Stereospecific analytical method development and preliminary <i>in vivo</i> pharmacokinetic characterization of pinostrobin in the rat
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
The complete pharmacokinetic disposition of the chiral flavonoid (±) pinostrobin remains unknown without the development of an analytical method of detection and quantitation of its individual enantiomers. Resolution of the enantiomers of pinostrobin was achieved using as simple high-performance liquid chromatographic method. A Chiralpak(®) AD-RH column was employed to perform baseline separation with UV detection at 287 nm. The standard curves were linear ranging from 0.5 to 100 µg/mL for each enantiomer. The limit of quantification was 0.5 µg/mL. Precision and accuracy of the assay was < 15% (RSD) and was with a bias <15% for all points on the calibration curve. The assay was applied successfully to stereoselective serum disposition of pinostrobin enantiomers in rats. Both enantiomers had a serum half-life of ~7 h. They also shared similar values of volume of distribution (V(d) S-pinostrobin, 8.2 L/kg; V(d) R-pinostrobin, 8.9 L/kg), total clearance (S-pinostrobin CL(total), 0.959 L//h/kg; R-pinostrobin CL(total), 1.055 L//h/kg), and area under the curve (S-pinostrobin AUC(inf), 23.16 µg h/mL; R-pinostrobin AUC(inf), 21.296 µg h/mL). The large volume of distribution suggests extensive distribution of pinostrobin into tissues.
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) | 0.000 | 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