Loss of the TNFα function inhibits Wnt/β-catenin signaling, exacerbates obesity development in adolescent spontaneous obese mice

Tumor necrosis factor alpha (TNFα) is an adipokine involved in the regulation of cell differentiation and lipid metabolism, but its specific role has not been clearly understood. We validated a hypothesis that loss of TNFα function would inhibit Wnt/β-catenin signaling and accelerate adipogenesis in adolescent genetic obese mice. Epididymal white adipose tissues (eWAT) from TNFα deficient (TNFα(−/−)), leptin receptor deficient (db/db) and double gene mutant (db/db/TNFα(−/−), DT) male mice were used for comparative analysis of key molecules in Wnt/β-catenin signaling and adipogenic markers by qRT-PCR and western blot techniques. Compared with TNFα(−/−) and WT mice of 28 days old, an obese trait was observed in both db/db and DT mice, while the latter showed more significant body weight gain and eWAT hypertrophy. The mRNA level of key molecules in Wnt/β-catenin pathway was reduced in both obese groups, while the DT group was the lowest. Expression of adipocyte-specific genes was up-regulated during obese development in the two obese groups, while the DT group revealed more correlation than that of db/db group. At the protein level, a down regulation of Wnt10b and β-catenin in obese eWAT showed similar tendency with that of mRNA level. Compared with the lean groups, the levels of adiponectin and PPARγ2 for the obese groups were down-regulated at 21-day-old age, while they were elevated at older age. Our results suggested that deficiency in TNFα inhibited Wnt/β-catenin signaling of the obese eWAT and up-regulated expression of adipokines, and accelerated adipogenesis in genetic obese mice on a chow diet. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11010-014-1987-5) contains supplementary material, which is available to authorized users

Model estimates of China's terrestrial water storage variation due to reservoir operation

Understanding the role of reservoirs in the terrestrial water cycle is critical to support the sustainable management of water resources especially for China where reservoirs have been extensively built nationwide. However, this has been a scientific challenge due to the limited availability of continuous, long-term reservoir operation records at large scales, and a process-based modeling tool to accurately depict reservoirs as part of the terrestrial water cycle is still lacking. Here, we develop a continental-scale land surface-hydrologic model over the mainland China by explicitly representing 3,547 reservoirs in the model with a calibration-free conceptual operation scheme for ungauged reservoirs and a hydrodynamically based two-way coupled scheme. The model is spatially calibrated and then extensively validated against streamflow observations, reservoir storage observations and GRACE-based terrestrial water storage anomalies. A 30-year simulation is then performed to quantify the seasonal dynamics of China’s reservoir water storage (RWS) and its role in China\u27s terrestrial water storage (TWS) over recent decades. We estimate that, over a seasonal cycle, China\u27s RWS variation is 15%, 16%, and 25% of TWS variation during 1981–1990, 1991–2000, and 2001–2010, respectively, and one-fifth of China’s reservoir capacity are effectively used annually. In most regions, reservoirs play a growing role in modulating the water cycle over time. Despite that, an estimated 80 million people have faced increasing water resources challenges in the past decades due to the significantly weakened reservoir regulation of the water cycle. Our approaches and findings could help the government better address the water security challenges under environmental changes

The NLRP3 inflammasome is involved in resident intruder paradigm-induced aggressive behaviors in mice

Background: Aggressive behaviors are one of the most important negative behaviors that seriously endangers human health. Also, the central para-inflammation of microglia triggered by stress can affect neurological function, plasticity, and behavior. NLRP3 integrates stress-related signals and is a key driver of this neural para-inflammation. However, it is unclear whether the NLRP3 inflammasome is implicated in the development of aggressive behaviors.Methods: First, aggressive behavior model mice were established using the resident intruder paradigm. Then, aggressive behaviors were determined with open-field tests (OFT), elevated plus-maze (EPM), and aggressive behavior tests (AT). Moreover, the expression of P2X7R and NLRP3 inflammasome complexes were assessed by immunofluorescence and Western blot. The levels of NLRP3 and inflammatory cytokines were evaluated using enzyme-linked immunosorbent assay (ELISA) kits. Finally, nerve plasticity damage was observed by immunofluorescence, transmission electron microscope, and BrdU staining.Results: Overall, the resident intruder paradigm induced aggressive behaviors, activated the hippocampal P2X7R and NLRP3 inflammasome, and promoted the release of proinflammatory cytokines IL-1β in mice. Moreover, NLRP3 knockdown, administration of P2X7R antagonist (A804598), and IL-1β blocker (IL-1Ra) prevented NLRP3 inflammasome-driven inflammatory responses and ameliorated resident intruder paradigm-induced aggressive behaviors. Also, the resident intruder paradigm promoted the activation of mouse microglia, damaging synapses in the hippocampus, and suppressing hippocampal regeneration in mice. Besides, NLRP3 knockdown, administration of A804598, and IL-1Ra inhibited the activation of microglia, improved synaptic damage, and restored hippocampal regeneration.Conclusion: The NLRP3 inflammasome-driven inflammatory response contributed to resident intruder paradigm-induced aggressive behavior, which might be related to neuroplasticity. Therefore, the NLRP3 inflammasome can be a potential target to treat aggressive behavior-related mental illnesses

Dynamic Jumps in Global Oil Price and its Impacts on China\u27s Bulk Commodities

This paper investigated the impacts of oil price shocks, especially dynamic jumps in its returns on China\u27s bulk commodity markets at both the aggregate and industry levels. After setting a zero lower bound to the jump intensity of the ARJI model, we found that dynamic jumps exist in oil price movements. Moreover, under shocks of oil price jumps, not only the returns but also the risks of China\u27s bulk commodity markets are affected significantly, and the reactions of risks are characterized by “overreactions”. Meanwhile, by decomposing oil price shocks into expected positive (negative), and unexpected positive (negative) components, we discovered that the impacts of unexpected shocks are positive and significantly asymmetric at both levels, while those of the expected shocks are negative and insignificantly asymmetric at the industry level. In addition, the volatility clustering of all price movements and the permanent volatility effects on China\u27s bulk commodities are also authenticated by applying the GARCH family models

Distributed sliding-mode cloud predictive formation control of networked multi-agent systems with application to air-bearing spacecraft simulators

This paper investigates the application of distributed sliding-mode cloud predictive control scheme in networked multi-agent control systems (NMACS). A sliding-mode cloud predictive control (SMCPC) scheme based on the cloud control system is designed. Combining the advantages of variable structure control (VSC) of sliding-mode control(SMC) and the advantages of cloud predictive control (CPC) in handling network delays, the network delay is actively compensated while ensuring the stability and output consistency of the NMACS. Also taking advantage of the small online computation of SMC, reduces the burden of CPC in processing big data and increases the computation rate. In addition, the scheme includes multi-step state prediction and output prediction as well as coordinated optimization among multiple agents. By optimizing the cost function design, the SMCPC scheme is guaranteed to achieve the desired control performance in multi-agent formation control. And the feasibility of the control scheme is verified by stability and consistency analysis. The applicability of the control scheme in practical applications is verified by air-bearing spacecraft simulator (ABS) formation control experiments

Centralized cloud predictive control of multiple lighting systems

This paper studies the application of centralized cloud predictive control based on dSPACE system in multiple lighting system control. A centralized cloud predictive control scheme is designed to achieve the consistency and stability of multiple lighting control at the same time. The dSPACE multiple lighting control system is corrected and modeled. The design of cloud prediction controller based on dSPACE system is introduced in detail. The cloud predictive control scheme is analyzed through simulation experiments, and the effective parameters of stability and consistency of closed-loop multiple lighting control system are given. The effectiveness of the proposed scheme on the dynamic behavior and control performance of multiple lighting system is verified. The research results provide a foundation for multiple lighting cooperative control and its application. Finally, the stability and consistency of the controller are verified by the physical experiment platform based on dSPACE

Ascorbic acid promotes 3T3-L1 cells adipogenesis by attenuating ERK signaling to upregulate the collagen VI

Abstract Background Type VI collagen is supposed to be a regulation factor in adipogenesis. This study aimed to assess the promoting effect of vitamin C (VC) on adipogenic differentiation of preadipocytes as well as its mechanism. Methods Five sets of different combinations of chemicals were used to inhibit synthesis of type I to VI collagens, blocking ERK1/2 phosphorylation during adipogenesis of 3T3-L1 preadipocytes. Furthermore, to explore whether collagen VI plays a critical role during adipogenesis, specific knockdown of collagen VI was performed by using RNA interference. The morphology and expression patterns of several target factors involved in adipogenesis were assessed at various time points. Results A reduction in ERK1/2 phosphorylation and an increase in collagen VI and adipogenic-specific factors, such as C/EBPβ, PPARγ and C/EBPα, were observed after treating adipogenic 3T3-L1 cells with AA2P, a stable derivative of VC. Inhibition of collagen synthesis by ethyl-3, 4-dihydroxybenzoate (EDHB) or by specific knockdown of collagen VI by RNAi could promote ERK1/2 phosphorylation. The ERK1/2 phosphorylation in both cases could be attenuated by AA2P treatment. In addition, the inhibition of ERK1/2 phosphorylation by U0126, a highly selective inhibitor of both MEK1 and MEK2 and a type of MAPK/ERK kinase, up-regulated the expression of collagen VI, while it down-regulated the adipogenic-specific factors. Conclusion AA2P could up-regulate the expression of collagen VI by attenuating ERK1/2 phosphorylation, further up-regulating adipocyte-specific factors, thus finally promoting the adipogenesis of 3T3-L1 preadipocytes

CMADS-Driven Simulation and Analysis of Reservoir Impacts on the Streamflow with a Simple Statistical Approach

The reservoir operation is a notable source of uncertainty in the natural streamflow and it should be represented in hydrological modelling to quantify the reservoir impact for more effective hydrological forecasting. While many researches focused on the effect of large reservoirs only, this study developed an online reservoir module where the small reservoirs were aggregated into one representative reservoir by employing a statistical approach. The module was then integrated into the coupled Noah Land Surface Model and Hydrologic Model System (Noah LSM-HMS) for a quantitative assessment of the impact of both large and small reservoirs on the streamflow in the upper Gan river basin, China. The Noah LSM-HMS was driven by the China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) with a very good performance and a Nash-Sutcliffe coefficient of efficiency (NSE) of 0.89, which proved to be more effective than the reanalysis data from the National Centers for Environmental Prediction (NCEP) over China. The simulation results of the integrated model indicate that the proposed reservoir module can acceptably depict the temporal variation in the water storage of both large and small reservoirs. Simulation results indicate that streamflow is increased in dry seasons and decreased in wet seasons, and large and small reservoirs can have equally large effects on the streamflow. With the integration of the reservoir module, the performance of the original model is improved at a significant level of 5%

Fractional order distributed model predictive control of fast and strong interacting systems

Fast and strong interacting systems are hard to control from both performance and control effort points of view. Moreover, multiple objective functions or objectives with various identifiers of varying weights can hold unfeasible solutions at times. A novel cost objective function is proposed here to overcome both feasibility set limitations and computational burdens. An application example is used to illustrate its added value, which is a fast and strong interacting multivariable system: a landscape office lighting regulatory problem. New lighting technology and an intelligent control system have been produced to improve control accuracy and reduce power consumption. While optimizing the hardware of the lighting system, the energy consumption can be further reduced by applying advanced control strategy in the lighting system. This paper designed a fractional order distributed model predictive control (FOMPC) scheme to realize the reference tracking and stability control of multiple illuminations at the same time. In order to test the efficiency of the control strategy, an experiment was carried out on the lighting setup based on the dSPACE control system. The FOMPC scheme was analyzed through simulation and lighting experiments based on the dSPACE control system. Through a comparison with the mode predictive control (MPC) scheme, the superiority of the FOMPC scheme for the dynamic behavior and control performance of multiple lighting systems was verified. The research results provide a basis for multiple lighting control and its application