Multifunctional carbonized nanogels to treat lethal acute hepatopancreatic necrosis disease
Bibliographic record
Abstract
BACKGROUND: Shrimp aquaculture has suffered huge economic losses over the past decade due to the outbreak of acute hepatopancreatic necrosis disease (AHPND), which is mainly caused by the bacteria Vibrio parahaemolyticus (V. parahaemolyticus) with the virulence pVA1 plasmid, which encodes a secretory photorhabdus insect-related (Pir) toxin composed of PirA and PirB proteins. The Pir toxin mainly attacks the hepatopancreas, a major metabolic organ in shrimp, thereby causing necrosis and loss of function. The pandemic of antibiotic-resistant strains makes the impact worse. METHODS: Mild pyrolysis of a mixture of polysaccharide dextran 70 and the crosslinker 1,8-diaminooctane at 180 ℃ for 3 h to form carbonized nanogels (DAO/DEX-CNGs) through controlled cross-linking and carbonization. The multifunctional therapeutic CNGs inherit nanogel-like structures and functional groups from their precursor molecules. RESULTS: DAO/DEX-CNGs manifest broad-spectrum antibacterial activity against Vibrio parahaemolyticus responsible for AHPND and even multiple drug-resistant strains. The polymer-like structures and functional groups on graphitic-carbon within the CNGs exhibit multiple treatment effects, including disruption of bacterial membranes, elevating bacterial oxidative stress, and neutralization of PirAB toxins. The inhibition of Vibrio in the midgut of infected shrimp, protection of hepatopancreas tissue from Pir toxin, and suppressing overstimulation of the immune system in severe V. parahaemolyticus infection, revealing that CNGs can effectively guard shrimp from Vibrio invasion. Moreover, shrimps fed with DAO/DEX-CNGs were carefully examined, such as the expression of the immune-related genes, hepatopancreas biopsy, and intestinal microbiota. Few adverse effects on shrimps were observed. CONCLUSION: Our work proposes brand-new applications of multifunctional carbon-based nanomaterials as efficient anti-Vibrio agents in the aquatic industry that hold great potential as feed additives to reduce antibiotic overuse in aquaculture.
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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 | 0.000 |
| 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".