Abstracts from the ISSAID 2021 Periodic Congress
Bibliographic record
Abstract
Introduction: Systemic Auto Inflammatory Diseases(SAID) is a group of rare hereditary fever syndromes.Phenotypic heterogeneity among SAID patients is quite common, and epigenetic factors can be a cause of these variable clinical profiles.MiRNAs take an active role in the regulation of inflammation.Objectives: This study aims to investigate the potential impact of miRNAs in autoinflammation.Methods: Expression levels of miRNAs in blood samples of 6 severe FMF and 7 mild FMF, 6 other rare SAIDs, and healthy controls were analyzed by miRNA array, bioinformatics tools and pathway analyzes related to inflammatory pathways.The candidate miRNAs were functionally studied for expression levels of inflammatory genes, caspase I activation, apoptosis, cell migration assays in SW982 cells.Then, 3'UTR luciferase activity experiments were carried out to determine the target gene.Then, target gene expression studies were performed at both RNA and protein levels.Also, miR-30e-3p was analyzed in a group (total of 44 patients) of European patients (Germany, Italy, and the Netherland).Results: The expression levels of miRNAs by miRNA array were confirmed by qRT-PCR.miR-30e-3p was significantly reduced among patient groups.After pre-miR transfection of miR-30e-3p; expression levels of inflammatory genes (IL1β, IL18, TNFα, TGFβ) and apoptosis rates decreased, caspase I activation and cell migration rate decreased significantly (p <0.05).As a result of functional analysis, target gene studies were performed with miR-30e, which has an anti-inflammatory effect in all experimental systems.It has been shown that miR-30e is the direct target of the IL-1β gene.Expression of the IL-1β gene at RNA and protein levels decreased in pre-miR-30e-3p transfected cells.Also, miR-30e-3p was decreased in a group of European SAID patients (Germany, Italy, and the Netherland).Conclusion: The results showed that miR-30e-3p has an antiinflammatory effect by regulating IL-1β expression, which is a key protein in inflammatory pathways.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.304 | 0.144 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".