Design of an electrospun tubular construct combining a mechanical and biological approach to improve tendon repair
Bibliographic record
Abstract
Hand tendon injuries represent a major clinical problem and might dramatically diminish a patient's life quality. In this study, a targeted solution for flexor tendon repair was developed by combining a mechanical and biological approach. To this end, a novel acrylate-endcapped urethane-based polymer (AUP) was synthesized and its physico-chemical properties were characterized. Next, tubular repair constructs were developed using electrospinning of the AUP material with incorporated naproxen and hyaluronic acid (i.e. anti-inflammatory and anti-adhesion compounds, respectively), and with a tubular braid as mechanical reinforcement. Tensile testing of the repair constructs using ex vivo sheep tendons showed that the developed repair constructs fulfilled the required mechanical properties for tendon repair (i.e. minimal ultimate stress of 4 MPa), with an ultimate stress of 6.4 ± 0.6 MPa. Moreover, in vitro biological assays showed that the developed repair tubes and the incorporated bioactive components were non-cytotoxic. In addition, when equine tenocytes and mesenchymal stem cells were co-cultured with the repair tubes, an increased production of collagen and non-collagenous proteins was observed. In conclusion, this novel construct in which a mechanical approach (fulfilling the required mechanical properties) was combined with a biological approach (incorporation of bioactive compounds), shows potential as flexor tendon repair application. Graphical abstract.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".