Single‐wall carbon nanotubes assisted photothermal cancer therapy: Animal study with a murine model of squamous cell carcinoma
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: There has been a dramatic increase in photothermal therapy as a minimally invasive treatment modality for cancer treatment due to the development of novel nanomaterials as the light absorption agents. Single-wall carbon nanotubes (SWNTs) with strong optical absorption in the broad visible and near IR offer unique advantages for photothermal cancer therapy. A broad range of wavelengths can be used for the treatment with SWNTs, whereas conventional photothermal therapeutic agent is designed to absorb light only near one selected wavelength. The objective of this study is to validate the hypothesis that intratumoral injected SWNTs can absorb 785 nm near IR laser light and generate significant local hyperthermia to destroy tumors. STUDY DESIGN/MATERIALS AND METHODS: SCCVII tumor in C3H/HeN mice was exposed to 785-nm laser after intratumoral injection of SWNTs with different light and SWNTs dose combinations. The temperatures of the tumor with laser irradiation were monitored. In vivo and ex vivo Raman spectra in different organs were obtained with a rapid Raman system. Tumor responses (tumor volume and mouse survival) were documented daily after treatment up to day 45 to assess the effectiveness of the treatment. RESULTS: The temperature within the tumors increased in a light- and SWNTs-dose dependent manner. Squamous cell carcinomas can be eradicated at a moderate light irradiance and fluence (200 mW/cm² and 120 J/cm²). This light dose is also comparable to those used with photodynamic therapy. Tissue Raman spectroscopy measurements revealed that SWNTs remained localized in the tumor even 3 months after injection but was not found in other organs. CONCLUSIONS: This animal study represents a significant step forward towards the goal of advancing SWNTs based photothermal cancer therapy into clinical applications.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".