<i>Rheum ribes</i> extract‐loaded nanoliposome as a novel phytogenic antibiotic alternative in mice challenged by <i>Escherichia coli</i> (O157:H7)
Bibliographic record
Abstract
This study was performed to compare the noncapsulated with nanoliposome-encapsulated phenolic-rich fraction (PRF) obtained from Rheum ribes as a dietary additive and to assess their health-promoting potentials in the mice infected by enteropathogenic Escherichia coli (O157:H7). Upon fractionation, the ethyl acetate fraction with 46.9 ± 2.17 mg GAE/g DW was found as a highest phenolic content. The PRF successfully loaded into nanoliposome structure with a nanometer in size (193.2 nm) and spherical shape and homogeneous dispersion. The gallic acid, salicylic acid, caffeic acid, cinnamic acid, catechin, ellagic acid, and ferulic acid are bioactive phenolics present in the nanoliposome-loaded PRF; however, the main bioactive compounds are cinnamic acid (911 μg/g DW) and ellagic acid (826 μg/g DW). The infection caused by E. coil impaired the weight gain and food intake, liver function, morpho structural characteristics of jejunum, upregulated the expression of inflammatory genes (Cox2, iNOS), downregulation of antioxidant-related genes (SOD, GPX), and increased the ileal population of E. coil. The addition of nonencapsulated PRF and nanoliposome-encapsulated PRF at the concentration of 10 mg TPC/kg BW/day improved these parameters although the nanoliposome-encapsulated PRF revealed more potential as compared with the nonencapsulated PRF in improving the health parameters in mice. The higher health-promoting activity of nanoliposome-encapsulated PRF could be associated with its enhanced intestinal absorption, bioavailability, bioaccessibility, and bioactivity. Consequently, the nanoliposome-encapsulated PRF could be considered as a promising phytobiotic against E. coil infection in mice.
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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) | 0.000 | 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 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".