Laser Diode Thermal Desorption/Atmospheric Pressure Chemical Ionization Tandem Mass Spectrometry Analysis of Selected Steroid Hormones in Wastewater: Method Optimization and Application
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
A rapid and reliable method enabling high-throughput sample analysis for quicker data generation, detection, and monitoring of eight selected steroid hormones in water matrixes was developed and validated. Our approach is based on a novel sample introduction method, the laser diode thermal desorption/atmospheric pressure chemical ionization (LDTD/APCI) coupled to tandem mass spectrometry (MS/MS). The optimization of instrumental parameters and a method application are presented. Our method was successfully applied to spiked effluent wastewater in the low-nanogram per liter concentrations with total analysis time reduced to seconds (15 s) using LDTD/APCI-MS/MS compared to minutes with traditional liquid-chromatography coupled to tandem mass spectrometry (LC-MS/MS) following solid-phase extraction (SPE). The instrumental detection limits for LDTD/APCI-MS/MS ranged from 5 to 24 microg L(-1) and from 13 to 43 ng L(-1) for the method detection limits. Calibration curves in wastewater matrix showed good linearity (R(2) > 0.99), and precision (intraday and interday) was below 20%. This work demonstrates that LDTD/APCI-MS/MS could be used for fast and effective quantitative analysis of emerging contaminants in different water matrixes with reduced cost by eliminating the chromatography step used in traditional LC-MS/MS.
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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 | 0.002 |
| 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 it