Urinary Antibiotics and Bile Acid Homeostasis in Chinese Adults
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
Bile acid homeostasis plays a key role in human health. Environmental exposure to antibiotics may influence bile acid homeostasis, but relevant data remain limited in human. We investigated 4247 adults in Shanghai, East China, and measured 31 antibiotics (six human antibiotics (HAs), 10 veterinary antibiotics (VAs), and 15 human/veterinary antibiotics (H/VAs)) and 10 typical bile acids transformed or untransformed microbially (chenodeoxycholic acid, cholic acid, lithocholic acid, ursodeoxycholic acid, and deoxycholic acid, and their respective species conjugated with glycine) in morning fasting urine. Eight concentration ratios of transformed to untransformed bile acids were constructed to indicate the microbial transformations of the bile acids. HAs, VAs, and H/VAs were, respectively, detected in 10.0%, 28.3%, and 58.1% urine samples with the 99th percentiles of creatinine-adjusted concentrations being 2.6 × 10 2 ug/g, 7.5 ug/g, and 3.2 × 10 2 ug/g, respectively. Multiple linear regression analysis showed that creatinine-adjusted concentrations of HAs, VAs, and H/VAs as well as eight typical antibiotics, including chlortetracycline, enrofloxacin, ciprofloxacin, ofloxacin, azithromycin, trimethoprim, chloramphenicol, and florfenicol, were associated with bile acids or decreased bile acid ratios. Environmental exposure to antibiotics was likely to disturb bile acid homeostasis in adults by affecting the microbial transformations of the bile acids.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| 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