Challenges of traditional herbal teas: plant infusions and their mixtures with bioactive properties
Bibliographic record
Abstract
In order to characterize and study the bioactivities of individual plant species and to determine how these characteristics are modified when preparing blends, five different plant species were selected: Erica australis L., Genista tridentata L., Melissa officinalis L., Mentha spicata L., and Prunella vulgaris L. Infusions prepared from each plant species and from three selected mixtures were analyzed in terms of nutritional values, phenolic compositions, and bioactive properties (antioxidant, antimicrobial, cytotoxic, and anti-inflammatory activities). The major compound detected in M. officinalis, M. spicata, and P. vulgaris infusions was rosmarinic acid, whilst in E. australis and G. tridentata flavonoid derivatives such as quercetin and genistein were identified. P. vulgaris and M. officinalis presented the best results in TBARS and OxHLIA assays, respectively. M. spicata and all mixtures presented anti-inflammatory activity. M. spicata showed the best cytotoxic properties and antimicrobial activity, and none of the infusions showed hepatotoxicity for non-tumour cells.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".