Serum and Urinary Cell–free MiR-146a and MiR-155 in Patients with Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: Recent studies showed that micro-RNA play important roles in the pathogenesis of autoimmune diseases. We studied the levels of miR-146a and miR-155 in the serum and urinary supernatant of patients with systemic lupus erythematosus (SLE). METHODS: The serum and urinary supernatant levels of miR-146a and miR-155 were determined by real-time quantitative polymerase chain reaction in 40 patients with SLE and 30 healthy controls. RESULTS: Compared to controls, serum miR-146a and miR-155 levels were lower, and the urinary level of miR-146a was higher, in SLE. Estimated glomerular filtration rate (eGFR) correlated with both serum miR-146a (r = 0.519, p = 0.001) and miR-155 (r = 0.384, p = 0.014). Serum miR-146a inversely correlated with proteinuria (r = -0.341, p = 0.031) and the SLE Disease Activity Index (r = -0.465, p = 0.003). Serum miR-146a and miR-155 levels also correlated with red blood cell count, platelet count, and lymphocyte count. After treatment with calcitriol for 6 months, serum miR-146a level of SLE patients increased significantly (p < 0.001), and its change inversely correlated with the level of calcium-phosphate product (r = -0.466, p = 0.003). CONCLUSION: The results suggested that serum miR-146a and miR-155 participate in the pathophysiology of SLE and might be used as biomarkers of SLE.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".