Critical Discussion on the Relationship between Failure Occurrence and Severity Using Reliability Functions

In today's competitive world, the basis of many maintenance decisions is their associated risk and this parameter is directly related to occurrence and severity of failures. In this paper, the relationship between the two parameters has been investigated for which, reliability functions has been used. The results imply that this relationship is not compatible with the traditional diagram used in risk analysis approaches such as Failure Modes and Effects Analysis (FMEA) and respectively, decision making based on existing approaches might be risky. Key words: Diagram; Severity; Occurrence; Risk; FMEA; Reliability functio

Persian topic detection based on Human Word association and graph embedding

In this paper, we propose a framework to detect topics in social media based on Human Word Association. Identifying topics discussed in these media has become a critical and significant challenge. Most of the work done in this area is in English, but much has been done in the Persian language, especially microblogs written in Persian. Also, the existing works focused more on exploring frequent patterns or semantic relationships and ignored the structural methods of language. In this paper, a topic detection framework using HWA, a method for Human Word Association, is proposed. This method uses the concept of imitation of mental ability for word association. This method also calculates the Associative Gravity Force that shows how words are related. Using this parameter, a graph can be generated. The topics can be extracted by embedding this graph and using clustering methods. This approach has been applied to a Persian language dataset collected from Telegram. Several experimental studies have been performed to evaluate the proposed framework's performance. Experimental results show that this approach works better than other topic detection methods

A Human Word Association based model for topic detection in social networks

With the widespread use of social networks, detecting the topics discussed in these networks has become a significant challenge. The current works are mainly based on frequent pattern mining or semantic relations, and the language structure is not considered. The meaning of language structural methods is to discover the relationship between words and how humans understand them. Therefore, this paper uses the Concept of the Imitation of the Mental Ability of Word Association to propose a topic detection framework in social networks. This framework is based on the Human Word Association method. A special extraction algorithm has also been designed for this purpose. The performance of this method is evaluated on the FA-CUP dataset. It is a benchmark dataset in the field of topic detection. The results show that the proposed method is a good improvement compared to other methods, based on the Topic-recall and the keyword F1 measure. Also, most of the previous works in the field of topic detection are limited to the English language, and the Persian language, especially microblogs written in this language, is considered a low-resource language. Therefore, a data set of Telegram posts in the Farsi language has been collected. Applying the proposed method to this dataset also shows that this method works better than other topic detection methods

A Role for IFITM Proteins in Restriction of Mycobacterium tuberculosis Infection

SummaryThe interferon (IFN)-induced transmembrane (IFITM) proteins are critical mediators of the host antiviral response. Here, we expand the role of IFITM proteins to host defense against intracellular bacterial infection by demonstrating that they restrict Mycobacterium tuberculosis (MTb) intracellular growth. Simultaneous knockdown of IFITM1, IFITM2, and IFITM3 by RNAi significantly enhances MTb growth in human monocytic and alveolar/epithelial cells, whereas individual overexpression of each IFITM impairs MTb growth in these cell types. Furthermore, MTb infection, Toll-like receptor 2 and 4 ligands, and several proinflammatory cytokines induce IFITM1–3 gene expression in human myeloid cells. We find that IFITM3 co-localizes with early and, in particular, late MTb phagosomes, and overexpression of IFITM3 enhances endosomal acidification in MTb-infected monocytic cells. These findings provide evidence that the antiviral IFITMs participate in the restriction of mycobacterial growth, and they implicate IFITM-mediated endosomal maturation in its antimycobacterial activity

HIV-1 Replication Is Differentially Regulated by Distinct Clinical Strains of Mycobacterium tuberculosis

(MTb), the causative agent of TB, are known to modify the host immune response in a strain-specific manner. However, a MTb strain-specific impact upon the regulation of HIV-1 replication has not previously been established.. Furthermore, we show that the distinct pattern of CDC1551 or HN878 induced HIV-1 replication is associated with significantly increased levels of TNF and IL-6, and of the transcription and nuclear translocation of the p65 subunit of the transcription factor NF-κB, by CDC1551 relative to HN878.These results provide a precedent for TB strain-specific effects upon HIV-1 replication and thus for TB strain-specific pathogenesis in the outcome of HIV-1/TB co-infection. MTb strain-specific factors and mechanisms involved in the regulation of HIV-1 during co-infection will be of importance in understanding the basic pathogenesis of HIV-1/TB co-infection

The use of HaloTag-based technology in flow and laser scanning cytometry analysis of live and fixed cells

<p>Abstract</p> <p>Background</p> <p>Combining the technologies of protein tag labeling and optical microscopy allows sensitive analysis of protein function in cells.</p> <p>Findings</p> <p>Here, we describe development of applications using protein tag technology (HaloTag (HT)-based) for flow and laser scanning cytometry (LSC). Cell lines, expressing recombinant surface β1-integrin-HT and HT-p65 fusion protein, and a CD4 T cell line (Jurkat) infected with human immunodeficiency virus type 1 (HIV-1) reporter virus expressing the unfused HT (HIV-1_Lai-Halo), were stained with different HT ligands and successfully detected by flow cytometers equipped with 488 and 561 nm lasers as well as a laser scanning cytometer (equipped with 488 and 405 nm lasers) alone or combined with cell cycle and viability markers.</p> <p>Conclusions</p> <p>Use of HT technology for cytometric applications has advantages over its use in microscopy as it allows for the statistical measurement of protein expression levels in individual cells within a heterogeneous cell population in combination with cell cycle analysis. Another advantage is the ability of the HaloTag to withstand long fixation and high concentration of fixative, which can be useful in research of infectious agents like HIV and/or mycobacteria.</p

NFAT5 Regulates HIV-1 in Primary Monocytes via a Highly Conserved Long Terminal Repeat Site

To replicate, HIV-1 capitalizes on endogenous cellular activation pathways resulting in recruitment of key host transcription factors to its viral enhancer. RNA interference has been a powerful tool for blocking key checkpoints in HIV-1 entry into cells. Here we apply RNA interference to HIV-1 transcription in primary macrophages, a major reservoir of the virus, and specifically target the transcription factor NFAT5 (nuclear factor of activated T cells 5), which is the most evolutionarily divergent NFAT protein. By molecularly cloning and sequencing isolates from multiple viral subtypes, and performing DNase I footprinting, electrophoretic mobility shift, and promoter mutagenesis transfection assays, we demonstrate that NFAT5 functionally interacts with a specific enhancer binding site conserved in HIV-1, HIV-2, and multiple simian immunodeficiency viruses. Using small interfering RNA to ablate expression of endogenous NFAT5 protein, we show that the replication of three major HIV-1 viral subtypes (B, C, and E) is dependent upon NFAT5 in human primary differentiated macrophages. Our results define a novel host factor–viral enhancer interaction that reveals a new regulatory role for NFAT5 and defines a functional DNA motif conserved across HIV-1 subtypes and representative simian immunodeficiency viruses. Inhibition of the NFAT5–LTR interaction may thus present a novel therapeutic target to suppress HIV-1 replication and progression of AIDS

Regulation of Mycobacterium tuberculosis-Dependent HIV-1 Transcription Reveals a New Role for NFAT5 in the Toll-Like Receptor Pathway

Tuberculosis (TB) disease in HIV co-infected patients contributes to increased mortality by activating innate and adaptive immune signaling cascades that stimulate HIV-1 replication, leading to an increase in viral load. Here, we demonstrate that silencing of the expression of the transcription factor nuclear factor of activated T cells 5 (NFAT5) by RNA interference (RNAi) inhibits Mycobacterium tuberculosis (MTb)-stimulated HIV-1 replication in co-infected macrophages. We show that NFAT5 gene and protein expression are strongly induced by MTb, which is a Toll-like receptor (TLR) ligand, and that an intact NFAT5 binding site in the viral promoter of R5-tropic HIV-1 subtype B and subtype C molecular clones is required for efficent induction of HIV-1 replication by MTb. Furthermore, silencing by RNAi of key components of the TLR pathway in human monocytes, including the downstream signaling molecules MyD88, IRAK1, and TRAF6, significantly inhibits MTb-induced NFAT5 gene expression. Thus, the innate immune response to MTb infection induces NFAT5 gene and protein expression, and NFAT5 plays a crucial role in MTb regulation of HIV-1 replication via a direct interaction with the viral promoter. These findings also demonstrate a general role for NFAT5 in TLR- and MTb-mediated control of gene expression

FcγR-mediated SARS-CoV-2 infection of monocytes activates inflammation

SARS-CoV-2 can cause acute respiratory distress and death in some patients1. Although severe COVID-19 disease is linked to exuberant inflammation, how SARS-CoV-2 triggers inflammation is not understood2. Monocytes and macrophages are sentinel cells that sense invasive infection to form inflammasomes that activate caspase-1 and gasdermin D (GSDMD), leading to inflammatory death (pyroptosis) and release of potent inflammatory mediators3. Here we show that about 6% of blood monocytes in COVID-19 patients are infected with SARS-CoV-2. Monocyte infection depends on uptake of antibody-opsonized virus by Fcγ receptors. Vaccine recipient plasma does not promote antibody-dependent monocyte infection. SARS-CoV-2 begins to replicate in monocytes, but infection is aborted, and infectious virus is not detected in infected monocyte culture supernatants. Instead, infected cells undergo inflammatory cell death (pyroptosis) mediated by activation of NLRP3 and AIM2 inflammasomes, caspase-1 and GSDMD. Moreover, tissue-resident macrophages, but not infected epithelial and endothelial cells, from COVID-19 lung autopsies have activated inflammasomes. These findings taken together suggest that antibody-mediated SARS-CoV-2 uptake by monocytes/macrophages triggers inflammatory cell death that aborts production of infectious virus but causes systemic inflammation that contributes to COVID-19 pathogenesis