Nano‐liposomal encapsulation of <i>Artemisia aucheri</i> phenolics as a potential phytobiotic against <i>Campylobacter jejuni</i> infection in mice
Bibliographic record
Abstract
Abstract Background Artemisia aucheri contains antibacterial phenolic compounds. The current work was implemented to evaluate the effectiveness of a nanoliposome‐encapsulated phenolic‐rich fraction (PRF‐NLs), as a dietary phytobiotic derived from Artemisia aucheri's areal parts, on the inhibition of enteropathogenic Campylobacter jejuni ( C. jejuni ) infection in mice. Methods The phenolic‐rich fraction was loaded into the nanoliposome structure to obtain a nanometer‐scale size liposome with homogenous dispersion. Next, 40 white male balb/c mice were assigned to 4 treatment groups. The PRF‐NLs antibacterial potential was evaluated by evaluating the blood parameters, liver lipid peroxidation, and gene expression profiling in the mice challenged by C. jejuni infection. Results Mice infected by C. jejuni showed impairment in food intake, weight gain, liver function, ileum morphometric features, and ileum tissue inflammation. The diet of fortified food with the nonencapsulated and nanoliposome‐encapsulated phenolic compounds was found to improve these parameters at 10 mg TPC/kg BW/day concentration. Our data indicated that the nanoliposome‐encapsulated PRF was more effective in promoting the health parameters in mice as compared to nonencapsulated PRF. Conclusion It could be concluded that the liposomal encapsulation can promote the solubility, availability, and effectiveness of Artemisia aucheri phenolic compounds playing a key role as phytobiotic in mice intervened by enteropathogenic C. jejuni .
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".