NF-κB activity marks cells engaged in receptor editing

Because of the extreme diversity in immunoglobulin genes, tolerance mechanisms are necessary to ensure that B cells do not respond to self-antigens. One such tolerance mechanism is called receptor editing. If the B cell receptor (BCR) on an immature B cell recognizes self-antigen, it is down-regulated from the cell surface, and light chain gene rearrangement continues in an attempt to edit the autoreactive specificity. Analysis of a heterozygous mutant mouse in which the NF-κB–dependent IκBα gene was replaced with a lacZ (β-gal) reporter complementary DNA (cDNA; IκBα+/lacZ) suggests a potential role for NF-κB in receptor editing. Sorted β-gal+ pre–B cells showed increased levels of various markers of receptor editing. In IκBα+/lacZ reporter mice expressing either innocuous or self-specific knocked in BCRs, β-gal was preferentially expressed in pre–B cells from the mice with self-specific BCRs. Retroviral-mediated expression of a cDNA encoding an IκBα superrepressor in primary bone marrow cultures resulted in diminished germline κ and rearranged λ transcripts but similar levels of RAG expression as compared with controls. We found that IRF4 transcripts were up-regulated in β-gal+ pre–B cells. Because IRF4 is a target of NF-κB and is required for receptor editing, we suggest that NF-κB could be acting through IRF4 to regulate receptor editing

Bacterial Effector Binding to Ribosomal Protein S3 Subverts NF-κB Function

Enteric bacterial pathogens cause food borne disease, which constitutes an enormous economic and health burden. Enterohemorrhagic Escherichia coli (EHEC) causes a severe bloody diarrhea following transmission to humans through various means, including contaminated beef and vegetable products, water, or through contact with animals. EHEC also causes a potentially fatal kidney disease (hemolytic uremic syndrome) for which there is no effective treatment or prophylaxis. EHEC and other enteric pathogens (e.g., enteropathogenic E. coli (EPEC), Salmonella, Shigella, Yersinia) utilize a type III secretion system (T3SS) to inject virulence proteins (effectors) into host cells. While it is known that T3SS effectors subvert host cell function to promote diarrheal disease and bacterial transmission, in many cases, the mechanisms by which these effectors bind to host proteins and disrupt the normal function of intestinal epithelial cells have not been completely characterized. In this study, we present evidence that the E. coli O157:H7 nleH1 and nleH2 genes encode T3SS effectors that bind to the human ribosomal protein S3 (RPS3), a subunit of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) transcriptional complexes. NleH1 and NleH2 co-localized with RPS3 in the cytoplasm, but not in cell nuclei. The N-terminal region of both NleH1 and NleH2 was required for binding to the N-terminus of RPS3. NleH1 and NleH2 are autophosphorylated Ser/Thr protein kinases, but their binding to RPS3 is independent of kinase activity. NleH1, but not NleH2, reduced the nuclear abundance of RPS3 without altering the p50 or p65 NF-κB subunits or affecting the phosphorylation state or abundance of the inhibitory NF-κB chaperone IκBα NleH1 repressed the transcription of a RPS3/NF-κB-dependent reporter plasmid, but did not inhibit the transcription of RPS3-independent reporters. In contrast, NleH2 stimulated RPS3-dependent transcription, as well as an AP-1-dependent reporter. We identified a region of NleH1 (N40-K45) that is at least partially responsible for the inhibitory activity of NleH1 toward RPS3. Deleting nleH1 from E. coli O157:H7 produced a hypervirulent phenotype in a gnotobiotic piglet model of Shiga toxin-producing E. coli infection. We suggest that NleH may disrupt host innate immune responses by binding to a cofactor of host transcriptional complexes

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

Parameter Matching of Power Systems and Design of Vehicle Control Strategies for Mini-Electric Trucks

Mini-electric trucks have been widely used because of their high efficiency and zero emission with the rapid development of electronic commerce and express industry. So, improvement of dynamic performance and economy becomes crucial. The research in this field mainly focuses on passenger vehicles at present. However, most passenger vehicles are front−engine, front-drive vehicles; for mini trucks of front−engine and rear-drive, if the dynamics model of passenger vehicles is applied to mini−electric trucks, the dynamic parameters calculated will not be accurate. To enhance the accuracy of the dynamic parameters of mini-electric trucks, by combining the characteristics of mini trucks, the dynamic parameters are designed, and the types of drive motors and power batteries are selected, the dynamic model of mini−electric trucks is established. To improve the economy, control strategies, with five working modes switching, were established. On this basis, the simulation model is established, and the dynamic and economy simulation analysis and performance test were carried out. In applying the method, the error rate of maximum speed, acceleration time, and maximum gradient between simulation results and test results are 0.641% and 5.63% (15.328%), respectively, proving that the dynamic index has reached the expected value and endurance mileage is up to 295 Km under UDC conditions, increased by 5% after the vehicle control strategy was adopted. The results show that the parameter matching is reasonable and the vehicle control strategy is suitable for mini-electric trucks. The research method and conclusions can provide valuable references for the development of power systems for mini−electric trucks

Influence of Financialization of Heavily Polluting Enterprises on Technological Innovation under the Background of Environmental Pollution Control

In the wake of the acceleration of China’s industrialization and rapid economic growth, environmental pollution has also attracted great attention. The technological innovation of heavily polluting enterprises is conducive to reducing pollution emissions and promoting environmental health. The financial investment tendency and behavior of real enterprises have a significant impact on the technological innovation decision-making of enterprises. A panel model is used in this paper in order to empirically test the impact of financialization of Chinese heavily polluting enterprises on technological innovation based on the data of Listed Companies in Chinese heavily polluting industries from 2008 to 2019. The + results show that the financialization of heavily polluting enterprises has a significant crowding out effect on technological innovation. After introducing arbitrage motivation as the regulating variable, further research finds that arbitrage motivation weakens the inhibitory effect of enterprise financialization on technological innovation, that is, the stronger the arbitrage motivation, the smaller the negative effect of financialization on enterprise technological innovation, which weakens this crowding out effect. Finally, the listed enterprises in heavily polluting industries are divided into state-owned enterprises and non-state-owned enterprises according to their corporate attributes. Compared with state-owned enterprises, the financialization of non-state-owned enterprises has a greater squeeze out of technological innovation; and arbitrage motivation has a more significant regulatory effect on the impact of enterprise financialization on technological innovation

Assessing and prioritizing biogas energy barriers: A sustainable roadmap for energy security

Pakistan is trying to alleviate energy poverty by tapping into the full potential of biogas. However, the production of biogas is hampered by a variety of barriers. Although many researchers have pointed out these barriers, their impact on Pakistan's biogas market remains unclear. This study prioritizes possible barriers and identifies the most practical solutions for energy security in the nation in an effort to bridge this knowledge gap. We find 25 sub-barriers and classify them into five major categories using a literature study and a modified Delphi approach. The analytical hierarchy process (AHP) is used to assign a priority ranking based on weight allocation to barriers. The most influential alternatives to these barriers have been prioritized using the Grey Technique for Order Preference by Similarity to Ideal Solution (G-TOPSIS). According to study findings, among the major categories, “monetary barrier” is the most significant barrier. The top sub-barrier is “high initial price.” “Suitable monetary rewards” and “improved specialized technology” have been proposed as the most viable alternative. Finally, study findings suggest essential and useful policy recommendations to speed up the current progress of biogas energy through coherent and consistent efforts