MicroRNA-27a-3p enhances the inflammatory phenotype of Juvenile Idiopathic Arthritis fibroblast-like synoviocytes
Bibliographic record
Abstract
Abstract Background Juvenile Idiopathic Arthritis (JIA) is the most prevalent chronic pediatric rheumatic disorder. In joints of JIA patients, aggressive phenotypic changes in fibroblast-like synoviocytes (FLS) of the synovial lining play a key role in inflammation. MicroRNAs are dysregulated in rheumatoid arthritis and JIA, including miR-27a-3p. However, it is not understood if miR-27a-3p, enriched in JIA synovial fluid (SF) and leukocytes, alters FLS function. Methods Primary JIA FLS cells were transfected with a miR-27a-3p mimic or a negative control microRNA (miR-NC) and stimulated with pooled JIA SF or inflammatory cytokines. Viability and apoptosis were analyzed by flow cytometry. Proliferation was evaluated using a 3H-thymidine incorporation assay. Cytokine production was assessed by qPCR and ELISA. Expression of TGF-β pathway genes was determined using a qPCR array. Results MiR-27a-3p was constitutively expressed in FLS. Overexpression of miR-27a-3p caused increased interleukin-8 secretion in resting FLS, and interleukin-6 was elevated in SF-activated FLS compared to miR-NC. Furthermore, stimulation with pro-inflammatory cytokines augmented FLS proliferation in miR-27a-3p-transfected FLS relative to miR-NC. Expression of multiple TGF-β pathway genes was modulated by overexpression of miR-27a-3p. Conclusions MiR-27a-3p significantly contributes to FLS proliferation and cytokine production, making it a potential candidate for epigenetic therapy that targets FLS in arthritis.
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.
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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".