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Ubiquitin stress-induced NEDDylation leads to the formation of aggresome-like bodies (ALBs) in the perinuclear region of cells. Therefore, imaging analysis is essential for characterizing the biological phenotypes of ALBs. Here, we describe a protocol to monitor ALBs induced by ubiquitin stress using immunocytochemistry and to quantify cells containing ALBs. This optimized protocol details the use of readily available materials and reagents and can be applied to explore diverse molecules involved in stress-induced ALBs. For complete details on the use and execution of this protocol, please refer to Kim et al. (2021).In many biological applications, the readout of somatic mutations in individual cells is essential. For example, it can be used to mark individual cancer cells or identify progenies of a stem cell. Here, we present a protocol to perform single-cell RNA-seq and single-cell amplicon-seq using 10X Chromium technology. Our protocol demonstrates how to (1) isolate CD34+ progenitor cells from human bone marrow aspirate, (2) prepare single-cell amplicon libraries, and (3) analyze the libraries to assign somatic mutations to individual cells. For complete details on the use and execution of this protocol, please refer to Van Egeren et al. (2021).Exogenous overexpression of target genes in both general and specific cell types is important for mechanistic studies of gene function. Here, we provide a step-by-step protocol for cell culture, plasmid transfection in HEK293T, and adenoviral infection in C2C12 cells for gene overexpression in vitro, using MG53 as an example. This protocol enables sufficient and efficient gene expression for the downstream functional analysis. For complete details on the use and execution of this protocol, please refer to Jiang et al. (2021).The AMP-activated protein kinase (AMPK) is a principal nutrient sensor and a master regulator of cellular energy homeostasis. Once activated, AMPK induces glucose uptake, which leads to a transient decrease in blood glucose level and can be used as an indicator of AMPK activity. Here, we present a protocol accessing AMPK activity in mice by measuring glucose uptake induced by AMPK activators, MK8722 and A769662. This protocol can be used to evaluate AMPK signaling in vivo under various pathophysiological conditions. For complete details on the use and execution of this protocol, please refer to Jiang et al. (2021).Bladder dysfunction, including incontinence, difficulty emptying the bladder, or urgency to urinate is a pervasive health and quality of life concern. However, risk factors for developing these symptoms are not completely understood, and the influence of exposure to environmental chemicals, especially during development, on the formation and function of the bladder is understudied. Environmental contaminants such as polychlorinated biphenyls (PCBs) are known to pose a risk to the developing brain; however, their influence on the development of peripheral target organs, such as bladder, are unknown. To address this data gap, C57Bl/6J mouse dams were exposed to an environmentally-relevant PCB mixture at 0, 0.1, 1 or 6 mg/kg daily beginning two weeks prior to mating and continuing through gestation and lactation. Bladders were collected from offspring at postnatal days (P) 28-31. PCB concentrations were detected in bladders in a dose-dependent manner. PCB effects on the bladder were sex- and dose-dependent. Overbladder volume in male mice.ESX-1 is a major virulence factor of Mycobacterium tuberculosis, a secretion machinery directly involved in the survival of the microorganism from the immune system defence. It disrupts the phagosome membrane of the host cell through a contact-dependent mechanism. Recently, the structure of the inner-membrane core complex of the homologous ESX-3 and ESX-5 was resolved; however, the elements involved in the secretion through the outer membrane or those acting on the host cell membrane are unknown. Protein substrates might form this missing element. Here, we describe the oligomerisation process of the ESX-1 substrate EspB, which occurs upon cleavage of its C-terminal region and is favoured by an acidic environment. Cryo-electron microscopy data shows that quaternary structure of EspB is conserved across slow growing species, but not in the fast growing M. JAK drugs smegmatis. EspB assembles into a channel with dimensions and characteristics suitable for the transit of ESX-1 substrates, as shown by the presence of another EspB trapped within. Our results provide insight into the structure and assembly of EspB, and suggests a possible function as a structural element of ESX-1.Log messages are widely used in cloud servers and other systems. Millions of logs are generated each day which makes them important for anomaly detection. However, they are complex unstructured text messages which makes this task difficult. In this paper, a hybrid log message anomaly detection technique is proposed which employs pruning of positive and negative logs. Reliable positive log messages are first selected using a Gaussian mixture model algorithm. Then reliable negative logs are selected using the K-means, Gaussian mixture model and Dirichlet process Gaussian mixture model methods iteratively. It is shown that the precision for positive and negative logs with pruning is high. Anomaly detection is done using a deep learning long short-term memory network. The proposed model is evaluated using the well-known BGL, Openstack, and Thunderbird data sets. The results obtained indicate that the proposed model performs better than several well-known algorithms.The Coronavirus Disease 2019 (COVID-19) which first emerged in Wuhan, China in late December, 2019, has now spread to all the countries in the world. Conventional testing methods such as the antigen test, serology tests, and polymerase chain reaction tests are widely used. However, the test results can take anything from a few hours to a few days to reach the patient. Chest CT scan images have been used as alternatives for the detection of COVID-19 infection. Use of CT scan images alone might have limited capabilities, which calls attention to incorporating clinical features. In this paper, deep learning algorithms have been utilized to integrate the chest CT scan images obtained from patients with their clinical characteristics for fast and accurate diagnosis of COVID-19 patients. The framework uses an ANN to obtain the probability of the patient being infected with COVID-19 using their clinical information. Beyond a certain threshold, the chest CT scan of the patient is classified using a deep learning model which has been trained to classify the CT scan with 99% accuracy.Recently, the destructive impact of Coronavirus 2019, commonly known as COVID-19, has affected public health and human lives. This catastrophic effect disrupted human experience by introducing an exponentially more damaging unpredictable health crisis since the Second World War (Kursumovic et al. in Anaesthesia 75 989-992, 2020). Strong communicable characteristics of COVID-19 within human communities make the world's crisis a severe pandemic. Due to the unavailable vaccine of COVID-19 to control rather than cure, early and accurate detection of the virus can be a promising technique for tracking and preventing the infection from spreading (e.g., by isolating the patients). This situation indicates improving the auxiliary COVID-19 detection technique. Computed tomography (CT) imaging is a widely used technique for pneumonia because of its expected availability. The artificial intelligence-aided images analysis might be a promising alternative for identifying COVID-19. This paper presents a promising technique of predicting COVID-19 patients from the CT image using convolutional neural networks (CNN). The novel approach is based on the most recent modified CNN architecture (DenseNet-121) to predict COVID-19. The results outperformed 92% accuracy, with a 95% recall showing acceptable performance for the prediction of COVID-19.

This review aims to summarize the current knowledge of the extracellular matrix remodeling during hepatic fibrosis. We discuss the diverse interactions of the extracellular matrix with hepatic cells and the surrounding matrix in liver fibrosis, with the focus on the molecular pathways and the mechanisms that regulate extracellular matrix remodeling.

The extracellular matrix not only provides structure and support for the cells, but also controls cell behavior by providing adhesion signals and by acting as a reservoir of growth factors and cytokines.

Hepatic fibrosis is characterized by an excessive accumulation of extracellular matrix. During fibrogenesis, the natural remodeling process of the extracellular matrix varies, resulting in the excessive accumulation of its components, mainly collagens. Signals released by the extracellular matrix induce the activation of hepatic stellate cells, which are the major source of extracellular matrix and most abundant myofibroblasts in the liver.

The common view of emotional expressions is that certain configurations of facial-muscle movements reliably reveal certain categories of emotion. The principal exemplar of this view is the Duchenne smile, a configuration of facial-muscle movements (i.e., smiling with eye constriction) that has been argued to reliably reveal genuine positive emotion. In this paper, we formalized a list of hypotheses that have been proposed regarding the Duchenne smile, briefly reviewed the literature weighing on these hypotheses, identified limitations and unanswered questions, and conducted two empirical studies to begin addressing these limitations and answering these questions. Both studies analyzed a database of 751 smiles observed while 136 participants completed experimental tasks designed to elicit amusement, embarrassment, fear, and physical pain. Study 1 focused on participants' self-reported positive emotion and Study 2 focused on how third-party observers would perceive videos of these smiles. Most of the hypotheses that have been proposed about the Duchenne smile were either contradicted by or only weakly supported by our data. Eye constriction did provide some information about experienced positive emotion, but this information was lacking in specificity, already provided by other smile characteristics, and highly dependent on context. Eye constriction provided more information about perceived positive emotion, including some unique information over other smile characteristics, but context was also important here as well. Overall, our results suggest that accurately inferring positive emotion from a smile requires more sophisticated methods than simply looking for the presence/absence (or even the intensity) of eye constriction.

The impact of biologic aging on immune checkpoint inhibitor (ICI) toxicity and efficacy is underexplored in metastatic melanoma (MM). In peripheral blood T-lymphocytes (PBTLs), biologic aging is characterized by changes in T-cell composition and cellular senescence. Whether indicators of PBTL biologic aging vary in MM patients or can be used to predict premature ICI discontinuation (pID) is unknown.

We prospectively collected PBTLs from 117 cancer-free controls and 46 MM patients scheduled to begin pembrolizumab or nivolumab monotherapy. 74 mRNAs indicative of T-cell subsets, activation, co-stimuation/inhibition and cellular senescence were measured by Nanostring. Relationships between each mRNA and chronologic age were assessed in patients and controls. Candidate biomarkers were identified by calculating the hazard ratio (HR) for pID in patients divided into low and high groups based on log-transformed mRNA levels or the magnitude by which each mRNA measurement deviated from the control trend (Δage). Area under the curve (AUC) analyses explored the ability of each biomarker to discriminate between patients with and without pID at 6 months and 1 year.