Development of protein level cytokine assays and assessment of the impact of implanted Acoustic Telemetry Tags on the Rainbow Trout (Oncorhynchus mykiss) immune system
Bibliographic record
Abstract
Telemetry tags are a widely used technology for tracking animals that are difficult to observe in their natural environment. This technology has been increasingly used to monitor and study populations of high value salmonid species in Canadian waters. This study examined the heretofore unexplored impacts of tag implantation on the immune system of Rainbow Trout (Oncorhynchus mykiss). Pro-inflammatory cytokines and protein level markers were examined in fish that underwent peritoneal implantation of three tag types as well as a sham surgery control group. The different coating on the tags showed differential immune induction extending over a two-month period. This included peritoneal total protein, IL-1protein, IgT and IgM, as well as pro-inflammatory transcripts in the spleen. These results are suggestive of a prolonged, costly foreign body response which may be differentially induced by the different types of tag coating. \nAt day 2 all tagged fish showed less peritoneal IgM and more peritoneal total protein than sham controls. This could indicate the onset of the foreign body response to tag presence. IFN, an important immunomodulator was quantified at both the transcript and protein level using a newly developed quantitative ELISA assay. Results suggest that a prolonged foreign body response occurred as a result of tag implantation. We also observed some differences associated with the type of tag coating. Additionally, efforts to develop an ELISPOT assay during this study uncovered a previously unreported serum borne, endogenous alkaline phosphatase enzyme. It is demonstrated that very precise quantification of this potential biomarker is possible with low effort and cost. Thus it may represent a useful metric for the assessment of fish health and vaccine efficacy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".