Non-Lethal Blood Sampling of Fish in the lab and Field With Methods for Dried Blood Plasma Spot Omic Analyses
Bibliographic record
Abstract
There is global acknowledgment that humane methods in animal research are a priority, but few environmental effects monitoring programs use nonlethal methods for fish. The goal of the present study was to determine the impacts of sampling small volumes of blood in larger-bodied fish on survival and healing. In addition to evaluating survival following blood sampling, we evaluated the utility of dried blood spots as an alternative for sample processing and storage in the field. In our approach, we housed 80 rainbow trout ( Oncorhynchus mykiss ) in our flow-through aquatic facility. We then anaesthetized using MS-222 and sampled 1 μl/g bw of blood via puncture of the caudal vasculature. We tested four different post-blood sampling treatments on the puncture wound: 1. application of liquid bandage; 2. a swab of betadine; 3. a swab of fish mucous; and 4. compared survival outcomes to a group where no post-treatment was performed (negative control). Overall, we observed 90% survival among all treatments, with the most effective approach being the negative control (100% survival). Based upon these results, we repeated the blood sampling with no-post treatment by housing 20 rainbow trout (not previously tested upon) in cages at a nearby creek and monitored survival for 2 weeks post sampling. The survival rate was 95% with full healing of the puncture site in all subjects. In addition to this, we tested the efficacy of dry blood spotting on proteomic, lipidomic and amino acid analysis as an alternative method for blood sample processing and storage. It was found that dried plasma spotting using parafilm in conjunction with a modified Bligh-Dyer extraction offered the best balance for good recovery of protein, lipid and amino acids relative to wet plasma and Noviplex dried plasma spot cards. In this article, we will present the detailed results of these combined studies and describe what we have determined to be the safest non-lethal blood sampling protocol.
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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) | 0.000 | 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) | 0.000 | 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".