Two unique biological response-modifier glucans beneficially regulating gut microbiota and faecal metabolome in a non-alcoholic steatohepatitis animal model, with potential applications in human health and disease
Bibliographic record
Abstract
OBJECTIVE: The gut microbiome and its metabolites are influenced by age and stress and reflect the metabolism and health of the immune system. We assessed the gut microbiota and faecal metabolome in a static animal model of non-alcoholic steatohepatitis (NASH). DESIGN: This model was subjected to the following treatments: reverse osmosis water, AFO-202, N-163, AFO-202+N-163 and telmisartan treatment. Faecal samples were collected at 6 and 9 weeks of age. The gut microbiome was analysed using 16S ribosomal RNA sequences acquired by next-generation sequencing, and the faecal metabolome was analysed using gas chromatography-mass spectrometry. RESULTS: Gut microbial diversity increased greatly in the AFO-202+N-163 group. Postintervention, the abundance of Firmicutes decreased, whereas that of Bacteroides increased and was the highest in the AFO-202+N-163 group. The decrease in the abundance of Enterobacteriaceae and other Firmicutes and the abundance of Turicibacter and Bilophila were the highest in the AFO-202 and N-163 groups, respectively. Lactobacillus abundance was highest in the AFO-202+N-163 group. The faecal metabolite spermidine, which is beneficial against inflammation and NASH, was significantly decreased (p=0.012) in the N-163 group. Succinic acid, which is beneficial in neurodevelopmental and neurodegenerative diseases, was increased in the AFO-202 group (p=0.06). The decrease in fructose was the highest in the N-163 group (p=0.0007). Isoleucine and Leucine decreased with statistical significance (p=0.004 and 0.012, respectively), and tryptophan also decreased (p=0.99), whereas ornithine, which is beneficial against chronic immune-metabolic-inflammatory pathologies, increased in the AFO-202+N-163 group. CONCLUSION: AFO-202 treatment in mice is beneficial against neurodevelopmental and neurodegenerative diseases, and has prophylactic potential against metabolic conditions. N-163 treatment exerts anti-inflammatory effects against organ fibrosis and neuroinflammation. In combination, these compounds exhibit anticancer activity.
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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 | 0.001 | 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 | 0.001 |
| 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".