SynthesisFrontiers in cellular and infection microbiology2023
Identifying key genes related to inflammasome in severe COVID-19 patients based on a joint model with random forest and artificial neural network.
Synthesis in Frontiers in cellular and infection microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- Viral Mechanisms and Drug Influences on Janus Kinase/Signal Transducers and Activators of Transcription (JAK/STAT) Pathway in Human Coronaviruses Infection: A Systematic Review.Health science reports · 2026Review
- Therapeutic targets for diabetic nephropathy identified by druggable genome mendelian randomization: the role of the gut microbiota-metabolite axis.Frontiers in endocrinology · 2026Article
- Identification of Shared Gene Signatures Associated with Alzheimer's Disease and COVID-19 through Bioinformatics Analysis.Combinatorial chemistry & high throughput screening · 2026Article
- Multitemporal single-cell profiling uncovers alveolar IL1βClinical and translational medicine · 2025Article
- Genetic and Inflammatory Signatures Associated With Worse Prognosis in Hospitalized Patients With Severe SARS-CoV-2 Infection With and Without Diabetes.Journal of medical virology · 2025Article
- Screening of Herbs with Potential Modulation of NLRP3 Inflammasomes for Acute Liver Failure: A Study Based on the Herb-Compound-Target Network and the ssGSEA Algorithm.Current topics in medicinal chemistry · 2025Article
- Human pan-cancer analysis of the predictive biomarker for the CDKN3.European journal of medical research · 2024Article
- Multi-Omics Data Analysis Identifies Prognostic Biomarkers across Cancers.Medical sciences (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The coronavirus disease 2019 (COVID-19) has been spreading astonishingly and caused catastrophic losses worldwide. The high mortality of severe COVID-19 patients is an serious problem that needs to be solved urgently. However, the biomarkers and fundamental pathological mechanisms of severe COVID-19 are poorly understood. The aims of this study was to explore key genes related to inflammasome in severe COVID-19 and their potential molecular mechanisms using random forest and artificial neural network modeling. Methods: Differentially expressed genes (DEGs) in severe COVID-19 were screened from GSE151764 and GSE183533 Results: Using combining Conclusion: The five genes related to inflammasome, including AXL, MKI67, CDKN3, BCL2 and PTGS2, are important for severe COVID-19 patients, and these molecules are related to the activation of NLRP3 inflammasome. Furthermore, AXL, MKI67, CDKN3, BCL2 and PTGS2 as a marker combination could be used as potential markers to identify severe COVID-19 patients.
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Registered trials
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