Immunostimulant effects of Pituitary Adenylate Cyclase-Activating Polypeptide and double-stranded (ds)RNA in Orconectes propinquus
Bibliographic record
Abstract
Disease outbreaks in crustacean aquaculture caused by opportunistic and obligate pathogens cause severe economic losses to the industry. Antibiotics are frequently used as prophylactic treatments worldwide, although its overuse and misuse has led to microbial resistance, which has driven the search for novel molecules with immunostimulant and antibacterial activities. Antimicrobial peptides (AMP) and double-stranded (ds)RNAs constitute promising immunostimulants in the fight against infectious diseases in aquaculture. Scientists have made significant progress in testing these molecules in aquatic organisms as potential candidates for replacing conventional antibiotics. However, most studies have been conducted in teleost fish, thus little is known about the immunostimulatory effects in crustaceans, especially in freshwater crayfishes. Consequently, in the present work, we evaluate the immunomodulatory effects of the AMP Pituitary Adenylate Cyclase Activating Polypeptide (PACAP) and high molecular weight (HMW) Poly (I:C) in the northern clearwater crayfish Orconectes propinquus. Two bioassays were conducted to evaluate the effects of different doses of PACAP and Poly (I:C) HMW, different administration routes, as well as the effects of the combined treatment on the crayfish immune system. Results showed the immunostimulatory role of PACAP and Poly (I:C) HMW with effects depending on the dose, the site of injection and the treatment assessed. These findings offer new insights into the crayfish immune system and contribute to the development of effective broad-spectrum immune therapies in aquaculture.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".