Has China gained significant influence over ASEAN? : from the golden decade to the diamond decade

published_or_final_versionInternational and Public AffairsMasterMaster of International and Public Affair

Accurately identifying hemagglutinin using sequence information and machine learning methods

IntroductionHemagglutinin (HA) is responsible for facilitating viral entry and infection by promoting the fusion between the host membrane and the virus. Given its significance in the process of influenza virus infestation, HA has garnered attention as a target for influenza drug and vaccine development. Thus, accurately identifying HA is crucial for the development of targeted vaccine drugs. However, the identification of HA using in-silico methods is still lacking. This study aims to design a computational model to identify HA.MethodsIn this study, a benchmark dataset comprising 106 HA and 106 non-HA sequences were obtained from UniProt. Various sequence-based features were used to formulate samples. By perform feature optimization and inputting them four kinds of machine learning methods, we constructed an integrated classifier model using the stacking algorithm.Results and discussionThe model achieved an accuracy of 95.85% and with an area under the receiver operating characteristic (ROC) curve of 0.9863 in the 5-fold cross-validation. In the independent test, the model exhibited an accuracy of 93.18% and with an area under the ROC curve of 0.9793. The code can be found from https://github.com/Zouxidan/HA_predict.git. The proposed model has excellent prediction performance. The model will provide convenience for biochemical scholars for the study of HA

Slug enhances invasion ability of pancreatic cancer cells through upregulation of matrix metalloproteinase-9 and actin cytoskeleton remodeling

Slug, a member of the Snail family of transcription factors, has a crucial role in the regulation of epithelial-mesenchymal transition (EMT) by suppressing several epithelial markers and adhesion molecules, including E-cadherin. A recent study demonstrated that no relationship exists between Slug and E-cadherin in pancreatic cancer. Another study showed that in malignant mesothelioma effusions Slug was associated with matrix metalloproteinase (MMP) expression, but that there was no association with E-cadherin. F-ascin is an actin-bundling protein involved in filopodia assembly and cancer invasion and metastasis of multiple epithelial cancer types. In this study, we investigated Slug, E-cadherin, and MMP-9 expression using immunohistochemistry in 60 patients with pancreatic cancer and their correlation with carcinoma invasion and metastasis. Additionally, we observed the effects of Slug on invasion and metastasis in the pancreatic cancer cell line PANC-1. Alterations in Slug, MMP-9, and E-cadherin were determined by RT-PCR, western blot, and immunohistochemistry. Alterations in MMP-9 and F-actin cytoskeleton were determined by immunofluorescence staining, flow cytometry (FCM), or gelatin zymography. Slug, E-cadherin, and MMP-9 expression in pancreatic cancer was significantly associated with lymph node metastases and we found a significant correlation between Slug and MMP-9 expression; however, no significant correlation was observed between Slug and E-cadherin expression. Slug transfection significantly increased invasion and metastasis in PANC-1 cells and orthotopic tumor of mouse in vivo, and significantly upregulated and activated MMP-9; however, there was no effect on E-cadherin expression. Slug promoted the formation of lamelliopodia or filopodia in PANC-1 cells. The intracellular F-actin and MMP-9 was increased and relocated to the front of the extending pseudopodia from the perinuclear pool in Slug-transfected PANC-1 cells. These results suggest that Slug promotes migration and invasion of PANC-1 cells, which may correlate with the reorganization of MMP-9 and remodeling of the F-actin cytoskeleton, but not with E-cadherin expression

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

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

Risk Factors Associated with the Incidence of Ventricular Arrhythmias Complicating Acute Myocardial Infarction and Prognosis Analysis

Ventricular arrhythmias (VTA) usually occur following acute myocardial infarction (AMI). However, risk factors for VTA attack after AMI have been not well-recognized. The purpose of the study is to identify risk factors associated with the incidence of VTA complicating AMI. A total of 200 patients with AMI who were admitted to our hospital from February 2018 to February 2020 were retrospectively analyzed. These 200 patients were classified into a non-VTA group (n=140) and a VTA group (n=60) based on the occurrence of VTA within 24 after AMI. Patients in the VTA group were older than those in the non-VTA group. The VTA group had more numbers of WBCs and neutrophils than the non-VTA group. The level of serum potassium was lower, but the levels of cTnT and CK-MB were higher in the VTA group than in the non-VTA group. The VTA group presented an increase in proportions of anterior MI, TpTe, and proportions of Killip classification≥class II but a decline in LVEF when comparable to the non-VTA group. The two groups were not significantly different concerning other variables including sex, tobacco use, alcohol consumption, diabetes mellitus, hypertension, heart rate, Scr, SUA, BUN, PTL counts, TC, TG, HDL-C, LDL-C, D-dimer, BNP, LVS, LVP, and LVEDd. The levels of hsCRP, endothelin-1, and TNF-α were remarkably higher in the VTA group than in the non-VTA group (P<0.001). Multivariate logistic regression analysis was performed, with clinical variables including age, WBCs, neutrophils, serum potassium, cTnT, CK-MB, hsCRP, endothelin-1, TNF-α, anterior MI, TpTe, proportions of Killip classification≥class II, and LVEF as an independent variable and with the occurrence of VTA as a dependent variable. It was revealed that serum potassium, cTnT, CK-MB, hsCRP, endothelin-1, TpTe, proportions of Killip classification≥class II, and LVEF were independent risk factors of VTA complicating AMI. Compared with the non-VTA group, the incidence rate of simple left heart failure, total heart failure, stroke, and dyslipidemia in the VTA group was significantly higher than those in the non-VTA group (P<0.05). It was found that the proportion of all-cause deaths within one year outside the hospital was higher in the VAT group than in the non-VAT group (P<0.05). Collectively, the study demonstrates serum potassium, cTnT, CK-MB, hsCRP, endothelin-1, TpTe, proportions of Killip classification≥class II, and LVEF were independent risk factors of VTA complicating AMI

Risk prediction for dermatomyositis-associated hepatocellular carcinoma

Abstract Objective To explore dermatomyositis signature genes as potential biomarkers of hepatocellular carcinoma and their associated molecular regulatory mechanisms. Methods Based on the mRNA-Seq data of dermatomyositis and hepatocellular carcinoma in public databases, five dermatomyositis signature genes were screened by LASSO regression analysis and support vector machine (SVM) algorithm, and their biological functions in dermatomyositis with hepatocellular carcinoma were investigated, and a nomogram risk prediction model for hepatocellular carcinoma was constructed and its predictive efficiency was initially evaluated. The immune profile in hepatocellular carcinoma was examined based on the CIBERSORT and ssGSEA algorithms, and the correlation between five dermatomyositis signature genes and tumor immune cell infiltration and immune checkpoints in hepatocellular carcinoma was investigated. Results The expression levels of five dermatomyositis signature genes were significantly altered in hepatocellular carcinoma and showed good diagnostic efficacy for hepatocellular carcinoma, suggesting that they may be potential predictive targets for hepatocellular carcinoma, and the risk prediction model based on five dermatomyositis signature genes showed good risk prediction efficacy for hepatocellular carcinoma and has good potential for clinical application. In addition, we also found that the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through integrin-mediated activation, which in turn regulates the development and progression of hepatocellular carcinoma. Conclusion LY6E, IFITM1, GADD45A, MT1M, and SPP1 are potential predictive targets for new-onset hepatocellular carcinoma in patients with dermatomyositis, and the upregulation of SPP1 expression may activate the PI3K/ART signaling pathway through the mediation of integrins to promote the development and progression of hepatocellular carcinoma