Regulation of NLRP3 Inflammasome by Phosphorylation

The cytosolic pattern recognition receptor (PRR) NOD-like receptor family, pyrin domain containing 3 (NLRP3) senses a wide range of pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs). Upon activation, NLRP3 triggers the assembly of inflammasome via the self-oligomerization and the recruitment of apoptosis-associated speck-like protein containing a caspase-recruitment domain (ASC) and pro-caspase-1, facilitating the robust immune responses including the secretion of proinflammatory cytokines and pyroptosis. The NLRP3 inflammasome must be well orchestrated to prevent the aberrant activations under physiological and pathological conditions, because uncontrolled activation of NLRP3 inflammasome is one of the major causes of a variety of autoimmune diseases and metabolic disorders. Therefore, understanding the molecular mechanisms for controlling NLRP3 inflammasome activation may provide novel strategies for the treatment of NLRP3-related diseases. Although NLRP3 inflammasome can be regulated at the transcriptional level, the post-translational modification (PTM) of NLRP3 as well as other inflammasome components has also been showed to be critical for the regulation of its activation. Several kinases and phosphatases have been shown to control NLRP3 inflammasome activation in response to either exogenous pathogen infections or endogenous molecules, such as bile acids. In this review, we summarize our current knowledge of phosphorylation patterns and their functional role in the regulation of NLRP3 inflammasome, and suggest interesting areas for future research

Kullback-Leibler entropy and Penrose conjecture in the Lemaitre-Tolman-Bondi model

Our universe hosts various large-scale structures from voids to galaxy clusters, so it would be interesting to find some simple and reasonable measure to describe the inhomogeneities in the universe. We explore two different methods for this purpose: the Kullback-Leibler entropy and the Weyl curvature tensor. These two quantities characterize the deviation of the actual distribution of matter from the unperturbed background. We calculate these two measures in the spherically symmetric Lemaitre-Tolman-Bondi model in the dust universe. Both exact and perturbative calculations are presented, and we observe that these two measures are in proportion up to second order.Comment: 8 page

An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm.

Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be satisfied when the TPS-QC tool generated re-optimized plans without sacrificing other dosimetric endpoints. In addition to its feasibility and accuracy, the proposed TPS-QC tool is also user-friendly and easy to operate, both of which are necessary characteristics for clinical use

Integrable Open Spin Chains from Flavored ABJM Theory

We compute the two-loop anomalous dimension matrix in the scalar sector of planar ${\cal N}=3$ flavored ABJM theory. Using coordinate Bethe ansatz, we obtain the reflection matrix and confirm that the boundary Yang-Baxter equations are satisfied. This establishes the integrability of this theory in the scalar sector at the two-loop order.Comment: v2, 25 pages, 2 figures, minor corrections, references adde

Identification of open crack of beam using model based method

This research aims at identifying the position and depth of the open transverse crack of the beam using the model based method. The stiffness matrix of the cracked beam element and the basic principle of the model based method are introduced. It is discussed to estimate the generalized displacement of all nodes of the beam by the measured displacements of a few degrees of freedom. The relative change rate of the equivalent external load between the intact and cracked elements is compared with that of mode shape, nature frequency and displacement amplitude between the intact and cracked beam. The position and depth of the crack are identified by the model based method in two cases. In first case, the measured displacement is assumed not to include noise. The identification results based on the actual displacement and rotation of all nodes are compared with the results using the estimated generalized displacement. In second case, the measured displacement includes noise and the generalized displacement of all nodes is estimated by the displacement of two measurement points. The simulation results shown there is no error to identify the position, the relative depth identification error of the crack with 1 μm depth is 2.34 % without noise, and the relative depth identification error of the crack with 200 μm depth could be down to about 5 % with the energy signal to noise ratio being about 7.00 before denoising

To Achieve Security and High Spectrum Efficiency: A New Transmission System Based on Faster-than-Nyquist and Deep Learning

With the rapid development of various services in wireless communications, spectrum resource has become increasingly valuable. Faster-than-Nyquist (FTN) signaling, which was proposed in the 1970s, has been a promising paradigm to improve the spectrum utilization. In this paper, we try to apply FTN into secure communications and propose a secure and high-spectrum-efficiency transmission system based on FTN and deep learning (DL). In the proposed system, the hopping symbol packing ratio with random values makes it difficult for the eavesdropper to obtain the accurate symbol rate and inter-symbol interference (ISI). While the receiver can use the blind estimation to choose the true parameters with the aid of DL. The results show that without the accurate symbol packing ratio, the eavesdropper will suffer from severe performance degradation. As a result, the system can achieve a secure transmission with a higher spectrum efficiency. Also, we propose a simplified symbol packing ratio estimation which has bee employed in our proposed system. Results show that the proposed simplified estimation achieves nearly the same performance as the original structure while its complexity has been greatly reduced