Scaling of Anisotropic Flows and Nuclear Equation of State in Intermediate Energy Heavy Ion Collisions

Elliptic flow ($v_2$) and hexadecupole flow ($v_4$) of light clusters have been studied in details for 25 MeV/nucleon $^{86}$Kr + $^{124}$Sn at large impact parameters by Quantum Molecular Dynamics model with different potential parameters. Four parameter sets which include soft or hard equation of state (EOS) with/without symmetry energy term are used. Both number-of-nucleon ($A$) scaling of the elliptic flow versus transverse momentum ($p_t$) and the scaling of $v_4/A^{2}$ versus $(p_t/A)^2$ have been demonstrated for the light clusters in all above calculation conditions. It was also found that the ratio of $v_4/{v_2}^2$ keeps a constant of 1/2 which is independent of $p_t$ for all the light fragments. By comparisons among different combinations of EOS and symmetry potential term, the results show that the above scaling behaviors are solid which do not depend the details of potential, while the strength of flows is sensitive to EOS and symmetry potential term.Comment: 5 pages, 5 figure

BAG5 Interacts with DJ-1 and Inhibits the Neuroprotective Effects of DJ-1 to Combat Mitochondrial Oxidative Damage

Loss-of-function mutations in gene encoding DJ-1 contribute to the pathogenesis of autosomal recessive early-onset familial forms of Parkinson’s disease (PD). DJ-1 is a multifunctional protein and plays a protective role against oxidative stress-induced mitochondrial damage and cell death, but the exact mechanism underlying this is not yet clearly understood. Here, using coimmunoprecipitation (Co-IP) and immunofluorescence methods, we prove that Bcl-2-associated athanogene 5 (BAG5), a BAG family member, interacts with DJ-1 in mammalian cells. Moreover, we show that BAG5 could decrease stability of DJ-1 and weaken its role in mitochondrial protection probably by influencing dimerization in stress condition. Our study reveals the relationship of BAG5 and DJ-1 suggesting a potential role for BAG5 in the pathogenesis of PD through its functional interactions with DJ-1

Development of a deep learning model for early gastric cancer diagnosis using preoperative computed tomography images

BackgroundGastric cancer is a highly prevalent and fatal disease. Accurate differentiation between early gastric cancer (EGC) and advanced gastric cancer (AGC) is essential for personalized treatment. Currently, the diagnostic accuracy of computerized tomography (CT) for gastric cancer staging is insufficient to meet clinical requirements. Many studies rely on manual marking of lesion areas, which is not suitable for clinical diagnosis.MethodsIn this study, we retrospectively collected data from 341 patients with gastric cancer at the First Affiliated Hospital of Wenzhou Medical University. The dataset was randomly divided into a training set (n=273) and a validation set (n=68) using an 8:2 ratio. We developed a two-stage deep learning model that enables fully automated EGC screening based on CT images. In the first stage, an unsupervised domain adaptive segmentation model was employed to automatically segment the stomach on unlabeled portal phase CT images. Subsequently, based on the results of the stomach segmentation model, the image was cropped out of the stomach area and scaled to a uniform size, and then the EGC and AGC classification models were built based on these images. The segmentation accuracy of the model was evaluated using the dice index, while the classification performance was assessed using metrics such as the area under the curve (AUC) of the receiver operating characteristic (ROC), accuracy, sensitivity, specificity, and F1 score.ResultsThe segmentation model achieved an average dice accuracy of 0.94 on the hand-segmented validation set. On the training set, the EGC screening model demonstrated an AUC, accuracy, sensitivity, specificity, and F1 score of 0.98, 0.93, 0.92, 0.92, and 0.93, respectively. On the validation set, these metrics were 0.96, 0.92, 0.90, 0.89, and 0.93, respectively. After three rounds of data regrouping, the model consistently achieved an AUC above 0.9 on both the validation set and the validation set.ConclusionThe results of this study demonstrate that the proposed method can effectively screen for EGC in portal venous CT images. Furthermore, the model exhibits stability and holds promise for future clinical applications

Calibration of X-ray telescope prototypes at PANTER

We report a ground X-ray calibration of two X-ray telescope prototypes at the PANTER X-ray Test Facility, of the Max-Planck-Institute for Extraterrestrial Physics, in Neuried, Germany. The X-ray telescope prototypes were developed by the Institute of Precision Optical Engineering (IPOE) of Tongji University, in a conical Wolter-I configuration, using thermal glass slumping technology. Prototype #1 with 3 layers and Prototype #2 with 21 layers were tested to assess the prototypes' on-axis imaging performance. The measurement of Prototype #1 indicates a Half Power Diameter (HPD) of 82" at 1.49 keV. As for Prototype #2, we performed more comprehensive measurements of on-axis angular resolution and effective area at several energies ranging from 0.5-10 keV. The HPD and effective area are 111" and 39 cm^2 at 1.49 keV, respectively, at which energy the on-axis performance of the prototypes is our greatest concern.Comment: 11 pages, 9 figure

Study on the One-Proton Halo Structure in 23^{23}Al

The Glauber theory has been used to investigate the reaction cross section of proton-rich nucleus $^{23}$Al. A core plus a proton structure is assumed for $^{23}$Al. HO-type density distribution is used for the core while the density distribution for the valence proton is calculated by solving the eigenvalue problem of Woods-Saxon potential. The transparency function in an analytical expression is obtained adopting multi-Gaussian expansion for the density distribution. Coulomb correction and finite-range interaction are introduced. This modified Glauber model is apt for halo nuclei. A dominate s-wave is suggested for the last proton in $^{23}$Al from our analysis which is possible in the RMF calculation.Comment: 4 pages, 4 figure

A simulation study on the measurement of D0-D0bar mixing parameter y at BES-III

We established a method on measuring the \dzdzb mixing parameter $y$ for BESIII experiment at the BEPCII $e^+e^-$ collider. In this method, the doubly tagged $\psi(3770) \to D^0 \overline{D^0}$ events, with one $D$ decays to CP-eigenstates and the other $D$ decays semileptonically, are used to reconstruct the signals. Since this analysis requires good $e/\pi$ separation, a likelihood approach, which combines the $dE/dx$, time of flight and the electromagnetic shower detectors information, is used for particle identification. We estimate the sensitivity of the measurement of $y$ to be 0.007 based on a $20fb^{-1}$ fully simulated MC sample.Comment: 6 pages, 7 figure

1,8-Cineole Ameliorates LPS-Induced Vascular Endothelium Dysfunction in Mice via PPAR-γ Dependent Regulation of NF-κB

1,8-Cineole (eucalyptol), a monoterpene, has been widely reported for the anti-inflammatory effects. Our previous data confirmed that 1,8-cineole ameliorated the inflammatory phenotype of human umbilical vein endothelial cells (HUVECs) by mediating NF-κB expression in vitro. At present, we investigated the protection effects of 1,8-cineole on vascular endothelium in lipopolysaccharide (LPS)-induced acute inflammatory injury mice and the potential mechanisms involved in the protection in HUVECs. Results from enzyme linked immunosorbent assays revealed that 1,8-cineole suppressed the secretion of interleukin (IL)-6 and IL-8 and increased the expression of IL-10 in the serum of LPS-induced mice. 1,8-Cineole reduced the inflammatory infiltration and the expression of vascular cell adhesion molecular 1 (VCAM-1) in the sections of thoracic aorta in LPS-induced acute inflammatory mice. Western blotting indicated that 1,8-cineole significantly decreased the phosphorylation of NF-κB p65 and increased the expression of PPAR-γ in the thoracic aorta tissue. 1,8-Cineole increased the expression of PPAR-γ in LPS-induced HUVECs. 1,8-Cineole and rosiglitazone reduced the protein and mRNA levels of VCAM-1, E-selectin, IL-6, and IL-8 in LPS-induced HUVECs, which could be reversed by the action of GW9662 (inhibitor of PPAR-γ). 1,8-Cineole and rosiglitazone blocked the LPS-induced IκBα degradation and NF-κB p65 nucleus translocation, which could be reversed by the pretreatment of GW9662 or silence of PPAR-γ gene. In conclusion, 1,8-cineole attenuated LPS-induced vascular endothelial cells injury via PPAR-γ dependent modulation of NF-κB