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Total Marrow and Lymphoid Irradiation (TMLI) at a Dose of 2000cGy in Combination with Post-Transplant Cyclophosphamide (PTCy)-Based Graft Versus Host Disease (GvHD) Prophylaxis Is Safe and Associated with Favorable GvHD-Free/Relapse-Free Survival at 1 Year in Patients with Acute Myeloid Leukemia (AML)

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BLOOD 2020年 136卷 41-42页

作者： Stein, Anthony S. Al Malki, Monzr M. Yang, Dongyun Palmer, Joycelynne Tsai, Ni-Chun Aldoss, Ibrahim Ali, Haris Aribi, Ahmed Artz, Andrew S. Farol, Len Hui, Susanta Karanes, Chatchada Khaled, Samer Liu, An Marcucci, Guido Nakamura, Ryotaro Pullarkat, Vinod A. Radany, Eric Rosenthal, Joseph Salhotra, Amandeep Sanchez, James F. Spielberger, Ricardo Snyder, David S. Forman, Stephen J. Wong, Jeffrey Gehr Family Center for Leukemia Research City of Hope Duarte CA Department of Computational and Quantitative Medicine-BRI City of Hope National Medical Center Duarte CA Bone Marrow Transplant Program Southern California Kaiser Permanente Los Angeles CA Department of Radiation Oncology Beckman Research Institute City of Hope Duarte CA Department of Hematology and Hematopoietic Cell Transplantation City of Hope Duarte CA Department of Radiation Oncology City of Hope Duarte CA Department of Hematologic Malignancies Translational Science Gehr Family Center for Leukemia Research Hematologic Malignancies and Stem Cell Transplantation Institute Beckman Research Institute City of Hope Monrovia CA Department of Pediatrics City of Hope Duarte CA

Background : Allogeneic hematopoietic cell transplantation (alloHCT) is the approach that offers the highest curative rate for acute myelogenous leukemia (AML) with intermediate or high-risk cytogenetics. Graft versus host disease (GvHD) has remained the main cause of post-transplantation mortality and morbidity, despite advances in prophylaxis and therapy, adding significant economic burden and affecting quality of life. It would be desirable to reduce the rate of GvHD among patients in complete remission (CR) without increasing the risk of relapse. In this study, we have developed a novel conditioning regimen of total marrow and lymphoid irradiation (TMLI) at 2000 cGy, together with post-transplant cyclophosphamide (PTCy), to 1) reduce the possibly increased risk of relapse from PTCy, by using escalated radiation doses of TMLI, as increasing radiation doses has the potential to decrease the post-transplantation relapse rate (Blood, vol 76, pp. 1867-1871, 1990); and 2) reduce the risk of chronic GvHD by using PTCy. The major goal of this pilot study of TMLI and PTCy (***: NCT03467386), was to thus improve GvHD-free/relapse-free survival (GRFS), reported to be 45% from total body irradiation (TBI) and tacrolimus/sirolimus prophylaxis (BBMT, vol 26(2), pp. 292-299, 2020), in patients with AML in remission. Patients and Methods : A total of 18 patients were enrolled and treated (see Table) between March 2018 and December 2019. Key criteria were ages 18 to 60, first or second CR, minimal residual disease negative by multi-color flow cytometry, and normal organ function. TMLI was administered on days -4 to 0 without addition of chemotherapy. The radiation dose for all patients (n=18) was 2000 cGy, delivered in 200 cGy fractions twice daily. The radiation dose delivered to the liver and brain was kept at 1200 cGy. Remaining organs were considered non-targeted. All patients received peripheral blood stem cells on day 0. Cyclophosphamide was given on days +3

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Rapid identification and monitoring of cooking oil fume-based toxic volatile organic aldehydes in lung tissue for predicting exposure level and cancer risks

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Chemosphere 2023年 339卷 139704页

作者： Prakasham, Karthikeyan Gurrani, Swapnil Wu, Chia-Fang Wu, Ming-Tsang Hsieh, Tusty-Jiuan Peng, Chiung-Yu Huang, Po-Chin Krishnan, Anbarasu Tsai, Pei-Chien Lin, Yu-Chia Tsai, Bongee Lin, Yuan-Chung Ponnusamy, Vinoth Kumar Kaohsiung City807 Taiwan Kaohsiung City807 Taiwan International Master Program of Translational Medicine College of Engineering and Science National United University Miaoli Taiwan Kaohsiung City807 Taiwan Department of Public Health College of Health Sciences Kaohsiung Medical University Kaohsiung City807 Taiwan Miaoli County 35053 Taiwan Department of Computational Biology Institute of Bioinformatics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai602105 India Kaohsiung City807 Taiwan Corporation No.392 Yucheng Rd. Zuoying District. Kaohsiung City813 Taiwan Center for Emerging Contaminants Research National Sun Yat-Sen University Kaohsiung City804 Taiwan Institute of Environmental Engineering National Sun Yat-Sen University Kaohsiung City804 Taiwan Kaohsiung Medical University Kaohsiung City807 Taiwan Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan Department of Family Medicine Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan

Cooking oil fumes (COFs) comprised of a mixture of cancer-causing volatile organic aldehydes (VOAs), particularly trans, trans-2,4-decadienal (t,t-DDE), 4-hydroxy-hexenal (4-HHE), and 4-hydroxy-nonenal (4-HNE). Monitoring toxic VOAs levels in people exposed to different cooking conditions is vital to predicting the cancer risk. For this purpose, we developed a fast tissue extraction (FaTEx) technique combined with UHPLC-MS/MS to monitor three toxic VOAs in mice lung tissue samples. FaTEx pre-treatment protocol was developed by combining two syringes for extraction and clean-up process. The various procedural steps affecting the FaTEx sample pre-treatment process were optimized to enhance the target VOAs’ extraction efficiency from the sample matrix. Under the optimal experimental conditions, results exhibit good correlation coefficient values > 0.99, detection limits were between 0.5–3 ng/g, quantification limits were between 1–10 ng/g, and the matrix effect was © 2023 Elsevier Ltd

关键词： Diseases

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A linked data graph approach to integration of immunological data

A linked data graph approach to integration of immunological...

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Syed Ahmad Chan Bukhari Jeff Mandell Steven H. Kleinstein Kei-Hoi Cheung Division of Computer Science Mathematics and Science Lesley H. & William L. Collins College of Professional Studies St. John's University Interdepartmental Program in Computational Biology and Bioinformatics Yale University Department of Pathology Interdepartmental Program in Computational Biology and Bioinformatics Yale University Department of Emergency Medicine and Yale Center for Medical Informatics Computationa Biology and Bioinformaticcs Yale University

ISBN: (纸本)9781728118680

Systems biology involves the integration of multiple data types (across different data sources) to offer a more complete picture of the biological system being studied. While many existing biological databases are implemented using the traditional SQL (Structured Query Language) database technology, NoSQL database technologies have been explored as a more relationship-based, flexible and scalable method of data integration. In this paper, we describe how to use the Neo4J graph database to integrate a variety of types of data sets in the context of systems vaccinology. Specifically, we have converted into a common graph model diverse types of vaccine response measurement data from the NIH/NIAID ImmPort data repository, pathway data from Reactome, influenza virus strains from WHO, and taxonomic data from NCBI Taxon. While Neo4J provides a graph-based query language (Cypher) for data retrieval, we develop a web-based dashboard for users to easily browse and visualize data without the need to learn Cypher. In addition, we have prototyped a natural language query interface for users to interact with our system. In conclusion, we demonstrate the feasibility of using a graph-based database for storing and querying immunological data with complex biological relationships. Querying a graph database through such relationships has the potential to reveal novel relationships among heterogeneous biological data.

关键词： ontology knowledgebase graph database immunology influenza vaccine graphic library Knowledge Bases Influenza Vaccines Ontology Immunology data integration Passwords DNA Integration integration data types Data sources SQL

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Cover Image, Volume 5, Number 3, March 2023

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Carbon Energy 2023年第3期5卷

作者： Jun Yang Xing Li Ke Qu Yixian Wang Kangqi Shen Changhuan Jiang Bo Yu Pan Luo Zhuangzhi Li Mingyang Chen Bingshu Guo Mingshan Wang Junchen Chen Zhiyuan Ma Yun Huang Zhenzhong Yang Pengcheng Liu Rong Huang Xiaodi Ren David Mitlin School of New Energy and Materials Southwest Petroleum University Chengdu China Energy Storage Research Institute Southwest Petroleum University Chengdu China Ke Qu Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China. China Key Laboratory of Polar Materials and Devices (MOE) and Department of Electronics East China Normal University Shanghai 200062 China. Mingyang Chen Beijing Computational Science Research Center Beijing 100193 China. Center for Green Innovation School of Materials Science and Engineering University of Science and Technology Beijing Beijing 100083 China. Rong Huang China Key Laboratory of Polar Materials and Devices (MOE) and Department of Electronics East China Normal University Shanghai 200062 China. Xiaodi Ren Hefei National Research Center for Physical Sciences at the Microscale Department of Materials Science and Engineering University of Science and Technology of China Hefei Anhui 230026 China. David Mitlin Materials Science Program and Texas Materials Institute The University of Texas at Austin Austin Texas 78712-1591 USA. Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China China Key Laboratory of Polar Materials and Devices (MOE) Department of Electronics East China Normal University Shanghai China Xing Li School of New Energy and Materials Southwest Petroleum University Chengdu China. Materials Science Program and Texas Materials Institute The University of Texas at Austin Austin Texas USA Beijing Computational Science Research Center Beijing China School of Materials Science and Engineering Center for Green Innovation University of Science and Technology Beijing Beijing China Department of Materials Science and Engineering Hefei National Research Center for Physical Sciences at the Microscale University of Science and Technology of China Hefei Anhui China

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Hyper-molecules: On the representation and recovery of dynamical structures, with application to flexible macro-molecular structures in cryo-EM

arXiv

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arXiv 2019年

作者： Lederman, Roy R. Andén, Joakim Singer, Amit Department of Statistics and Data Science Yale University New HavenCT United States Center for Computational Mathematics Flatiron Institute New YorkNY United States Department of Mathematics and Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States

Cryo-electron microscopy (cryo-EM), the subject of the 2017 Nobel Prize in Chemistry, is a technology for determining the 3-D structure of macromolecules from many noisy 2-D projections of instances of these macromolecules, whose orientations and positions are unknown. The molecular structures are not rigid objects, but flexible objects involved in dynamical processes. The different conformations are exhibited by different instances of the macromolecule observed in a cryo-EM experiment, each of which is recorded as a particle image. The range of conformations and the conformation of each particle are not known a priori;one of the great promises of cryo-EM is to map this conformation space. Remarkable progress has been made in determining rigid structures from homogeneous samples of molecules in spite of the unknown orientation of each particle image and significant progress has been made in recovering a few distinct states from mixtures of rather distinct conformations, but more complex heterogeneous samples remain a major challenge. We introduce the "hyper-molecule" framework for modeling structures across different states of heterogeneous molecules, including continuums of states. The key idea behind this framework is representing heterogeneous macromolecules as high-dimensional objects, with the additional dimensions representing the conformation space. This idea is then refined to model properties such as localized heterogeneity. In addition, we introduce an algorithmic framework for recovering such maps of heterogeneous objects from experimental data using a Bayesian formulation of the problem and Markov chain Monte Carlo (MCMC) algorithms to address the computational challenges in recovering these high dimensional hyper-molecules. We demonstrate these ideas in a prototype applied to synthetic data. Copyright © 2019, The Authors. All rights reserved.

关键词： Medical imaging

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SeqScreen: a biocuration platform for robust taxonomic and biological process characterization of nucleic acid sequences of interest

SeqScreen: a biocuration platform for robust taxonomic and b...

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Dreycey Albin Dan Nasko R. A. Leo Elworth Jacob Lu Advait Balaji Christian Diaz Nidhi Shah Jeremy Selengut Chris Hulme-Lowe Pravin Muthu Gene Godbold Mikael Lindvall Madeline Diep Adam Porter Mihai Pop Krista Ternus Todd J. Treangen Program in Systems Synthetic and Physical Biology Rice University Center for Bioinformatics and Computational Biology University of Maryland Department of Computer Science Rice University Signature Science LLC Fraunhofer Center for Experimental Software Engineering Department of Computer Science University of Maryland

ISBN: (纸本)9781728118680

Rapid advancements in synthetic biology and nucleic acid synthesis, in particular concerns about its intentional or accidental misuse, call for more sophisticated screening tools to identify genes of interest within short sequence fragments. One major gap in predicting genes of concern is the inadequacy of current tools and ontologies to describe the specific biological processes of pathogenic proteins. The objective of this work is to design software that sensitively assigns taxonomic classifications, functional annotations, and biological processes of interest to short nucleotide sequences of unknown origin (50bp-1,000bp). The overarching goal is to perform sensitive characterization of short sequences and highlight specific pathogenic biological processes of interest (BPoIs). The SeqScreen software executes these tasks in analytical workflows with Nextflow and outputs results in a tab-delimited report. Local and global alignments differentiate hits to taxonomically-related sequences from similar but unrelated sequences, and an ensemble approach leverages multiple tools and databases to assign a variety of functional terms to each query sequence. Final biological process assessments are made from the predicted functional annotations, which leverage information in pre-existing databases, as well as new custom biocurations. Machine learning models predict each biological process of interest on large protein databases before incorporation into the SeqScreen framework to streamline computational efficiency, ensure reproducible results, allow for version control, and facilitate the review of the automated predictions by expert biocurators. The SeqScreen source code is available at .

关键词： Biological Process interest Base Sequence Nucleic acids Version control protein database Database synthetic biology ANNOTATIONS Leverage

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EMPRESS. XI. SDSS and JWST Search for Local and z ∼ 4–5 Extremely Metal-Poor Galaxies (EMPGs): Clustering and Chemical Properties of Local EMPGs

arXiv

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arXiv 2023年

作者： Nishigaki, Moka Ouchi, Masami Nakajima, Kimihiko Ono, Yoshiaki Rauch, Michael Isobe, Yuki Harikane, Yuichi Narita, Kanako Zahedy, Fakhri Xu, Yi Yajima, Hidenobu Fukushima, Hajime Hirai, Yutaka Kim, Ji Hoon Inoue, Shigeki Kusakabe, Haruka Lee, Chien-Hsiu Nagao, Tohru Onodera, Masato Department of Astronomical Science The Graduate University for Advanced Studies SOKENDAI 2-21-1 Osawa Mitaka Tokyo181-8588 Japan National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa Chiba277-8582 Japan University of Tokyo Chiba Kashiwa277-8583 Japan Observatories of the Carnegie Institution for Science 813 Santa Barbara Street PasadenaCA91101 United States Department of Physics Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan Department of Astronomy Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan Center for Computational Sciences University of Tsukuba Ten-nodai 1-1-1 Tsukuba Ibaraki305-8577 Japan Department of Physics and Astronomy University of Notre Dame 225 Nieuwland Science Hall Notre DameIN46556 United States Astronomical Institute Tohoku University 6-3 Aoba Aramaki Aoba-ku Sendai Miyagi980-8578 Japan Astronomy Program Department of Physics and Astronomy Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of SNU Astronomy Research Center Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of Faculty of Science Hokkaido University Hokkaido Sapporo060-0810 Japan Observatoire de Genève Université de Genève 51 Chemin de Pégase Versoix1290 Switzerland W. M. Keck Observatory 65-1120 Mamalahoa Hwy KamuelaHI96743 United States Research Center for Space and Cosmic Evolution Ehime University Ehime Matsuyama790-8577 Japan 650 North A’ohoku Place HiloHI96720 United States

We search for local extremely metal-poor galaxies (EMPGs), selecting photometric candidates by broadband color excess and machine-learning techniques with the SDSS photometric data. After removing stellar contaminants by shallow spectroscopy with Seimei and Nayuta telescopes, we confirm that three candidates are EMPGs with 0.05–0.1 Z☉ by deep Magellan/MagE spectroscopy for faint [Oiii]λ4363 lines. Using a statistical sample consisting of 105 spectroscopically-confirmed EMPGs taken from our study and the literature, we calculate cross-correlation function (CCF) of the EMPGs and all SDSS galaxies to quantify environments of EMPGs. Comparing another CCF of all SDSS galaxies and comparison SDSS galaxies in the same stellar mass range (107.0 − 108.4M☉), we find no significant (> 1σ) difference between these two CCFs. We also compare mass-metallicity relations (MZRs) of the EMPGs and those of galaxies at z ∼ 0–4 with a steady chemical evolution model and find that the EMPG MZR is comparable with the model prediction on average. These clustering and chemical properties of EMPGs are explained by a scenario of stochastic metal-poor gas accretion on metal-rich galaxies showing metal-poor star formation. Extending the broadband color-excess technique to a high-z EMPG search, we select 17 candidates of z ∼ 4–5 EMPGs with the deep (' 30 mag) near-infrared JWST/NIRCam images obtained by ERO and ERS programs. We find galaxy candidates with negligible [Oiii]λλ4959,5007 emission weaker than the local EMPGs and known high-z galaxies, suggesting that some of these candidates may fall in 0–0.01 Z☉, which potentially break the lowest metallicity limit known to date. Copyright © 2023, The Authors. All rights reserved.

关键词： Infrared devices

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Biomedical discovery through the integrative biomedical knowledge hub (iBKH)

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iscience 2023年第4期26卷 106460页

作者： Su, Chang Hou, Yu Zhou, Manqi Rajendran, Suraj Maasch, Jacqueline R.M. A. Abedi, Zehra Zhang, Haotan Bai, Zilong Cuturrufo, Anthony Guo, Winston Chaudhry, Fayzan F. Ghahramani, Gregory Tang, Jian Cheng, Feixiong Li, Yue Zhang, Rui DeKosky, Steven T. Bian, Jiang Wang, Fei Department of Health Service Administration and Policy College of Public Health Temple University Philadelphia 19122 PA United States Department of Population Health Sciences Weill Cornell Medicine New York 10065 NY United States Department of Surgery University of Minnesota Minneapolis 55455 MN United States Department of Computational Biology Cornell University Ithaca 14850 NY United States Tri-Institutional Computational Biology & Medicine Program Cornell University New York 10065 NY United States Department of Computer Science Cornell Tech New York 10044 NY United States Department of Physiology and Biophysics Weill Cornell Medicine New York 10065 NY United States Computer Science Cornell University Ithaca 14850 NY United States Department of Medicine Weill Cornell Medicine New York 10021 NY United States Mila-Quebec AI Institute and HEC Montreal Montreal H2S 3H1 QC Canada Genomic Medicine Institute Lerner Research Institute Cleveland Clinic Cleveland 44195 OH United States Department of Molecular Medicine Cleveland Clinic Lerner College of Medicine Case Western Reserve University Cleveland 44195 OH United States Case Comprehensive Cancer Center Case Western Reserve University School of Medicine Cleveland 44106 OH United States School of Computer Science McGill University Montreal H3A 0C6 QC Canada Department of Neurology College of Medicine University of Florida Gainesville 32610 FL United States Department of Health Outcomes & Biomedical Informatics College of Medicine University of Florida Gainesville 32610 FL United States

The abundance of biomedical knowledge gained from biological experiments and clinical practices is an invaluable resource for biomedicine. The emerging biomedical knowledge graphs (BKGs) provide an efficient and effective way to manage the abundant knowledge in biomedical and life science. In this study, we created a comprehensive BKG called the integrative Biomedical Knowledge Hub (iBKH) by harmonizing and integrating information from diverse biomedical resources. To make iBKH easily accessible for biomedical research, we developed a web-based, user-friendly graphical portal that allows fast and interactive knowledge retrieval. Additionally, we also implemented an efficient and scalable graph learning pipeline for discovering novel biomedical knowledge in iBKH. As a proof of concept, we performed our iBKH-based method for computational in-silico drug repurposing for Alzheimer's disease. The iBKH is publicly available. © 2023 The Authors

关键词： Bioinformatics Drugs Systems biology

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Optimized large hyperuniform binary colloidal suspensions in two dimensions

arXiv

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arXiv 2020年

作者： Ma, Zheng Lomba, Enrique Torquato, Salvatore Department of Physics Princeton University PrincetonNJ08544 United States Instituto de Química Física Rocasolano CSIC Calle Serrano 119 MadridE-28006 Spain Department of Chemistry Department of Physics Princeton Institute for the Science and Technology of Materials Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

The creation of disordered hyperuniform materials with potentially extraordinary optical properties requires a capacity to synthesize large samples that are effectively hyperuniform down to the nanoscale. Motivated by this challenge, we propose a fabrication protocol using binary paramagnetic colloidal particles confined in a 2D plane. The strong and long-ranged dipolar interaction induced by a tunable magnetic field is free from screening effects that attenuates long-ranged electrostatic interactions in charged colloidal systems. Specifically, we find a family of optimal size ratios that makes the two-phase system effectively hyperuniform. We show that hyperuniformity is a general consequence of low isothermal compressibilities, which makes our protocol suitable to systems with other long-ranged soft interactions, dimensionalities and/or polydispersity. Our methodology paves the way to synthesize large photonic hyperuniform materials that function in the visible to infrared range and hence may accelerate the discovery of novel photonic materials. Copyright © 2020, The Authors. All rights reserved.

关键词： Suspensions (fluids)

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A meta-analysis of Boolean network models reveals design principles of gene regulatory networks

arXiv

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arXiv 2020年

作者： Kadelka, Claus Butrie, Taras-Michael Hilton, Evan Kinseth, Jack Schmidt, Addison Serdarevic, Haris Department of Mathematics Iowa State University AmesIA50011 United States Department of Aerospace Engineering Iowa State University AmesIA50011 United States Department of Computer Science Iowa State University AmesIA50011 United States Bioinformatics and Computational Biology Program Iowa State University AmesIA50011 United States

Gene regulatory networks (GRNs) play a central role in cellular decision-making. Understanding their structure and how it impacts their dynamics constitutes thus a fundamental biological question. GRNs are frequently modeled as Boolean networks, which are intuitive, simple to describe, and can yield qualitative results even when data is sparse. We assembled the largest repository of expert-curated Boolean GRN models. A meta-analysis of this diverse set of models reveals several design principles. GRNs exhibit more canalization, redundancy and stable dynamics than expected. Moreover, they are enriched for certain recurring network motifs. This raises the important question why evolution favors these design mechanisms. Copyright © 2020, The Authors. All rights reserved.

关键词： Decision making

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