Leveraging Vitamin C to Augment Nanoenabled Photothermal Immunotherapy
Bibliographic record
Abstract
Photothermal immunotherapy (PTI) is valuable for precise tumor targeting and immune activation. However, its efficacy is hindered by insufficient immune response, elevated antioxidant levels within tumor, and intrinsic tumor resistance mechanisms. This study introduces Vitamin C (VC), a widely available dietary nutrient, as an effective enhancer for PTI. High-dose VC induces oxidative imbalance in tumor cells, making them more susceptible to nanoenabled near-infrared-II photothermal therapy (NIR-II PTT) with the photosensitizer IR1080. The combination of VC and NIR-II PTT significantly amplifies antitumor immunity by upregulating CXCL16 expression and promoting CXCR6 + T cell infiltration. Clinical data reveal that higher CXCL16 and CXCR6 levels in human tumors correlate with improved survival and T cell infiltration, underscoring the translational potential of this approach. This study positions VC as a safe, accessible, and cost-effective dietary enhancer for PTI, reshaping the role of dietary nutrients in cancer therapy and offering a strategy for overcoming treatment resistance.
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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) | 0.000 | 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 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".