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Aim: To investigate whether silibinin impacts diabetic periodontitis (DP) via mitochondrial regulation. Materials and Methods: In vivo, rats were divided into control, diabetes, DP and DP combined with silibinin groups. Diabetes and periodontitis were induced by streptozocin and silk ligation, respectively. Bone turnover was evaluated by microcomputed tomography, histology and immunohistochemistry. In vitro, human periodontal ligament cells (hPDLCs) were exposed to hydrogen peroxide (H2O2) with or without silibinin. Osteogenic function was analysed by Alizarin Red and alkaline phosphatase staining. Mitochondrial function and biogenesis were investigated by mitochondrial imaging assays and quantitative polymerase chain reaction. Activator and lentivirus-mediated knockdown of peroxisome proliferator-activated receptor gamma-coactivator 1-alpha (PGC-1α), a critical regulator of mitochondria biogenesis, was used to explore the mitochondrial mechanisms. Results: Silibinin attenuated periodontal destruction and mitochondrial dysfunction and enhanced mitochondrial biogenesis and PGC-1α expression in rats with DP. Meanwhile, silibinin promoted cell proliferation, osteogenesis and mitochondrial biogenesis and increased the PGC-1α level in hPDLCs exposed to H2O2. Silibinin also protected PGC-1α from proteolysis in hPDLCs. Furthermore, both silibinin and activator of PGC-1α ameliorated cellular injury and mitochondrial abnormalities in hPDLCs, while knockdown of PGC-1α abolished the beneficial effect of silibinin. Conclusions: Silibinin attenuated DP through the promotion of PGC-1α-dependent mitochondrial biogenesis.

Objective: Accurate preoperative prediction of sinonasal inverted papilloma (SNIP) malignant transformation is essential and challenging. In this study, 3.0T magnetic resonance was used for qualitative, quantitative, and multi-parametric analysis to evaluate the predictive value of magnetic resonance imaging (MRI) in malignant transformation. Methods: The data of patients with SNIP (n=83) or SNIP-transformed squamous cell carcinoma (SNIP-SCC) (n=21) were analysed retrospectively. Univariate analysis and multivariate logistic regression were used to establish models to predict the risk factors for the malignant transformation of SNIP. Receiver operating characteristic (ROC) curves were used to evaluate the ability of independent risk factors and related combination models to predict malignant transformation of SNIP. Result: Convoluted cerebriform pattern (CCP) mutation, apparent diffusion coefficient ratio (ADCr), and wash-in index (WII) 2 and 3 were independent risk factors for predicting malignant transformation of SNIP, with area under the ROC curve (AUC) values of 0.845, 0.862, 0.727, and 0.704, respectively. The AUC of the quantitative parameter model combined with ADCr and WII 2 and 3 was 0.910 for diagnosing malignant transformation. The AUC of the comprehensive model comprising all independent risk factors was 0.937, with a sensitivity, specificity, and accuracy of 90.48%, 90.36%, and 92.31%, respectively. Conclusion: Compared with assessing independent risk factors of CCP mutation, ADCr and WII, and the quantitative parameter model, the comprehensive model could improve the differential diagnosis ability of SNIP and SNIP-SCC, which provides an important imaging basis for the possible accurate preoperative evaluation of malignant transformation of SNIP.

Introduction: Limited experience exists regarding the clinical features of focal lipogranuloma inflammation of the lung, and there are no supporting guidelines for the diagnostic approach. Case Description: We present the case of a 20-year-old man who was found to have a pulmonary nodule with a smooth margin during a health examination. He underwent wedge resection of the left lower lung to achieve a tissue diagnosis; this showed focal lipogranuloma inflammation of the lung. Conclusion: In this report, we combined imaging and pathological findings to reach the diagnosis, with a view to assisting clinicians in navigating this challenging clinical situation.

Cloud storage has been deployed in various real-world applications. But how to enable Internet users to search over encrypted data and to enable data owners to perform fine-grained search authorization are of huge challenge. Attribute-based keyword search (ABKS) is a well-studied solution to the challenge, but there are some drawbacks that prevent its practical adoption in cloud storage context. First, the access policy in the index and the attribute set in the trapdoor are both in plaintext, they are likely to reveal the privacy of data owners and users. Second, the current ABKS schemes cannot provide multi-keyword search under the premise of ensuring security and efficiency. We explore an efficient way to connect the inner product encryption with the access control mechanism and search process in ABKS, and propose a privacy-protecting attribute-based conjunctive keyword search scheme. The proposed scheme provides conjunctive keyword search and ensures that the access policy and attribute set are both fully hidden. Formal security models are defined and the scheme is proved IND-CKA, IND-OKGA, access policy hiding and attribute set hiding. Finally, empirical simulations are carried out on real-world dataset, and the results demonstrate that our design outperforms other existing schemes in security and efficiency. &nbsp

Customer churn prevention has been one of the most pressing concerns for telcos to tackle in the rapidly changing telecom business over the past decade, as the industry has faced increased market saturation and intense competition. Social media electronic word-of-mouth (e-WoM) offers telcos with insights into the consumer experience. Capturing preferences and views about products/services via text messaging might increase the recovery mechanism for clients who may churn. This study collects postings from social media forums concerning Taiwan’s top five telecom firms in order to perform an opinion analysis that is thought to be strongly linked with prospective churning consumers. To collect topic-sentiment information, we employ the doc-based Heuristics-N-Phrase-Rules technique. In this study, the sentiment score of negative terms is determined, and correspondence analysis is used to highlight the features and profiles of probable churn consumers. To validate its efficacy, we propose comparing the derived profile information to the telecom company’s lost consumers. &nbsp

The aim of Sudoku puzzle is to fill in the blank cells in a square matrix consisting of nine 3x3 blocks with the numbers 1-9 in a way that no number appears more than once in any row, column, or block. We combined image processing, a convolutional neural network (CNN), and a Sudoku game algorithm to automatically place the numbers 1-9 in the blank cells of a Sudoku square matrix. An image of the Sudoku square matrix is first captured using a camera, and then the vertical lines, horizontal lines, and outer frame of the Sudoku square matrix are detected using Hough transform (HT). Based on the OpenCV module, we proposed an image processing algorithm that captures the numbers in the image and calculates the location coordinates of the numbers in the image. We trained the CNN using the MNIST handwritten digit dataset to recognize the numbers in the Sudoku square matrix. Finally, we used the Python programming language to design a Sudoku puzzle backtrace algorithm that automatically deduces and fills in the blank cells in the square matrix. This study provides further understanding of the critical operating principles of CNNs and lays down a foundation for future research. &nbsp

BACKGROUND: The main objective of this study was to predict the status of blood and the occurrence of lower limb deep vein thrombosis (DVT) after total knee arthroplasty(TKA) by means of mean platelet volume (MPV) combined with thromboelastography (TEG). METHODS: We collected 180 patients who underwent unilateral total knee arthroplasty between May 2015 and March 2022, and the patients were divided into DVT group and control group according to whole-leg ultrasonography on the seventh postoperative day. Blood count and TEG were performed on the day before surgery, the first day after surgery and the seventh day respectively. Multifactorial analysis was used to investigate whether the relevant parameters were independent predictors of DVT after TKA. RESULTS: MPV has the strongest correlation with the maximum amplitude (MA), followed by alpha-angle; MPV and alpha-angle on the first postoperative day are independent predictors of DVT. MPV in patients with thrombosis tends to rise and then fall in the perioperative period. The optimal threshold for MPV to predict thrombosis is 10.85 fL and the area under the ROC curve is 0.694, The area under the ROC curve increases to 0.815 using MPV combined with alpha-angle. In addition, MA, α-angle, composite coagulation index (CI) and MPV were all statistically higher in the DVT group than in the control group (p < 0.001). CONCLUSION: MPV is a predictor of DVT after TKA. It can reflect the hypercoagulable state of blood after surgery; Combination of MPV and alpha-angle on the first day after surgery in patients with TKA improves predictive power of DVT.

BACKGROUND: In view of the underlying health risks posed by X-ray radiation, the main goal of the present research is to achieve high-quality CT images at the same time as reducing x-ray radiation. In recent years, convolutional neural network (CNN) has shown excellent performance in removing low-dose CT noise. However, previous work mainly focused on deepening and feature extraction work on CNN without considering fusion of features from frequency domain and image domain. OBJECTIVE: To address this issue, we propose to develop and test a new LDCT image denoising method based on a dual-domain fusion deep convolutional neural network (DFCNN). METHODS: This method deals with two domains, namely, the DCT domain and the image domain. In the DCT domain, we design a new residual CBAM network to enhance the internal and external relations of different channels while reducing noise to promote richer image structure information. For the image domain, we propose a top-down multi-scale codec network as a denoising network to obtain more acceptable edges and textures while obtaining multi-scale information. Then, the feature images of the two domains are fused by a combination network. RESULTS: The proposed method was validated on the Mayo dataset and the Piglet dataset. The denoising algorithm is optimal in both subjective and objective evaluation indexes as compared to other state-of-the-art methods reported in previous studies. CONCLUSIONS: The study results demonstrate that by applying the new fusion model denoising, denoising results in both image domain and DCT domain are better than other models developed using features extracted in the single image domain.

In this paper, we investigated the relationship between ethanol conversion, C4 olefin selectivity, and temperature by establishing a series of mathematical models. Specifically, the relationship between temperature and ethanol conversion and selectivity to C4 olefins is discussed by solving linear regression equations. In addition, the support vector machine regression (SVR) model was used to describe the effect of independent variables on the ethanol conversion rate and C4 olefin selectivity. Finally, we investigated the effect of temperature change on catalyst activity.

Background: Low-Dose computed tomography (LDCT) reduces radiation damage to patients, however, the reconstructed images contain severe noise, which affects doctors’ diagnosis of the disease. The convolutional dictionary learning has the advantage of the shift-invariant property. The deep convolutional dictionary learning algorithm (DCDicL) combines deep learning and convolutional dictionary learning, which has great suppression effects on Gaussian noise. However, applying DCDicL to LDCT images cannot get satisfactory results. Objective: To address this challenge, this study proposes and tests an improved deep convolutional dictionary learning algorithm for LDCT image processing and denoising. Methods: First, we use a modified DCDicL algorithm to improve the input network and make it do not need to input noise intensity parameter. Second, we use DenseNet121 to replace the shallow convolutional network to learn the prior on the convolutional dictionary, which can obtain more accurate convolutional dictionary. Last, in the loss function, we add MSSIM to enhance the detail retention ability of the model. Results: The experimental results on the Mayo dataset show that the proposed model obtained an average value of 35.2975 dB in PSNR, which is 0.2954 –1.0573 dB higher than the mainstream LDCT algorithm, indicating the excellent denoising performance. Conclusion: The study demonstrates that the proposed new algorithm can effectively improve the quality of LDCT images acquired in the clinical practice.

Chunjiao Lu,&ast; Yi Liu,&ast; Yao Liu, Guanhua Kou, Yang Chen, Xuewei Wu, Yuhang Lv, Jiahao Cai, Renyuan Chen, Juanjuan Luo, Xiaojun Yang Guangdong Provincial Key Laboratory of Infectious Disease and Molecular Immunopathology, Shantou University Medical College, Shantou, 515041, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Juanjuan Luo; Xiaojun Yang, Guangdong Provincial Key Laboratory of Infectious Disease and Molecular Immunopathology, Shantou University Medical College, Shantou, 515041, People’s Republic of China, Tel +86-754-88900236, Fax +86-754-88900276, Email lujj770@163.com; yangx@stu.edu.cnIntroduction: Silver nanoparticles (AgNP) are widely used as coating materials. However, the potential risks of AgNP to human health, especially for neural and vascular systems, are still poorly understood.Methods: The vascular and neurotoxicity of various concentrations of AgNP in zebrafish were examined using fluorescence microscopy. In addition, Illumina high-throughput global transcriptome analysis was performed to explore the transcriptome profiles of zebrafish embryos after exposure to AgNP. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to elucidate the top 3000 differentially expressed genes (DEGs) between AgNP-exposed and control groups.Results: We systematically investigated the neural and vascular developmental toxicities of AgNP exposure in zebrafish. The results demonstrated that AgNP exposure could cause neurodevelopmental anomalies, including a small-eye phenotype, neuronal morphology defects, and inhibition of athletic abilities. In addition, we found that AgNP exposure induces angiogenesis malformation in zebrafish embryos. Further RNA-seq revealed that DEGs were mainly enriched in the neuroactive ligand-receptor interaction and vascular endothelial growth factor (Vegf) signaling pathways in AgNP-treated zebrafish embryos. Specifically, the mRNA levels of the neuroactive ligand-receptor interaction pathway and Vegf signaling pathway-related genes, including si:ch73-55i23.1, nfatc2a, prkcg, si:ch211-132p1.2, lepa, mchr1b, pla2g4aa, rac1b, p2ry6, adrb2, chrnb1, and chrm1b, were significantly regulated in AgNP-treated zebrafish embryos.Conclusion: Our findings indicate that AgNP exposure transcriptionally induces developmental toxicity in neural and vascular development by disturbing neuroactive ligand-receptor interactions and the Vegf signaling pathway in zebrafish embryos.Keywords: silver nanoparticles, neurological development, vascular development, developmental toxicity, zebrafish

Zinc is one of the essential trace elements in the human body. In recent years, Human society as a whole is increasingly aware of the nutritional role that zinc plays in human health.This paper mainly discusses the relationship between zinc and human health and how to supplement zinc scientifically and lists the various effects of zinc on human metabolism. In this paper, the trace element zinc was studied through literature analysis, case analysis, data analysis, and review methods. The research data mainly came from various types of zinc literature and newspapers and magazines. This paper finds that zinc is extremely important element for human growth and development, it can resist and eliminate pathogens in the body. Meanwhile, the relationship between zinc and the metabolism of our human body is very close. Only by obtaining enough zinc, can the cells in our various organs and tissues maintain a relatively high metabolic rate.

Three new species of the Clubiona corticalis group in China are described: Clubiona bidactylinasp. nov., C. camelasp. nov., and C. subhuimingsp. nov.

Peiru Si,1 Jiaxing Lei,1 Chen Yang,1 Peipei Zhang,1 Xiaojiao Li,2 Shaohua Zheng,3 Qingqing Li,1 Jiye Zhang1 1School of Pharmacy, Health Science Center, Xi’an Jiaotong University, Xi’an, People’s Republic of China; 2Biobank, the First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, People’s Republic of China; 3Department of Anesthesiology, the First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, People’s Republic of ChinaCorrespondence: Qingqing Li; Jiye Zhang, School of Pharmacy, Health Science Center, Xi’an Jiaotong University, No. 76 Yanta Westroad, Xi’an, People’s Republic of China, Email liqingqing0217@xjtu.edu.cn; zjy2011@xjtu.edu.cnIntroduction: Hepatic ischemia-reperfusion injury (HIRI) is the main reason for liver dysfunction or failure after liver resection and liver transplantation. As excess accumulation of reactive oxygen species (ROS) is the leading factor, ceria nanoparticle, a cyclic reversible antioxidant, is an excellent candidate for HIRI.Methods: Manganese doped mesoporous hollow ceria nanoparticles (MnOx-CeO2 NPs) were prepared, and the physicochemical characteristics, such as particle size, morphology, microstructure, etc. were elucidated. The in vivo safety and liver targeting effect were examined after i.v. injection. The anti-HIRI was determined by a mouse HIRI model.Results: MnOx-CeO2 NPs with 0.40% Mn doped exhibited the strongest ROS-scavenging capability, which may due to the increased specific surface area and surface oxygen concentration. The nanoparticles accumulated in the liver after i.v. injection and exhibited good biocompatibility. In the HIRI mice model, MnOx-CeO2 NPs significantly reduced the serum ALT and AST level, decreased the MDA level and increased the SOD level in the liver, prevent pathological damages in the liver.Conclusion: MnOx-CeO2 NPs were successfully prepared and it could significantly inhibit the HIRI after i.v. injection.Graphical Abstract: Keywords: hepatic ischemia reperfusion injury, Mn-doped mesoporous hollow cerium oxide nanoparticles, oxidative stress

Hornsby and Langton argued the viewpoint of “illocutionary disablement” in pornography based on Austin’s Speech Act theory. They called this silencing and regarded it as a violation of free speech. Sharma has presented a profound criticism of the former study and issued her own opinions based mainly on the intentionalist point of view, which is inaccurate and not satisfactory enough. To further the discussion, this paper argues that the reason for her defects locates in the intentional fundament. This paper creatively puts speech acts into the framework of Wittgenstein’s Language Game Theory and Brandom’s Asserting Theory, namely, the social view. This paper finally reaches a conclusion that the basic essence of speech acts is conventionality based on language game and the social web created by asserting. The intention is the secondary essence, which is highly related to securing uptake when it comes to further taxonomy. On this new framework, this paper also put forward the questions of the relationships between speech act verbs and speech acts, the further taxonomy of non-conventional speech acts for future discussions.

Risk communcation strategies during the spread period of COVID-19 outbreak could have huge impacts on the development and transmission of pandemic. A proper strategy of risk communication could effectively reduce the adverse outcomes of the disease and lead to a nationwide recovery. In this study, the risk communication strategies adapted by two nations: China and Australia is investigated and concentrated on the January 2020 to July 2020, when the transmission of the disease was in an exponential ascending trend. The result of this study suggested that risk communication requires decent preparedness to be effective, and many lessons could be learnt from the reaction of both countries for further improvements.

ZTA ceramic materials are widely used in the field of orthodontics, however, the existing material preparation and its properties do not meet the requirements of orthodontic instruments. In this paper, SiC whiskers with high purity, high aspect ratio and stable properties were prepared by adding high hydrogen-containing silicone oil to ZTA ceramics to improve their fracture toughness and densities, and the ceramic matrix was prepared by gelation, curing and sintering with cellulose acrylic acid graft co-polymer as binder. In particular, the synergistic toughening effect with zirconia in the gel-injected film of oral bracket materials.