Depth of photothermal conversion of gold nanorods embedded in a tissue-like phantom
Bibliographic record
Abstract
Gold nanorod (AuNR)-assisted photothermal therapy has emerged as a viable method for selective killing of cancer cells and shows promise for tumor destruction in vivo. This study examined the distribution of AuNR conversion expected to occur during photothermal therapy in vivo. Tissue-like phantoms were prepared with polyethylene glycol AuNRs distributed homogeneously at a concentration representative of a systemic injection. Phantoms were illuminated with a nanosecond pulsed laser (800 nm) at a variety of combinations of pulse energy (12-120 mJ) and pulse count (1-1000). Operating at the American National Standards Institute safety limit for human skin exposure (30 mJ cm(-2)), a diameter of 13 mm and a depth of 7.6 mm of AuNR conversion were observed in the gel phantoms after 1000 laser pulses (100 s exposure). Significant AuNR conversion was measured to a depth of 6 mm after only 100 pulses. Comparison of the measured AuNR conversion distribution with Monte Carlo simulation suggested that the fluence threshold for AuNR conversion estimated from phantom measurements was in the range of 20-43 mJ cm(-2). The results suggest that AuNR-assisted photothermal therapy will be effective for tumors within 10 mm of the illuminated tissue surface.
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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".