Unraveling the role of VLDL in the relationship between type 2 diabetes and coronary atherosclerosis: a Mendelian randomization analysis

BackgroundThe causal link between Type 2 diabetes (T2D) and coronary atherosclerosis has been established through wet lab experiments; however, its analysis with Genome-wide association studies (GWAS) data remains unexplored. This study aims to validate this relationship using Mendelian randomization analysis and explore the potential mediation of VLDL in this mechanism.MethodsEmploying Mendelian randomization analysis, we investigated the causal connection between T2D and coronary atherosclerosis. We utilized GWAS summary statistics from European ancestry cohorts, comprising 23,363 coronary atherosclerosis patients and 195,429 controls, along with 32,469 T2D patients and 183,185 controls. VLDL levels, linked to SNPs, were considered as a potential mediating causal factor that might contribute to coronary atherosclerosis in the presence of T2D. We employed the inverse variance weighted (IVW), Egger regression (MR-Egger), weighted median, and weighted model methods for causal effect estimation. A leave-one-out sensitivity analysis was conducted to ensure robustness.ResultsOur Mendelian randomization analysis demonstrated a genetic association between T2D and an increased coronary atherosclerosis risk, with the IVW estimate at 1.13 [95% confidence interval (CI): 1.07–1.20]. Additionally, we observed a suggestive causal link between T2D and VLDL levels, as evidenced by the IVW estimate of 1.02 (95% CI: 0.98–1.07). Further supporting lipid involvement in coronary atherosclerosis pathogenesis, the IVW-Egger estimate was 1.30 (95% CI: 1.06–1.58).ConclusionIn conclusion, this study highlights the autonomous contributions of T2D and VLDL levels to coronary atherosclerosis development. T2D is linked to a 13.35% elevated risk of coronary atherosclerosis, and within T2D patients, VLDL concentration rises by 2.49%. Notably, each standard deviation increase in VLDL raises the likelihood of heart disease by 29.6%. This underscores the significant role of lipid regulation, particularly VLDL, as a mediating pathway in coronary atherosclerosis progression

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

Characterization and Hepatoprotections of Ganoderma lucidum Polysaccharides against Multiple Organ Dysfunction Syndrome in Mice

Background. The liver is one of the most commonly affected organs in multiple organ dysfunction syndrome (MODS). In recent years, there have been many studies on Ganoderma lucidum polysaccharides (GLP), but the role of GLP in MODS is still unclear. The purpose of this work was to explore the antioxidant, anti-inflammatory, and protective effects of GLP on the liver in MODS model mice. Methods. The characteristic properties of GLP were processed by physicochemical analysis. The MODS models were successfully established with intraperitoneal injection of zymosan in Kunming strain mice. The antioxidant, anti-inflammatory, and hepatoprotective effects of GLP were processed both in vitro and in vivo by evaluating the oxidative parameters, inflammatory factors, and liver pathological observations. Results. The characterization analysis revealed that GLP was a pyranose mainly composed of glucose with the molecular weights (Mw) of 8309 Da. The experimental results proved that GLP had potential hepatoprotection possibly by improving the antioxidant status (scavenging excessive oxygen radicals, increasing the antioxidant enzyme activities, and reducing the lipid peroxide), alleviating the inflammatory response (reducing the inflammatory factor levels), and guaranteeing the liver functions. Conclusions. This research suggested that GLP had the potential to be developed as a natural medicine for the treatment of multiple organ failure

DEEP LEARNING MODELING USING T1-WEIGHTED IMAGES IN MAGNETIC RESONANCE IMAGING OF THE KNEE JOINTS AND ITS USE IN AGE ESTIMATION OF LIVING BODIES

Objective To discuss deep learning modeling using T1-weighted images (T1WI) in magnetic resonance imaging (MRI) of the knee joints and its use in age estimation of adolescents. Methods The T1WI of the knee joints were collected from 1 212 male patients aged 10-18 years who were admitted to The Affiliated Hospital of Qingdao University from January 2015 to December 2021 (internal data set) and 341 male patients of the same ages who were admitted to Qingdao Municipal Hospital during the same period (external data set). After labeling and image segmentation of the epiphyseal plates of the distal femurs and proximal tibiae, the internal data set was divided into training group (971 cases) and validation group (241 cases) at a ratio of 8∶2 according to their age groups using a random number table for modeling, and the external data set (test group) was used for model evaluation. The performance of the model was tested and validated based on accuracy, precision, recall rate, sensitivity, and specificity. Results The accuracy, precision, recall rate, specificity, and sensitivity of the validation group were 85.713%, 84.732%, 85.713%, 97.729%, and 85.713%, respectively; the same indicators of the test group were 82.578%, 83.145%, 82.578%, 97.442%, and 82.578%, respectively. There were no significant differences in the above indicators between the validation group and the test group (P>0.05). Conclusion A deep learning model based on the T1WI of the knee joints is successfully constructed, and it can be used for age estimation of adolescents aged 10-18 years

Metal transducer-assisted acoustic deformation potential characterization via coherent acoustic phonon dynamics

Acoustic deformation potential (ADP) plays a significant role in quantifying carrier-acoustic phonon interactions in semiconductors. In this work, we report a novel ultrafast spectroscopy method to extract the ADP coupling constant of a semiconductor by jointly analyzing the coherent acoustic phonon signals with and without a metal transducer. By applying this method to GaAs, the ADP coupling constant corresponding to the band gap was extracted using a pump photon energy near the band gap, which agrees well with literature values. With a larger pump photon energy, the ADP coupling constant deviates from the one for the band gap, which is attributed to contributions from the carrier dynamics in multiple energy and wavevector states