Overview of the application of inorganic nanomaterials in cancer photothermal therapy
Bibliographic record
Abstract
Cancer photothermal therapy (PTT) has captured the attention of researchers worldwide due to its localized and trigger-activated therapeutic effect. In this field, nanomaterials capable of converting the energy of the irradiation light into heat have been showing promising results in several pre-clinical and clinical assays. Such a therapeutic modality takes advantage of the innate capacity of nanomaterials to accumulate in the tumor tissue and their capacity to interact with NIR laser irradiation to exert a therapeutic effect. Therefore, several nanostructures composed of different materials and organizations for mediating a photothermal effect have been developed. In this review, the most common inorganic nanomaterials, such as gold, carbon-based materials, tungsten, copper, molybdenum, and iron oxide, which have been explored for mediating a tumor-localized photothermal effect, are summarized. Moreover, the physicochemical parameters of nanoparticles that influence the PTT effectiveness are discussed and the recent clinical advances involving inorganic nanomaterial-mediated cancer photothermal therapy are also presented.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".