Pharmacokinetics of Tinidazole in Chinese subjects: Comparison of Mongolian, Korean, Hui, Uighur and Han nationalities
Bibliographic record
Abstract
PURPOSE: This study investigated the pharmacokinetics of tinidazole in subjects of five different Chinese nationalities (Han, Mongolian, Korean, Hui, and Uighur). METHODS: Fifty healthy subjects (five male and five female of each nationality) were recruited for the study, and each received 1 g tinidazole. A total of 14 blood samples were collected over a 72-hour period after administration. RESULTS: Pharmacokinetic profiles, including area under the curve from time zero to infinity (AUC0-inf), peak plasma concentration (Cmax), time to reach Cmax (tmax), oral clearance (CL/F), elimination rate constant (Ke), and elimination half-life (t1/2), were determined following a single oral dose of tinidazole. The respective pharmacokinetic properties of Han, Mongolian, Korean, Hui, and Uighur nationalities were: half-life (h): 16.94+/-2.40, 16.40+/-1.79, 16.63+/-1.82, 16.81+/-1.56, 14.34+/-1.92; Cmax (microg/mL): 19.04+/-2.42, 19.22+/-4.93, 20.83+/-3.33, 20.25+/-4.05, 18.81+/-3.10; AUC0-inf (h*microg/mL): 483.13+/-65.65, 479.70+/-99.74, 511.07+/-53.47, 514.25+/-130.78, 388.58+/-37.37. The t1/2 and AUC0-inf of Uighur subjects were significantly lower (p =0.023, 0.011) and the CL/F and Ke were significantly higher (p = 0.003, 0.013) than those of other nationalities. After normalization by weight, the differences in AUC0-inf and CL/F between Uigur subjects and those of other races were still significant. CONCLUSIONS: The results indicate that ethnicity had significant impact on the pharmacokinetics of tinidazole after a single oral dose in healthy volunteers of different nationalities in China.
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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 | 0.000 | 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) | 0.001 | 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".