<i>Lactobacillus pentosus</i> S-PT84 Prevents Low-Grade Chronic Inflammation-Associated Metabolic Disorders in a Lipopolysaccharide and High-Fat Diet C57/BL6J Mouse Model
Bibliographic record
Abstract
A long-term exposure to lipopolysaccharides results in the gut inflammation and its impaired barrier function, leading to the development of metabolic disorders. In this study, the role of dietary heat killed Lactobacillus pentosus S-PT84 on preventing endotoxemia to maintain metabolic homeostasis was studied. We demonstrated that the treatment of L. pentosus S-PT84 improved the gut integrity by maintaining tight-junction protein expression, in order to suppress the infiltration of endotoxin into plasma. The systemic inflammatory responses were inhibited via reducing the secretion of TNF-α and MCP-1. Furthermore, the blood lipid profile and glucose level as well as adiponectin in both plasma and white adipose tissues (WAT) were preserved by L. pentosus S-PT84 through upregulation of PPAR-γ and IRS-1 expression in WAT. The above findings suggest that the metabolic homeostasis in mice treated with HFD and LPS was sustained by L. pentosus S-PT84, leading to reducing the early risk for progression into 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 | 0.001 |
| 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".