3-O-Ethyl-l-ascorbic acid

In the crystal structure of the title compound, C8H12O6, mol­ecules are linked to each other by O—H⋯O hydrogen bonding

Identification of diagnostic biomarkers in Alzheimer’s disease by integrated bioinformatic analysis and machine learning strategies

BackgroundAlzheimer’s disease (AD) is the most prevalent form of dementia, and is becoming one of the most burdening and lethal diseases. More useful biomarkers for diagnosing AD and reflecting the disease progression are in need and of significance.MethodsThe integrated bioinformatic analysis combined with machine-learning strategies was applied for exploring crucial functional pathways and identifying diagnostic biomarkers of AD. Four datasets (GSE5281, GSE131617, GSE48350, and GSE84422) with samples of AD frontal cortex are integrated as experimental datasets, and another two datasets (GSE33000 and GSE44772) with samples of AD frontal cortex were used to perform validation analyses. Functional Correlation enrichment analyses were conducted based on Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and the Reactome database to reveal AD-associated biological functions and key pathways. Four models were employed to screen the potential diagnostic biomarkers, including one bioinformatic analysis of Weighted gene co-expression network analysis (WGCNA)and three machine-learning algorithms: Least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF) analysis. The correlation analysis was performed to explore the correlation between the identified biomarkers with CDR scores and Braak staging.ResultsThe pathways of the immune response and oxidative stress were identified as playing a crucial role during AD. Thioredoxin interacting protein (TXNIP), early growth response 1 (EGR1), and insulin-like growth factor binding protein 5 (IGFBP5) were screened as diagnostic markers of AD. The diagnostic efficacy of TXNIP, EGR1, and IGFBP5 was validated with corresponding AUCs of 0.857, 0.888, and 0.856 in dataset GSE33000, 0.867, 0.909, and 0.841 in dataset GSE44770. And the AUCs of the combination of these three biomarkers as a diagnostic tool for AD were 0.954 and 0.938 in the two verification datasets.ConclusionThe pathways of immune response and oxidative stress can play a crucial role in the pathogenesis of AD. TXNIP, EGR1, and IGFBP5 are useful biomarkers for diagnosing AD and their mRNA level may reflect the development of the disease by correlation with the CDR scores and Breaking staging

The C-Terminal Effector Domain of Non-Structural Protein 1 of Influenza A Virus Blocks IFN-β Production by Targeting TNF Receptor-Associated Factor 3

Influenza A virus non-structural protein 1 (NS1) antagonizes interferon response through diverse strategies, particularly by inhibiting the activation of interferon regulatory factor 3 (IRF3) and IFN-β transcription. However, the underlying mechanisms used by the NS1 C-terminal effector domain (ED) to inhibit the activation of IFN-β pathway are not well understood. In this study, we used influenza virus subtype of H5N1 to demonstrate that the NS1 C-terminal ED but not the N-terminal RNA-binding domain, binds TNF receptor-associated factor 3 (TRAF3). This results in an attenuation of the type I IFN signaling pathway. We found that the NS1 C-terminal ED (named NS1/126-225) inhibits the active caspase activation and recruitment domain-containing form of RIG-I [RIG-I(N)]-induced IFN-β reporter activity, the phosphorylation of IRF3, and the induction of IFN-β. Further analysis showed that NS1/126-225 binds to TRAF3 through the TRAF domain, subsequently decreasing TRAF3 K63-linked ubiquitination. NS1/126-225 binding also disrupted the formation of the mitochondrial antiviral signaling (MAVS)–TRAF3 complex, increasing the recruitment of IKKε to MAVS; ultimately shutting down the RIG-I(N)-mediated signal transduction and cellular antiviral responses. This attenuation of cellular antiviral responses leads to evasion of the innate immune response. Taken together, our findings offer an important insight into the interplay between the influenza virus and host innate immunity