Effects of Electrospun Nanostructure versus Microstructure on Human Aortic Endothelial Cell Behavior
Bibliographic record
Abstract
This study examines the effect of electrospun polyethylene terephthalate mats fiber diameter, orientation, and surface properties on the Human Aortic Endothelial Cell behavior. Mats with two different average fiber diameters (740 +/- 200 nm and 1.8 +/- 0.2 microm); orientations (low and high); NaOH-treated and untreated were prepared. NaOH treatment altered mats physical properties. AlamarBlue assay revealed that all four test mats supported cell adhesion and growth. Cell growth was observed to be faster for mat with large fiber diameter than for the small fiber diameter mat. Fluorescent staining and scanning electron microscopy showed that fiber diameter and orientation influenced cell morphology. Cells were randomly spread on the 740-nm diameter fibers whereas most of them were oriented along the fibers with 1.8 microm diameter. Mat with higher fiber alignment showed higher cell orientation. Cells penetrated into the mats having 1.8 +/- 0.2 microm fiber diameter but remained on the surface of the mat with 740 +/- 200 nm, as determined from histological analysis. These findings highly suggest that the two mats may be potential materials to construct a two layer vascular graft scaffold in which the mat with small diameter fibers forms the luminal surface and the mat with larger fiber diameter the abluminal surface.
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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".