Comparison of Serum Metabolite Changes of Radiated Mice Administered with Panax quinquefolium from Different Cultivation Regions Using UPLC-Q/TOF-MS Based Metabolomic Approach
Bibliographic record
Abstract
Chemometric analysis of bioactive compounds revealed that American ginsengs (AGs) from different cultivation regions of China had a difference in quality, which indicates their possible pharmacological difference. A UPLC-Q/TOF-MS-based untargeted metabolomic approach was used to uncover serum metabolite changes in radiated mice pre-administered with AG root decoctions from seven cultivation regions and to further assess their quality difference. OPLS-DA revealed that 51 metabolites (ESI−) and 110 (ESI+) were differentially expressed in sera between the control and the radiated model mice. Heatmap analysis further revealed that AG could not reverse most of these radiation-altered metabolites, which indicates dietary supplement of AG before cobalt radiation had the weak potential to mediate serum metabolites that were altered by the sub-lethal high dose radiation. In addition, 83 (ESI−) and 244 (ESI+) AG altered metabolites were detected in radiated mice under radiation exposure. Both OPLS-DA on serum metabolomes and heatmap analysis on discriminant metabolites showed that AGs from different cultivation regions differentially influenced metabolic alterations in radiated mice, which indicates AGs from different cultivation regions showed the pharmacological difference in modulation of metabolite changes. AGs from Shandong, Shanxi, and Beijing provinces had more similar pharmacological effects than AGs from USA, Canada, Jilin, and Heilongjiang. Finally, 28 important potential biomarkers were annotated and assigned onto three metabolic pathways including lipid, amino acid, and energy metabolisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".