Biological Activities of Extracts from Sumac (Rhus spp.): A Review
Bibliographic record
Abstract
Abstract Sumac is the common name for a genus (Rhus) that contains over 250 individual species of flowering plants in the family Anacardiaceae. These plants are found in temperate and tropical regions worldwide, often grow in areas of marginal agricultural capacity, and have a long history of use by indigenous peoples for medicinal and other uses. The research efforts on sumac extracts to date indicate a promising potential for this plant family to provide renewable bioproducts with the following reported desirable bioactivities: antifibrogenic, antifungal, antiinflammatory, antimalarial, antimicrobial, antimutagenic, antioxidant, antithrombin, antitumorigenic, antiviral, cytotoxic, hypoglycaemic, and leukopenic. As well, the bioactive components can be extracted from the plant material using environmentally benign solvents that allow for both food and industrial end-uses. The favorable worldwide distribution of sumac also suggests that desirable bioproducts may be obtained at source, with minimal transportation requirements from the source through processing to end consumer. However, previous work has focussed on only a few members of this large plant family. In addition, not all of the species studied to date have been fully characterized for potential bioactive components and bioactivities. Thus, there remains a significant research gap spanning the range from lead chemical discovery through process development and optimization in order to better understand the full potential of the Rhus genus as part of global green technology based bioproduct and bioprocess research programs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".