Sichuan University of Science and Engineering

BACKGROUND/AIMS: To study the potential role of the 78kDa glucose regulated protein (GRP78) in the pathogenesis of acute pancreatitis (AP) in vitro. METHODOLOGY: AR42J cells were stimulated by cerulein or cerulein plus lipoplysaccharide (LPS). The severity of pancreatic inflammation was evaluated by amylase, lipase, TNF-a, and IL-6. Apoptosis was determined by flow cytometry; the expressions of apoptotic genes, GRP78 and the downstream molecules were determined by real-time quantitative PCR and Western blot. RESULTS: After cerulein stimulation, the levels of amylase, lipase, TNF-a and IL-6 were all increased, with a more pronounced increase after cerulein plus LPS stimulation. Apoptosis was different in two cell models, high apoptosis in cerulein group; whereas cerulein plus LPS induced relatively less apoptosis. Apoptotic gene expressions revealed more pronounced increase in the cerulein group than those in cerulein plus LPS group. The expressions of GRP78 and downstream molecules were different in two cell models. GRP78 expression was down-regulated in cerulein group and upregulated in cerulein plus LPS group. CONCLUSIONS: GRP78 expression was associated with apoptosis and the severity of cerulein-induced pancreatic inflammation, indicating that GRP78 might prevent apoptosis in pancreatic acinar cells thereby deteriorating the severity of AP.

The present study provides an overview of the coronavirus disease 2019 (COVID-19) outbreak which has rapidly extended globally within a short period. COVID-19 is a highly infectious respiratory disease caused by a new coronavirus known as SARS-CoV-2 (severe acute respiratory syndrome-coronavirus-2). SARS-CoV-2 is different from usual coronaviruses responsible for mild sickness such as common cold among human beings. It is crucial to understand the impact and outcome of this pandemic. We therefore overview the changes in the curves of COVID-19 confirmed cases and fatality rate in China and outside of China from 31st of December 2019 to 25th of March 2020. We also aimed to assess the temporal developments and death rate of COVID-19 in China and worldwide. More than 414,179 confirmed cases of COVID-19 have been reported in 197 countries, including 81,848 cases in China and 332,331 outside of China. Furthermore, 18,440 infected patients died from COVID-19 infection; 3,287 cases were from China and 15,153 fatalities were reported worldwide. Among the worldwide infected cases, 113,802 patients have been recovered and discharged from different hospitals. Effective prevention and control measures should be taken to control the disease. The presented Chinese model (protocol) of disease prevention and control could be utilized in order to curb the pandemic situation.

Background In recent years, since the molecular docking technique can greatly improve the efficiency and reduce the research cost, it has become a key tool in computer‐assisted drug design to predict the binding affinity and analyze the interactive mode. Results This study introduces the key principles, procedures and the widely‐used applications for molecular docking. Also, it compares the commonly used docking applications and recommends which research areas are suitable for them. Lastly, it briefly reviews the latest progress in molecular docking such as the integrated method and deep learning. Conclusion Limited to the incomplete molecular structure and the shortcomings of the scoring function, current docking applications are not accurate enough to predict the binding affinity. However, we could improve the current molecular docking technique by integrating the big biological data into scoring function.

BACKGROUND/AIMS: To investigate the effectiveness and safety of central pancreatectomy. METHODOLOGY: We retrospectively studied 44 cases that underwent central pancreatectomy (CP), 55 patients who underwent distal pancreatectomy (DP), and 62 patients who underwent pancreatoduodenectomy (PD) for their benign or borderline pancreatic lesions; as well as the different management styles for pancreatic stumps in CP. RESULTS: The duration of surgery and length of hospital stay were shorter in the CP group than that of PD group, and blood loss was also less in CP group. There were no differences between the CP and DP groups in duration of surgery, length of hospital stay, and blood loss. The incidence of common surgical complications was higher in the PD group. There were more pancreatic fistulas (grade B/C) in CP and PD groups compared to that of the DP group. New onset or worsening of diabetes occurred only in the CP and PD groups at 4.8% and 10.9%, respectively. A pancreaticogastrostomy for distal pancreatic stumps reduced the incidence of pancreatic fistula (p=0.038). Duct-to-mucosa anastomosis had less pancreatic fistula than invagination anastomosis (p=0.017). There was no difference in incidence of pancreatic fistula between pancreaticojejunostomy and oversewing of proximal pancreatic stumps (p=0.601). CONCLUSIONS: CP is an available and safe operation for benign or borderline lesions located in the pancreatic neck. A pancreaticogastrostomy for distal pancreatic stumps or duct-to-mucosa anastomosis may reduce the risk of pancreatic fistula.

The orthogonal-signal-generator-based phase-locked loops (OSG-PLLs) are among the most popular single-phase PLLs within the areas of power electronics and power systems, mainly because they are often easy to be implemented and offer a robust performance against the grid disturbances. The main aim of this paper is to present a survey of the comparative performance evaluation among the state-of-the-art OSG-PLLs (include Delay-PLL, Deri-PLL, Park-PLL, SOGI-PLL, DOEC-PLL, VTD-PLL, CCF-PLL, and TPFA-PLL) under different grid disturbances such as voltage sags, phase, and frequency jumps, and in the presence of dc offset, harmonic components, and white noise in their input. This analysis provides a useful insight about the advantages and disadvantages of these PLLs. The performance enhancement of Delay-PLL, Deri-PLL, and CCF-PLL by including a moving average filter into their structure is another goal of this paper.

In this paper, we study a challenging problem in image restoration, namely, how to develop an all-in-one method that could recover images from a variety of unknown corruption types and levels. To this end, we propose an All-in-one Image Restoration Network (AirNet) consisting of two neural modules, named Contrastive-Based Degraded Encoder (CBDE) and Degradation-Guided Restoration Network (DGRN). The major advantages of AirNet are two-fold. First, it is an all-in-one solution which could recover various degraded images in one network. Second, AirNet is free from the prior of the corruption types and levels, which just uses the observed corrupted image to perform inference. These two advantages enable AirNet to enjoy better flexibility and higher economy in real world scenarios wherein the priors on the corruptions are hard to know and the degradation will change with space and time. Extensive experimental results show the proposed method outperforms 17 image restoration baselines on four challenging datasets. The code is available at https://github.com/XLearning-SCU/2022-CVPR-AirNet.

This research aimed to investigate effect of transformational leadership (TL) in stimulating employee creativity (EC) leading to organizational innovation (OI) and assess the moderating role of Intrinsic Motivation (IM) between TL and EC. The data was collected from 164 supervisor-employee dyads of 31 Pakistani software firms. A three-step approach to SEM was applied to examine mediator and moderator variables. The findings indicate that the Idealized Influence, Intellectual Stimulation, and Inspirational Motivation have a great influence on OI and EC but Individual Consideration was not found to be significantly related to OI and EC. The findings further proved the positive and significant moderating effect of IM for TL and EC. Thus, through TL style, EC can be promoted with the interactive effect of IM by inspiring employees to think out of the box leading to innovation in the organization. This paper attempts to contribute to the current literature by developing moderating role of IM. Furthermore, we have also examined how each dimension of TL is affecting EC, and OI, further some interesting discoveries are also made which other studies have not done before.

Bioceramics, because of its excellent biocompatible and mechanical properties, has always been considered as the most promising materials for hard tissue repair. It is well know that an appropriate cellular response to bioceramics surfaces is essential for tissue regeneration and integration. As the in vivo implants, the implanted bioceramics are immediately coated with proteins from blood and body fluids, and it is through this coated layer that cells sense and respond to foreign implants. Hence, the adsorption of proteins is critical within the sequence of biological activities. However, the biological mechanisms of the interactions of bioceramics and proteins are still not well understood. In this review, we will recapitulate the recent studies on the bioceramic-protein interactions.

Urbanization is a continuous process for a city’s economic development. Though rapid urbanization provides a huge employment opportunity for people, urban threats also increase proportionately due to natural and man-made hazards. Understanding urban resilience and sustainability is an urgent matter to face hazards in the rapidly urbanized world. Therefore, this study aims to clarify the concept and develop key indications of urban resilience and sustainability from the existing literature. A systematic literature review guided by PRISMA has been conducted using literature from 1 January 2001 to 30 November 2021. It argues that sustainability and resilience are interrelated paradigms that emphasize a system’s capacity to move toward desirable development paths. Resilience and sustainability are fundamentally concerned with preserving societal health and well-being within the context of a broader framework of environmental change. There are significant differences in their emphasis and time scales, particularly in the context of urbanization. This study has identified key indicators of urban resilience under three major components like adaptive capacity (education, health, food, and water), absorptive capacity (community support, urban green space, protective infrastructure, access to transport), and transformative capacity (communication technology, collaboration of multi-stakeholders, emergency services of government, community-oriented urban planning). This study also identified several indicators under major dimensions (social, economic, and environmental) of urban sustainability. The findings will be fruitful in understanding the dynamics of urban vulnerability and resilience and its measurement and management strategy from developed indicators.

Virtually all organosulfur compounds react with Fe(0) carbonyls to give the title complexes. These reactions are reviewed in light of major advances over the past few decades, spurred by interest in Fe2(μ-SR)2(CO)x centers at the active sites of the [FeFe]-hydrogenase enzymes. The most useful synthetic route to Fe2(μ-SR)2(CO)6 involves the reaction of thiols with Fe2(CO)9 and Fe3(CO)12. Such reactions can proceed via mono-, di-, and triiron intermediates. The reactivity of Fe(0) carbonyls toward thiols is highly chemoselective, and the resulting dithiolato complexes are fairly rugged. Thus, many complexes tolerate further synthetic elaboration directed at the organic substituents. A second major route involves alkylation of Fe2(μ-S2)(CO)6, Fe2(μ-SH)2(CO)6, and Li2Fe2(μ-S)2(CO)6. This approach is especially useful for azadithiolates Fe2[(μ-SCH2)2NR](CO)6. Elaborate complexes arise via addition of the FeSH group to electrophilic alkenes, alkynes, and carbonyls. Although the first example of Fe2(μ-SR)2(CO)6 was prepared from ferrous reagents, ferrous compounds are infrequently used, although the Fe(II)(SR)2 + Fe(0) condensation reaction is promising. Almost invariably low-yielding, the reaction of Fe3(CO)12, S8, and a variety of unsaturated substrates results in C-H activation, affording otherwise inaccessible derivatives. Thiones and related C═S-containing reagents are highly reactive toward Fe(0), often giving complexes derived from substituted methanedithiolates and C-H activation.

About half of the people who develop heart failure (HF) die within five years of diagnosis. Over the years, researchers have developed several machine learning-based models for the early prediction of HF and to help cardiologists to improve the diagnosis process. In this paper, we introduce an expert system that stacks two support vector machine (SVM) models for the effective prediction of HF. The first SVM model is linear and L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> regularized. It has the capability to eliminate irrelevant features by shrinking their coefficients to zero. The second SVM model is L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> regularized. It is used as a predictive model. To optimize the two models, we propose a hybrid grid search algorithm (HGSA) that is capable of optimizing the two models simultaneously. The effectiveness of the proposed method is evaluated using six different evaluation metrics: accuracy, sensitivity, specificity, the Matthews correlation coefficient (MCC), ROC charts, and area under the curve (AUC). The experimental results confirm that the proposed method improves the performance of a conventional SVM model by 3.3%. Moreover, the proposed method shows better performance compared to the ten previously proposed methods that achieved accuracies in the range of 57.85%-91.83%. In addition, the proposed method also shows better performance than the other state-of-the-art machine learning ensemble models.

Poly-γ-glutamic acid (γ-PGA) is a naturally occurring biopolymer made from repeating units of l-glutamic acid, d-glutamic acid, or both. Since some bacteria are capable of vigorous γ-PGA biosynthesis from renewable biomass, γ-PGA is considered a promising bio-based chemical and is already widely used in the food, medical, and wastewater industries due to its biodegradable, non-toxic, and non-immunogenic properties. In this review, we consider the properties, biosynthetic pathway, production strategies, and applications of γ-PGA. Microbial biosynthesis of γ-PGA and the molecular mechanisms regulating production are covered in particular detail. Genetic engineering and optimization of the growth medium, process control, and downstream processing have proved to be effective strategies for lowering the cost of production, as well as manipulating the molecular mass and conformational/enantiomeric properties that facilitate screening of competitive γ-PGA producers. Finally, future prospects of microbial γ-PGA production are discussed in light of recent progress, challenges, and trends in this field.

Oncolytic viruses (OVs) are emerging as potentially useful platforms in treatment methods for patients with tumors. They preferentially target and kill tumor cells, leaving healthy cells unharmed. In addition to direct oncolysis, the essential and attractive aspect of oncolytic virotherapy is based on the intrinsic induction of both innate and adaptive immune responses. To further augment this efficacious response, OVs have been genetically engineered to express immune regulators that enhance or restore antitumor immunity. Recently, combinations of OVs with other immunotherapies, such as immune checkpoint inhibitors (ICIs), chimeric antigen receptors (CARs), antigen-specific T-cell receptors (TCRs) and autologous tumor-infiltrating lymphocytes (TILs), have led to promising progress in cancer treatment. This review summarizes the intrinsic mechanisms of OVs, describes the optimization strategies for using armed OVs to enhance the effects of antitumor immunity and highlights rational combinations of OVs with other immunotherapies in recent preclinical and clinical studies.

Compared with the conventional DFT approach, SCC-DFTB method is more effective to deal with the adsorption issues of large size organic corrosion inhibitors on metal surface.

The novel coronavirus pneumonia (COVID-19) is an infectious acute respiratory infection caused by the novel coronavirus. The virus is a positive-strand RNA virus with high homology to bat coronavirus. In this study, conserved domain analysis, homology modeling, and molecular docking were used to compare the biological roles of certain proteins of the novel coronavirus. The results showed the ORF8 and surface glycoprotein could bind to the porphyrin, respectively. At the same time, orf1ab, ORF10, and ORF3a proteins could coordinate attack the heme on the 1-beta chain of hemoglobin to dissociate the iron to form the porphyrin. The attack will cause less and less hemoglobin that can carry oxygen and carbon dioxide. The lung cells have extremely intense poisoning and inflammatory due to the inability to exchange carbon dioxide and oxygen frequently, which eventually results in ground-glass-like lung images. The mechanism also interfered with the normal heme anabolic pathway of the human body, is expected to result in human disease. According to the validation analysis of these finds, chloroquine could prevent orf1ab, ORF3a, and ORF10 to attack the heme to form the porphyrin, and inhibit the binding of ORF8 and surface glycoproteins to porphyrins to a certain extent, effectively relieve the symptoms of respiratory distress. Since the ability of chloroquine to inhibit structural proteins is not particularly obvious, the therapeutic effect on different people may be different. Favipiravir could inhibit the envelope protein and ORF7a protein bind to porphyrin, prevent the virus from entering host cells, and catching free porphyrins. This paper is only for academic discussion, the correctness needs to be confirmed by other laboratories. Due to the side effects and allergic reactions of drugs such as chloroquine, please consult a qualified doctor for treatment details, and do not take the medicine yourself.

A unique microbiome that metabolizes lactate rather than ethanol for n-caproate production was obtained from a fermentation pit used for the production of Chinese strong-flavour liquor (CSFL). The microbiome was able to produce n-caproate at concentrations as high as 23.41 g/L at a maximum rate of 2.97 g/L/d in batch trials without in-line extraction. Compared with previous work using ethanol as the electron donor, the n-caproate concentration increased by 82.89%. High-throughput sequencing analysis showed that the microbiome was dominated by a Clostridium cluster IV, which accounted for 79.07% of total reads. A new process for n-caproate production was proposed, lactate oxidation coupled to chain elongation, which revealed new insight into the well-studied lactate conversion and carbon chain elongation. In addition, these findings indicated a new synthesis mechanism of n-caproate in CSFL. We believe that this efficient process will provide a promising opportunity for the innovation of waste recovery as well as for n-caproate biosynthesis.

Image processing plays a major role in neurologists' clinical diagnosis in the medical field. Several types of imagery are used for diagnostics, tumor segmentation, and classification. Magnetic resonance imaging (MRI) is favored among all modalities due to its noninvasive nature and better representation of internal tumor information. Indeed, early diagnosis may increase the chances of being lifesaving. However, the manual dissection and classification of brain tumors based on MRI is vulnerable to error, time-consuming, and formidable task. Consequently, this article presents a deep learning approach to classify brain tumors using an MRI data analysis to assist practitioners. The recommended method comprises three main phases: preprocessing, brain tumor segmentation using k-means clustering, and finally, classify tumors into their respective categories (benign/malignant) using MRI data through a finetuned VGG19 (i.e., 19 layered Visual Geometric Group) model. Moreover, for better classification accuracy, the synthetic data augmentation concept i s introduced to increase available data size for classifier training. The proposed approach was evaluated on BraTS 2015 benchmarks data sets through rigorous experiments. The results endorse the effectiveness of the proposed strategy and it achieved better accuracy compared to the previously reported state of the art techniques.

One of the main environmentally threatening factors is plastic waste which generates in great quantity and causes severe damage to both inhabitants and the environment. Commonly, plastic waste generated on the land ends up in water bodies, resulting in detrimental solid impacts on the aquatics via poisoning and flooding the marine ecosystem. Exploring various approaches to convert plastic wastes into new products known as an efficient way to manage them and to enhance the sustainability of the environment, discussed in this article. Moreover, the limitation of the application of plastic waste for construction purposes is also considered. It is wind up that the usage of plastic waste for construction purposes will significantly rectify the sustainability of our environment and also be regarded as a trustworthy source of materials for applying in conventional materials such as concrete and asphalt.

Chinese traditional liquor, a major type of global distilled spirits, offers a unique flavor system acquired across thousands of years of development. Owing to the various raw brewing materials, types of koji, fermentation vessels, and processes used during liquor production, significant differences can occur in the content of flavor chemical components, such as esters, alcohols, aromatics, ketones, nitrogen compounds, acids, and aldehydes in the resulting liquor. Therefore, the liquor can be characterized on the basis of four basic flavors: sauce-, strong-, light-, and rice-aroma, and eight derivative flavors: feng-, sesame-, chi-, te-, mixed-, laobaigan-, herbal-, and fuyu-aroma. In this review, we describe the production and development process of Chinese traditional liquor in detail; summarize the flavor types, flavor chemical composition characteristics, and research progress related to this liquor; and discuss the influence of trace chemical components on liquor flavor, with the aim of laying a theoretical foundation for stabilizing the quality and increasing the yield of traditional liquor.

Abscisic acid (ABA) plays a key role in plant growth and development. The effect of ABA in plants mainly depends on its concentration, which is determined by a balance between biosynthesis and catabolism of ABA. In this study, we characterize a unique UDP-glucosyltransferase (UGT), UGT71C5, which plays an important role in ABA homeostasis by glucosylating ABA to abscisic acid -: glucose ester (GE) in Arabidopsis (Arabidopsis thaliana). Biochemical analyses show that UGT71C5 glucosylates ABA in vitro and in vivo. Mutation of UGT71C5 and down-expression of UGT71C5 in Arabidopsis cause delay in seed germination and enhanced drought tolerance. In contrast, overexpression of UGT71C5 accelerates seed germination and reduces drought tolerance. Determination of the content of ABA and ABA-GE in Arabidopsis revealed that mutation in UGT71C5 and down-expression of UGT71C5 resulted in increased level of ABA and reduced level of ABA-GE, whereas overexpression of UGT71C5 resulted in reduced level of ABA and increased level of ABA-GE. Furthermore, altered levels of ABA in plants lead to changes in transcript abundance of ABA-responsive genes, correlating with the concentration of ABA regulated by UGT71C5 in Arabidopsis. Our work shows that UGT71C5 plays a major role in ABA glucosylation for ABA homeostasis.