Targeting NLRP3 Inflammasome in the Treatment of CNS Diseases

Central nervous system (CNS) is one of the largest killers of people’s health all over the world. The overactivation of the immune and inflammatory responses is considered as an important factor, contributing to the pathogenesis and progression of CNS disorders. Among all kinds of immune and inflammatory reaction, the inflammasome, a complex of proteins, has been drawn increasingly attention to by researchers. The initiation and activation of the inflammasome is involved in the onset of various kinds of diseases. The NLRP3 inflammasome, the most studied member of the inflammasome, is closely associated with many kinds of CNS disorders. Here in this review, the roles of the NLRP3 inflammasome in the pathogenesis and progression of several well-known CNS diseases would be discussed, including cerebrovascular diseases, neurodegenerative diseases, multiple sclerosis, depression as well as other CNS disorders. In addition, several therapeutic strategies targeting on the NLRP3 inflammasome for the treatment of CNS disorders would be described in this review

A Generalized Robust Minimization Framework for Low-Rank Matrix Recovery

This paper considers the problem of recovering low-rank matrices which are heavily corrupted by outliers or large errors. To improve the robustness of existing recovery methods, the problem is solved by formulating it as a generalized nonsmooth nonconvex minimization functional via exploiting the Schatten p-norm (0 < p ≤1) and Lq(0 < q ≤1) seminorm. Two numerical algorithms are provided based on the augmented Lagrange multiplier (ALM) and accelerated proximal gradient (APG) methods as well as efficient root-finder strategies. Experimental results demonstrate that the proposed generalized approach is more inclusive and effective compared with state-of-the-art methods, either convex or nonconvex

Nonlocality of two-qubit and three-qubit Schmidt-Correlated states

We investigate the nonlocality of Schmidt-correlated (SC) states, and present analytical expressions of the maximum violation value of Bell inequalities. It is shown that the violation of Clauser-Horne-Shimony-Holt (CHSH) inequality is necessary and sufficient for the nonlocality of two-qubit SC states, whereas the violation of the Svetlichny inequality is only a sufficient condition for the genuine nonlocality of three-qubit SC states. Furthermore, the relations among the maximum violation values, concurrence and relative entropy entanglement are discussed.Comment: 12 page

Proton-Boron Fusion Yield Increased by Orders of Magnitude with Foam Targets

A novel intense beam-driven scheme for high yield of the tri-alpha reaction 11B(p,{\alpha})2{\alpha} was investigated. We used a foam target made of cellulose triacetate (TAC, C_9H_{16}O_8) doped with boron. It was then heated volumetrically by soft X-ray radiation from a laser heated hohlraum and turned into a homogenous, and long living plasma. We employed a picosecond laser pulse to generate a high-intensity energetic proton beam via the well-known Target Normal Sheath Acceleration (TNSA) mechanism. We observed up to 10^{10}/sr {\alpha} particles per laser shot. This constitutes presently the highest yield value normalized to the laser energy on target. The measured fusion yield per proton exceeds the classical expectation of beam-target reactions by up to four orders of magnitude under high proton intensities. This enhancement is attributed to the strong electric fields and nonequilibrium thermonuclear fusion reactions as a result of the new method. Our approach shows opportunities to pursue ignition of aneutronic fusion

High Diversity of Tick-associated Microbiota from Five Tick Species in Yunnan, China

Ticks are obligate blood-sucking vectors for multiple zoonotic diseases. In this study, tick samples were collected from Yunnan Province, China, which is well-known as the “Global Biodiversity Hotspot” in the world. This study aimed to clarify the microbial populations, including pathogens, associated with ticks and to identify the diversity of tick-borne microbiota in this region. The 16S rRNA full-length sequencing from pooled tick DNA samples and PCR amplification of pathogenic genera from individual samples were performed to understand tick-associated microbiota in this region. A total of 191 adult ticks of 5 tick species were included and revealed 11 phyla and 126 genera bacteria, including pathogenic Anaplasma , Ehrlichia , Candidatus Neoehrlichia, Rickettsia , Borrelia , and Babesia . Further identification suggested that Rickettsia sp. YN01 was a variant strain of Rickettsia spp. IG-1, but Rickettsia sp. YN02 and Rickettsia sp. YN03, were potentially two new SFGR species. This study revealed the complexity of ecological interactions between host and microbe and provided insight for the biological control of ticks. A high microbial diversity in ticks from Yunnan was identified, and more investigation should be undertaken to elucidate the pathogenicity in the area

Corrigendum to: The TianQin project: current progress on science and technology

In the originally published version, this manuscript included an error related to indicating the corresponding author within the author list. This has now been corrected online to reflect the fact that author Jun Luo is the corresponding author of the article

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO