Effects of Three Homogalacturonan-Type Pectins on Mice with Metabolic Syndrome
Bibliographic record
Abstract
Pectin, a class of dietary fiber, has received increasing attention in recent years for its ameliorative effects on metabolic diseases. However, the structural variability of pectin leads to differential effects on these diseases. The intrinsic mechanism by which pectin, derived from different sources, differentially influences metabolic syndrome by interacting with gut microbiota and host metabolism remains elusive and warrants thorough investigation. To address this, we investigated the effects of HG-type pectins from apple, citrus, and pomelo on phenotypic expressions, inflammatory factors, oxidative stress, and serum hormone levels in mice with metabolic syndrome. In addition, we sought to identify pivotal bacterial species and metabolites by integrating genomics and metabolomics approaches. Our exploration also extended to the relationship between structural characteristics of pectins, gut microbiota, and metabolic syndrome. Our findings revealed that the three pectins diversely improved metabolic syndrome in mice, which correlated with gut microbiota and their beneficial metabolites. Notably, all three pectins were closely associated with Bacteroides and Bacteroides acidifaciens . Besides, the potential mediators of the therapeutic effects included Bacteroides, Lactococcus, and Lachnoclostriclum for apple pectin; Colidextribacter, Bacteroides, Lachnospiraceae _NK4A136_group, and Lachnoclostriclum for citrus pectin; and Lachnospiraceae _NK4A136_group, Bacteroides, and Mucispirillum for pomelo pectin. Metabolites such as arachidonic acid, kynurenic acid, lithocholic acid, deoxycholic acid, and indoleacetic acid, linked to these microbes, may serve as the mediators of pectin’s benefits. Ultimately, the molecular weight, degree of esterification, and monosaccharide composition of pectins significantly influenced the outcomes. This study may contribute to a more nuanced understanding that can inform targeted nutritional strategies to modulate gut microbiota for metabolic syndrome management.
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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 | 0.000 | 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 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".