Characterization of Water Extractable Crude Polysaccharides from Cherry, Raspberry, and Ginseng Berry Fruits: Chemical Composition and Bioactivity
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Bibliographic record
Abstract
Water extractable crude polysaccharides from three sweet cherry varieties, raspberries, and ginseng berry pulp were evaluated for their chemical composition, structural features, molecular weight, and bioactive properties. The yields of the crude polysaccharides isolated from cherries, raspberries, and ginseng berry pulp ranged from 0.79 to 0.18% on a dry weight fruit basis. All of the crude polysaccharides contained protein, phenolic compounds, and uronic acid. Each crude polysaccharide contained the sugar monomers: rhamnose, arabinose, xylose, mannose, galactose, and glucose. Of the water extractable polysaccharides obtained from the mature fruits, the crude polysaccharides from the raspberries had the highest molecular weight while the crude polysaccharides from the ginseng berry pulp had the smallest molecular weight. Results from Fourier transform infrared spectroscopy suggested that the crude polysaccharides contained a monosaccharide with six carbon atoms in a D-glucopyranose ring and a protein component. The crude polysaccharides from cherries, raspberries, and ginseng berry pulp were shown to possess antioxidant activity as determined with the ferric reducing antioxidant power and the 2,2-azinobis (3-ethyl-benzothiazoline-6-sulfonic acid) (ABTS) radical scavenging assays. The effect of crude polysaccharides on: (1) caspase 3 activation, which was determined using a hypoxia/reoxygenation model, and (2) immunostimulation, which was determined by evaluating the inflammatory mediator response, were examined. Only crude polysaccharides obtained from certain varieties of sweet cherries inhibited caspase 3 activation in a dose-dependent manner, while only the crude polysaccharides obtained from ginseng berry pulp stimulated immune function. Crude polysaccharides present in small fruits do possess bioactivities that may enhance human health.
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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 it