Broad-spectrum ginsentides are principal bioactives in unraveling the cure-all effects of ginseng
Bibliographic record
Abstract
Abstract Ginseng has been known as a “cure-all” traditional medicine to treat various illnesses and as an adaptogen to relieve stress. However, the known active compounds of ginseng are small-molecule metabolites. Here we report ginsentides, which are disulfide-dense, super-stable and cell-penetrating peptides with 31–33 amino acids, as active compounds and adaptogens that restore homeostasis in response to stress. Using mass spectrometry-based target identification and functional studies, we show that ginsentides promote vasorelaxation by producing nitric oxide through endothelial cells via the PI3K/Akt signaling pathway. Ginsentides were also found to alleviate α1-adrenergic receptor overactivity by reversing phenylephrine-induced constriction of the aorta, decrease monocyte adhesion to endothelial cells via CD166/ESAM/CD40, inhibit P2Y12 receptors, reduce platelet aggregation, and thrombus formation in the lung. Orally administered ginsentides were effective in anti-stress behavior using animal models of tail suspension and forced swimming tests. Together, these results suggest that ginsentides interact with multiple systems to restore homeostasis by reversing stress-induced physiological changes and provide new insights into the panacea medicinal effects of ginseng.
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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 | 0.000 | 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 | 0.001 |
| 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".