Boron Neutron Capture Therapy: Clinical Application and Research Progress
Bibliographic record
Abstract
Boron neutron capture therapy (BNCT) is a binary modality that is used to treat a variety of malignancies, using neutrons to irradiate boron-10 (10B) nuclei that have entered tumor cells to produce highly linear energy transfer (LET) alpha particles and recoil 7Li nuclei (10B [n, α] 7Li). Therefore, the most important part in BNCT is to selectively deliver a large number of 10B to tumor cells and only a small amount to normal tissue. So far, BNCT has been used in more than 2000 cases worldwide, and the efficacy of BNCT in the treatment of head and neck cancer, malignant meningioma, melanoma and hepatocellular carcinoma has been confirmed. We collected and collated clinical studies of second-generation boron delivery agents. The combination of different drugs, the mode of administration, and the combination of multiple treatments have an important impact on patient survival. We summarized the critical issues that must be addressed, with the hope that the next generation of boron delivery agents will overcome these challenges.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".