Anti-Inflammatory Activity of Isomaltodextrin in a C57BL/6NCrl Mouse Model with Lipopolysaccharide-Induced Low-Grade Chronic Inflammation
Bibliographic record
Abstract
The purpose of this study was to identify the anti-inflammatory activity and mechanism of isomaltodextrin (IMD) in a C57BL/6NCrl mouse model with lipopolysaccharide (LPS)-induced systemic low-grade chronic inflammation and the effect on inflammation-induced potential risk of metabolic disorders. Pre-treatment of IMD decreased the production of pro-inflammatory mediators, TNF-α and MCP-1, and stimulated the production of the anti-inflammatory mediator, adiponectin by increasing the protein expression of peroxisome proliferator-activated receptor gamma (PPAR-γ) in the white adipose tissues. IMD administration reduced plasma concentrations of endotoxin, decreased macrophage infiltration into adipocytes, and increased expression of mucin 2, mucin 4, and the tight junction protein claudin 4. These results suggest that IMD administration exerted an anti-inflammatory effect on mice with LPS-induced inflammation, potentially by decreasing circulating endotoxin, suppressing pro-inflammatory mediators and macrophage infiltration, or by improving mucus or tight junction integrity. IMD exerted protein expression of insulin receptor subset-1 (IRS-1). IMD alleviated the disturbance of gut microflora in LPS-treated mice, as the number of B. bifidum, L. casei, and B. fragilis increased, and E. coli and C. difficile decreased, when compared to LPS-treated mice. The analysis of short chain fatty acids (SCFAs) further supported that the concentrations of acetic and butyric acids were positively correlated with IMD, as well as the number of beneficial bacteria. This study provides evidence that IMD possesses anti-inflammatory properties and exerts beneficial functions to prevent systemic low-grade chronic inflammation and reduces the risk of developing insulin resistance and associated metabolic diseases.
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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".