An analog of Clarias gariepinus Pituitary Adenylate Cyclase-Activating Polypeptide (PACAP-38) contributes to immune homeostasis and defences against Vibrio parahaemolyticus in Litopenaeus vannamei
Bibliographic record
Abstract
Disease outbreaks in aquaculture are a major challenge, often leading to the widespread use of antibiotics for prevention and treatment. However, excessive and improper antibiotic use leads to antimicrobial resistance, posing risks to both aquatic species and human health. Therefore, researchers are looking into new alternatives such as antimicrobial peptides. Pituitary adenylate cyclase-activating polypeptide (PACAP), a neuropeptide with antimicrobial and immunomodulatory properties, has shown potential applications in fish and shellfish aquaculture. Nevertheless, few studies have been conducted to date in shellfish species. Given the importance of crustacean aquaculture, the current study aimed to assess the effect of synthetic Clarias gariepinus PACAP-38 and a PACAP modified sequence in shrimp L. vannamei during a Vibrio parahaemolyticus infection. Shrimp were treated for one week with four injections of each peptide administrated every 48 h. After the last treatment, animals were inoculated with a sublethal dose of V. parahaemolyticus, and samples were collected at 0-, 20-, and 68-h post-inoculation. The immunological status of the shrimp was assessed by measuring hemolymph immunological indicators and RT-qPCR. The results suggest that the modified form of PACAP exhibited an immunomodulatory effect, mostly maintaining stable levels of immune parameters throughout the challenge, unlike the native PACAP-38 and control groups, which exhibited more fluctuating responses. This modified variant of PACAP also demonstrated a strong antibacterial effect against V. parahaemolyticus. Overall, our findings provide more insights regarding the role of PACAP in crustacean immunology and its potential use as an alternative to antibiotics 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".