Effects of an aqueous extract of North American ginseng on MOG<sub>(35–55)</sub>-induced EAE in mice
Bibliographic record
Abstract
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system, in which the release of reactive oxygen species by infiltrating immune cells contributes to demyelination. American ginseng ( Panax quinquefolius ) is a natural health product with numerous beneficial properties, including anti-inflammatory and anti-oxidant effects. The purpose of this study was to determine whether ginseng could influence the course of the disease experimental autoimmune encephalomyelitis (EAE), an animal model of MS. C57BL/6J mice were immunized with MOG((35-55)) peptide to induce EAE. After clinical disease appeared, mice received either oral doses of an aqueous extract of ginseng (150 mg/kg body mass), or the vehicle. Clinical symptoms were recorded, and spinal cord tissue samples were analyzed for pathological signs of disease. The aqueous extract of ginseng significantly decreased (i) clinical signs of EAE, (ii) levels of circulating TNF-α, and (iii) central nervous system immunoreactive iNOS and demyelination scores, without a change in other neuropathological measures. This study shows that an aqueous extract of ginseng may be able to attenuate certain signs of EAE, suggesting that it may be a useful adjuvant therapy for MS.
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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".