Regulatory Effect of Isomaltodextrin on a High-Fat Diet Mouse Model with LPS-Induced Low-Grade Chronic Inflammation
Bibliographic record
Abstract
This study aimed to identify the effects of isomaltodextrin (IMD) on sustaining the gut integrity and microbiota composition in a high-fat diet (HFD) with a lipopolysaccharide (LPS)-induced low-grade inflammation mouse model. The homeostasis of the immune response is important to reduce the risk of developing metabolic syndromes. The results of this study showed that pre-treatment of IMD at 5% (w/v) suppressed the concentration of endotoxin and pro-inflammatory mediators TNF-α, MCP-1, and IL-6 while increasing the adiponectin level in the plasma. Subsequently, IMD supplementation maintained the structural integrity and intestinal permeability by upregulating the tight junction protein expressions, leading to reducing D-mannitol concentration in the blood. In addition, dysbiosis was observed in mice induced by HFD plus LPS, suggesting that unhealthy dietary factors elicit metabolic endotoxemia and associated dysbiosis to impair the barrier function. However, IMD supplementation was shown to restore the microbial diversity, promote the growth of Bacteroides-Prevotella, and upregulate the related d -glucarate and d -galactarate degradation pathways, together demonstrating the benefits of IMD as a prebiotic able to promote energy homeostasis. Our results also showed that the blood lipid profile and glucose level in the low-grade inflammation mouse model were modulated by IMD. Moreover, IMD supplementation effectively prevented the metabolic disorder and modulated immune responses in inflamed white adipose tissues by inhibiting the macrophage infiltration and restoring the adiponectin, PPAR-γ, and IRS-1 expression. These findings provide strong evidence for IMD to be a potential prebiotic that acts to sustain a healthy gut microbiota composition and barrier function. By protecting against an unhealthy diet-impaired metabolic balance and maintaining immune homeostasis, IMD may affect the development of metabolic disorders.
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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 | 0.000 |
| 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 | 0.000 | 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".