Analysis of steroid hormones and their conjugated forms in water and urine by on-line solid-phase extraction coupled to liquid chromatography tandem mass spectrometry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: In recent years, endocrine disrupting compounds (EDCs) have been found in rivers that receive significant inputs of wastewater. Among EDCs, natural and synthetic steroid hormones are recognized for their potential to mimic or interfere with normal hormonal functions (development, growth and reproduction), even at ultratrace levels (ng L(-1)). Although conjugated hormones are less active than free hormones, they can be cleaved and release the unconjugated estrogens through microbial processes before or during the treatment of wastewater. Due to the need to identify and quantify these compounds, a new fully automated method was developed for the simultaneous determination of the two forms of several steroid hormones (free and conjugated) in different water matrixes and in urine. RESULTS: The method is based on online solid phase extraction coupled with liquid chromatography and tandem mass spectrometry (SPE-LC-MS/MS). Several parameters were assessed in order to optimize the efficiency of the method, such as the type and flow rate of the mobile phase, the various SPE columns, chromatography as well as different sources and ionization modes for MS. The method demonstrated good linearity (R(2) > 0.993) and precision with a coefficient of variance of less than 10 %. The quantification limits vary from a minimum of 3-15 ng L(-1) for an injection volume of 1 and 5 mL, respectively, with the recovery values of the compounds varying from 72 to 117 %. CONCLUSION: The suggested method has been validated and successfully applied for the simultaneous analysis of several steroid hormones in different water matrixes and in urine.
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.
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) | 0.001 | 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 it