Increasing levels of Parasutterella in the gut microbiome correlate with improving low-density lipoprotein levels in healthy adults consuming resistant potato starch during a randomised trial
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Prebiotics, defined as a substrate that is selectively utilized by host microorganisms conferring a health benefit, present a potential option to optimize gut microbiome health. Elucidating the relationship between specific intestinal bacteria, prebiotic intake, and the health of the host remains a primary microbiome research goal. OBJECTIVE: To assess the correlations between gut microbiota, serum health parameters, and prebiotic consumption in healthy adults. METHODS: We performed ad hoc exploratory analysis of changes in abundance of genera in the gut microbiome of 75 participants from a randomized, placebo-controlled clinical trial that evaluated the effects of resistant potato starch (RPS; MSPrebiotic®, N = 38) intervention versus a fully digestible placebo (N = 37) for which primary and secondary outcomes have previously been published. Pearson correlation analysis was used to identify relationships between health parameters (ie. blood glucose and lipids) and populations of gut bacteria. RESULTS: Abundance of Parasutterella (phylum Proteobacteria) tended to increase in the gut microbiome of individuals consuming RPS and those increases in Parasutterella were correlated with reductions in low-density lipoprotein (LDL) levels in participants consuming RPS but not placebo. Segregating RPS-consuming individuals whose LDL levels decreased (ie "Responders") from those who did not (ie. "Non-Responders") revealed that LDL Responders had significantly higher levels of Parasutterella both at baseline and after 12 weeks of consuming RPS. CONCLUSION: Our analyses suggest that RPS may help improve LDL levels depending upon the levels of Parasutterella in an individual's gut microbiome. TRIAL REGISTRATION: This study protocol was reviewed and approved by Health Canada (Submission #188517; "Notice of Authorization" dated 06/05/13) and registered as NCT01977183 (10/11/13) listed on NIH website: ClinicalTrials.gov. Data generated in this study have been submitted to NCBI ( http://www.ncbi.nlm.nih.gov/bioproject/381931 ). FUNDING: MSP Starch Products Inc.
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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 | 0.001 | 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 | 0.000 |
| 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