Synergistic effects of black pepper Nano-emulsion and Lactobacillus acidophilus against Salmonella enteritidis in food systems
Bibliographic record
Abstract
Today, the importance of probiotic bacteria in ensuring human health and food safety has become clearer. This study investigates the synergic effects of Lactobacillus acidophilus and black pepper essential oil (BPEO) Nano-emulsion (BPEON) against Salmonella enteritidis in-vitro and in a ground beef model. The chemical composition of BPEO was analyzed via Gas Chromatography/Mass Spectrometry (GC-Mass), revealing major components such as Delta-3-Carene and Trans-Caryophyllene. The BPEON demonstrated significant antimicrobial properties, with minimum inhibitory concentrations (MIC) of 16 mg/ml in TSB and 50 mg/g in ground beef. BPEON effectively reduced S. enteritidis populations by 1.4 up to 3.47 CFU/ml and 0.8 up to 1.83 CFU/ml in vitro and ground beef, respectively, particularly at higher concentrations with combined treatments. Furthermore, RT-qPCR analysis showed a concentration- and time-dependent downregulation of up to 3.98, -4.74, and -5.15 and -6.35, -6.98, and -9.64-fold-change of the invA , avrA , and hilA genes in-vitro and ground beef, respectively. These findings contribute to understanding the synergistic effect of BPEON (as a natural antimicrobial agent and prebiotic) and probiotic bacteria, offering insights into innovative strategies for enhancing food safety and mitigating the risks associated with foodborne pathogens by creating synbiotic conditions. • Synergistic antimicrobial effect of BPEON and Lactobacillus acidophilus. • BPEON downregulates S. Enteritidis virulence genes in vitro and in ground beef. • MIC of BPEON is 16 mg/ml in vitro, 50 mg/g in ground beef. • Combined BPEON and probiotics enhance pathogen control in food safety. • BPEON and probiotics offer a natural preservation strategy for meat products.
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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".