54 Evaluating the effectiveness of Lactobacillus zeae against enterotoxigenic Escherichia coli F4 infection in a porcine intestinal epithelial cell model
Bibliographic record
Abstract
Abstract Lactobacillus zeae (LB1) has been shown to prevent Caenorhabditis elegans from death caused by enterotoxigenic Escherichia coli (ETEC) infection through downregulating the gene expression of ETEC toxins and mediating antimicrobial peptides/defense molecules under the p38 MAPK and DAF/IGF signaling pathways in the nematode. However, the protective effects of LB1 at a cellular level have not been investigated yet. In the present study, porcine intestinal cells (IPEC-J2) were used to examine the potential of LB1 on modulating intestinal barrier and innate immune functions and protecting against intestinal injuries and inflammatory reactions induced by ETEC F4 infection. The results showed that the pretreatment of IPEC-J2 cells with LB1 significantly alleviated the cytotoxicity and inhibited gene expression of interleukin (IL)-8 and IL-6, and secretion of IL-8 induced by ETEC F4 (P < 0.05). The LB1 pretreatment significantly maintained a higher value of TEER concomitantly with lower dextran-fluorescein fluxes from the apical side to the basolateral side when compared with that challenged by ETEC F4. LB1 pretreatment also prevented morphological damage of tight junction and cytoskeleton caused by the ETEC F4 challenge, indicating that LB1 pretreatment maintained the structural integrity of tight junction. However, LB1 inclusion showed no significant protection on ZO-1 expression at both gene and protein levels from the ETEC F4 challenge, but a considerable increase in the protein expression of occludin (P < 0.05). LB1 administration influenced neither ETEC F4 adhesion nor secretion of antimicrobial defensin (pBD2, pBD3), while dramatically reduced the mRNA level of toll-like receptor 4 (TLR4). These results suggested that probiotics LB1 could effectively protect the mucosa from ETEC F4 infection by inhibiting inflammation and maintaining barrier integrity via downregulating TLR4 expression. Our data provide further evidence on the mechanisms at the cellular level that probiotics could improve pig gut health.
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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) | 0.000 | 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".