Leprosy: treatment, prevention, immune response and gene function

Since the leprosy cases have fallen dramatically, the incidence of leprosy has remained stable over the past years, indicating that multidrug therapy seems unable to eradicate leprosy. More seriously, the emergence of rifampicin-resistant strains also affects the effectiveness of treatment. Immunoprophylaxis was mainly carried out through vaccination with the BCG but also included vaccines such as LepVax and MiP. Meanwhile, it is well known that the infection and pathogenesis largely depend on the host’s genetic background and immunity, with the onset of the disease being genetically regulated. The immune process heavily influences the clinical course of the disease. However, the impact of immune processes and genetic regulation of leprosy on pathogenesis and immunological levels is largely unknown. Therefore, we summarize the latest research progress in leprosy treatment, prevention, immunity and gene function. The comprehensive research in these areas will help elucidate the pathogenesis of leprosy and provide a basis for developing leprosy elimination strategies

Predictive modeling of plant messenger RNA polyadenylation sites

BACKGROUND: One of the essential processing events during pre-mRNA maturation is the post-transcriptional addition of a polyadenine [poly(A)] tail. The 3'-end poly(A) track protects mRNA from unregulated degradation, and indicates the integrity of mRNA through recognition by mRNA export and translation machinery. The position of a poly(A) site is predetermined by signals in the pre-mRNA sequence that are recognized by a complex of polyadenylation factors. These signals are generally tri-part sequence patterns around the cleavage site that serves as the future poly(A) site. In plants, there is little sequence conservation among these signal elements, which makes it difficult to develop an accurate algorithm to predict the poly(A) site of a given gene. We attempted to solve this problem. RESULTS: Based on our current working model and the profile of nucleotide sequence distribution of the poly(A) signals and around poly(A) sites in Arabidopsis, we have devised a Generalized Hidden Markov Model based algorithm to predict potential poly(A) sites. The high specificity and sensitivity of the algorithm were demonstrated by testing several datasets, and at the best combinations, both reach 97%. The accuracy of the program, called poly(A) site sleuth or PASS, has been demonstrated by the prediction of many validated poly(A) sites. PASS also predicted the changes of poly(A) site efficiency in poly(A) signal mutants that were constructed and characterized by traditional genetic experiments. The efficacy of PASS was demonstrated by predicting poly(A) sites within long genomic sequences. CONCLUSION: Based on the features of plant poly(A) signals, a computational model was built to effectively predict the poly(A) sites in Arabidopsis genes. The algorithm will be useful in gene annotation because a poly(A) site signifies the end of the transcript. This algorithm can also be used to predict alternative poly(A) sites in known genes, and will be useful in the design of transgenes for crop genetic engineering by predicting and eliminating undesirable poly(A) sites

Neutrino Physics with JUNO

The Jiangmen Underground Neutrino Observatory (JUNO), a 20 kton multi-purposeunderground liquid scintillator detector, was proposed with the determinationof the neutrino mass hierarchy as a primary physics goal. It is also capable ofobserving neutrinos from terrestrial and extra-terrestrial sources, includingsupernova burst neutrinos, diffuse supernova neutrino background, geoneutrinos,atmospheric neutrinos, solar neutrinos, as well as exotic searches such asnucleon decays, dark matter, sterile neutrinos, etc. We present the physicsmotivations and the anticipated performance of the JUNO detector for variousproposed measurements. By detecting reactor antineutrinos from two power plantsat 53-km distance, JUNO will determine the neutrino mass hierarchy at a 3-4sigma significance with six years of running. The measurement of antineutrinospectrum will also lead to the precise determination of three out of the sixoscillation parameters to an accuracy of better than 1\%. Neutrino burst from atypical core-collapse supernova at 10 kpc would lead to ~5000inverse-beta-decay events and ~2000 all-flavor neutrino-proton elasticscattering events in JUNO. Detection of DSNB would provide valuable informationon the cosmic star-formation rate and the average core-collapsed neutrinoenergy spectrum. Geo-neutrinos can be detected in JUNO with a rate of ~400events per year, significantly improving the statistics of existing geoneutrinosamples. The JUNO detector is sensitive to several exotic searches, e.g. protondecay via the $p\to K^++\bar\nu$ decay channel. The JUNO detector will providea unique facility to address many outstanding crucial questions in particle andastrophysics. It holds the great potential for further advancing our quest tounderstanding the fundamental properties of neutrinos, one of the buildingblocks of our Universe

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

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Embedded Programmable Single Point Multiple Output Intelligent Data Acquisition and Transmission System

To effectively solve the problems of inconsistent communication protocols in automatic monitoring equipment, and limited data acquisition transmission and monitoring equipment, this paper developed programmable single point multiple output intelligent data acquisition and transmission system. It made an in-depth elaboration of the data acquisition and transmission system from hardware design, software architecture and principle, main functions and technical parameters. Finally, it came up with four innovation points: (i) intelligent (automatic) matching a variety of communication protocols for environmental monitoring equipment, (ii) realizing multi-protocol and multi-target parallel data transmission, (iii) realizing remote dynamic input of control instructions through wired or wireless network, and (iv) supporting configuration (process) simulation of field equipment DCS operating conditions

3D CSAMT modelling in anisotropic media using edge-based finite-element method

Controlled-source audio-frequency magnetotellurics (CSAMT) is an important geophysical technique. Numerous studies have shown that the electrical anisotropy in the Earth cannot be ignored because it would probably lead to misinterpretations of electromagnetic data. It is necessary and meaningful to study CSAMT responses in three-dimensional (3D) electrical anisotropic media; therefore, we have developed an edge-based finite element method for 3D CSAMT forward modelling in generalised anisotropic media. The total electric field in this approach is decomposed into a primary electric field and a secondary electric field, and the Galerkin weighted residuals method is adopted to obtain the variational equation. The accuracy of this algorithm was initially validated by comparing solutions with those obtained in previous work on a 3D arbitrary anisotropic model. We then studied the responses of an oblique source as well as equatorial and axial configurations and the tensor source for anomalies with different Euler's angles. Several meaningful conclusions can be derived from this work and a synthetic model is developed; the results also confirm the validity of previous conclusions. This study shows that a tensor source is necessary for a CSAMT survey in 3D anisotropic media, and the anisotropic parameters of anomalies have complex and significant influences on CSAMT responses

Leakage Current and Low-Frequency Noise Analysis and reduction in a Suspended SOI Lateral p-i-n Diode

In this paper, we present a detailed analysis of leakage current in a silicon-on-insulator (SOI) lateral P+P−N+ (p-i-n) diode suspended on a microheating platform, combining device experimental characterization and numerical simulation. The diode leakage currents have been extensively studied using the back-gate bias as a means to alter the space-charge (SC) condition at the P− region (I-region)/buried oxide interface from accumulation to full depletion, and finally to inversion. Both dark leakage current analysis and low-frequency noise characterization performed on the suspended SOI lateral p-i-n diode indicate device degradation induced by microelectromechanical systems postprocessing (i.e., deep reactive-ion etching or aluminum deposition). A low-temperature (∼250 °C) in situ (i.e., using embedded microheater) annealing of SOI lateral p-i-n diode after postprocessing allows reduction of the diode leakage current and optimization of the device performance by neutralizing the interface traps and improving carriers’ lifetime and surface recombination velocity.Numerical simulations have been performed with Atlas/SILVACO for deeper analysis of the leakage current behavior in the lateral p-i-n diode and identification of the generation mechanism dominating the diode leakage behavior. Simulation reveals that the dominant generation rate in the diode depends on the SC conditions, the interface trap density, and the carriers’ lifetime in the I-region. The experimental and simulated behaviors of “as processed” and annealed diode leakage current are shown to be in good qualitative agreement