Antibiotic Body Burden of Chinese School Children: A Multisite Biomonitoring-based Study
Bibliographic record
Abstract
To explore the antibiotic body burden of Chinese school children, total urinary concentrations (free and conjugated) of 18 representative antibiotics (5 macrolides, 2 β-lactams, 3 tetracyclines, 4 quinolones, and 4 sulfonamides) were measured by ultraperformance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry among 1064 school students recruited from 3 economically and geographically distinct areas in east China in 2013. All 18 antibiotics were detected in urine samples with the detection frequencies ranging from 0.4 to 19.6%. The antibiotics were detected in 58.3% of urine samples overall, and this detection frequency reached at 74.4% in one study site. Of them, 47.8% of the urine samples had a sum of mass concentration of all antibiotics between 0.1 (minimum) and 20.0 ng/mL, and 8 antibiotics had their concentrations of above 1000 ng/mL in some urine samples. Three veterinary antibiotics, 4 human antibiotics, and 11 human/veterinary antibiotics were found overall in 6.3, 19.9, and 49.4% of urine samples, respectively. The detection frequencies and concentration levels of antibiotics in urine samples differed by study areas. Concerning mixed exposures, a total of 137 combinations of antibiotics and 20 combinations of antibiotic categories were found overall. Two or more antibiotics or categories were concurrently detected in more than 20% of urine samples. On the basis of a usage analysis, contaminated food or environment might be relevant exposure sources for tetracyclines, quinolones, and sulfonamides.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".