STAT3 is involved in IL-6-Mediated Downregulation of Hepatic Transporters in Mice
Bibliographic record
Abstract
Interleukin (IL)-6 decreases hepatic expression of numerous transporters. Although IL-6 signaling occurs through STAT3, the extent of the involvement of the STAT3 signaling pathway has not been elucidated. PURPOSE: Our objective was to investigate whether IL-6-mediated effects occur through STAT3, and whether PXR plays a role in this regulation. METHOD: PXR null (-/-) or wild-type (+/+) male mice were pre-dosed with a selective STAT3 inhibitor S3I-201 (7.5 mg/kg ip) or vehicle (n=5-8/group) 30 minutes before receiving a single dose of IL-6 (1 µg ip) or saline. Animals were sacrificed after 6 hours and liver samples were analyzed using qRT-PCR and western blotting. RESULTS: As compared to saline controls, IL-6 decreased the expression of Cyp3a, Abcb1a, Abcc3, and Slco1a4 20-70% similarly in PXR (+/+) and (-/-) mice at 6 hr, while downregulation of Abcb11, Abcc2, Slc10a1and Slco2b1 was only seen in PXR (+/+). Pre-administration of S3I-201 attenuated IL-6-mediated changes of most transporters in PXR (+/+) and PXR (-/-) mice. At early times after IL-6 administration (10-120 minutes), transcript levels of Socs3, PXR, Abcb1a, Abcc3, Abcb11, Slco1a4 and Slco2b1were increased in PXR (+/+) mice. CONCLUSIONS: Our findings demonstrate that IL-6 imposes a significant downregulation of numerous ABC and SLC transporters in liver primarily through activation of the STAT3 signaling pathway. Based on time-dependent changes in transporter expression, downregulation likely occurs downstream of STAT3 activation. As IL-6 is elevated in many diseases, understanding the underlying mechanism(s) involved in transporter dysregulation will allow us to predict potential drug-disease interactions.
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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 | 0.001 | 0.001 |
| 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 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".