Kefir microbial composition is a deciding factor in the physiological impact of kefir in a mouse model of obesity
Bibliographic record
Abstract
Kefir consumption has been demonstrated to improve lipid and cholesterol metabolism; however, our previous study identified that benefits vary between different commercial and traditional kefir. Here, we investigate the ability of pitched culture kefir, that is, kefir produced by a small number of specific strains, to recapitulate health benefits of a traditional kefir, in a diet-induced obesity mouse model, and examine how microbial composition of kefir impacts these benefits. Eight-week-old female C57BL/6 mice were fed a high-fat diet (40 % energy from fat) supplemented with one of five kefir varieties (traditional, pitched, pitched with no Lactobacillus, pitched with no yeast and commercial control) at 2 ml in 20 g of food for 8 weeks prior to analysis of plasma and liver lipid profiles, and liver gene expression profiles related to lipid metabolism. Both traditional and pitched kefir lowered plasma cholesterol by about 35 % (P = 0·0005) and liver TAG by about 55 % (P = 0·0001) when compared with commercial kefir despite no difference in body weight. Furthermore, pitched kefir produced without either yeast or Lactobacillus did not lower cholesterol. The traditional and pitched kefir with the full complement of microbes were able to impart corresponding decreases in the expression of the cholesterol and lipid metabolism genes encoding 3-hydroxy-3-methylglutaryl-coenzyme A reductase, PPARγ and CD36 in the liver. These results demonstrate that traditional kefir organisms can successfully be utilised in a commercial process, while highlighting the importance of microbial interactions during fermentation in the ability of fermented foods to benefit host health.
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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) | 0.001 | 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".