Photodynamic therapy for the treatment of metastatic lesions in bone: studies in rat and porcine models
Bibliographic record
Abstract
This study represents the first reported use of photodynamic therapy in bone and specifically, as a treatment for spinal metastases. A metastatic model in rat confirmed the efficacy of benzoporphyrin derivative-monoacid-mediated PDT for treating lesions within the spine and appendicular bone. Fluorimetry confirmed the selective accumulation of drug into the tumor(s) at 3 hours post-injection. 48 hrs post light delivery into the vertebral body of the rat spine loss of bioluminescent signal and histological analyses of sectioned spine confirmed MT-1 tumor cell kill in vivo as previously confirmed in vitro using an established cell viability assay. Porcine vertebrae provided a model comparable to that of human for light propagation and PDT response. Light measurements were recorded at 2.5 mm increments as the detector probe was retracted out of the vertebral body away from a diffusing fiber at 70-90° planar angle to it. At 30 minutes or 1hr post BPD-MA administration (6 mg/m2), light (648 J, 150 mW/cm, 690 nm) was delivered to vertebrae L1 and/or L2. Vertebrae were harvested and sectioned for histology 48 hrs following PDT. Light propagation was plotted as distance (μm) from the emitting source. Results support the application of PDT to the treatment of primary or metastatic lesions within bone.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".