bluuebunny/crossref_metadata_2025 huggingface dataset:
STAT6/VDR Axis Mitigates Lung Inflammatory Injury by Promoting Nrf2 Signaling Pathway
Authors: Yang Youjing , Li Qianmin , Wei Shuhui , Chu Kaimiao , Xue Lian , Liu Jie , Ma Yu , Tao Shasha
Published: January 2022

Lung inflammatory injury is a global public health concern. It is characterized by infiltration of diverse inflammatory cells and thickening of pulmonary septum along with oxidative stress to airway epithelial cells. STAT6 is a nuclear transcription factor that plays a crucial role in orchestrating the immune response, but its function in tissue inflammatory injury has not been comprehensively studied. Here, we demonstrated that STAT6 activation can protect against particle-induced lung inflammatory injury by resisting oxidative stress. Specifically, genetic ablation of STAT6 was observed to worsen particle-induced lung injury mainly by disrupting the lungs’ antioxidant capacity, as reflected by the downregulation of the Nrf2 signaling pathway, an increase in malondialdehyde levels, and a decrease in glutathione levels. Vitamin D receptor (VDR) has been previously proved to positively regulate Nrf2 signals. In this study, silencing VDR expression in human bronchial epithelial BEAS-2B cells consistently suppressed autophagy-mediated activation of the Nrf2 signaling pathway, thereby aggravating particle-induced cell damage. Mechanically, STAT6 activation promoted the nuclear translocation of VDR, which increased the transcription of autophagy-related genes and induced Nrf2 signals, and silencing VDR abolished these effects. Our research provides important insights into the role of STAT6 in oxidative damage and reveals its potential underlying mechanism. This information not only deepens the appreciation of STAT6 but also opens new avenues for the discovery of therapies for inflammatory respiratory system disorders.
Brain Tumor Detection and Classification by MRI Using Biologically Inspired Orthogonal Wavelet Transform and Deep Learning Techniques
Authors: Arif Muhammad , Ajesh F. , Shamsudheen Shermin , Geman Oana , Izdrui Diana , Vicoveanu Dragos
Published: January 2022

Radiology is a broad subject that needs more knowledge and understanding of medical science to identify tumors accurately. The need for a tumor detection program, thus, overcomes the lack of qualified radiologists. Using magnetic resonance imaging, biomedical image processing makes it easier to detect and locate brain tumors. In this study, a segmentation and detection method for brain tumors was developed using images from the MRI sequence as an input image to identify the tumor area. This process is difficult due to the wide variety of tumor tissues in the presence of different patients, and, in most cases, the similarity within normal tissues makes the task difficult. The main goal is to classify the brain in the presence of a brain tumor or a healthy brain. The proposed system has been researched based on Berkeley’s wavelet transformation (BWT) and deep learning classifier to improve performance and simplify the process of medical image segmentation. Significant features are extracted from each segmented tissue using the gray-level-co-occurrence matrix (GLCM) method, followed by a feature optimization using a genetic algorithm. The innovative final result of the approach implemented was assessed based on accuracy, sensitivity, specificity, coefficient of dice, Jaccard’s coefficient, spatial overlap, AVME, and FoM.
Application of Virtual Reality Based on Computer Vision in Sports Posture Correction
Authors: Zhu Chengdong , Shao Ruizhi , Zhang Xinmiao , Gao Shan , Li Bowen
Published: January 2022

In recent years, with the rise of virtual and sports, people are often injured due to irregular movements during exercise. Based on this, this article takes the basic concept of computer virtual reality as the starting point and analyzes the adoption of computer virtual reality in sports correction. The choice of corrective exercises depends on the daily wrong exercises. If there is an error in any operation, please select the corresponding operation mode for the error operation for corrective training. If there are multiple errors at the same time, we compare and select the error operation that needs to be resolved first and the error operation that needs to be resolved later. In our daily life, the squat action pattern of Tai Chi Half-squat stance ball is closely related to us, and its action pattern can fully reflect the core stability of the subject. In this study, 42 students were selected as the students of a college sports college in Dalian. There are 7 people in each group, divided into 6 groups. The first three groups used exercise correction to assist the traditional teaching method (experimental group). It was found that the performance error rate of the first three groups reached 65%, and the last three groups used the assisted virtual reality teaching method, and the error rate was only 4%. Therefore, we adopted the teaching of virtual reality can reduce the error rate of the movement posture. We trained them for half a year and assessed and scored them once a month. We collect this data and analyze it to reach a conclusion. The experimental results prove that the experimental group has a significant difference before and after the squat test (

P
<
0.05

), and postexperiment there is a remarkable disparity among the experimental group and the comparison group (

P
<
0.05

). Therefore, squatting correction training is effective in improving the wrong squat. It is very effective for problems such as posture movement mode and joint limitation. Therefore, it is a very meaningful thing to explore the exercise correction training based on the virtual reality of computer vision.
Studies on Synthesis and Characterization of Fe3O4@SiO2@Ru Hybrid Magnetic Composites for Reusable Photocatalytic Application
Authors: Kumar Avvaru Praveen , Bilehal Dinesh , Desalegn Tegene , Kumar Shalendra , Ahmed Faheem , Murthy H. C. Ananda , Kumar Deepak , Gupta Gaurav , Chellappan Dinesh Kumar , Singh Sachin Kumar , Dua Kamal , Lee Yong-Ill
Published: January 2022

Degradation of dye pollutants by the photocatalytic process has been regarded as the most efficient green method for removal organic dyes from contaminated water. The current research work describes the synthesis of Fe3O4@SiO2@Ru hybrid magnetic composites (HMCs) and their photocatalytic degradation of two azo dye pollutants, methyl orange (MO) and methyl red (MR), under irradiation of visible light. The synthesis of Fe3O4@SiO2@Ru HMCs involves three stages, including synthesis of Fe3O4 magnetic microspheres (MMSs), followed by silica (SiO2) coating to get Fe3O4@SiO2 MMSs, and then incorporation of presynthesized Ru nanoparticles (~3 nm) onto the surface of Fe3O4@SiO2 HMCs. The synthesized HMCs were characterized by XRD, FTIR, TEM, EDS, XPS, BET analysis, UV-DRS, PL spectroscopy, and VSM to study the physical and chemical properties. Furthermore, the narrow band gap energy of the HMC photocatalyst is a significant parameter that provides high photocatalytic properties due to the high light adsorption. The photocatalytic activity of synthesized Fe3O4@SiO2@Ru HMCs was assessed by researching their ability to degrade the aqueous solution of MO and MR dyes under visible radiation, and the influence of various functional parameters on photocatalytic degradation has also been studied. The results indicate that the photocatalytic degradation of MO and MR dyes is more than 90%, and acid media favors better degradation. The probable mechanism of photodegradation of azo dyes by Fe3O4@SiO2@Ru HMC catalysts has been proposed. Furthermore, due to the strong ferromagnetic Fe3O4 core, HMCs were easily separated from the solution after the photocatalytic degradation process for reuse. Also, the photocatalytic activity after six cycles of use is greater than 90%, suggesting the stability of the synthesized Fe3O4@SiO2@Ru HMCs.
Circulating MicroRNAs for Diagnosis of Acute Pulmonary Embolism: Still a Long Way to Go
Authors: Sobrero Matteo , Montecucco Fabrizio , Carbone Federico
Published: January 2022

Venous thromboembolism (VTE) represents the third most frequent cause of acute cardiovascular syndrome. Among VTE, acute pulmonary embolism (APE) is the most life‐threatening complication. Due to the low specificity of symptoms clinical diagnosis of APE may be sometimes very difficult. Accordingly, the latest European guidelines only suggest clinical prediction tests for diagnosis of APE, eventually associated with D‐dimer, a biomarker burdened by a very low specificity. A growing body of evidence is highlighting the role of miRNAs in hemostasis and thrombosis. Due to their partial inheritance and susceptibility to the environmental factors, miRNAs are increasingly described as active modifiers of the classical Virchow’s triad. Clinical evidence on deep venous thrombosis reported specific miRNA signatures associated to thrombosis development, organization, recanalization, and resolution. Conversely, data of miRNA profiling as a predictor/diagnostic marker of APE are still preliminary. Here, we have summarized clinical evidence on the potential role of miRNA in diagnosis of APE. Despite some intriguing insight, miRNA assay is still far from any potential clinical application. Especially, the small sample size of cohorts likely represents the major limitation of published studies, so that extensive analysis of miRNA profiles with a machine learning approach are warranted in the next future. In addition, the cost‐benefit ratio of miRNA assay still has a negative impact on their clinical application and routinely test.
Prediction of Lung Infection during Palliative Chemotherapy of Lung Cancer Based on Artificial Neural Network
Authors: Guo Wei , Gao Guoyun , Dai Jun , Sun Qiming
Published: January 2022

Lung infection seriously affects the effect of chemotherapy in patients with lung cancer and increases pain. The study is aimed at establishing the prediction model of infection in patients with lung cancer during chemotherapy by an artificial neural network (ANN). Based on the data of historical cases in our hospital, the variables were screened, and the prediction model was established. A logistic regression (LR) model was used to screen the data. The indexes with statistical significance were selected, and the LR model and back propagation neural network model were established. A total of 80 cases of advanced lung cancer patients with palliative chemotherapy were predicted, and the prediction performance of different model was evaluated by the receiver operating characteristic curve (ROC). It was found that

age
≧
60

years, length of

stay
≧
14

 d, surgery history, combined chemotherapy, myelosuppression, diabetes, and hormone application were risk factors of infection in lung cancer patients during chemotherapy. The area under the ROC curve of the LR model for prediction lung infection was

0.729
±
0.084

, which was less than that of the ANN model (

0.897
±
0.045

). The results concluded that the neural network model is better than the LR model in predicting lung infection of lung cancer patients during chemotherapy.
A Real-Time Complex Road AI Perception Based on 5G-V2X for Smart City Security
Authors: Xu Cheng , Wu Hongjun , Zhang Yinong , Dai Songyin , Liu Hongzhe , Tian Jin
Published: January 2022

The Internet of Vehicles and information security are key components of a smart city. Real-time road perception is one of the most difficult tasks. Traditional detection methods require manual adjustment of parameters, which is difficult, and is susceptible to interference from object occlusion, light changes, and road wear. Designing a robust road perception algorithm is still challenging. On this basis, we combine artificial intelligence algorithms and the 5G-V2X framework to propose a real-time road perception method. First, an improved model based on Mask R-CNN is implemented to improve the accuracy of detecting lane line features. Then, the linear and polynomial fitting methods of feature points in different fields of view are combined. Finally, the optimal parameter equation of the lane line can be obtained. We tested our method in complex road scenes. Experimental results show that, combined with 5G-V2X, this method ultimately has a faster processing speed and can sense road conditions robustly under various complex actual conditions.
A Stochastic SEIRS Epidemic Model with Infection Forces and Intervention Strategies
Authors: Lijuan Zhang , Fuchang Wang , Hongri Liang
Published: January 2022

The spread of epidemics has been extensively investigated using susceptible-exposed infectious-recovered-susceptible (SEIRS) models. In this work, we propose a SEIRS pandemic model with infection forces and intervention strategies. The proposed model is characterized by a stochastic differential equation (SDE) framework with arbitrary parameter settings. Based on a Markov semigroup hypothesis, we demonstrate the effect of the proliferation number

R
0
S

on the SDE solution. On the one hand, when

R
0
S

<
1

, the SDE has an illness-free solution set under gentle additional conditions. This implies that the epidemic can be eliminated with a likelihood of 1. On the other hand, when

R
0
S

>
1

, the SDE has an endemic stationary circulation under mild additional conditions. This prompts the stochastic regeneration of the epidemic. Also, we show that arbitrary fluctuations can reduce the infection outbreak. Hence, valuable procedures can be created to manage and control epidemics.
The Influence of the Inclination of Lattice Columns on the Safety of Combined Tower Crane
Authors: Wang Yongquan , Li Tianfu , Dong Kaifa , Guo Zhengxing , Fu Jing
Published: January 2022

The combined tower crane foundation is widely used in construction sites due to its advanced utilization rate. However, the immature construction method, unavoidable construction deviation during the installation process, and influence of the surrounding construction generally cause the lattice columns to tilt. As the main force transmission components of the tower crane foundation, once its stress and deformation exceed the limit, the entire tower crane will collapse, which requires engineers to accurately control its safety. Therefore, the objective of the work reported here was to study the safety of the lattice columns during operation. A geometrically nonlinear finite element model was utilized to simulate the strain and deformation capacity of tower cranes under various working conditions, including vertical and inclined working conditions, operation and shutdown conditions, and conditions with the tower boom in different orientations. In addition, this study combines the simulation with the on‐site measurement. The results of on‐site measurement were also recorded to verify the correctness of the proposed calculation model. It was concluded that the inclination of lattice columns has a significant effect on the deformation and stress of the lattice columns of the tower crane foundation, and the measured data and the calculated data trend are consistent. Engineers can accurately judge the safety of the lattice columns of the tower crane foundation through geometric nonlinear finite element model analysis and on‐site monitoring to avoid the failure of the lattice columns and the occurrence of safety accidents.
Development of a Hepatoprotective Herbal Drug from Turnera diffusa
Authors: Delgado-Montemayor Cecilia , Cordero-Pérez Paula , Torres-González Liliana , Salazar-Cavazos María de la L. , Saucedo Alma L. , Paniagua-Vega David , Waksman-Minsky Noemí H.
Published: January 2022

The incidence of liver diseases, such as nonalcoholic fatty liver disease and drug-induced liver injury, continues to rise and is one of the leading causes of acute hepatitis. Current trends suggest that these types of conditions will increase in the coming years. There are few drugs available for the prevention or treatment of hepatic diseases, and there is a growing need for the development of safe hepatoprotective agents. The medicinal plant, Turnera diffusa, has many ethnopharmacological uses, one of which is the production of a flavonoid named hepatodamianol, which is the principal component responsible for this plant’s hepatoprotective properties. In the present study, we describe the development and standardization of an active extract obtained from T. diffusa. We conducted nuclear magnetic resonance spectroscopy to identify hepatodamianol unambiguously in each sample. Using this extract, hepatoprotection could be demonstrated in vivo for the first time. The hepatoprotective effect did not display a significant difference in vivo when compared with silymarin used as a positive control at the same doses. Implementation of quality criteria used for standardization, such as flavonoid and hepatodamianol content, hepatoprotective activity, and absence of residual solvents, will allow future preclinical trials with this herbal drug.
3β,23-Dihydroxy-12-ene-28-ursolic Acid Isolated from Cyclocarya paliurus Alleviates NLRP3 Inflammasome-Mediated Gout via PI3K-AKT-mTOR-Dependent Autophagy
Authors: Lou Dongxiao , Zhang Xiaogai , Jiang Cuihua , Zhang Fang , Xu Chao , Fang Shengzuo , Shang Xulan , Zhang Jian , Yin Zhiqi
Published: January 2022

Gout is regarded as a painful inflammatory arthritis induced by the deposition of monosodium urate crystals in joints and soft tissues. Nucleotide-binding oligomerization domain (NOD)-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome-mediated IL-1β production plays a crucial role in the pathological process of gout. Cyclocarya paliurus (CP) tea was found to have an effect on reducing the blood uric acid level of people with hyperuricemia and gout. However, its medicinal ingredients and mechanism for the treatment of gout are still unclear. Thus, this study was designed to investigate the effects of the active triterpenoids isolated from C. paliurus on gout and explore the underlying mechanism. The results showed that compound 2 (3β,23-dihydroxy-12-ene-28-ursolic acid) from C. paliurus significantly decreased the protein expression of IL-1β, caspase-1, pro-IL-1β, pro-caspase-1, and NLRP3. Furthermore, the production of ROS in the intracellular was reduced after compound 2 treatment. However, ROS agonist rotenone remarkably reversed the inhibitory effect of compound 2 on the protein expression of NLRP3 inflammasome. Additionally, the expression level of LC3 and the ratio of LC3II/LC3I were increased, but the expression level of p62 was suppressed by compound 2 whereas an autophagy inhibitor 3-methyladenine (3-MA) significantly abolished the inhibitory effects of compound 2 on the generation of ROS and the protein expression of NLRP3 inflammasome. Moreover, compound 2 could ameliorate the expression ratio of p-PI3K/PI3K, p-AKT/AKT, and p-mTOR/mTOR. Interestingly, mTOR activator MHY-1485 could block the promotion effect of compound 2 on autophagy regulation and inhibitory effect of compound 2 on induction of ROS and IL-1β. In conclusion, these findings suggested that compound 2 may effectively improve NLRP3 inflammasome-mediated gout via PI3K-AKT-mTOR-dependent autophagy and could be further investigated as a potential agent against gout.
User Authentication Method via Speaker Recognition and Speech Synthesis Detection
Authors: Park Hyun , Kim TaeGuen
Published: January 2022

As the Internet has been developed, various online services such as social media services are introduced and widely used by many people. Traditionally, many online services utilize self-certification methods that are made using public certificates or resident registration numbers, but it is found that the existing methods pose the risk of recent personal information leakage accidents. The most popular authentication method to compensate for these problems is biometric authentication technology. The biometric authentication techniques are considered relatively safe from risks like personal information theft, forgery, etc. Among many biometric-based methods, we studied the speaker recognition method, which is considered suitable to be used as a user authentication method of the social media service usually accessed in the smartphone environment. In this paper, we first propose a speaker recognition-based authentication method that identifies and authenticates individual voice patterns, and we also present a synthesis speech detection method that is used to prevent a masquerading attack using synthetic voices.
Attention Neural Network for Biomedical Word Sense Disambiguation
Authors: Zhang Chun-Xiang , Pang Shu-Yang , Gao Xue-Yao , Lu Jia-Qi , Yu Bo
Published: January 2022

In order to improve the disambiguation accuracy of biomedical words, this paper proposes a disambiguation method based on the attention neural network. The biomedical word is viewed as the center. Morphology, part of speech, and semantic information from 4 adjacent lexical units are extracted as disambiguation features. The attention layer is used to generate a feature matrix. Average asymmetric convolutional neural networks (Av‐ACNN) and bidirectional long short‐term memory (Bi‐LSTM) networks are utilized to extract features. The softmax function is applied to determine the semantic category of the biomedical word. At the same time, CNN, LSTM, and Bi‐LSTM are applied to biomedical WSD. MSH corpus is adopted to optimize CNN, LSTM, Bi‐LSTM, and the proposed method and testify their disambiguation performance. Experimental results show that the average disambiguation accuracy of the proposed method is improved compared with CNN, LSTM, and Bi‐LSTM. The average disambiguation accuracy of the proposed method achieves 91.38%.
Data Mining in Employee Healthcare Detection Using Intelligence Techniques for Industry Development
Authors: Mehbodniya Abolfazl , Khan Ihtiram Raza , Chakraborty Sudeshna , Karthik M. , Mehta Kamakshi , Ali Liaqat , Nuagah Stephen Jeswinde
Published: January 2022

Background. Even in today’s environment, when there is a plethora of information accessible, it may be difficult to make appropriate choices for one’s well-being. Data mining, machine learning, and computational statistics are among the most popular arenas of training today, and they are all aimed at secondary empowered person in making good decisions that will maximize the outcome of whatever working area they are involved with. Because the degree of rise in the number of patient roles is directly related to the rate of people growth and lifestyle variations, the healthcare sector has a significant need for data processing services. When it comes to cancer, the prognosis is an expression that relates to the possibility of the patient surviving in general, but it may also be used to describe the severity of the sickness as it will present itself in the patient's future timeline. Methodology. The proposed technique consists of three stages: input data acquisition, preprocessing, and classification. Data acquisition consists of input raw data which is followed by preprocessing to eliminate the missed data and the classification is carried out using ensemble classifier to analyze the stages of cancer. This study explored the combined influence of the prominent labels in conjunction with one another utilizing the multilabel classifier approach, which is successful. Finally, an ensemble classifier model has been constructed and experimentally validated to increase the accuracy of the classifier model, which has been previously shown. The entire performance of the recommended and tested models demonstrates a steady development of 2% to 6% over the baseline presentation on the baseline performance. Results. Providing a good contribution to the general health welfare of noncommercial potential workers in the healthcare sector is an opportunity provided by this recommended job outcome. It is anticipated that alternative solutions to these constraints, as well as automation of the whole process flow of all five phases, will be the key focus of the work to be carried out shortly. Predicting health status of employee in industry or information trends is made easier by these data patterns. The proposed classifier achieves the accuracy rate of 93.265%.
Study on the Mechanism of Platelet-Released Clusterins Inducing Restenosis after Carotid Endarterectomy by Activating TLR3/NF-κb p65 Signaling Pathway
Authors: Meng Qingyu , Li Xichun , Zhao Mingyu , Lin Shusen , Yu Xiangwen , Dong Guanglong
Published: January 2022

This study aimed to explore the role of clusterin released by platelet aggregation in restenosis after carotid endarterectomy. 35 patients who underwent carotid endarterectomy due to carotid artery stenosis were enrolled in this study. They were admitted to the Third Affiliated Hospital of Qiqihar Medical University from January 2018 to January 2019. All the patients were divided into two groups: the restenosis group and the nonrestenosis group, according to the follow-up results within 12 months. Peripheral blood was collected on the first day, 6 months, and 12 months after operation. The expression of CLU in serum of plasma and platelet culture medium was detected by an ELISA experiment. The vascular endothelial cells were cultured in vitro with 100 ng/mL of human recombinant CLU added to the medium. Cell proliferation, migration, and invasion were detected by CCK8, scratch, and Transwell invasion tests. The expression level of TLR3 and NF-κb p65 proteins in cells was detected by western blot. TLR3 knockout plasmids in vascular endothelial cell lines were transfected. Cell proliferation and migration were detected by CCK8 and the scratch assay. The CLU content in peripheral blood plasma and supernatant of platelet culture medium was significantly higher in the restenosis group than that of the control group (

p
=
0.003

) 6 months after operation (

p
=
0.047

) and 12 months after operation (

p
=
0.011

). When CLU was added to vascular endothelial cell culture medium, the proliferation and migration were significantly enhanced. The TLR3/NF-κb p65 protein expression level in cells also significantly increased. After the transfection of TLR3 knockout plasmids into vascular endothelial cell lines, CLU cannot promote the proliferation and migration of vascular endothelial cells. Platelet-released clusterin can induce vascular endothelial cell proliferation and migration by activating the TLR3/NF-kb p65 signaling pathway, leading to carotid artery restenosis after carotid endarterectomy.
The Oxidative Balance Orchestrates the Main Keystones of the Functional Activity of Cardiomyocytes
Authors: Bevere Michele , Morabito Caterina , Mariggiò Maria A. , Guarnieri Simone
Published: January 2022

This review is aimed at providing an overview of the key hallmarks of cardiomyocytes in physiological and pathological conditions. The main feature of cardiac tissue is the force generation through contraction. This process requires a conspicuous energy demand and therefore an active metabolism. The cardiac tissue is rich of mitochondria, the powerhouses in cells. These organelles, producing ATP, are also the main sources of ROS whose altered handling can cause their accumulation and therefore triggers detrimental effects on mitochondria themselves and other cell components thus leading to apoptosis and cardiac diseases. This review highlights the metabolic aspects of cardiomyocytes and wanders through the main systems of these cells: (a) the unique structural organization (such as different protein complexes represented by contractile, regulatory, and structural proteins); (b) the homeostasis of intracellular Ca2+ that represents a crucial ion for cardiac functions and E-C coupling; and (c) the balance of Zn2+, an ion with a crucial impact on the cardiovascular system. Although each system seems to be independent and finely controlled, the contractile proteins, intracellular Ca2+ homeostasis, and intracellular Zn2+ signals are strongly linked to each other by the intracellular ROS management in a fascinating way to form a “functional tetrad” which ensures the proper functioning of the myocardium. Nevertheless, if ROS balance is not properly handled, one or more of these components could be altered resulting in deleterious effects leading to an unbalance of this “tetrad” and promoting cardiovascular diseases. In conclusion, this “functional tetrad” is proposed as a complex network that communicates continuously in the cardiomyocytes and can drive the switch from physiological to pathological conditions in the heart.
A Pyroptosis-Based Prognostic Model for Immune Microenvironment Estimation of Hepatocellular Carcinoma
Authors: Chen Zhihong , Zou Yiping , Zhang Yuanpeng , Chen Zhenrong , Wu Fan , Jin Haosheng , Shi Ning
Published: January 2022

Background. Hepatocellular carcinoma (HCC), an aggressive malignant tumor, has a high incidence and unfavorable prognosis. Recently, the synergistic effect of pyroptosis in antitumor therapy and regulation of tumor immune microenvironment has made it possible to become a novel therapeutic method, but its potential mechanism still needs further exploration. Methods. Differentially expressed genes with prognostic value in Liver Hepatocellular Carcinoma Project of The Cancer Genome Atlas (TCGA-LIHC) cohort were screened and incorporated into the risk signature by Cox proportional hazards regression model and least absolute shrinkage and selection operator. Kaplan-Meier (KM) curves and receiver operating characteristic (ROC) curves were applied to conduct survival comparisons and estimate prediction ability. The dataset of Liver Cancer-RIKEN, Japan Project from International Cancer Genome Consortium (ICGC-LIRI-JP) cohort was used to verify the reliability of the signature. Correlation analysis between clinicopathological characteristics, immune infiltration, drug sensitivities, and risk scores was conducted. Functional annotation analyses were performed for the genes differentially expressed between high-risk and low-risk groups. Results. A risk signature consisting of 6 pyroptosis-related genes in HCC was developed and validated. KM curves and ROC curves revealed its considerable predictive accuracy. Higher risk scores meant more advanced grade, higher alpha-fetoprotein level, and stronger invasive ability. Overexpressed genes in high-risk population were more enriched in the immune-associated pathways, and these patients might be more sensitive to immune checkpoint inhibitors instead of Sorafenib. Intriguingly, 6 identified genes were promising to be prognostic biomarkers and therapeutic targets of HCC. Conclusions. The signature may have crucial clinical significance in predicting survival prognosis, immune infiltration, and drug efficacy based on pyroptosis-related genes.
Intentional Fallers with Complex Pelvic and Acetabular Fractures Do Not Have worse Radiological and Functional Outcomes than Accidental Fallers
Authors: Yu Yi-Hsun , Chou Ying-Chao , Yeh Bo-Yan , Hsu Yung-Heng , Chen I-Jung , Wei Lien-Chung
Published: January 2022

Individuals who fall from heights of ≥6 m can suffer from complex pelvic and acetabular fractures. The extent to which an intentional fall correlates with prognosis and outcome after osteosynthesis is unclear. Therefore, we aimed to investigate the clinical outcomes of fallers with pelvic and acetabular fractures after osteosynthesis and compare the radiological and functional outcomes between intentional and accidental fallers. We retrospectively reviewed 49 fallers who fell from heights of ≥6 m, developed pelvic and acetabular fractures, survived after resuscitation, and completed surgical treatment between 2014 and 2017. Fallers were divided into intentional and accidental fallers. Sixteen patients were intentional fallers, whereas the rest of the patients were accidental fallers. Psychiatric counseling was provided to each of the intentional fallers during follow‐up. All intentional fallers had preexisting mental disorders, and the most common diagnosis was adjustment disorder. The group of intentional fallers predominantly comprised females that had a higher injury and new injury severity scores and longer hospital stays. However, early loss of fixation (<3 months) and functional outcomes (Merle d’Aubigné and Majeed hip scores at 6‐ and 12‐month follow‐ups) did not significantly differ between intentional and accidental fallers. We found that intentional fallers with pelvic and acetabular fractures may have more severe combined injuries compared to accidental fallers. However, the radiological and functional outcomes of the intentional fallers after osteosynthesis were not inferior to those of the accidental fallers with the implementation of well‐designed surgical protocols and individualized physical and mental rehabilitation programs.
Optimized Multivariate Adaptive Regression Splines for Predicting Crude Oil Demand in Saudi Arabia
Authors: Alkhammash Eman H. , Kamel Abdelmonaim Fakhry , Al-Fattah Saud M. , Elshewey Ahmed M.
Published: January 2022

This paper presents optimized linear regression with multivariate adaptive regression splines (LR‐MARS) for predicting crude oil demand in Saudi Arabia based on social spider optimization (SSO) algorithm. The SSO algorithm is applied to optimize LR‐MARS performance by fine‐tuning its hyperparameters. The proposed prediction model was trained and tested using historical oil data gathered from different sources. The results suggest that the demand for crude oil in Saudi Arabia will continue to increase during the forecast period (1980–2015). A number of predicting accuracy metrics including Mean Absolute Error (MAE), Median Absolute Error (MedAE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and coefficient of determination (R2) were used to examine and verify the predicting performance for various models. Analysis of variance (ANOVA) was also applied to reveal the predicting result of the crude oil demand in Saudi Arabia and also to compare the actual test data and predict results between different predicting models. The experimental results show that optimized LR‐MARS model performs better than other models in predicting the crude oil demand.
Impact Coefficient Analysis of Curved Box Girder Bridge Based on Vehicle-Bridge Coupling
Authors: Guo Fei , Cai Heng , Li Huifang
Published: January 2022

In the current vehicle-bridge dynamics research studies, displacement impact coefficients are often used to replace the moment and shear force impact coefficients, and the vehicle model is also simplified as a moving-load model without considering the contribution of vehicle stiffness and damping to the system in some concerned research studies, which cannot really reflect the mechanical behavior of the structures under vehicle dynamic loads. This paper presents a vehicle-bridge coupling model for the prediction of dynamic responses and impact coefficient of the long-span curved bending beam bridge. The element stiffness matrix and mass matrix of a curved box girder bridge with 9 freedom degrees are directly deduced based on the principle of virtual work and dynamic finite element theory. The vibration equations of vehicle-bridge coupling are established by introducing vehicle mode with 7 freedom degrees. The Newmark-β method is adopted to solve vibration response of the system under vehicle dynamic loads, and the influences of flatness of bridge surface, vehicle speed, load weight, and primary beam stiffness on the impact coefficient are comprehensively discussed. The results indicate that the impact coefficient presents a nonlinear increment as the flatness of bridge surface changes from good to terrible. The vehicle-bridge coupling system resonates when the vehicle speeds reach 60 km/h and 100 km/h. The moment design value will maximally increase by 2.89%, and the shear force design value will maximally decrease by 34.9% when replacing moment and shear force impact coefficients with the displacement impact coefficient for the section internal force design. The load weight has a little influence on the impact coefficient; the displacement and moment impact coefficients are decreased with an increase in primary beam stiffness, while the shear force impact coefficient is increased with an increase in primary beam stiffness. The theoretical results presented in this paper agree well with the ANSYS results.
Heme Oxygenase-1 Inhibits the Proliferation of Hepatic Stellate Cells by Activating PPARγ and Suppressing NF-κB
Authors: Yang Hui , Zhang Li , Chen Jie , Zhang Xiaoqian , Zhao Zhongfu , Zhao Longfeng
Published: January 2022

Background. Hepatic stellate cells (HSCs) are reported to play significant roles in the development of liver fibrosis. Heme oxygenase-1 (HO-1) is a key rate-limiting enzyme, which could decrease collagen synthesis and liver damage. Nevertheless, it was yet elusive towards the function and mechanism of HO-1. Methods. An HO-1 inducer Hemin or an HO-1 inhibitor ZnPP-IX was used to treat the activated HSC-T6, respectively. MTT assay was adopted to detect cell proliferation. Immunocytochemical staining was employed to test the levels of alpha-smooth muscle actin (α-SMA), peroxisome proliferator-activated receptor-γ (PPARγ), and nuclear factor-kappa B (NF-kappa B) levels in HSC-T6. HO-1, PPARγ, and NF-κB expression levels were measured by qRT-PCR and Western blotting. ELISA was then used to detect the levels of transforming growth factor- (TGF-) beta 1 (TGF-β1), interleukin-6 (IL-6), serum hyaluronic acid (HA), and serum type III procollagen aminopeptide (PIIIP). Results. HSC-T6 proliferation was inhibited in Hemin-treated HSCs. The levels of α-SMA, HA, and PIIIP and the production of ECM were lower in Hemin-treated HSCs, whereas those could be rescued by ZnPP-IX. NF-κB activation was decreased, but PPARγ expression was increased after HO-1 upregulation. Furthermore, the levels of TGF-β1 and IL-6, which were downstream of activated NF-κB in HSC-T6, were reduced. The PPAR-specific inhibitor GW9662 could block those mentioned effects. Conclusions. Our data demonstrated that HO-1 induction could inhibit HSC proliferation and activation by regulating PPARγ expression and NF-κB activation directly or indirectly, which makes it a promising therapeutic target for liver fibrosis.
Molecular Docking for Ligand-Receptor Binding Process Based on Heterogeneous Computing
Authors: Li Jianhua , Liu Guanlong , Zhen Zhiyuan , Shen Zihao , Li Shiliang , Li Honglin
Published: January 2022

Molecular docking aims to predict possible drug candidates for many diseases, and it is computationally intensive. Particularly, in simulating the ligand-receptor binding process, the binding pocket of the receptor is divided into subcubes, and when the ligand is docked into all cubes, there are many molecular docking tasks, which are extremely time-consuming. In this study, we propose a heterogeneous parallel scheme of molecular docking for the binding process of ligand to receptor to accelerate simulating. The parallel scheme includes two layers of parallelism, a coarse-grained layer of parallelism implemented in the message-passing interface (MPI) and a fine-grained layer of parallelism focused on the graphics processing unit (GPU). At the coarse-grain layer of parallelism, a docking task inside one lattice is assigned to one unique MPI process, and a grouped master-slave mode is used to allocate and schedule the tasks. Meanwhile, at the fine-gained layer of parallelism, GPU accelerators undertake the computationally intensive computing of scoring functions and related conformation spatial transformations in a single docking task. The results of the experiments for the ligand-receptor binding process show that on a multicore server with GPUs the parallel program has achieved a speedup ratio as high as 45 times in flexible docking and as high as 54.5 times in semiflexible docking, and on a distributed memory system, the docking time for flexible docking and that for semiflexible docking gradually decrease as the number of nodes used in the parallel program gradually increases. The scalability of the parallel program is also verified in multiple nodes on a distributed memory system and is approximately linear.
Experimental Investigation on the Vertical Bearing Characteristics of Jacked Piles in Saturated Silt Foundations under Excavation
Authors: Jiu Yong-Zhi , Zhang Zhen , Zhang Xiang-Yu
Published: January 2022

A model test system for vertical bearing characteristics of the jacked piles in saturated soil foundations under excavation has been introduced. The system device comprises a soil pressure loading system, a model pile loading system, a soil vacuum saturation system, a model box, a model pile, and a control and data acquisition system. The soil vacuum saturation system designed for the model box of this test device can ensure that the saturated soil in the model box can reach a higher degree of saturation. Loading and unloading were conducted on the soil sample in the model box through the soil pressure loading system to simulate the soil excavation so that the soil sample and that in the field have the same stress state and history. The soil consolidation pressure, pile jacking pressure, pile tip force, soil consolidation settlement, and pile displacement at the top were collected and monitored in real time through the control and data acquisition system. This device is used to conduct an experimental study on the bearing characteristics of the jacked piles in saturated silt foundations under excavation. The results indicate that the static load test increases the residual pressure on the tip of the jacked pile while also increasing soil stiffness at pile tip and ultimate tip resistance, thereby increasing the pile top stiffness and ultimate load‐carrying capacity. However, when the jacked pile is left undisturbed for the same time, the static load test on the jacked pile does not affect the pile skin friction resistance. There is a better linear relationship between the pile skin friction resistance and the undrained shear strength of the soil under the corresponding stress path during the static load test of the normally consolidated soil and the jacked pile after overburden pressure unloading. There is a good linear relationship between the ultimate resistance and the undrained shear strength of the soil under the corresponding stress path in pile sinking, normally consolidated soil, and during the static load test on jacked pile after unloading.
Influential Nodes in the OBOR Fossil Energy Trade Network Based on D‐S Theory: Detection and Evolution Analysis
Authors: Gao Cuixia , Tao Simin , Li Kehu , He Yuyang
Published: January 2022

The structure formed by fossil energy trade among countries can be divided into multiple subcommodity networks. However, the difference of coupling mode and transmission mechanism between layers of the multirelationship network will affect the measurement of node importance. In this paper, a framework of multisource information fusion by considering data uncertainty and the classical network centrality measures is build. Then, the evidential centrality (EVC) indicator is proposed, by integrating Dempster–Shafer evidence theory and network theory, to empirically identify influential nodes of fossil energy trade along the Belt and Road Initiative. The initial result of the heterogeneity characteristics of the constructed network drives us to explore the core node issue further. The main detected evidential nodes include Russia, Kazakhstan, Czechia, Slovakia, Egypt, Romania, China, Saudi Arabia, and Singapore, which also have higher impact on network efficiency. In addition, cluster analysis discovered that resource endowment is an essential factor influencing country’s position, followed by geographical distance, economic level, and economic growth potential. Therefore, the above aspects should be considered when ensuring national trade security. At last, the rationality and comprehensiveness of EVC are verified by comparing with some benchmark centralities.
Combination of Methyl from Methane Early Cracking: A Possible Mechanism for Carbon Isotopic Reversal of Overmature Natural Gas
Authors: Mi Jingkui , He Kun , Shuai Yanhuan , Guo Jinhao
Published: January 2022

In this study, a methane (CH4) cracking experiment in the temperature range of 425–800°C is presented. The experimental result shows that there are some alkane and alkene generation during CH4 cracking, in addition to hydrogen (H2). Moreover, the hydrocarbon gas displays carbon isotopic reversal (

δ

13

C

1

>

δ

13

C

2

) below 700°C, while solid carbon appears on the inner wall of the gold tube above 700°C. The variation in experimental products (including gas and solid carbon) with increasing temperature suggests that CH4 does not crack into carbon and H2 directly during its cracking, but first cracks into methyl (CH3⋅) and proton (H+) groups. CH3⋅ shares depleted 13C for preferential bond cleavage in 12C–H rather than 13C–H. CH3⋅ combination leads to depletion of 13C in heavy gas and further causes the carbon isotopic reversal (

δ

13

C

1

>

δ

13

C

2

) of hydrocarbon gas. Geological analysis of the experimental data indicates that the amount of heavy gas formed by the combination of CH3⋅ from CH4 early cracking and with depleted 13C is so little that can be masked by the bulk heavy gas from organic matter (OM) and with enriched 13C at

R

o

<
2.5
%

. Thus, natural gas shows normal isotope distribution (

δ

13

C

1

<

δ

13

C

2

) in this maturity stage. CH3⋅ combination (or CH4 polymerization) intensifies on exhaustion gas generation from OM in the maturity range of

R

o

>
2.5
%

. Therefore, the carbon isotopic reversal of natural gas appears at the overmature stage. CH4 polymerization is a possible mechanism for carbon isotopic reversal of overmature natural gas. The experimental results indicate that although CH4 might have start cracking at

R

o

>
2.5
%

, but it cracks substantially above 6.0%

R

o

in actual geological settings.
The Association of Predicted Resting Energy Expenditure with Risk of Breast Cancer among Postmenopausal Women in the Women's Health Initiative Cohort
Authors: Arthur Rhonda S. , Mossavar-Rahmani Yasmin , Prentice Ross L. , Shadyab Aladdin H. , Luo Juhua , Sattari Maryam , Xue Xiaonan , Kamensky Victor , Chen Guo-Chong , Qi Qibin , Anderson Garnet L. , Wassertheil-Smoller Sylvia , Neuhouser Marian L. , Rohan Thomas E.
Published: January 2022

Obesity and obesity-related metabolic disorders, such as diabetes and chronic inflammation, have been positively associated both with postmenopausal breast cancer and with resting energy expenditure (REE). However, there is limited epidemiologic evidence on the associations between REE and risk of postmenopausal breast cancer. We used multivariable Cox proportional hazards models to examine the association between predicted REE (calculated using the Ikeda, Livingston, and Mifflin equations) and risk of postmenopausal breast cancer overall and by subtypes, and by level of body fat) among 137,283 postmenopausal women in the Women's Health Initiative (WHI). All predicted REEs were positively associated with risk of invasive breast cancer [HRq5 vs. q1 = 1.69; 95% confidence interval (CI), 1.57–1.81; HR = 1.69; 95% CI, 1.57–1.82; and HR = 1.68; 95% CI, 1.56–1.80 for Ikeda, Livingston, and Mifflin, respectively]. These positive associations were observed irrespective of the hormone receptor subtype, grade, and stage of the tumors, but were most pronounced for estrogen receptor–positive/progesterone receptor–positive tumors. After additional adjustment for body mass index (BMI), the associations were mostly attenuated and remained statistically significant for most of the outcomes. We also observed an interaction between the predicted REEs and BMI, with the associations being somewhat stronger among normal weight and overweight women than among obese women (Pinteractions < 0.05). Our findings indicate that relatively high REE is associated with increased risk of invasive breast cancer among postmenopausal women (particularly for the obesity-related tumor subtypes), irrespective of the equation used. Further studies using more objective measures of REE are, however, needed to confirm our findings.

Prevention Relevance:

This study showed that higher resting energy expenditure (REE) was associated with higher postmenopausal breast cancer risk. REE provides energy to support cancer-associated disorders such as obesity and inflammation. Thus, studies on its association with breast cancer can help to improve our understanding of the pathophysiology of breast cancer.