Biosynthesized Silver Nanoparticle (AgNP) From Pandanus odorifer Leaf Extract Exhibits Anti-metastasis and Anti-biofilm Potentials
Bibliographic record
Abstract
Cancer and the associated secondary bacterial infections is a leading cause of mortality, due to the paucity of effective drugs. Here, we have synthesized silver nanoparticles (AgNPs) from organic resource and confirmed their anti-cancer and anti-microbial potentials. Microwave irradiation method was employed to synthesize AgNPs using Pandanus odorifer leaf extract. Anti-cancer potential of AgNPs was evaluated by scratch assay on the monolayer of rat basophilic leukemia (RBL) cells, indicating that the synthesized AgNPs inhibit the migration of RBL cells. The synthesized AgNPs showed MIC value of 4-16 µg/mL against both Gram +ve and Gram -ve bacterial strains, exhibiting the anti-microbial potential. Biofilm inhibition was recorded at sub-MIC values against Gram +ve and Gram -ve bacterial strains. Violacein and alginate productions were reduced by 89.6% and 75.6% respectively at 4 and 8 µg/mL of AgNPs, suggesting anti-quorum sensing activity. Exopolysaccharide production was decreased by 61-79% and 84% for Gram -ve and Gram +ve pathogens respectively. Flagellar driven swarming mobility was also reduced significantly. Furthermore, In vivo study confirmed their tolerability in mice, indicating their clinical perspective. Collective, we claim that the synthesized AgNPs have anti-metastasis as well as anti-microbial activities. Hence this can be further tested for therapeutic options to treat cancer and secondary bacterial infections.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
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; both teacher heads agree on what is shown here.
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".