Alternative splicing and intron retention: Their profiles and roles in cutaneous fibrosis of systemic sclerosis.

BACKGROUND: Alternative splicing (AS) and intron retention (IR) implicated in multiple pathophysiological processes, have rarely been reported in systemic sclerosis (SSc). METHODS: We integrated bulk RNA-seq and 4D label-free mass spectrometry to perform a multi-omics analysis of AS and IR in SSc skin tissue and fibroblasts. RMATS and iREAD were used to identify AS and IR, which were validated by real-time PCR. Spearman correlation and the LASSO method were employed to assess correlations among clinical features, introns, splicing factors (regulators of AS) and proteins. FINDINGS: AS profiles showed distinct alterations in SSc skin tissue, with the most pronounced changes occurring in IR. AS and IR were associated with total modified Rodnan skin score (mRSS) and local skin score. Upon TGF-ß stimulation, fibroblasts exhibited significant alterations in IR profiles, affecting genes related to fibroblast proliferation and collagen fibril organization. A comprehensive integrated analysis of introns, exons, and proteome profiles revealed that IR exerted a negative impact on protein expression, with certain changes being under intronic control. RT-PCR confirmed the presence of intron and exon-derived sequences of CTTN, OGA, MED16 and PHYKPL. Additionally, notable changes were observed in the regulatory network of splicing factors in SSc skin tissues. These factors are also involved in fibrosis pathways and correlated with clinical features. CONCLUSION: Totally, abnormal AS, IR profiles and splicing factors were identified in SSc, altered IRs and splicing factors participated in fibrosis-related pathways. IR exerted a negative impact on protein expression in TGF-ß-stimulated fibroblasts. Clarification of the IR mechanisms will provide new insights into the pathophysiology of SSc.

Contributions of Immune Cells and Stromal Cells to the Pathogenesis of Systemic Sclerosis: Recent Insights.

Systemic sclerosis (SSc) is a multisystem rheumatic disease characterized by vascular dysfunction, autoimmune abnormalities, and progressive organ fibrosis. A series of studies in SSc patients and fibrotic models suggest that immune cells, fibroblasts, and endothelial cells participate in inflammation and aberrant tissue repair. Furthermore, the growing number of studies on single-cell RNA sequencing (scRNA-seq) technology in SSc elaborate on the transcriptomics and heterogeneities of these cell subsets significantly. In this review, we summarize the current knowledge regarding immune cells and stromal cells in SSc patients and discuss their potential roles in SSc pathogenesis, focusing on recent advances in the new subtypes by scRNA-seq.

Malicious Network Behavior Detection Using Fusion of Packet Captures Files and Business Feature Data.

Information and communication technologies have essential impacts on people's life. The real time convenience of the internet greatly facilitates the information transmission and knowledge exchange of users. However, network intruders utilize some communication holes to complete malicious attacks. Some traditional machine learning (ML) methods based on business features and deep learning (DL) methods extracting features automatically are used to identify these malicious behaviors. However, these approaches tend to use only one type of data source, which can result in the loss of some features that can not be mined in the data. In order to address this problem and to improve the precision of malicious behavior detection, this paper proposed a one-dimensional (1D) convolution-based fusion model of packet capture files and business feature data for malicious network behavior detection. Fusion models improve the malicious behavior detection results compared with single ones in some available network traffic and Internet of things (IOT) datasets. The experiments also indicate that early data fusion, feature fusion and decision fusion are all effective in the model. Moreover, this paper also discusses the adaptability of one-dimensional convolution and two-dimensional (2D) convolution to network traffic data.

PKM2-dependent glycolysis promotes skeletal muscle cell pyroptosis by activating the NLRP3 inflammasome in dermatomyositis/polymyositis.

OBJECTIVES: Muscle cell necrosis is the most common pathological manifestation of idiopathic inflammatory myopathies. Evidence suggests that glycolysis might participate in it. However, the mechanism is unclear. This study aimed to determine the role of glycolysis in the muscle damage that occurs in DM/PM. METHODS: Mass spectrometry was performed on muscle lesions from DM/PM and control subjects. The expression levels of pyruvate kinase isozyme M2 (PKM2), the nucleotide-binding and oligomerization domain-like receptor family pyrin domain containing 3 (NLRP3) inflammasome and pyroptosis-related genes in muscle tissues or plasma were determined by real-time PCR, western blot analysis, IF and ELISA. In addition, IFNγ was used to stimulate myotubes, and the relationships among PMK2 expression, NLRP3 inflammasome activation and pyroptosis were investigated. RESULTS: Mass spectrometry and bioinformatics analysis suggested that multiple glycolysis processes, the NLRP3 inflammasome and programmed cell death pathway-related proteins were dysregulated in the muscle tissues of DM/PM. PKM2 and the NLRP3 inflammasome were upregulated and positively correlated in the muscle fibres of DM/PM. Moreover, the pyroptosis-related proteins were increased in muscle tissues of DM/PM and were further increased in PM. The levels of PKM2 in muscle tissues and IL-1ß in plasma were high in patients with anti-signal recognition particle autoantibody expression. The pharmacological inhibition of PKM2 in IFNγ-stimulated myotubes attenuated NLRP3 inflammasome activation and subsequently inhibited pyroptosis. CONCLUSION: Our study revealed upregulated glycolysis in the lesioned muscle tissues of DM/PM, which activated the NLRP3 inflammasome and leaded to pyroptosis in muscle cells. The levels of PKM2 and IL-1ß were high in patients with anti-signal recognition particle autoantibody expression. These proteins might be used as new biomarkers for muscle damage.

Global analysis of protein expression in muscle tissues of dermatomyositis/polymyosisits patients demonstrated an association between dysferlin and human leucocyte antigen A.

OBJECTIVES: DM and PM are characterized by myofibre damage with inflammatory cell infiltration due to the strong expressions of MHC class I HLA-A and monocyte chemoattractant protein-1 (MCP-1). Dysferlin (DYSF) is a transmembrane glycoprotein that anchors in the sarcolemma of myofibres. DYSF mutation is closely associated with inherited myopathies. This study aimed to determine the role of DYSF in the development of DM/PM. METHODS: Mass spectrometry was performed in muscle tissues from DM/PM patients and controls. The DYSF levels in muscle tissue, peripheral blood cells and serum were detected by Western blotting, IF, flow cytometry or ELISA. Double IF and co-immunoprecipitation were used to investigate the relationship between DYSF and HLA-A. RESULTS: Mass spectrometry and bioinformatics analysis findings suggested the dysregulated proteins in DM/PM patients participated in common biological processes and pathways, such as the generation of precursor metabolites and energy. DYSF was upregulated in the muscle tissue and serum of DM/PM patients. DYSF was mainly expressed in myofibres and co-localized with HLA-A and MCP-1. DYSF and HLA-A expressions were elevated in myocytes and endothelial cells after being stimulated by patient serum and IFN-ß. However, no direct interactions were found between DYSF and HLA-A by co-immunoprecipitation. CONCLUSION: Our study revealed the dysregulated proteins involved in common and specific biological processes in DM/PM patient samples. DYSF is upregulated and exhibits a potential role along with that of HLA-A and MCP-1 in inflammatory cell infiltration and muscle damage during the development of DM/PM.