Pharmacokinetics of Oral Rosiglitazone in Taiwanese and Post Hoc Comparisons with Caucasian, Japanese, Korean, and Mainland Chinese Subjects
Bibliographic record
Abstract
PURPOSE: Rosiglitazone, an insulin-sensitizing thiazolidinedione, acts as a ligand for the y-subtype of the peroxisome proliferator-activated receptor in the regulation of glucose homeostasis and lipid metabolism. The aims of this study were to determine the pharmacokinetics of oral rosiglitazone in Taiwanese and to post hoc compare the ethnic differences among Caucasian, Japanese, Korean, and Mainland Chinese. METHODS: Twelve Taiwanese healthy male subjects received 4 and 8 mg of rosiglitazone. Similar protocols were used in the previously unpublished studies conducted in 25 Caucasian, 32 Japanese, 8 Korean, and 12 Mainland Chinese healthy male subjects. The 4 mg dose data were used for ethnicity comparisons. RESULTS: The respective pharmacokinetic properties of Taiwanese, Caucasian, Japanese, Korean and Mainland Chinese are: terminal half-life (hr): 4.18 +/- 0.43, 3.96 +/- 1.31, 3.83 +/- 0.78, 4.70 +/- 1.19 and 4.37 +/- 0.63; Cmax (ng/ml): 384.1 +/- 59.3, 260.2 +/- 75.7, 401.9 +/- 102.3, 345.3 +/- 60.6, and 406.2 +/- 52.0; AUC0-inf (h*ng/ml): 2078 +/- 433, 1249 +/- 566, 1901 +/- 397, 1938 +/- 534, and 2158 +/- 498. The Cmax and AUC0-inf of Caucasian were significantly (p = 0.002, 0.008) lower and CL/F and V/F were significantly (p = 0.000, 0.003) higher than those of other races. These differences of Cmax, AUC0-inf, CL/F and V/F between Caucasian and other races became insignificant after normalized by dose and weight. CONCLUSIONS: In a given dose by body weight, ethnicity had no significant impact on the pharmacokinetics of rosiglitazone in normal healthy volunteers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".