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  1. Article ; Online: Impacts of tree species diversity on microbial carbon use efficiency.

    Chen, Yongliang / Hu, Hang-Wei

    Global change biology

    2023  Volume 30, Issue 1, Page(s) e17015

    MeSH term(s) Trees ; Carbon ; Forests ; Soil ; Soil Microbiology ; Ecosystem
    Chemical Substances Carbon (7440-44-0) ; Soil
    Language English
    Publishing date 2023-11-02
    Publishing country England
    Document type Journal Article
    ZDB-ID 1281439-8
    ISSN 1365-2486 ; 1354-1013
    ISSN (online) 1365-2486
    ISSN 1354-1013
    DOI 10.1111/gcb.17015
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  2. Article ; Online: Total metagenomes outperform viromes in recovering viral diversity from sulfuric soils.

    Bi, Li / He, Ji-Zheng / Hu, Hang-Wei

    ISME communications

    2024  Volume 4, Issue 1, Page(s) ycae017

    Abstract: Recent metagenomic advancements have offered unprecedented insights into soil viral ecology. However, it remains a challenge to select the suitable metagenomic method for investigating soil viruses under different environmental conditions. Here, we ... ...

    Abstract Recent metagenomic advancements have offered unprecedented insights into soil viral ecology. However, it remains a challenge to select the suitable metagenomic method for investigating soil viruses under different environmental conditions. Here, we assessed the performance of viral size-fraction metagenomes (viromes) and total metagenomes in capturing viral diversity from hypersulfidic soils with neutral pH and sulfuric soils with pH <3.3. Viromes effectively enhanced the sequencing coverage of viral genomes in both soil types. Viomes of hypersulfidic soils outperformed total metagenomes by recovering a significantly higher number of viral operational taxonomic units (vOTUs). However, total metagenomes of sulfuric soils recovered ~4.5 times more vOTUs than viromes on average. Altogether, our findings suggest that the choice between viromes and total metagenomes for studying soil viruses should be carefully considered based on the specific environmental conditions.
    Language English
    Publishing date 2024-01-27
    Publishing country England
    Document type Journal Article
    ISSN 2730-6151
    ISSN (online) 2730-6151
    DOI 10.1093/ismeco/ycae017
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  3. Article ; Online: iPiDA-SWGCN

    Jialu Hou / Hang Wei / Bin Liu

    PLoS Computational Biology, Vol 19, Iss 6, p e

    Identification of piRNA-disease associations based on Supplementarily Weighted Graph Convolutional Network.

    2023  Volume 1011242

    Abstract: Accurately identifying potential piRNA-disease associations is of great importance in uncovering the pathogenesis of diseases. Recently, several machine-learning-based methods have been proposed for piRNA-disease association detection. However, they are ... ...

    Abstract Accurately identifying potential piRNA-disease associations is of great importance in uncovering the pathogenesis of diseases. Recently, several machine-learning-based methods have been proposed for piRNA-disease association detection. However, they are suffering from the high sparsity of piRNA-disease association network and the Boolean representation of piRNA-disease associations ignoring the confidence coefficients. In this study, we propose a supplementarily weighted strategy to solve these disadvantages. Combined with Graph Convolutional Networks (GCNs), a novel predictor called iPiDA-SWGCN is proposed for piRNA-disease association prediction. There are three main contributions of iPiDA-SWGCN: (i) Potential piRNA-disease associations are preliminarily supplemented in the sparse piRNA-disease network by integrating various basic predictors to enrich network structure information. (ii) The original Boolean piRNA-disease associations are assigned with different relevance confidence to learn node representations from neighbour nodes in varying degrees. (iii) The experimental results show that iPiDA-SWGCN achieves the best performance compared with the other state-of-the-art methods, and can predict new piRNA-disease associations.
    Keywords Biology (General) ; QH301-705.5
    Subject code 006
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
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  4. Article ; Online: Microbial hydrogen cycling in agricultural systems - plant beneficial or detrimental?

    Islam, Zahra F / Greening, Chris / Hu, Hang-Wei

    Microbial biotechnology

    2023  Volume 16, Issue 8, Page(s) 1623–1628

    Abstract: Hydrogen-oxidising bacteria play a key role in maintaining the composition of gases within the atmosphere and are ubiquitous in agricultural soils. While studies have shown that hydrogen accumulates in soil surrounding legume nodules and the soil surface, ...

    Abstract Hydrogen-oxidising bacteria play a key role in maintaining the composition of gases within the atmosphere and are ubiquitous in agricultural soils. While studies have shown that hydrogen accumulates in soil surrounding legume nodules and the soil surface, soils as a whole act as a net sink for hydrogen, raising questions about how hydrogen is internally recycled by soils. Can the energy derived from hydrogen oxidation be directly funnelled into plants to promote their growth or does it only act as a booster for other plant-growth promoting bacteria? Moreover, while the fertilisation effect of hydrogen on plants has previously been shown to be beneficial, questions remain about the upper limit of hydrogen uptake by plants before it becomes detrimental. Agricultural practices such as fertilisation may impact the balance of hydrogen-oxidisers and hydrogen-producers in these ecosystems, potentially having detrimental effects on not only agricultural land but also global biogeochemical cycles. In this perspectives piece, we highlight the importance of understanding the contribution of hydrogen to agricultural soils and the effects of agricultural practices on the ability for bacteria to cycle hydrogen in agricultural soils. We propose a framework to gain better insights into microbial hydrogen cycling within agroecosystems, which could contribute to the development of new agricultural biotechnologies.
    MeSH term(s) Ecosystem ; Hydrogen ; Soil Microbiology ; Agriculture ; Plants ; Soil/chemistry ; Bacteria/genetics
    Chemical Substances Hydrogen (7YNJ3PO35Z) ; Soil
    Language English
    Publishing date 2023-06-24
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2406063-X
    ISSN 1751-7915 ; 1751-7915
    ISSN (online) 1751-7915
    ISSN 1751-7915
    DOI 10.1111/1751-7915.14300
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  5. Article ; Online: Microlensed fiber allows subcellular imaging by laser-based mass spectrometry.

    Meng, Yifan / Hang, Wei / Zare, Richard N

    Nature protocols

    2023  Volume 18, Issue 8, Page(s) 2558–2578

    Abstract: Mass spectrometry imaging (MSI) enables the chemical mapping of molecules and elements in a label-free, high-throughput manner. Because this approach can be accomplished rapidly, it also enables chemical changes to be monitored. Here, we describe a ... ...

    Abstract Mass spectrometry imaging (MSI) enables the chemical mapping of molecules and elements in a label-free, high-throughput manner. Because this approach can be accomplished rapidly, it also enables chemical changes to be monitored. Here, we describe a protocol for MSI with subcellular spatial resolution. This is achieved by using a microlensed fiber, which is made by grinding an optical fiber. It is a universal and economic technique that can be adapted to most laser-based mass spectrometry methods. In this protocol, the output of laser radiation from the microlensed fiber causes laser ablation of the sample, and the resulting plume is mass spectrometrically analyzed. The microlensed fiber can be used with matrix-assisted laser desorption ionization, laser desorption ionization, laser ablation electrospray desorption ionization and laser ablation inductively coupled plasma, in each case to achieve submicroscale imaging of single cells and biological tissues. This report provides a detailed introduction of the microlensed fiber design and working principles, sample preparation, microlensed fiber ion source setup and multiple MSI platforms with different kinds of mass spectrometers. A researcher with a little background (such as a trained graduate student) is able to complete all the steps for the experimental setup in ~2 h, including fiber test, laser coupling and ion source modification. The imaging time spent mainly depends on the size of the imaging area. It is suggested that most existing laser-based MSI platforms, especially atmospheric pressure applications, can achieve breakthroughs in spatial resolution by introducing a microlensed fiber module.
    MeSH term(s) Humans ; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methods ; Lasers ; Diagnostic Imaging ; Spectrophotometry ; Spectrometry, Mass, Electrospray Ionization/methods
    Language English
    Publishing date 2023-07-21
    Publishing country England
    Document type Journal Article ; Review ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, Non-U.S. Gov't
    ZDB-ID 2244966-8
    ISSN 1750-2799 ; 1754-2189
    ISSN (online) 1750-2799
    ISSN 1754-2189
    DOI 10.1038/s41596-023-00848-1
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  6. Article ; Online: Engineering biodegradable coatings for sustainable fertilisers

    Hang-Wei Hu / Pavel V. Cherepanov / Zahra F. Islam

    Microbiology Australia, Vol 44, Iss 1, Pp 9-

    2023  Volume 12

    Abstract: With the pressures of a changing global climate and ever-growing population, the need for sustainable agricultural practices that increase crop yields while decreasing greenhouse gas emissions are critical. Currently used practices to increase yields can ...

    Abstract With the pressures of a changing global climate and ever-growing population, the need for sustainable agricultural practices that increase crop yields while decreasing greenhouse gas emissions are critical. Currently used practices to increase yields can often be problematic due to low nitrogen use efficiency or a potential overreliance on agrichemicals that can alter the community composition of a given ecosystem, although this is typically system and situation dependent. As such, the next generation of enhanced efficiency fertilisers that combine chemical, materials engineering and biological components are likely to be a game changer. Integral to their success is a better understanding of how plant–soil microbiomes interact with the new enhanced efficiency fertilisers, and how we can best tailor the fertilisers to suit different plant–soil combinations. In particular, the biodegradation properties of new fertiliser coatings must be given careful consideration so as to not further burden agricultural soils with microplastics or cause ecotoxicity problems. This perspective proposes novel, interdisciplinary strategies to generate highly efficient, biodegradable fertiliser coatings for use in the agricultural sector.
    Keywords agriculture ; biodegradation ; biotechnology ; fertilisers ; plant–microbiome interactions ; polymers ; Microbiology ; QR1-502
    Language English
    Publishing date 2023-01-01T00:00:00Z
    Publisher CSIRO Publishing
    Document type Article ; Online
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  7. Article ; Online: iPiDA-GCN

    Jialu Hou / Hang Wei / Bin Liu

    PLoS Computational Biology, Vol 18, Iss 10, p e

    Identification of piRNA-disease associations based on Graph Convolutional Network.

    2022  Volume 1010671

    Abstract: Motivation Piwi-interacting RNAs (piRNAs) play a critical role in the progression of various diseases. Accurately identifying the associations between piRNAs and diseases is important for diagnosing and prognosticating diseases. Although some ... ...

    Abstract Motivation Piwi-interacting RNAs (piRNAs) play a critical role in the progression of various diseases. Accurately identifying the associations between piRNAs and diseases is important for diagnosing and prognosticating diseases. Although some computational methods have been proposed to detect piRNA-disease associations, it is challenging for these methods to effectively capture nonlinear and complex relationships between piRNAs and diseases because of the limited training data and insufficient association representation. Results With the growth of piRNA-disease association data, it is possible to design a more complex machine learning method to solve this problem. In this study, we propose a computational method called iPiDA-GCN for piRNA-disease association identification based on graph convolutional networks (GCNs). The iPiDA-GCN predictor constructs the graphs based on piRNA sequence information, disease semantic information and known piRNA-disease associations. Two GCNs (Asso-GCN and Sim-GCN) are used to extract the features of both piRNAs and diseases by capturing the association patterns from piRNA-disease interaction network and two similarity networks. GCNs can capture complex network structure information from these networks, and learn discriminative features. Finally, the full connection networks and inner production are utilized as the output module to predict piRNA-disease association scores. Experimental results demonstrate that iPiDA-GCN achieves better performance than the other state-of-the-art methods, benefitted from the discriminative features extracted by Asso-GCN and Sim-GCN. The iPiDA-GCN predictor is able to detect new piRNA-disease associations to reveal the potential pathogenesis at the RNA level. The data and source code are available at http://bliulab.net/iPiDA-GCN/.
    Keywords Biology (General) ; QH301-705.5
    Subject code 006
    Language English
    Publishing date 2022-10-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
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  8. Article ; Online: A case report on a nasal and oral cavity involving large solitary fibrous tumor and comprehensive review of case literature.

    Lu, Xing / Zhang, Jin-Ling / Zhai, Xiang / Liu, Qing / Hang, Wei

    Oral oncology

    2024  Volume 150, Page(s) 106715

    Abstract: Solitary fibrous tumor (SFT) represents an uncommon spindle cell sarcoma predominantly situated within soft tissue, with a notably infrequent occurrence in the nasal cavity and paranasal sinuses. In this report, we present a case involving a middle-aged ... ...

    Abstract Solitary fibrous tumor (SFT) represents an uncommon spindle cell sarcoma predominantly situated within soft tissue, with a notably infrequent occurrence in the nasal cavity and paranasal sinuses. In this report, we present a case involving a middle-aged male with a sizable solitary fibrous tumor affecting both the nasal and oral cavities.
    MeSH term(s) Middle Aged ; Humans ; Male ; Nose Neoplasms/diagnosis ; Nose Neoplasms/pathology ; Solitary Fibrous Tumors/diagnosis ; Paranasal Sinuses/pathology ; Nasal Cavity/pathology ; Sarcoma/pathology
    Language English
    Publishing date 2024-02-09
    Publishing country England
    Document type Review ; Case Reports ; Letter
    ZDB-ID 1120465-5
    ISSN 1879-0593 ; 0964-1955 ; 1368-8375
    ISSN (online) 1879-0593
    ISSN 0964-1955 ; 1368-8375
    DOI 10.1016/j.oraloncology.2024.106715
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  9. Article: Editorial: Nitrogen-cycling microorganisms under global change: Response and feedback.

    Lin, Yongxin / Hu, Hang-Wei / Gao, Gui-Feng / Cai, Yanjiang

    Frontiers in microbiology

    2023  Volume 14, Page(s) 1166306

    Language English
    Publishing date 2023-03-02
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2587354-4
    ISSN 1664-302X
    ISSN 1664-302X
    DOI 10.3389/fmicb.2023.1166306
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  10. Article ; Online: T-wave alternans: an ominous pattern for malignant arrhythmias.

    Feng, Hang-Wei / Zhao, Yun-Tao / Lin, Jian / Weng, Cui-Lian

    QJM : monthly journal of the Association of Physicians

    2023  Volume 116, Issue 9, Page(s) 781–783

    MeSH term(s) Humans ; Arrhythmias, Cardiac/diagnosis ; Electrocardiography
    Language English
    Publishing date 2023-05-19
    Publishing country England
    Document type Journal Article
    ZDB-ID 1199985-8
    ISSN 1460-2393 ; 0033-5622 ; 1460-2725
    ISSN (online) 1460-2393
    ISSN 0033-5622 ; 1460-2725
    DOI 10.1093/qjmed/hcad097
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