bluuebunny/crossref_metadata_2025 huggingface dataset:
Baicalin Ameliorates Radiation-Induced Lung Injury by Inhibiting the CysLTs/CysLT1 Signaling Pathway
Authors: Bao Wu-An , Wang Yue-Zhen , Zhu Xiang , Lin Juan , Fan Ju-Fen , Yang Yang , Zhou Xia
Published: June 2022

Objective. Radiation-induced lung injury (RILI) is a common complication of radiotherapy for thoracic tumors. This study investigated the alleviating effect of baicalin (BA) on RILI and its possible mechanism. Methods. RILI model was established by chest irradiation (IR) of C57BL/6 mice for 16 weeks. Different concentrations of BA were administered, and dexamethasone (DXM) was used as a positive control. Then, the lung pathological changes were observed by HE and Masson staining. The levels of TGF-β, TNF-α, IL-1β, IL-6, CysLT, LTC4, and LTE4 were measured by ELISA. The CysLT1 expression was detected by qPCR, immunohistochemistry, and western blot. Type II AEC cells were pretreated with LTD-4 to establish the RILI cell model and intervened with different concentrations of BA. Then, the collagen I protein level was measured by ELISA. The CysLT1 and α-SMA expression were detected by qPCR, immunofluorescence, and western blot. Results. BA could effectively improve lung histopathological changes and pulmonary fibrosis. In vivo, BA could inhibit the levels of TGF-β, TNF-α, IL-1β, and IL-6 and reduce the levels of CysLT, LTC4, and LTE4. In vitro, different concentrations of LTD4 could reduce the viability of type II AEC cells, which could be reversed by the administration of different concentrations of BA. In addition, BA could reduce CysLT1 mRNA, as well as CysLT1 and α-SMA protein levels in vitro and in vivo. Conclusion. BA attenuated lung inflammation and pulmonary fibrosis by inhibiting the CysLTs/CysLT1 pathway, thereby protecting against RILI.
Linear Stability Analysis of the Cahn–Hilliard Equation in Spinodal Region
Authors: Ham Seokjun , Jeong Darae , Kim Hyundong , Lee Chaeyoung , Kwak Soobin , Hwang Youngjin , Kim Junseok
Published: June 2022

We study a linear stability analysis for the Cahn–Hilliard (CH) equation at critical and off-critical compositions. The CH equation is solved by the linearly stabilized splitting scheme and the Fourier-spectral method. We define the analytic and numerical growth rates and compare these growth rates with respect to the different average levels. In this study, the linear stability analysis is conducted by classifying three average levels such as zero average, spinodal average, and near critical point levels of free energy function, in the one-dimensional (1D) space. The numerical results provide insight for the dynamics of CH equation at critical and off-critical compositions.
Topological Models of Rough Sets and Decision Making of COVID‐19
Authors: El-Gayar Mostafa A. , El Atik Abd El Fattah
Published: June 2022

The basic methodology of rough set theory depends on an equivalence relation induced from the generated partition by the classification of objects. However, the requirements of the equivalence relation restrict the field of applications of this philosophy. To begin, we describe two kinds of closure operators that are based on right and left adhesion neighbourhoods by any binary relation. Furthermore, we illustrate that the suggested techniques are an extension of previous methods that are already available in the literature. As a result of these topological techniques, we propose extended rough sets as an extension of Pawlak’s models. We offer a novel topological strategy for making a topological reduction of an information system for COVID‐19 based on these techniques. We provide this medical application to highlight the importance of the offered methodologies in the decision‐making process to discover the important component for coronavirus (COVID‐19) infection. Furthermore, the findings obtained are congruent with those of the World Health Organization. Finally, we create an algorithm to implement the recommended ways in decision‐making.
Evaluating the Vocal Music Teaching Using Backpropagation Neural Network
Authors: Cao WanLing
Published: June 2022

The vocal music teaching for evaluating performers is affected by multiple factors. Evaluators are greatly influenced by subjective factors in scoring outputs. The backpropagation (BP) neural network provides a novel technology that can theoretically simulate any nonlinear continuous function within a certain accuracy range. The backpropagation neural network is composed of adaptive feedforward learning network that is widely used in artificial intelligence (AI). In addition, the backpropagation neural network can simulate the nonlinear mapping composed of various factors. The novelty of the neural network is that it can model the nonlinear process without knowing the cause of the data, which can overcome the human subjective arbitrariness and make the evaluation outcomes. Furthermore, accurate and effective scoring systems can be designed using neural networks. In this paper, we establish a vocal music evaluation research system in order to objectivize each vocal music teaching evaluation index. To do so, we use the score vector as the input and obtain a reasonable and objective output score through the backpropagation neural network. Moreover, according to the characteristics of the backpropagation neural network, the factors of vocal music teaching evaluation are analyzed, and a backpropagation neural network model for vocal music teaching evaluation and evaluation is constructed. The experimental outcomes demonstrate that the trained backpropagation network can simulate a stable vocal music teaching evaluation research system. Furthermore, we observed that the backpropagation neural network can be well utilized for vocal music teaching evaluation research.
Optimization of Regional Industrial Structure Based on Multiobjective Optimization and Fuzzy Set
Authors: Guo Lina
Published: June 2022

With the development of China’s economy, it is required to change the mode of economic growth, from extensive growth mode to intensive growth mode. Therefore, the research on industrial structure is of great significance. This study proposes a regional industrial structure optimization method based on multiobjective optimization and fuzzy set. Firstly, the multiobjective industrial structure evaluation model is constructed, then the evaluation model based on improved fuzzy industrial structure is proposed, and finally the application effect of improved fuzzy industrial structure evaluation model is analyzed. The results show that the first generation iteration speed of the improved fuzzy industrial structure evaluation model is fast, but it is slow in the second to eighth iterations. Compared with the traditional square method, the convergence of the fuzzy structure is improved to a certain extent. The improved evaluation model has also been improved. This is better than other algorithms. Using K-means and Manhattan distance to initialize the clustering method, the results are relatively stable. In terms of running time, Manhattan distance initialization method and K-means clustering method have less iterations and short time-consuming. Therefore, when the data sample is large, the application of K-means clustering algorithm will be more effective.
Feasibility Study of a Hybrid PV/Hydro System for Remote Area Electrification in Rwanda
Authors: Niringiyimana Emile , WanQuan Sun , Dushimimana Giovanni
Published: June 2022

Rwanda is among the least developed countries on the globe with total access to electricity not exceeding 63%, where the rest of the population lives in areas with no access to electricity. One such a place, which is the focus of this research, is Musanze district (1.4919 S, 29.5572 E), where 60% of the population in this area are located in remote areas, which makes the task of their electrification via grid system very difficult. Micro hydropower has been developed so far to reduce the deficit of energy access in this area. However, the power generated is not enough to cover the area, and the major problem is the decrease in river water level in the dry season, which affects the power generation. In this work, the feasibility of a hybrid PV/hydroelectric supply system is studied and optimized to increase the number of homes accessing electricity in this area. A 200 kW Mutobo micro hydro system in Musanze district under operation is considered a case study where a 100 kW PV array tied to the micro hydropower system is designed. The optimized PV-hydro hybrid system was proposed using a modified

P

and O MPPT algorithm to enhance the PV-generated power. The model was designed and simulated using MATLAB/Simulink, and data recorded from Mutobo micro hydropower station, Rwanda Energy Group, and National Meteorological Agency were used to estimate solar energy potentials. The results showed that the hybrid PV/hydro system is feasible and effectively contributes to the power shortage mitigation in remote areas during the dry season.
Prediction of the Control Effect of Fractured Leakage in Unconventional Reservoirs Using Machine Learning Method
Authors: Pu Lei , Song Jianjian , Xu Mingbiao , Zhou Jun , Xu Peng , Zhou Shanshan
Published: June 2022

Bridging plugging is the most used method of plugging in unconventional oil reservoirs, and many factors affect the effect of bridging and plugging. Since the laboratory cannot simulate the actual leakage size of the lost formation and the corresponding leakage plugging process at the drilling site, the laboratory experiment results cannot reflect the actual leakage plugging construction effect. Aiming at the problem of frequent fracture leakage during drilling in Chepaizi block, Xinjiang, China, this paper proposes a set of machine learning methods based on a neural network. Three types of factors and 14 parameters with a strong correlation with the leakage control effect were screened out. Three categories of factors include construction parameters, choice of plugging material, and fluid properties of the carrier fluid. The training was carried out based on the collected field data, the appropriate activation function was set, and the deep well network structure was optimized. By improving the field plugging measures in the later period, the model was verified by these actual cases, and the results showed that the established model produced the highest

R

2

of 0.974, has a good fit, and predicts well.
Results of the Pinhole Test Correlate with Hybrid Contact Lens Visual Acuity in Patients with Visual Impairment due to Corneal Diseases
Authors: Kanclerz Piotr
Published: June 2022

Introduction. Trial rigid lens fitting is considered the best approach to determine whether the correction of residual defocus and irregular astigmatism might improve the visual acuity in patients with corneal disorders including keratoconus. This study aimed to analyze the correlation between hybrid lenses and pinhole visual acuity (VA). Methods. Patients undergoing hybrid contact lens fitting at the Hygeia Clinic, Poland, were included. The VA of each patient was assessed as decimal Snellen fractions under the following conditions: (i) uncorrected VA, (ii) VA with spherocylindrical correction (i.e., corrected distance VA), (iii) VA with a single 1.2 mm pinhole occluder, and (iv) VA with the best-fitted hybrid contact lens. Pearson’s correlation coefficient r was used to assess correlations among variables. Results. This study involved 29 eyes of 19 patients, mainly with advanced keratoconus. The uncorrected VA was 0.11 ± 0.10. The pinhole test provided significantly improved VA over corrected distance VA (0.51 ± 0.29 vs. 0.31 ± 0.20, respectively;

p
<
0.0001

). Similarly, the fitted hybrid contact lenses provided improved VA over corrected distance VA (0.66 ± 0.26 vs. 0.31 ± 0.20, respectively;

p
<
0.0001

). The pinhole VA was strongly correlated with the hybrid contact lens VA (r = 0.8135; 95% CI: 0.61–0.92;

p
<
0.0001

). The improvement in the pinhole test over corrected distance VA was moderately correlated with the improvement with the fitted lens over corrected distance VA (r = 0.6269; 95% confidence interval (CI): 0.32–0.80;

p
=
0.0005

). Conclusions. A significant improvement in VA with the pinhole test is a simple predictor of general improvement with hybrid contact lenses. The pinhole test should be used in patients with corneal diseases such as keratoconus to determine whether optical aberrations associated with the disease cause their visual impairment.
Prevalence, Etiology, and Risk Factors Associated with Occurrence of Canine Cutaneous Myiasis in Kitui County, Kenya
Authors: Mutinda Kamuti N. , Gichohi Mbuthia P. , Maina Waruiru R. , Maina Githigia S. , Agosa Keya E.
Published: June 2022

Myiasis is the infestation of living tissues of animals with dipterous larvae. In Africa, Cordylobia species (C. anthropophaga, C. rodhaini, and C. ruandae) and Dermatobia hominis are reported as the principal cause of nonmigratory cutaneous myiasis of domestic animals. None of these have been reported in dogs in Kenya. A cross-sectional study was conducted in eight subcounties of Kitui County, Kenya, from March to August 2021 to estimate the prevalence, risk factors, and etiological agents associated with canine cutaneous myiasis (CCM). A questionnaire was administered to dog owners to collect information on CCM risk factors. A total of 400 dogs were physically examined and larvae collected from myiasis skin lesions and preserved in 70% ethanol, taken to the laboratory, processed and identified using parasitological morphological features. Live larvae were incubated and emerging adults were captured and identified. The overall prevalence of CCM was 45% (180/400) (95% confidence interval: 40.0–50.0%). A total of 434 larvae were collected from 180 dogs infested with cutaneous myiasis. All larvae (100%) were identified as C. anthropophaga and hatched adults were “tumbu” flies. There were no significant differences in the prevalence of CCM at 95% confidence interval among different age and sex groups (

p
>
0.05

), although puppies (<6 months) appeared more affected. The highest prevalence of myiasis was in Kitui Central at 65% (95% confidence interval: 51.6–76.9%), Mwingi North at 52.5% (95% confidence interval: 36.1–68.4%), Kitui South at 48.5% (95% confidence interval: 31.5–63.9%), Kitui Rural at 40% (95% confidence interval: 27.6–53.5%), Mwingi Central at 40% (95% confidence interval: 24.9–56.7%), Mwingi West at 40% (95% confidence interval: 24.9–56.7%), Kitui West at 38.3% (95% confidence interval: 26.1–51.8%), and Kitui East subcounty at 36.7% (95% confidence interval: 24.6–50.1%). Lack of housing, housing structures, and dog living area environmental hygiene were the main risk factors associated with the occurrence of CCM (

p
<
0.05

). The CCM occurrence was significantly different among breeds (

p
<
0.05

). Cordylobia anthropophaga larvae were the etiological agent of CCM in Kitui County. There is a need for improved dog housing and hygiene measures to prevent the occurrence of CCM, and affected dogs should be treated to prevent the spread of CCM among the dogs.
A Systematic Pan-Cancer Analysis of YY1 Aberrations and their Relationship with Clinical Outcome, Tumor Microenvironment, and Therapeutic Targets
Authors: Fu Xinghao , Ji Feihong , He Qi , Qiu Xinguang
Published: June 2022

Yin-Yang 1 (YY1) has a crucial function in the development of several malignancies, according to recent research. However, nothing is known about its aberrant expression and prognostic significance in human pan-cancer. We first explored the potential carcinogenic effect of YY1 in 33 cancers using the cancer genome atlas (TCGA) project and gene expression omnibus (GEO) datasets in this research. Then, we contained a variety of elements, for instance, gene expression, the state of survival, gene alterations, protein phosphorylation, immune infiltration, and related cellular pathways, and used a series of bioinformatics methods to investigate the underlying molecular mechanism of YY1 in the etiology or clinical prognosis of various malignancies. In most malignancies, YY1 was expressed at high levels, and the level of YY1 expression was statistically associated with the prognosis of tumor patients. The S118 site of YY1 implied higher phosphorylation expression in breast cancer, colon cancer, uterine corpus endometrial carcinoma (UCEC), and lung adenocarcinoma (LUAD) tumor tissues, but lower phosphorylation levels in ovarian cancer and clear cell carcinoma tumor tissues. For S247, higher phosphorylation levels were found in colon cancer, UCEC, and LUAD tumor tissue, and lower phosphorylation expression was found in clear cell carcinoma tumor tissue. In TCGA database, YY1 expression in BRCA, BRCA-LumA, BRCA-LumB, CESC, CHOL, COAD, ESCA, HNSC, HNSC-HPV-, KIRP, LGG, LIHC, and PAAD tumor tissues was a statistically significant positive connection of the estimated infiltration value of cancer-associated fibroblasts but a negative correlation in TGCT. In addition, the functional mechanism of YY1 also involves viral carcinogenesis and ribonucleic acid (RNA) metabolism related functions. Our first pan-cancer analysis offers a pretty comprehensive knowledge of YY1’s oncogenic involvement in various cancers.
Isoflavaspidic Acid PB Extracted from Dryopteris fragrans (L.) Schott Inhibits Trichophyton rubrum Growth via Membrane Permeability Alternation and Ergosterol Biosynthesis Disruption
Authors: Zhang Zhisi , Liu Xueping , Shen Zhibin , Chen Yanfen , Chen Cong , SiTu Ying , Tang Chunping , Jiang Tao
Published: June 2022

Isoflavaspidic acid PB (PB), a phloroglucinol derivative extracted from aerial parts of Dryopteris fragrans (L.) Schott, had antifungal activity against several dermatophytes. This study was aimed at exploring the antifungal mechanism of PB against Trichophyton rubrum (T. rubrum). The effectiveness of PB in inhibiting T. rubrum growth was detected by time‐kill kinetics study and fungal biomass determination. Studies on the mechanism of action were investigated using scanning electron microscopy (SEM), transmission electron microscopy (TEM), sorbitol and ergosterol assay, nucleotide leakage measurement, and UPLC‐based test and enzyme‐linked immunosorbent assay. Fungicidal activity of PB was concentration‐ and time‐dependent at 2 × MIC (MIC: 20 μg/mL) after 36 h. The total biomass of T. rubrum was reduced by 64.17%, 77.65%, and 84.71% in the presence of PB at 0.5 × MIC, 1 × MIC, and 2 × MIC, respectively. SEM analysis showed that PB changed mycelial morphology, such as shrinking, twisting, collapsing, and even flattening. TEM images of treated cells exhibited abnormal distributions of polysaccharide particles, plasmolysis, and cytoplasmic content degradation accompanied by plasmalemma disruption. There were no changes in the MIC of PB in the presence of sorbitol. However, the MIC values of PB were increased by 4‐fold with exogenous ergosterol. At 4 h and 8 h, PB increased nucleotide leakage. Besides, ergosterol content in T. rubrum membrane treated with PB at 0.5 × MIC, 1 × MIC, and 2 × MIC was decreased by 9.58%, 15.31%, and 76.24%, respectively. There was a dose‐dependent decrease in the squalene epoxidase (SE) activity. And the reduction in the sterol 14α‐demethylase P450 (CYP51) activity was achieved after PB treatments at 1 × MIC and 2 × MIC. These results suggest that PB displays nonspecific action on the cell wall. The membrane damaging effects of PB were attributed to binding with ergosterol to increase membrane permeability and interfering ergosterol biosynthesis involved with the reduction of SE and CYP51 activities. Further study is needed to develop PB as a natural antifungal candidate for clinical use.
The Influence of Language Style and Brand Name on Crowdfunding Performance of Environmental Protection Enterprises
Authors: Sun Qiong , Jiang Jingjing , Hu Jie
Published: June 2022

Crowdfunding, as an emerging phenomenon of enterprise after entrepreneurship financing, has maintained rapid and sustained growth in recent years. For crowdfunding environmental protection enterprises, one of the main challenges in financing is to reduce the uncertainty of public investors about the quality, management level, and products or services of crowdfunding projects. After reading the text of crowdfunding projects, the public investors have a subjective impression of the crowdfunding environmental protection projects, which determines the public investors’ judgment on the risks and prospects of environmental protection projects and the willingness to invest. Therefore, the texts of crowdfunding projects are very important. In this paper, the data of 130 crowdfunding environmental protection projects on the Modian website are selected, and the ordinal logistic regression model is used. This paper explores the influence of language style in the description text and brand name in the title text on crowdfunding performance.
A Violent Video Detection Method Based on Image Semantic Segmentation
Authors: Zhang Lei , Zhao Zihao , Wu Shuai , Yang Suqing , Liu Minghao
Published: June 2022

With the rapid growth of the network user base and the number of short videos, a large number of videos related to terrorism and violence have emerged in the Internet, which has brought great challenges to the governance of the network environment. At present, most short-video platforms still adopt manual-review and user-report mechanisms to filter videos related to terrorism and violence, which cannot adapt to the development trend of short-video business in terms of recognition accuracy and timeliness. In the single-mode recognition method of violent video, this paper mainly studies the scene recognition mode. Firstly, the U-Net network is improved with the SE-block module. After pretraining on the Cityscapes dataset, semantic segmentation of video frames is carried out. On this basis, semantic features of scenes are extracted using the VGG16 network loaded with ImageNet pretraining weights. SE-U-Net-VGG16 scene recognition model is constructed. The experimental results show that the prediction accuracy of SE-U-Net model is much higher than that of the FCN model and U-Net model. SE-U-Net model has significant advantages in the modal research of scene recognition.
An In Vivo Study of Lactobacillus rhamnosus (PTCC 1637) as a New Therapeutic Candidate in Esophageal Cancer
Authors: Hashemi-Khah Malihe-sadat , Arbab-Soleimani Nazila , Forghanifard Mohammad-Mahdi , Gholami Omid , Taheri Saba , Amoueian Sakineh
Published: June 2022

Statement of Novelty. Esophageal cancer is one of the most common types of cancer globally. Nowadays, Lactobacilli with probiotic potency is a preventing factor in cancer and many diseases. The anti‐tumor properties of these bacteria have been indicated in various studies. Objective. This study is aimed at investigating the effect of probiotic Lactobacillus rhamnosus on esophageal cancer in vivo and in vitro. Methods and Results. In this study, the cytotoxicity effects of L. rhamnosus supernatant and whole‐cell culture on a cancer cell line (Kyse30) compared to 5fu were evaluated by the MTT assay. The real‐time PCR method was used to analyse the L. rhamnosus supernatant effect on the expression of Wnt signaling pathway genes. An in vivo investigation in nude mice was done to assess the anti‐tumor activity of L. rhamnosus supernatant and whole‐cell culture. Both supernatant and whole‐cell culture of L. rhamnosus reduced cell survival (Kyse30) P < 0.001. The supernatant of this bacterium significantly reduced the expression of Wnt signaling pathway genes. Administration of supernatant and whole‐cell culture of L. rhamnosus expressively reduced tumor growth compared to the control group. The effects of this bacterium on tumor necrosis were quite evident, pathologically P < 0.01. Conclusion. This study is the first report that assessed the potential impact of L. rhamnosus, especially its supernatant on esophageal cancer and Wnt signaling pathway genes. Therefore, this bacterium can be a harmless candidate for esophageal cancer therapy.
Potential Material Basis of Yupingfeng Powder for the Prevention and Treatment of 2019 Novel Coronavirus Pneumonia: A Study Involving Molecular Docking and Molecular Dynamic Simulation Technology
Authors: Yu Ying , Zhang Gong , Han Tao , Liu Hongjie , Huang Hailiang
Published: June 2022

Objective. In this study, we investigated the potential material basis of Yupingfeng powder in the prevention and treatment of 2019 novel coronavirus pneumonia (NCP) by applying molecular docking and molecular dynamic simulation technology. Design. The active ingredients and predictive targets of Yupingfeng powder were sourced using the TCMSP, ETCM, and TCMIP traditional Chinese medicine databases. NCP‐related targets were then acquired from the DisGeNET and GeneCards databases, and common disease‐drug targets were imported into the STRING database, and Cytoscape software was used to generate a protein‐protein interaction network following the use of a network topology algorithm to identify key target genes. Gene Ontology (GO) and KEGG pathway enrichment analysis was then performed using the target genes and GOEAST and DAVID online tools. The mechanism of Yupingfeng powder in the prevention and treatment of NCP was analyzed with reference to the relevant literature. AutoDock software was used for molecular docking, the preliminary analysis of binding status, and to identify the best conformation. Desmond software was used to perform molecular dynamic simulations for protein and compound complexes, perform free energy calculations and hydrogen bond analysis, and to further verify the binding mode. Results. Overall, 38 main active components and 218 predictive targets of Yupingfeng powder were identified and 298 disease targets related to NCP were retrieved from disease databases. Yupingfeng powder was found to act predominantly on the TNF, Toll‐like receptor, HIF‐1, NOD‐like receptor, cytokine‐receptor interaction, MAPK, T cell receptor, and VEGF signaling pathways. Molecular docking of the three selected key active components with the 3CL‐like protease (3CL‐Pro) of SARS‐CoV‐2 showed that they each had a strong binding force and good affinity. Conclusions. Yupingfeng powder primarily acts on multiple active ingredients and potential targets through multiple action channels and signal pathways. Molecular docking and molecular dynamic simulation technology were used to effectively predict and analyze the potential mechanism by which this Chinese medicine can combat NCP. These results provide a reference for developing new modern Chinese medicine preparations against NCP in the future.
Evaluation of a Dual PI3K/mTOR Inhibitor PF-04691502 against Bladder Cancer Cells
Authors: Shang Xiaosong , Na Xinyu , Wang Lei , Yang Zhiqin , Ren Pengpeng
Published: June 2022

Targeting the phosphatidylinositol-3 kinase/protein kinase B/mammalian target of rapamycin (PI3K/Akt/mTOR) signalling pathway is a promising strategy for the treatment of various cancers, including bladder cancer (BC). PF-04691502 is a relatively novel dual PI3K/mTOR inhibitor that exerts inhibitory effects against various cancer cells. However, the effects of PF-04691502 in BC cells have not been clarified thus far. This study aimed to evaluate the antitumour effects of PF-04691502 and the mechanisms underlying these antitumour effects in BC cells. The effects of PF-04691502 on the viabilities of BC cells were examined using the cell counting kit 8 (CCK-8) assay. Cell migration and invasion were measured using the wound healing assay and transwell assay, respectively. Cellular apoptosis was determined using flow cytometry. The change in the cellular protein levels was measured using western blotting. siRNA was used to study the role of PTEN in the antitumour effects of PF-04691502. PF-04691502 inhibited the proliferation, migration, and invasion of BC cells. Additionally, PF-04691502 induced apoptosis of BC cells via the intrinsic pathway. PF-04691502 inhibited the expression of Mcl-1 and the PI3K/Akt/mTOR pathway in BC cells. In addition, PF-04691502 increased the apoptosis induced by various chemotherapeutic agents in BC cells. Taken together, PF-04691502 could be used alone or in combination with other chemotherapeutic agents in the treatment of BC.
Research on Graphic-Text Relationship in Film and Television Works Based on Big Data Model
Authors: Liu Jun , Zhang YuQin
Published: June 2022

With the rise of microblog, social network, mobile APP, location-based services, and other technologies, the global data has exploded. Big data provides a rich source for data mining and analysis, and the results mined from it will become more meaningful and even full of surprises. In this paper, through the problems in processing film and television data, the corresponding model is established to deal with the corresponding problems. According to the related technologies of big data processing and the filtering algorithm of the model, the processing strategies and methods are put forward. The middle also introduces the big data mining method. Finally, according to the different data characteristics and different data processing requirements of the intelligent analysis system of film and television data, comparing the data of film works and TV dramas, the experimental results show that, based on the big data model, the pictures and words in both film works and TV dramas are inseparable and indispensable. In the later research, we choose the appropriate data processing scheme to design and implement the data processing flow, and successfully apply the film and television big data processing strategy and method proposed in this paper to practice, which provides reliable data support for the content analysis of film and television works. The model-based filtering algorithm calculates the relationship between image and text, turns the point into the probability formula of node-to-meta path, and takes the approximate value to achieve efficient model learning.
A Neural Network Model for Business Performance Management Based on Random Matrix Theory
Authors: Zhang Jing
Published: June 2022

This paper uses random matrix theory to construct a neural network model for business performance management. The random sample covariance matrix of the random monitoring matrix is constructed, and the maximum eigenvalue and the minimum eigenvalue of the sample covariance matrix are solved. The ratio of eigenvalues is used to construct the eigenvalue detection index and determine the eigenvalue index detection threshold algorithm to judge the abnormal state of enterprise operation. The data of 66 listed Internet finance companies are selected, normalized, and correlation tested, and the index weights of each level are obtained using hierarchical analysis to derive the expected output of the BP neural network. Finally, the constructed BP neural network performance evaluation model is used for network training and simulation analysis, in which 192 data of 48 companies in the last four years are selected as training samples and 8 companies in the last four years are used as test samples to analyze the simulation output results. Using the original data instead of the main factor to join the BP neural network model, after two systematic optimizations, the final model with high accuracy, low mean square error, and low average error was formed. When applying the newly added data for testing, an accuracy of 95.98% was achieved for the ranking prediction, and the average deviation of 0.0021 points for the score prediction, which fully reflected the feasibility and adaptability of the model.
Differential Efficacy of B‐Ultrasound Combined with Molybdenum Target Detection Mode for Breast Cancer Staging and Correlation of Blood Flow Parameters with IGF‐1 and IGF‐2 Expression Level and Prognosis
Authors: He Huiliao , Zhang Guifan , Zhou Haixian , Lin Chunyang , Xu Qun , Liu Ruixing , Yu Beibei , Zhou Xiuping , Wang Zhejin , Xu Zhihua , Lin Lejing
Published: June 2022

The study investigates the diagnostic efficacy of ultrasound combined with the molybdenum target mode in breast cancer staging and the relationship between blood flow parameters and the expression of insulin‐like growth factor 1 (IGF‐1) and factor 2 (IGF‐2) and prognosis. A total of 96 patients admitted to hospital from January 2020 to January 2021 are included in the breast cancer group, and 58 patients admitted to our hospital during the same period are included in the control group, who are diagnosed with benign breast lesions. All patients receive clinicopathological diagnosis, ultrasound detection, and X‐ray molybdenum detection. Ultrasound detection, molybdenum target detection, ultrasound combined with the molybdenum target detection mode, and clinicopathological diagnosis results are compared. B‐ultrasound combined with the molybdenum target detection mode has high efficiency in diagnosing breast cancer and differentiating pathological stages. Besides, blood flow parameters of patients are closely related to IGF‐1 and IGF‐2, and IGF‐1 and IGF‐2 expressions are closely related to the prognosis of patients. Subsequent diagnosis of the disease degree of breast cancer patients can be carried out by ultrasound combined with the molybdenum target detection mode. In addition, the expression of IGF‐1 and IGF‐2 in patients can be monitored to improve the clinical diagnosis and treatment plan to improve the prognosis of patients, which has a high clinical application value and is worth promoting.
Enterprise Financial Risk Prevention and Control and Data Analysis Method Based on Blockchain Technology
Authors: Liu Julin , Chen Ken
Published: June 2022

With the development of engineering technology and computer networks, artificial neural networks, which mimic human brain neural networks, are being used in financial market forecasting to improve the accuracy of stock predictions and are making significant progress. Therefore, there is a great need to actively investigate the method of financial data analysis based on blockchain technology. The purpose of this paper is to investigate the neural network method of financial data analysis based on blockchain technology. Shanghai Index and Shenzhen 200 Index are chosen as experimental data, which are divided into two subsets: training and test samples. The BP model is constructed based on blockchain technology to analyze MARE, RMSRE, MSPEE, RMSPE, and MARE errors. The results show that the mean absolute error rate (MARE), RMSPE, and MSPEE of training samples of blockchain-based BP model are 0.0056, 0.0787, and 0.0085, respectively. Blockchain-based BP model plays an important role in solving financial data analysis problems.
Risk Factors and Distribution Characteristics of Intracranial and Intracranial Artery Stenosis in Young Sufferers with Ischemic Stroke
Authors: Wang Yongchao , Wei Yan
Published: June 2022

In order to explore the risk factors of intracranial and intracranial arterial stenosis, the distribution of young ischemic stroke sufferers with intracranial and intracranial arterial stenosis and the related are analyzed. In this study, a total of 213 young sufferers with ischemic stroke (IS) admitted to our hospital from February 2019 to September 2021 are selected. According to the CT diagnosis of intracranial artery stenosis (AS), 213 patients are divided into two groups, with 86 in the AS Group and 127 in the non‐AS Group. To analyze the distribution of intracranial and intracranial AS in young patients with ischemic stroke, 86 patients with AS are examined by carotid B‐mode ultrasound. Furthermore, a univariate analysis is performed on the relevant indicators of the sufferers in the cancer (CA) set and the two sets without CA, and then, the indicators with statistically extensive disparity were selected for multivariate logistic regression analysis of the risk factors for CA symptoms. The results show 50% of the sufferers with moderate or severe ischemic CA in young adults and 63.95% of the sufferers with intracranial artery stenosis. It is clearly evident that the main risk factors affecting the occurrence of intracranial and intracranial arteries in young IS are hypertension and long‐term smoking, long‐term drinking, and hyperlipidemia.
Air Quality in a Dental Skills Lab during the SARS-CoV-2 Pandemic: Results of an Experimental Study
Authors: Graetz Christian , Sayk Naomi , Düffert Paulina , Heidenreich Ralf , Dörfer Christof E. , Cyris Miriam
Published: June 2022

Objectives. The study aimed to analyze different ways to control air quality during/after aerosol-generating procedures (AGPs) in a small skills lab with restricted natural air ventilation in preclinical dental training (worst-case scenario for aerogen infection control). Different phases were investigated (AGP1: intraoral high-volume evacuation (HVE); AGP2: HVE plus an extraoral mobile scavenger (EOS)) and afterward (non-AGP1: air conditioning system (AC), non-AGP2: AC plus opened door). Methods. Continuous data collection was performed for PM1, PM2.5, and PM10 (µg/m3), CO2 concentration (ppm), temperature (K), and humidity (h−1) during two summer days (AGP: n = 30; non-AGP: n = 30). While simulating our teaching routine, no base level for air parameters was defined. Therefore, the change in each parameter (Δ = [post]-[pre] per hour) was calculated. Results. We found significant differences in ΔPM2.5 and ΔPM1 values (median (25/75th percentiles)) comparing AGP2 versus AGP1 (ΔPM2.5: 1.6(0/4.9)/−3.5(−10.0/−1.1),

p
=
0.003

; ΔPM1: 1.6(0.6/2.2)/−2.2(−9.3/−0.5),

p
=
0.001

). Between both non-AGPs, there were no significant differences in all the parameters that were measured. ΔCO2 increased in all AGP phases (AGP1/AGP2: 979.0(625.7/1126.9)/549.9(4.0/788.8)), while during non-AGP phases, values decreased (non-AGP1/non-AGP2: −447.3(−1122.3/641.2)/−896.6(−1307.3/−510.8)). ∆Temperature findings were similar (AGP1/AGP2: 12.5(7.8/17.0)/9.3(1.8/15.3) versus non-AGP1/non-AGP2: −13.1(−18.7/0)/−14.7(−16.8/−6.8);

p
≤
0.003

)), while for ∆humidity, no significant difference (

p
>
0.05

) was found. Conclusions. Within the limitations of the study, the combination of HVE and EOS was similarly effective in controlling aerosol emissions of particles between one and ten micrometers in skill labs during AGPs versus that during non-AGPs. After AGPs, air exchange with the AC should be complemented by open doors for better air quality if natural ventilation through open windows is restricted.
Application Effect of Sevoflurane Combined with Nerve Block Anesthesia in Surgical Anesthesia in Patients with Uterine Fibroids
Authors: Fan Shujing , Li Shiduo
Published: June 2022

Sevoflurane has been widely used clinically as an inhalation anesthetic. A review of domestic and domestic research, combined with the current synthesis research, pharmacological progress, existing production capacity, production, and sales status, can show that sevoflurane is a very good new type of inhalation anesthetic. Objective. To study the effect of sevoflurane combined with nerve block anesthesia on stress response and hemodynamics in patients with uterine fibroids surgery. Methods. We selected 100 cases of myomectomy patients as the research objects and divided them into observation and control groups according to the random number table method, with 50 cases in each group. The comparison group received propofol combined with remifentanil intravenous compound anesthesia, while the observation group received sevoflurane combined with nerve block anesthesia. The stress response and hemodynamic changes were compared between the two groups 5 minutes before anesthesia (T1), 30 minutes after pneumoperitoneum (T2), and at the end of the operation (T3). At the same time, the differences in cognitive function and adverse reactions were also compared 1 day before surgery and 1 day after surgery. Results. At T2 and T3, the stress response indexes of cortisol, epinephrine, norepinephrine, and blood sugar in the observation group were lower than those in the control group. In addition, hemodynamic indicators heart rate, mean arterial pressure, and blood sample saturation levels were also lower than those in the control group. One day after the operation, the score of the Simple Mental State Scale in the observation group was higher than that in the control group, and the time phrase for the completion of the connection test was in the control group. The incidence of adverse reactions in the observation group was lower than that in the comparison group. Conclusion. Sevoflurane combined with nerve block anesthesia in patients undergoing myomectomy can significantly reduce the body’s response to hormones, maintain hemodynamic stability, reduce cognitive impairment, and help avoid adverse reactions.
Relationship between Fragmented QRS and Microvascular Dysfunction in Masked Hypertension
Authors: Mahfouz Ragab A. , Mesbah Mohamed , Gad Marwa M. , Abulfotouh Moheye , Arab Mohamed
Published: June 2022

Aim: The aim of this study was to investigate the presence of fQRS and its association with subclinical systolic and microvascular dysfunction in patients with masked hypertension (MH). Methods: The study population consisted of 95 (mean age 48.9 ± 11.3, 61% males) subjects with MH and 80 age- and gender-matched healthy individuals who served as a control group. Coronary flow reserve (CFR) using transthoracic echocardiography and for left ventricular global longitudinal strain (LVGLS) using speckle-tracking strain imaging were performed. Patients with MH were stratified into two groups according to the presence of fQRS on surface electrocardiogram. Results: Fragmented QRS was more common among MH patients compared with controls (38.9% vs. 6.25%, p < 0.003). CFR was significantly lower in patients with fQRS compared with those without fQRS and controls (p < 0.001). Likewise, LVGLS values were lower in MH patients with fQRS (p < 0.001) compared with subjects without fQRS and controls. Fragmented fQRS was significantly correlated with systolic blood pressure, CFR, and LVGLS. Multivariate analysis showed that the presence of fQRS, number of leads, and CFR were independent predictors of subclinical systolic dysfunction. With ROC cure analysis, number of leads with fQRS ≥4 was the optimal value for predicting the presence of subclinical systolic dysfunction in subjects with MH. Conclusions: Fragmented QRS is more frequent among subjects with MH compared with controls. The presence of fQRS is related with pronounced subclinical left ventricular systolic dysfunction. Furthermore, CFR was significantly reduced in subjects with MH, a finding supposed that microvascular dysfunction to be a mechanistic link.
Supravenous Repigmentation of Hair Shafts in a Patient with Regrowing Alopecia Totalis: A Case Report and Hypothesis
Authors: Rotrosen Elizabeth T. , Lam Jimmy , Goldberg Lynne J.
Published: June 2022

Introduction: Alopecia areata (AA) is a type of nonscarring alopecia that has autoimmune etiology, in which the hair follicle, usually an immune-privileged site, becomes the target of attack. Alopecia totalis (AT) is a subset of AA in which patients completely lose hair on the scalp. Initial hair regrowth is often fine and without pigment. We present a case of AT in which pigmented hair grew only overlying superficial veins, a finding which has not been previously reported. Case Presentation: An adult female with brown hair presented with AA that progressed to AT despite the use of triamcinolone ointment and topical 2% tofacitinib ointment. She was treated with nightly augmented betamethasone dipropionate 0.05% ointment under occlusion. Two months later, she noticed diffuse regrowth of thin hair on her scalp, most of which was depigmented. However, linear bands of darkly pigmented hairs were noted overlying superficial scalp veins. Discussion/Conclusion: Loss of pigmentation and subsequent repigmentation of the hair shaft in regrowing AA is not entirely understood. Initial hair regrowth in AA tends to be fine and depigmented, although the hair will usually regain normal texture and color. Pigmentation following a vein suggests that local temperature may play a role, possibly augmented by corticosteroid induced reduced expression of inflammatory cytokines and endothelial release of the vasoconstrictor hormone endothelin, which stimulates melanogenesis.
Pan-Esophageal Submucosal Dissection following Transesophageal Echocardiography
Authors: Qatomah Abdulrahman , Cools-Lartigue Jonathan , Moss Emmanuel , Wyse Jonathan , Miller Corey S.
Published: June 2022

A 73-year-old female underwent open mitral valve replacement with transesophageal echocardiography (TEE) guidance. She developed upper gastrointestinal bleeding postoperatively and was found on upper endoscopy to have a bleeding site at the gastric cardia with the appearance of focal trauma and a possible puncture site. A submucosal bluish protrusion was seen throughout the esophagus with a mucosal flap at the proximal esophagus. As a unifying diagnosis, it was suspected that the intraoperative TEE probe caused a submucosal dissection with point of entry at the proximal esophagus, running the entire length of the esophagus and exiting at the gastric cardia, giving rise to a clinical upper gastrointestinal bleed. Closure of the esophageal defect was achieved using an endoclip. A CT scan showed focal pneumomediastinum along the proximal esophagus, confirming the hypothesis. We report the first case to our knowledge of iatrogenic pan-esophageal submucosal dissection, which, in this case, presented as a clinical bleed from the exit point trauma to the gastric cardia mucosa caused by a TEE probe. Endoscopic management of the gastric injury as well as the esophageal defect led to resolution of the bleeding and avoidance of mediastinitis, respectively, allowing for an excellent recovery.
Model Predictability of Hail Precipitation with a Moderate Hailstorm Case. Part I: Impact of Improved Initial Conditions by Assimilating High-Density Observations
Authors: Li Rumeng , Sun Juanzhen , Zhang Qinghong , Jensen Anders A.
Published: June 2022

Hailstones have large damage potential; however, their explicit prediction remains quite challenging. The uncertainty in a model’s initial condition and microphysics are two of the significant contributors to the challenge. This two-part study aims to investigate the impacts of improved initial condition and microphysics on hail prediction for a moderate hailstorm that occurred in Beijing on 10 June 2016. In the first part, the role of initial conditions on hail prediction is explored by assimilating high-density observations into a numerical model with a recently developed explicit hail microphysics scheme. High-resolution and high-frequency observations from radar and surface networks are assimilated using the Weather Research and Forecasting (WRF) Model’s three-dimensional variational data assimilation (3DVAR) system. The role of the initial conditions in improving explicit hail prediction with two different planetary boundary layer (PBL) schemes, the Yonsei University (YSU) scheme and the Mellor–Yamada–Janjić (MYJ) scheme, is then examined. Results indicate that the data assimilation significantly improves the hail size and location prediction for both PBL schemes by reducing errors in surface wind, temperature, and moisture fields. It is also shown that the improved analyses of low-level and midlevel vertical wind shear, resulting mainly from radar data assimilation, are pivotal to the improvement of hailstorm prediction with the YSU scheme, while the improved analysis of thermodynamic field resulting from the assimilation of both radar and surface data plays a more important role with the MYJ scheme. The results of this work shed light on the influence of data assimilation and provide insights on explicit hail predictability with respect to model initial conditions.