Lactobacillus fermentum CECT5716 ameliorates high fat diet-induced obesity in mice through modulation of gut microbiota dysbiosis
Bibliographic record
Abstract
Background and Purpose: Obesity is a complex condition where a low-grade chronic inflammation and gut dysbiosis contribute to the development of the related metabolic dysfunctions. Nowadays, its management of such disease implies drastic changes in lifestyle and different anti-obesity drugs. Unfortunately, most of them present limited effectiveness and important side effects. Therefore there is an urgent demand for more effective and safer strategies for obesity management. In this sense, probiotics are emerging as a promising therapy. Different probiotics have demonstrated beneficial effects on this condition, increasing the interest in the development of probiotic treatments. Lactobacillus fermentum CECT5716 has shown anti-inflammatory effects and capacity to modulate microbiota composition in different experimental models. Experimental Approach: L. fermentum CECT5716 (5x10 8 CFU/mice/day) was evaluated in a model of high fat diet-induced obesity in mice. Key results: L. fermentum exerts anti-obesity effects, associated with its anti-inflammatory properties and amelioration endothelial dysfunction and gut dysbiosis. The probiotic restores Akkermansia sp. abundance and reduced Erysipelotrichi class and Clostridium spp presence as well as increased Bacteroides proportion. Conclusion and Implications: This probiotic represents a very interesting approach. Our findings describe, for the first time, the ability of this probiotic to ameliorate experimental obesity through microbiome modulation, affecting different bacteria that have been reported to play a key role in the pathogenesis of obesity. Therefore, this suggests a potential use of L. fermentum CECT5716 in clinical practice, also taking into account that probiotic treatments have demonstrated to be relatively safe and well tolerated.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".