Effect of Sample Handling on Thiamine and Thiaminolytic Activity in Alewife
Bibliographic record
Abstract
Abstract Alewives Alosa pseudoharengus were collected to evaluate handling and processing conditions that may affect the measurement of their thiamine–thiaminase content. Fish were captured by otter trawl, and reference samples of live fish were quick-frozen on dry ice immediately following capture. Other samples were placed on wet ice (4°C) or held in ambient lake water (21.5°C) for periods of up to 5 h before freezing. Total thiamine levels for reference samples averaged 26 nmol/g and consisted of 66, 15, and 19% thiamine pyrophosphate (TPP), thiamine monophosphate (TMP), and unphosphorylated thiamine (Th), respectively. After 120 min at either 4°C or 21.5°C, total thiamine concentrations were lower. At 21.5°C, the TPP proportion had decreased by 30 min and the proportion as Th increased after 60 min. In the groups sampled after 5 h, total thiamine concentrations were not altered but the proportion of TPP was lower and that of Th was higher than in reference samples. The stability of thiamine in thawed muscle samples from previously frozen alewives was poor (40% loss by 1 h at 22°C and 30% loss by 2 h at 4°C). Thiaminase activity averaged 5,975 pmol·g wet weight−1·min−1 in reference samples. In fresh-caught alewives, thiaminase activities were remarkably consistent throughout the sampling period. At 4°C, thiaminase activity in muscle tissue from previously frozen alewives was stable for the entire investigation period. At 25°C, the activity initially increased by 40% after 60 min but then decreased to 50% of initial value after 5 h. We conclude that sampling times greater than 25 min could cause some changes in the various thiamine forms and net loss in total thiamine. The thiamine content in previously frozen alewife samples is highly labile, requiring low temperatures during processing for analysis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".