Extracts from Frangula alnus Mill. and Their Effects on Environmental and Probiotic Bacteria
Bibliographic record
Abstract
The bark of Frangula alnus Mill (FAM), the so-called alder buckthorn, has been widely investigated for its medicinal properties, especially its laxative effects and the bioactive properties of the plant material extract. Still, there is no wider study devoted to its antibacterial properties. This is important in the context of its impact on probiotic gut bacteria. The aim of the research was to recognize the effect of FAM extract on bacterial cells, and to determine how the bioactive properties and composition of the extract are influenced by the type of solvent used for the extraction. To find the most suitable conditions for the FAM extraction, we used four solvent solutions with different polarities, including water, methanol, ethanol, and isopropanol. We assessed the quality and composition of the extracts with spectral analysis, using spectrophotometric (FTIR, UV-Vis) and chromatographic methods (GC-MS). Finally, we analyzed the extractant impact of the extracts on the selected bacterial cells. The results showed that the chemical diversity of the extracts increased with the increase in solvent polarity, in which the abundance of frangulin, the main bioactive compound in buckthorn bark, was confirmed. Pseudomonas fluorescens ATCC 17400 was particularly sensitive to the action of extracts, whereas other strains of the Pseudomonas genus showed practically no adverse effects. Ethanolic extracts had the strongest effect on most of the selected bacteria strains. We found that the probiotic Lactobacillus strain, which represents intestinal microflora, has no direct effect on probiotic microorganisms. The research shown FAM extracts can be safe for probiotic bacteria present in human gut microflora. Moreover, the study indicated that contact with the extracts may reduce the total permeability of the bacterial membranes. This opens up the possibility of using FAM extracts as a factor regulating transport into cells, which may be used to support the action of other bioactive substances.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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".