Novel and Simple Alternative to Create Nanofibrillar Matrices of Interest for Tissue Engineering
Bibliographic record
Abstract
Synthetic analogs to natural extracellular matrix (ECM) at the nanometer level are of great potential for regenerative medicine. This study introduces a novel and simple method to produce polymer nanofibers and evaluates the properties of the resulting structures, as well as their suitability to support cells and their potential interest for bone and vascular applications. The devised approach diffracts a polymer solution by means of a spraying apparatus and of an airstream as sole driving force. The resulting nanofibers were produced in an effective fashion and a factorial design allowed isolating the processing parameters that control nanofiber size and distribution. The nanofibrillar matrices revealed to be of very high porosity and were effectively colonized by human bone marrow mesenchymal cells, while allowing ECM production and osteoblastic differentiation. In vivo, the matrices provided support for new bone formation and provided a good patency as small diameter vessel grafts.
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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".