TLR8 aggravates skin inflammation and fibrosis by activating skin fibroblasts in systemic sclerosis.

OBJECTIVES: Innate immunity significantly contributes to systemic sclerosis (SSc) pathogenesis. TLR8 is an important innate immune mediator that is implicated in autoimmunity and fibrosis. However, the expression, mechanism of action, and pathogenic role of TLR8 in SSc remain unclear. The aim of this study was to explore the roles and underlying mechanisms of TLR8 in SSc. METHODS: The expression of TLR8 was analyzed based on a public dataset and then verified in skin tissues and skin fibroblasts of SSc patients. The role of TLR8 in inflammation and fibrosis was investigated using a TLR8-overexpression vector, activator (VTX-2337), inhibitor (cu-cpt-8m), and TLR8 siRNA in skin fibroblasts. The pathogenic role of TLR8 in skin inflammation and fibrosis was further validated in a bleomycin (BLM)-induced mouse skin inflammation and fibrosis model. RESULTS: TLR8 levels were significantly elevated in SSc skin tissues and myofibroblasts, along with significant activation of the TLR8 pathway. In vitro studies showed that overexpression or activation of TLR8 by a recombinant plasmid or VTX-2337 upregulated IL-6, IL-1ß, COL I, COL III, and α-SMA in skin fibroblasts. Consistently, both TLR8-siRNA and cu-cpt-8m reversed the phenotypes observed in TLR8-activating fibroblasts. Mechanistically, TLR8 induces skin fibrosis and inflammation in a manner dependent on the MAPK, NF-κB, and SMAD2/3 pathways. Subcutaneous injection of cu-cpt-8m significantly alleviated BLM-induced skin inflammation and fibrosis in vivo. CONCLUSION: TLR8 might be a promising therapeutic target to improve the treatment strategy for SSc skin inflammation and fibrosis.

The impact of natural resource consumption on carbon emissions: evidence of a symmetric and asymmetric effect from Sub-Saharan Africa.

Sub-Saharan African countries are among mineral-rich developing countries strategically competing to guarantee sustainable economic development through resource exploration. The possibility of increasing the level of carbon emission due to using low-cost fuels and high pollutants during mineral resource extraction activities leading to environmental degradation continues to draw the attention of researchers and policy makers. This research aims to analyze the response of carbon emissions in the African continent to symmetric and asymmetric shocks on resource consumption, economic growth, urbanization, and energy consumption. Following the Shin et al. (2014a) linear and nonlinear autoregressive distributed lag (ARDL) methodology in panel form, we construct symmetric and asymmetric panel ARDL-PMG model to evaluate both short- and long-run impacts of resource consumption on carbon dioxide emissions for a panel of 44 African countries over the period 2000-2019. The symmetric results show that the effect is not statistically significant despite natural resource consumption positively impacting carbon emission in the long and short runs. Energy consumption was found to affect environmental quality in the long and short runs adversely. Interestingly, economic growth was found to improve environmental quality in the long run significantly, and no significant impact was reported in the case of urbanization. However, the asymmetric results prove that a positive and negative shock to natural resource consumption contributes significantly to carbon emission, contrary to the insignificant impact established in the linear framework. The gradual growth in the manufacturing sector and an expansion in the transportation sector in Africa led to high demand and consumption of fossil fuels. This possibly accounts for the adverse effect of energy consumption on carbon emissions. Most African countries depend mainly on exploring natural resource endowment and agricultural activities to drive the growth of their economies. Due to the weak environmental regulatory frameworks in most African countries and public corruption, multinational companies (MNCs) in the extractive sector do not adhere to environmentally friendly activities. The majority of African countries are also battling illegal mining activities and illicit felling of trees, which may account for the positive relationship between natural resource rents and environmental quality reported. In terms of policy implications of the study, governments in Africa must preserve natural resources, use environmentally friendly and technologically advanced resource extraction methods, opt for green energy, and strictly apply environmental laws to promote environmental quality on the continent.

A Memetic Algorithm for Solving the Robust Influence Maximization Problem on Complex Networks against Structural Failures.

Many transport systems in the real world can be modeled as networked systems. Due to limited resources, only a few nodes can be selected as seeds in the system, whose role is to spread required information or control signals as widely as possible. This problem can be modeled as the influence maximization problem. Most of the existing selection strategies are based on the invariable network structure and have not touched upon the condition that the network is under structural failures. Related studies indicate that such strategies may not completely tackle complicated diffusion tasks in reality, and the robustness of the information diffusion process against perturbances is significant. To give a numerical performance criterion of seeds under structural failure, a measure has been developed to define the robust influence maximization (RIM) problem. Further, a memetic optimization algorithm (MA) which includes several problem-orientated operators to improve the search ability, termed RIMMA, has been presented to deal with the RIM problem. Experimental results on synthetic networks and real-world networks validate the effectiveness of RIMMA, its superiority over existing approaches is also shown.

A Novel Analytical Modeling Approach for Quality Propagation of Transient Analysis of Serial Production Systems.

Production system modeling (PSM) for quality propagation involves mapping the principles between components and systems. While most existing studies focus on the steady-state analysis, the transient quality analysis remains largely unexplored. It is of significance to fully understand quality propagation, especially during transients, to shorten product changeover time, decrease quality loss, and improve quality. In this paper, a novel analytical PSM approach is established based on the Markov model, to explore product quality propagation for transient analysis of serial multi-stage production systems. The cascade property for quality propagation among correlated sequential stages was investigated, taking into account both the status of the current stage and the quality of the outputs from upstream stages. Closed-form formulae to evaluate transient quality performances of multi-stage systems were formulated, including the dynamics of system quality, settling time, and quality loss. An iterative procedure utilizing the aggregation technique is presented to approximate transient quality performance with computational efficiency and high accuracy. Moreover, system theoretic properties of quality measures were analyzed and the quality bottleneck identification method was investigated. In the case study, the modeling error was 0.36% and the calculation could clearly track system dynamics; quality bottleneck was identified to decrease the quality loss and facilitate continuous improvement. The experimental results illustrate the applicability of the proposed PSM approach.