A liquid chromatography–mass spectrometric method for the quantification of azithromycin in human plasma
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 liquid chromatographic mass spectrometric assay for the quantification of azithromycin in human plasma was developed. Azithromycin and imipramine (as internal standard, IS) were extracted from 0.5 mL human plasma using extraction with diethyl ether under alkaline conditions. Chromatographic separation of drug and IS was performed using a C18 column at room temperature. A mobile phase consisting of methanol, water, ammonium hydroxide and ammonium acetate was pumped at 0.2 mL/min. The mass spectrometer was operated in positive ion mode and selected ion recording acquisition mode. The ions utilized for quantification of azithromycin and IS were m/z 749.6 (M + H)(+) and m/z 591.4 (fragment) for azithromycin, and 281.1 m/z for internal standard; retention times were 6.9 and 3.4 min, respectively. The calibration curves were linear (r(2) > 0.999) in the concentration ranges of 10-1000 ng/mL. The mean absolute recoveries for 50 and 500 ng/mL azithromycin and 1 µg/ mL IS were >75%. The percentage coefficient of variation and mean error were <11%. Based on validation data, the lower limit of quantification was 10 ng/mL. The present method was successfully applied to determine azithromycin pharmacokinetic parameters in two obese volunteers. The assay had applicability for use in pharmacokinetic studies.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| 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