Role of long non-coding RNAs and circular RNAs in kawasaki disease: a systematic review
Bibliographic record
Abstract
OBJECTIVE: Previous research has identified the significant roles of non-coding RNAs (ncRNAs) in Kawasaki disease (KD). This systematic review aims to elucidate the involvement and significance of long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) in the pathogenesis and progression of KD. STUDY DESIGN: A systematic search was conducted across four databases (PubMed, Embase, Scopus, and Web of Science) up to June 19, 2023, without year restrictions. The risk of bias was assessed using the Newcastle-Ottawa Scale. RESULTS: This review included 9 studies encompassing a total of 1894 individuals diagnosed with KD. Seven lncRNAs-Slco4a1, SOCS2-AS1, SRA, HCG22, MHRT, XLOC_006277, and HSD11B1-AS1-were found to be associated with KD, including polymorphisms such as lncRNA rs1814343 C > T and AC008392.1 rs7248320. Additionally, four circRNAs-circRNA-3302, circ7632, circANRIL, and hsa_circ_0123996-were associated with KD. CONCLUSIONS: Both linear lncRNAs and circRNAs play critical roles in unraveling the mechanisms underlying KD, contributing to biomarker identification and potential therapeutic advances.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| 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) | 0.000 | 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".