Highly Active Probiotic Yogurt Against Cyclophosphamide-Induced Immunosuppression in Mice by Regulating Immune Response and Gut Microbiota
Bibliographic record
Abstract
Abstract Probiotics play a crucial role in modulating the immune system and maintaining the integrity of intestinal epithelial barrier. The study investigates the effects of high-activity probiotic yogurt on immunosuppressed mice induced by cyclophosphamide. On days 7, 8, and 9 of the experiment, ICR male mice (eight-week-old) were injected intraperitoneally with cyclophosphamide (80 mg/kg body weight/day) to establish an immunosuppressive model (n = 10). Mice fed with normal diet or high-activity probiotic yogurt for consecutive 14 days. The effect of high-activity probiotic yogurt on immunosuppressed mice was investigated by HE staining, enzyme-linked immunosorbent assay (ELISA), Western blotting, and 16s rRNA assay. Results indicated that after the treatment of high-activity probiotic yogurt, the immune organ indices, interleukin-6(IL-6), interleukin-12(IL-12), tumor necrosis factor-α (TNF-α), and intestinal structure are significantly increased in immunosuppressed mice (P < 0.05). Western blotting analysis find that high-activity probiotic yogurt improves the expression of toll-like receptor 4 (TLR4), nuclear factor kappa-B –p65(p65), TNF receptor associated factor 6(TRAF6). Furthermore, microbiota analysis showed that high-activity probiotic yogurt significantly increased the diversity and richness of the gut microbiota(P < 0.05). These findings indicated that high-activity probiotic yogurt may improve the immune function of mice by improve intestinal homeostasis and activation of TLR pathway.
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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 | 0.000 | 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".