Tissue Reaction to Polypyrrole-Coated Polyester Fabrics: An <i>in Vivo</i> Study in Rats
Bibliographic record
Abstract
Electrically conductive polypyrrole is very attractive for tissue engineering because of its potential to modulate cellular activities through electrical stimulation. However, its in vivo behaviors have not been fully studied. This paper investigates the in vivo biocompatibility and biostability of PPy-coated polyester fabrics. Three PPy-coated fabrics were prepared using phosphonylation (PPy-Phos), plasma activation (PPy-Plas), and plasma activation plus heparin treatment (PPy-Plas-HE). Virgin and fluoropassivated fabrics (F-PET) were controls. The specimens were implanted subcutaneously in the back of rats for 3-90 days, then harvested and processed for enzymatic, histological, and morphological analyses. A noninvasive MRI method was used to continuously monitor the inflammation. The level of acid and alkaline phosphatase showed a similar or a less intensive cellular reaction by the PPy-coated fabrics, when compared to the controls. Histology supported the enzymatic results and showed a fast collagen infiltration at 28 days for the PPy-Phos fabric. MRI reported an overall decrease of inflammation over time, with the PPy-coated fabrics showing a similar or mild inflammation in contrast to the non-coated fabrics. PPy clusters and excessive PPy laminary coating on the PPy-Plas and PPy-Plas-HE were lost with the implantation. This experiment suggests a similar in vivo biocompatibility of the PPy-coated and noncoated polyester fabrics and the importance of achieving a thin, uniform PPy coating.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".