Transcriptional activation of follistatin by Nrf2 protects pulmonary epithelial cells against silica nanoparticle-induced oxidative stress

Silica nanoparticles (SiO2 NPs) cause oxidative stress in respiratory system. Meanwhile, human cells launch adaptive responses to overcome SiO2 NP toxicity. However, besides a few examples, the regulation of SiO2 NP-responsive proteins and their functions in SiO2 NP response remain largely unknown. In this study, we demonstrated that SiO2 NP induced the expression of follistatin (FST), a stress responsive gene, in mouse lung tissue as well as in human lung epithelial cells (A549). The levels of Ac-H3(K9/18) and H3K4me2, two active gene markers, at FST promoter region were significantly increased during SiO2 NP treatment. The induction of FST transcription was mediated by the nuclear factor erythroid 2-related factor 2 (Nrf2), as evidenced by the decreased FST expression in Nrf2-deficient cells and the direct binding of Nrf2 to FST promoter region. Down-regulation of FST promoted SiO2 NP-induced apoptosis both in cultured cells and in mouse lung tissue. Furthermore, knockdown of FST increased while overexpression of FST decreased the expression level of NADPH oxidase 1 (NOX1) and NOX5 as well as the production of cellular reactive oxygen species (ROS). Taken together, these findings demonstrated a protective role of FST in SiO2 NP-induced oxidative stress and shed light on the interaction between SiO2 NPs and biological systems

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

The Analysis Method about Change Region of Process Model based on Module

Business process management is a common approach of analyzing evolution and formulation of process models. But it is inevitable to come about the change problem of process models in BPMN, so that quickly and accurately seeking the change region of process models is the key thing of BPMN. Existing research is mainly dependent on the target model, and seeks the change region of process models by fixing the observation points. However, on the one hand, this way needs to compare with the target model. On the other hand, by static analysis, it can not quickly and accurately seek the change region of process models. In this paper, firstly, module decomposition and behavioural relation of module are analyzed based on Petri net and behavioural profile, without building the target model, thus avoid the inaccuracy of seeking the change region by comparing the models. Secondly, by dynamic search, this paper presents a novel way to seek the change region of process model and confirm the minimal change region of process model. Finally, this method is valid by theory and example analysis

TMEM97/Sigma 2 Receptor Increases Estrogen Receptor α Activity in Promoting Breast Cancer Cell Growth

Aberrant estrogen receptor (ER) signaling is a major driver of breast tumor growth and progression. Sigma 2 receptor has long been implicated in breast carcinogenesis based on pharmacological studies, but its molecular identity had been elusive until TMEM97 was identified as the receptor. Herein, we report that the TMEM97/sigma 2 receptor is highly expressed in ER-positive breast tumors and its expression is strongly correlated with ERs and progesterone receptors (PRs) but not with HER2 status. High expression levels of TMEM97 are associated with reduced overall survival of patients. Breast cancer cells with increased expression of TMEM97 had a growth advantage over the control cells under both nutrition-limiting and sufficient conditions, while the knockdown of TMEM97 expression reduced tumor cell proliferations. When compared to their vector control cells, MCF7 and T47D cells with increased TMEM97 expression presented increased resistance to tamoxifen treatment and also grew better under estrogen-depleted conditions. The TMEM97/sigma 2 receptor enhanced the ERα transcriptional activities and increased the expression of genes responsive to estrogen treatment. Increased TMEM97 also stimulated the mTOR/S6K1 signaling pathways in the MCF7 and T47D cells. The increased level of active, phosphorylated ERα, and the enhanced resistance to tamoxifen treatment with increased TMEM97, could be blocked by an mTOR inhibitor. The knockdown of TMEM97 expression reduced the ERα and mTOR/S6K1 signaling activities, rendering the cells with an increased sensitivity to tamoxifen. The observations suggest that the TMEM97/sigma 2 receptor is a novel regulator of ERα activities in breast tumor cell growth

The Differential Evolution Method for Constraint Web Service Composition Based on Fuzzy Petri Net

Abstract: For independent global constraints Web services composition problem, it is difficult to analyze the optimal composition plan. The study presents an optimization method of Web service composition with constraint using Fuzzy Petri Net (FPN) and Differential Evolution (DE), which can transforms solving the optimal service composition problem into locating the largest trust value of legal firing sequences in the FPN model. Then we use the DE algorithm to locate the optimal legal sequences in order to obtain the optimal Web service composition. The experimental results show that the method is effective