Dissection of the Functional Mechanism of Human Gut Bacterial Strain AD16 by Secondary Metabolites’ Identification, Network Pharmacology, and Experimental Validation
Bibliographic record
Abstract
Gut microbiota plays important roles in several metabolic processes, such as appetite and food intake and absorption of nutrients from the gut. It is also of great importance in the maintenance of the health of the host. However, much remains unknown about the functional mechanisms of human gut microbiota itself. Here, we report the identification of one anticancer gut bacterial strain AD16, which exhibited potent suppressive effects on a broad range of solid and blood malignancies. The secondary metabolites of the strain were isolated and characterized by a bioactivity-guided isolation strategy. Five new compounds, streptonaphthalenes A and B (1-2), pestaloficins F and G (3-4), and eudesmanetetraiol A (5), together with nine previously known compounds, were isolated from the effective fractions of AD16. Structures of the new compounds were established by 1D and 2D NMR and MS analysis, and the absolute configurations were determined by the CD method. The analysis of network pharmacology suggested that 3, 2, and 13 could be the key components for the anti-NSCLC activity of AD16. In addition to the PI3K-Akt signaling pathway, the proteoglycans in cancer pathway could be involved in the anti-NSCLC action of AD16.
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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) | 0.001 | 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) | 0.001 | 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".