Bicyclol attenuates tetracycline-induced fatty liver associated with inhibition of hepatic ER stress and apoptosis in mice
Bibliographic record
Abstract
Endoplasmic reticulum (ER) stress is known to be involved in the development of several metabolic disorders, including non-alcoholic fatty liver disease (NAFLD). Tetracycline can cause hepatic steatosis, and ER stress may be involved in tetracycline-induced fatty liver. Our previous study showed that bicyclol has been proven to protect against tetracycline-induced fatty liver in mice, and ER stress may also be involved in bicyclol's hepatoprotective effect. Therefore, this study was performed to investigate the underlying mechanisms associated with ER stress and apoptosis, by which bicyclol attenuated tetracycline-induced fatty liver in mice. Bicyclol (300 mg/kg) was given to mice by gavage 3 times. Tetracycline (200 mg/kg, intraperitoneally) was injected at 1 h after the last dose of bicyclol. At 6 h and 24 h after single dose of tetracycline injection, serum ALT, AST, TG, CHO and hepatic histopathological examinations were performed to evaluate liver injuries. Hepatic steatosis was assessed by the accumulation of hepatic TG and CHO. Moreover, hepatic apoptosis and ER stress related markers were determined by TUNEL, real-time PCR, and western blot. As a result, bicyclol significantly protected against tetracycline-induced fatty liver as evidenced by the decrease of elevated serum transaminases and hepatic triglyceride, and the attenuation of histopathological changes in mice. In addition, bicyclol remarkably alleviated hepatic apoptosis and the gene expression of caspase-3, and increased the gene expression of XIAP. The gene expressions of ER stress-related markers, including CHOP, GRP78, IRE-1α, and ATF6, which were downregulated by bicyclol pretreatment in tetracycline-injected mice. These results suggested that bicyclol protected tetracycline-induced fatty liver partly due to its ability of anti-apoptosis associated with ER stress.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".