Differences in alcohol versus aqueous extracts of North American Ginseng in protecting against eccentric exercise‐induced muscle damage in rats
Bibliographic record
Abstract
The extraction process employed with North American Ginseng extracts (NAGE) is known to influence their composition and pharmacological action. Hence, the effects of different NAGE on muscle protection against acute exercise were examined. Male Wistar rats were given daily supplementation (300 mg/kg) of an Alcohol (Al) or Aqueous (Aq) ginseng extract or water placebo (P). After 14 days, each group was randomly divided into non‐exercise Control (C) or Exercise (Ex) conditions. The Ex groups ran (−14 % grade) for 1hr at a speed of 24 m/min and were sacrificed 24hr later. Plasma creatine kinase (CK) levels, structural damage (haematoxylin and eosin) and inflammation (immunostaining of the neutrophil marker, HIS48) in the soleus were analyzed. Both Al and Aq treatments significantly reduced (~18% and 25%, respectively), typical exercise‐induced rise in blood CK levels (p<0.002). However, only the Aq extract reduced morphological signs of damage (H&E) and inflammation (HIS48) (p<0.001). Steroidal saponins known as ginsenosides, found in both extracts, can reduce CK leakage by enhancing sarcolemma integrity thus lowering membrane disruption. Meanwhile, immunosuppressant actions of polysaccharides native to the Aq extract, known for their ability to attenuate over‐activation of leukocytes may explain the lack of similar protection from the Al extract. Supported by ORF grant #RE02‐049 & CIHR grant #CCT‐83029
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".