TPU-based antiplatelet cardiovascular prostheses prepared using fused deposition modelling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This work describes the use of fused deposition modelling (FDM) to prepare antiplatelet thermoplastic polyurethane (TPU)-based tubular grafts. FDM 3D-printing technology is widely available and provides the ability to easily design tubular grafts on demand, enabling the customisation of vascular prosthesis dimensions. An antiplatelet drug, dipyridamole (DIP), was combined with TPU using hot-melt extrusion to prepare filaments. DIP cargos ranged between 5 and 20% (w/w). The resulting filaments were used to prepare small diameter vascular grafts using FDM. These grafts were characterised. Moreover, DIP release kinetics, antiplatelet activity and in vitro hemo- and cytocompatibility were evaluated. The results suggested that the materials could provide sustained DIP release for 30 days. Moreover, the presence of 5% DIP in the material showed a clear antiplatelet effect compared with pristine TPU. Alternatively, higher DIP loadings resulted higher surface roughness leading to higher platelet adhesion. Therefore, the biocompatibility of 5% DIP samples was tested showing that this type of materials allowed higher HUVEC cell proliferation compared to pristine TPU samples. Finally, DIP loaded TPU was combined with rifampicin-loaded TPU to prepare double-layered tubular grafts. These grafts demonstrated a clear antimicrobial activity against both Staphylococcus aureus and Escherichia coli.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 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 it