into liposomes, to confer light-triggered IRI release. IRI-loaded PoP liposomes containing ammonium sucrosulfate (ASOS) as a complexing agent were more stable in serum compared to liposomes employing the more conventional ammonium sulfate. Without irradiation, PoP IRI liposomes released less than 5% IRI during 8 h of incubation in bovine serum at 37 °C, but released over 90% of the drug within minutes of exposure to red light (665 nm) irradiation. A single treatment with IRI-PoP liposomes and light exposure (15 mg/kg IRI with 250 J/cm 2 ) resulted in tumor eradication in mice bearing either MIA PaCa-2 tumors or low-passage patient-derived tumor xenografts that recapitulate characteristics of the clinical disease. Analogous monotherapies of IRI or photodynamic therapy were ineffective in controlling tumor growth. Enhanced drug uptake could be visualized within laser-treated tumors by direct in situ imaging of irinotecan. Biodistribution analysis of IRI, its active metabolite (SN-38), and major metabolite (SN-38 G) showed that laser treatment significantly increased tumor accumulation of all IRI-derived molecular species. A pharmacokinetic model that hypothesized tumor vasculature permeabilization as the primary reason underlying the increased drug deposition accounted for the enhanced drug influx into tumors.
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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) | 0.001 | 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 it