Polar surface chemistry of nanofibrous polyurethane scaffold affects annulus fibrosus cell attachment and early matrix accumulation
Bibliographic record
Abstract
Regeneration of the annulus fibrosus (AF), one of the three components of the intervertebral disc (IVD), is challenging because of the tissue complexity and our limited knowledge about AF cell biology. The purpose of this study was to determine if modulating surface chemistry of polycarbonate polyurethane (PU) scaffolds would influence annulus fibrosus cell adhesion and early tissue formation. To vary surface energy, a novel anionic dihydroxyl oligomer (ADO) was synthesized and incorporated into the PU base polymer at three different concentrations [0.05, 0.5, and 5% (wt %)]. The polymeric materials were fabricated into nanoscale fibrous scaffolds using electrospinning. PU nanofibrous scaffolds in the absence or presence of different amounts of ADO were similar in appearance. Surface energy was significantly enhanced with increasing ADO content, as indicated by the decreasing water contact angle measurements. Increasing the material surface's polar character for the scaffolds resulted in a positive enhancement of AF cell attachment. The mechanism of this effect was complex as at higher ADO concentrations, increased cell adhesion was mediated by both serum and newly synthesized proteins, whereas at low ADO concentrations the latter had minimal effect. Collagen but not proteoglycan accumulation was also modulated by increasing ADO content. This study demonstrated that nanoscale fibrous PU scaffolds containing ADO may be appropriate candidates in the formation of tissue engineered annulus fibrosus tissue, and that material surface polar character can be used to influence AF cell attachment and collagen accumulation.
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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) | 0.000 | 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".