Discovering common pathogenetic processes between COVID-19 and sepsis by bioinformatics and system biology approach.

Corona Virus Disease 2019 (COVID-19), an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly worldwide, resulting in a pandemic with a high mortality rate. In clinical practice, we have noted that many critically ill or critically ill patients with COVID-19 present with typical sepsis-related clinical manifestations, including multiple organ dysfunction syndrome, coagulopathy, and septic shock. In addition, it has been demonstrated that severe COVID-19 has some pathological similarities with sepsis, such as cytokine storm, hypercoagulable state after blood balance is disrupted and neutrophil dysfunction. Considering the parallels between COVID-19 and non-SARS-CoV-2 induced sepsis (hereafter referred to as sepsis), the aim of this study was to analyze the underlying molecular mechanisms between these two diseases by bioinformatics and a systems biology approach, providing new insights into the pathogenesis of COVID-19 and the development of new treatments. Specifically, the gene expression profiles of COVID-19 and sepsis patients were obtained from the Gene Expression Omnibus (GEO) database and compared to extract common differentially expressed genes (DEGs). Subsequently, common DEGs were used to investigate the genetic links between COVID-19 and sepsis. Based on enrichment analysis of common DEGs, many pathways closely related to inflammatory response were observed, such as Cytokine-cytokine receptor interaction pathway and NF-kappa B signaling pathway. In addition, protein-protein interaction networks and gene regulatory networks of common DEGs were constructed, and the analysis results showed that ITGAM may be a potential key biomarker base on regulatory analysis. Furthermore, a disease diagnostic model and risk prediction nomogram for COVID-19 were constructed using machine learning methods. Finally, potential therapeutic agents, including progesterone and emetine, were screened through drug-protein interaction networks and molecular docking simulations. We hope to provide new strategies for future research and treatment related to COVID-19 by elucidating the pathogenesis and genetic mechanisms between COVID-19 and sepsis.

Network Pharmacology and Bioinformatics Analysis Identifies Potential Therapeutic Targets of Paxlovid Against LUAD/COVID-19.

Background: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a pandemic in many countries around the world. The virus is highly contagious and has a high fatality rate. Lung adenocarcinoma (LUAD) patients may have higher susceptibility and mortality to COVID-19. While Paxlovid is the first oral drug approved by the U.S. Food and Drug Administration (FDA) for COVID-19, its specific drug mechanism for lung cancer patients infected with COVID-19 remains to be further studied. Methods: COVID-19 related genes were obtained from NCBI, GeneCards, and KEGG, and then the transcriptome data for LUAD was downloaded from TCGA. The drug targets of Paxlovid were revealed through BATMAN-TCM, DrugBank, SwissTargetPrediction, and TargetNet. The genes related to susceptibility to COVID-19 in LUAD patients were obtained through differential analysis. The interaction of LUAD/COVID-19 related genes was evaluated and displayed by STRING, and a COX risk regression model was established to screen and evaluate the correlation between genes and clinical characteristics. The Venn diagram was drawn to select the candidate targets of Paxlovid against LUAD/COVID-19, and the functional analysis of the target genes was performed using KEGG and GO enrichment analysis. Finally, Cytoscape was used to screen and visualize the Hub Gene, and Autodock was used for molecular docking between the drug and the target. Result: Bioinformatics analysis was performed by combining COVID-19-related genes with the gene expression and clinical data of LUAD, including analysis of prognosis-related genes, survival rate, and hub genes screened out by the prognosis model. The key targets of Paxlovid against LUAD/COVID-19 were obtained through network pharmacology, the most important targets include IL6, IL12B, LBP. Furthermore, pathway analysis showed that Paxlovid modulates the IL-17 signaling pathway, the cytokine-cytokine receptor interaction, during LUAD/COVID-19 treatment. Conclusions: Based on bioinformatics and network pharmacology, the prognostic signature of LUAD/COVID-19 patients was screened. And identified the potential therapeutic targets and molecular pathways of Paxlovid Paxlovid in the treatment of LUAD/COVID. As promising features, prognostic signatures and therapeutic targets shed light on improving the personalized management of patients with LUAD.

RNA sequencing reveals dynamic expression of lncRNAs and mRNAs in caprine endometrial epithelial cells induced by Neospora caninum infection.

BACKGROUND: The effective transmission mode of Neospora caninum, with infection leading to reproductive failure in ruminants, is vertical transmission. The uterus is an important reproductive organ that forms the maternal-fetal interface. Neospora caninum can successfully invade and proliferate in the uterus, but the molecular mechanisms underlying epithelial-pathogen interactions remain unclear. Accumulating evidence suggests that host long noncoding RNAs (lncRNAs) play important roles in cellular molecular regulatory networks, with reports that these RNA molecules are closely related to the pathogenesis of apicomplexan parasites. However, the expression profiles of host lncRNAs during N. caninum infection has not been reported. METHODS: RNA sequencing (RNA-seq) analysis was used to investigate the expression profiles of messenger RNAs (mRNAs) and lncRNAs in caprine endometrial epithelial cells (EECs) infected with N. caninum for 24 h (TZ_24h) and 48 h (TZ_48 h), and the potential functions of differentially expressed (DE) lncRNAs were predicted by using Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of their mRNA targets. RESULTS: RNA-seq analysis identified 1280.15 M clean reads in 12 RNA samples, including six samples infected with N. caninum for 24 h (TZ1_24h-TZ3_24h) and 48 h (TZ1_48h-TZ3_48h), and six corresponding control samples (C1_24h-C3_24h and C1_48h-C3_48h). Within the categories TZ_24h-vs-C_24h, TZ_48h-vs-C_48h and TZ_48h-vs-TZ_24h, there were 934 (665 upregulated and 269 downregulated), 1238 (785 upregulated and 453 downregulated) and 489 (252 upregulated and 237 downregulated) DEmRNAs, respectively. GO enrichment and KEGG analysis revealed that these DEmRNAs were mainly involved in the regulation of host immune response (e.g. TNF signaling pathway, MAPK signaling pathway, transforming growth factor beta signaling pathway, AMPK signaling pathway, Toll-like receptor signaling pathway, NOD-like receptor signaling pathway), signaling molecules and interaction (e.g. cytokine-cytokine receptor interaction, cell adhesion molecules and ECM-receptor interaction). A total of 88 (59 upregulated and 29 downregulated), 129 (80 upregulated and 49 downregulated) and 32 (20 upregulated and 12 downregulated) DElncRNAs were found within the categories TZ_24h-vs-C_24h, TZ_48h-vs-C_48h and TZ_48h-vs-TZ_24h, respectively. Functional prediction indicated that these DElncRNAs would be involved in signal transduction (e.g. MAPK signaling pathway, PPAR signaling pathway, ErbB signaling pathway, calcium signaling pathway), neural transmission (e.g. GABAergic synapse, serotonergic synapse, cholinergic synapse), metabolism processes (e.g. glycosphingolipid biosynthesis-lacto and neolacto series, glycosaminoglycan biosynthesis-heparan sulfate/heparin) and signaling molecules and interaction (e.g. cytokine-cytokine receptor interaction, cell adhesion molecules and ECM-receptor interaction). CONCLUSIONS: This is the first investigation of global gene expression profiles of lncRNAs during N. caninum infection. The results provide valuable information for further studies of the roles of lncRNAs during N. caninum infection.

Deciphering SARS CoV-2-associated pathways from RNA sequencing data of COVID-19-infected A549 cells and potential therapeutics using in silico methods.

BACKGROUND: Coronavirus (CoV) disease (COVID-19) identified in Wuhan, China, in 2019, is mainly characterized by atypical pneumonia and severe acute respiratory syndrome (SARS) and is caused by SARS CoV-2, which belongs to the Coronaviridae family. Determining the underlying disease mechanisms is central to the identification and development of COVID-19-specific drugs for effective treatment and prevention of human-to-human transmission, disease complications, and deaths. METHODS: Here, next-generation RNA sequencing (RNA Seq) data were obtained using Illumina Next Seq 500 from SARS CoV-infected A549 cells and mock-treated A549 cells from the Gene Expression Omnibus (GEO) (GSE147507), and quality control (QC) was assessed before RNA Seq analysis using CLC Genomics Workbench 20.0. Differentially expressed genes (DEGs) were imported into BioJupies to decipher COVID-19 induced signaling pathways and small molecules derived from chemical synthesis or natural sources to mimic or reverse COVID -19 specific gene signatures. In addition, iPathwayGuide was used to identify COVID-19-specific signaling pathways, as well as drugs and natural products with anti-COVID-19 potential. RESULTS: Here, we identified the potential activation of upstream regulators such as signal transducer and activator of transcription 2 (STAT2), interferon regulatory factor 9 (IRF9), and interferon beta (IFNß), interleukin-1 beta (IL-1ß), and interferon regulatory factor 3 (IRF3). COVID-19 infection activated key infectious disease-specific immune-related signaling pathways such as influenza A, viral protein interaction with cytokine and cytokine receptors, measles, Epstein-Barr virus infection, and IL-17 signaling pathway. Besides, we identified drugs such as prednisolone, methylprednisolone, diclofenac, compound JQ1, and natural products such as Withaferin-A and JinFuKang as candidates for further experimental validation of COVID-19 therapy. CONCLUSIONS: In conclusion, we have used the in silico next-generation knowledge discovery (NGKD) methods to discover COVID-19-associated pathways and specific therapeutics that have the potential to ameliorate the disease pathologies associated with COVID-19.

Coronavirus disease 2019 and pityriasis rosea: A review of the immunological connection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is characterized by the activation of a cytokine storm derived from an excess release of cytokine (interleukin [IL]-6, interferon [IFN] I, C-X-C motif chemokine ligand [CXCL]10, tumor necrosis factor [TNF]-α, macrophage inflammatory protein [MIP]1) due to an uncontrolled immune activation. There has been a fivefold increase in the number of cases of pityriasis rosea during the SARS-CoV-2 pandemic. Using the keywords "pityriasis" and "COVID-19", we carried out a PubMed search, including all articles in the English language published until November 2021. We aimed to investigate the possible connection between SARS-CoV-2 and pityriasis rosea (PR). Pityriasis could be considered an immunological disease due to the involvement of cytokines and chemokines. Our analysis yielded 65 articles of which 53 were not considered; the others (n = 12) concerning the association between PR and COVID-19 were included in our study. We suggest two mechanisms underlying the involvement of the skin in viral infections: (i) viruses directly affecting the skin and/or inducing host immune response thus causing cutaneous manifestations; and (ii) viruses as a possible inducer of the reactivation of another virus. The first mechanism is probably related to a release of pro-inflammatory cytokine and infection-related biomarkers; in the second, several pathways could be involved in the reactivation of other latent viruses (human herpesviruses 6 and 7), such as a cytokine-cytokine receptor interaction, the Janus kinase-signal transducer and activator of transcription signaling pathway, and the IL-17 signaling pathway. We thus believe that a cytokine storm could be directly or indirectly responsible for a cutaneous manifestation. More investigations are needed to find specific pathways involved and thus confirm our speculations.

Individual genetic variability mainly of Proinflammatory cytokines, cytokine receptors, and toll-like receptors dictates pathophysiology of COVID-19 disease.

Innate and acquired immunity responses are crucial for viral infection elimination. However, genetic variations in coding genes may exacerbate the inflammation or initiate devastating cytokine storms which poses severe respiratory conditions in coronavirus disease-19 (COVID-19). Host genetic variations in particular those related to the immune responses determine the patients' susceptibility and COVID-19 severity and pathophysiology. Gene polymorphisms such as single nucleotide polymorphisms (SNPs) of interferons, TNF, IL1, IL4, IL6, IL7, IL10, and IL17 predispose patients to the severe form of COVID-19 or severe acute respiratory syndrome coronavirus-2 (SARS-COV-2). These variations mainly alter the gene expression and cause a severe response by B cells, T cells, monocytes, neutrophils, and natural killer cells participating in a cytokine storm. Moreover, cytokines and chemokines SNPs are associated with the severity of COVID-19 and clinical outcomes depending on the corresponding effect. Additionally, genetic variations in genes encoding toll-like receptors (TLRs) mainly TLR3, TLR7, and TLR9 have been related to the COVID-19 severe respiratory symptoms. The specific relation of these mutations with the novel variants of concern (VOCs) infection remains to be elucidated. Genetic variations mainly within genes encoding proinflammatory cytokines, cytokine receptors, and TLRs predispose patients to COVID-19 disease severity. Understanding host immune gene variations associated with the SARS-COV-2 infection opens insights to control the pathophysiology of emerging viral infections.

2-Deoxy-d-glucose induces deglycosylation of proinflammatory cytokine receptors and strongly reduces immunological responses in mouse models of inflammation.

Anti-proinflammatory cytokine therapies against interleukin (IL)-6, tumor necrosis factor (TNF)-α, and IL-1 are major advancements in treating inflammatory diseases, especially rheumatoid arthritis. Such therapies are mainly performed by injection of antibodies against cytokines or cytokine receptors. We initially found that the glycolytic inhibitor 2-deoxy-d-glucose (2-DG), a simple monosaccharide, attenuated cellular responses to IL-6 by inhibiting N-linked glycosylation of the IL-6 receptor gp130. Aglycoforms of gp130 did not bind to IL-6 or activate downstream intracellular signals that included Janus kinases. 2-DG completely inhibited dextran sodium sulfate-induced colitis, a mouse model for inflammatory bowel disease, and alleviated laminarin-induced arthritis in the SKG mouse, an experimental model for human rheumatoid arthritis. These diseases have been shown to be partially dependent on IL-6. We also found that 2-DG inhibited signals for other proinflammatory cytokines such as TNF-α, IL-1ß, and interferon -γ, and accordingly, prevented death by another inflammatory disease, lipopolysaccharide (LPS) shock. Furthermore, 2-DG prevented LPS shock, a model for a cytokine storm, and LPS-induced pulmonary inflammation, a model for acute respiratory distress syndrome of coronavirus disease 2019 (COVID-19). These results suggest that targeted therapies that inhibit cytokine receptor glycosylation are effective for treatment of various inflammatory diseases.

Role of immune mediators in predicting hospitalization of SARS-CoV-2 positive patients.

BACKGROUND: Several immune mediators (IM) including cytokines, chemokines, and their receptors have been suggested to play a role in COVID-19 pathophysiology and severity. AIM: To determine if early IM profiles are predictive of clinical outcome and which of the IMs tested possess the most clinical utility. METHODS: A custom bead-based multiplex assay was used to measure IM concentrations in a cohort of SARS-CoV-2 PCR positive patients (n = 326) with varying disease severities as determined by hospitalization status, length of hospital stay, and survival. Patient groups were compared, and clinical utility was assessed. Correlation plots were constructed to determine if significant relationships exist between the IMs in the setting of COVID-19. RESULTS: In PCR positive SARS-CoV-2 patients, IL-6 was the best predictor of the need for hospitalization and length of stay. Additionally, MCP-1 and sIL-2Rα were moderate predictors of the need for hospitalization. Hospitalized PCR positive SARS-CoV-2 patients displayed a notable correlation between sIL-2Rα and IL-18 (Spearman's ρ = 0.48, P=<0.0001). CONCLUSIONS: IM profiles between non-hospitalized and hospitalized patients were distinct. IL-6 was the best predictor of COVID-19 severity among all the IMs tested.

Single-cell analysis reveals cell communication triggered by macrophages associated with the reduction and exhaustion of CD8+ T cells in COVID-19.

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak caused by severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) has become an ongoing pandemic. Understanding the respiratory immune microenvironment which is composed of multiple cell types, together with cell communication based on ligand-receptor interactions is important for developing vaccines, probing COVID-19 pathogenesis, and improving pandemic control measures. METHODS: A total of 102 consecutive hospitalized patients with confirmed COVID-19 were enrolled in this study. Clinical information, routine laboratory tests, and flow cytometry analysis data with different conditions were collected and assessed for predictive value in COVID-19 patients. Next, we analyzed public single-cell RNA-sequencing (scRNA-seq) data from bronchoalveolar lavage fluid, which offers the closest available view of immune cell heterogeneity as encountered in patients with varying severity of COVID-19. A weighting algorithm was used to calculate ligand-receptor interactions, revealing the communication potentially associated with outcomes across cell types. Finally, serum cytokines including IL6, IL1ß, IL10, CXCL10, TNFα, GALECTIN-1, and IGF1 derived from patients were measured. RESULTS: Of the 102 COVID-19 patients, 42 cases (41.2%) were categorized as severe. Multivariate logistic regression analysis demonstrated that AST, D-dimer, BUN, and WBC were considered as independent risk factors for the severity of COVID-19. T cell numbers including total T cells, CD4+ and CD8+ T cells in the severe disease group were significantly lower than those in the moderate disease group. The risk model containing the above mentioned inflammatory damage parameters, and the counts of T cells, with AUROCs ranged from 0.78 to 0.87. To investigate the molecular mechanism at the cellular level, we analyzed the published scRNA-seq data and found that macrophages displayed specific functional diversity after SARS-Cov-2 infection, and the metabolic pathway activities in the identified macrophage subtypes were influenced by hypoxia status. Importantly, we described ligand-receptor interactions that are related to COVID-19 serverity involving macrophages and T cell subsets by communication analysis. CONCLUSIONS: Our study showed that macrophages driving ligand-receptor crosstalk contributed to the reduction and exhaustion of CD8+ T cells. The identified crucial cytokine panel, including IL6, IL1ß, IL10, CXCL10, IGF1, and GALECTIN-1, may offer the selective targets to improve the efficacy of COVID-19 therapy. TRIAL REGISTRATION: This is a retrospective observational study without a trial registration number. Video Abstract.

A bioinformatic approach to investigating cytokine genes and their receptor variants in relation to COVID-19 progression.

Severe acute respiratory syndrome coronavirus 2 infection produces a wide spectrum of manifestations, ranging from no symptom to viral pneumonia. This study aimed to determine the genetic variations in cytokines and their receptors in relation to COVID-19 pathogenesis using bioinformatic tools. Single nucleotide polymorphisms (SNPs) of genes encoding the cytokines and cytokine receptors elevated in patients with COVID-19 were determined from the National Biotechnology Information Center website (using the dbSNP database). Missense variants were found in 3 cytokine genes and 10 cytokine receptor genes. Computational analyses were conducted to detect the effects of these missense SNPs via cloud-based software tools. Also, the miRSNP database was used to explore whether SNPs in the 3'-UTR altered the miRNA binding efficiency for genes of cytokines and their receptors. Our in silico studies revealed that one SNP in the vascular endothelial growth factor receptor 2 (VEGFR2) gene was predicted as deleterious using sorting intolerant from tolerant. Also, the stability of VEGFR2 decreased in the I-Mutant2.0 (biotool for predicting stability changes upon mutation from the protein sequence or structure) prediction. It was suggested that the decrease in VEGFR2 function (due to the rs1870377 polymorphism) may be correlated with the progression of COVID-19 or contribute to the pathogenesis. Moreover, 27 SNPs were determined to affect miRNA binding for the genes of cytokine receptors. CXCR2 rs1126579, TNFRSF1B rs1061624 and IL10RB rs8178562 SNPs were predicted to break the miRNA-mRNA binding sites for miR-516a-3, miR-720 and miR-328, respectively. These miRNAs play an important role in immune regulation and lung damage repair. Further studies are needed to evaluate the importance of these miRNAs and the SNPs.

50 Years of structural immunology.

Fifty years ago, the first landmark structures of antibodies heralded the dawn of structural immunology. Momentum then started to build toward understanding how antibodies could recognize the vast universe of potential antigens and how antibody-combining sites could be tailored to engage antigens with high specificity and affinity through recombination of germline genes (V, D, J) and somatic mutation. Equivalent groundbreaking structures in the cellular immune system appeared some 15 to 20 years later and illustrated how processed protein antigens in the form of peptides are presented by MHC molecules to T cell receptors. Structures of antigen receptors in the innate immune system then explained their inherent specificity for particular microbial antigens including lipids, carbohydrates, nucleic acids, small molecules, and specific proteins. These two sides of the immune system act immediately (innate) to particular microbial antigens or evolve (adaptive) to attain high specificity and affinity to a much wider range of antigens. We also include examples of other key receptors in the immune system (cytokine receptors) that regulate immunity and inflammation. Furthermore, these antigen receptors use a limited set of protein folds to accomplish their various immunological roles. The other main players are the antigens themselves. We focus on surface glycoproteins in enveloped viruses including SARS-CoV-2 that enable entry and egress into host cells and are targets for the antibody response. This review covers what we have learned over the past half century about the structural basis of the immune response to microbial pathogens and how that information can be utilized to design vaccines and therapeutics.

Decoy nanoparticles protect against COVID-19 by concurrently adsorbing viruses and inflammatory cytokines.

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has highlighted the urgent need to rapidly develop therapeutic strategies for such emerging viruses without effective vaccines or drugs. Here, we report a decoy nanoparticle against COVID-19 through a powerful two-step neutralization approach: virus neutralization in the first step followed by cytokine neutralization in the second step. The nanodecoy, made by fusing cellular membrane nanovesicles derived from human monocytes and genetically engineered cells stably expressing angiotensin converting enzyme II (ACE2) receptors, possesses an antigenic exterior the same as source cells. By competing with host cells for virus binding, these nanodecoys effectively protect host cells from the infection of pseudoviruses and authentic SARS-CoV-2. Moreover, relying on abundant cytokine receptors on the surface, the nanodecoys efficiently bind and neutralize inflammatory cytokines including interleukin 6 (IL-6) and granulocyte-macrophage colony-stimulating factor (GM-CSF), and significantly suppress immune disorder and lung injury in an acute pneumonia mouse model. Our work presents a simple, safe, and robust antiviral nanotechnology for ongoing COVID-19 and future potential epidemics.

Serum Protein Profiling Reveals a Landscape of Inflammation and Immune Signaling in Early-stage COVID-19 Infection.

Coronavirus disease 2019 (COVID-19) is a highly contagious infection and threating the human lives in the world. The elevation of cytokines in blood is crucial to induce cytokine storm and immunosuppression in the transition of severity in COVID-19 patients. However, the comprehensive changes of serum proteins in COVID-19 patients throughout the SARS-CoV-2 infection is unknown. In this work, we developed a high-density antibody microarray and performed an in-depth proteomics analysis of serum samples collected from early COVID-19 (n = 15) and influenza (n = 13) patients. We identified a large set of differentially expressed proteins (n = 132) that participate in a landscape of inflammation and immune signaling related to the SARS-CoV-2 infection. Furthermore, the significant correlations of neutrophil and lymphocyte with the CCL2 and CXCL10 mediated cytokine signaling pathways was identified. These information are valuable for the understanding of COVID-19 pathogenesis, identification of biomarkers and development of the optimal anti-inflammation therapy.

A pharmacological interactome between COVID-19 patient samples and human sensory neurons reveals potential drivers of neurogenic pulmonary dysfunction.

The SARS-CoV-2 virus infects cells of the airway and lungs in humans causing the disease COVID-19. This disease is characterized by cough, shortness of breath, and in severe cases causes pneumonia and acute respiratory distress syndrome (ARDS) which can be fatal. Bronchial alveolar lavage fluid (BALF) and plasma from mild and severe cases of COVID-19 have been profiled using protein measurements and bulk and single cell RNA sequencing. Onset of pneumonia and ARDS can be rapid in COVID-19, suggesting a potential neuronal involvement in pathology and mortality. We hypothesized that SARS-CoV-2 infection drives changes in immune cell-derived factors that then interact with receptors expressed by the sensory neuronal innervation of the lung to further promote important aspects of disease severity, including ARDS. We sought to quantify how immune cells might interact with sensory innervation of the lung in COVID-19 using published data from patients, existing RNA sequencing datasets from human dorsal root ganglion neurons and other sources, and a genome-wide ligand-receptor pair database curated for pharmacological interactions relevant for neuro-immune interactions. Our findings reveal a landscape of ligand-receptor interactions in the lung caused by SARS-CoV-2 viral infection and point to potential interventions to reduce the burden of neurogenic inflammation in COVID-19 pulmonary disease. In particular, our work highlights opportunities for clinical trials with existing or under development rheumatoid arthritis and other (e.g. CCL2, CCR5 or EGFR inhibitors) drugs to treat high risk or severe COVID-19 cases.