Study on the biomechanical properties of 3D printed blended esophageal stents with different structural parameters based on patient CT

Introduction: Esophageal stenting is a widely used treatment for esophageal diseases, which can also be used for adjuvant therapy and feeding after chemotherapy for esophageal cancer. The structural parameters of the stent have a significant impact on its mechanical properties and patient comfort.Methods: In the present work, we reconstructed the esophagus model based on the patient’s computed tomography (CT) data, and designed stents with different structural parameters. We used 3D printing technology to achieve rapid production of the designed stents by using Thermoplastic polyurethane (TPU)/Poly-ε-caprolactone (PCL) blends as the materials. The mechanical properties and effects on the esophagus of polymer stents with four different structural parameters of diameter, wall thickness, length and flaring were investigated by in vitro tests of radial compression and migration of the stents, as well as by finite element simulations of the stent implantation process in the esophagus and of the stent migration process. An artificial neural network model was established to predict the radial force of the stent and the maximum equivalent stress of the esophagus during implantation based on these four structural parameters.Results: The results show that wall thickness was the structural parameter that had the greatest impact on the radial force of the stent (statistically significant, p < 0.01), and flaring was the structural parameter that had the greatest impact on the maximum equivalent stress of the esophageal wall after stent implantation (statistically significant, p < 0.01). No. 6 stent had a maximum radial force of 18.07 N, which exceeded that of commercial esophageal stents and had good mechanical properties. And the maximum equivalent force on the esophagus caused by its implantation was only 30.39 kPa, which can improve patient comfort. The predicted values of the constructed back propagation (BP) neural network model had an error of less than 10% from the true values, and the overall prediction accuracies were both above 97%, which can provide guidance for optimizing the design of the stent and for clinical research.Discussion: 3D printing technology presents a wide range of applications for the rapid fabrication of personalized TPU/PCL blend stents that are more suitable for individual patients

Genome-Wide Linkage Mapping Reveals QTLs for Seed Vigor-Related Traits Under Artificial Aging in Common Wheat (Triticum aestivum)

Long-term storage of seeds leads to lose seed vigor with slow and non-uniform germination. Time, rate, homogeneity, and synchrony are important aspects during the dynamic germination process to assess seed viability after storage. The aim of this study is to identify quantitative trait loci (QTLs) using a high-density genetic linkage map of common wheat (Triticum aestivum) for seed vigor-related traits under artificial aging. Two hundred and forty-six recombinant inbred lines derived from the cross between Zhou 8425B and Chinese Spring were evaluated for seed storability. Ninety-six QTLs were detected on all wheat chromosomes except 2B, 4D, 6D, and 7D, explaining 2.9–19.4% of the phenotypic variance. These QTLs were clustered into 17 QTL-rich regions on chromosomes 1AL, 2DS, 3AS (3), 3BS, 3BL (2), 3DL, 4AS, 4AL (3), 5AS, 5DS, 6BL, and 7AL, exhibiting pleiotropic effects. Moreover, 10 stable QTLs were identified on chromosomes 2D, 3D, 4A, and 6B (QaMGT.cas-2DS.2, QaMGR.cas-2DS.2, QaFCGR.cas-2DS.2, QaGI.cas-3DL, QaGR.cas-3DL, QaFCGR.cas-3DL, QaMGT.cas-4AS, QaMGR.cas-4AS, QaZ.cas-4AS, and QaGR.cas-6BL.2). Our results indicate that one of the stable QTL-rich regions on chromosome 2D flanked by IWB21991 and IWB11197 in the position from 46 to 51 cM, presenting as a pleiotropic locus strongly impacting seed vigor-related traits under artificial aging. These new QTLs and tightly linked SNP markers may provide new valuable information and could serve as targets for fine mapping or markers assisted breeding

The LSD1-Interacting Protein GILP Is a LITAF Domain Protein That Negatively Regulates Hypersensitive Cell Death in Arabidopsis

Hypersensitive cell death, a form of avirulent pathogen-induced programmed cell death (PCD), is one of the most efficient plant innate immunity. However, its regulatory mechanism is poorly understood. AtLSD1 is an important negative regulator of PCD and only two proteins, AtbZIP10 and AtMC1, have been reported to interact with AtLSD1.To identify a novel regulator of hypersensitive cell death, we investigate the possible role of plant LITAF domain protein GILP in hypersensitive cell death. Subcellular localization analysis showed that AtGILP is localized in the plasma membrane and its plasma membrane localization is dependent on its LITAF domain. Yeast two-hybrid and pull-down assays demonstrated that AtGILP interacts with AtLSD1. Pull-down assays showed that both the N-terminal and the C-terminal domains of AtGILP are sufficient for interactions with AtLSD1 and that the N-terminal domain of AtLSD1 is involved in the interaction with AtGILP. Real-time PCR analysis showed that AtGILP expression is up-regulated by the avirulent pathogen Pseudomonas syringae pv. tomato DC3000 avrRpt2 (Pst avrRpt2) and fumonisin B1 (FB1) that trigger PCD. Compared with wild-type plants, transgenic plants overexpressing AtGILP exhibited significantly less cell death when inoculated with Pst avrRpt2, indicating that AtGILP negatively regulates hypersensitive cell death.These results suggest that the LITAF domain protein AtGILP localizes in the plasma membrane, interacts with AtLSD1, and is involved in negatively regulating PCD. We propose that AtGILP functions as a membrane anchor, bringing other regulators of PCD, such as AtLSD1, to the plasma membrane. Human LITAF domain protein may be involved in the regulation of PCD, suggesting the evolutionarily conserved function of LITAF domain proteins in the regulation of PCD

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

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

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