Determination of serum aldosterone by liquid chromatography and tandem mass spectrometry: a liquid–liquid extraction method for the ABSCIEX API-5000 mass spectrometry system
Why this work is in the frame
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Bibliographic record
Abstract
AIMS: Accurate serum aldosterone determination is critical to the screening and diagnosis of primary aldosteronism, the localisation of aldosterone producing tumours, and the investigation of other disorders of the renin-angiotensin system. Mass spectrometry offers a means to overcome problems with method-dependent bias between competitive immunoassays for aldosterone. The authors have developed a simple, sensitive and precise liquid-liquid extraction aldosterone method for the ABSCIEX API-5000 liquid chromatography and tandem mass spectrometry (LC-MS/MS) system. METHODS: Using d7-aldosterone internal standard, 500 μl of sample is extracted with 2500 μl of methyl tertbutyl ether followed by dry-down, reconstitution and LC-MS/MS analysis in ESI negative mode. Method validation was undertaken using standard approaches and comparison made against a commercial radioimmunoassay. Accuracy was assessed using EQA material with assigned aldosterone concentrations. RESULTS: The assay was linear up to 3420 pmol/l (LOQ=50 pmol/l, LOD<22 pmol/l). Total CVs were ≤5% for concentrations ≥120 pmol/l and 10% at the LOQ. Mean accuracy was 98.5% against GCMS assigned material. CONCLUSION: The authors present a precise, sensitive and simple aldosterone method suitable for routine clinical use that requires no solid phase extraction or specialised ion sources.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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