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  1. Book ; Online: Machine Learning for Flow Cytometry Data Analysis

    Xu, Yanhua

    2023  

    Abstract: Flow cytometry mainly used for detecting the characteristics of a number of biochemical substances based on the expression of specific markers in cells. It is particularly useful for detecting membrane surface receptors, antigens, ions, or during DNA/RNA ...

    Abstract Flow cytometry mainly used for detecting the characteristics of a number of biochemical substances based on the expression of specific markers in cells. It is particularly useful for detecting membrane surface receptors, antigens, ions, or during DNA/RNA expression. Not only can it be employed as a biomedical research tool for recognising distinctive types of cells in mixed populations, but it can also be used as a diagnostic tool for classifying abnormal cell populations connected with disease. Modern flow cytometers can rapidly analyse tens of thousands of cells at the same time while also measuring multiple parameters from a single cell. However, the rapid development of flow cytometers makes it challenging for conventional analysis methods to interpret flow cytometry data. Researchers need to be able to distinguish interesting-looking cell populations manually in multi-dimensional data collected from millions of cells. Thus, it is essential to find a robust approach for analysing flow cytometry data automatically, specifically in identifying cell populations automatically. This thesis mainly concerns discover the potential shortcoming of current automated-gating algorithms in both real datasets and synthetic datasets. Three representative automated clustering algorithms are selected to be applied, compared and evaluated by completely and partially automated gating. A subspace clustering ProClus also implemented in this thesis. The performance of ProClus in flow cytometry is not well, but it is still a useful algorithm to detect noise.

    Comment: MSc thesis
    Keywords Computer Science - Machine Learning ; Computer Science - Artificial Intelligence ; Quantitative Biology - Quantitative Methods
    Subject code 004
    Publishing date 2023-03-15
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article: Identification and evaluation of educational technology trends from 2004 to 2022: Evidence based on computers in human behavior and horizon report.

    Liu, Jun / Liu, Zile / Wang, Cong / Xu, Yanhua

    Heliyon

    2024  Volume 10, Issue 2, Page(s) e24277

    Abstract: The increasing influence of technology on education has attracted considerable attention. This study aims to determine the current status and development trends of educational technologies. At first, we used COOC, HistCite, and VOSviewer to ... ...

    Abstract The increasing influence of technology on education has attracted considerable attention. This study aims to determine the current status and development trends of educational technologies. At first, we used COOC, HistCite, and VOSviewer to systematically review 1562 educational articles published in
    Language English
    Publishing date 2024-01-17
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2024.e24277
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Clinical retrospective study on the digital data of orthodontic cases by Andrews six elements.

    Liu, Chaofeng / Xu, Yanhua / Yi, Chunyan / Liu, Yan

    Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology

    2024  Volume 40, Issue 2, Page(s) 183–188

    Abstract: Objectives: Andrews six elements was used to explore the possible influences of gender, extraction/non-extraction, and different bracket types on the evaluation of orthodontic treatment outcome.: Methods: Digital data from 320 selected orthodontic ... ...

    Abstract Objectives: Andrews six elements was used to explore the possible influences of gender, extraction/non-extraction, and different bracket types on the evaluation of orthodontic treatment outcome.
    Methods: Digital data from 320 selected orthodontic cases in Kunming Medical University Affiliated Stomatological Hospital during the period of 2016-2020 were divided into groups in accordance with gender, tooth extraction, and type of orthodontic brackets (DamonQ self-ligating brackets and MBT brackets). Measurement was performed using Andrews six elements as standard. The mean and standard deviation of each individual score and total score for different groups were calculated and statistically tested.
    Results: The differences in total scores between female and male cases exhibited no statistical significance (
    Conclusions: Digital 3D models can be used in the clinical retrospective studies of patients after orthodontic treatment. These models can be measured repeatedly and have clinical application value. For cases with incomplete orthodontic treatment, the control of the anteroposterior position of the incisor and the width of the arch of the upper tooth is crucial. Total treatment efficiency between female and male cases exhibited no difference, but the skeletal width change of the maxilla between extraction and non-extraction cases may exert an effect on cases with complete orthodontic treatment. The group that used DamonQ self-ligating brackets may achieve good adjustment of the bucco-lingual border change of the arch.
    Language Chinese
    Publishing date 2024-04-10
    Publishing country China
    Document type Journal Article
    ZDB-ID 1202342-5
    ISSN 2618-0456 ; 1000-1182
    ISSN (online) 2618-0456
    ISSN 1000-1182
    DOI 10.7518/hxkq.2022.02.009
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Emerging advances in delivery systems for mRNA cancer vaccines.

    Jiang, Zhimei / Xu, Yanhua / Du, Guangsheng / Sun, Xun

    Journal of controlled release : official journal of the Controlled Release Society

    2024  Volume 370, Page(s) 287–301

    Abstract: The success of lipid nanoparticles (LNPs) in treating COVID-19 promotes further research of mRNA vaccines for cancer vaccination. Aiming at overcoming the constraints of currently available mRNA carriers, various alternative nano-vectors have been ... ...

    Abstract The success of lipid nanoparticles (LNPs) in treating COVID-19 promotes further research of mRNA vaccines for cancer vaccination. Aiming at overcoming the constraints of currently available mRNA carriers, various alternative nano-vectors have been developed for delivering tumor antigen encoding mRNA and showed versatility to induce potent anti-tumor immunity. The rationally designed nano-vaccines increase the immune activation capacity of the mRNA vaccines by promoting crucial aspects including mRNA stability, cellular uptake, endosomal escape and targeting of immune cells or organs. Herein, we summarized the research progress of various mRNA based nano-vaccines that have been reported for cancer vaccination, including LNPs, lipid enveloped hybrid nanoparticles, polymeric nanoparticles etc. Several strategies that have been reported for further enhancing the immune stimulation efficacy of mRNA nano-vaccines, including developing nano-vaccines for co-delivering adjuvants, combination of immune checkpoint inhibitors, and optimizing the injection routes for boosting immune responses, have been reviewed. The progress of mRNA nano-vaccines in clinical trials and the prospect of the mRNA vaccines for cancer vaccination are also discussed.
    Language English
    Publishing date 2024-05-01
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 632533-6
    ISSN 1873-4995 ; 0168-3659
    ISSN (online) 1873-4995
    ISSN 0168-3659
    DOI 10.1016/j.jconrel.2024.04.039
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Dive into machine learning algorithms for influenza virus host prediction with hemagglutinin sequences.

    Xu, Yanhua / Wojtczak, Dominik

    Bio Systems

    2022  Volume 220, Page(s) 104740

    Abstract: Influenza viruses mutate rapidly and can pose a threat to public health, especially to those in vulnerable groups. Throughout history, influenza A viruses have caused pandemics between different species. It is important to identify the origin of a virus ... ...

    Abstract Influenza viruses mutate rapidly and can pose a threat to public health, especially to those in vulnerable groups. Throughout history, influenza A viruses have caused pandemics between different species. It is important to identify the origin of a virus in order to prevent the spread of an outbreak. Recently, there has been increasing interest in using machine learning algorithms to provide fast and accurate predictions for viral sequences. In this study, real testing data sets and a variety of evaluation metrics were used to evaluate machine learning algorithms at different taxonomic levels. As hemagglutinin is the major protein in the immune response, only hemagglutinin sequences were used and represented by position-specific scoring matrix and word embedding. The results suggest that the 5-grams-transformer neural network is the most effective algorithm for predicting viral sequence origins, with approximately 99.54% AUCPR, 98.01% F
    MeSH term(s) Algorithms ; Hemagglutinins/genetics ; Influenza A virus/genetics ; Machine Learning ; Orthomyxoviridae
    Chemical Substances Hemagglutinins
    Language English
    Publishing date 2022-08-04
    Publishing country Ireland
    Document type Journal Article
    ZDB-ID 186234-0
    ISSN 1872-8324 ; 0303-2647
    ISSN (online) 1872-8324
    ISSN 0303-2647
    DOI 10.1016/j.biosystems.2022.104740
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Triassic provenance shifts and tectonic evolution of southeast Ordos Basin, Central China

    Xu, Yanhua / He, Dengfa

    Palaeogeography, palaeoclimatology, palaeoecology. 2022 July 15, v. 598

    2022  

    Abstract: Tectonic evolution of the North China Craton underwent a complicated process during the early Mesozoic owing to almost simultaneous closures of the Mianlue Ocean to the south and the Palaeo-Asian Ocean to the north. The tectonic setting of the Triassic ... ...

    Abstract Tectonic evolution of the North China Craton underwent a complicated process during the early Mesozoic owing to almost simultaneous closures of the Mianlue Ocean to the south and the Palaeo-Asian Ocean to the north. The tectonic setting of the Triassic sedimentary basin in the southern North China Craton remains a subject of debate. The conventional view is that early Mesozoic basins resulted from plate collision and crustal shortening, whereas new petrological evidence of crustal extension has been identified in the southern North China Craton. In this study, we used petrology, sedimentology, subsidence and geochronology to trace basin provenance and reconstruct source-to-sink around the southeast Ordos Basin. The petrographic modal compositions showed that the provenance changed from recycled orogenic to a mixture of recycled orogenic and arc magmatic materials. Tectonic subsidence of the southeast Ordos Basin revealed two episodes of rapid subsidence, the second of which lasted ~10 Ma and caused the depocenter of the basin to move southward. Early Triassic detrital zircons with distinguishing ages of 1100–700 Ma were derived from the Central China Orogenic Belt and North China Craton; then, they were sourced from the Inner Mongolia Palaeo-uplift, based on zircon ages clustered at ~400–250 Ma. The petrographic modal composition, tectonic subsidence and zircon age distribution imply a provenance shift from short and rapid uplift (North Qinling Orogenic Belt) to remote continuous uplift (Inner Mongolia Palaeo-uplift); this is also supported by the palaeo-current direction. This shift defined a change in the Qinling Orogenic Belt from collision and uplift to extension, which caused the depositional centre of the Ordos Basin to move southward. This integrated tectono-sedimentary environment study provides new insight into the closure process of the Mianlue Ocean during the Triassic and its impact on the tectonic environment of the southern North China Craton.
    Keywords Triassic period ; basins ; geochronology ; palaeogeography ; paleoclimatology ; paleoecology ; provenance ; subsidence ; tectonics ; zircon ; China
    Language English
    Dates of publication 2022-0715
    Publishing place Elsevier B.V.
    Document type Article
    ZDB-ID 417718-6
    ISSN 0031-0182
    ISSN 0031-0182
    DOI 10.1016/j.palaeo.2022.111002
    Database NAL-Catalogue (AGRICOLA)

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  7. Article: A systematic review of studies on stress during the COVID-19 pandemic by visualizing their structure through COOC, VOS viewer, and Cite Space software.

    Lu, Liyun / Liu, Guiping / Xu, Yanhua / Jiang, Jinxiu / Wei, Zizi

    Frontiers in psychiatry

    2024  Volume 15, Page(s) 1297112

    Abstract: Background: The COVID-19 epidemic generated different forms of stress. From this period, there has been a remarkable increase in the quantity of studies on stress conducted by scholars. However, few used bibliometric analyses to focus on overall trends ... ...

    Abstract Background: The COVID-19 epidemic generated different forms of stress. From this period, there has been a remarkable increase in the quantity of studies on stress conducted by scholars. However, few used bibliometric analyses to focus on overall trends in the field.
    Purpose: This study sought to understand the current status and trends in stress development during COVID-19, as well as the main research drives and themes in this field.
    Methods: 2719 publications from the Web of Science(WOS) core repository on stress during COVID-19 were analyzed by utilizing Co-Occurrence (COOC), VOS viewer, and Cite Space bibliometric software. The overall features of research on stress during COVID-19 were concluded by analyzing the quantity of publications, keywords, countries, and institutions.
    Results: The results indicated that the United States had the largest number of publications and collaborated closely with other countries with each other. University of Toronto was the most prolific institution worldwide. Visualization and analysis demonstrated that the influence of stress during COVID-19 on the work, life, mental and spiritual dimensions is a hot research topic. Among other things, the frequency of each keyword in research on stress during COVID-19 increased from 2021 to 2022, and the researchers expanded their scope and study population; the range of subjects included children, nurses, and college students, as well as studies focusing on different types of stress, and emphasizing the handling of stress.
    Conclusion: Our findings reveal that the heat of stress research during COVID-19 has declined, and the main research forces come from the United States and China. Additionally, subsequent research should concern more on coping methods with stress, while using more quantitative and qualitative studies in the future.
    Language English
    Publishing date 2024-01-25
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2564218-2
    ISSN 1664-0640
    ISSN 1664-0640
    DOI 10.3389/fpsyt.2024.1297112
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Degradation of Aflatoxin B1 in Moldy Maize by Pseudomonas aeruginosa and Safety Evaluation of the Degradation Products

    Xu, Yanhua / Zhao, Renyong / Liu, Chenxi

    Foods. 2023 Mar. 13, v. 12, no. 6

    2023  

    Abstract: Aflatoxin B₁ (AFB₁) is the most harmful mycotoxin commonly found in food and feed. Pollution from AFB₁ causes serious economic and health issues worldwide because it causes strong mutagenicity and carcinogenicity in humans and animals. In this study, ... ...

    Abstract Aflatoxin B₁ (AFB₁) is the most harmful mycotoxin commonly found in food and feed. Pollution from AFB₁ causes serious economic and health issues worldwide because it causes strong mutagenicity and carcinogenicity in humans and animals. In this study, Pseudomonas aeruginosa was used to degrade AFB₁ in moldy maize, and the safety of this biological method was investigated using genotoxicity and cytotoxicity tests. Using response surface methodology, we established the optimal conditions for degrading AFB₁ by the fermentation supernatant of P. aeruginosa. Under these conditions, the degradation rate of AFB₁ reached 99.67%. Furthermore, the Ames mutagenicity test showed that AFB₁ treated with P. aeruginosa fermentation supernatant for 72 h was not mutagenic. CCK-8 cell assay showed that AFB₁ cytotoxicity was significantly reduced after degradation. Overall, our findings show that the fermentation supernatant of P. aeruginosa may be a good candidate for biodegradation of AFB₁.
    Keywords Pseudomonas aeruginosa ; aflatoxin B1 ; biodegradation ; carcinogenicity ; corn ; cytotoxicity ; fermentation ; genotoxicity ; genotoxicity tests ; molds (fungi) ; mutagenicity ; mutagens ; pollution ; response surface methodology
    Language English
    Dates of publication 2023-0313
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article ; Online
    ZDB-ID 2704223-6
    ISSN 2304-8158
    ISSN 2304-8158
    DOI 10.3390/foods12061217
    Database NAL-Catalogue (AGRICOLA)

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  9. Book ; Online: MC-NN

    Xu, Yanhua / Wojtczak, Dominik

    An End-to-End Multi-Channel Neural Network Approach for Predicting Influenza A Virus Hosts and Antigenic Types

    2023  

    Abstract: Influenza poses a significant threat to public health, particularly among the elderly, young children, and people with underlying dis-eases. The manifestation of severe conditions, such as pneumonia, highlights the importance of preventing the spread of ... ...

    Abstract Influenza poses a significant threat to public health, particularly among the elderly, young children, and people with underlying dis-eases. The manifestation of severe conditions, such as pneumonia, highlights the importance of preventing the spread of influenza. An accurate and cost-effective prediction of the host and antigenic sub-types of influenza A viruses is essential to addressing this issue, particularly in resource-constrained regions. In this study, we propose a multi-channel neural network model to predict the host and antigenic subtypes of influenza A viruses from hemagglutinin and neuraminidase protein sequences. Our model was trained on a comprehensive data set of complete protein sequences and evaluated on various test data sets of complete and incomplete sequences. The results demonstrate the potential and practicality of using multi-channel neural networks in predicting the host and antigenic subtypes of influenza A viruses from both full and partial protein sequences.

    Comment: Accepted version submitted to the SN Computer Science; Published in the SN Computer Science 2023; V1: minor updates were made to the Results section; V2: minor updates regarding data description
    Keywords Computer Science - Machine Learning ; Quantitative Biology - Quantitative Methods
    Publishing date 2023-06-08
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article: Degradation of Aflatoxin B

    Xu, Yanhua / Zhao, Renyong / Liu, Chenxi

    Foods (Basel, Switzerland)

    2023  Volume 12, Issue 6

    Abstract: Aflatoxin ... ...

    Abstract Aflatoxin B
    Language English
    Publishing date 2023-03-13
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2704223-6
    ISSN 2304-8158
    ISSN 2304-8158
    DOI 10.3390/foods12061217
    Database MEDical Literature Analysis and Retrieval System OnLINE

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