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Derivatives (halogen, nitro and amino) of 8-hydroxyquinoline with highly potent antimicrobial and antioxidant activities

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Biochemistry and Biophysics Reports 2016年 6卷 135-141页

作者： Cherdtrakulkiat, Rungrot Boonpangrak, Somchai Sinthupoom, Nujarin Prachayasittikul, Supaluk Ruchirawat, Somsak Prachayasittikul, Virapong Department of Clinical Microbiology and Applied Technology Faculty of Medical Technology Mahidol University Bangkok 10700 Thailand Center for Innovation Development and Technology Transfer Faculty of Medical Technology Mahidol University Bangkok 10700 Thailand Center of Data Mining and Biomedical Informatics Faculty of Medical Technology Mahidol University Bangkok 10700 Thailand Laboratory of Medicinal Chemistry Chulabhorn Research Institute and Program in Chemical Biology Chulabhorn Graduate Institute Bangkok 10210 Thailand Center of Excellence on Environmental Health and Toxicology Commission on Higher Education (CHE) Ministry of Education Thailand

8-Hydroxyquinoline (8HQ) compounds have been reported to possess diverse bioactivities. In recent years, drug repositioning has gained considerable attention in drug discovery and development. Herein, 8HQ (1) and its derivatives (2-9) bearing various substituents (amino, nitro, cyano and halogen) were investigated for their antimicrobial against 27 microorganisms (agar dilution method) and antioxidant (DPPH method) activities. The parent 8HQ (1) exerted a highly potent antimicrobial activity against Gram-positive bacteria including diploid fungi and yeast with MIC values in the range of 3.44-13.78 μM. Moreover, the halogenated 8HQ, especially 7-bromo-8HQ (4) and clioquinol (6), displayed a high antigrowth activity against Gram-negative bacteria compared with the parent compound (1). Apparently, the derivatives with a relatively high safely index, e.g., nitroxoline (2), exhibited strong antibacterial activity against Aeromonas hydrophila (MIC=5.26 μM) and selectively inhibited the growth of P. aeruginosa with the MIC value of 84.14 μM;cloxyquin (3) showed a strong activity against L. monocytogenes and P. shigelloides with MIC values of 5.57 and 11.14 μM, respectively. Most compounds displayed an antioxidant activity. Specifically, 5-amino-8HQ (8) was shown to be the most potent antioxidant (IC₅₀=8.70 μM) compared with the positive control (α-tocopherol) with IC₅₀ of 13.47 μM. The findings reveal that 8HQ derivatives are potential candidates to be further developed as antimicrobial and antioxidant agents. © 2016 The Authors.

关键词： 8-Hydroxyquinoline Antimicrobial Antioxidant Clioquinol Cloxyquin Nitroxoline

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Fanconi anemia protein FANCD2 inhibits TRF1 polyADP-ribosylation through tankyrase1-dependent manner

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Genome Integrity 2011年第1期2卷 1-10页

作者： Lyakhovich, Alex Ramirez, Maria J. Castellanos, Andres Castella, Maria Simons, Amanda M. Parvin, Jeffrey D. Surralles, Jordi Department of Genetics and Microbiology Universitat Autonoma de Barcelona Bellaterra Barcelona 08193 Edifici C Spain Cancer and Stem Cell Research Program Duke-NUS Graduate Medical School 169857 College Rd. 6 Singapore Centre for Biomedical Network Research on Rare Diseases (CIBERER) Instituto de Salud Carlos III Spain Fred Hutchinson Cancer Research Center Seattle United States Department of Pathology Harvard Medical School and Brigham and Women's Hospital Boston MA United States Department of Biomedical Informatics The Ohio State University Columbus OH 460 W. 12th Avenue United States

Background: Fanconi anemia (FA) is a rare autosomal recessive syndrome characterized by developmental abnormalities, progressive bone marrow failure, and predisposition to cancer. The key FA protein FANCD2 crosstalks with members of DNA damage and repair pathways that also play a role at telomeres. Therefore, we investigated whether FANCD2 has a similar involvement at ***: We reveal that FANCD2 may perform a novel function separate to the FANCD2/BRCA pathway. This function includes FANCD2 interaction with one of the telomere components, the PARP family member tankyrase-1. Moreover, FANCD2 inhibits tankyrase-1 activity in vitro. In turn, FANCD2 deficiency increases the polyADP-ribosylation of telomere binding factor ***: FANCD2 binding and inhibiting tankyrase-1PARsylation at telomeres may provide an additional step within the FA pathway for the regulation of genomic integrity. © 2011 Lyakhovich et al;licensee BioMed Central Ltd.

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Understanding ADC variation by fat content effect using a dual-function MRI phantom

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European Radiology Experimental 2024年第1期8卷 19页

作者： Liu, Yi-Jui Tsai, Tung-Sheng Li, Ya-Hui Peng, Jo-Hua Chang, Hing-Chiu Peng, Hsu-Hsia Lee, Ying-Chieh Lee, Tung-Yang Liou, Chang-Hsien Lin, Tz-Feng Chew, Fatt-Yang Chou, Ruey-Hwang Juan, Chun-Jung Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital 199 Sec. 1 Xinglong Rd. Hsinchu County Zhubei City 302 Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Biomedical Engineering Chinese University of Hong Kong Hong Kong Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Institute of Nuclear Engineering and Science National Tsing Hua University Hsinchu Taiwan Department of Fiber and Composite Materials Feng Chia University Taichung Taiwan Department of Medical Imaging China Medical University Hospital Taichung Taiwan Department of Radiology School of Medicine China Medical University Taichung Taiwan Graduate Institute of Biomedical Sciences China Medical University Taichung 406 Taiwan Center for Molecular Medicine China Medical University Hospital Taichung Taiwan Department of Medical Laboratory and Biotechnology Asia University Taichung Taiwan

Background: A dual-function phantom designed to quantify the apparent diffusion coefficient (ADC) in different fat contents (FCs) and glass bead densities (GBDs) to simulate the human tissues has not been documented yet. We propose a dual-function phantom to quantify the FC and to measure the ADC at different FCs and different GBDs. Methods: A fat-containing diffusion phantom comprised by 30 glass-bead-containing fat-water emulsions consisting of six different FCs (0, 10, 20, 30, 40, and 50%) multiplied by five different GBDs (0, 0.1, 0.25, 0.5, and 1.0 g/50 mL). The FC and ADC were measured by the “iterative decomposition of water and fat with echo asymmetry and least squares estimation-IQ,” IDEAL-IQ, and single-shot echo-planar diffusion-weighted imaging, SS-EP-DWI, sequences, respectively. Linear regression analysis was used to evaluate the relationship among the fat fraction (FF) measured by IDEAL-IQ, GBD, and ADC. Results: The ADC was significantly, negatively, and linearly associated with the FF (the linear slope ranged from -0.005 to -0.017, R² = 0.925 to 0.986, all p < 0.001). The slope of the linear relationship between the ADC and the FF, however, varied among different GBDs (the higher the GBD, the lower the slope). ADCs among emulsions across different GBDs and FFs were overlapped. Emulsions with low GBDs plus high FFs shared a same lower ADC range with those with median or high GBDs plus median or lower FFs. Conclusions: A novel dual-function phantom simulating the human tissues allowed to quantify the influence of FC and GBD on ADC. Relevance statement: The study developed an innovative dual-function MRI phantom to explore the impact of FC on ADC variation that can affect clinical results. The results revealed the superimposed effect on FF and GBD density on ADC measurements. Key points: • A dual-function phantom made of glass bead density (GBD) and fat fraction (FF) emulsion has been developed. • Apparent diffusion coefficient (ADC) values

关键词： Adipose tissue Diffusion magnetic resonance imaging Phantoms (imaging) Quality assurance (healthcare) Quality control

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Microarray analysis of genes associated with cell surface NIS protein levels in breast cancer

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BMC Research Notes 2011年第1期4卷 1-14页

作者： Beyer, Sasha J. Zhang, Xiaoli Jimenez, Rafael E. Lee, Mei-Ling T. Richardson, Andrea L. Huang, Kun Jhiang, Sissy M. Integrated Biomedical Sciences Graduate Program Ohio State University Columbus OH 43210 United States Department of Physiology and Cell Biology Ohio State University Columbus OH 43210 United States Center for Biostatistics Ohio State University Columbus OH 43210 United States Department of Anatomic Pathology Mayo Clinic Rochester MN 55901 United States Department of Epidemiology and Biostatistics University of Maryland College Park MD 20742 United States Department of Pathology Brigham and Women's Hospital Harvard Medical School Boston MA 02115 United States Department of Biomedical Informatics Ohio State University Columbus OH 43210 United States

Background: Na+/I- symporter (NIS)-mediated iodide uptake allows radioiodine therapy for thyroid cancer. NIS is also expressed in breast tumors, raising potential for radionuclide therapy of breast cancer. However, NI... 详细信息

Background: Na⁺/I^- symporter (NIS)-mediated iodide uptake allows radioiodine therapy for thyroid cancer. NIS is also expressed in breast tumors, raising potential for radionuclide therapy of breast cancer. However, NIS expression in most breast cancers is low and may not be sufficient for radionuclide therapy. We aimed to identify biomarkers associated with NIS expression such that mechanisms underlying NIS modulation in human breast tumors may be elucidated. Methods. Published oligonucleotide microarray data within the National Center for Biotechnology Information Gene Expression Omnibus database were analyzed to identify gene expression tightly correlated with NIS mRNA level among human breast tumors. NIS immunostaining was performed in a tissue microarray composed of 28 human breast tumors which had corresponding oligonucleotide microarray data available for each tumor such that gene expression associated with cell surface NIS protein level could be identified. Results and Discussion. NIS mRNA levels do not vary among breast tumors or when compared to normal breast tissues when detected by Affymetrix oligonucleotide microarray platforms. Cell surface NIS protein levels are much more variable than their corresponding NIS mRNA levels. Despite a limited number of breast tumors examined, our analysis identified cysteinyl-tRNA synthetase as a biomarker that is highly associated with cell surface NIS protein levels in the ER-positive breast cancer subtype. Conclusions: Further investigation on genes associated with cell surface NIS protein levels within each breast cancer molecular subtype may lead to novel targets for selectively increasing NIS expression/function in a subset of breast cancers patients. © 2011 Jhiang et al;licensee BioMed Central Ltd.

关键词： Breast Cancer Breast Tumor Oligonucleotide Microarray Breast Cancer Molecular Subtype Cars Protein

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Cardiorespiratory fitness level correlates inversely with excess post-exercise oxygen consumption after aerobic-type interval training

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BMC Research Notes 2012年第1期5卷 1-4页

作者： Matsuo, Tomoaki Ohkawara, Kazunori Seino, Satoshi Shimojo, Nobutake Yamada, Shin Ohshima, Hiroshi Tanaka, Kiyoji Mukai, Chiaki Space Biomedical Research Office Japan Aerospace Exploration Agency (JAXA) Tsukuba Ibaraki 305-8505 2-1-1 Sengen Japan Faculty of Informatics and Engineering University of Electro-Communications Chofu Tokyo 182-8585 1-5-1 Chofugaoka Japan Health Promotion and Exercise Program National Institute of Health and Nutrition Shinjuku Tokyo 162-8636 1-23-1 Toyama Japan Graduate School of Comprehensive Human Sciences University of Tsukuba Tsukuba Ibaraki 305-8574 1-1-1 Tennodai Japan

Background: The purpose of this study was to reveal any association between cardiorespiratory fitness level and excess post-exercise oxygen consumption (EPOC) using three cycling protocols with varying degrees of exercise intensity, i.e., sprint interval training (SIT), high-intensity interval aerobic training (HIAT), and continuous aerobic training (CAT). Findings. Ten healthy men, aged 20 to 31 years, attended a cross-over experiment and completed three exercise sessions: SIT consisting of 7 sets of 30-s cycling at 120% VO₂ with a 15-s rest between sets;HIAT consisting of 3 sets of 3-min cycling at 80∼90% VO₂ with a 2-min active rest at 50% VO₂ between sets;and CAT consisting of 40 min of cycling at 60∼65% VO₂. During each session, resting VO₂, exercise VO₂, and a 180-min post-exercise VO₂ were measured. The net exercise VO ₂ during the SIT, HIAT, and CAT averaged 14.7 ± 1.5, 31.8 ± 4.1, and 71.1 ± 10.0 L, and the EPOCs averaged 6.8 ± 4.0, 4.5 ± 3.3, and 2.9 ± 2.8 L, respectively. The EPOC with SIT was greater than with CAT (P < 0.01) and HIAT (P = 0.12). Correlation coefficients obtained between subjects' VO₂ and the ratio of EPOC to net exercise VO₂ for SIT, HIAT, and CAT were -0.61 (P = 0.06), -0.79 (P < 0.01), and -0.42 (P = 0.23), respectively. Conclusions: Our data suggest that cardiorespiratory fitness level correlates negatively with the magnitude of EPOC, especially when performing aerobic-type interval training. © 2012 Matsuo et al.;licensee BioMed Central Ltd.

关键词： Aerobic fitness Cycling Energy expenditure Exercise physiology Maximal oxygen consumption

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IntLIM: Integration using linear models of metabolomics and gene expression data

arXiv

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arXiv 2018年

作者： Siddiqui, Jalal K. Baskin, Elizabeth Liu, Mingrui Cantemir-Stone, Carmen Z. Zhang, Bofei Bonneville, Russell McElroy, Joseph P. Coombes, Kevin R. Mathé, Ewy A. Department of Biomedical Informatics College of Medicine Ohio State University ColumbusOH United States Biomedical Sciences Graduate Program Ohio State University ColumbusOH United States Comprehensive Cancer Center Department of Internal Medicine Ohio State University ColumbusOH United States Center for Biostatistics Ohio State University ColumbusOH United States

Background: Integration of transcriptomic and metabolomic data improves functional interpretation of disease-related metabolomic phenotypes, and facilitates discovery of putative metabolite biomarkers and gene targets. For this reason, these data are increasingly collected in large (> 100 participants) cohorts, thereby driving a need for the development of user-friendly and open-source methods/tools for their integration. Of note, clinical/translational studies typically provide snapshot (e.g. one time point) gene and metabolite profiles and, oftentimes, most metabolites measured are not identified. Thus, in these types of studies, pathway/network approaches that take into account the complexity of transcript-metabolite relationships may neither be applicable nor readily uncover novel relationships. With this in mind, we propose a simple linear modeling approach to capture disease-(or other phenotype) specific gene-metabolite associations, with the assumption that co-regulation patterns reflect functionally related genes and metabolites. Results: The proposed linear model, metabolite ~ gene + phenotype + gene:phenotype, specifically evaluates whether gene-metabolite relationships differ by phenotype, by testing whether the relationship in one phenotype is significantly different from the relationship in another phenotype (via a statistical interaction gene:phenotype p-value). Statistical interaction p-values for all possible gene-metabolite pairs are computed and significant pairs are then clustered by the directionality of associations (e.g. strong positive association in one phenotype, strong negative association in another phenotype). We implemented our approach as an R package, IntLIM, which includes a user-friendly R Shiny web interface, thereby making the integrative analyses accessible to non-computational experts. We applied IntLIM to two previously published datasets, collected in the NCI-60 cancer cell lines and in human breast tumor and non-tumor tissue,

关键词： Integration

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Enhancing Automated Microorganism Classification: A Study on the Influence of Compression, Non-Uniform Scaling, and Data Augmentation Using Deep Learning

SSRN

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SSRN 2024年

作者： Boukouvalas, Dimitria Theophanis Bissaco, Márcia A.S. Dellê, Humberto Deana, Alessandro M. Belan, Peterson A. de Araújo, Sidnei Alves Universidade Nove de Julho Informatics and Knowledge Management Graduate Program Rua Vergueiro 235/249 SP São Paulo01504-001 Brazil Universidade de Mogi das Cruzes Biomedical Engineering Graduate Program Av. Dr. Cândido Xavier de Almeida e Souza 200 Mogi das Cruzes SP São Paulo08780-911 Brazil Universidade Nove de Julho Medicine Graduate Program Rua Vergueiro 235/249 SP São Paulo01504-001 Brazil

With the advent of "Laboratory 4.0", a concept that represents the recent technological breakthroughs in laboratory automation, there is an increasing demand for solutions that can automate, standardize, and enhance the accuracy and speed of microorganism classification. One promising approach is the use of convolutional neural networks (CNNs), a powerful deep learning technique that has shown significant results in biomedical image analysis. However, its application in microorganism classification is still nascent mainly due to the unavailability of extensive datasets, which is a basic requirement to ensure generalization ability in learning CNNs. This study aims to fill a significant gap in the literature by exploring the influence of factors such as image compression, non-uniform scaling, and data augmentation on the performance of CNNs, specifically when using small image datasets of microorganisms. We focus on two CNN architectures, AlexNet and DenseNet-121, which have shown promising results in previous microorganism classification studies. Our experiments reveal that certain factors like the type of data compression and non-uniform scaling applied to the images can negatively impact the performance of CNNs. On the other hand, data augmentation techniques such as mirroring, rotation, and noise addition can enhance their performance. By utilizing training datasets and optimized parameters based on our findings, we were able to achieve classification accuracies of 98.61% and 99.82% with AlexNet and DenseNet-121, respectively, surpassing the results reported in current state-of-the-art studies. This research has significant implications for Laboratory 4.0, potentially reducing dataset preparation and CNN training time, lowering computational costs, and improving the consistency and accuracy of microorganism classification. It paves the way for more efficient and accurate microorganism classification methods in automated laboratories. © 2024, The Authors. All righ

关键词： Classification (of information)

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Session introduction: Characterizing the importance of environmental exposures, interactions between the environment and genetic architecture, and genetic interactions: New methods for understanding the etiology of complex traits and disease 20

Session introduction: Characterizing the importance of envir...

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20th Pacific Symposium on Biocomputing, PSB 2015

作者： Hall, Molly A. Verma, Shefali Setia Wall, Dennis P. Moore, Jason H. Keating, Brendan Campbell, Daniel B. Gibson, Gregory Asselbergs, Folkert W. Pendergrass, Sarah Center for Systems Genomics Department of Biochemistry and Molecular Biology Pennsylvania State University University ParkPA16802 United States Department of Pediatrics Division of Systems Medicine Program in Biomedical Informatics Stanford University StanfordCA94305 United States Institute for Quantitative Biomedical Sciences Department of Genetics Geisel School of Medicine Dartmouth College HanoverNH03755 United States Center for Applied Genomics Children's Hospital of Philadelphia PhiladelphiaPA19104 United States Department of Psychiatry and the Behavioral Sciences Zilkha Neurogenetic Institute Center for Genomic Psychiatry Neuroscience Graduate Program Keck School of Medicine University of Southern California Los AngelesCA90089 United States Center for Integrative Genomics Department of Biology Georgia Institute of Technology AtlantaGA30332 United States Department of Cardiology Division of Heart and Lungs University Medical Center Ultrecht Netherlands

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Challenges and Opportunities for Developing More Generalizable Polygenic Risk Scores

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biomedical Data Science 1000年第1期5卷 293-320页

作者： Ying Wang Kristin Tsuo Masahiro Kanai Benjamin M. Neale Alicia R. Martin 2Stanley Center for Psychiatric Research and Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge Massachusetts USA 1Analytic and Translational Genetics Unit Massachusetts General Hospital Boston Massachusetts USA email: armartin@*** 3Biological and Biomedical Sciences Harvard Medical School Boston Massachusetts USA 4Department of Biomedical Informatics Harvard Medical School Boston Massachusetts USA 5Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan

Polygenic risk scores (PRS) estimate an individual's genetic likelihood of complex traits and diseases by aggregating information across multiple genetic variants identified from genome-wide association studies. PRS can predict a broad spectrum of diseases and have therefore been widely used in research settings. Some work has investigated their potential applications as biomarkers in preventative medicine, but significant work is still needed to definitively establish and communicate absolute risk to patients for genetic and modifiable risk factors across demographic groups. However, the biggest limitation of PRS currently is that they show poor generalizability across diverse ancestries and cohorts. Major efforts are underway through methodological development and data generation initiatives to improve their generalizability. This review aims to comprehensively discuss current progress on the development of PRS, the factors that affect their generalizability, and promising areas for improving their accuracy, portability, and implementation.

关键词： polygenic risk scores (PRS) genetic risk prediction diverse ancestry populations PRS generalizability clinical translation of PRS

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Cellular deconvolution of GTEx tissues powers discovery of disease and cell-type associated regulatory variants (vol 11, 955, 2020)

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NATURE COMMUNICATIONS 2020年第1期11卷 955页

作者： Donovan, Margaret K. R. D'Antonio-Chronowska, Agnieszka D'Antonio, Matteo Frazer, Kelly A. University of California San Diego Bioinformatics and Systems Biology Graduate Program La Jolla USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) University of California San Diego Department of Biomedical Informatics La Jolla USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) University of California San Diego Department of Pediatrics and Rady Children’s Hospital La Jolla USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) University of California San Diego Department of Pediatrics and Rady Children’s Hospital La Jolla USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242) University of California San Diego Institute for Genomic Medicine La Jolla USA (GRID:grid.266100.3) (ISNI:0000 0001 2107 4242)

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

关键词： Gene expression Genetic association study RNA sequencing

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