Antibacterial and Antibiofilm Efficacy of Green Synthesised <i>Haloxylon</i> Capped Silver Nanoparticles Against <scp> <i>Enterococcus faecalis</i> </scp>
Bibliographic record
Abstract
This study synthesised and characterised Haloxylon-capped silver nanoparticles (Haloxylon-AgNPs) and assessed their antibacterial and antibiofilm activity against Enterococcus faecalis. The study also examined Haloxylon-AgNPs' ability to target E. faecalis biofilms in root canals. Haloxylon salicornicum extract was used to synthesise silver nanoparticles. Physiochemical characterisation of Haloxylon-AgNPs was conducted. Antimicrobial and antibiofilm activity of Haloxylon-AgNPs was studied by agar diffusion method, minimum inhibitory concentration (MIC) determination, time-kill assay, confocal laser scanning microscopy (CLSM) and qPCR for virulence gene attenuation. One hundred and twenty extracted teeth were infected with E. faecalis and treated with either Haloxylon-AgNPs, chlorhexidine, calcium hydroxide or saline. The data were analysed using a one-way ANOVA and Tukey multiple comparison test to investigate the bacterial reduction between groups (p < 0.05, significant; p < 0.001, highly significant). A significant reduction in the thickness of biofilm and expression of cylA virulence gene of Haloxylon-AgNPs treated E. faecalis was observed. No difference was observed between Haloxylon-AgNPs, chlorhexidine and calcium hydroxide in the tooth model.
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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) | 0.001 | 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".