Enriched Graphene Oxide-Polypropylene Suture Threads Buttons Modulate the Inflammatory Pathway Induced by Escherichia coli Lipopolysaccharide
Bibliographic record
Abstract
Graphene oxide (GO), derived from graphene, has remarkable chemical–physical properties such as stability, strength, and thermal or electric conductivity and additionally shows antibacterial and anti-inflammatory properties. The present study aimed to evaluate the anti-inflammatory effects of polypropylene suture threads buttons (PPSTBs), enriched with two different concentrations of GO, in the modulation of the inflammatory pathway TLR4/MyD 88/NFκB p65/NLRP3 induced by the Escherichia coli (E. coli) lipopolysaccharide (LPS-E). The gene and the protein expression of inflammatory markers were evaluated in an in vitro model of primary human gingival fibroblasts (hGFs) by real-time PCR, western blotting, and immunofluorescence analysis. Both GO concentrations used in the polypropylene suture threads buttons-GO constructs (PPSTBs-GO) decreased the expression of inflammatory markers in hGFs treated with LPS-E. The hGFs morphology and adhesion on the PPSTBs-GO constructs were also visualized by inverted light microscopy, scanning electron microscopy (SEM), and real-time PCR. Together, these results suggest that enriched PPSTBs-GO modulates the inflammatory process through TLR4/MyD 88/NFκB p65/NLRP3 pathway.
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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".