Antioxidants in Medicines and Spices as Cardioprotective Agents in Tibetan Highlanders
Bibliographic record
Abstract
Dietary and medicinal phytochemicals may contribute to the reportedly low incidence of cardiovascular disease (CVD) among Tibetan highlanders, despite elevated hematocrit levels and a diet high in saturated fat and low in fruits and vegetables. Antioxidant activity was measured in 14 plant species most commonly incorporated in Tibetan medicines prescribed for the treatment of cardiovascular related disease according to indigenous pharmacopoeias. Methanol extracts of Terminalia chebula, Syzygium aromaticum, Aquilaria agallocha, Santalum album, Amomum subulatum, Justicia adhatoda and Myristica fragrans displayed strong free radical scavenging activity using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical. These plants were further partitioned into a hexane, chloroform, ethyl acetate, and water fraction, and re-tested with DPPH assay. Fractions displaying strongest activity were examined in vitro for their ability to protect human low-density lipoprotein (LDL) from Cu 2+ - catalyzed oxidation measured using thiobarbituric acid reactive substances (TBARS) production and formation of conjugated dienes. The hexane fraction of S. aromaticum displayed an ability to reduced LDL susceptibility to oxidation (1339.96 ± 7.01 min lag time) three-times longer than Trolox ® (431.02 ± 21.9 min lag time), a hydrophilic analog of a-tocopherol. Approximately half of all plants included in this study contained fractions that displayed significant antioxidant activity. Our results suggest that these spices and medicinal plants may provide a therapeutic benefit towards CVD prevention and treatment, and reinforces the merits of traditional Tibetan medicine.
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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 | 0.001 |
| 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) | 0.001 | 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".