Weissella Paramesenteroides’ Effects on Two Neglected Wild Food Plants (Hydrocotyle bonariensis and Garcinia kola) Used in the Treatment of Hypertension in Côte d’Ivoire
Bibliographic record
Abstract
Lactic acid fermentation is a promising approach for enhancing the nutritional and functional properties of certain underutilised food plants. In this study, Hydrocotyle bonariensis and Garcinia kola were subjected to controlled fermentation by a probiotic lactic acid bacteria strain identified as Weissella paramesenteroides by 16S ribosomal gene sequencing. The resulting matrices were analysed to assess their antioxidant and anti-inflammatory activities using the DPPH and protein denaturation inhibition tests, respectively. The fermentation process significantly increased the content of proteins and minerals while reducing anti-nutritional factors such as phytates and oxalates. These biochemical changes correlated with enhanced antioxidant activity and anti-inflammatory potential in vitro. The antioxidant activity of Hydrocotyle bonariensis increased from 60.74±4.09% to 83.55±0.68%. Anti-inflammatory activity also increased after fermentation, reaching 72.96±0.89% for Hydrocotyle bonariensis and 98.11±2.67% for Garcinia kola. Fermentation also significantly increased levels of protein, vitamins (A, D and E) and essential minerals, such as magnesium, zinc, sodium and potassium. These nutritional and functional improvements suggest that incorporating Hydrocotyle bonariensis and Garcinia kola based fermented products into a diet for the prevention of hypertension and other metabolic diseases could improve intestinal health due to the beneficial effects of lactic fermentation.
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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 | 0.001 |
| 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".