The effect of diet-derived thiaminase on survival, growth, and liver transketolase activity in two strains of lake trout (Salvelinus namaycush)
Bibliographic record
Abstract
The consumption of invasive, high-thiaminase prey fishes can cause thiamine deficiency, which has been hypothesized to be a major barrier for lake trout ( Salvelinus namaycush ) restoration in the Laurentian Great Lakes. Here, we compared the effects of diet-derived thiaminase on survival and performance-related traits between two strains of lake trout that differ in historical exposure to thiaminase. Juvenile lake trout from the Seneca Lake (higher historical exposure to thiaminase) and Slate Islands (lower historical exposure) strains were reared in a common garden environment and received either an experimental diet containing bacterial derived-thiaminase or a control diet. Six months after the initiation of the experimental diets, survival, liver transketolase activity, growth, and food conversion efficiency were compared between strains and treatments. Unexpectedly, both diets resulted in liver transketolase latency values that were consistent with thiamine deficiency, and this was true for both strains. The thiaminase diet had larger negative effects on growth, food conversion efficiency, and survival compared to the control diet, and, except for survival, these effects did not differ between the two strains. Fish from the Seneca Lake strain had lower survival when fed the thiaminase diet than when fed the control diet; no difference in survival was found between diets fed to the Slate Islands fish, which was unexpected given their lower historical exposure to thiaminase. Our results confirm the negative effects of thiaminase in lake trout and identify potential strategies that could mitigate effects via strain selection.
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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".