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Hepatitis is one of the dangerous diseases that result from viral infections. This virus attacks the liver leading to its inflammation. Inflammation may lead to the death of the liver cells and affect the functionality of the liver. Five main types of hepatitis have been identified, namely hepatitis A, B, C, D, and E viruses. The most common types of these are hepatitis A virus, hepatitis B virus (HBV), and hepatitis C virus (HCV). Among these, HBV and HCV will cause chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma. It is estimated that 257 and 71 million people around the world are currently infected with HBV and HCV, respectively. The prevalence of HBV depends on the geographic area, and its overall prevalence was estimated at 3.6% in the world. The HCV global prevalence in adults is 2.5%. Furthermore, the incidence of HCV was estimated between 0.5% and 2.8% in various studies. According to previous studies, African and Asian countries have the highest prevalence of HBV and HCV. In Iran, the prevalence of HBV and HCV was about 2.2 and 0.5% in the general population, respectively. Prediction of chronic diseases plays an important role in health informatics. Hepatitis is one of the chronic diseases that can lead to liver cirrhosis and hepatocellular carcinoma, which cause deaths around the world. Therefore, early diagnosis is needed to control, treat, and reduce the effects of this disease. [ABSTRACT FROM AUTHOR]

Many companies all over the globe are adopting environmental management techniques that incorporate all types of green solutions as part of their present efforts to ensure survival and sustainability. While some common tools and knowledge may be used to monitor, track, and assess these green components in a linked element, they are usually managed on a piecemeal basis and under multiple management standards; and they are most typically managed as ad-hoc initiatives rather than programmes. To date, two primary stakeholders--management and customers--have exerted pressure on the company to implement sustainability measures. As a case study, this concept paper examines one organization's use of green management and sustainable green practises. It asserts that management has a responsibility to play in reducing negative sustainability consequences. Two theoretical lenses were offered to provide significance to the study, however further research is needed to back up the conclusions of this work. [ABSTRACT FROM AUTHOR]

Abstract Background Systemic lupus erythematosus (SLE) is known to be clinically heterogeneous. Previous efforts to characterize subsets of SLE patients based on gene expression analysis have not been reproduced because of small sample sizes or technical problems. The aim of this study was to develop a robust patient stratification system using gene expression profiling to characterize individual lupus patients. Methods We employed gene set variation analysis (GSVA) of informative gene modules to identify molecular endotypes of SLE patients, machine learning (ML) to classify individual patients into molecular subsets, and logistic regression to develop a composite metric estimating the scope of immunologic perturbations. SHapley Additive ExPlanations (SHAP) revealed the impact of specific features on patient sub-setting. Results Using five datasets comprising 2183 patients, eight SLE endotypes were identified. Expanded analysis of 3166 samples in 17 datasets revealed that each endotype had unique gene enrichment patterns, but not all endotypes were observed in all datasets. ML algorithms trained on 2183 patients and tested on 983 patients not used to develop the model demonstrated effective classification into one of eight endotypes. SHAP indicated a unique array of features influential in sorting individual samples into each of the endotypes. A composite molecular score was calculated for each patient and significantly correlated with standard laboratory measures. Significant differences in clinical characteristics were associated with different endotypes, with those with the least perturbed transcriptional profile manifesting lower disease severity. The more abnormal endotypes were significantly more likely to experience a severe flare over the subsequent 52 weeks while on standard-of-care medication and specific endotypes were more likely to be clinical responders to the investigational product tested in one clinical trial analyzed (tabalumab). Conclusions Transcriptomic profiling and ML reproducibly separated lupus patients into molecular endotypes with significant differences in clinical features, outcomes, and responsiveness to therapy. Our classification approach using a composite scoring system based on underlying molecular abnormalities has both staging and prognostic relevance.

Abstract Systemic lupus erythematosus (SLE) is a multi-organ autoimmune disorder with a prominent genetic component. Individuals of Asian-Ancestry (AsA) disproportionately experience more severe SLE compared to individuals of European-Ancestry (EA), including increased renal involvement and tissue damage. However, the mechanisms underlying elevated severity in the AsA population remain unclear. Here, we utilized available gene expression data and genotype data based on all non-HLA SNP associations in EA and AsA SLE patients detected using the Immunochip genotyping array. We identified 2778 ancestry-specific and 327 trans-ancestry SLE-risk polymorphisms. Genetic associations were examined using connectivity mapping and gene signatures based on predicted biological pathways and were used to interrogate gene expression datasets. SLE-associated pathways in AsA patients included elevated oxidative stress, altered metabolism and mitochondrial dysfunction, whereas SLE-associated pathways in EA patients included a robust interferon response (type I and II) related to enhanced cytosolic nucleic acid sensing and signaling. An independent dataset derived from summary genome-wide association data in an AsA cohort was interrogated and identified similar molecular pathways. Finally, gene expression data from AsA SLE patients corroborated the molecular pathways predicted by SNP associations. Identifying ancestry-related molecular pathways predicted by genetic SLE risk may help to disentangle the population differences in clinical severity that impact AsA and EA individuals with SLE.

Abstract Regulation of intron retention (IR), a form of alternative splicing, is a newly recognized checkpoint in gene expression. Since there are numerous abnormalities in gene expression in the prototypic autoimmune disease systemic lupus erythematosus (SLE), we sought to determine whether IR was intact in patients with this disease. We, therefore, studied global gene expression and IR patterns of lymphocytes in SLE patients. We analyzed RNA-seq data from peripheral blood T cell samples from 14 patients suffering from systemic lupus erythematosus (SLE) and 4 healthy controls and a second, independent data set of RNA-seq data from B cells from16 SLE patients and 4 healthy controls. We identified intron retention levels from 26,372 well annotated genes as well as differential gene expression and tested for differences between cases and controls using unbiased hierarchical clustering and principal component analysis. We followed with gene-disease enrichment analysis and gene-ontology enrichment analysis. Finally, we then tested for significant differences in intron retention between cases and controls both globally and with respect to specific genes. Overall decreased IR was found in T cells from one cohort and B cells from another cohort of patients with SLE and was associated with increased expression of numerous genes, including those encoding spliceosome components. Different introns within the same gene displayed both up- and down-regulated retention profiles indicating a complex regulatory mechanism. These results indicate that decreased IR in immune cells is characteristic of patients with active SLE and may contribute to the abnormal expression of specific genes in this autoimmune disease.

Objectives Type I interferon (IFN) plays a role in the pathogenesis of systemic lupus erythematosus (SLE), but insufficient attention has been directed to the differences in IFN responses between ancestral populations. Here, we explored the expression of the interferon gene signatures (IGSs) in SLE patients of European ancestry (EA) and Asian ancestry (AsA).Methods We used gene set variation analysis with multiple IGS encompassing the response to both type 1 and type 2 IFN in isolated CD14+ monocytes, CD19+B cells, CD4+T cells and Natural Killer (NK) cells from patients with SLE stratified by self-identified ancestry. The expression of genes upstream of the IGS and influenced by lupus-associated risk alleles was also examined. Lastly, we employed machine learning (ML) models to assess the most important features classifying patients by disease activity.Results AsA patients with SLE exhibited greater enrichment in the IFN core and IFNA2 IGS compared with EA patients in all cell types examined and, in the presence and absence of autoantibodies. Overall, AsA patients with SLE demonstrated higher expression of genes upstream of the IGS than EA counterparts. ML with feature importance analysis indicated that IGS expression in NK cells, anti-dsDNA, complement levels and AsA status contributed to disease activity.Conclusions AsA patients with SLE exhibited higher IGS than EA patients in all cell types regardless of autoantibody status, with enhanced expression of genetically associated genes upstream of the IGS potentially contributing. AsA, along with the IGS in NK cells, anti-dsDNA and complement, independently influenced SLE disease activity.

IntroductionPathologic inflammation is a major driver of kidney damage in lupus nephritis (LN), but the immune mechanisms of disease progression and risk factors for end organ damage are poorly understood.MethodsTo characterize molecular profiles through the development of LN, we carried out gene expression analysis of microdissected kidneys from lupus-prone NZM2328 mice. We examined male mice and the congenic NZM2328.R27 strain as a means to define mechanisms associated with resistance to chronic nephritis. Gene expression profiles in lupus mice were compared with those in human LN.ResultsNZM2328 mice exhibited progress from acute to transitional and then to chronic glomerulonephritis (GN). Each stage manifested a unique molecular profile. Neither male mice nor R27 mice progressed past the acute GN stage, with the former exhibiting minimal immune infiltration and the latter enrichment of immunoregulatory gene signatures in conjunction with robust kidney tubule cell profiles indicative of resistance to cellular damage. The gene expression profiles of human LN were similar to those noted in the NZM2328 mouse suggesting comparable stages of LN progression.ConclusionsOverall, this work provides a comprehensive examination of the immune processes involved in progression of murine LN and thus contributes to our understanding of the risk factors for end-stage renal disease. In addition, this work presents a foundation for improved classification of LN and illustrates the applicability of murine models to identify the stages of human disease.

COVID-19 manifests a spectrum of respiratory symptoms, with the more severe often requiring hospitalization. To identify markers for disease progression, we analyzed longitudinal gene expression data from patients with confirmed SARS-CoV-2 infection admitted to the intensive care unit (ICU) for acute hypoxic respiratory failure (AHRF) as well as other ICU patients with or without AHRF and correlated results of gene set enrichment analysis with clinical features. The results were then compared with a second dataset of COVID-19 patients separated by disease stage and severity. Transcriptomic analysis revealed that enrichment of plasma cells (PCs) was characteristic of all COVID-19 patients whereas enrichment of interferon (IFN) and neutrophil gene signatures was specific to patients requiring hospitalization. Furthermore, gene expression results were used to divide AHRF COVID-19 patients into 2 groups with differences in immune profiles and clinical features indicative of severe disease. Thus, transcriptomic analysis reveals gene signatures unique to COVID-19 patients and provides opportunities for identification of the most at-risk individuals.

Abstract To compare lupus pathogenesis in disparate tissues, we analyzed gene expression profiles of human discoid lupus erythematosus (DLE) and lupus nephritis (LN). We found common increases in myeloid cell-defining gene sets and decreases in genes controlling glucose and lipid metabolism in lupus-affected skin and kidney. Regression models in DLE indicated increased glycolysis was correlated with keratinocyte, endothelial, and inflammatory cell transcripts, and decreased tricarboxylic (TCA) cycle genes were correlated with the keratinocyte signature. In LN, regression models demonstrated decreased glycolysis and TCA cycle genes were correlated with increased endothelial or decreased kidney cell transcripts, respectively. Less severe glomerular LN exhibited similar alterations in metabolism and tissue cell transcripts before monocyte/myeloid cell infiltration in some patients. Additionally, changes to mitochondrial and peroxisomal transcripts were associated with specific cells rather than global signal changes. Examination of murine LN gene expression demonstrated metabolic changes were not driven by acute exposure to type I interferon and could be restored after immunosuppression. Finally, expression of HAVCR1, a tubule damage marker, was negatively correlated with the TCA cycle signature in LN models. These results indicate that altered metabolic dysfunction is a common, reversible change in lupus-affected tissues and appears to reflect damage downstream of immunologic processes.

Abstract SARS-CoV2 is a previously uncharacterized coronavirus and causative agent of the COVID-19 pandemic. The host response to SARS-CoV2 has not yet been fully delineated, hampering a precise approach to therapy. To address this, we carried out a comprehensive analysis of gene expression data from the blood, lung, and airway of COVID-19 patients. Our results indicate that COVID-19 pathogenesis is driven by populations of myeloid-lineage cells with highly inflammatory but distinct transcriptional signatures in each compartment. The relative absence of cytotoxic cells in the lung suggests a model in which delayed clearance of the virus may permit exaggerated myeloid cell activation that contributes to disease pathogenesis by the production of inflammatory mediators. The gene expression profiles also identify potential therapeutic targets that could be modified with available drugs. The data suggest that transcriptomic profiling can provide an understanding of the pathogenesis of COVID-19 in individual patients.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by the production of autoantibodies predominantly to nuclear material. Many aspects of disease pathology are mediated by the deposition of nucleic acid containing immune complexes, which also induce the type 1interferon response, a characteristic feature of SLE. Notably, SLE is remarkably heterogeneous, with a variety of organs involved in different individuals, who also show variation in disease severity related to their ancestries. Here, we probed one potential contribution to disease heterogeneity as well as a possible source of immunoreactive nucleic acids by exploring the expression of human endogenous retroviruses (HERVs). We investigated the expression of HERVs in SLE and their potential relationship to SLE features and the expression of biochemical pathways, including the interferon gene signature (IGS). Towards this goal, we analyzed available and new RNA-Seq data from two independent whole blood studies using Telescope. We identified 481 locus specific HERV encoding regions that are differentially expressed between case and control individuals with only 14% overlap of differentially expressed HERVs between these two datasets. We identified significant differences between differentially expressed HERVs and non-differentially expressed HERVs between the two datasets. We also characterized the host differentially expressed genes and tested their association with the differentially expressed HERVs. We found that differentially expressed HERVs were significantly more physically proximal to host differentially expressed genes than non-differentially expressed HERVs. Finally, we capitalized on locus specific resolution of HERV mapping to identify key molecular pathways impacted by differential HERV expression in people with SLE.

A distinct B cell population marked by elevated CD11c expression is found in patients with systemic lupus erythematosus (SLE). Cells with a similar phenotype have been described during chronic infection, but variable gating strategies and nomenclature have led to uncertainty of their relationship to each other. We isolated CD11chi cells from peripheral blood and characterized them using transcriptome and IgH repertoire analyses. Gene expression data revealed the CD11chi IgD+ and IgD− subsets were highly similar to each other, but distinct from naive, memory, and plasma cell subsets. Although CD11chi B cells were enriched in some germinal center (GC) transcripts and expressed numerous negative regulators of B cell receptor (BCR) activation, they were distinct from GC B cells. Gene expression patterns from SLE CD11chi B cells were shared with other human diseases, but not with mouse age-associated B cells. IgH V-gene sequencing analysis showed IgD+ and IgD− CD11chi B cells had somatic hypermutation and were clonally related to each other and to conventional memory and plasma cells. However, the IgH repertoires expressed by the different subsets suggested that defects in negative selection during GC transit could contribute to autoimmunity. The results portray a pervasive B cell population that accumulates during autoimmunity and chronic infection and is refractory to BCR signaling.

Autoimmune diseases, such as systemic lupus erythematosus, are characterized by excessive inflammation in response to self-antigens. Loss of appropriate immunoregulatory mechanisms contribute to disease exacerbation. We previously showed the suppressive effect of vancomycin treatment during the “active-disease” stage of lupus. In this study, we sought to understand the effect of the same treatment given before disease onset. To develop a model in which to test the regulatory role of the gut microbiota in modifying autoimmunity, we treated lupus-prone mice with vancomycin in the period before disease development (3–8 weeks of age). We found that administration of vancomycin to female MRL/lpr mice early, only during the pre-disease period but not from 3 to 15 weeks of age, led to disease exacerbation. Early vancomycin administration also reduced splenic regulatory B (Breg) cell numbers, as well as reduced circulating IL-10 and IL-35 in 8-week old mice. Further, we found that during the pre-disease period, administration of activated IL-10 producing Breg cells to mice treated with vancomycin suppressed lupus initiation, and that bacterial DNA from the gut microbiota was an inducer of Breg function. Oral gavage of bacterial DNA to mice treated with vancomycin increased Breg cells in the spleen and mesenteric lymph node at 8 weeks of age and reduced autoimmune disease severity at 15 weeks. This work suggests that a form of oral tolerance induced by bacterial DNA-mediated expansion of Breg cells suppress disease onset in the autoimmune-prone MRL/lpr mouse model. Future studies are warranted to further define the mechanism behind bacterial DNA promoting Breg cells.

Autoantibody production by plasma cells (PCs) plays a pivotal role in the pathogenesis of systemic lupus erythematosus (SLE). The molecular pathways by which B cells become pathogenic PC secreting autoantibodies in SLE are incompletely characterized. Histone deactylase 6 (HDAC6) is a unique cytoplasmic HDAC that modifies the interaction of a number of tubulin- associated proteins; inhibition of HDAC6 has been shown to be beneficial in murine models of SLE, but the downstream pathways accounting for the therapeutic benefit have not been clearly delineated. In the current study, we sought to determine whether selective HDAC6 inhibition would abrogate abnormal B cell activation in SLE. We treated NZB/W lupus mice with the selective HDAC6 inhibitor, ACY-738, for 4 weeks beginning at 20 weeks-of age. After only 4 weeks of treatment, manifestation of lupus nephritis (LN) were greatly reduced in these animals. We then used RNAseq to determine the genomic signatures of splenocytes from treated and untreated mice and applied computational cellular and pathway analysis to reveal multiple signaling events associated with B cell activation and differentiation in SLE that were modulated by HDAC6 inhibition. PC development was abrogated and germinal center (GC) formation was greatly reduced. When the HDAC6 inhibitor-treated lupus mouse gene signatures were compared to human lupus patient gene signatures, the results showed numerous immune, and inflammatory pathways increased in active human lupus were significantly decreased in the HDAC6 inhibitor treated animals. Pathway analysis suggested alterations in cellular metabolism might contribute to the normalization of lupus mouse spleen genomic signatures, and this was confirmed by direct measurement of the impact of the HDAC6 inhibitor on metabolic activities of murine spleen cells. Taken together, these studies show HDAC6 inhibition decreases B cell activation signaling pathways and reduces PC differentiation in SLE and suggest that a critical event might be modulation of cellular metabolism.

Autoimmune diseases (AID) such as systemic lupus erythematosus (SLE), primary Sjögren's syndrome (pSS), and rheumatoid arthritis (RA) are chronic inflammatory diseases in which abnormalities of B cell function play a central role. Although it is widely accepted that autoimmune B cells are hyperactive in vivo, a full understanding of their functional status in AID has not been delineated. Here, we present a detailed analysis of the functional capabilities of AID B cells and dissect the mechanisms underlying altered B cell function. Upon BCR activation, decreased spleen tyrosine kinase (Syk) and Bruton's tyrosine kinase (Btk) phosphorylation was noted in AID memory B cells combined with constitutive co-localization of CD22 and protein tyrosine phosphatase (PTP) non-receptor type 6 (SHP-1) along with hyporesponsiveness to TLR9 signaling, a Syk-dependent response. Similar BCR hyporesponsiveness was also noted specifically in SLE CD27− B cells together with increased PTP activities and increased transcripts for PTPN2, PTPN11, PTPN22, PTPRC, and PTPRO in SLE B cells. Additional studies revealed that repetitive BCR stimulation of normal B cells can induce BCR hyporesponsiveness and that tissue-resident memory B cells from AID patients also exhibited decreased responsiveness immediately ex vivo, suggesting that the hyporesponsive status can be acquired by repeated exposure to autoantigen(s) in vivo. Functional studies to overcome B cell hyporesponsiveness revealed that CD40 co-stimulation increased BCR signaling, induced proliferation, and downregulated PTP expression (PTPN2, PTPN22, and receptor-type PTPs). The data support the conclusion that hyporesponsiveness of AID and especially SLE B cells results from chronic in vivo stimulation through the BCR without T cell help mediated by CD40–CD154 interaction and is manifested by decreased phosphorylation of BCR-related proximal signaling molecules and increased PTPs. The hyporesponsiveness of AID B cells is similar to a form of functional anergy.

Systemic lupus erythematosus (SLE) is characterized by abnormalities in B cell and T cell function, but the role of disturbances in the activation status of macrophages (Mϕ) has not been well described in human patients. To address this, gene expression profiles from isolated lymphoid and myeloid populations were analyzed to identify differentially expressed (DE) genes between healthy controls and patients with either inactive or active SLE. While hundreds of DE genes were identified in B and T cells of active SLE patients, there were no DE genes found in B or T cells from patients with inactive SLE compared to healthy controls. In contrast, large numbers of DE genes were found in myeloid cells (MC) from both active and inactive SLE patients. Among the DE genes were several known to play roles in Mϕ activation and polarization, including the M1 genes STAT1 and SOCS3 and the M2 genes STAT3, STAT6, and CD163. M1-associated genes were far more frequent in data sets from active versus inactive SLE patients. To characterize the relationship between Mϕ activation and disease activity in greater detail, weighted gene co-expression network analysis (WGCNA) was used to identify modules of genes associated with clinical activity in SLE patients. Among these were disease activity-correlated modules containing activation signatures of predominantly M1-associated genes. No disease activity-correlated modules were enriched in M2-associated genes. Pathway and upstream regulator analysis of DE genes from both active and inactive SLE MC were cross-referenced with high-scoring hits from the drug discovery Library of Integrated Network-based Cellular Signatures (LINCS) to identify new strategies to treat both stages of SLE. A machine learning approach employing MC gene modules and a generalized linear model was able to predict the disease activity status in unrelated gene expression data sets. In summary, altered MC gene expression is characteristic of both active and inactive SLE. However, disease activity is associated with an alteration in the activation of MC, with a bias toward the M1 proinflammatory phenotype. These data suggest that while hyperactivity of B cells and T cells is associated with active SLE, MC potentially direct flare-ups and remission by altering their activation status toward the M1 state.

The liquid chromatography-high resolution mass spectrometry (LC-HRMS) technique enables the detection of phytochemicals present in the extracts. LC-HRMS-generated mass list showed abundant compounds of interest, artifacts, and primary metabolites. The identification of a secondary metabolite of interest within the extract is very challenging. We hypothesized that identifying the "new metabolite" in the whole metabolome is more challenging than identifying it within the class of metabolites. The proposed prioritization strategy focused on the elimination of unknown and prioritizing the known class of secondary metabolites to identify new metabolites. The prioritization strategy demonstrated on Murraya paniculata for the identification of new metabolites. LC-HRMS-generated information is used as a filter to target the secondary metabolite and the new metabolites. This strategy successfully annotated the new coumarin and coumarin alkaloids from the mass list of 1448 metabolites. Varanasine ( 3 ), schroffanone ( 4 ), schroffanene ( 5 ), and O -methylmurraol ( 9 ) are new compounds, and coumarin ( 1 , 2 , and 6-8 ) are known. Varanasine ( 3 ) is the first naturally occurring 7-aminocoumarin with additional N -formyl functionality. The isolates were screened for cytotoxicity against the panel of cancer cell lines. Varanasine ( 3 ) and minumicrollin ( 6 ) showed significant cytotoxicity and apoptosis-inducing potential. The immunoblot analysis confirmed inhibition of apoptotic protein PARP-1 and caspase-3 expression by 3 and 6 .