Fabrication and Plasma Modification of Nanofibrous Tissue Engineering Scaffolds
Bibliographic record
Abstract
This paper provides a comprehensive overview of nanofibrous structures for tissue engineering purposes and the role of non-thermal plasma technology (NTP) within this field. Special attention is first given to nanofiber fabrication strategies, including thermally-induced phase separation, molecular self-assembly, and electrospinning, highlighting their strengths, weaknesses, and potentials. The review then continues to discuss the biodegradable polyesters typically employed for nanofiber fabrication, while the primary focus lies on their applicability and limitations. From thereon, the reader is introduced to the concept of NTP and its application in plasma-assisted surface modification of nanofibrous scaffolds. The final part of the review discusses the available literature on NTP-modified nanofibers looking at the impact of plasma activation and polymerization treatments on nanofiber wettability, surface chemistry, cell adhesion/proliferation and protein grafting. As such, this review provides a complete introduction into NTP-modified nanofibers, while aiming to address the current unexplored potentials left within the field.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".