Gut Microbial Signatures of Distinct Trimethylamine N-Oxide Response to Raspberry Consumption
Bibliographic record
Abstract
The aim of this exploratory study was to evaluate the gut microbial signatures of distinct trimethylamine N-oxide (TMAO) responses following raspberry consumption. Investigations were carried out in 24 subjects at risk of developing metabolic syndrome who received 280 g/day of frozen raspberries for 8 weeks. Blood and stool samples were collected at weeks 0 and 8. Inter-individual variability in plasma TMAO levels was analyzed, 7 subjects were excluded due to noninformative signals and 17 subjects were kept for analysis and further stratified according to their TMAO response. Whole-metagenome shotgun sequencing analysis was used to determine the impact of raspberry consumption on gut microbial composition. Before the intervention, the relative abundance of Actinobacteriota was significantly higher in participants whose TMAO levels increased after the intervention (p = 0.03). The delta TMAO (absolute differences of baseline and week 8 levels) was positively associated with the abundance of gut bacteria such as Bilophila wadsworthia (p = 0.02; r2 = 0.37), from the genus Granulicatella (p = 0.03; r2 = 0.48) or the Erysipelotrichia class (p = 0.03; r2 = 0.45). Changes in the gut microbial ecology induced by raspberry consumption over an 8-week period presumably impacted quaternary amines-utilizing activity and thus plasma TMAO levels.
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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) | 0.000 | 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) | 0.001 | 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".