The Notch signaling pathway, known to be a highly conserved signaling pathway in embryonic development and adult tissue homeostasis, participates in cell fate decisions that include cellular ...differentiation, cell survival and cell death. However, other studies have shown that aberrant in Notch signaling is pro-tumorigenic, particularly in hepatocellular carcinoma (HCC). HCC is one of the most common malignant tumors in the world and has a high mortality rate. Growing evidence supports that Notch signaling plays a critical role in the development of HCC by regulating the tumor microenvironment, tumorigenesis, progression, angiogenesis, invasion and metastasis. Accordingly, overexpression of Notch is closely associated with poor prognosis in HCC. In this review, we focus on the pro-tumorigenic role of Notch signaling in HCC, summarize the current knowledge of Notch signaling and its role in HCC development, and outline the therapeutic potential of targeting Notch signaling in HCC.
Bridge local scour involves extremely complex interactions among the flow, the sediments, and the pier. Our understanding of the underlying mechanism, especially at the microscale, is far from ...complete. The newly emerged multiphase numerical simulation overcomes the technical limitations imposed on physical experiments. To advance knowledge of the sediment dynamics under turbulent junction flows, this paper employed a CFD-DEM two-way coupled numerical model to simulate the local scour behavior of uniform spherical mass particles around an oblong pier. In this coupled system, the flow phase was described as a continuum by a detached eddy simulation (DES) model, and motion of the discrete particles was governed by Newton’s laws of motion (DEM). The flow–sediment interactions were directly considered through the momentum exchange between the two phases. The two-way coupled model was shown to successfully capture microscopic sediment dynamics similar to those observed in the literature. Sediment grains in the bed-load layer were shown to be eroded in the form of sliding and saltation. The erosional forces acting on two representative target particles, together with their correspondent motions/trajectories, provide valuable insights into the mechanism that dictates the scour initiation.
Reactive oxygen species (ROS) production in phagocytes is a major defense mechanism against pathogens. However, the cellular self-protective mechanism against such potential damage from oxidative ...stress remains unclear. Here we show that the kinases Mst1 and Mst2 (Mst1/2) sense ROS and maintain cellular redox balance by modulating the stability of antioxidant transcription factor Nrf2. Site-specific ROS release recruits Mst1/2 from the cytosol to the phagosomal or mitochondrial membrane, with ROS subsequently activating Mst1/2 to phosphorylate kelch like ECH associated protein 1 (Keap1) and prevent Keap1 polymerization, thereby blocking Nrf2 ubiquitination and degradation to protect cells against oxidative damage. Treatment with the antioxidant N-acetylcysteine disrupts ROS-induced interaction of Mst1/2 with phagosomes or mitochondria, and thereby diminishes the Mst-Nrf2 signal. Consistently, loss of Mst1/2 results in increased oxidative injury, phagocyte ageing and death. Thus, our results identify the Mst-Nrf2 axis as an important ROS-sensing and antioxidant mechanism during an antimicrobial response.
Abstract
TLR4 signaling plays key roles in the innate immune response to microbial infection. Innate immune cells encounter different mechanical cues in both health and disease to adapt their ...behaviors. However, the impact of mechanical sensing signals on TLR4 signal-mediated innate immune response remains unclear. Here we show that TLR4 signalling augments macrophage bactericidal activity through the mechanical sensor Piezo1. Bacterial infection or LPS stimulation triggers assembly of the complex of Piezo1 and TLR4 to remodel F-actin organization and augment phagocytosis, mitochondrion-phagosomal ROS production and bacterial clearance and genetic deficiency of Piezo1 results in abrogation of these responses. Mechanistically, LPS stimulates TLR4 to induce Piezo1-mediated calcium influx and consequently activates CaMKII-Mst1/2-Rac axis for pathogen ingestion and killing. Inhibition of CaMKII or knockout of either Mst1/2 or Rac1 results in reduced macrophage bactericidal activity, phenocopying the Piezo1 deficiency. Thus, we conclude that TLR4 drives the innate immune response via Piezo1 providing critical insight for understanding macrophage mechanophysiology and the host response.
The response of AMP-activated protein kinase (AMPK) to oxidative stress has been recently reported but the downstream signals of this response are largely unknown. Meanwhile, the upstream events for ...the activation of nuclear factor erythroid-2-related factor-2 (Nrf2), a critical transcriptional activator for antioxidative responses, remain unclear. In the present study, we investigated the relationship between AMPK and Nrf2 signal pathways in lipopolysaccharide (LPS)-triggered inflammatory system, in which berberine (BBR), a known AMPK activator, was used for inflammation suppression.
In inflammatory macrophages, BBR attenuated LPS-induced expression of inflammatory genes (inducible nitric oxide synthase iNOS, cyclooxygenase-2 COX2, interleukin IL-6), and the generation of nitric oxide and reactive oxygen species, but increased the transcription of Nrf2-targeted antioxidative genes (NADPH quinone oxidoreductase-1 NQO-1, heme oxygenase-1 HO-1), as well as the nuclear localization and phosphorylation of Nrf2 protein. Importantly, we found BBR-induced activation of Nrf2 is AMPK-dependent, as either pharmacologically or genetically inactivating AMPK blocked the activation of Nrf2. Consistent with in vitro experiments, BBR down-regulated the expression of proinflammatory genes but upregulated those of Nrf2-targeted genes in lungs of LPS-injected mice, and these effects were attenuated in Nrf2-deficient mice. Moreover, the effect of BBR on survival time extension and plasma redox regulation in endotoxin-shocked mice was largely weakened when Nrf2-depleted.
Our results demonstrate convergence between AMPK and Nrf2 pathways and this intersection is essential for anti-inflammatory effect of BBR in LPS-stimulated macrophages and endotoxin-shocked mice. Uncovering this intersection is significant for understanding the relationship between energy homeostasis and antioxidative responses and may be beneficial for developing new therapeutic strategies against inflammatory diseases. Antioxid. Redox Signal. 20, 574-588.
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic poses an unprecedented public health crisis. Evidence suggests that SARS-CoV-2 infection causes dysregulation of the immune ...system. However, the unique signature of early immune responses remains elusive. We characterized the transcriptome of rhesus macaques and mice infected with SARS-CoV-2. Alarmin S100A8 was robustly induced in SARS-CoV-2-infected animal models as well as in COVID-19 patients. Paquinimod, a specific inhibitor of S100A8/A9, could rescue the pneumonia with substantial reduction of viral loads in SARS-CoV-2-infected mice. Remarkably, Paquinimod treatment resulted in almost 100% survival in a lethal model of mouse coronavirus infection using the mouse hepatitis virus (MHV). A group of neutrophils that contributes to the uncontrolled pathological damage and onset of COVID-19 was dramatically induced by coronavirus infection. Paquinimod treatment could reduce these neutrophils and regain anti-viral responses, unveiling key roles of S100A8/A9 and aberrant neutrophils in the pathogenesis of COVID-19, highlighting new opportunities for therapeutic intervention.
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•S100A8 is dramatically upregulated in SARS-CoV-2-infected animal models and patients•A group of aberrant immature neutrophils is induced during SARS-CoV-2 infection•Immune disorder is mediated by the S100A8/A9-TLR4 pathway•S100A8/A9 inhibitor, Paquinimod, could prevent COVID-19-associated immune disorder
Guo et al. demonstrate that over-activation of S100A8/A9-TLR4 signaling results in immune imbalance and expansion of aberrant immature neutrophils during SARS-CoV-2 infection. Relevant therapeutic targets were validated in animal infection models.
The employment of college students is an important issue that affects national development and social stability. In recent years, the increase in the number of graduates, the pressure of employment, ...and the epidemic have made the phenomenon of 'slow employment' increasingly prominent, becoming an urgent problem to be solved. Data mining and machine learning methods are used to analyze and predict the employment prospects for graduates and provide effective employment guidance and services for universities, governments, and graduates. It is a feasible solution to alleviate the problem of 'slow employment' of graduates. Therefore, this study proposed a feature selection prediction model (bGEBA-SVM) based on an improved bat algorithm and support vector machine by extracting 1694 college graduates from 2022 classes in Zhejiang Province. To improve the search efficiency and accuracy of the optimal feature subset, this paper proposed an enhanced bat algorithm based on the Gaussian distribution-based and elimination strategies for optimizing the feature set. The training data were input to the support vector machine for prediction. The proposed method is experimented by comparing it with peers, well-known machine learning models on the IEEE CEC2017 benchmark functions, public datasets, and graduate employment prediction dataset. The experimental results show that bGEBA-SVM can obtain higher prediction Accuracy, which can reach 93.86%. In addition, further education, student leader experience, family situation, career planning, and employment structure are more relevant characteristics that affect employment outcomes. In summary, bGEBA-SVM can be regarded as an employment prediction model with strong performance and high interpretability.
Recent studies have revealed that long noncoding RNA HNF1A‐antisense 1 (HNF1A‐AS1) plays an important role in the development of several human malignancy entities. However, the expression and ...function of HNF1A‐AS1 in the carcinogenesis and development of osteosarcoma remains unknown. In this study, we detected the HNF1A‐AS1 levels in human osteosarcoma tissues and cell lines by quantitative real‐time polymerase chain reaction (qRT‐PCR), and investigated its role in osteosarcoma by using in vitro assays. Our study showed that HNF1A‐AS1 expression was significantly up‐regulated in human osteosarcoma tissues and cell lines compared with their normal counterparts, and its expression level was positively correlated with the distance metastasis (P = 0.009) and tumour stage (P = 0.019). Moreover, Kaplan–Meier curves with the log‐rank test showed that higher expression of HNF1A‐AS1 conferred a significantly poorer survival and multivariate Cox proportional hazards analysis revealed that HNF1A‐AS1 was an independent risk factor of overall survival. In addition, the expression of HNF1A‐AS1 in serum is correlated with patients’ status and receiver operating characteristic (ROC) curve analysis demonstrated that HNF1A‐AS1 could distinguish patients with osteosarcoma from healthy individuals (the area under curve 0.849, P < 0.001). Furthermore, in vitro knockdown of HNF1A‐AS1 by siRNA significantly inhibited cell proliferation and G1/S transition, and suppressed migration and invasion by reducing the epithelial‐mesenchymal transition (EMT) program in osteosarcoma cells. Taken together, our data suggested that HNF1A‐AS1 is a novel molecule involved in osteosarcoma progression, which may provide as a potential diagnostic, prognostic biomarker and therapeutic target.
This paper considers the parameter identification of Wiener systems with colored noise. The difficulty in the identification is that the model is nonlinear and the intermediate variable cannot be ...measured. Particle swarm optimization is an artificial intelligence evolutionary method and is effective in solving nonlinear optimization problem. In this paper, we obtain the identification model of the Wiener system and then transfer the parameter identification problem into an optimization problem. Then, we derive a particle swarm optimization iterative (PSOI) identification algorithm to identify the unknown parameter of the Wiener system. Furthermore, a gradient iterative identification algorithm is proposed to compare with the particle swarm optimization iterative algorithm. Numerical simulation is carried out to evaluate the performance of the PSOI algorithm and the gradient iterative algorithm. The simulation results indicate that the proposed algorithms are effective and the PSOI algorithm can achieve better performance over the gradient iterative algorithm.
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