Effectiveness of Egg Immersion in Aqueous Solutions of Thiamine and Thiamine Analogs for Reducing Early Mortality Syndrome
Bibliographic record
Abstract
Abstract Protocols used for therapeutic thiamine treatments in salmonine early mortality syndrome (EMS) were investigated in lake trout Salvelinus namaycush and coho salmon Oncorhynchus kisutch to assess their efficacy. At least 500 mg of thiamine HCl/L added to egg baths was required to produce a sustained elevation of thiamine content in lake trout eggs. Thiamine uptake from egg baths was not influenced by a pH ranging from 5.5 to 7.5 or by a water hardness between 2 and 200 mg CaCO3/L. There was poorer thiamine uptake when initial thiamine levels were low, suggesting that current treatment regimes may not be as effective when thiamine levels are severely depressed and that higher treatment doses are necessary. Exposure of eggs to the more lipid-soluble thiamine analog allithiamine (1,000 mg/L) during water hardening increased egg thiamine levels by 1.5–2.5 nmol/g and was completely effective at reversing EMS. Another more lipid-soluble thiamine analog, benfotiamine (100 mg/L), reduced EMS but did not produce detectable increases in egg thiamine content. Although benfotiamine may be more effective than thiamine at mitigating EMS, it is more expensive than thiamine HCl or allithiamine. In addition, there still needs to be a more thorough examination of dose–response relationships. We conclude that allithiamine is an alternative to the use of thiamine in egg baths as a therapeutic treatment for salmonid EMS.
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".