Chemical Composition, Antimicrobial and Antioxidant Activity of Echinophora platyloba DC
Bibliographic record
Abstract
The existence of artificial additives in food seems to be unhealthy from the consumers' point of view, and it is why scientists are looking for some solutions to reduce the unhealthy varieties of additives in manufactured products. This article presents a revision of studies published in recent years on this topic and looks at possible future trends in the sector on one of the indigenous plant activities, which is used as a food seasoning in Iran. Echinophora platyloba DC has a high potency to act as an antimicrobial and antioxidant at the same time. In 3 sections this article explains the subject as follows. The first part includes determination of chemical constituents of isolated fresh and dry aerial parts by different extraction methods. They were analyzed by Gas Chromatography. In the second part antibacterial and antifungal activity of both plant extracts and its essential oil were evaluated against gram positives and gram negatives followed by fungus. Finally in the last part, antioxidant properties of the plant are mentioned. The essential oil and the crude extracts from E. platyloba species are of active candidates which can be used as antioxidant, antimicrobial agents so they still would be the novel ones for further researches.
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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 | 0.001 | 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".