Endovascular Treatment with Platinum Coils
Bibliographic record
Abstract
SUMMARY: Recanalization after coil occlusion is a concern for long-term results of endovascular treatment. Knowledge of molecular events following coil occlusion and recanalization could help design specific strategies to promote permanent occlusion. Platinum coils were implanted into canine maxillary, vertebral or lingual arteries. Coil occlusion (treatment 1), routinely followed by recanalization was compared with two strategies to prevent recanalization: beta radiation using (32)P coils (treatment 2) and endothelial denudation, using an endovascular device, followed by coil occlusion (treatment 3). The evolution of initial complete occlusions was followed by angiography and pathology at three months. Levels of messenger RNA of vWF (von Willebrand factor), SMA (smooth muscle actin), CD14, CD31 (or PECAM-1: Platelet Endothelial Cell Adhesion Molecule-1), PDGFBB (platelet-derived growth factor), TGF-b1 (transforming growth factor), MCP-1 (macrophage chemoattractant protein), Angiopoietins, Metalloproteinases-9, 14 and inhibitors (TIMP- 2, 4) were followed by Reverse Transcription and Polymerase Chain Reaction (RT-PCR). Analyses were performed one, four, seven and 14 days after coiling, and levels of expression after the three treatments were compared using ANOVAs. Intact arteries treated with platinum coils routinely recanalize (100%), but arteries treated by denudation and coiling or with radioactive coils recanalize in only 17% and 4% respectively (P<.001). Recanalization was associated with increased levels of vWF mRNA at seven days, a finding that was not observed with denudation or radiation (P=.015). There was no other significant difference. Recanalization is associated with early vWF expression, perhaps reflecting the development of endothelialized channels through thrombus formed after coil occlusion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".