bluuebunny/crossref_metadata_2025 huggingface dataset:
Mild Hypothermia Promotes Ischemic Tolerance and Survival of Neural Stem Cell Grafts by Enhancing Global SUMOylation
Authors: Cai Heng , Ma Xiaofang , Lu Dading , Chen Liangyu , Bian Xiyun , Zhang Nan , Tang Wei , Liu Xiaozhi , Li Zhiqing
Published: May 2022

Cerebral infarct penumbra due to hypoxia and toxin accumulation is not conducive to the transplantation of neural stem cells (NSCs), although mild hypothermia can improve the local microenvironment of the ischemic penumbra and exert neuroprotective effects. However, insufficient understanding of the molecular mechanism by which mild hypothermia protects the brain limits widespread clinical application. This study evaluated the molecular mechanism of mild hypothermia-induced brain protection from the perspective of global protein small ubiquitin-like modifier (SUMO) modification, with the aim of improving NSC transplant survival rates in the penumbra to enhance neurological function. NSCs from neonatal rats were extracted to detect the effects of hypoxia and mild hypothermia on SUMOylation modification levels, cell stemness, and hypoxia-induced injury. Overexpression and knockdown of UBC9 in NSCs were used to evaluate their ability to maintain stemness and withstand hypoxic injury. Finally, a rat middle cerebral artery occlusion (MCAO) model was used to verify the effect of mild hypothermia treatment and UBC9 overexpression on neural function of NSCs following penumbra transplantation in rats. Results showed that hypoxia and mild hypothermia promoted both the SUMOylation modification and maintenance of NSC stemness. Overexpression of UBC9 enhanced the abilities of NSCs to maintain stemness and resist hypoxic injury, while UBC9 knockdown had the opposite effect. Following transplantation into the ischemic penumbra of MCAO model rats, mild hypothermia and Ubc9-overexpressing NSCs significantly reduced cerebral infarct areas and improved neurological function. In conclusion, this study demonstrated that global protein SUMOylation is an important molecular mechanism for NSCs to tolerate hypoxia, and mild hypothermia can further increase the degree of global SUMOylation to enhance the hypoxia tolerance of NSCs, which increases their survival during transplantation in situ and ability to perform nerve repair in the penumbra of cerebral infarction.
Crystalline Characteristic Effect of In Situ Interaction between ZnO and Pht on Inducing β Nucleation of Isotactic Polypropylene
Authors: Cheng Shuya , Zhang Kai , Xu Guomin , Shan Chunyan , He Min , Qin Shuhao , Yu Jie
Published: May 2022

The β-nucleating agent (β-NA), zinc phthalate (ZnPht), was prepared from a mixture of zinc oxide (ZnO) and phthalic anhydride (Pht) during the extrusion of isotactic polypropylene (iPP). To establish the relationship between the crystalline characteristic of ZnO and the crystallization of iPP, single-crystalline ZnO (ZnO(S)) and polycrystalline ZnO (ZnO(P)) were selected and mixed with Pht, respectively, to in situ inducing the β-crystal form of iPP (β-iPP). Compared to ZnO(S)/Pht, ZnO(P)/Pht has the selectivity of β-crystal nucleation during the crystallization of iPP; indeed, the relative content of β-crystal (

k

β

) improved from 18.0% for ZnO(S)/Pht/iPP to 84.6% for ZnO(P)/Pht/iPP. Moreover, the impact strength of the ZnO(P)/Pht/iPP was nearly 2.0 times greater than pure iPP; for ZnO(S)/Pht/iPP, it was approximately 1.4 times greater than pure iPP. To explain these phenomena, we propose a mechanism that the content of ZnPht generated by ZnO(P)/Pht is more than that of ZnO(S)/Pht during its in situ reaction; evidence from Fourier transform infrared spectroscopy, wide-angle X-ray diffraction, and thermogravimetric infrared spectroscope analysis was consistent with this mechanism. This study may provide a new perspective to control the crystal type of polymorphic polymer by adjusting the crystalline characteristic of the nucleating agent.
Spectral-Spatial Attention Transformer with Dense Connection for Hyperspectral Image Classification
Authors: Dang Lanxue , Weng Libo , Dong Weichuan , Li Shenshen , Hou Yane
Published: May 2022

In recent years, deep learning has been widely used in hyperspectral image (HSI) classification and has shown good capabilities. Particularly, the use of convolutional neural network (CNN) in HSI classification has achieved attractive performance. However, HSI contains a lot of redundant information, and the CNN-based model is limited by the receptive field of CNN and cannot balance the performance and depth of the model. Furthermore, considering that HSI can be regarded as sequence data, CNN-based models cannot mine sequence features well. In this paper, we propose a model named SSA-Transformer to address the above problems and extract spectral-spatial features of HSI more efficiently. The SSA-Transformer model combines a modified CNN-based spectral-spatial attention mechanism and a self-attention-based transformer with dense connection. The SSA-Transformer model can combine the local and global features of HSI to improve the performance of the model. A series of experiments showed that the SSA-Transformer achieved competitive classification accuracy compared with other CNN-based classification methods using three HSI datasets: University of Pavia (PU), Salinas (SA), and Kennedy Space Center (KSC).
3D Reconstruction and Intelligent Digital Conservation of Ancient Buildings Based on Laser Point Cloud Data
Authors: Qiu Yahui
Published: May 2022

With the wide application of computer technology, how to carry out digital modeling and virtual simulation for the protection of ancient buildings has become a new research field. The combination of LiDAR (LiDAR) point cloud data can significantly improve the performance of 3D spatial information extraction of buildings. To improve the level of ancient building conservation, this article uses LiDAR point cloud data to collect ancient building data, extracts 3D spatial location information from multisource remote sensing optical stereo images, restores 3D spatial structure information of buildings from LiDAR point cloud data, conducts optimized topology research work, jointly extracts 3D spatial information of buildings with structural constraints, and compares the collected data with the original data. The research results show that the traditional data collection method has a large error of about 10%, while the data collected by LiDAR (LiDAR) point cloud data in this article is close to the original data. The error is around 3%, which can well complete the 3D reconstruction and protection of ancient buildings.
Impact of Diversification on Bank Stability: Evidence from Emerging and Developing Countries
Authors: Adem Mohammed
Published: May 2022

As a result of the continual debate between portfolio optimization and the assumption of corporate strategy, it is debatable whether diversification enhances stability. This study examines the effect of diversification on bank stability by employing panel data representing 45 African nations between 2000 and 2020. Based on dynamic panel generalized moments techniques, the results support portfolio theory; diversification reduces risk and improves bank stability in emerging and developing economies during crisis and noncrisis periods. Bank diversification and stability have a quadratic association; overdiversification exposes banks to risk. The results also suggest that banks with a high interest margin, liquidity, and an increased cost‐to‐income ratio tend to become less stable. On the other hand, banks with higher leverage and operating in a country with country‐level solid corporate governance are more stable. GDP growth and inflation have a substantial influence on the financial health of banks. This research has significant repercussions for banks, policymakers, and academics aware of the impact of diversification on a bank’s risk and stability in emerging and developing markets.
Anticorrosive Effect of Halogenated Aniline Enaminoesters on Carbon Steel in HCl
Authors: Carlos Mariana F. P. , Barboza Geicy K. P. , Echevarria Aurea
Published: May 2022

Four enaminoesters derived from halogenated aniline, with potential anticorrosion activity, were synthesized and tested against carbon steel AISI 1020 in acid medium using 1.0 mol L-1 HCl. The synthesis was demonstrated through the reaction of ethyl acetoacetate with four different amines, in the presence of glacial acetic acid and molecular sieve, using ethanol as solvent for 24 h. The evaluation of the anticorrosive activity was performed using the gravimetric technique and electrochemical methods, such as electrochemical impedance spectroscopy (EIS), linear polarization resistance (LPR), and potentiodynamic polarization (PP). Results indicated that the F-EN (Ethyl (2Z)-3-[(4-fluoro-phenyl)-amino]-but-2-enoate) inhibitor had higher corrosion inhibition efficiency, of 98% by mass loss, and 85% by electrochemical techniques. Adsorption obeyed the Langmuir isotherm, thus suggesting that the inhibitors form a monolayer film in metal surface. These results also contributed to the calculations of the physicochemical parameters ofEa,△H≠ads, and△S≠ads, which confirmed the corrosion inhibition when compared to the absence of the inhibitors.
Clinical Factors of Blood Transfusion-Related Acute Lung Injury and Changes in Levels of Treg-Related Cytokines
Authors: Sun Lifang , Liu Yu
Published: May 2022

Objective. Analysis of clinical factors and changes in regulatory T cell (Treg)-related cytokine levels in transfusion-associated acute lung injury (TRALI). Methods. 62 patients who underwent blood transfusion and developed TRALI (TRALI group) in our hospital between January 2018 and December 2021 and 58 patients who did not develop TRALI (non-TRALI group) from blood transfusion were selected to collect clinical data from patients and construct a logistic regression model to analyze clinical risk factors for TRALI. Based on the prognosis of TRALI patients, they were divided into survival group (50 cases) and death group (12 cases), and serum CD4 + CD25 + Treg and Treg-related cytokines (interleukin 10 (IL-10), transforming growth factor-β (TGF-β)) levels were compared between the two groups, and the correlation between CD4 + CD25 + Treg and IL-10 and TGF-β was analyzed by Pearson. Results. The differences in smoking history, human leukocyte antigen (HLA) antibody II, pretransfusion shock, and CD4 + CD25 + Treg between the TRALI group and non-TRALI group were statistically significant (

P
<
0.05

). Logistic regression analysis showed that HLA antibody II and increased CD4 + CD25 + Treg were independent risk factors of TRALI (

P
<
0.05

). The levels of CD4 + CD25 + Treg, IL-10, and TGF-β in the death group were significantly higher than those in the survival group (

P
<
0.05

). CD4 + CD25 + Treg was positively correlated with levels of IL-10 and TGF-β (

P
<
0.05

). Conclusion. Elevated HLA antibody II and CD4 + CD25 + Treg are the main clinical risk factors for TRALI, and CD4 + CD25 + Treg may be involved in immunosuppression by increasing the expression levels of IL-10 and TGF-β. Early clinical monitoring of changes in Treg-related cytokine levels can provide some guidance for prognostic assessment of TRALI patients.
Identification of Hub Genes Associated with Nonspecific Orbital Inflammation by Weighted Gene Coexpression Network Analysis
Authors: Liu Hanhan , Chen Lu , Lei Xiang , Ren Hong , Li Gaoyang , Deng Zhihong
Published: May 2022

Background. Nonspecific orbital inflammation is a common ophthalmopathy with a high prevalence among adult females. Yet, its molecular mechanisms behind are poorly understood. Regulation of gene expression probably plays an important role in this disease. Thus, we utilized gene coexpression networks to identify key modules and hub genes involved in nonspecific orbital inflammation. Methods. Data of gene expression in nonspecific orbital inflammation samples (

n
=
61

) and healthy samples (

n
=
28

) were obtained from the public Gene Expression Omnibus database. Afterward, differentially expressed genes were performed. Then, weighted correlation network analysis was done to define the key modules. Next, functional enrichment analysis was conducted by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway in key modules. Finally, a protein-protein interaction network and Cytohubba plugin were used to screen hub genes. Results. Differential expression of 716 genes was identified, among which 169 genes were upregulated and 547 genes were downregulated in the nonspecific orbital inflammation group. In weighted correlation network analysis, we clarified 2 key modules (MEturquoise and MEblue) that are likely to play key roles in nonspecific orbital inflammation. Functional enrichment analysis indicated that these genes are predominately involved in immune response and matrix homeostasis. In addition, among 2 key modules, there are 20 hub genes identified. Conclusion. With this new approach, we identified several genes that could be critical to pathologies of nonspecific orbital inflammation. These findings may contribute to further therapeutic target development.
Exosomal CXCL14 Contributes to M2 Macrophage Polarization through NF-κB Signaling in Prostate Cancer
Authors: Tian Hong-Yang , Liang Qi , Shi Zhen , Zhao Hang
Published: May 2022

Chemokine (C-X-C motif) ligand 14 (CXCL14) plays a critical role in maintaining homeostasis and inflammation in the local cell environment and regulating cancer progression. However, the role of CXCL14 in prostate cancer (PC) has not been fully investigated. In this study, the expression of CXCL14 was determined in PC tumor tissues by qRT-PCR and immunohistochemistry assay. Wound healing, invasion, colony formation, cell proliferation, and apoptosis assays were performed to evaluate the role of CXCL14 in PC progression. Exosomes were isolated from PC cell-condition medium by using ultracentrifugation assay and identified by using transmission electron microscopy and nanoparticle tracking analysis. M2 macrophage polarization-associated genes were measured by using qRT-PCR and Western blot assays. A PC xenograft mouse model was used to assess the role of CXCL14 in tumor growth in vivo. The results showed that CXCL14 was significantly upregulated in PC tissues and was positively correlated with pathological stages, lymph node metastasis, and angiolymphatic invasion. The positive correlations were also observed between CXCL14 and PD-L1 and IL-10. Knockdown CXCL14 dramatically inhibited PC cell proliferation, invasion, and colony formation, but not apoptosis. CXCL14 promoted M2 macrophage polarization through the NF-κB signaling pathway and exosome-mediated mechanism. Moreover, CXCL14 knockdown inhibited tumor growth in vivo. Taken together, exosomal CXCL14 promoted M2 macrophage polarization through the NF-κB signaling pathway and contributed to PC progression.
A Study of Engine Intake Noise Control Based on the Improved Filtered-x Least Mean Square Algorithm
Authors: Lan Chaofeng , Zhang Lei , Lv Shou , Jiang Pengwei
Published: May 2022

To reduce the intake noise of automobile engines, an active control system model of engine intake noise is established with the Filtered-x least mean square (FxLMS) algorithm. The offline identification method is adopted to identify the secondary path. The engine speed signal is used to construct the reference signal of a sound source to avoid interference of a secondary sound source to the reference signal. A variable-step algorithm is proposed, in which parameters are added to the normalized algorithm instead of the sinusoidal variable-step algorithm to adjust the amplitude range. This algorithm not only has the advantages of fast convergence speed and small steady-state error but also adapts to the characteristics of a time-varying reference signal and easy selection of parameters. In this paper, the noise of automobile engines under the New European Driving Cycle (NEDC) is studied and the proposed algorithm has faster convergence speed compared with the normalization algorithm, better adaptability to the change of the reference signal, and better stability compared with the sinusoidal variable step-size algorithm. The results show that the algorithm proposed can effectively reduce the intake noise of the engine at each speed and the noise reduction effect can reach 23.11 dB at a certain frequency. Meanwhile, the stability of the system is improved.
Intelligent Supply Chain and Logistics Route Optimization Algorithm in Wireless Sensor Network
Authors: Ma Zhijun , Yang Xiaobei , Li Huahui
Published: May 2022

This article first proposes the design of the ZigBee wireless sensor network node based on Arduino, from the design and implementation of the node hardware system to the design and implementation of the node software system, and expands on the design details. The node function was applied to the node design environment, and simulation tests were performed, and execution was tested to confirm the feasibility and practicability of the design. Based on this, the article proposes the service construction process of the software and hardware platform of the smart supply chain system, and then clarifies the basic mathematical problem of the distribution plan in line with the service strategy, that is, “the logistics route optimization algorithm with capacity and time constraint optimization,” which aims to study statically design, define, and model, and test two precise solutions representing heuristic genetic algorithms and analyze their results. In addition, additional hardware such as smart supply chain and cabinet boards are tested and designed according to system requirements, and the interaction mechanism is adapted to the user interface and supporting structure design so as to ensure the completion of user-related business processes. Combining the existing theoretical knowledge, the first priority is to meet customer needs, build a smart supply chain model under the premise of on-time delivery, and solve the model in time. Based on this point, this article tries to use hybrid branch algorithm link and tabu search algorithm to increase the consideration of traffic conditions, collect accurate algorithms, and modern heuristic algorithms to solve the actual situation of the case. At the end, the article proposes some related issues for the above problems. Suggesting through the research of wireless sensor network, this paper applies it to the research of intelligent supply chain and logistics route optimization algorithm and promotes the development of more intelligent supply chain in the future.
Porous Carbons Derived from Desiliconized Rice Husk Char and Their Applications as an Adsorbent in Multivalent Ions Recycling for Spent Battery
Authors: Sun Yating , Su Geng , He Zhaocai , Wei Yuan , Hu Jinbo , Liu Huaifei , Liu Gonggang
Published: May 2022

Recycling of spent lithium-ion batteries (LIBs) has attracted increasing attentions recently on account of continuous growth demand for corresponding critical metals/materials and environmental requirement of solid waste disposal. In this work, rice husk as one of the most abundant renewable fuel materials in the world was used to prepare rice husk char (RC) and applied to recycle multivalent ions in waste water from hydrometallurgical technology dispose of spent LIBs. Rice husk char with specific surface area and abundant pores was obtained via pickling and desilication process (DPRC). The structural characterization of the obtained rice husk char and its adsorption capacity for multivalent ions in recycled batteries were studied. XRD, TEM, SEM, Raman, and BET were used for the characterization of the raw and the modified samples. The results show rice husk chars after desilication has more flourishing pore structure and larger pore size about 50–60 nm. Meanwhile, after desilication, the particle size of rice husk char decreased to 31.392 μm, and the specific surface area is about 402.10 m2/g. Its nitrogen adsorption desorption curve (BET) conforms to the type IV adsorption isotherm with H3 hysteresis ring, indicating that the prepared rice husk char is a mesoporous material. And the adsorption capacity of optimized DPRC for Ni, Co, and Mn ions is 7.00 mg/g, 4.84 mg/g, and 2.67 mg/g, respectively. It also demonstrated a good fit in the Freundlich model for DPRC-600°C, and a possible adsorption mechanism is proposed. The study indicates biochar materials have great potential as an adsorbent to recover multivalent ions from spent batteries.
Analysis of the Adult Education Policy Initiatives in Ethiopia: Implications for Policy Reconsideration
Authors: Abate Samuel Getnet
Published: May 2022

Using a qualitative research approach, this article analyzes the adult education policy initiatives in Ethiopia as of 1994. The data were collected from nine adult education professionals/officers who are working at regional-, zonal-, and district-level education offices through in-depth interviews and official documents. The results indicated that the adult education initiatives of the country lack consistency and clarity and affected the practice of adult education. The National Adult Education Strategy (NAES) and its implementation guideline lack a clear framework for stakeholders to collaborate effectively in the provision of the program. Moreover, different policy issues such as partnership, coordination mechanisms, communication strategy, funding, innovation, and monitoring and evaluation were rarely considered in the implementation of the policy. Therefore, for effective adult education provision, a clear adult education policy and greater synergy between policies and practices must be in place.
Numerical Investigation of an Anisotropic Permeability Model for Bedded Coal Based on the Equivalent Fracture Aperture Coefficient
Authors: Qi Xianyin , Fu Peng , Wang Shengwei
Published: May 2022

Permeability evaluation of bedded coal is always a difficult problem, thereby an improved permeability model is established based on the equivalent fracture aperture coefficient. The equivalent fracture aperture coefficient can reflect the anisotropy of coal in mechanical and seepage properties. This model is executed into COMSOL Multiphysics to perform numerical simulations. The evolutions of permeability, gas pressure, and cumulative gas production on three typical boundary conditions are investigated. Our simulation results show that this model is competent to represent evolution of anisotropic permeability in bedded coal during gas production, which is governed by the competitive effects of desorption and effective stress. Under the same boundary conditions, different equivalent fracture aperture coefficients lead to significantly different trends in anisotropic permeability evolution. Anisotropic permeability changes with gas pressure and time during production, and the magnitude of change depends on both the equivalent fracture aperture coefficient and applied boundary conditions. Our model shows that the bedding characteristics of permeability have a significant effect on gas production forecasts.
Effect of Narrative Nursing Combined with Thinking Map Health Education on Parturient Self-Efficacy and Neonatal Nursing Ability
Authors: Wang Yan , Xu Yan , Li Jingjing
Published: May 2022

The motivation behind this study is to explore the influence of narrative nursing combined with thinking map health education on parturient self-efficacy and neonatal nursing ability. To verify this claim, we have selected 60 parturients who were treated in the hospital from February 2019 to April 2021. Moreover, these patients were randomly assigned to control and study groups. The former received narrative nursing, and the latter received narrative nursing combined with thinking map health education. The nursing satisfaction, maternal and neonatal nursing ability, maternal health knowledge awareness score, maternal self-efficacy, anxiety, and depression scores were compared. Initially, we have compared the nursing satisfaction: in the study group, 22 cases were satisfied, 8 cases were basically satisfied, and 0 cases were dissatisfied, and the satisfaction rate was 100.00%; in the control group, 12 cases were satisfied, 14 cases were basically satisfied, and 4 cases were dissatisfied, and the satisfaction rate was 86.67%. The nursing satisfaction in the study group was higher compared to the control group (

P
<
0.05

). Secondly, we compared the mastery of neonatal nursing ability. The study group mastered the relevant knowledge of neonatal nursing in 23 cases, basically mastered 6 cases, and did not master 1 case, with a mastery rate of 96.67%. The control group mastered the knowledge of neonatal nursing in 12 cases, basically mastered 10 cases, and did not master 8 cases with a mastery rate of 73.33%. In the comparison between the two groups, the mastery of neonatal nursing ability in the study group was higher compared to the control group (

P
<
0.05

). Considering the scores of maternal health knowledge, the scores of neonatal basic nursing, physiological characteristics, breastfeeding methods, environmental nursing knowledge, vaccination, and physical examination requirements in the study group were higher compared to the control group (

P
<
0.05

). In the comparison of maternal self-efficacy, the total scores for promoting development, health care, safety, feeding, and self-efficacy in the study group were significantly higher compared to the control group (

P
<
0.05

). Finally, we compared the scores for anxiety and depression. Before nursing, there exhibited no significant difference (

P
>
0.05

). After nursing, the anxiety and depression scores decreased. Furthermore, the anxiety and depression scores of the study group were lower compared to the control group (

P
<
0.05

). In the health education of primary parturient, the adoption of narrative nursing combined with thought guiding schema can enhance the level of nursing satisfaction and self-efficacy, strengthen the nursing ability of primiparas and the awareness rate of health knowledge, and reduce the occurrence of a maternal bad mood, which is more in line with the requirements of parturient.
Enhancement of Detection of Diabetic Retinopathy Using Harris Hawks Optimization with Deep Learning Model
Authors: Gundluru Nagaraja , Rajput Dharmendra Singh , Lakshmanna Kuruva , Kaluri Rajesh , Shorfuzzaman Mohammad , Uddin Mueen , Rahman Khan Mohammad Arifin
Published: May 2022

In today’s world, diabetic retinopathy is a very severe health issue, which is affecting many humans of different age groups. Due to the high levels of blood sugar, the minuscule blood vessels in the retina may get damaged in no time and further may lead to retinal detachment and even sometimes lead to glaucoma blindness. If diabetic retinopathy can be diagnosed at the early stages, then many of the affected people will not be losing their vision and also human lives can be saved. Several machine learning and deep learning methods have been applied on the available data sets of diabetic retinopathy, but they were unable to provide the better results in terms of accuracy in preprocessing and optimizing the classification and feature extraction process. To overcome the issues like feature extraction and optimization in the existing systems, we have considered the Diabetic Retinopathy Debrecen Data Set from the UCI machine learning repository and designed a deep learning model with principal component analysis (PCA) for dimensionality reduction, and to extract the most important features, Harris hawks optimization algorithm is used further to optimize the classification and feature extraction process. The results shown by the deep learning model with respect to specificity, precision, accuracy, and recall are very much satisfactory compared to the existing systems.
Sports Risk Analysis Based on Knowledge Discovery and Data Driven
Authors: Zheng Jinling , Fan Chunyan
Published: May 2022

Sports have gradually gained popularity, and the risks associated with them have risen as well. In today’s world, college students are a diverse population, and sports are very popular among them. The construction of sports risk assessment system in ordinary colleges is significant to improve physical quality of college students and ensure safety. College sports accidents have occurred on occasion in recent years, causing not only enormous pain to students and parents, but also casting a dark shadow over the sport. This work takes the risk analysis of college students’ sports as the background, and uses a data-driven neural network to conduct knowledge discovery of college sports threats. It evaluates the sports risks of college students’ physical education, and builds an index system of sports risk assessment in ordinary colleges and universities, which provides a certain basis for avoiding and reducing sports risks. This work studies an end-to-end one-dimensional convolutional neural network algorithm for risk assessment of college sports. In order to extract complementary structures in different scales, a multi-scale fusion framework is constructed using convolution kernels of diverse sizes. In this paper, the residual network structure is introduced to deepen and improve the network, and an attention module suitable for one-dimensional residual network is designed. It is embedded into the residual module to construct a multi-scale attention residual network (MSAR) model. Finally, validity and superiority of proposed model are verified by experimental data, which can effectively evaluate the sports risk of college students.
Research on Nonlinear Associations and Interactions for Short-Distance Travel Mode Choice of Car Users
Authors: He Mingwei , Pu Lijuan , Liu Yang , Shi Zhuangbin , He Chengfeng , Lei Jiayou
Published: May 2022

Encouraging car users who travel short distances to shift from car mode to active travel modes can effectively alleviate urban traffic congestion and reduce carbon emissions. However, few studies have examined the determinants of the travel mode choice of short-distance car users and ignored the nonlinear associations and interactions between variables. This paper conducts a questionnaire survey to investigate the short-distance travel mode choice of car users who travel less than 4 km in a specific city. A random forest (RF) model is applied to examine the influence of key variables on these three travel mode choices of short-distance car users and to explore the nonlinear associations and interactions of the variables. Compared with multinomial logic model, the results of RF show that significant threshold effects exist in the relationship between the car user’s travel mode choice and the selected explanatory variables, mainly travel distance, road network density, distance to CBD, and number of bus stops. In particular, 1.2 km is a critical turning point for car and active travel mode choice, before which car users prefer to travel by walking and cycling and after which there is a significant increase in the car use probability. When the road network density was between 2.5 km/km2 and 6.5 km/km2, the proportion of car users who chose cycling showed an increasing trend, while car use showed a decreasing trend. These findings can provide a solid basis for planning managers to develop policy measures to encourage environmentally sustainable travel.
Bone Mesenchymal Stem Cell-Derived Exosome-Enclosed miR-181a Induces CD4+CD25+FOXP3+ Regulatory T Cells via SIRT1/Acetylation-Mediated FOXP3 Stabilization
Authors: Wang Renyong , Li Ruixue , Li Tiehan , Zhu Lei , Qi Zongze , Yang Xiaokui , Wang Huan , Cao Baoquan , Zhu Hong
Published: May 2022

Bone marrow mesenchymal stem cells (BMSCs) have been identified as a potential therapeutic approach to immune-related diseases. Here, we show that BMSC-derived exosomes promote FOXP3 expression and induce the conversion of CD4+ T cells into CD4+CD25+FOXP3+ Treg cells, which is significant for immunosuppressive activity. We found that miR-181a-5p is upregulated in BMSC-derived exosomes and can be transferred to CD4+ T cells. In CD4+ cells, miR-181a directly targets SIRT1 and suppresses its expression. Moreover, downregulated SIRT1 enhances FOXP3 via protein acetylation. In conclusion, our data demonstrated that BMSC-derived exosomal miR-181a is critical in the maintenance of immune tolerance. Furthermore, our results reveal that BMSC-derived exosomal miR-181a induces the production of CD4+CD25+FOXP3+ Treg cells via SIRT1/acetylation/FOXP3.
Practice and Research of Blended Learning Model Guided by Deep Learning Model
Authors: Yang Fan , Rao Yutai
Published: May 2022

An innovative approach to education and teaching, with a deeper integration of teaching and learning through a deeper mix of learning and study was proposed. The new organisational format combines independent learning in the form of microlessons and flipped classrooms with communication and cooperation in forums. In the context of the rapid development of Internet + education, big data information technology, and the accelerated promotion of education informatization by the Ministry of Education, this paper studies how to use the blended learning model to achieve the deep integration of information technology and classroom teaching through the innovative form of “microlesson and flipped classroom,” so as to improve students’ independent learning ability. Taking the university course of dynamic web design as an example, this course aims to achieve the teaching objectives of this course by using a deep learning model to guide the deep integration of information technology and classroom in a blended learning mode.
Bushen Huoxue Formula Modulates Autophagic Flux and Inhibits Apoptosis to Protect Nucleus Pulposus Cells by Restoring the AMPK/SIRT1 Pathway
Authors: Gao Shang , Li Nianhu , Chen Renchang , Su Youxiang , Song Yun , Liang Songlin
Published: May 2022

Background. Low back pain (LBP) has the characteristics of chronic and persistence, which is a heavy social burden. Intervertebral disc degeneration (IVDD) is a major cause of LBP. The typical features of IVDD are extracellular matrix (ECM) degradation and nucleus pulposus cell (NP) apoptosis. Bushen Huoxue Formula (BSHXF) has good clinical effects on LBP. However, the mechanism of BSHXF affecting ECM and NP cells is still unclear. Aim of the Study. In this study, the impact of BSHXF on autophagy and apoptosis of NP cells was studied through the AMPK/SIRT1 pathway. Material and Methods. NP cells were extracted through the digestion of collagenase and trypsin, and the components of BSHXF were identified. Cell Counting Kit‐8 was applied to detect the impact of BSHXF on NP cells. Mitochondrial function was detected using MitoTracker assay, ATP kit, and SOD kit. Autophagy and apoptosis were detected by RT‐qPCR, western blotting, and flow cytometry. Results. BSHXF promoted NP cell survival in a concentration‐dependent manner, and the elimination of rat serum did not increase cell proliferation; TNF‐α accelerated ECM degradation, ROS accumulation, and NP cell apoptosis and decreased autophagic flux. BSHXF restored mitochondrial function and autophagic flux. In addition, AMPK/SIRT1 pathway activation was associated with IVDD. Conclusions. BSHXF regulates autophagy and enhances autophagic flux to suppress excessive ROS production and restore mitochondrial function in an AMPK/SIRT1‐dependent manner. However, the protection of BSHXF on TNF‐α‐treated cells was eliminated by 3‐MA. Furthermore, the protective impact of BSHXF on ECM degradation and apoptosis induced by TNF‐α was restrained by an AMPK inhibitor. Therefore, maintaining the proper autophagy illustrates treatment strategy for IVDD.
The Effect of Psychological Support Intervention Based on Structure-Process-Result Three-Dimensional Quality Assessment on Maternal Role Adaptation and Pelvic Floor Rehabilitation Exercise Compliance of Women in Spontaneous Labor
Authors: Wang Lichun , Shi Lu , Wang Lijun , Wu Yan , Zhang Xiaohong , Chen Tuo , Huo Congmin
Published: May 2022

Objective. A case-control study was conducted to explore the effect of psychological support intervention based on structure-process-result three-dimensional quality assessment on maternal role adaptation and pelvic floor rehabilitation exercise compliance. Methods. 110 parturients who delivered naturally in our hospital from January 2019 to October 2021 were randomly divided into the control group and the study group. Patients in the former group received routine nursing measures, while patients in the latter group received psychological support intervention based on structure-process-outcome three-dimensional quality assessment (intervention group). Psychological intervention measures include health education, cognitive therapy, behavioral therapy, collective psychological intervention, and happiness therapy. The Edinburgh postpartum depression (PPD) scale and general self-efficacy scale were adopted before intervention, on the day of discharge, and 42 days after delivery. Meanwhile, the mother’s role adaptation questionnaire was adopted 42 days after delivery. The PPD, the change of self-efficacy, the function of the pelvic floor, the role adaptation of mothers, and the compliance of pelvic floor rehabilitation exercise in the control group and the intervention group were analyzed. Results. There was a significant difference in the EPDS score between the two groups at 42 days after delivery. There was a significant difference in the incidence of depression 42 days after delivery between the two groups (

P
<
0.05

). The score of pelvic floor function in the two groups after intervention was higher than that before intervention, and that in the intervention group was higher than that in the control group (

P
<
0.05

). The score of self-efficacy in the two groups after intervention was higher than that before intervention, and that in the intervention group was higher than that in the control group (

P
<
0.05

). The role adaptation of mothers in the intervention group was better than that in the control group (

P
<
0.05

). The compliance rate of pelvic floor rehabilitation exercise in the intervention group was higher than that in the control group (

P
<
0.05

). Conclusion. Psychological support intervention based on structure-process-result three-dimensional quality assessment can effectively enhance the sense of self-efficacy, pelvic floor function, maternal role adaptation, and pelvic floor rehabilitation exercise compliance of parturients and can effectively reduce the incidence of PPD and play a positive role in the prevention of PPD.
Human Leukocyte Antigen (HLA) System: Genetics and Association with Bacterial and Viral Infections
Authors: Medhasi Sadeep , Chantratita Narisara
Published: May 2022

The human leukocyte antigen (HLA) system is one of the most crucial host factors influencing disease progression in bacterial and viral infections. This review provides the basic concepts of the structure and function of HLA molecules in humans. Here, we highlight the main findings on the associations between HLA class I and class II alleles and susceptibility to important infectious diseases such as tuberculosis, leprosy, melioidosis, Staphylococcus aureus infection, human immunodeficiency virus infection, coronavirus disease 2019, hepatitis B, and hepatitis C in populations worldwide. Finally, we discuss challenges in HLA typing to predict disease outcomes in clinical implementation. Evaluation of the impact of HLA variants on the outcome of bacterial and viral infections would improve the understanding of pathogenesis and identify those at risk from infectious diseases in distinct populations and may improve the individual treatment.
Impact of Technical Indicators and Leading Indicators on Stock Trends on the Internet of Things
Authors: Chen Chien-Ming , Gong Yuxiao , Wu Jimmy Ming-Tai
Published: May 2022

The Internet of things (IoT) has had an enormous impact on the financial industry. With IoT, people can obtain real-time financial information; moreover, investment and financial management have become more flexible and diverse. Because of their high returns and strong liquidity, stocks have become essential commodities through which people invest and manage money. However, high returns are often associated with high risks. Therefore, it is important for investors to forecast the trends of future stock prices. This study uses a new stock trend prediction framework to predict changes in the stock price direction on the next trading day using data from the past 30 trading days. This framework uses two-dimensional convolutional neural networks to classify stock prices into three categories: up, down, and flat. In addition, to analyze the influence of different types of input on the prediction model, historical data, futures, options, technical indicators, and mixed data are taken as the model’s input. Experiments on US and Taiwan stocks proved the validity of the prediction model. The method proposed in this study is compared with buy-and-hold and random choice trading strategies. Results show that the model’s profitability is better than the two baseline strategies.
Risk Factors for Fracture in Patients with Coexisting Chronic Kidney Disease and Type 2 Diabetes: An Observational Analysis from the CREDENCE Trial
Authors: Young Tamara K. , Toussaint Nigel D. , Di Tanna Gian Luca , Arnott Clare , Hockham Carinna , Kang Amy , Schutte Aletta E. , Perkovic Vlado , Mahaffey Kenneth W. , Agarwal Rajiv , Bakris George L. , Charytan David M. , Heerspink Hiddo J. L. , Levin Adeera , Pollock Carol , Wheeler David C. , Zhang Hong , Jardine Meg J.
Published: May 2022

Background. The fracture pathophysiology associated with type 2 diabetes and chronic kidney disease (CKD) is incompletely understood. We examined individual fracture predictors and prediction sets based on different pathophysiological hypotheses, testing whether any of the sets improved prediction beyond that based on traditional osteoporotic risk factors. Methods. Within the CREDENCE cohort with adjudicated fracture outcomes, we assessed the association of individual factors with fracture using Cox regression models. We used the Akaike information criteria (AIC) and Schwartz Bayes Criterion (SBC) to assess six separate variable sets based on hypothesized associations with fracture, namely, traditional osteoporosis, exploratory general population findings, cardiovascular risk, CKD-mineral and bone disorder, diabetic osteodystrophy, and an all-inclusive set containing all variables. Results. Fracture occurred in 135 (3.1%) participants over a median 2.35 [1.88–2.93] years. Independent fracture predictors were older age (hazard ratio [HR] 1.04, confidence interval [CI] 1.01–1.06), female sex (HR 2.49, CI 1.70–3.65), previous fracture (HR 2.30, CI 1.58–3.34), Asian race (HR 1.74, CI 1.09–2.78), vitamin D therapy requirement (HR 2.05, CI 1.31–3.21), HbA1c (HR 1.14, CI 1.00–1.32), prior cardiovascular event (HR 1.60, CI 1.10–2.33), and serum albumin (HR 0.41, CI 0.23–0.74) (lower albumin associated with greater risk). The goodness of fit of the various hypothesis sets was similar (AIC range 1870.92–1849.51, SBC range 1875.60–1948.04). Conclusion. Independent predictors of fracture were identified in the CREDENCE participants with type 2 diabetes and CKD. Fracture prediction was not improved by models built on alternative pathophysiology hypotheses compared with traditional osteoporosis predictors.
Efficacy of Low-Dose Aspirin in Colorectal Cancer Risk Prevention is Dependent onADH1BandALDH2Genotype in Japanese Familial Adenomatous Polyposis Patients
Authors: Mure Kanae , Ishikawa Hideki , Mutoh Michihiro , Horinaka Mano , Otani Takahiro , Suzuki Sadao , Wakabayashi Keiji , Sakai Toshiyuki ,   J-FAPP Study IV group, Sato Yasushi , Doyama Hisashi , Tajika Masahiro , Tanaka Shinji , Horimatsu Takahiro , Takeuchi Yoji , Kashida Hiroshi , Tashiro Jun , Ezoe Yasumasa , Nakajima Takeshi , Ikematsu Hiroaki , Hori Shinichiro , Takayama Tetsuji , Ohda Yoshio
Published: May 2022

Aspirin has gained great attention as a cancer preventive agent. Our previous study revealed that the low-dose aspirin prevents colorectal tumor recurrence in Japanese patients with colorectal adenomas and/or adenocarcinomas, whereas aspirin increases risks in smokers and has no effects on regular drinkers. Our recent study revealed that aspirin reduces polyp growth in Japanese patients with familial adenomatous polyposis (FAP). In this study, we have studied the association of genotypes of alcohol metabolizing enzymes (ADH1B and ALDH2) on aspirin's efficacy of suppressing polyp growth (≥5 mm) in a total of 81 Japanese patients with FAP. Our study revealed that aspirin showed significant preventive effects for patients with ADH1B-AA and AA+GA types [OR = 0.21; 95% confidence interval (CI), 0.05–0.95, and OR = 0.31; 95% CI, 0.10–0.95, respectively], and for patients with ALDH2-GG and GG+GA types (OR = 0.10; 95% CI, 0.01–0.92, and OR = 0.29; 95% CI, 0.09–0.94, respectively), but not for patients with ADH1B-GG and GA+GG types, and ALDH2-AA and GA+AA types. In addition, substantial preventive effects of aspirin were seen for patients with ADH1B-AA type who do not drink regularly (<3 times/week, OR = 0.11; 95% CI, 0.02–0.78), where a statistically significant interaction between aspirin and ADH1B was observed (Pinteraction = 0.036). Results from this exploratory study strongly indicate that aspirin is beneficial in prevention of polyp growth for patients with FAP with ADH1B-AA and AA+GA types, and ALDH2-GG and GG+GA types. Taken together, we propose ADH1B and ALDH2 as candidate markers for the personalized prevention by aspirin.

Significance:

Aspirin is beneficial to patients with FAP with ADH1B-AA and AA+GA types or ALDH2-GG and GG+GA types. ADH1B and ALDH2 genotypes can be the markers for the personalized prevention of colorectal cancer by aspirin.
Aneurismas intracranianos: epidemiologia e análise morfológica por angiografia digital
Authors: Molina Gabriela Modulo , Figueira Gabriel de Pontes , Paiva Narayana Silva , Hidalgo Raquel Cristina Trovo , Batigália Fernando
Published: May 2022

Introdução: Aneurismas intracranianos (AIC) são dilatações vasculares de elevada prevalência que podem ser identificadas por angiotomografia, angiorressonância e por angiografia de subtração digital (ASD), exame considerado padrão-ouro. Para AIC não rotos, ainda inexiste consenso absoluto sobre padronização de conduta terapêutica, que depende, intrinsecamente, de aspectos morfológicos e topográficos ao exame angiográfico. Objetivo: Analisar características epidemiológicas, morfológicas e topográficas de AIC não rotos identificados por ASD e as correlacionar com fatores de risco. Método: Foram considerados 160 prontuários eletrônicos de pacientes com AIC não rotos diagnosticados por ASD entre 2014 e 2018. Variáveis consideradas foram aspectos epidemiológicos (gênero, idade e grupo étnico), morfológicos (formato, presença ou ausência de colo e tamanho), topografia, número de AIC por paciente e fatores de risco (hipertensão arterial sistêmica, tabagismo e etilismo), com análise estatística por correlação de Spearman. Resultados: De 160 pacientes, avaliaram-se 207 AIC não rotos. Houve predomínio do sexo feminino, da faixa etária de 60 a 69 anos e da etnia branca. Em relação a fatores de risco, 58,75% apresentavam hipertensão arterial sistêmica. A maioria dos pacientes apresentava um único aneurisma, e a localização mais prevalente foi artéria carótida interna direita. Predominaram aneurismas saculares, pequenos (menor que 7 mm) e de colo largo. Demonstrou-se correlação estatística entre tamanho e localização (p < 0,001), tamanho e tipo de colo (p = 0,0005) e entre formato e tipo de colo (p < 0,001). Conclusão: Houve prevalência de AIC não rotos em indivíduos do sexo feminino de meia idade, brancos e hipertensos, com predomínio de aneurisma sacular não lobulado, único, pequeno, de colo largo em artéria carótida interna direita. Presença de correlação estatística de AIC sacular com colo largo, AIC gigante em artéria carótida interna, e de AIC pequeno com colo largo.