Analysis of 17β‐estradiol, estriol and estrone in American eel ( <scp> <i>Anguilla rostrata</i> </scp> ) tissue samples using liquid chromatography coupled to electrospray differential ion mobility tandem mass spectrometry
Bibliographic record
Abstract
RATIONALE: 17β-Estradiol (E2), estrone (E1) and estriol (E3) are steroid hormones responsible for the regulation of the female reproductive system. Estradiol is planned to be used to feminize eels in aquaculture in order to improve their size and marketability. The residual levels of these hormones in fish tissue must be monitored to meet the requirements of food regulatory agencies. Few studies have studied these hormones in complex biological matrices such as fish tissue. METHODS: We developed a method to analyze E1, E2 and E3 in fish tissue using liquid chromatography in combination with differential ion mobility spectrometry (DMS) and tandem mass spectrometry (MS/MS). The mass spectrometer was operated in negative polarity selected reaction monitoring (SRM) mode. To test the performance of this method, residual levels of E1, E2 and E3 were measured in the muscle tissue of juvenile eels subjected to feminization treatment with E2. RESULTS: We report that following 17β-estradiol treatment, E2 is rapidly metabolized from the eel tissue, with a 50% depletion rate per day. Five days post-treatment, E2 returned to the level found in non-treated controls, similar to levels found in wild mature female eels. CONCLUSIONS: The method presented herein allows the quantitative analysis of E1, E2 and E3 in fish tissue samples. Under the experimental conditions, E2 in fish tissue samples returned to physiological levels post hormonal treatment. Copyright © 2017 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".