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  1. Article ; Online: A Bayesian network perspective on neonatal pneumonia in pregnant women with diabetes mellitus

    Yue Lin / Jia Shen Chen / Ni Zhong / Ao Zhang / Haiyan Pan

    BMC Medical Research Methodology, Vol 23, Iss 1, Pp 1-

    2023  Volume 12

    Abstract: Abstract Objective To predict the influencing factors of neonatal pneumonia in pregnant women with diabetes mellitus using a Bayesian network model. By examining the intricate network connections between the numerous variables given by Bayesian networks ( ...

    Abstract Abstract Objective To predict the influencing factors of neonatal pneumonia in pregnant women with diabetes mellitus using a Bayesian network model. By examining the intricate network connections between the numerous variables given by Bayesian networks (BN), this study aims to compare the prediction effect of the Bayesian network model and to analyze the influencing factors directly associated to neonatal pneumonia. Method Through the structure learning algorithms of BN, Naive Bayesian (NB), Tree Augmented Naive Bayes (TAN), and k-Dependence Bayesian Classifier (KDB), complex networks connecting variables were presented and their predictive abilities were tested. The BN model and three machine learning models computed using the R bnlean package were also compared in the data set. Results In constraint-based algorithms, three algorithms had different presentation DAGs. KDB had a better prediction effect than NB and TAN, and it achieved higher AUC compared with TAN. Among three machine learning modes, Support Vector Machine showed a accuracy rate of 91.04% and 67.88% of precision, which was lower than TAN (92.70%; 72.10%). Conclusion KDB was applicable, and it can detect the dependencies between variables, identify more potential associations and track changes between variables and outcome.
    Keywords Bayesian networks ; Neonatal pneumonia ; Naive Bayes network ; Tree Augmented Naive Bayes model ; K-Dependence Bayesian Classifier ; Medicine (General) ; R5-920
    Subject code 006
    Language English
    Publishing date 2023-10-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Impact of the cytotoxic T-lymphocyte associated antigen-4 rs231775 A/G polymorphism on cancer risk

    Haiyan Pan / Zebin Shi / Lei Gao / Li Zhang / Shuzhang Wei / Yin Chen / Chao Lu / Jianzhong Wang / Li Zuo / Lifeng Zhang

    Heliyon, Vol 9, Iss 12, Pp e23164- (2023)

    2023  

    Abstract: Background: Cytotoxic T-lymphocyte associated antigen-4 (CTLA-4) is an immunosuppressive checkpoint that is involved in the development and metastasis of cancers. Several studies revealed that CTLA-4 rs231775A/G polymorphism may be associated with the ... ...

    Abstract Background: Cytotoxic T-lymphocyte associated antigen-4 (CTLA-4) is an immunosuppressive checkpoint that is involved in the development and metastasis of cancers. Several studies revealed that CTLA-4 rs231775A/G polymorphism may be associated with the risk of cancer in some populations, but the conclusions of these studies are not consistent. Methods: We conducted a pooled analysis with eligible studies to explore the association between the CTLA-4 rs231775 variant and cancer risk. Additionally, we used in silico tools to evaluated the expression of CTLA-4 on urinary system cancer. Moreover, we adopted the enzyme-linked immunosorbent assay (ELISA), and Gene Set Enrichment Analysis (GSEA) to investigate the effects of CTLA-4 on bladder cancer (BLCA). Results: In total, 92 case-control studies involving 29,987 patients with cancer and 36,484 healthy individuals (controls) were included in the pooled analysis. In the stratified analysis based on cancer type, the rs231775 A/G polymorphism was associated with increased bladder cancer risk in the heterozygote contrast model (OR = 1.23, 95% CI = 1.01–1.51, P = 0.040). The race-stratified analysis revealed that East Asians with the GG genotype had a 12% lower risk of developing cancer than those with the GA + AA genotype (95% CI = 0.81–0.95, P = 0.001). The in silico analysis showed that CTLA-4 expression was augmented in patients with BLCA. The ELISA results revealed that CTLA-4 expression was reduced in patients with BLCA carrying the AA genotype. Several signaling pathways, including cytokine-cytokine receptor interactions and T-cell receptor signaling, were associated with CTLA-4 expression. Conclusion: The CTLA-4 rs231775 A/G polymorphism is associated with cancer risk in East Asian population. This polymorphism is especially associated with BLCA.
    Keywords Cancer ; CTLA-4 ; Variant ; Analysis ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
    Subject code 616
    Language English
    Publishing date 2023-12-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Updating of Land Cover Maps and Change Analysis Using GlobeLand30 Product

    Haiyan Pan / Xiaohua Tong / Xiong Xu / Xin Luo / Yanmin Jin / Huan Xie / Binbin Li

    Remote Sensing, Vol 12, Iss 3147, p

    A Case Study in Shanghai Metropolitan Area, China

    2020  Volume 3147

    Abstract: Accurate land cover mapping and change analysis is essential for natural resource management and ecosystem monitoring. GlobeLand30 is a global land cover product from China with 30 m resolution that provides reliable data for many international ... ...

    Abstract Accurate land cover mapping and change analysis is essential for natural resource management and ecosystem monitoring. GlobeLand30 is a global land cover product from China with 30 m resolution that provides reliable data for many international scientific programs. Few studies have focused on systematically implementing this global land cover product in regional studies. Therefore, this paper presents an object-based extended change vector analysis (ECVA_OB) and transfer learning method to update the reginal land cover map using GlobeLand30 product. The method is designed to highlight small and subtle changes through the concept of uncertain area analysis. Updating is carried out by classifying changed objects using a change-detection-based transfer learning method. Land cover changes are analyzed and the factors affecting updating results are explored. The method was tested with data from Shanghai, China, a city that has experienced significant changes in the past decade. The experimental results show that: (1) the change detection and classification accuracy of the proposed method are 83.30% and 78.77%, respectively, which are significantly better than the values obtained for the multithreshold change vector analysis (MCVA) and the multithreshold change vector analysis and support vector machine (MCVA + SVM) methods; (2) the updated results agree well with GlobeLand30 2010, especially for cultivated land and artificial surfaces, indicating the effectiveness of the proposed method; (3) the most significant changes over the past decade in Shanghai were from cultivated land to artificial surfaces, and the total area containing artificial surfaces in Shanghai increased by about 55% from 2000 to 2011. The factors affecting the updating results are also discussed, which be attributed to the classification accuracy of the base image, extended change vector analysis, and object-based image analysis.
    Keywords GlobeLand30 ; extended change vector analysis ; change detection ; object-based method ; transfer learning ; Science ; Q
    Subject code 910
    Language English
    Publishing date 2020-09-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Incidence and risk factors of delirium after percutaneous coronary intervention in individuals hospitalised for acute myocardial infarction

    Kaizhuang Huang / Jiaying Lu / Yaoli Zhu / Dahao Du / Xueqin Qian / Haiyan Pan / Shaofei Lou

    BMJ Open, Vol 10, Iss

    protocol for a systematic review and meta-analysis

    2020  Volume 12

    Abstract: Introduction Delirium in the postoperative period is a wide-reaching problem that affects important clinical outcomes. The incidence and risk factors of delirium in individuals with acute myocardial infarction (AMI) after primary percutaneous coronary ... ...

    Abstract Introduction Delirium in the postoperative period is a wide-reaching problem that affects important clinical outcomes. The incidence and risk factors of delirium in individuals with acute myocardial infarction (AMI) after primary percutaneous coronary intervention (PCI) has not been completely determined and no relevant systematic review and meta-analysis of incidence or risk factors exists. Hence, we aim to conduct a systematic review and meta-analysis to ascertain the incidence and risk factors of delirium among AMI patients undergoing PCI.Methods and analyses We will undertake a comprehensive literature search among PubMed, EMBASE, Cochrane Library, PsycINFO, CINAHL and Google Scholar from their inception to the search date. Prospective cohort and cross-sectional studies that described the incidence or at least one risk factor of delirium will be eligible for inclusion. The primary outcome will be the incidence of postoperative delirium. The quality of included studies will be assessed using a risk of bias tool for prevalence studies and the Cochrane guidelines. Heterogeneity of the estimates across studies will be assessed. Incidence and risk factors associated with delirium will be extracted. Incidence data will be pooled. Each risk factor reported in the included studies will be recorded together with its statistical significance; narrative and meta-analytical approaches will be employed. The systematic review and meta-analysis will be presented according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses.Ethics and dissemination This proposed systematic review and meta-analysis is based on published data, and thus there is no requirement for ethics approval. The study will provide an up to date and accurate incidence and risk factors of delirium after PCI among patients with AMI, which is necessary for future research in this area. The findings of this study will be disseminated through publication in a peer-reviewed journal.PROSPERO registration number CRD42020184388.
    Keywords Medicine ; R
    Subject code 610
    Language English
    Publishing date 2020-12-01T00:00:00Z
    Publisher BMJ Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: KRT6A Promotes Lung Cancer Cell Growth and Invasion Through MYC-Regulated Pentose Phosphate Pathway

    Di Che / Mingshuo Wang / Juan Sun / Bo Li / Tao Xu / Yuxiong Lu / Haiyan Pan / Zhaoliang Lu / Xiaoqiong Gu

    Frontiers in Cell and Developmental Biology, Vol

    2021  Volume 9

    Abstract: Keratin 6A (KRT6A) belongs to the keratin protein family which is a critical component of cytoskeleton in mammalian cells. Although KRT6A upregulation in non-small cell lung cancer (NSCLC) has been reported, the regulatory mechanism and functional role ... ...

    Abstract Keratin 6A (KRT6A) belongs to the keratin protein family which is a critical component of cytoskeleton in mammalian cells. Although KRT6A upregulation in non-small cell lung cancer (NSCLC) has been reported, the regulatory mechanism and functional role of KRT6A in NSCLC development have been less well investigated. In this study, KRT6A was confirmed to be highly expressed in NSCLC tissue samples, and its high expression correlated with poor patient prognosis. Furthermore, overexpression of KRT6A promotes NSCLC cell proliferation and invasion. Mechanistically, KRT6A overexpression is sufficient to upregulate glucose-6-phosphate dehydrogenase (G6PD) levels and increase the pentose phosphate pathway flux, an essential metabolic pathway to support cancer cell growth and invasion. In addition, we discovered that lysine-specific demethylase 1A (LSD1) functions upstream to promote KRT6A gene expression. We also found that the MYC family members c-MYC/MYCN are involved in KRT6A-induced G6PD upregulation. Therefore, this study reveals an underappreciated mechanism that KRT6A acts downstream of LSD1 and functions as a pivotal driver for NSCLC progression by upregulating G6PD through the MYC signaling pathway. Together, KRT6A and LSD1 may serve as potential prognostic indictors and therapeutic targets for NSCLC.
    Keywords NSCLC ; LSD1 ; G6PD ; MYC ; KRT6A ; Biology (General) ; QH301-705.5
    Subject code 500
    Language English
    Publishing date 2021-06-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Improved A-Star Algorithm for Long-Distance Off-Road Path Planning Using Terrain Data Map

    Zhonghua Hong / Pengfei Sun / Xiaohua Tong / Haiyan Pan / Ruyan Zhou / Yun Zhang / Yanling Han / Jing Wang / Shuhu Yang / Lijun Xu

    ISPRS International Journal of Geo-Information, Vol 10, Iss 785, p

    2021  Volume 785

    Abstract: To overcome the limitation of poor processing times for long-distance off-road path planning, an improved A-Star algorithm based on terrain data is proposed in this study. The improved A-Star algorithm for long-distance off-road path planning tasks was ... ...

    Abstract To overcome the limitation of poor processing times for long-distance off-road path planning, an improved A-Star algorithm based on terrain data is proposed in this study. The improved A-Star algorithm for long-distance off-road path planning tasks was developed to identify a feasible path between the start and destination based on a terrain data map generated using a digital elevation model. This study optimised the algorithm in two aspects: data structure, retrieval strategy. First, a hybrid data structure of the minimum heap and 2D array greatly reduces the time complexity of the algorithm. Second, an optimised search strategy was designed that does not check whether the destination is reached in the initial stage of searching for the global optimal path, thus improving execution efficiency. To evaluate the efficiency of the proposed algorithm, three different off-road path planning tasks were examined for short-, medium-, and long-distance path planning tasks. Each group of tasks corresponded to three different off-road vehicles, and nine groups of experiments were conducted. The experimental results show that the processing efficiency of the proposed algorithm is significantly better than that of the conventional A-Star algorithm. Compared with the conventional A-Star algorithm, the path planning efficiency of the improved A-Star algorithm was accelerated by at least 4.6 times, and the maximum acceleration reached was 550 times for long-distance off-road path planning. The simulation results show that the efficiency of long-distance off-road path planning was greatly improved by using the improved algorithm.
    Keywords path planning ; long distance ; terrain data map ; A-Star algorithm ; efficiency ; Geography (General) ; G1-922
    Subject code 006
    Language English
    Publishing date 2021-11-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Exosomes Derived From Macrophages Enhance Aerobic Glycolysis and Chemoresistance in Lung Cancer by Stabilizing c-Myc via the Inhibition of NEDD4L

    Huan Wang / Lie Wang / Haiyan Pan / Yaona Wang / Miao Shi / Hang Yu / Chaoye Wang / Xinfu Pan / Zhijun Chen

    Frontiers in Cell and Developmental Biology, Vol

    2021  Volume 8

    Abstract: As one of the most common and lethal cancer, lung cancer severely threatens the health of human. It has been reported that tumor-associated macrophages promote initiation, progression, as well as chemoresistance in human cancers. However, the underneath ... ...

    Abstract As one of the most common and lethal cancer, lung cancer severely threatens the health of human. It has been reported that tumor-associated macrophages promote initiation, progression, as well as chemoresistance in human cancers. However, the underneath molecular mechanism that drives chemoresistance in lung cancer is yet not fully characterized. In this article, we demonstrated that M2 macrophage-derived exosomes (MDE) is the key factor to promote cisplatin-resistance in lung cancer. MDE exhibited high expression level of several miRNA including miR-3679-5p. Mechanistically, miR-3679-5p was delivered to lung cancer cells by MDE, downregulating the expression of a known E3 ligase, NEDD4L, which has been identified as a key regulator controlling the stability of c-Myc. Such decreased NEDD4L expression level resulted in the stabilization of c-Myc and elevated glycolysis. The enhanced glycolysis drives the chemoresistance in lung cancer. Taken together, our findings not only show that M2 macrophage induce chemoresistance in lung cancer through MDE mediated miR-3679-5R/NEDD4L/c-Myc signaling cascade, but also shed the light on the mechanism of the cross-talk between M2 macrophage and lung cancers. By pinpointing a potential novel survival signaling pathway, our data could provide a new potential therapeutic target for lung cancer treatment and management.
    Keywords glycolysis ; M2 macrophage-derived exosomes ; NEDD4L ; lung cancer ; chemoresistance ; Biology (General) ; QH301-705.5
    Subject code 610
    Language English
    Publishing date 2021-03-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Active Fire Detection Using a Novel Convolutional Neural Network Based on Himawari-8 Satellite Images

    Zhonghua Hong / Zhizhou Tang / Haiyan Pan / Yuewei Zhang / Zhongsheng Zheng / Ruyan Zhou / Zhenling Ma / Yun Zhang / Yanling Han / Jing Wang / Shuhu Yang

    Frontiers in Environmental Science, Vol

    2022  Volume 10

    Abstract: Fire is an important ecosystem process and has played a complex role in terrestrial ecosystems and the atmosphere environment. Sometimes, wildfires are highly destructive natural disasters. To reduce their destructive impact, wildfires must be detected ... ...

    Abstract Fire is an important ecosystem process and has played a complex role in terrestrial ecosystems and the atmosphere environment. Sometimes, wildfires are highly destructive natural disasters. To reduce their destructive impact, wildfires must be detected as soon as possible. However, accurate and timely monitoring of wildfires is a challenging task due to the traditional threshold methods easily be suffered to the false alarms caused by small forest clearings, and the omission error of large fires obscured by thick smoke. Deep learning has the characteristics of strong learning ability, strong adaptability and good portability. At present, few studies have addressed the wildfires detection problem in remote sensing images using deep learning method in a nearly real time way. Therefore, in this research we proposed an active fire detection system using a novel convolutional neural network (FireCNN). FireCNN uses multi-scale convolution and residual acceptance design, which can effectively extract the accurate characteristics of fire spots. The proposed method was tested on dataset which contained 1,823 fire spots and 3,646 non-fire spots. The experimental results demonstrate that the FireCNN is fully capable of wildfire detection, with the accuracy of 35.2% higher than the traditional threshold method. We also examined the influence of different structural designs on the performance of neural network models. The comparison results indicates the proposed method produced the best results.
    Keywords active fire detection ; deep learning ; active fire dataset ; wildfire ; himawari-8 imagery ; fireCNN ; Environmental sciences ; GE1-350
    Subject code 006
    Language English
    Publishing date 2022-03-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: Automated Subpixel Surface Water Mapping from Heterogeneous Urban Environments Using Landsat 8 OLI Imagery

    Huan Xie / Xin Luo / Xiong Xu / Haiyan Pan / Xiaohua Tong

    Remote Sensing, Vol 8, Iss 7, p

    2016  Volume 584

    Abstract: Water bodies are a fundamental element of urban ecosystems, and water mapping is critical for urban and landscape planning and management. Remote sensing has increasingly been used for water mapping in rural areas; however, when applied to urban areas, ... ...

    Abstract Water bodies are a fundamental element of urban ecosystems, and water mapping is critical for urban and landscape planning and management. Remote sensing has increasingly been used for water mapping in rural areas; however, when applied to urban areas, this spatially- explicit approach is a challenging task due to the fact that the water bodies are often of a small size and spectral confusion is common between water and the complex features in the urban environment. Water indexes are the most common method of water extraction at the pixel level. More recently, spectral mixture analysis (SMA) has been widely employed in analyzing the urban environment at the subpixel level. The objective of this study is to develop an automatic subpixel water mapping method (ASWM) which can achieve a high accuracy in urban areas. Specifically, we first apply a water index for the automatic extraction of mixed land-water pixels, and the pure water pixels that are generated in this process are exported as the final result. Secondly, the SMA technique is applied to the mixed land-water pixels for water abundance estimation. As for obtaining the most representative endmembers, we propose an adaptive iterative endmember selection method based on the spatial similarity of adjacent ground surfaces. One classical water index method (the modified normalized difference water index (MNDWI)), a pixel-level target detection method (constrained energy minimization (CEM)), and two widely used SMA methods (fully constrained least squares (FCLS) and multiple endmember spectral mixture analysis (MESMA)) were chosen for the water mapping comparison in the experiments. The results indicate that the proposed ASWM was able to detect water pixels more efficiency than other unsupervised water extraction methods, and the water fractions estimated by the proposed ASWM method correspond closely to the reference fractions with the slopes of 0.97, 1.02, 1.04, and 0.98 and the R-squared values of 0.9454, 0.9486, 0.9665, and 0.9607 in regression analysis ...
    Keywords water mapping ; urban ; subpixel classification ; Landsat 8 OLI ; endmember selection ; Science ; Q
    Subject code 710
    Language English
    Publishing date 2016-07-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article: Bis‐substituted thiophene‐containing oxime sulfonates photoacid generators for cationic polymerization under UV–visible LED irradiation

    Sun, Xin / Decheng Wan / Haiyan Pan / Hongting Pu / Ming Jin / Xingyu Wu

    Journal of polymer science. 2018 Apr. 1, v. 56, no. 7

    2018  

    Abstract: Three novel types of thiophene‐containing oxime sulfonates with a big π‐conjugated system were reported as non‐ionic photoacid generators. The irradiation of the newly synthesized photoacid generators using near UV–visible light‐emitting ... ...

    Abstract Three novel types of thiophene‐containing oxime sulfonates with a big π‐conjugated system were reported as non‐ionic photoacid generators. The irradiation of the newly synthesized photoacid generators using near UV–visible light‐emitting diodes (LEDs) (365–475 nm) results in the cleavage of two weak NO bonds in single molecules, which lead to the generation of different sulfonic acids in good quantum and chemical yields. The mechanism for the NO bond cleavage for acid generation was supported by the UV–visible spectra and real‐time ¹H NMR spectra. They are developed as high‐performance photoinitiators without any additives for the cationic polymerization of epoxide and vinyl ether upon exposure to near‐UV and visible LEDs (365–475 nm) at low concentration. In the field of photopolymerization, especially visible light polymerization, it has great potential for application. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2018, 56, 776–782
    Keywords additives ; cleavage (chemistry) ; irradiation ; light emitting diodes ; nuclear magnetic resonance spectroscopy ; polymerization ; polymers ; sulfonates ; sulfonic acid
    Language English
    Dates of publication 2018-0401
    Size p. 776-782.
    Publishing place John Wiley & Sons, Ltd
    Document type Article
    Note JOURNAL ARTICLE
    ISSN 0887-624X
    DOI 10.1002/pola.28951
    Database NAL-Catalogue (AGRICOLA)

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