Search

The NLRP3 inflammasome is a critical component of innate immunity that defends the host from microbial infections. However, its aberrant activation contributes to the pathogenesis of several inflammatory diseases. Activation of the NLRP3 inflammasome induces the secretion of proinflammatory cytokines IL-1β and IL-18, and pyroptotic cell death. NLRP3 contains a leucine-rich repeat (LRR) domain at its C-terminus. Although posttranslational modifications in this LRR domain have been shown to regulate NLRP3 inflammasome activation, the role of the entire LRR domain in NLRP3 inflammasome activation remains controversial. Here, we generated mouse macrophages that express an endogenous NLRP3 mutant lacking the LRR domain. Deletion of the LRR domain destabilized endogenous NLRP3 protein and abolished NLRP3 inflammasome activation in macrophages. Furthermore, using NLRP3-deficient macrophages that are reconstituted with NLRP3 mutants lacking the LRR domain, we found that deletion of the LRR domain inhibited NLRP3 inflammasome activation. Mechanistically, deletion of the LRR domain abolished NLRP3 self-association, oligomerization, and interaction with the essential regulator NEK7. Our results demonstrate a critical role for the LRR domain in NLRP3 inflammasome activation.

The performance of an optimized aerodynamic shape is further improved by a second-step optimization using the design knowledge discovered by a data mining technique based on Proper Orthogonal Decomposition (POD) in the present study. Data generated in the first-step optimization by using evolution algorithms is saved as the source data, among which the superior data with improved objectives and maintained constraints is chosen. Only the geometry components of the superior data are picked out and used for constructing the snapshots of POD. Geometry characteristics of the superior data illustrated by POD bases are the design knowledge, by which the second-step optimization can be rapidly achieved. The optimization methods are demonstrated by redesigning a transonic compressor rotor blade, NASA Rotor 37, in the study to maximize the peak adiabatic efficiency, while maintaining the total pressure ratio and mass flow rate. Firstly, the blade is redesigned by using a particle swarm optimization method, and the adiabatic efficiency is increased by 1.29%. Then, the second-step optimization is performed by using the design knowledge, and a 0.25% gain on the adiabatic efficiency is obtained. The results are presented and addressed in detail, demonstrating that geometry variations significantly change the pattern and strength of the shock wave in the blade passage. The former reduces the separation loss, while the latter reduces the shock loss, and both favor an increase of the adiabatic efficiency. Keywords: Aerodynamic shape optimization, Computational fluid dynamics, Data mining, Particle swarm optimization, Proper Orthogonal Decomposition, Transonic flow, Turbomachinery

53GB Ge/Si APD TO-CAN ROSA were designed and fabricated with record breaking sensitivities of -23.2dBm at BER=1E-3 for 53GB NRZ and -16.0dBm at BER=2E-4 for 53GB PAM4, respectively.

In this work, a novel airframe/propulsion integration design method of the wing-body configuration for hypersonic cruise aircraft is proposed, where the configuration is integrated with inward-turning inlets. With the help of this method, the major design concern of balancing the aerodynamic performance against the requirements for efficient propulsion can be well addressed. A novel geometric parametrically modelling method based on a combination of patched class and shape transition (CST) and COONs surface is proposed to represent the configuration, especially a complex configuration with an irregular inlet lip shape. The modelling method enlarges the design space of components on the premise of guaranteeing the configuration integrity via special constraints imposed on the interface across adjacent surfaces. A basic flow inside a cone shaped by a dual-inflection-point generatrix is optimized to generate the inward-turning inlet with improvements of both compression efficiency and flow uniformity. The performance improvement mechanism of this basic flow is the compression velocity variation induced by the variation of the generatrix slope along the flow path. At the design point, numerical simulation results show that the lift-to-drag ratio of the configuration is as high as 5.2 and the inlet works well with a high level of compression efficiency and flow uniformity. The design result also has a good performance on off-design conditions. The achievement of all the design targets turns out that the integration design method proposed in this paper is efficient and practical.

To make a compromise between compression efficiency and aerodynamic performance, a novel multistage optimization approach is proposed to improve the design of the shape morphing hypersonic inward-turning inlet. In the first stage, a parent flow inside an internal cone shaped from a special dual-inflection-point generatrix is optimized for the improvements of total pressure recovery and flow uniformity. The second stage is established to design the inlet lip shape via a single-objective optimization aiming to minimize the inviscid drag of the inlet. For rapidly predicting the inlet inviscid drag, we propose a streamline integral method characterized by high levels of computational efficiency and accuracy. The last stage is auxiliary to improve the practicability, mainly including an algebraic shape transition to regulate the inlet exit shape. Numerical results demonstrate that both the flow non-uniformity and the total pressure loss of the optimized parent flow are decreased significantly compared with the baseline parent flow. With the optimized lip shape, the inlet inviscid drag per unit mass flow rate is decreased as well. A simple quadratic function is the best choice to achieve the shape transition, which is beneficial to improve the inlet practicability with a less performance loss. With the multistage optimization framework, the improvements of the compression efficiency and the aerodynamic performance are both achieved and the balance between them is carefully manipulated as well. All the above demonstrates that the proposed optimization approach for the design of the shape morphing hypersonic inward-turning inlet is practical and efficient.

106 Gb/s (53GBaud PAM4) normal-incidence Ge/Si APDs were demonstrated with sensitivities of -16.8 dBm. To our knowledge, this is the best sensitivity reported for 100G APD.

The popular use of response surface methodology (RSM) accelerates the solutions of parameter identification and response analysis issues. However, accurate RSM models subject to aleatory and epistemic uncertainties are still challenging to construct, especially for multidimensional inputs, which is widely existed in real-world problems. In this study, an adaptive interval response surface methodology (AIRSM) based on extended active subspaces is proposed for mixed random and interval uncertainties. Based on the idea of subspace dimension reduction, extended active subspaces are given for mixed uncertainties, and interval active variable representation is derived for the construction of AIRSM. A weighted response surface strategy is introduced and tested for predicting the accurate boundary. Moreover, an interval dynamic correlation index is defined, and significance check and cross validation are reformulated in active subspaces to evaluate the AIRSM. The effectiveness of AIRSM is demonstrated on two test examples: three-dimensional nonlinear function and speed reducer design. They both possess a dominant one-dimensional active subspace with small estimation error, and the accuracy of AIRSM is verified by comparing with full-dimensional Monte Carlo simulates, thus providing a potential template for tackling high-dimensional problems involving mixed aleatory and interval uncertainties.

Applying a parameterization technique with fewer parameters and high fidelity improves the efficiency and accuracy of aerodynamic shape optimization. The class and shape transformation (CST) method is concise and efficient. Nevertheless, it is difficult to parameterize complex vehicle configurations using a unified CST method. This article presents a multi-block CST method after analyzing the mathematical description of the method, and this method joins adjacent surfaces smoothly and retains the good properties of the CST method. Modeling cases indicate that the multi-block CST method can reduce the number of design variables used to represent surfaces with uneven curvature distributions and can smoothly model various classes of surfaces. A system of aerodynamic shape optimization is developed based on the multi-block CST method, Pareto genetic algorithms and hypersonic aerodynamic engineering analysis, and the aerodynamic characteristics of a quasi-waverider wing-body vehicle are improved significantly after optimization. A novel configuration is also created using the optimization system. The optimization results indicate that the multi-block CST method, which involves fewer design variables and yields higher fidelity, is a powerful tool for aerodynamic shape optimization.

The NLRP3 inflammasome is a critical component of the innate immune system that activates caspase-1 to induce secretion of pro-inflammatory cytokines interleukin (IL)-1β/IL-18 and cell death in response to microbial infection and cellular damage. However, aberrant activation of the NLRP3 inflammasome contributes to the pathogenesis of several inflammatory disorders, including cryopyrin-associated periodic syndromes, Alzheimer’s disease, type 2 diabetes, and atherosclerosis. Although extensively investigated, the mechanism of NLRP3 inflammasome activation remains not fully understood. Here we used a proteomic approach to identify Nlrp3-interacting proteins in mouse macrophages and found that Rack1 (Receptor for activated C-kinase 1) interacts with both Nlrp3 and Nek7. Inhibition of Rack1 expression abrogated caspase-1 activation and IL-1β release in response to Nlrp3 stimuli, but not Nlrc4 or Aim2 stimuli. Furthermore, this function of Rack1 was independent of its ribosomal association. Mechanistically, Rack1 was required for Nlrp3-mediated Asc speck formation and Nlrp3 stimuli-induced inflammasome complex assembly. Our work therefore identifies Rack1 as a potential therapeutic target for treating NLRP3 inflammasome-driven inflammatory diseases. Given the fact that Rack1 is a critical component of plant innate R protein complexes and contributes to the host defense against rice blast infection, our work further highlights a conserved link in innate immunity between mammals and plants.

G protein-coupled receptors (GPCRs) are important modulators of many physiological functions and excellent drug targets for many diseases. However, to study the functions of endogenous GPCRs is still a challenging task, partially due to the low expression level of GPCRs and the lack of highly potent and selective GPCR antibodies. Overexpression or knock-in of tagged GPCRs, or knockout of specific GPCRs in mice, are common strategies used to study the in vivo functions of these receptors. However, generating separate mice carrying tagged GPCRs or conditional alleles for GPCRs is labor intensive, and requires additional breeding costs. Here we report the generation of mice carrying an HA-tagged DOR (delta opioid receptor) flanked by LoxP sequences at the endogenous DOR locus using a single recombination step, aided by the TALEN system. These animals can be used directly to study the expression, localization, protein-protein interaction and signal transduction of endogenous DOR using anti-HA antibodies. By crossing with mice expressing tissue-specific Cre, these mice can also generate offspring with DOR knockout within specific tissues. These mice are powerful tools to study the in vivo functions of DOR. Furthermore, the gene modification strategy could also be used to study the functions of many other GPCRs.

This paper presents an iterative inverse design methodology based on proper orthogonal decomposition (POD) and its applications to the inverse design of turbomachinery blades. In the aerodynamic system with a number of snapshots, the aerodynamic performance with the corresponding aerodynamic shape within the design space can be described as a linear combination of a series of POD basis modes. In the present paper, the description ability of Gappy POD is evaluated firstly and the influence of different parametrization methods and different snapshot approaches are studied and compared in detail. In the POD-based inverse design, the aerodynamic shape can be obtained by only one design process. However, due to the error between the predicted aerodynamic performance by Gappy POD and that obtained from computational fluid dynamics, an iterative inverse design methodology is proposed herein based on the error correction to the target aerodynamic performance. Three inverse design studies of turbomachinery blades are performed. In the first two cases, the profiles of two-dimensional turbine blades are modified to approach the target pressure distributions on the blade surface in subsonic and transonic flow, respectively. In the third case, a three-dimensional supersonic turbine blade is restaggered along span to achieve a given loading distribution in the spanwise direction at the outlet. The design results are presented and compared in detail, demonstrating the effectiveness and improved accuracy of the POD-based iterative inverse design method.Copyright © 2015 by ASME