Ameliorative Effects of Probiotic <i>Lactobacillus paracasei</i> NL41 on Insulin Sensitivity, Oxidative Stress, and Beta‐Cell Function in a Type 2 Diabetes Mellitus Rat Model
Bibliographic record
Abstract
SCOPE: The present study aims to assess the antidiabetic effect of Lactobacillus paracasei strain NL41 and its potential mechanisms in rats with type 2 diabetes mellitus (T2DM) induced by a high-fat diet and low-dose streptozotocin administration (HFD/STZ). METHODS AND RESULTS: Eighteen Sprague-Dawley (SD) rats are randomly assigned to three groups: one control, one HFD/STZ model, and one HFD/STZ-Lactobacillus protection group with administration of strain NL41 for 12 weeks. Blood is collected for biochemical parameters analysis and tissue samples for histological analysis. Treatment with strain NL41 results in excellent blood glucose regulation and significantly decreases insulin resistance, and HbA1c, glucagon, and leptin levels, accompanied by remarkable improvement of dyslipidemia and oxidative stress status in the animals. Islets of Langerhans, liver, and kidney are significantly protected in the NL41-treated rats compared to the HFD/STZ-T2DM model rats. Histochemistry shows that strain NL41 inhibits beta-cell loss and alpha-cell expansion, indicating pancreatic islets as the targeted tissues for the primary ameliorative effect of the probiotic strain on HFD/STZ-T2DM rats. Crosstalk between the gut-liver and liver-pancreas endocrine axes is discussed. CONCLUSION: Probiotic strain NL41 prevents HFD/STZ-T2DM by decreasing insulin resistance and oxidative stress status, and protecting beta-cell function.
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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) | 0.000 | 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 | 0.001 |
| 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".