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

Optimization and Corroboration of the Regulatory Pathway of p42.3 Protein in the Pathogenesis of Gastric Carcinoma

Aims. To optimize and verify the regulatory pathway of p42.3 in the pathogenesis of gastric carcinoma (GC) by intelligent algorithm. Methods. Bioinformatics methods were used to analyze the features of structural domain in p42.3 protein. Proteins with the same domains and similar functions to p42.3 were screened out for reference. The possible regulatory pathway of p42.3 was established by integrating the acting pathways of these proteins. Then, the similarity between the reference proteins and p42.3 protein was figured out by multiparameter weighted summation method. The calculation result was taken as the prior probability of the initial node in Bayesian network. Besides, the probability of occurrence in different pathways was calculated by conditional probability formula, and the one with the maximum probability was regarded as the most possible pathway of p42.3. Finally, molecular biological experiments were conducted to prove it. Results. In Bayesian network of p42.3, probability of the acting pathway “S100A11→RAGE→P38→MAPK→Microtubule-associated protein→Spindle protein→Centromere protein→Cell proliferation” was the biggest, and it was also validated by biological experiments. Conclusions. The possibly important role of p42.3 in the occurrence of gastric carcinoma was verified by theoretical analysis and preliminary test, helping in studying the relationship between p42.3 and gastric carcinoma

Corrigendum to “Optimization and Corroboration of the Regulatory Pathway of p42.3 Protein in the Pathogenesis of Gastric Carcinoma”

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In the article “Optimization and Corroboration of the Regu-latory Pathway of p42.3 Protein in the Pathogenesis of Gastric Carcinoma ” [1], there was an error in the author information. The affiliations for the authors were incorrectly listed. The correct author line and affiliations are shown above. References [1] Y. Hao, T. Fan, and K. Nan, “Optimization and corroboration of the regulatory pathway of p42.3 protein in the pathogenesis o

Establishment of apoptotic regulatory network for genetic markers of colorectal cancer

Our purpose is to screen out genetic markers applicable to early diagnosis for colorectal cancer and to establish apoptotic regulatory network model for colorectal cancer, thereby providing theoretical evidence and targeted therapy for early diagnosis of colorectal cancer. Taking databases including CNKI, VIP, Wanfang data, Pub Med, and MEDLINE as main sources of literature retrieval, literatures associated with genetic markers applied to early diagnosis of colorectal cancer were searched to perform comprehensive and quantitative analysis by Meta analysis, hence screening genetic markers used in early diagnosis of colorectal cancer. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were employed to establish apoptotic regulatory network model based on screened genetic markers, and then verification experiment was conducted. Through Meta analysis, seven genetic markers were screened out, including WWOX, K-ras, COX-2, p53, APC, DCC and PTEN, among which DCC shows highest diagnostic efficiency. GO analysis of genetic markers found that six genetic markers played role in biological process, molecular function and cellular component. It was indicated in apoptotic regulatory network built by KEGG analysis and verification experiment that WWOX could promote tumor cell apoptotic in colorectal cancer and elevate expression level of p53. The apoptotic regulatory model of colorectal cancer established in this study provides clinically theoretical evidence and targeted therapy for early diagnosis of colorectal cancer

Establishment of optimal regulatory network of colorectal cancer based on p42.3 protein

Objective: to establish regulatory network of colorectal cancer involving p42.3 protein and to provide theoretical evidence for deep functional exploration of p42.3 protein in the onset and development of colorectal cancer. Methods: with protein similarity algorithm, reference protein set of p42.3 cell apoptosis was built according to structural features of p42.3. GO and KEGG databases were used to establish regulatory network of tumor cell apoptosis involving p42.3; meanwhile, the largest possible working pathway that involves p42.3 protein was screened out based on Bayesian network theory. Besides, GO and KEGG were used to build regulatory network on early diagnosis gene markers for colorectal cancer including WWOX, K-ras, COX-2, p53, APC, DCC and PTEN, at the same time, a regulatory network of colorectal cancer cell apoptosis which involves p42.3 was established. Results: cell apoptotic regulatory network that p42.3 participates in primarily consists of Bcl-2 family genes and the largest possible pathway is p42.3 → FKBP → Bcl-2 centered as FKBP protein. Combined with colorectal cancer regulatory network that involves early diagnosis gene markers, it can be predicted that p42.3 is most likely to regulate the colorectal cancer cell apoptosis through FKBP → Bcl-2 → Bax → caspase-9 → caspase-3 pathway. Conclusion: the colorectal cancer apoptosis network based on p42.3 established in the study provides theoretical evidence for deep exploration of p42.3 regulatory mechanism and molecular targeting treatment of colorectal cancer

High Skp2/Low p57Kip2 Expression is Associated with Poor Prognosis in Human Breast Carcinoma

Downregulation of p57 Kip2 is involved in tumor progression, and S-phase kinase-associated protein 2 (Skp2) is an E3 ligase that regulates a variety of cell cycle proteins. However, the prognostic value of p57 Kip2 and its correlation with Skp2 in breast cancer have not been fully elucidated. Here we report our study on the expression of p57 Kip2 and Skp2 in 102 breast cancer patients by immunohistochemistry, and analysis of clinicopathologic parameters in relation to patient prognosis. The expression of p57 Kip2 was negatively associated with Skp2 expression in breast cancer ( r = −0.26, P = 0.009). Kaplan–Meier analysis indicated that both high Skp2 and low p57 Kip2 correlated with poor disease-free survival (DFS) (P < 0.05), and a group with the combination of high Skp2/low p57 Kip2 demonstrated even worse DFS (log-rank = 21.118, P < 0.001). In addition, univariate analysis showed that Skp2, p57 Kip2 , histological grade, lymph node metastasis, and estrogen and progesterone receptors (ER and PR) were all associated with DFS, and multivariate analysis revealed that lymph node metastasis and Skp2 were independent prognostic biomarkers. The correlation between p57 and Skp2 was further demonstrated in multiple breast cancer cell lines and cell cycle phases. Half-life and immunoprecipitation (IP) experiments indicated that Skp2 directly interacts with p57 Kip2 and promotes its degradation, rather than its mutant p57 Kip2 (T310A). Overall, our findings demonstrate that Skp2 directly degrades p57 Kip2 , and an inverse correlation between these proteins (high skp2/low p57 Kip2 ) is associated with poor prognosis in breast cancer. Thus, our results indicate a combined prognostic value of these markers in breast cancer diagnosis and treatment