Antibacterial studies of vitamin E encapsulated lemongrass oil nanoemulsions against gram‐negative and gram‐positive bacteria
Bibliographic record
Abstract
Abstract The current study assessed the antibacterial properties of vitamin E nanoemulsions, synthesized using a low‐energy phase inversion emulsification method. The nanoemulsions were characterized through particle size analysis, and their antimicrobial efficacy was assessed against the bacteria Staphylococcus aureus and Escherichia coli by disc diffusion method. The mechanisms underlying the antibacterial activity were investigated through scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). The vitamin E nanoemulsions demonstrated significant antibacterial activity against both bacterial strains. Specifically, the zone inhibition diameters for S. aureus and E. coli increased by 5.68 times and 2.61 times, respectively, compared to the pure vitamin E component. The incorporation of Tween 80 as a surfactant resulted in a reduction of the antibacterial properties of the nanoemulsions. Furthermore, the study found that the vitamin E encapsulated lemongrass oil nanoemulsion demonstrated higher antibacterial activity to S. aureus and E. coli when compared to other nanoemulsions. The nanoemulsions exhibited significantly greater resistance to S. Aureus as compared to E. coli . SEM and FTIR analyses revealed that the nanoemulsions induced alterations in bacterial cell membrane permeability and surface characteristics. These results confirmed the mechanism of vitamin E nanoemulsions antibacterial activity and established a crucial base for their potential use in food matrices.
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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".