Explore the vast range of titles available.

B cells and the humoral immunity are important players in the pathogenesis of autoimmune diseases. BAFF (also known as BLYS) and a proliferation-inducing ligand APRIL are required for the maintenance of the B-cell pool and humoral immunity. BAFF and APRIL can promote B-cell differentiation, maturation, and plasma cell antibody secretion. BAFF/APRIL overexpression has been identified in several autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, IgA nephropathy, etc. Telitacicept, a novel fully human TACI-Fc fusion protein that binds both BAFF and APRIL, was approved in China in March 2021 for the treatment of systemic lupus erythematosus at a recommended dose of 160 mg/w subcutaneously and is in clinical trials for the treatment of multiple indications in other autoimmune diseases. In this review, we explored telitacicept’s mechanism of action and clinical data. In addition, the immune features of autoimmune nephropathy were discussed, emphasizing lupus nephritis, IgA nephropathy, and membranous nephropathy.

The modulation classification technology for radar intra-pulse signals is important in the electronic countermeasures field. As the high quality labeled radar signals are difficult to be captured in the real applications, the signal modulation classification base on the limited number of labeled samples is playing a more and more important role. To relieve the requirement of the labeled samples, many self-supervised learning (SeSL) models exist. However, as they cannot fully explore the information of the labeled samples and rely significantly on the unlabeled samples, highly time-consuming processing of the pseudo-labels of the unlabeled samples is caused. To solve these problems, a supervised learning (SL) model, using the contrastive learning (CL) method (SL-CL), is proposed in this paper, which achieves a high classification accuracy, even adopting limited number of labeled training samples. The SL-CL model uses a two-stage training structure, in which the CL method is used in the first stage to effectively capture the features of samples, then the multilayer perceptron is applied in the second stage for the classification. Especially, the supervised contrastive loss is constructed to fully exploring the label information, which efficiently increases the classification accuracy. In the experiments, the SL-CL outperforms the comparison models in the situation of limited number of labeled samples available, which reaches 94% classification accuracy using 50 samples per class at 5 dB SNR.

High-mobility group box-1 (HMGB1), a ubiquitous nuclear protein, acts as a late mediator of lethality when released extracellularly during sepsis. The major source of circulating HMGB1 in sepsis is hepatocytes. However, the mechanism of HMGB1 release of hepatocytes during sepsis is not very clear. We have previously shown that bacterial endotoxin [lipopolysaccharide (LPS)] sensing pathways, including Toll-like receptor (TLR)4 and caspase-11, regulate hepatocyte HMGB1 release in response to LPS. Here, we report the novel function of caspase-11 and gasdermin D (GsdmD) in LPS-induced active HMGB1 released from hepatocytes. HMGB1 release during endotoxemia was caspase-11/GsdmD dependent via an active way and . Caspase-11/GsdmD was responsible for HMGB1 translocation from nucleus to the cytoplasm via calcium changing-induced phosphorylation of calcium-calmodulin kinase kinase (camkk)β during endotoxemia. Cleaved GsdmD accumulated on the endoplasmic reticulum, suggesting this may lead to calcium leak and intracellular calcium increase. Furthermore, we investigated that exosome was an important pathway for HMGB1 release from hepatocytes; this process was dependent on TLR4, independent of caspase-11 and GsdmD and . These findings provide a novel mechanism that TLR4 signaling results in an increase in caspase-11 expression, as well as increased exosome release, while caspase-11/GsdmD activation/cleavage leads to accumulation of HMGB1 in the cytoplasm through a process associated with the release of calcium from the endoplasmic reticulum and camkkβ activation.

Nonalcoholic fatty liver disease (NAFLD) is the liver manifestation of metabolic syndrome and is the most common chronic liver disease in the world. The pathogenesis of NAFLD has not been fully clarified; it involves metabolic disturbances, inflammation, oxidative stress, and various forms of cell death. The “intestinal-liver axis” theory, developed in recent years, holds that there is a certain relationship between liver disease and the intestinal tract, and changes in intestinal flora are closely involved in the development of NAFLD. Many studies have found that the intestinal flora regulates the pathogenesis of NAFLD by affecting energy metabolism, inducing endotoxemia, producing endogenous ethanol, and regulating bile acid and choline metabolism. In this review, we highlighted the updated discoveries in intestinal flora dysregulation and their link to the pathogenesis mechanism of NAFLD and summarized potential treatments of NAFLD related to the gut microbiome.

Objective: Internet addiction has emerged as a growing concern worldwide. This study aimed to compare the prevalence of Internet addiction between left-behind children (LBC) and non-left-behind children (non-LBC), and explore the role of paternal and maternal parent-child communication on LBC. Methods: We conducted a cross-sectional survey in rural areas in Anhui, China. The complete data were available from 699 LBC and 740 non-LBC. Multivariable logistic regression was used to examine 1) whether LBC were more likely to develop Internet addiction, and 2) the association between parent-child communication and Internet addiction among LBC. Results: LBC had a higher likelihood to report Internet addiction when compared to non-LBC (OR = 2.03, 95%CI = 1.43–2.88, p < 0.001). Among LBC, parent-child communication (both mother-child and father-child) was protective factor for children’s Internet addiction. The role of mother-child communication played well among male LBC. Conclusions: The lack of parental supervision may lead to Internet addiction. It is highly recommended for migrant parents to improve the quality of communication with their children. Also, gender-matching effects should be considered in the relationship between children’s behavior and parental factors.

Background Global distributions and trends of the risk-attributable burdens of chronic obstructive pulmonary disease (COPD) have rarely been systematically explored. To guide the formulation of targeted and accurate strategies for the management of COPD, we analyzed COPD burdens attributable to known risk factors. Methods Using detailed COPD data from the Global Burden of Disease study 2019, we analyzed disability-adjusted life years (DALYs), years lived with disability (YLDs), years of life lost (YLLs), and deaths attributable to each risk factor from 1990 to 2019. Additionally, we calculated estimated annual percentage changes (EAPCs) during the study period. The population attributable fraction (PAF) and summary exposure value (SEV) of each risk factor are also presented. Results From 1990 to 2019, the age-standardized DALY and death rates of COPD attributable to smoking and household air pollution, occupational particles, secondhand smoke, and low temperature presented consistently declining trends in almost all socio-demographic index (SDI) regions. However, the decline in YLD was not as dramatic as that of the death rate. In contrast, the COPD burden attributable to ambient particulate matter, ozone, and high temperature exposure showed undesirable increasing trends in the low- and low-middle-SDI regions. In addition, the age-standardized DALY and death rates attributable to each risk factor except household air pollution and low temperature were the highest in the low-middle-SDI region. In 2019, the COPD burden attributable to smoking ambient particulate matter, ozone, occupational particles, low and high temperature was obviously greater in males than in females. Meanwhile, the most important risk factors for female varied across regions (low- and low-middle-SDI regions: household air pollution; middle-SDI region: ambient particles; high-middle- and high-SDI region: smoking). Conclusions Increasing trends of COPD burden attributable to ambient particulate matter, ozone, and high temperature exposure in the low-middle- and low-SDI regions call for an urgent need to implement specific and effective measures. Moreover, considering the gender differences in COPD burdens attributable to some risk factors such as ambient particulate matter and ozone with similar SEV, further research on biological differences between sexes in COPD and relevant policy-making of disease prevention are required.

The newly proposed term “metabolic dysfunction-associated fatty liver disease” (MAFLD) is replacing the old term “non-alcoholic fatty liver disease” (NAFLD) in many global regions, because it better reflects the pathophysiology and cardiometabolic implications of this common liver disease. The proposed change in terminology from NAFLD to MAFLD is not simply a single-letter change in an acronym, since MAFLD is defined by a set of specific and positive diagnostic criteria. In particular, the MAFLD definition specifically incorporates within the classification recognized cardiovascular risk factors. Although convincing evidence supports a significant association between both NAFLD and MAFLD, with increased risk of CVD morbidity and mortality, neither NAFLD nor MAFLD have received sufficient attention from the Cardiology community. In fact, there is a paucity of scientific guidelines focusing on this common and burdensome liver disease from cardiovascular professional societies. This Perspective article discusses the rationale and clinical relevance for Cardiologists of the newly proposed MAFLD definition.

Background: The impairment of neurite outgrowth is an early pathological hallmark underlying various neurodegenerative disorders. The promotion of neurite outgrowth was considered as a feasible strategy to treat neurodegenerative disorders. 9-Methylfascaplysin (9-MF), a marine-derived, bioactive compound, has exhibited multiple neuroprotective activities. Methods and Result: In this study, 9-MF at nanomolar concentrations promoted neurite outgrowth, upregulated the expression of growth-associated protein-43 (GAP-43), and increased the mitochondrial positive area with similar efficacy as retinoic acid in PC12 cells. 9-MF-associated differentiated expressed genes were enriched in mitochondria and synapse, forming a Rho-associated coiled-coil containing a protein kinase 2 (ROCK2)-centralized network. CMap analysis further identified positive connections between 9-MF-induced perturbation and perturbations caused by the inhibition of the ROCK2 pathway. Molecular docking analysis demonstrated a high binding affinity between 9-MF and ROCK2, indicating that 9-MF could inhibit ROCK2. Furthermore, 9-MF significantly reduced the phosphorylation of ROCK2 with a similar efficacy as fasudil, a ROCK2 inhibitor. Narciclasine, a known ROCK2 activator, almost completely abolished the effects of 9-MF on the induction of neurite outgrowth in PC12 cells. Conclusions: 9-MF effectively promoted neurite outgrowth possibly via the inhibition of ROCK2, providing supporting evidence that 9-MF might be developed as a novel neurological drug.

Background There has been an increasing prevalence of parental separation in China due to divorce or migration for work in recent decades. However, few studies have compared the impacts of these two types of separation on children’s mental health. This study aimed to investigate how parental divorce and parental migration impact children’s mental health and self-injurious thoughts and behaviors (SITB), while considering positive factors, including parent-adolescent communication and psychological resilience. Methods We randomly recruited participants in grades 5–8 from 18 schools in 2 counties in Anhui Province. A self-administered questionnaire was conducted to measure children’s mental health, SITB, parent-adolescent communication, psychological resilience, and socio-demographic characteristics. Results Data from 1026 children with both parents migrating (BLBC), 1322 children with one parent migrating (SLBC), 475 children living in a divorced family (DC) and 1160 children with non-migrating parents (NLBC) were included. Regression model results showed that, compared to the other three groups (BLBC, SLBC, NLBC), DC exhibited higher internalizing problems (p < 0.05), higher externalizing problems (p < 0.01), less prosocial behaviors (p < 0.05), and higher rates of suicidal ideation (SI) (p < 0.05) and non-suicidal self-injury (NSSI) behaviors (p < 0.05) when adjusting for social-demographic variables. However, when further adjusting for parent-adolescent communication and psychological resilience, DC no longer had higher levels of internalizing problems, externalizing problems, NSSI and SI than left-behind groups (BLBC, SLBC). Conclusions The experience of separation from divorced parents had stronger negative effects on the mental health of children than was observed in LBC. The Chinese government should design special policy frameworks that provide support to DC.

The existing research on deep learning for radar signal intra–pulse modulation classification is mainly based on supervised leaning techniques, which performance mainly relies on a large number of labeled samples. To overcome this limitation, a self–supervised leaning framework, contrastive learning (CL), combined with the convolutional neural network (CNN) and focal loss function is proposed, called CL––CNN. A two–stage training strategy is adopted by CL–CNN. In the first stage, the model is pretrained using abundant unlabeled time–frequency images, and data augmentation is used to introduce positive–pair and negative–pair samples for self–supervised learning. In the second stage, the pretrained model is fine–tuned for classification, which only uses a small number of labeled time–frequency images. The simulation results demonstrate that CL–CNN outperforms the other deep models and traditional methods in scenarios with Gaussian noise and impulsive noise–affected signals, respectively. In addition, the proposed CL–CNN also shows good generalization ability, i.e., the model pretrained with Gaussian noise–affected samples also performs well on impulsive noise–affected samples.