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  • Oxford University Press (OUP)  (51)
  • 1
    Online Resource
    Online Resource
    Prospective observational cohort study on grading the severity of postoperative complications in global surgery research
    Oxford University Press (OUP) ; 2019
    In:  British Journal of Surgery Vol. 106, No. 2 ( 2019-01-08), p. e73-e80
    Details
    In: British Journal of Surgery, Oxford University Press (OUP), Vol. 106, No. 2 ( 2019-01-08), p. e73-e80
    Abstract: The Clavien–Dindo classification is perhaps the most widely used approach for reporting postoperative complications in clinical trials. This system classifies complication severity by the treatment provided. However, it is unclear whether the Clavien–Dindo system can be used internationally in studies across differing healthcare systems in high- (HICs) and low- and middle-income countries (LMICs). Methods This was a secondary analysis of the International Surgical Outcomes Study (ISOS), a prospective observational cohort study of elective surgery in adults. Data collection occurred over a 7-day period. Severity of complications was graded using Clavien–Dindo and the simpler ISOS grading (mild, moderate or severe, based on guided investigator judgement). Severity grading was compared using the intraclass correlation coefficient (ICC). Data are presented as frequencies and ICC values (with 95 per cent c.i.). The analysis was stratified by income status of the country, comparing HICs with LMICs. Results A total of 44 814 patients were recruited from 474 hospitals in 27 countries (19 HICs and 8 LMICs). Some 7508 patients (16·8 per cent) experienced at least one postoperative complication, equivalent to 11 664 complications in total. Using the ISOS classification, 5504 of 11 664 complications (47·2 per cent) were graded as mild, 4244 (36·4 per cent) as moderate and 1916 (16·4 per cent) as severe. Using Clavien–Dindo, 6781 of 11 664 complications (58·1 per cent) were graded as I or II, 1740 (14·9 per cent) as III, 2408 (20·6 per cent) as IV and 735 (6·3 per cent) as V. Agreement between classification systems was poor overall (ICC 0·41, 95 per cent c.i. 0·20 to 0·55), and in LMICs (ICC 0·23, 0·05 to 0·38) and HICs (ICC 0·46, 0·25 to 0·59). Conclusion Caution is recommended when using a treatment approach to grade complications in global surgery studies, as this may introduce bias unintentionally.
    Type of Medium: Online Resource
    ISSN: 0007-1323 , 1365-2168
    URL: Article
    DOI: 10.1002/bjs.11025
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
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  • 2
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    Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2024
    Oxford University Press (OUP) ; 2024
    In:  Nucleic Acids Research Vol. 52, No. D1 ( 2024-01-05), p. D18-D32
    Details
    In: Nucleic Acids Research, Oxford University Press (OUP), Vol. 52, No. D1 ( 2024-01-05), p. D18-D32
    Abstract: The National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support the global academic and industrial communities. With the rapid accumulation of multi-omics data at an unprecedented pace, CNCB-NGDC continuously expands and updates core database resources through big data archiving, integrative analysis and value-added curation. Importantly, NGDC collaborates closely with major international databases and initiatives to ensure seamless data exchange and interoperability. Over the past year, significant efforts have been dedicated to integrating diverse omics data, synthesizing expanding knowledge, developing new resources, and upgrading major existing resources. Particularly, several database resources are newly developed for the biodiversity of protists (P10K), bacteria (NTM-DB, MPA) as well as plant (PPGR, SoyOmics, PlantPan) and disease/trait association (CROST, HervD Atlas, HALL, MACdb, BioKA, BioKA, RePoS, PGG.SV, NAFLDkb). All the resources and services are publicly accessible at https://ngdc.cncb.ac.cn.
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
    URL: Article
    DOI: 10.1093/nar/gkad1078
    RVK:
    WA 15000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2024
    detail.hit.zdb_id: 186809-3
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  • 3
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    Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2022
    Oxford University Press (OUP) ; 2022
    In:  Nucleic Acids Research Vol. 50, No. D1 ( 2022-01-07), p. D27-D38
    Details
    In: Nucleic Acids Research, Oxford University Press (OUP), Vol. 50, No. D1 ( 2022-01-07), p. D27-D38
    Abstract: The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global research in both academia and industry. With the explosively accumulated multi-omics data at ever-faster rates, CNCB-NGDC is constantly scaling up and updating its core database resources through big data archive, curation, integration and analysis. In the past year, efforts have been made to synthesize the growing data and knowledge, particularly in single-cell omics and precision medicine research, and a series of resources have been newly developed, updated and enhanced. Moreover, CNCB-NGDC has continued to daily update SARS-CoV-2 genome sequences, variants, haplotypes and literature. Particularly, OpenLB, an open library of bioscience, has been established by providing easy and open access to a substantial number of abstract texts from PubMed, bioRxiv and medRxiv. In addition, Database Commons is significantly updated by cataloguing a full list of global databases, and BLAST tools are newly deployed to provide online sequence search services. All these resources along with their services are publicly accessible at https://ngdc.cncb.ac.cn.
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
    URL: Article
    DOI: 10.1093/nar/gkab951
    RVK:
    WA 15000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
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  • 4
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    Dehydrogenase MnGutB1 catalyzes 1-deoxynojirimycin biosynthesis in mulberry
    Oxford University Press (OUP) ; 2023
    In:  Plant Physiology Vol. 192, No. 2 ( 2023-05-31), p. 1307-1320
    Details
    In: Plant Physiology, Oxford University Press (OUP), Vol. 192, No. 2 ( 2023-05-31), p. 1307-1320
    Abstract: As the prevalence of diabetes continues to increase, the number of individuals living with diabetes complications will reach an unprecedented magnitude. Continuous use of some synthetic agents to reduce blood glucose levels causes severe side effects, and thus, the demand for nontoxic, affordable drugs persists. Naturally occurring compounds, such as iminosugars derived from the mulberry (Morus spp.), have been shown to reduce blood glucose levels. In mulberry, 1-deoxynojirimycin (DNJ) is the predominant iminosugar. However, the mechanism underlying DNJ biosynthesis is not completely understood. Here, we showed that DNJ in mulberry is derived from sugar and catalyzed through 2-amino-2-deoxy-D-mannitol (ADM) dehydrogenase MnGutB1. Combining both targeted and nontargeted metabolite profiling methods, DNJ and its precursors ADM and nojirimycin (NJ) were quantified in mulberry samples from different tissues. Purified His-tagged MnGutB1 oxidized the hexose derivative ADM to form the 6-oxo compound DNJ. The mutant MnGutB1 D283N lost this remarkable capability. Furthermore, in contrast to virus-induced gene silencing of MnGutB1 in mulberry leaves that disrupted the biosynthesis of DNJ, overexpression of MnGutB1 in hairy roots and light-induced upregulation of MnGutB1 enhanced DNJ accumulation. Our results demonstrated that hexose derivative ADM, rather than lysine derivatives, is the precursor in DNJ biosynthesis, and it is catalyzed by MnGutB1 to form the 6-oxo compound. These results represent a breakthrough in producing DNJ and its analogs for medical use by metabolic engineering or synthetic biology.
    Type of Medium: Online Resource
    ISSN: 0032-0889 , 1532-2548
    URL: Article
    DOI: 10.1093/plphys/kiad065
    RVK:
    WA 15000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
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  • 5
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    MSIsensor-ct: microsatellite instability detection using cfDNA sequencing data
    Oxford University Press (OUP) ; 2021
    In:  Briefings in Bioinformatics Vol. 22, No. 5 ( 2021-09-02)
    Details
    In: Briefings in Bioinformatics, Oxford University Press (OUP), Vol. 22, No. 5 ( 2021-09-02)
    Abstract: Motivation: Microsatellite instability (MSI) is a promising biomarker for cancer prognosis and chemosensitivity. Techniques are rapidly evolving for the detection of MSI from tumor-normal paired or tumor-only sequencing data. However, tumor tissues are often insufficient, unavailable, or otherwise difficult to procure. Increasing clinical evidence indicates the enormous potential of plasma circulating cell-free DNA (cfNDA) technology as a noninvasive MSI detection approach. Results: We developed MSIsensor-ct, a bioinformatics tool based on a machine learning protocol, dedicated to detecting MSI status using cfDNA sequencing data with a potential stable MSIscore threshold of 20%. Evaluation of MSIsensor-ct on independent testing datasets with various levels of circulating tumor DNA (ctDNA) and sequencing depth showed 100% accuracy within the limit of detection (LOD) of 0.05% ctDNA content. MSIsensor-ct requires only BAM files as input, rendering it user-friendly and readily integrated into next generation sequencing (NGS) analysis pipelines. Availability: MSIsensor-ct is freely available at https://github.com/niu-lab/MSIsensor-ct. Supplementary information: Supplementary data are available at Briefings in Bioinformatics online.
    Type of Medium: Online Resource
    ISSN: 1467-5463 , 1477-4054
    URL: Article
    DOI: 10.1093/bib/bbaa402
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
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  • 6
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    Comprehensive review and evaluation of computational methods for identifying FLT3 -internal tandem duplication in acute myeloid leukaemia
    Oxford University Press (OUP) ; 2021
    In:  Briefings in Bioinformatics Vol. 22, No. 5 ( 2021-09-02)
    Details
    In: Briefings in Bioinformatics, Oxford University Press (OUP), Vol. 22, No. 5 ( 2021-09-02)
    Abstract: Internal tandem duplication (ITD) of FMS-like tyrosine kinase 3 (FLT3-ITD) constitutes an independent indicator of poor prognosis in acute myeloid leukaemia (AML). AML with FLT3-ITD usually presents with poor treatment outcomes, high recurrence rate and short overall survival. Currently, polymerase chain reaction and capillary electrophoresis are widely adopted for the clinical detection of FLT3-ITD, whereas the length and mutation frequency of ITD are evaluated using fragment analysis. With the development of sequencing technology and the high incidence of FLT3-ITD mutations, a multitude of bioinformatics tools and pipelines have been developed to detect FLT3-ITD using next-generation sequencing data. However, systematic comparison and evaluation of the methods or software have not been performed. In this study, we provided a comprehensive review of the principles, functionality and limitations of the existing methods for detecting FLT3-ITD. We further compared the qualitative and quantitative detection capabilities of six representative tools using simulated and biological data. Our results will provide practical guidance for researchers and clinicians to select the appropriate FLT3-ITD detection tools and highlight the direction of future developments in this field. Availability: A Docker image with several programs pre-installed is available at https://github.com/niu-lab/docker-flt3-itd to facilitate the application of FLT3-ITD detection tools.
    Type of Medium: Online Resource
    ISSN: 1467-5463 , 1477-4054
    URL: Article
    DOI: 10.1093/bib/bbab099
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
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  • 7
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    MTHFR and risk of stroke and heart disease in a low-folate population: a prospective study of 156 000 Chinese adults
    Oxford University Press (OUP) ; 2023
    In:  International Journal of Epidemiology Vol. 52, No. 6 ( 2023-12-25), p. 1862-1869
    Details
    In: International Journal of Epidemiology, Oxford University Press (OUP), Vol. 52, No. 6 ( 2023-12-25), p. 1862-1869
    Abstract: The relevance of folic acid for stroke prevention in low-folate populations such as in China is uncertain. Genetic studies of the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism, which increases plasma homocysteine (tHcy) levels, could clarify the causal relevance of elevated tHcy levels for stroke, ischaemic heart disease (IHD) and other diseases in populations without folic acid fortification. Methods In the prospective China Kadoorie Biobank, 156 253 participants were genotyped for MTHFR and 12 240 developed a stroke during the 12-year follow-up. Logistic regression was used to estimate region-specific odds ratios (ORs) for total stroke and stroke types, IHD and other diseases comparing TT genotype for MTHFR C677T (two thymine alleles at position 677 of MTHFR C677T polymorphism) vs CC (two cytosine alleles) after adjustment for age and sex, and these were combined using inverse-variance weighting. Results Overall, 21% of participants had TT genotypes, but this varied from 5% to 41% across the 10 study regions. Individuals with TT genotypes had 13% (adjusted OR 1.13, 95% CI 1.09–1.17) higher risks of any stroke [with a 2-fold stronger association with intracerebral haemorrhage (1.24, 1.17–1.32) than for ischaemic stroke (1.11, 1.07–1.15)] than the reference CC genotype. In contrast, MTHFR C677T was unrelated to risk of IHD or any other non-vascular diseases, including cancer, diabetes and chronic obstructive lung disease. Conclusions In Chinese adults, the MTHFR C677T polymorphism was associated with higher risks of stroke. The findings warrant corroboration by further trials of folic acid and implementation of mandatory folic acid fortification programmes for stroke prevention in low-folate populations.
    Type of Medium: Online Resource
    ISSN: 0300-5771 , 1464-3685
    URL: Article
    DOI: 10.1093/ije/dyad147
    RVK:
    XF 4100
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
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  • 8
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    How Big Data and High-Performance Computing Drive Brain Science
    Oxford University Press (OUP) ; 2019
    In:  Genomics, Proteomics & Bioinformatics Vol. 17, No. 4 ( 2019-08-01), p. 381-392
    Details
    In: Genomics, Proteomics & Bioinformatics, Oxford University Press (OUP), Vol. 17, No. 4 ( 2019-08-01), p. 381-392
    Abstract: Brain science accelerates the study of intelligence and behavior, contributes fundamental insights into human cognition, and offers prospective treatments for brain disease. Faced with the challenges posed by imaging technologies and deep learning computational models, big data and high-performance computing (HPC) play essential roles in studying brain function, brain diseases, and large-scale brain models or connectomes. We review the driving forces behind big data and HPC methods applied to brain science, including deep learning, powerful data analysis capabilities, and computational performance solutions, each of which can be used to improve diagnostic accuracy and research output. This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible, by improving data standardization and sharing, and by providing new neuromorphic insights.
    Type of Medium: Online Resource
    ISSN: 1672-0229 , 2210-3244
    URL: Article
    DOI: 10.1016/j.gpb.2019.09.003
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
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  • 9
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    Comprehensive fundamental somatic variant calling and quality management strategies for human cancer genomes
    Oxford University Press (OUP) ; 2021
    In:  Briefings in Bioinformatics Vol. 22, No. 3 ( 2021-05-20)
    Details
    In: Briefings in Bioinformatics, Oxford University Press (OUP), Vol. 22, No. 3 ( 2021-05-20)
    Abstract: Next-generation sequencing (NGS) technology has revolutionised human cancer research, particularly via detection of genomic variants with its ultra-high-throughput sequencing and increasing affordability. However, the inundation of rich cancer genomics data has resulted in significant challenges in its exploration and translation into biological insights. One of the difficulties in cancer genome sequencing is software selection. Currently, multiple tools are widely used to process NGS data in four stages: raw sequence data pre-processing and quality control (QC), sequence alignment, variant calling and annotation and visualisation. However, the differences between these NGS tools, including their installation, merits, drawbacks and application, have not been fully appreciated. Therefore, a systematic review of the functionality and performance of NGS tools is required to provide cancer researchers with guidance on software and strategy selection. Another challenge is the multidimensional QC of sequencing data because QC can not only report varied sequence data characteristics but also reveal deviations in diverse features and is essential for a meaningful and successful study. However, monitoring of QC metrics in specific steps including alignment and variant calling is neglected in certain pipelines such as the ‘Best Practices Workflows’ in GATK. In this review, we investigated the most widely used software for the fundamental analysis and QC of cancer genome sequencing data and provided instructions for selecting the most appropriate software and pipelines to ensure precise and efficient conclusions. We further discussed the prospects and new research directions for cancer genomics.
    Type of Medium: Online Resource
    ISSN: 1467-5463 , 1477-4054
    URL: Article
    DOI: 10.1093/bib/bbaa083
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2068142-2
    detail.hit.zdb_id: 2036055-1
    SSG: 12
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  • 10
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    Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2023
    Oxford University Press (OUP) ; 2023
    In:  Nucleic Acids Research Vol. 51, No. D1 ( 2023-01-06), p. D18-D28
    Details
    In: Nucleic Acids Research, Oxford University Press (OUP), Vol. 51, No. D1 ( 2023-01-06), p. D18-D28
    Abstract: The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global academic and industrial communities. With the explosive accumulation of multi-omics data generated at an unprecedented rate, CNCB-NGDC constantly expands and updates core database resources by big data archive, integrative analysis and value-added curation. In the past year, efforts have been devoted to integrating multiple omics data, synthesizing the growing knowledge, developing new resources and upgrading a set of major resources. Particularly, several database resources are newly developed for infectious diseases and microbiology (MPoxVR, KGCoV, ProPan), cancer-trait association (ASCancer Atlas, TWAS Atlas, Brain Catalog, CCAS) as well as tropical plants (TCOD). Importantly, given the global health threat caused by monkeypox virus and SARS-CoV-2, CNCB-NGDC has newly constructed the monkeypox virus resource, along with frequent updates of SARS-CoV-2 genome sequences, variants as well as haplotypes. All the resources and services are publicly accessible at https://ngdc.cncb.ac.cn.
    Type of Medium: Online Resource
    ISSN: 0305-1048 , 1362-4962
    URL: Article
    DOI: 10.1093/nar/gkac1073
    RVK:
    WA 15000
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2023
    detail.hit.zdb_id: 186809-3
    detail.hit.zdb_id: 1472175-2
    SSG: 12
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