Immunostimulation of <i><scp>S</scp>almo salar</i> L., and its effect on <i><scp>L</scp>epeophtheirus salmonis</i> (Krøyer) <scp>P</scp>‐glycoprotein <scp>mRNA</scp> expression following subsequent emamectin benzoate exposure
Bibliographic record
Abstract
Control of sea lice, Lepeophtheirus salmonis, on farmed Atlantic salmon, Salmo salar, relies heavily on chemotherapeutants. However, reduced efficacy of many treatments and need for integrated sea lice management plans require innovative strategies. Resistance to emamectin benzoate (EMB), a major sea lice parasiticide, has been linked with P-glycoprotein (P-gp) expression. We hypothesized that host immunostimulation would complement EMB treatment outcome. Lepeophtheirus salmonis-infected Atlantic salmon were fed immunostimulatory or control feeds. Sea lice were collected for 24-h EMB bioassays 1 and 2 weeks prior to commencement of EMB treatment of the fish. Two weeks after cessation of immunostimulant-treated feed, EMB was administered at 150 μg kg(-1) fish biomass for 7 days. The bioassay revealed stage, gender and immunostimulant-related differences in EMB EC(50) . Sea lice attached to salmon with a history of immunostimulation exhibited significantly greater survival than those on control feeds, despite similar levels of EMB in host tissues. Lepeophtheirus salmonis from salmon with a history of immunostimulation also exhibited higher P-gp mRNA expression as well as greater survivability compared to controls. Administration of immunostimulants prior to EMB treatment caused increased expression of P-gp mRNA which could have consequently caused decreased efficacy of the parasiticide.
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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".