Silver and Copper Nanoparticles Hosted by Carboxymethyl Cellulose Reduce the Infective Effects of Enterotoxigenic Escherichia coli:F4 on Porcine Intestinal Enterocyte IPEC-J2
Bibliographic record
Abstract
Zero-valent copper and silver metals (Ms) nanoparticles (NPs) supported on carboxymethylcellulose (CMC) were synthesized for treating Enterotoxigenic Escherichia coli fimbriae 4 (ETEC:F4), a major cause of diarrhea in post-weaned pigs. The antibacterial properties of Cu0/CMC and Ag0/CMC were assessed on infected porcine intestinal enterocyte IPEC-J2, an in vitro model mimicking the small intestine. The lower average particle size (218 nm) and polydispersity index [PDI]: 0.25) for Ag0/CMC, when compared with those of Cu0/CMC (367 nm and PDI 0.96), were explained by stronger Ag0/CMC interactions. The minimal inhibitory concentration (MIC) and half inhibitory concentration (IC50) of Ag0/CMC were lower in both bacteria and IPEC-J2 cells than those of Cu0/CMC, confirming that silver nanoparticles are more bactericidal than copper counterparts. IPEC-J2, less sensitive in MNP/CMC treatment, was used to further investigate the infective process by ETEC:F4. The IC50 of MNP/CMC increased significantly when infected IPEC-J2 cells and ETEC were co-treated, showing an inhibition of the cytotoxicity effect of ETEC:F4 infection and protection of treated IPEC-J2. Thus, it appears that metal insertion in CMC induces an inhibiting effect on ETEC:F4 growth and that MNP/CMC dispersion governs the enhancement of this effect. These results open promising prospects for metal-loaded biopolymers for preventing and treating swine diarrhea.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".