A New Technique for Physiodesis Using Photodynamic Therapy
Bibliographic record
Abstract
Vascularization of developing growth plates is integral to the process of endochondral ossification. We hypothesized photodynamic therapy could be used to initiate premature vascularization and calcification of growth plates in mice on the induction of vascular endothelial growth factor. Three-week-old transgenic mice that emit bioluminescence on activation of the vascular endothelial growth factor gene were treated with different regimens of benzoporphyrin derivative mono-acid-mediated photodynamic therapy in the right, proximal tibial growth plate. We quantified changes in vascular endothelial growth factor-related bioluminescence at times after photodynamic therapy in vivo. The expression of vascular endothelial growth factor protein and CD31-labeled vasculature in growth plates also were examined with growth plate histology. Measurements of limb length were assessed in vivo using conventional radiography and confirmed on harvesting. Mice exposed to repeat treatments of 10 J x2 displayed enhanced bioluminescence 2 weeks after photodynamic therapy. Histology confirmed increased vasculature immediately adjacent to the growth plates with evidence of physeal closure. At 4 weeks posttreatment, limbs were shortened by an average of 9.5% +/- 4.4% without complication, confirming the potential application of photodynamic therapy for physiodesis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".