Modulation of Zebrafish (Danio rerio) Intestinal Mucosal Barrier Function Fed Different Postbiotics and a Probiotic from Lactobacilli
Bibliographic record
Abstract
It is generally accepted that microbes play a critical role in maintaining gut barrier function, making them ideal to target in order to mitigate the effects of intestinal diseases such as inflammatory bowel disease with specialist supplementations such as probiotic or postbiotic preparations. In this study, specific strains of Lactobacillus helvictus both live and inactivated and Lactobacillus plantarum inactivated were fed to zebrafish at an inclusion level of 6 × 106 cells/g in order to assess the effects on gut barrier function and protection. Taken together, our results indicate that dietary administration of pro- or postbiotics strengthens the gut barrier function and innate immunity of healthy zebrafish in a strain-specific and process-dependent way. With some differences in the response intensity, the three treatments led to increased intestinal villi length and proportion of IELs, reinforcement of the GC population and up-regulated expression of biomarkers of AMP production and tight junction zona-occludin 2a (zo-2a). In addition, LPPost had an impact on the adaptive immune response, and we hypothesized that it conferred the potential to drive Th17/ILC3 immunity, as suggested by its effect on the gene expression of il22, of different AMPs, and the expression of zo2a. Moreover, LPPost showed the potential to drive Th1/ILC1-like immunity, with a higher percentage of CD8+ cells and higher ifnγ gene expression. In summary, the use of inactivated Lactobacilli species in this study represented a promising strategy for improving barrier function and regulating the immune fate of the intestinal mucosa in a strain-specific way.
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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".