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Auf dem Weg zur automatisierten Oligosaccharid‐ Synthese

Angewandte Chemie 2011年第50期123卷

作者： Che‐Hsiung Hsu Shang‐Cheng Hung Chung‐Yi Wu Chi‐Huey Wong The Genomics Research Center Academia Sinica Taiwan 128 Academia Road Section 2 Nankang Taipei 115 (Taiwan) Chemical Biology and Molecular Biophysics Taiwan International Graduate Program Academia Sinica (Taiwan) Institute of Bioinformatics and Structural Biology National Tsing‐Hua University Hsin‐Chu (Taiwan) Department of Chemistry The Scripps Research Institute 10550 North Torrey Pines Road La Jolla CA 92037 (USA)

Kohlenhydrate spielen eine wichtige Rolle bei biologischen Vorgängen. Das Fortschrittstempo der Kohlenhydratforschung ist jedoch relativ langsam, was unter anderem mit der Komplexität der Kohlenhydratstrukturen und dem Fehlen allgemein anwendbarer Synthesemethoden und Verfahren zur Untersuchung dieser Klasse von Biomolekülen zusammenhängt. Jüngste Fortschritte in der Synthese haben ergeben, dass viele dieser Probleme umgangen werden können. In diesem Aufsatz beschreiben wir die Methoden, die entwickelt wurden, um mit den Herausforderungen kohlenhydratvermittelter biologischer Vorgänge umzugehen. Besonderes Augenmerk wird dabei auf die Entwicklung der automatisierten Synthese von Oligosacchariden gerichtet. Darüber hinaus werden auch Kohlenhydrat‐Mikroarrays und Impfstoffe auf Kohlenhydratbasis behandelt.

关键词： Eintopfreaktionen Festphasensynthese Impfstoffe Kohlenhydrate Mikroarrays

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An integrative and multiscale approach to study dengue virus-like particle dynamics

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Biophysical Journal 2023年第3期122卷 44a-44a页

作者： Venkata Raghuvamsi Palur Gielenny Salem Fan-Chi Chen Shang-Rung Wu Peter J. Bond Day-Yu Chao Jan K. Marzinek Bioinformatics Institute (A∗STAR) Singapore Republic of Singapore Graduate Institute of Microbiology and Public Health College of Veterinary Medicine National Chung Hsing University Taichung City Taiwan Microbial Genomics PhD Program National Chung Hsing University and Academia Sinica Taichung City Taiwan Department of Dentistry & Institute of Oral Medicine National Cheng Kung University Tainan Taiwan Department of Biological Sciences National University of Singapore Singapore Republic of Singapore

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Computation of Microbial Ecosystems in Time and Space (COMETS): An open source collaborative platform for modeling ecosystems metabolism

arXiv

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arXiv 2020年

作者： Dukovski, Ilija Bajić, Djordje Chacón, Jeremy M. Quintin, Michael Vila, Jean C.C. Sulheim, Snorre Pacheco, Alan R. Bernstein, David B. Riehl, William J. Korolev, Kirill S. Sanchez, Alvaro Harcombe, William R. Segrè, Daniel Bioinformatics Program Boston University BostonMA United States Biological Design Center Boston University BostonMA United States Department of Ecology and Evolutionary Biology Yale University New HavenCT United States Microbial Sciences Institute Yale University West HavenCT United States Department of Ecology Evolution and Behavior University of Minnesota St. PaulMN United States BioTechnology Institute University of Minnesota St. PaulMN United States Department of Biotechnology and Food Science Norwegian University of Science and Technology Trondheim Norway Department of Biotechnology and Nanomedicine SINTEF Industry Trondheim Norway Environmental Genomics and Systems Biology Division Lawrence Berkeley National Laboratory BerkeleyCA United States Department of Biomedical Engineering Boston University BostonMA United States Department of Physics Boston University BostonMA United States Department of Biology Boston University BostonMA United States

Genome-scale stoichiometric modeling of metabolism has become a standard systems biology tool for modeling cellular physiology and growth. Extensions of this approach are also emerging as a valuable avenue for predicting, understanding and designing microbial communities. COMETS (Computation Of Microbial Ecosystems in Time and Space) was initially developed as an extension of dynamic flux balance analysis, which incorporates cellular and molecular diffusion, enabling simulations of multiple microbial species in spatially structured environments. Here we describe how to best use and apply the most recent version of this platform, COMETS 2, which incorporates a more accurate biophysical model of microbial biomass expansion upon growth, as well as several new biological simulation modules, including evolutionary dynamics and extracellular enzyme activity. COMETS 2 provides user-friendly Python and MATLAB interfaces compatible with the well-established COBRA models and methods, and comprehensive documentation and tutorials, facilitating the use of COMETS for researchers at all levels of expertise with metabolic simulations. This protocol provides a detailed guideline for installing, testing and applying COMETS 2 to different scenarios, with broad applicability to microbial communities across biomes and scales. Copyright © 2020, The Authors. All rights reserved.

关键词： Microorganisms

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401P Moderate-term dimethyl fumarate treatment reduces fibrosis of skeletal and cardiac muscle in in the mdx mouse model of Duchenne muscular dystrophy

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Neuromuscular Disorders 2024年 43卷 104441.272-104441.272页

作者： Timpani, C. Kourakis, S. Bagaric, R. Qi, B. Ali, B. Spiesberger, G. Boyer, R. Kandhari, N. Yan, X. Stupka, N. van Putten, M. Aartsma-Rus, A. Deveson-Lucas, D. Fischer, D. Rybalka, E. Victoria University Institute for Health & Sport Melbourne Australia Australian Institute for Musculoskeletal Science Inherited and Acquired Myopathy Program St Albans Australia The University of Melbourne Department of Medicine - Western Health Melbourne Medical School St Albans Australia Monash University Monash Genomics and Bioinformatics Platform Biomedical Discovery Institute Clayton Australia Australian Institute for Musculoskeletal Science Sarcopenia Research Program St Albans Australia Leiden University Medical Center Department of Human Genetics Leiden Netherlands University Children's Hospital of Basel Division of Neuropediatric and Developmental Medicine Basel Switzerland

Duchenne muscular dystrophy (DMD), a fatal inherited neuromuscular disease, is associated with hyper-immune responsivity secondary to the intense muscle degeneration caused by primary dystrophin deficiency. Corticosteroids (e.g., prednisone (PRED)) are potent immunomodulators that have been used in standard care for decades to control this aspect. However, for many patients, the side-effect profile is significant despite prolonging ambulation, which can limit clinical utility. Other immunomodulatory drugs could have a better benefit to side-effect profile. We recently demonstrated short-term treatment with repurposed dimethyl fumarate (DMF), an alternative pharmacological immunomodulator indicated for multiple sclerosis, more selectively modulates the DMD disease program compared to PRED. Here, we aimed to evaluate the therapeutic potential of moderate-term DMF treatment in dystrophic mdx mice. Male mdx mice were gavaged daily from 3 weeks of age with either vehicle (0.5% methylcellulose; VEH), DMF (100mg/kg), PRED (5mg/kg) or combinatorial DMF+PRED until 8 weeks of age. WT controls received daily VEH gavage. Bi-weekly treadmill running was used to aggravate the mdx phenotype from 4 weeks of age. At the experimental endpoint, grip strength and motor co-ordination (rotarod) were assessed. Then mice were sacrificed, and muscle damage, fibrosis and inflammation were quantified in the quadriceps and heart using H&E, Masson's Trichrome and pan macrophage CD68+ marker immuno-/histology staining, respectively. The quadriceps transcriptome was also assessed via bulk RNA sequencing. In mdx mice, DMF was the only treatment to improve a functional index (grip strength). DMF treatment alone improved muscle quality by reducing fibrosis of the quadriceps and heart. However, at 8 weeks age, a more stable phase of murine disease, it had no effect on the unhealthy:healthy tissue ratio. In combination, DMF+PRED treatment notably increased fibrosis of quadriceps muscle. This may be as

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Corrigendum to "Comparative genome analysis of Lactobacillus plantarum GB-LP3 provides candidates of survival-related genetic factors" [Infect. Genet. Evol. 9 (2017) 218-226]

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Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases 2018年 59卷 186页

作者： Soomin Jeon Jaehoon Jung Kwondo Kim DongAhn Yoo Chanho Lee Jungsun Kang Kyungjin Cho Dae-Kyung Kang Woori Kwak Sook Hee Yoon Heebal Kim Seoae Cho Department of Agricultural Biotechnology and Research Institute of Population Genomics Seoul National University Seoul 151-742 Republic of Korea. CNK genomics Main Bldg. #514 SNU Research Park Seoul National University Mt.4-2 NakSeoungDae Seoul 151-919 Gwanakgu Republic of Korea Interdisciplinary Program in Bioinformatics Seoul National University Seoul 151-742 Republic of Korea. Genebiotech Co. Ltd. Seocho-Gu Seoul 137-787 Republic of Korea. Department of Animal Resources Science Dankook University Cheonan Republic of Korea. Department of Agricultural Biotechnology and Research Institute of Population Genomics Seoul National University Seoul 151-742 Republic of Korea CNK genomics Main Bldg. #514 SNU Research Park Seoul National University Mt.4-2 NakSeoungDae Seoul 151-919 Gwanakgu Republic of Korea. Electronic address: seoae@***.

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Functional Analysis of an FHOD3 Founder Variant Causing Hypertrophic Cardiomyopathy in the Balkans Population

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Heart, Lung and Circulation 2024年 33卷 S97-S98页

作者： R. Bagnall S. Li G. Ranpura M. Holliday B. Hanna J. Ingles S. Kumar C. Semsarian S. Lim Bioinformatics and Molecular Genetics Centenary Institute Newtown NSW Australia The University of Sydney Sydney NSW Australia Agnes Ginges Centre for Molecular Cardiology Centenary Institute Newtown NSW Australia Department of Medical Genetics Westmead Hospital Sydney NSW Australia Genomics and Inherited Disease Program Garvan Institute of Medical Research Sydney NSW Australia Department of Cardiology Royal Prince Alfred Hospital Sydney NSW Australia Department of Cardiology Westmead Hospital Sydney NSW Australia

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Artificial intelligence-driven genotype–epigenotype–phenotype approaches to resolve challenges in syndrome diagnostics

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eBioMedicine 2025年 115卷 105677-105677页

作者： Mak, Christopher C.Y. Klinkhammer, Hannah Choufani, Sanaa Reko, Nikola Christman, Angela K. Pisan, Elise Chui, Martin M.C. Lee, Mianne Leduc, Fiona Dempsey, Jennifer C. Sanchez-Lara, Pedro A. Bombei, Hannah M. Bernat, John A. Faivre, Laurence Mau-Them, Frederic Tran Palafoll, Irene Valenzuela Canham, Natalie Sarkar, Ajoy Zarate, Yuri A. Callewaert, Bert Bukowska-Olech, Ewelina Jamsheer, Aleksander Zankl, Andreas Willems, Marjolaine Duncan, Laura Isidor, Bertrand Cogne, Benjamin Boute, Odile Vanlerberghe, Clémence Goldenberg, Alice Stolerman, Elliot Low, Karen J. Gilard, Vianney Amiel, Jeanne Lin, Angela E. Gordon, Christopher T. Doherty, Dan Krawitz, Peter M. Weksberg, Rosanna Hsieh, Tzung-Chien Chung, Brian H.Y. Department of Paediatrics and Adolescent Medicine School of Clinical Medicine The University of Hong Kong Hong Kong SAR China Institute for Genomic Statistics and Bioinformatics University Hospital Bonn Rheinische Friedrich-Wilhelms-Universität Bonn Bonn Germany Institute for Medical Biometry Informatics and Epidemiology University Hospital Bonn Rheinische Friedrich-Wilhelms-Universität Bonn Bonn Germany Genetics and Genome Biology Program Research Institute The Hospital for Sick Children Toronto M5G 1X8 ON Canada Department of Pediatrics University of Washington Seattle 98195 WA United States Laboratory of Embryology and Genetics of Human Malformations Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1163 Institut Imagine Université Paris Cité Paris 75015 France CHU Lille Centre de Référence Anomalies du Développement et Syndromes Malformatifs Lille F-59000 France Department of Pediatrics Cedars-Sinai Medical Center Los Angeles CA United States Division of Medical Genetics and Genomics Stead Family Department of Pediatrics University of Iowa Hospitals Iowa City IA United States Centre de Génétique et Centre de Référence Anomalies du Développement et Syndromes Malformatifs FHU TRANSLAD Institut GIMI Hôpital d'Enfants CHU Dijon-Bourgogne Dijon France Equipe GAD INSERM UMR1231 Université de Bourgogne Franche Comté Dijon France UF 6254 Innovation en diagnostic Génomique des Maladies Rares Centre Hospitalier Universitaire de Dijon Dijon France Department of Clinical and Molecular Genetics University Hospital Vall d'Hebron and Medicine Genetics Group Valle Hebron Research Institute Barcelona Spain Liverpool Centre for Genomic Medicine Liverpool Women's Hospital Crown Street Liverpool United Kingdom Department of Clinical Genetics Nottingham University Hospitals National Health Service Trust Nottingham NG5 1PB United Kingdom Section of Genetics and Metabolism University of Arkansas for Medical Sciences Little Rock 72701 AR Uni

Background: Decisions to split two or more phenotypic manifestations related to genetic variations within the same gene can be challenging, especially during the early stages of syndrome discovery. Genotype-based diagnostics with artificial intelligence (AI)-driven approaches using next-generation phenotyping (NGP) and DNA methylation (DNAm) can be utilized to expedite syndrome delineation within a single gene. Methods: We utilized an expanded cohort of 56 patients (22 previously unpublished individuals) with truncating variants in the MN1 gene and attempted different methods to assess plausible strategies to objectively delineate phenotypic differences between the C-Terminal Truncation (CTT) and N-Terminal Truncation (NTT) groups. This involved transcriptomics analysis on available patient fibroblast samples and AI-assisted approaches, including a new statistical method of GestaltMatcher on facial photos and blood DNAm analysis using a support vector machine (SVM) model. Findings: RNA-seq analysis was unable to show a significant difference in transcript expression despite our previous hypothesis that NTT variants would induce nonsense mediated decay. DNAm analysis on nine blood DNA samples revealed an episignature for the CTT group. In parallel, the new statistical method of GestaltMatcher objectively distinguished the CTT and NTT groups with a low requirement for cohort number. Validation of this approach was performed on syndromes with known DNAm signatures of SRCAP, SMARCA2 and ADNP to demonstrate the effectiveness of this approach. Interpretation: We demonstrate the potential of using AI-based technologies to leverage genotype, phenotype and epigenetics data in facilitating splitting decisions in diagnosis of syndromes with minimal sample requirement. Funding: The specific funding of this article is provided in the acknowledgements section. © 2025 The Authors

关键词： GestaltMatcher MCTT Methylation MN1 Splitting Support vector machine

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17P Assessment of the Intratumoral Heterogeneity in Metastatic Breast Cancer (Mbc) Through the Analysis of the Frequency of Pik3Ca Mutant Alleles

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Annals of Oncology 2012年 23卷 ii19-ii20页

作者： L. De Mattos-Arruda J. Cortes A. Sánchez-Pla C. Aura V. Ortega J. Jimenez C. Saura J. Tabernero J. Seoane A. Vivancos Medical Oncology Vall d'Hebron University Hospital Barcelona SPAIN Breast Cancer Program Vall d'Hebron University Hospital Barcelona SPAIN Statistics and Bioinformatics Unit Institut de Recerca of Vall d'Hebron University Hospital Barcelona SPAIN Pathology Department Vall d'Hebron University Hospital. Barcelona SPAIN Gene Expression and Cancer Laboratory Vall d'Hebron Institute of Oncology Barcelona SPAIN Cancer Genomics Laboratory Vall d'Hebron Institute of Oncology Barcelona SPAIN

Introduction The phosphatidylinositol-3-kinase (PI3K) pathway has an important prognostic and predictive significance in MBC. Mutations of PI3KCA could be heterogeneously distributed within the tumor and this could have clinical implications. In this study, we sought to assess the frequency of PIK3CA mutant alleles in different MBC phenotypes taking into account that formalin-fixed paraffin-embedded (FFPE) samples contain non-tumor and tumor areas (TA). Methods The OncoCarta Panel v1.0 (Sequenom) was used to profile 67 consecutive MBC FFPE tumor samples. The relative ratio between the mutant and wild-type alleles (% mutant allele, mA) of PIK3CA mutations was quantified by the MassARRAY® System. The viable tumor zone was scored to determine the TA. Patients (pts) were stratified (luminal, LUM; HER2-positive, HER2; triple negative, TN). Results 26.8% of MBC pts had PIK3CA mutation. PIK3CA mutation in LUM tumors was more frequent than non-LUM (40% vs.15 %, p = 0.047) ( table 1 ). The mean PIK3CA mA (p = 0.029) and the mean TA (p = 0.014) differed among MBC phenotypes. There was a linear relation between mA and TA for the LUM tumors (r =0.71), but when HER2 and TN tumors were also considered, this relation was less substantial (r = 0.53). Conclusion We could assess the intratumoral heterogeneity through the PIK3CA mA/TA ratio in the analyzed tumor samples. In the case of a homogeneous cellular distribution of heterozygous PIK3CA mutations within the tumor mass, the mA/TA ratio should be around 0.5. Interestingly, the mA/TA ratio of PIK3CA in LUM tumors was close to 0.5 while in the HER2 and TN tumors the ratio was lower. This suggests that LUM tumors might be more homogeneous regarding PIK3CA mutation than HER2 and TN. Therefore, PIK3CA oncogenic activation could be an early hit for tumor initiation or progression in LUM tumors and the use of PI3K inhibitors with endocrine therapy could have a greater clinical impact. Table 1 . PIK3CA mutant frequencies in MBC pts. Empt

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Identification of rare coding variants associated with Alzheimer’s disease.

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Alzheimer's & Dementia 2023年第S12期19卷

作者： Zainab Khurshid Lindsay A. Farrer Xiaoling Zhang Eden R. Martin Amanda B Kuzma John Farrell Tong Tong Congcong Zhu Adam C. Naj Laura B Cantwell Otto Valladares Li-San Wang Kathryn L. Lunetta Gerald D. Schellenberg Jonathan L. Haines Yuk Yee Leung Margaret A. Pericak-Vance Boston University Chobanian & Avedisian School of Medicine Boston MA USA Boston University Bioinformatics Program Boston MA USA John P. Hussman Institute for Human Genomics Miller School of Medicine Miami FL USA Penn Neurodegeneration Genomics Center Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Medicine (Biomedical Genetics) Boston University Chobanian & Avedisian School of Medicine Boston MA USA Penn Neurodegeneration Genomics Center Department of Pathology and Laboratory Medicine University of Pennsylvania Perelman School of Medicine Philadelphia PA USA University of Pennsylvania Perelman School of Medicine Philadelphia PA USA Penn Neurodegeneration Genomics Center University of Pennsylvania Perelman School of Medicine Philadelphia PA USA Department of Biostatistics Boston University School of Public Health Boston MA USA Department of Genetics and Genome Sciences Case Western Reserve University School of Medicine Cleveland OH USA University of Miami Miller School of Medicine Miami FL USA

Background Previous whole exome sequencing (WES) studies of Alzheimer’s disease (AD) have identified genome-wide significant associations with rare variants in several novel genes and highlighted the need for investigations in larger samples. We combined WES and whole genome sequencing (WGS) data assembled by the Alzheimer Disease Sequencing Project (ADSP) to increase the power for detecting associations of AD with rare variants in gene coding regions. Method We developed an efficient computational pipeline to perform both pre-merging and post-merging genotype, variant and sample-level quality control (QC) on WGS data containing 16,905 individuals and WES data for 20,504 individuals. The resultant sample included participants from European (EA, 11,279 AD cases, 8,924 controls), African American (AA, 2,757 AD cases, 4,336 controls), and Caribbean Hispanic (CH 1,438 AD cases, 3,256 controls) ancestries. We employed GENESIS to test association of AD with 250,465 bi-allelic QC’d variants using a logistic model including covariates for age, sex, exome capture kit, read length, and ancestry principal components (PCs). Result In the total sample, variants from APOE and other known AD genes including SORL1 (P = 5.30×10-7), NECTIN2 (P = 6.94×10-7), and TREM2 R47H (P = 2.34×10-13) crossed or neared the study-wide significance (SWS) threshold of P = 2.00×10-7 (0.05/250,465). SWS or borderline significant associations were also found with variants in several novel loci including TKTL2 (P = 2.35×10-8), D2HGDH , (P = 1.09×10-7) , CECR1 (P = 4.02×10-7), PDHA2 (P = 2.76×10-7), GOLGA1 (P = 1.72×10-7), CYLD (P = 1.84×10-7), and RP11-243M5.4 (P = 1.37×10-7). PSEN1 missense mutation G206A (rs63750082) previously associated with early onset AD in the CH group, was significantly associated with late onset AD in the same population (P = 1.58×10-13). SWS association of AD with APOE was observed in all groups. Significant associations were also observed with variants in SERPINB8 (P = 3.77×1

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Uncovering the conformational dynamics of dengue virus and its virus-like particles as novel vaccine candidates

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Biophysical Journal 2023年第3期122卷 508a-509a页

作者： Jan K. Marzinek Venkata Raghuvamsi Palur Gielenny Salem Fan-Chi Chen Shang-Rung Wu Peter J. Bond Day-Yu Chao Bioinformatics Institute Agency for Science Technology and Research Singapore Republic of Singapore Graduate Institute of Microbiology and Public Health College of Veterinary Medicine National Chung Hsing University Taichung City Taiwan Microbial Genomics Ph.D. Program National Chung Hsing University Taichung City Taiwan Academia Sinica Taipei Taiwan Department of Dentistry Institute of Oral Medicine National Cheng Kung University Tainan Taiwan Department of Biological Sciences National University of Singapore Singapore Republic of Singapore

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