Photothermal Therapy: From Encouraging Lab Results to Lackluster Clinical Translation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Cancer is a pervasive and complex disease that poses a significant threat to public health worldwide. The prevalent therapeutic options, including chemotherapy and radiotherapy, pose detrimental side effects. Consequently, non‐invasive and selective therapeutic strategies are sought, such as nanoparticle‐mediated photothermal therapy (PTT). This technique employs benign photothermal agents that gather within tumors post‐injection. Under near‐infra‐red light exposure, these agents induce localized hyperthermia, killing tumor cells. Here, the laboratory development, recent advances, and clinical status of photothermal therapy are examined. Despite two decades of development, photothermal therapy has yielded few clinical trials. A standout agent, the gold nanoshell, holds promise for prostate cancer treatment as the only one in human clinical trials. To provide context, PTT is compared to photodynamic therapy, which has over 250 human trials in 40 years, highlighting the need to bridge the gap for effective photothermal therapy translation. Therefore, we delve into the gap of clinical implementation between photothermal therapy and similar technologies, such as photodynamic therapy, laser interstitial thermal therapy, and cancer nanomedicines, offering insights and potential solutions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it