Effect of Bacillus subtilis on Aeromonas hydrophila-induced intestinal mucosal barrier function damage and inflammation in grass carp (Ctenopharyngodon idella)
Bibliographic record
Abstract
Abstract Our study explored the effect of oral intubation of Bacillus subtilis on Aeromonas hydrophila -induced intestinal mucosal barrier function damage and inflammation in grass carp. The mid-intestine mucosal tissue was collected for ATPase activity measurement. Intestinal mucosa was also ultrastructurally examined with transmission electron microscope (TEM), and its permeability was determined using Evans blue (EB) and D-lactic acid. The mid-intestine pro-inflammation cytokine, MyD88 and tight junction (TJ) protein mRNA expression levels were measured using real-time quantitative PCR. The results revealed that B. subtilis was found to prevent the decrease in the activity of Na + , K + -ATPase and Ca 2+ , Mg 2+ -ATPase, as well as the increase in EB and D-lactic acid concentration and inflammation induced by A. hydrophila in grass carp. Compared with A. hydrophila groups, B. subtilis safeguarded the integrity of intestinal villi and tight junction structure and restrained A. hydrophila -induced down-regulation of TJ proteins zonula occludens-1 (ZO-1) and occludin. B. subtilis also restrained up-regulation of TJ protein claudin b, pro-inflammation cytokine tumour necrosis factor α (TNF-α), cytokine interleukin 8 (IL-8), IL-1β, and adaptor protein myeloid differentiation factor 88 (MyD88) mRNA levels. Thus, oral intubation of B. subtilis could reduce A. hydrophila -induced intestinal mucosal barrier function damage and inflammation.
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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) | 0.000 | 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".