Metabolic Alterations in Shrimp Stomach During Acute Hepatopancreatic Necrosis Disease and Effects of Taurocholate on Vibrio parahaemolyticus
Bibliographic record
Abstract
Acute hepatopancreatic necrosis disease (AHPND), a recently emerged bacterial shrimp disease, has increased shrimp mortality and caused huge economic losses in many Asian countries. However, molecular factors underlying pathogenesis of this disease remain largely unknown. Our objective was to characterize metabolic alterations in shrimp stomach during AHPND and determine effects of taurocholate on AHPND-causing Vibrio parahaemolyticus. Based on metabolomics, pathways for lipid metabolism and for primary bile acid (BA) synthesis were majorly affected following AHPND infection. Bile acid metabolites, namely taurocholate, were downregulated in the metabolomics database. This prompted us to study effects of taurocholate on biofilm formation, PirABvp toxin release and biofilm detachment capabilities in AHPND-causing V. parahaemolyticus. Treatment of this bacterium with high concentration of taurocholate, a primary bile acid, induced biofilm formation, PirABvp toxin release and facilitated the dispersion of bacterial cells. Taken together, our findings suggest that AHPND infection can affect the lipid metabolites in shrimp stomach, and further suggest that the primary bile acid taurocholate is important for the virulence of AHPND-causing V. parahaemolyticus.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".