Sichuan University

About: Sichuan University is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 107623 authors who have published 102844 publications receiving 1612131 citations. The organization is also known as: Sìchuān Dàxué.

SARS-Coronavirus Open Reading Frame-3a drives multimodal necrotic cell death.

Abstract: The molecular mechanisms underlying the severe lung pathology that occurs during SARS-CoV infections remain incompletely understood The largest of the SARS-CoV accessory protein open reading frames (SARS 3a) oligomerizes, dynamically inserting into late endosomal, lysosomal, and trans-Golgi-network membranes While previously implicated in a non-inflammatory apoptotic cell death pathway, here we extend the range of SARS 3a pathophysiologic targets by examining its effects on necrotic cell death pathways We show that SARS 3a interacts with Receptor Interacting Protein 3 (Rip3), which augments the oligomerization of SARS 3a helping drive necrotic cell death In addition, by inserting into lysosomal membranes SARS 3a triggers lysosomal damage and dysfunction Consequently, Transcription Factor EB (TFEB) translocates to the nucleus increasing the transcription of autophagy- and lysosome-related genes Finally, SARS 3a activates caspase-1 either directly or via an enhanced potassium efflux, which triggers NLRP3 inflammasome assembly In summary, Rip3-mediated oligomerization of SARS 3a causes necrotic cell death, lysosomal damage, and caspase-1 activation—all likely contributing to the clinical manifestations of SARS-CoV infection

Structurally-Sensitive Multi-Scale Deep Neural Network for Low-Dose CT Denoising

Abstract: Computed tomography (CT) is a popular medical imaging modality and enjoys wide clinical applications. At the same time, the X-ray radiation dose associated with CT scannings raises a public concern due to its potential risks to the patients. Over the past years, major efforts have been dedicated to the development of low-dose CT (LDCT) methods. However, the radiation dose reduction compromises the signal-to-noise ratio, leading to strong noise and artifacts that down-grade the CT image quality. In this paper, we propose a novel 3-D noise reduction method, called structurally sensitive multi-scale generative adversarial net, to improve the LDCT image quality. Specifically, we incorporate 3-D volumetric information to improve the image quality. Also, different loss functions for training denoising models are investigated. Experiments show that the proposed method can effectively preserve the structural and textural information in reference to the normal-dose CT images and significantly suppress noise and artifacts. Qualitative visual assessments by three experienced radiologists demonstrate that the proposed method retrieves more information and outperforms competing methods.

Novel Multifunctional Organic–Inorganic Hybrid Curing Agent with High Flame-Retardant Efficiency for Epoxy Resin

Abstract: A novel multifunctional organic–inorganic hybrid was designed and prepared based on ammonium polyphosphate (APP) by cation exchange with diethylenetriamine (DETA), abbreviated as DETA-APP. Then DETA-APP was used as flame-retardant curing agent for epoxy resin (EP). Curing behavior, including the curing kinetic parameters, was investigated by differential scanning calorimetry (DSC) and X-ray photoelectron spectroscopy (XPS). The flame retardance and burning behavior of DETA-APP cured EP were also evaluated. The limiting oxygen index (LOI) value of DETA-APP/EP was enhanced to 30.5% with only 15 wt % of DETA-APP incorporated; and the UL-94 V-0 rating could be easily passed through with only 10 wt % of the hybrid. Compared with DETA/EP, the peak-heat release rate (PHRR), total heat release (THR), total smoke production (TSP), and peak-smoke production release (SPR) of DETA-APP/EP (15 wt % addition), obtained from cone calorimetry, were dropped by 68.3, 79.3, 79.0, and 30.0%, respectively, suggesting excellent...