Supplementation of mixed Lactobacillus alleviates metabolic impairment, inflammation, and dysbiosis of the gut microbiota in an obese mouse model
Bibliographic record
Abstract
Introduction Obesity is a complex metabolic disease, which is often accompanied with impaired glucose and lipid metabolism and chronic inflammation. Probiotics have been considered as a strategy for treating obesity, while the genus of Lactobacillus is the most commonly tested and approved probiotics. Some multi-strain probiotics were proven to produce synergistic effects on treating obesity as compared to mono-strain ones. Methods The purpose of this study was to investigate the anti-obesity effect of a new probiotic formation contained Lactobacillus plantarum L14, Lactobacillus paracasei L9, Lactobacillus rhamnosus GG, and Lactobacillus sakei X-MRS-2, designated as L-PPRS. Multi-strain probiotics L-PPRS was shown to have a better antiadipogenic effect than mono-strain probiotics in 3T3-L1 cell. Subsequently, L-PPRS was orally supplemented to a high-fat diet (HFD) induced obese mouse model for two kinds of treatment course, a short-term (8 weeks) one and a long-term (12 weeks) one. Results We found that intervention of L-PPRS not only significantly inhibited weight gain in HFD-fed mice, but also improved glucose tolerance, insulin sensitivity and reduced serum lipid levels. Furthermore, L-PPRS intervention reduced fat accumulation in the adipose tissue and the liver, and ameliorated the antioxidant capacity of liver in HFD-fed mice. L-PPRS intervention modulated the expression of lipid-metabolic genes, and exhibited excellent anti-inflammatory effect. In addition, L-PPRS intervention restored the dysbiosis of gut microbiota via reducing the Firmicutes/ Bacteroidetes ratio, and increasing the abundance of beneficial intestinal bacteria. In conclusion, this study proved that L-PPRS could effectively prevent the development of obesity and its associated abnormalities, and the long-term supplementation of L-PPRS provided a more profound benefit than the short-term. Discussion This study highlights the potential of L-PPRS as an effective anti-obesity strategy.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".