MicroRNA-204-5p suppresses IL6-mediated inflammatory response and chemokine generation in HK-2 renal tubular epithelial cells by targeting IL6R
Bibliographic record
Abstract
During the pathogenetic process of varied kidney diseases, renal tubules are the major sites in response to detrimental insults, including pro-inflammatory stimuli. MicroRNA-204-5p (miR-204-5p) can be detected in the renal tubular epithelial cells in the normal kidney; its expression, however, is downregulated in the kidney with pathological changes. This study aimed to investigate the role of miR-204-5p in interleukin 6 (IL6) mediated inflammatory response and chemokine production in HK-2 renal tubular cells. In HK-2 cells, the expression of miR-204-5p was downregulated in response to exogenous pro-inflammatory stimulus, tumor necrosis factor α (TNFα), or IL1β, while that of IL6 receptor α (IL6R) was upregulated. Dual-luciferase results confirmed that miRNA-204-5p directly targeted IL6R. In addition to suppressing IL6R expression, miRNA-204-5p agomir also inhibited the phosphorylation of signal transducer and activator of transcription 3 (STAT3) in HK-2 cells exposed to exogenous IL6. Further, miRNA-204-5p suppressed the overproduction of pro-inflammatory mediators (cyclooxygenase 2 and prostaglandin E2) and chemokines (C–C motif chemokine ligand 2 and C–X–C motif chemokine ligand 8). The anti-inflammatory effects of miRNA-204-5p were attenuated when IL6R was reexpressed in HK-2 cells. Collectively, our study reveals that miR-204-5p inhibits the inflammation and chemokine generation in renal tubular epithelial cells by modulating the IL6/IL6R axis.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 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".