Rheological Studies of an Injectable Radiopaque Hydrogel for Embolization of Abdominal Aortic Aneurysms
Bibliographic record
Abstract
Several embolizing agents have been tested for minimally invasive treatment of intracranial aneurysms, and more recently to prevent or treat persistent blood flow (endoleaks) in abdominal aortic aneurysms. However, frequent recurrence of endoleaks was seen in most studies, suggesting that current embolization agents are not satisfying yet. Here we report rheological studies of a radiopaque chitosan hydrogel as an embolizing agent. The aim is to provide an agent that would be visible during x-ray based guided interventions. In this study, a commercial contrast agent (iopamidol) was associated to chitosan at different concentrations and its influence on the rheological behavior of chitosan thermogel was evaluated. The resulting hydrogels have a homogenous coherent structure. The addition of iopamidol leaded to an initially more viscous solution. To have a good visibility of hydrogel via x-ray, an optimum iopamidol concentration of 20% v/v was chosen. The addition of 20% v/v iopamidol increased the gelation time. The use of a high βGP concentration constitutes a solution to overcome the slowing down of gelation by 20% v/v iopamidol. Formulations containing around 16-20% βGP provides viscous solutions which rapidly gel and could be promising injectable radiopaque hydrogels for embolization.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".