Porphyrin-lipid stabilized paclitaxel nanoemulsion for combined photodynamic therapy and chemotherapy
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Bibliographic record
Abstract
BACKGROUND: Porphyrin-lipids are versatile building blocks that enable cancer theranostics and have been applied to create several multimodal nanoparticle platforms, including liposome-like porphysome (aqueous-core), porphyrin nanodroplet (liquefied gas-core), and ultrasmall porphyrin lipoproteins. Here, we used porphyrin-lipid to stabilize the water/oil interface to create porphyrin-lipid nanoemulsions with paclitaxel loaded in the oil core (PLNE-PTX), facilitating combination photodynamic therapy (PDT) and chemotherapy in one platform. RESULTS: PTX (3.1 wt%) and porphyrin (18.3 wt%) were loaded efficiently into PLNE-PTX, forming spherical core-shell nanoemulsions with a diameter of 120 nm. PLNE-PTX demonstrated stability in systemic delivery, resulting in high tumor accumulation (~ 5.4 ID %/g) in KB-tumor bearing mice. PLNE-PTX combination therapy inhibited tumor growth (78%) in an additive manner, compared with monotherapy PDT (44%) or chemotherapy (46%) 16 days post-treatment. Furthermore, a fourfold reduced PTX dose (1.8 mg PTX/kg) in PLNE-PTX combination therapy platform demonstrated superior therapeutic efficacy to Taxol at a dose of 7.2 mg PTX/kg, which can reduce side effects. Moreover, the intrinsic fluorescence of PLNE-PTX enabled real-time tracking of nanoparticles to the tumor, which can help inform treatment planning. CONCLUSION: PLNE-PTX combining PDT and chemotherapy in a single platform enables superior anti-tumor effects and holds potential to reduce side effects associated with monotherapy chemotherapy. The inherent imaging modality of PLNE-PTX enables real-time tracking and permits spatial and temporal regulation to improve cancer treatment.
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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) | 0.001 | 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) | 0.000 | 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