Network-Based Data Analysis Reveals Ion Channel-Related Gene Features in COVID-19: A Bioinformatic Approach.

Coronavirus disease 2019 (COVID-19) seriously threatens human health and has been disseminated worldwide. Although there are several treatments for COVID-19, its control is currently suboptimal. Therefore, the development of novel strategies to treat COVID-19 is necessary. Ion channels are located on the membranes of all excitable cells and many intracellular organelles and are key components involved in various biological processes. They are a target of interest when searching for drug targets. This study aimed to reveal the relevant molecular features of ion channel genes in COVID-19 based on bioinformatic analyses. The RNA-sequencing data of patients with COVID-19 and healthy subjects (GSE152418 and GSE171110 datasets) were obtained from the Gene Expression Omnibus (GEO) database. Ion channel genes were selected from the Hugo Gene Nomenclature Committee (HGNC) database. The RStudio software was used to process the data based on the corresponding R language package to identify ion channel-associated differentially expressed genes (DEGs). Based on the DEGs, Gene Ontology (GO) functional and pathway enrichment analyses were performed using the Enrichr web tool. The STRING database was used to generate a protein-protein interaction (PPI) network, and the Cytoscape software was used to screen for hub genes in the PPI network based on the cytoHubba plug-in. Transcription factors (TF)-DEG, DEG-microRNA (miRNA) and DEG-disease association networks were constructed using the NetworkAnalyst web tool. Finally, the screened hub genes as drug targets were subjected to enrichment analysis based on the DSigDB using the Enrichr web tool to identify potential therapeutic agents for COVID-19. A total of 29 ion channel-associated DEGs were identified. GO functional analysis showed that the DEGs were integral components of the plasma membrane and were mainly involved in inorganic cation transmembrane transport and ion channel activity functions. Pathway analysis showed that the DEGs were mainly involved in nicotine addiction, calcium regulation in the cardiac cell and neuronal system pathways. The top 10 hub genes screened based on the PPI network included KCNA2, KCNJ4, CACNA1A, CACNA1E, NALCN, KCNA5, CACNA2D1, TRPC1, TRPM3 and KCNN3. The TF-DEG and DEG-miRNA networks revealed significant TFs (FOXC1, GATA2, HINFP, USF2, JUN and NFKB1) and miRNAs (hsa-mir-146a-5p, hsa-mir-27a-3p, hsa-mir-335-5p, hsa-let-7b-5p and hsa-mir-129-2-3p). Gene-disease association network analysis revealed that the DEGs were closely associated with intellectual disability and cerebellar ataxia. Drug-target enrichment analysis showed that the relevant drugs targeting the hub genes CACNA2D1, CACNA1A, CACNA1E, KCNA2 and KCNA5 were gabapentin, gabapentin enacarbil, pregabalin, guanidine hydrochloride and 4-aminopyridine. The results of this study provide a valuable basis for exploring the mechanisms of ion channel genes in COVID-19 and clues for developing therapeutic strategies for COVID-19.

Adaptor protein MyD88 confers the susceptibility to stress via amplifying immune danger signals.

Increasing evidence supports the pathogenic role of neuroinflammation in psychiatric diseases, including major depressive disorder (MDD) and neuropsychiatric symptoms of Coronavirus disease 2019 (COVID-19); however, the precise mechanism and therapeutic strategy are poorly understood. Here, we report that myeloid differentiation factor 88 (MyD88), a pivotal adaptor that bridges toll-like receptors to their downstream signaling by recruiting the signaling complex called 'myddosome', was up-regulated in the medial prefrontal cortex (mPFC) after exposure to chronic social defeat stress (CSDS) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. The inducible expression of MyD88 in the mPFC primed neuroinflammation and conferred stress susceptibility via amplifying immune danger signals, such as high-mobility group box 1 and SARS-CoV-2 spike protein. Overexpression of MyD88 aggravated, whereas knockout or pharmacological inhibition of MyD88 ameliorated CSDS-induced depressive-like behavior. Notably, TJ-M2010-5, a novel synthesized targeting inhibitor of MyD88 dimerization, alleviated both CSDS- and SARS-CoV-2 spike protein-induced depressive-like behavior. Taken together, our findings indicate that inhibiting MyD88 signaling represents a promising therapeutic strategy for stress-related mental disorders, such as MDD and COVID-19-related neuropsychiatric symptoms.

A systematic review and meta­analysis of Arbidol therapy for acute respiratory viral infections: A potential treatment for COVID­19.

Arbidol (ARB) is efficacious for the treatment of influenza, and has been recommended for COVID-19. The present systematic review was performed to assess the existing knowledge on ARB therapy for acute respiratory viral infections, especially COVID-19. Subsequently, six databases were searched for publications reporting clinical outcomes of ARB therapy, and registered clinical trials up to May 6, 2022. The available literature was rigorously appraised. Based on the inclusion and exclusion criteria, 20 articles were identified for the final review. The result of meta-analysis showed that there was no significant difference in the negative rate of PCR day 7 [risk ratio (RR), 1.1; 95% CI, 0.87-1.40], negative rate of PCR day 14 (RR, 1.24; 95% CI, 0.92-1.67), PCR negative conversion time [mean difference (MD), -0.26; 95% CI, -1.41-0.90], time of clinical improvement (MD, 1.11; 95% CI, 0.01-2.22), hospital stay (MD, 0.16; 95% CI, -1.62-1.93), rate of improvement on chest computed tomography (CT) (RR, 1.19; 95% CI, 0.74-1.91), duration of CT absorption (MD, -1.43; 95% CI, -10.28-7.42), disease progression (RR, 1.05; 95% CI, 0.64-1.71) and mortality (RR, 0.68; 95% CI, 0.42-1.11). ARB demonstrated significant difference in the rate of clinical improvement (RR, 0.81; 95% CI, 0.67-0.97), duration of fever (MD, -0.38; 95% CI, -0.74- -0.02) and adverse events (RR, 0.65; 95% CI, 0.45-0.94). Although past clinical studies indicates notable results of ARB on influenza, there is no consensus on the drug for therapeutic and prophylaxis of COVID-19. The safety of ARB should be carefully monitored. High quality randomized controlled studies are urgently needed to thoroughly evaluate the efficacy and safety of ARB in patients with acute respiratory viral infections, especially COVID-19.

Real-time infection prediction with wearable physiological monitoring and AI to aid military workforce readiness during COVID-19.

Infectious threats, like the COVID-19 pandemic, hinder maintenance of a productive and healthy workforce. If subtle physiological changes precede overt illness, then proactive isolation and testing can reduce labor force impacts. This study hypothesized that an early infection warning service based on wearable physiological monitoring and predictive models created with machine learning could be developed and deployed. We developed a prototype tool, first deployed June 23, 2020, that delivered continuously updated scores of infection risk for SARS-CoV-2 through April 8, 2021. Data were acquired from 9381 United States Department of Defense (US DoD) personnel wearing Garmin and Oura devices, totaling 599,174 user-days of service and 201 million hours of data. There were 491 COVID-19 positive cases. A predictive algorithm identified infection before diagnostic testing with an AUC of 0.82. Barriers to implementation included adequate data capture (at least 48% data was needed) and delays in data transmission. We observe increased risk scores as early as 6 days prior to diagnostic testing (2.3 days average). This study showed feasibility of a real-time risk prediction score to minimize workforce impacts of infection.

Applying Multiple Strategies to Enhance the Completion Rate of Critical Care in COVID-19 Patients

Background & Problems: Taiwan entered the community transmission stage of COVID-19 in May 2021, with numbers of locally confirmed cases and critical cases increasing sharply. Medical institutions deployed special units to treat patients. In our hospital, a special COVID-19 intensive care units staffed with nursing personnel across various specialties was established. The rate of COVID-19 critical care completion among nurses in this unit was 79.1%. The reasons for non-completion were found to include limited intensive care standards for COVID-19;inadequate training, teaching aids, and practice manuals;and the overwhelming amount of new COVID-19-related information and updates. Purpose: The aim of this project was to increase the team's COVID-19 critical care completion rate from 79.1% to 93.5%. Resolutions: Multiple strategies were implemented, including: (1) providing online education and training, (2) establishing a platform for sharing COVID-19-related updates, (3) creating a QR-code accessible COVID-19 reference database, (4) creating a COVID-19 practice manual, and (5) providing simulation training sessions on wearing personal protective equipment during critical care. Results: The critical-care completion rate for patients with COVID-19 infection increased significantly in this unit from 79.1% to 98.2%, which exceeded the project goal. Conclusions: Implementing a multi-strategy intervention that includes both online and simulation training may be effective in improving the critical care completion rate for patients with COVID-19 infection.