Assessment of a long-term in vitro model to characterize the mechanical behavior and macrophage-mediated degradation of a novel, degradable, electrospun poly-urethane vascular graft
Bibliographic record
Abstract
An assessment tool to evaluate the degradation of biodegradable materials in a more physiological environment is still needed. Macrophages are critical players in host response, remodeling and degradation. In this study, a cell culture model using monocyte-derived primary macrophages was established to study the degradation, macro-/micro-mechanical behavior and inflammatory behavior of a new designed, biodegradable thermoplastic polyurethane (TPU) scaffold, over an extended period of time in vitro. For in vivo study, the scaffolds were implanted subcutaneously in a rat model for up to 36 weeks. TPU scaffolds were fabricated via the electrospinning method. This technique provided a fibrous scaffold with an average fiber diameter of 1.39 ± 0.76 μm and an average pore size of 7.5 ± 1.1 μm. The results showed that TPU scaffolds supported the attachment and migration of macrophages throughout the three-dimensional matrix. Scaffold degradation could be detected in localized areas, emphasizing the role of adherent macrophages in scaffold degradation. Weight loss, molecular weight and biomechanical strength reduction were evident in the presence of the primary macrophage cells. TPU favored the switch from initial pro-inflammatory response of macrophages to an anti-inflammatory response over time both in vitro and in vivo. Expression of MMP-2 and MMP-9 (the key enzymes in tissue remodeling based on ECM modifications) was also evident in vitro and in vivo. This study showed that the primary monocyte-derived cell culture model represents a promising tool to characterize the degradation, mechanical behavior as well as biocompatibility of the scaffolds during an extended period of observation.
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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) | 0.000 | 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 | 0.001 |
| 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".