bluuebunny/crossref_metadata_2025 huggingface dataset:
Electrooxidation and Development of a Highly Sensitive Electrochemical Probe for Trace Determination of the Steroid 11-Desoxycorticosterone Drug Residues in Water
Authors: Alsaggaf Wejdan T. , El-Shahawi Mohammad S.
Published: May 2022

Anabolic-androgenic steroids (AASs), a class of compounds frequently misused by competitors and unfortunately by the general population, have lately attracted international attention. Thus, extraordinary demands for developing low cost, precise, rapid, and facile protocols for detection and/or determination of AAS have arisen. Hence, the current strategy explores for the first time the redox features of 21-hydroxypregn-4-ene-3, 20-dione, namely, 11-desoxycorticosterone (DCS) AA drug steroid at a glassy-carbon electrode (GCE) in a wide pH range (pH 2.0–10.0) by adsorptive differential pulse-anodic stripping voltammetry (DP- ASV) and cyclic voltammetry (CV). At pH 2, DP-ASV and CV at the optimized pH 2–3 displayed an irreversible anodic peak at 0.4 V versus Ag/AgCl electrode. The dependency of the anodic peak current of the CV at 0.4 V at various concentrations and scan rate of the DCS drug was characteristic of an electrode-coupled electron transfer of EE type mechanism. At the optimized parameters, the proposed strategy allowed quantification of DCS in the concentration range 2.5 -13.19 nM (0.83-4.36 ng mL−1) with satisfactory limits of detection (LOD) and quantization (LOQ) of 9.3 × 10−1 nM (3.1 × 10−1 ng mL−1) and 3.1 nM (1.02 ng mL−1), respectively. A relative standard deviation (RSD) of ±3.93% (n = 5) at 4.0 ng mL−1 DCS was achieved. The established probe was fruitfully employed and validated for trace determination of DCS residues in environmental water. The interference of several common diverse species on DCS sensing was insignificant revealing good selectivity. The established probe exhibited good sensitivity, selectivity, precision, and accuracy, short analytical time, and low cost compared with the reported methods, for DCS determination.
Diversified Integration and Integrated Application of Ideological and Political Teaching Resources Based on Artificial Intelligence Model Algorithm
Authors: Ding Peifen , Huang Xiang
Published: May 2022

In today’s society, China’s social market continues to develop, which has caused the whole society to attach great importance to the professional ethics of Chinese citizens and put forward new requirements and expectations for it. This paper aims to research and discuss the diversified integration and integrated application of ideological and political teaching resources based on artificial intelligence model algorithms. This paper first analyzes and discusses the feasibility of the integration and application of moral education resources in ideological and political textbooks. Political classrooms provide favorable support for the integration and application of moral education resources, and political classrooms have become a practical carrier for the integration and application of moral education resources. And then it introduces the artificial intelligence model algorithm-artificial neural network algorithm. Artificial intelligence is a new intelligent machine that can make intelligent responses similar to human actions according to human actions. Finally, it studies the use of social teaching resources for ideological and political education in city A and conducts a comprehensive analysis on the integration and utilization of moral education teaching resources for ideological and political courses in colleges and universities. In the survey of “Whether the introduction of local social resources in the political class of city A is helpful to students’ learning,” 84 teachers thought it was very helpful, 12 teachers thought it was helpful, and only 3 teachers thought it was not helpful. It can be found that most teachers think that it is helpful for students to introduce social resources in political lessons. At the same time, in order to better improve the reliability and validity of moral resources and to internalize social moral norms into students’ hearts, it is only by combining moral resources with students’ moral growth.
On Optimal Progressive Censoring Schemes from Models with U-Shaped Hazard Rate: A Comparison between Conventional and Fuzzy Priors
Authors: Feroze Navid , Noor-ul-Amin Muhammad , Sadiq Maryam , Hossain Md. Moyazzem
Published: May 2022

This paper explores the optimal censoring schemes from models with U-shaped hazard rates (USHRs) using Bayesian methods. Topp-Leone (TL) distribution has been considered as a special case. We have used conventional and fuzzy priors for the estimation. Further, the symmetric and asymmetric loss functions have been considered for the estimation. Since the Bayes estimators (BEs) for the parameters of the TL distribution cannot be derived in the closed form, we have used Quadrature method (QuM), Lindley’s approximation (LinA), Tierney and Kadane’s approximation (TKA), and Gibbs sampler (GiS) for the approximate estimation of the parameters. We also considered the different techniques to compare various progressive censoring schemes on the basis of their information contents and hence reported the optimal censoring schemes under Bayesian framework. The performance of the different BEs has been compared on the basis of a simulation study. A real-life example has been considered for the illustration.
Identification of Five m6A-Related lncRNA Genes as Prognostic Markers for Endometrial Cancer Based on TCGA Database
Authors: Shan Li , Lu Ye , Xiang Cheng-Cheng , Zhu Xiaoli , Zuo Er-Dong , Cheng Xu
Published: May 2022

Background. Due to difficulties involved in its early diagnosis and adequate prognostication, uterine corpus endometrial carcinoma (UCEC) is one of the most serious threats to human health, with the five-year survival rate being as low as roughly 60%. The discovery of specific biomarkers that serve as prognosticators of UCEC is of great significance. The role of N6-methyladenosine- (m6A-) related long noncoding RNAs (lncRNAs) in the pathogenesis of UCEC remains undefined. In this study, we explored the expression profiles of m6A-related lncRNAs of patients with UCEC and identified novel prognostic markers for UCEC. Methods. Gene expression and clinical data were extracted from The Cancer Genome Atlas. Coexpression analysis was performed to identify m6A-related lncRNAs, which were entered into univariate Cox regression models for evaluating the prognosis of UCEC. Clusters of UCEC patients and enrichment pathways were identified using consistent data clustering and gene set enrichment analysis (GSEA). A risk score model was established, and Kaplan–Meier analysis was conducted for investigating overall survival (OS) across two patient groups (high risk and low risk). Lastly, the relationship between the risk score and the cell content of 22 types of immune cells, clusters, age, programmed cell death 1 ligand-1 (PD-L1) expression level, immune score, and pathological grade was analyzed. Results. We identified a total of 2084 lncRNAs associated with m6A, of which 32 lncRNAs were prognostically relevant. Two clusters (clusters 1 and 2) of patients with UCEC were defined; patients in cluster 1 were found to have significantly higher pathological grades and shorter overall survival time compared to those in cluster 2. GSEA showed that “MITOTIC SPINDLE and other pathways” were more enriched in cluster 1. Five major lncRNAs associated with m6A were screened out, and risk score modeling was used for UCEC prognosis prediction. High risk scores were associated with a shorter OS. The risk score was also verified as an independent prognostic indicator for UCEC and was related to immune cell infiltration levels. Finally, we observed a higher pathological grade and greater levels of PD-L1 in the high-risk group than in the low-risk group of patients. Conclusions. m6A-related lncRNAs play an important role in UCEC progression. The risk-based model constructed from the five key m6A-related lncRNAs was implicated in immune cell infiltration and can potentially be an accurate prognosticator for UCEC.
Kudzu Celery Decoction Exerts Protection against Sepsis-Induced Myocardial Injury
Authors: Zhao Lin , Zhao Huadong , Sun Meng , Chen Mengfan , Wu Xue , Deng Chao , Yang Wenwen , Tian Ye , Wang Qibing , Liang Zhenxing , Xu Xuezeng , Yang Yang
Published: May 2022

Myocardial dysfunction is well-recognized manifestations of organ dysfunction in sepsis, which is the leading cause of death in critically ill patients. The underlying mechanisms associated with sepsis-induced myocardial injury (SIMI) include cardiac contractility, inflammatory response, oxidative stress, and apoptosis. Kudzu celery decoction (KCD) is composed of a variety of traditional Chinese medicine (TCM) such as kudzu and celery. The previous study found that the main ingredients in kudzu and celery have also been proved to have anti-inflammatory, antioxidative, and other biological activities. In this study, the therapeutic effects of KCD were evaluated in the cecal ligation and puncture (CLP) model of BALB/c mice. The effects of KCD on cardiac function, myocardium damage, inflammation, and fibrosis in CLP-injured mice were analyzed with echocardiography, histological staining, and quantitative real-time PCR. The results showed that KCD treatment improved the anal temperature, sepsis score, blood routine parameters, and blood biochemical parameters in CLP-injured mice. Then, we observed that KCD could remarkably alleviate cardiac dysfunction, myocardial fibrosis, oxidative stress, and inflammation in CLP-injured mice. In this study, we confirmed that KCD has a significant protective effect on SIMI, which may favor KCD a potential cardioprotective drug candidate to alleviate SIMI and further amplify the application of TCM prescription in clinic.
Constructing Tissue-Engineered Dressing Membranes with Adipose-Derived Stem Cells and Acellular Dermal Matrix for Diabetic Wound Healing: A Comparative Study of Hypoxia- or Normoxia-Culture Modes
Authors: Zhou Wen , Zhao Xin , Shi Xin , Chen Can , Cao Yanpeng , Liu Jun
Published: May 2022

Diabetes foot ulcer (DFU) is a serious complication of diabetes, characterized by impaired vascular function, limited angiogenesis, and chronic inflammation. Direct stem cell injection on treating DFU is far from satisfactory in clinical practice, as this therapy neither protects nor localizes the injected cell suspension at the chronic ulcer site. Meanwhile, most of injected cells gradually perished within several days due to senescence or apoptosis. Acellular dermal matrix (ADM) has the potential to act as excellent cell delivery vehicles, considering it is highly biomimetic to native dermal tissue, has low immunogenicity, and suitable for stem cell attachment and proliferation. Hypoxia culture has significantly enhanced effects on the survival ability of in vitro cultured stem cells, indicating this culture mode is a suitable way for inhibiting the senescence or apoptosis of transplanted cells. In the current study, we, respectively, culture adipose-derived stem cells (ADSCs) on an ADM membrane under a hypoxia or normoxia condition to construct two kinds of tissue-engineered dressing membranes (H-ADSCs/ADM and N-ADSCs/ADM) and then comparatively evaluated their efficacy on DFU healing using a diabetic rat model. In vitro results showed that hypoxia precondition could stimulate the ADSCs secreting VEGF-A, and the culture medium from hypoxia-preconditioned ADSCs could enhance the proliferation, migration, and angiogenesis of HUVECs. In vivo results indicated that compared to the N-ADSCs/ADM membrane, the transplanted cells in the H-ADSCs/ADM membrane can survive longer at the chronic ulcer site, consequently improve angiogenesis, inhibit inflammation, and increase extracellular matrix remodeling, eventually accelerating DFU closure. This study provides an innovative covering graft for the treatment of DFU in the clinic.
Effects of Nursing Intervention Based on Health Belief Model on Self‐Perceived Burden, Drug Compliance, and Quality of Life of Renal Transplant Recipients
Authors: Hu Shuqin , Xiong Rui , Hu Qingxiang , Li Qingling
Published: May 2022

Objective. To explore the effects of nursing intervention based on health belief model (HBM) on self‐perceived burden, drug compliance, and quality of life of renal transplant recipients. Methods. Sixty patients with renal transplantation treated in our hospital from February 2019 to July 2021 were enrolled. The patients were randomly assigned to control group and study group. The former received routine nursing and the latter received nursing intervention based on HBM. Results. The nursing satisfaction in the study group was higher compared to the control group (P < 0.05). Secondly, we compared the scores of self‐burdens. Before nursing, they exhibited no significant difference (P > 0.05); after nursing, they decreased. Moreover, the physical burden, economic burden, and emotional burden of the study group were lower compared to the control group (P < 0.05). In terms of drug compliance, the rates of no missed medication, noncontinuous missed medication, timely medication, dose‐by‐dose medication, and non‐self‐stopping medication in the study group were higher compared to the control group (P < 0.05). The scores of SAS and SDS exhibited no significant difference before nursing (P > 0.05). After nursing, they decreased. Furthermore, the scores of SAS and SDS of the study group were lower compared to the control group (P < 0.05). The self‐management ability exhibited no significant difference before nursing (P > 0.05); after nursing, it increased. Moreover, the self‐management ability of the study group at discharge and 1 month, 3 months, and 6 months after discharge was higher compared to the control group (P < 0.05). Finally, we compared the scores of quality of life. Before nursing, there was no significant difference (P > 0.05). The scores of physiological function, psychological function, social function, and health self‐cognition in the study group were lower compared to the control group (P < 0.05). Conclusion. The nursing intervention based on HBM can enhance the medication compliance of renal transplant recipients, and the intervention effect is long‐lasting. Meanwhile, it can effectively enhance the negative emotion of patients, reduce the burden of self‐feeling, promote the quality of life, strengthen the self‐management of patients, and facilitate the prognosis.
A High-Performance Energy-Balanced Forwarding Strategy for Wireless Sensor Networks
Authors: Hu Zhangxiang , Jiang Xiaodan , Ding Xiajun , Fang Kai , Zhou Xiaolong
Published: May 2022

The wireless sensor network (WSN) is composed of several sensor nodes organized by multi-hop self-organization, which is a typical network for the industrial internet in industrial application. However, the energy using and processing capacity of each node are greatly limited. Therefore, it is of great significance to study energy-saving and efficient communication protocols for WSN. To prolong the lifetime of WSN and improve network throughput, a high throughput routing protocol with balanced energy consumption is proposed. The designed protocol first employs the K-means clustering algorithm to cluster the nodes, then calculates the weights based on the residual energy of and distance between the nodes, and finally selects the best node as the cluster head. Moreover, the optimal size of the package is determined by the parameters of the wireless transceiver and the channel conditions. In the data transmission stage, the Dijkstra algorithm is used to calculate the multi-objective weight function as the link cost. Experimental results demonstrate the superior performance of the proposed protocol over the CERP and TEEN routing protocols in terms of energy saving of network nodes, so as to improve the throughput and survival time of the entire system.
Overview of Application of Nanomaterials in Medical Domain
Authors: Lan Jiabo
Published: May 2022

With the development of nanotechnology, the application of nanomaterials in the medical field has become a forefront hotspot in the field of scientific research in the 21st century. Compared with traditional drug carriers, drug carriers made of nanomaterials have advantages such as higher drug loading rate, better biocompatibility, and targeted transportation, which provide the possibility for the treatment of a variety of diseases. In this paper, the characteristics and advantages of nanomaterials as well as their applications in the medical field are reviewed and the research progress of nanomaterials is analyzed.
Cecal Patches Generate Abundant IgG2b-Bearing B Cells That Are Reactive to Commensal Microbiota
Authors: Tsuda Masato , Okada Hiraku , Kojima Natsuki , Ishihama Fumiya , Muraki Yuhei , Oguma Toshiki , Hattori Nanako , Mizoguchi Takumi , Mori Kiyoaki , Hachimura Satoshi , Takahashi Yoshimasa , Takahashi Kyoko , Kaminogawa Shuichi , Hosono Akira
Published: May 2022

Gut-associated lymphoid tissue (GALT), such as Peyer’s patches (PPs), are key inductive sites that generate IgA+ B cells, mainly through germinal center (GC) responses. The generation of IgA+ B cells is promoted by the presence of gut microbiota and dietary antigens. However, the function of GALT in the large intestine, such as cecal patches (CePs) and colonic patches (CoPs), and their regulatory mechanisms remain largely unknown. In this study, we demonstrate that the CePs possess more IgG2b+ B cells and have fewer IgA+ B cells than those in PPs from BALB/c mice with normal gut microbiota. Gene expression analysis of postswitched transcripts supported the differential expression of dominant antibody isotypes in B cells in GALT. Germ-free (GF) mice showed diminished GC B cells and had few IgA+ or IgG2b+ switched B cells in both the small and large intestinal GALT. In contrast, myeloid differentiation factor 88- (MyD88-) deficient mice exhibited decreased GC B cells and presented with reduced numbers of IgG2b+ B cells in CePs but not in PPs. Using ex vivo cell culture, we showed that CePs have a greater capacity to produce total and microbiota-reactive IgG2b, in addition to microbiota-reactive IgA, than the PPs. In line with the frequency of GC B cells and IgG2b+ B cells in CePs, there was a decrease in the levels of microbiota-reactive IgG2b and IgA in the serum of GF and MyD88-deficient mice. These data suggest that CePs have a different antibody production profile compared to PPs. Furthermore, the innate immune signals derived from gut microbiota are crucial for generating the IgG2b antibodies in CePs.
Prenatal Prediction of Fetal Growth Restriction and Postnatal Outcomes by Ultrasound Assessment of Fetal Myocardial Performance Index and Blood Flow Spectrum
Authors: Ma Yanchun , Li Chunmin , Wang Yan , Zhang Hong
Published: May 2022

Objective. Fetal growth restriction (FGR) affects 5% to 10% of newborns and is a major determinant of perinatal morbidity and mortality. Myocardial performance index (MPI), also known as the Tei index, is a useful, noninvasive, and Doppler-derived myocardial performance tool for fetal cardiac function evaluation. The purpose of the study is to evaluate ultrasonic prediction on FGR and postnatal outcomes using MPI and blood flow spectrum. Methods. This retrospective study included 240 pregnant women developing FGR and 240 healthy pregnant women. The blood flow spectrum of middle cerebral artery (MCA), umbilical artery (UA), and ductus venous including systolic to diastolic ratio (S/D), resistant index (RI), pulse index (PI), and peak ventricular systolic velocity/atrial contraction valley velocity (S/a) were examined using the GE Voluson E8 ultrasound system. Results. The MPI, S/D, RI, PI of UA, and S/a were all higher but S/D, RI, and PI of MCA were lower in the FGR group than those in the control group

P
<
0.001

. The MPI, S/D, RI, PI of UA, S/D, RI, PI of MCA, and ductus venous S/a yielded AUC of 0.813, 0.835, 0.791, 0.804, 0.789, 0.796, 0.803, and 0.784 when they were used to predict the incidence of FGR. Of note, the pregnant women with poor pregnancy outcomes exhibited higher values of MPI, S/D, RI, PI of UA, and S/a with lower scores of 1 min Apgar concomitant with lower values regarding S/D, RI, and PI of MCA than those with favorable pregnancy outcomes

P
<
0.001

. The MPI (r = −0.623), S/D (r = −0.660), RI (r = −0.601), PI (r = −630) of UA, and S/a (r = −0.573) shared negative correlations with 1 min Apgar scores

P
<
0.001

. Of note, the S/D (r = 0.562), RI (r = 0.597), and PI (r = 0.619) of MCA were positively correlated with 1 min Apgar scores

P
<
0.001

. It was revealed that the MPI, S/D, RI, PI of UA, S/D, RI, PI of MCA, and ductus venous S/a yielded AUC of 0.806, 0.833, 0.774, 0.788, 0.807, 0.729, 0.748, and 0.770 when they were used to predict the incidence of poor pregnancy outcomes for pregnant women developing FGR. Conclusion. Our study demonstrates good ultrasonic prediction on FGR and postnatal outcomes using MPI and blood flow spectrum.
Identification of Important Modules and Hub Gene in Chronic Kidney Disease Based on WGCNA
Authors: Wang Jia , Yin Yuan , Lu Qun , Zhao Yan-rong , Hu Yu-jie , Hu Yun-Zhao , Wang Zheng-Yin
Published: May 2022

Chronic kidney disease (CKD) is an ongoing deterioration of renal function that often progresses to end-stage renal disease. In this study, we aimed to screen and identify potential key genes for CKD using the weighted gene coexpression network (WGCNA) analysis tool. Gene expression data related to CKD were screened from GEO database, and expression datasets of GSE66494 and GSE62792 were obtained. After discrete analysis of samples, WGCNA analysis was performed to construct gene coexpression module, and the correlation between the module and disease was calculated. The modules with a significant correlation with the disease were selected for Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Then, the interaction network of related molecules was constructed, and the high score subnetwork was selected, and the candidate key molecules were identified. A total of 882 DEGs were identified in the screening datasets. A subnetwork containing 6 nodes was found with a high score of 12.08, including CEBPZ, IFI16, LYAR, BRIX1, BMS1, and DDX18. DEGs could significantly differentiate CKD and healthy individuals in principal component analysis. In addition, the MEturquiose, MEred, and MEblue in group were significantly correlated with disease in WGCNA. These 6 hub genes were found to significantly discriminate between CKD and healthy controls in the validation dataset, suggesting that they could use these molecules as candidate markers to distinguish CKD from healthy people. Overall, our study indicated that 6 hub genes may play key roles in the occurrence and development of CKD.
Hybrid Model for Detection of Cervical Cancer Using Causal Analysis and Machine Learning Techniques
Authors: Lilhore Umesh Kumar , Poongodi M. , Kaur Amandeep , Simaiya Sarita , Algarni Abeer D. , Elmannai Hela , Vijayakumar V. , Tunze Godwin Brown , Hamdi Mounir
Published: May 2022

Cervical cancer has become the third most common form of cancer in the in-universe, after the widespread breast cancer. Human papillomavirus risk of infection is linked to the majority of cancer cases. Preventive care, the most expensive way of fighting cancer, can protect about 37% of cancer cases. The Pap smear examination is a standard screening procedure for the initial screening of cervical cancer. However, this manual test procedure generates many false-positive outcomes due to individual errors. Various researchers have extensively investigated machine learning (ML) methods for classifying cervical Pap cells to enhance manual testing. The random forest method is the most popular method for anticipating features from a high-dimensional cancer image dataset. However, the random forest method can get too slow and inefficient for real-time forecasts when too many decision trees are used. This research proposed an efficient feature selection and prediction model for cervical cancer datasets using Boruta analysis and SVM method to deal with this challenge. A Boruta analysis method is used. It is improved from of random forest method and mainly discovers feature subsets from the data source that are significant to assigned classification activity. The proposed model’s primary aim is to determine the importance of cervical cancer screening factors for classifying high-risk patients depending on the findings. This research work analyses cervical cancer and various risk factors to help detect cervical cancer. The proposed model Boruta with SVM and various popular ML models are implemented using Python and various performance measuring parameters, i.e., accuracy, precision,

F
1
–
Score

, and recall. However, the proposed Boruta analysis with SVM performs outstanding over existing methods.
Preserving the Privacy of Healthcare Data over Social Networks Using Machine Learning
Authors: Veeramakali T. , Shobanadevi A. , Nayak Nihar Ranjan , Kumar Sumit , Singhal Sunita , Subramanian Manoharan
Published: May 2022

A key challenge in clinical recommendation systems is the problem of aberrant patient profiles in social networks. As a result of a person’s abnormal profile, numerous vests might be used to make fake remarks about them, cyber bullying, or cyber-attacks. Many clinical researchers have done extensive study on this topic. The most recent studies on this topic are summarized, and an overarching framework is provided. When it comes to the methods and datasets that make up the data collection, the feature presentation and algorithm selection layers provide an overview of the various types of algorithm selections available. The categorization and evaluation of diseases and disorders has been one of the major advantages of machine learning in medical. Because it was harder to predict, it rendered it more controllable. It might range from difficult-to-find cancers in the early stages to certain other illnesses spread through the bloodstream. In healthcare, we may pick methods in machine learning depending on reliable outcomes. To do so, we must run the findings through each method. The major issue arises during information training and validation. Because the dataset is so large, eliminating mistakes might be difficult. The providers, other characteristics, various algorithms, data labelling techniques, and assessment criteria are all presented and contrasted in depth. Detecting anomalous users in medical social networks, on the other hand, is a work in progress. The result evaluation layer provides an explanation of how to evaluate and mark up the results of the various algorithm selection layers. Finally, it looks forward to more study in this area.
Selenium Supplementation in Pregnancy-Maternal and Newborn Outcomes
Authors: Biswas Koushik , McLay James , Campbell Fiona M.
Published: May 2022

Background. Several studies have suggested that increased oxidative stress during pregnancy may be associated with adverse maternal and foetal outcomes. As selenium is an essential mineral with an antioxidant role, our aim was to perform a systematic review of the existing literature reporting the effects of selenium supplementation during pregnancy on maternal and neonatal outcomes. Materials and Methods. Six electronic databases (Medline, Embase, Cochrane Library, Web of Science, Scopus, and PubMed) were searched for studies reporting the effects of selenium supplementation during pregnancy and the postpartum period on maternal and neonatal outcomes. Only randomised controlled trials on human subjects reported in English and published up to October 2021 were included. Quality assessments were conducted using the modified Downs and Black quality assessment tool. Data were extracted using a narrative synthesis. Results. Twenty-two articles were included in our systematic review (seventeen reported on maternal outcomes, two on newborn outcomes, and three on both). Maternal studies reported the effects of selenium supplementation in the prevention of thyroid dysfunction, gestational diabetes, pregnancy-induced hypertension/preeclampsia, oxidative stress, postpartum depression, premature rupture of membranes, intrauterine growth retardation, breastmilk composition, and HIV-positive women. Newborn studies reported the effects of maternal selenium supplementation on foetal oxidation stress, foetal lipid profile, neonatal hyperbilirubinemia, and newborn outcomes in HIV-positive mothers. The majority of studies were inappropriately designed to establish clinical or scientific utility. Of interest, four studies reported that selenium supplementation reduced the incidence of thyroid dysfunction and permanent hypothyroidism during the postpartum period by reducing thyroid peroxidase and thyroglobulin antibody titres. Conclusion. The evidence supporting selenium supplementation during pregnancy is poor and there is a need for appropriately designed randomised controlled trials before routine use can be recommended.
Low-Voltage Diagnosis of Energy Distribution Network Based on Improved Particle Swarm Optimization Algorithm
Authors: Wang Ting , Ma Bingfeng , Dai Xiaohui , Li Jianfeng , Li Sheng
Published: May 2022

In order to improve the research on low-voltage fault diagnosis of energy distribution network, a low-voltage multiobjective diagnosis of AC/DC energy distribution network based on ICHPSO is proposed in this paper. Firstly, the types of objective functions are listed, the objective function is transformed into a single-objective function by using the linear weighting method, and the hybrid particle swarm optimization (HPSO) diagnosis algorithm is improved, which can guide the particles to escape from the local optimal solution space, prevent the particles from falling into the local optimal too early, and improve the search accuracy and global search ability of the algorithm. At the same time, the individuals with high fitness are retained, and the convergence performance of the algorithm is improved. Then, the algorithm is coded, and an example of AC/DC energy distribution network with improved ieee33 is adopted. DC side data comes from the first 13 nodes of AC side data, and the voltage level is 10 kV. The diagnostic effects of different schemes were compared. The results show that the expected mean value of node voltage deviation after power compensation diagnosis is 2.26%, which is 61.18% lower than that before diagnosis; the expected average voltage loss is 0.77 kv, which is 52.1% lower than that before diagnosis; the expectation of network loss is 196.45 kw, which is 49.56% lower than that before diagnosis; the minimum voltage of the AC side node (node 18) is expected to be 0.9514 p.u., 2.75% higher than that before diagnosis; and the minimum voltage of DC side node (node 8) is expected to be 0.9918 p.u., 1.11% higher than that before diagnosis. The comprehensive experimental results show that the proposed method can greatly reduce the node voltage deviation, voltage loss, and network loss of AC/DC energy distribution network, improve the node voltage quality, and maintain the stable operation of the whole AC/DC energy distribution network.
Research on the Impact of Home Nursing Based on Intelligent Medical Internet of Things on the Quality of Life of Patients with Hemophilia
Authors: Liu Mengyan , Zhao Sufang , Zhu Xiaming , Chen Ying
Published: May 2022

The purpose of this paper is to study the feasibility and economic benefits of intelligent medical Internet of Things (IOT) systems for improving the quality of life of hemophilia patients, thereby reducing the risk of teratogenicity and disability for patients. This article selects 60 severe hemophilia patients who were followed up in our hospital from 2018 to 2019 as the research object. In the intelligent medical system, the Gaussian mixture model discretization algorithm is used to preprocess patient data collection. The observation group uses the intelligent medical system to implement home nursing for the patients, and the control group uses ordinary home nursing. This paper evaluates the quality of life of the two groups of patients 6 months after the intervention, including self-care ability, transfer function, and home nursing cognitive ability. The research results show that the home nursing based on smart medical IOT proposed in this paper is feasible and effective for improving the quality of life of patients. It can effectively improve the patient’s self-care ability and joint functions and has important reference value for the development of intelligent medical IOT equipment.
An Improved BERT and Syntactic Dependency Representation Model for Sentiment Analysis
Authors: Liu Wenfeng , Yi Jing , Hu Zhanliang , Gao Yaling
Published: May 2022

Text representation of social media is an important task for users’ sentiment analysis. Utilizing the better representation, we can accurately acquire the real semantic information expressed by online users. However, existing works cannot achieve the best results. In this paper, we construct and implement a sentiment analysis model based on the improved BERT and syntactic dependency. Firstly, by studying the word embeddings of BERT, we have ameliorated the embeddings representation. Attention mechanism is added to the word embeddings, sentence embeddings, and position embeddings. Secondly, we have exploited the dependency syntax analysis of the text, and the dependency relationship of different syntactic components will be obtained. For different syntactic components, the hierarchical attention mechanism is used to construct the phrase embeddings or block embeddings. Finally, we splice the syntactic blocks for sentiment analysis. Extensive experiments show that the proposed model has a stronger ability than the baselines on two standard data sets.
Perceptual Mapping-Based Image Tamper Detection and Recovery Algorithm
Authors: Taha Taha Basheer , Ngadiran Ruzelita , Taha Dujan B.
Published: May 2022

The importance of digital image authentication has grown in the last decade particularly with the widespread availability of digital media and image manipulation tools. As a result, different techniques were developed to detect fraudulent alterations in digital images and restore the original data. In this paper, a new algorithm is proposed to authenticate images by hiding a copy of the approximation band in the original image. The approximation band is hidden by embedding it inside the image pixels. The intensity of the hiding was decided using a perceptual map that simulates the human vision system and adds more intensity in areas where the human eye cannot recognize changes. The perceptual map consists of three parts, luminance mask, texture mask, and edge detection mask. Results show a high ability to blindly recover images after different attacks such as removing and blocking attacks. At the same time, the structure similarity index of resultant images was higher than 0.99 for all tested images.
Artificial Intelligence-Based Spiral CT 3D Reconstruction in Transcatheter Aortic Valve Implantation
Authors: Zhang Kunpeng , Gao Yan , Lv Junwei , Li Jian , Liu Jingli
Published: May 2022

To evaluate the clinical application effect of spiral computed tomography (CT) three-dimensional (3D) reconstruction based on artificial intelligence in transcatheter aortic valve implantation (TAVI), a CT 3D reconstruction model based on deep convolutional neural networks (DCNN) was established in this research, which was compared with the model-based iterative reconstruction (MBIR) and used in clinical practice. Then, 62 patients with aortic stenosis (AS) who underwent TAVI surgery were recruited as the research objects. The accuracy, sensitivity, and specificity of the multislice spiral CT scan (MSCT) and transthoracic echocardiography (TTE) in predicting the type of TAVI surgical valve were compared and analyzed. The results showed that the mean absolute error (MAE) (0.01) and root mean square error (RMSE) (0.086) of the MBIR model were higher than the reconstruction model in this research. The structural similarity (SSIM) (0.831) and peak signal-to noise ratio (PSNR) (32.77 dB) of the MBIR model were lower than the reconstruction model, and the differences were considerable (

P
<
0.05

). Of the valve models selected based on the TTE measurement results, 35 cases were accurately predicted and 27 cases were incorrectly predicted. The accuracy of MSCT was 87.1%, the specificity was 98.84%, and the sensitivity was 92.87%; all of which were significantly higher than TTE (

P
<
0.05

). In summary, compared with the MBIR reconstruction model, the imaging results of the model established in this research were closer to the real image. Compared with TTE, MSCT had higher accuracy, sensitivity, and specificity and can provide more accurate preoperative predictions for patients undergoing TAVI surgery.
Paraclostridium benzoelyticum Bacterium-Mediated Zinc Oxide Nanoparticles and Their In Vivo Multiple Biological Applications
Authors: Faisal Shah , Abdullah  , Rizwan Muhammad , Ullah Riaz , Alotaibi Amal , Khattak Aishma , Bibi Nadia , Idrees Muhammad
Published: May 2022

We presented a low-cost, eco-friendly, and efficient bacterium-mediated synthesis of zinc oxide nanoparticles (ZnO-NPs) utilizing Paraclostridium benzoelyticum strain 5610 as a capping and reducing agent. Scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, energy-dispersive X-ray, and UV-vis spectroscopy were used to physiochemically characterize the biosynthesized ZnO-NPs. A major narrow peak at 441 nm was observed using UV-visible spectroscopy, verifying the presence of nanoparticles. According to SEM and TEM studies, the average dimensions of ZnO-NPs was 50 nm. The crystal size of 48.22 nm was determined by XRD analysis. FTIR analysis confirmed the presence of various reducing metabolites on the surface of ZnO-NPs. The synthesized nanoparticles were investigated for biological activity against Helicobacter suis, Helicobacter bizzozeronii, Helicobacter felis, and Helicobacter salomonis. Helicobacter suis was the most vulnerable strain, with an inhibitory zone of

19.53
±
0.62

 mm at 5 mg/mL dosage. The anti-inflammatory and the findings of the rat paw edema experiments revealed that the bacterium-mediated ZnO-NPs had a strong inhibitory action. In the arthritis model, the solution of ZnO-NPs showed

87.62
±
0.12

% inhibitory effect of edema after 21 days when linked with that of the standard drug. In the antidiabetic assay, ZnO-NPs sharply reduced glucose level in STZ-induced diabetic mice. In this study, the particle biocompatibility by human red blood cells was also determined. Keeping in view the biological importance of ZnO-NPs, we may readily get the conclusion that Paraclostridium benzoelyticum strain 5610-mediated ZnO-NPs will be a prospective antidiabetic, antibacterial, antiarthritic, and anti-inflammatory agent in vivo experimental models and can be used as a potent antidiabetic drug.
Aerobic Exercise Improves Type 2 Diabetes Mellitus-Related Cognitive Impairment by Inhibiting JAK2/STAT3 and Enhancing AMPK/SIRT1 Pathways in Mice
Authors: Lin Lili , Wang Yonghua , Xu Wenli , Huang Chaolu , Hu Jinrong , Chen Xixi , Lv Xinhuang , Qin Yuelin , Zhao Xiaoyong , Li Haiyan
Published: May 2022

Type 2 diabetes mellitus (T2DM) is a prevalent risk factor for cognitive impairment. Aerobic exercise can improve T2DM-related cognitive impairment; however, the possible mechanisms remain elusive. Thus, we assessed db/m mice and leptin receptor-deficient (db/db) mice that did or did not perform aerobic exercise (8 m/min, 60 min/day, and 5 days/week for 12 weeks). In this study, cognitive function was significantly impaired in the T2DM mice; aerobic exercise improved cognitive impairment through activating the AMPK/SIRT1 signalling pathway and inhibiting the JAK2/STAT3 signalling pathway in T2DM mice. However, after the application of RO8191 (JAK2 activator) or Compound C (AMPK inhibitor), the positive improvement of the exercise was evidently suppressed. Taken together, our data indicated that long-term aerobic exercise improves type 2 diabetes mellitus-related cognitive impairment by inhibiting JAK2/STAT3 and enhancing AMPK/SIRT1 pathways in mice.
Endogenous Hydrogen Sulfide Persulfidates Caspase-3 at Cysteine 163 to Inhibit Doxorubicin-Induced Cardiomyocyte Apoptosis
Authors: Ye Xiaoyun , Li Yingying , Lv Boyang , Qiu Bingquan , Zhang Shangyue , Peng Hanlin , Kong Wei , Tang Chaoshu , Huang Yaqian , Du Junbao , Jin Hongfang
Published: May 2022

Doxorubicin (DOX) is an efficient antitumor anthracycline drug, but its cardiotoxicity adversely affects the prognosis of the patients. In this study, we explored whether endogenous gasotransmitter hydrogen sulfide (H2S) could protect against DOX-induced cardiomyocyte apoptosis and its mechanisms. The results indicated that DOX significantly downregulated endogenous H2S production and endogenous synthetase cystathionine γ-lyase (CSE) expression and obviously stimulated the apoptosis in H9C2 cells. The supplement of H2S donor sodium hydrosulfide (NaHS) or overexpression of CSE inhibited DOX-induced H9C2 cell apoptosis. DOX enhanced the activities of caspase family members in cardiomyocytes, while NaHS attenuated DOX-enhanced caspase-3, caspase-2, and caspase-9 activities by 223.1%, 73.94%, and 52.29%, respectively. Therefore, taking caspase-3 as a main target, we demonstrated that NaHS or CSE overexpression alleviated the cleavage of caspase-3, suppressed caspase-3 activity, and inhibited the cleavage of poly ADP-ribose polymerase (PARP). Mechanistically, we found that H2S persulfidated caspase-3 in H9C2 cells and human recombinant caspase-3 protein, while the thiol-reducing agent dithiothreitol (DTT) abolished H2S-induced persulfidation of caspase-3 and thereby prevented the antiapoptotic effect of H2S on caspase-3 in H9C2 cells. The mutation of caspase-3 C148S and C170S failed to block caspase-3 persulfidation by H2S in H9C2 cells. However, caspase-3 C163S mutation successfully abolished the effect of H2S on caspase-3 persulfidation and the corresponding protection of H9C2 cells. Collectively, these findings indicate that endogenous H2S persulfidates caspase-3 at cysteine 163, inhibiting its activity and cardiomyocyte apoptosis. Sufficient endogenous H2S might be necessary for the protection against myocardial cell apoptosis induced by DOX. The results of the study might open new avenues with respect to the therapy of DOX-stimulated cardiomyopathy.
Conservative Treatment and Rehabilitation Training for Rectus Femoris Tear in Basketball Training Based on Computer Vision
Authors: Zhang Yupeng , Zhao Gaowei
Published: May 2022

Computer vision is an emerging artificial intelligence subject, whose purpose is to make computers have the same ability to perceive and understand image semantic information as humans. Computer vision technology is based on high-performance computers, which can obtain massive amounts of information and data in a short period of time and use intelligent algorithms to perform high-speed data processing on the information, which is conducive to the integration of information related to product design, production process management, etc. Due to the rapid development of visual sensing technology, computer technology, and image processing technology, computer vision technology has been widely used in the fields of food, medicine, construction, chemical industry, electronics, packaging, and automobiles. This article uses computer vision technology to compare four conservative treatments and rehabilitation training for rectus femoris in basketball training and analyze the best rehabilitation treatment for rectus femoris tear. The experimental results show that the average electroacupuncture plus muscle stretching exercise group after treatment has an average EMG value of 55.49, an average muscle strength rating of five, an average motor function score of 23.45, and an average treatment recovery time of 11.6 days. This group has the best treatment effect.
CAD-Assisted 3D Assembly of Automobile Electrical Switch considering PSO-BP Neural Network Algorithm
Authors: Zhang Hanting
Published: May 2022

The installation of automotive electrical switches is a complex three-dimensional space assembly project which has high requirements for installation accuracy. In order to improve the installation effect of automotive electrical switches, this paper applies the PSO-BP neural network algorithm to automotive electrical switches and integrates PSO and ELM algorithms. The training speed of the ELM model is fast, the model generalizes the data well, and the noise data have little effect on the model. Moreover, this article combines simulation research to evaluate the effect of this algorithm. After confirming the performance of the effect, this paper uses a case study to study the effect of the application of the PSO-BP neural network algorithm to the automotive electrical switch. The research results show that the CAD-assisted 3D assembly system of automobile electrical switch considering PSO-BP neural network algorithm has a good effect.
Relationship between External Environment, Internal Conditions, and Digital Transformation from the Perspective of Synergetics
Authors: Luo Xiaowen , Yu Shun-Chi
Published: May 2022

As the digital technologies develop, traditional pharmaceutical enterprises have also begun the exploration of digital transformation (DT). Previous studies mainly focused on the technology application, strategy, performance, and leadership of digital in manufacturing enterprises and small‐ and medium‐sized enterprises (SMEs), and more qualitative methods were used. However, few researchers systematically investigated the impact mechanism of pharmaceutical enterprises’ DT. The purpose of this study is to analyze the influencing factors of Chinese pharmaceutical enterprises’ DT by constructing the structural equation model (SEM) based on synergetics. This study shows that the influencing factors of pharmaceutical enterprises’ DT include the external environment (customer needs, market competition, government policy, and digital technology) and internal conditions (digital strategy, leadership, and organization capability). The theoretical innovation of this study is to explore the synergistic effect of external environment and internal conditions on DT and put forward that the internal conditions play mediating role in the external environment and DT. Customer needs and digital strategies have great impacts on pharmaceutical enterprises’ DT. Therefore, this study finds the main influencing factors, which are helpful in promoting pharmaceutical enterprises’ DT.