Recent advances in NIR-II fluorescence based theranostic approaches for glioma
Bibliographic record
Abstract
Gliomas are among the most common malignant tumors in the central nervous system and lead to poor life expectancy. However, the effective treatment of gliomas remains a considerable challenge. The recent development of near infrared (NIR) II (1000–1700 nm) theranostic agents has led to powerful strategies in diagnosis, targeted delivery of drugs, and accurate therapy. Because of the high capacity of NIR-II light in deep tissue penetration, improved spatiotemporal resolution can be achieved to facilitate the in vivo detection of gliomas via fluorescence imaging, and high contrast fluorescence imaging guided surgery can be realized. In addition to the precise imaging of tumors, drug delivery nano-platforms with NIR-II agents also allow the delivery process to be monitored in real-time. In addition, the combination of targeted drug delivery, photodynamic therapy, and photothermal therapy in the NIR region significantly improves the therapeutic effect against gliomas. Thus, this mini-review summarizes the recent developments in NIR-II fluorescence-based theranostic agents for glioma treatment.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".