1
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Thompson P, Ananiadou S, Basinas I, Brinchmann BC, Cramer C, Galea KS, Ge C, Georgiadis P, Kirkeleit J, Kuijpers E, Nguyen N, Nuñez R, Schlünssen V, Stokholm ZA, Taher EA, Tinnerberg H, Van Tongeren M, Xie Q. Supporting the working life exposome: Annotating occupational exposure for enhanced literature search. PLoS One 2024; 19:e0307844. [PMID: 39146349 DOI: 10.1371/journal.pone.0307844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 07/12/2024] [Indexed: 08/17/2024] Open
Abstract
An individual's likelihood of developing non-communicable diseases is often influenced by the types, intensities and duration of exposures at work. Job exposure matrices provide exposure estimates associated with different occupations. However, due to their time-consuming expert curation process, job exposure matrices currently cover only a subset of possible workplace exposures and may not be regularly updated. Scientific literature articles describing exposure studies provide important supporting evidence for developing and updating job exposure matrices, since they report on exposures in a variety of occupational scenarios. However, the constant growth of scientific literature is increasing the challenges of efficiently identifying relevant articles and important content within them. Natural language processing methods emulate the human process of reading and understanding texts, but in a fraction of the time. Such methods can increase the efficiency of both finding relevant documents and pinpointing specific information within them, which could streamline the process of developing and updating job exposure matrices. Named entity recognition is a fundamental natural language processing method for language understanding, which automatically identifies mentions of domain-specific concepts (named entities) in documents, e.g., exposures, occupations and job tasks. State-of-the-art machine learning models typically use evidence from an annotated corpus, i.e., a set of documents in which named entities are manually marked up (annotated) by experts, to learn how to detect named entities automatically in new documents. We have developed a novel annotated corpus of scientific articles to support machine learning based named entity recognition relevant to occupational substance exposures. Through incremental refinements to the annotation process, we demonstrate that expert annotators can attain high levels of agreement, and that the corpus can be used to train high-performance named entity recognition models. The corpus thus constitutes an important foundation for the wider development of natural language processing tools to support the study of occupational exposures.
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Affiliation(s)
- Paul Thompson
- Department of Computer Science, National Centre for Text Mining, University of Manchester, Manchester, United Kingdom
| | - Sophia Ananiadou
- Department of Computer Science, National Centre for Text Mining, University of Manchester, Manchester, United Kingdom
| | - Ioannis Basinas
- Centre for Occupational and Environmental Health, School of Health Sciences, University of Manchester, Manchester, United Kingdom
| | - Bendik C Brinchmann
- Federation of Norwegian Industries, Oslo, Norway
- Department of Occupational Medicine and Epidemiology, National Institute of Occupational Health, Oslo, Norway
| | - Christine Cramer
- Department of Public Health, Research Unit for Environment, Occupation and Health, Danish Ramazzini Centre, Aarhus University, Aarhus, Denmark
- Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark
| | - Karen S Galea
- Institute of Occupational Medicine, Edinburgh, United Kingdom
| | - Calvin Ge
- Netherlands Organisation for Applied Scientific Research, Utrecht, Netherlands
| | - Panagiotis Georgiadis
- Department of Computer Science, National Centre for Text Mining, University of Manchester, Manchester, United Kingdom
| | - Jorunn Kirkeleit
- Federation of Norwegian Industries, Oslo, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Eelco Kuijpers
- Netherlands Organisation for Applied Scientific Research, Utrecht, Netherlands
| | - Nhung Nguyen
- Department of Computer Science, National Centre for Text Mining, University of Manchester, Manchester, United Kingdom
| | - Roberto Nuñez
- Occupational Health Group, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | - Vivi Schlünssen
- Department of Public Health, Research Unit for Environment, Occupation and Health, Danish Ramazzini Centre, Aarhus University, Aarhus, Denmark
| | - Zara Ann Stokholm
- Department of Occupational Medicine, Danish Ramazzini Centre, Aarhus University Hospital, Aarhus, Denmark
| | - Evana Amir Taher
- Center for Occupational and Environmental Medicine, Stockholm, Sweden
| | - Håkan Tinnerberg
- School of Public Health and Community Medicine, University of Gothenburg, Gothenburg, Sweden
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Martie Van Tongeren
- Centre for Occupational and Environmental Health, School of Health Sciences, University of Manchester, Manchester, United Kingdom
| | - Qianqian Xie
- Department of Computer Science, National Centre for Text Mining, University of Manchester, Manchester, United Kingdom
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2
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Metz TO, Chang CH, Gautam V, Anjum A, Tian S, Wang F, Colby SM, Nunez JR, Blumer MR, Edison AS, Fiehn O, Jones DP, Li S, Morgan ET, Patti GJ, Ross DH, Shapiro MR, Williams AJ, Wishart DS. Introducing 'identification probability' for automated and transferable assessment of metabolite identification confidence in metabolomics and related studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.30.605945. [PMID: 39131324 PMCID: PMC11312557 DOI: 10.1101/2024.07.30.605945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence - the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies. Further refinement in identification levels have occurred, for example to accommodate use of ion mobility spectrometry in metabolomics workflows, and alternate approaches to communicate compound identification confidence also have been developed based on identification points schema. However, neither qualitative levels of identification confidence nor quantitative scoring systems address the degree of ambiguity in compound identifications in context of the chemical space being considered, are easily automated, or are transferable between analytical platforms. In this perspective, we propose that the metabolomics and related communities consider identification probability as an approach for automated and transferable assessment of compound identification and ambiguity in metabolomics and related studies. Identification probability is defined simply as 1/N, where N is the number of compounds in a reference library or chemical space that match to an experimentally measured molecule within user-defined measurement precision(s), for example mass measurement or retention time accuracy, etc. We demonstrate the utility of identification probability in an in silico analysis of multi-property reference libraries constructed from the Human Metabolome Database and computational property predictions, provide guidance to the community in transparent implementation of the concept, and invite the community to further evaluate this concept in parallel with their current preferred methods for assessing metabolite identification confidence.
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Affiliation(s)
- Thomas O. Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA USA
| | - Christine H. Chang
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA USA
| | - Vasuk Gautam
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Afia Anjum
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Siyang Tian
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Fei Wang
- Department of Computing Science, University of Alberta, Edmonton, AB, Canada
- Alberta Machine Intelligence Institute, Edmonton, AB, Canada
| | - Sean M. Colby
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA USA
| | - Jamie R. Nunez
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA USA
| | - Madison R. Blumer
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA USA
| | - Arthur S. Edison
- Department of Biochemistry & Molecular Biology, Complex Carbohydrate Research Center and Institute of Bioinformatics, University of Georgia, Athens, GA, USA
| | - Oliver Fiehn
- West Coast Metabolomics Center, University of California Davis, Davis, CA, USA
| | - Dean P. Jones
- Clinical Biomarkers Laboratory, Department of Medicine, Emory University, Atlanta, Georgia, USA
| | - Shuzhao Li
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Edward T. Morgan
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Gary J. Patti
- Center for Mass Spectrometry and Metabolic Tracing, Department of Chemistry, Department of Medicine, Washington University, Saint Louis, Missouri, USA
| | - Dylan H. Ross
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA USA
| | - Madelyn R. Shapiro
- Artificial Intelligence & Data Analytics Division, Pacific Northwest National Laboratory, Richland, WA USA
| | - Antony J. Williams
- U.S. Environmental Protection Agency, Office of Research & Development, Center for Computational Toxicology & Exposure (CCTE), Research Triangle Park, NC USA
| | - David S. Wishart
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
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3
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Lai Y, Koelmel JP, Walker DI, Price EJ, Papazian S, Manz KE, Castilla-Fernández D, Bowden JA, Nikiforov V, David A, Bessonneau V, Amer B, Seethapathy S, Hu X, Lin EZ, Jbebli A, McNeil BR, Barupal D, Cerasa M, Xie H, Kalia V, Nandakumar R, Singh R, Tian Z, Gao P, Zhao Y, Froment J, Rostkowski P, Dubey S, Coufalíková K, Seličová H, Hecht H, Liu S, Udhani HH, Restituito S, Tchou-Wong KM, Lu K, Martin JW, Warth B, Godri Pollitt KJ, Klánová J, Fiehn O, Metz TO, Pennell KD, Jones DP, Miller GW. High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:12784-12822. [PMID: 38984754 PMCID: PMC11271014 DOI: 10.1021/acs.est.4c01156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 06/11/2024] [Accepted: 06/12/2024] [Indexed: 07/11/2024]
Abstract
In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.
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Affiliation(s)
- Yunjia Lai
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Jeremy P. Koelmel
- Department
of Environmental Health Sciences, Yale School
of Public Health, New Haven, Connecticut 06520, United States
| | - Douglas I. Walker
- Gangarosa
Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, United States
| | - Elliott J. Price
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Stefano Papazian
- Department
of Environmental Science, Science for Life Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden
- National
Facility for Exposomics, Metabolomics Platform, Science for Life Laboratory, Stockholm University, Solna 171 65, Sweden
| | - Katherine E. Manz
- Department
of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Delia Castilla-Fernández
- Department
of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, 1010 Vienna, Austria
| | - John A. Bowden
- Center for
Environmental and Human Toxicology, Department of Physiological Sciences,
College of Veterinary Medicine, University
of Florida, Gainesville, Florida 32611, United States
| | | | - Arthur David
- Univ Rennes,
Inserm, EHESP, Irset (Institut de recherche en santé, environnement
et travail) − UMR_S, 1085 Rennes, France
| | - Vincent Bessonneau
- Univ Rennes,
Inserm, EHESP, Irset (Institut de recherche en santé, environnement
et travail) − UMR_S, 1085 Rennes, France
| | - Bashar Amer
- Thermo
Fisher Scientific, San Jose, California 95134, United States
| | | | - Xin Hu
- Gangarosa
Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, United States
| | - Elizabeth Z. Lin
- Department
of Environmental Health Sciences, Yale School
of Public Health, New Haven, Connecticut 06520, United States
| | - Akrem Jbebli
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Brooklynn R. McNeil
- Biomarkers
Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, New York 10032, United States
| | - Dinesh Barupal
- Department
of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Marina Cerasa
- Institute
of Atmospheric Pollution Research, Italian National Research Council, 00015 Monterotondo, Rome, Italy
| | - Hongyu Xie
- Department
of Environmental Science, Science for Life Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden
| | - Vrinda Kalia
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Renu Nandakumar
- Biomarkers
Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, New York 10032, United States
| | - Randolph Singh
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Zhenyu Tian
- Department
of Chemistry and Chemical Biology, Northeastern
University, Boston, Massachusetts 02115, United States
| | - Peng Gao
- Department
of Environmental and Occupational Health, and Department of Civil
and Environmental Engineering, University
of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
- UPMC Hillman
Cancer Center, Pittsburgh, Pennsylvania 15232, United States
| | - Yujia Zhao
- Institute
for Risk Assessment Sciences, Utrecht University, Utrecht 3584CM, The Netherlands
| | | | | | - Saurabh Dubey
- Biomarkers
Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, New York 10032, United States
| | - Kateřina Coufalíková
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Hana Seličová
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Helge Hecht
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Sheng Liu
- Department
of Environmental Health Sciences, Yale School
of Public Health, New Haven, Connecticut 06520, United States
| | - Hanisha H. Udhani
- Biomarkers
Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Irving Medical Center, New York, New York 10032, United States
| | - Sophie Restituito
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Kam-Meng Tchou-Wong
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
| | - Kun Lu
- Department
of Environmental Sciences and Engineering, Gillings School of Global
Public Health, The University of North Carolina
at Chapel Hill, Chapel Hill, North Carolina 27599, United States
| | - Jonathan W. Martin
- Department
of Environmental Science, Science for Life Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden
- National
Facility for Exposomics, Metabolomics Platform, Science for Life Laboratory, Stockholm University, Solna 171 65, Sweden
| | - Benedikt Warth
- Department
of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, 1010 Vienna, Austria
| | - Krystal J. Godri Pollitt
- Department
of Environmental Health Sciences, Yale School
of Public Health, New Haven, Connecticut 06520, United States
| | - Jana Klánová
- RECETOX,
Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic
| | - Oliver Fiehn
- West Coast
Metabolomics Center, University of California−Davis, Davis, California 95616, United States
| | - Thomas O. Metz
- Biological
Sciences Division, Pacific Northwest National
Laboratory, Richland, Washington 99354, United States
| | - Kurt D. Pennell
- School
of Engineering, Brown University, Providence, Rhode Island 02912, United States
| | - Dean P. Jones
- Department
of Medicine, School of Medicine, Emory University, Atlanta, Georgia 30322, United States
| | - Gary W. Miller
- Department
of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York 10032, United States
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4
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Zarei I, Eloranta AM, Klåvus A, Väistö J, Lehtonen M, Mikkonen S, Koistinen VM, Sallinen T, Haapala EA, Lintu N, Soininen S, Haikonen R, Atalay M, Schwab U, Auriola S, Kolehmainen M, Hanhineva K, Lakka TA. Eight-year diet and physical activity intervention affects serum metabolites during childhood and adolescence: A nonrandomized controlled trial. iScience 2024; 27:110295. [PMID: 39055945 PMCID: PMC11269805 DOI: 10.1016/j.isci.2024.110295] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 04/16/2024] [Accepted: 06/14/2024] [Indexed: 07/28/2024] Open
Abstract
Long-term lifestyle interventions in childhood and adolescence can significantly improve cardiometabolic health, but the underlying molecular mechanisms remain poorly understood. To address this knowledge gap, we conducted an 8-year diet and physical activity intervention in a general population of children. The research revealed that the intervention influenced 80 serum metabolites over two years, with 17 metabolites continuing to be affected after eight years. The intervention primarily impacted fatty amides, including palmitic amide, linoleamide, oleamide, and others, as well as unsaturated fatty acids, acylcarnitines, phospholipids, sterols, gut microbiota-derived metabolites, amino acids, and purine metabolites. Particularly noteworthy were the pronounced changes in serum fatty amides. These serum metabolite alterations could represent molecular mechanisms responsible for the observed benefits of long-term lifestyle interventions on cardiometabolic and overall health since childhood. Understanding these metabolic changes may provide valuable insights into the prevention of cardiometabolic and other non-communicable diseases since childhood.
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Affiliation(s)
- Iman Zarei
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Aino-Maija Eloranta
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, Kuopio, Finland
| | - Anton Klåvus
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Juuso Väistö
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Marko Lehtonen
- School of Pharmacy, Faculty of Health Science, University of Eastern Finland, Kuopio, Finland
- LC-MS Metabolomics Center, Biocenter Kuopio, Kuopio, Finland
| | - Santtu Mikkonen
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland
- Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, Finland
| | - Ville M. Koistinen
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Food Chemistry and Food Development Unit, Department of Biochemistry, University of Turku, Turku, Finland
| | - Taisa Sallinen
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Eero A. Haapala
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Niina Lintu
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Sonja Soininen
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Physician and Nursing Services, Health and Social Services Centre, Wellbeing Services County of North Savo, Varkaus, Finland
| | - Retu Haikonen
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Mustafa Atalay
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Ursula Schwab
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, Kuopio, Finland
| | - Seppo Auriola
- School of Pharmacy, Faculty of Health Science, University of Eastern Finland, Kuopio, Finland
| | - Marjukka Kolehmainen
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
| | - Kati Hanhineva
- Institute of Public Health and Clinical Nutrition, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Food Chemistry and Food Development Unit, Department of Biochemistry, University of Turku, Turku, Finland
| | - Timo A. Lakka
- Institute of Biomedicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
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5
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Wang Y, Chen J, Zhang Y, Yang Z, Zhang K, Zhang D, Zheng L. Advancing Microfluidic Immunity Testing Systems: New Trends for Microbial Pathogen Detection. Molecules 2024; 29:3322. [PMID: 39064900 PMCID: PMC11279515 DOI: 10.3390/molecules29143322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 07/10/2024] [Accepted: 07/12/2024] [Indexed: 07/28/2024] Open
Abstract
Pathogenic microorganisms play a crucial role in the global disease burden due to their ability to cause various diseases and spread through multiple transmission routes. Immunity tests identify antigens related to these pathogens, thereby confirming past infections and monitoring the host's immune response. Traditional pathogen detection methods, including enzyme-linked immunosorbent assays (ELISAs) and chemiluminescent immunoassays (CLIAs), are often labor-intensive, slow, and reliant on sophisticated equipment and skilled personnel, which can be limiting in resource-poor settings. In contrast, the development of microfluidic technologies presents a promising alternative, offering automation, miniaturization, and cost efficiency. These advanced methods are poised to replace traditional assays by streamlining processes and enabling rapid, high-throughput immunity testing for pathogens. This review highlights the latest advancements in microfluidic systems designed for rapid and high-throughput immunity testing, incorporating immunosensors, single molecule arrays (Simoas), a lateral flow assay (LFA), and smartphone integration. It focuses on key pathogenic microorganisms such as SARS-CoV-2, influenza, and the ZIKA virus (ZIKV). Additionally, the review discusses the challenges, commercialization prospects, and future directions to advance microfluidic systems for infectious disease detection.
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Affiliation(s)
- Yiran Wang
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Jingwei Chen
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Yule Zhang
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Zhijin Yang
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Kaihuan Zhang
- 2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
| | - Dawei Zhang
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai 200093, China
- Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment, University of Shanghai for Science and Technology, Shanghai 200093, China
- Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 200092, China
| | - Lulu Zheng
- Engineering Research Center of Optical Instrument and System, The Ministry of Education, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai 200093, China
- Shanghai Engineering Research Center of Environmental Biosafety Instruments and Equipment, University of Shanghai for Science and Technology, Shanghai 200093, China
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6
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Vélez-Ixta JM, Juárez-Castelán CJ, Ramírez-Sánchez D, Lázaro-Pérez NDS, Castro-Arellano JJ, Romero-Maldonado S, Rico-Arzate E, Hoyo-Vadillo C, Salgado-Mancilla M, Gómez-Cruz CY, Krishnakumar A, Piña-Escobedo A, Benitez-Guerrero T, Pizano-Zárate ML, Cruz-Narváez Y, García-Mena J. Post Natal Microbial and Metabolite Transmission: The Path from Mother to Infant. Nutrients 2024; 16:1990. [PMID: 38999737 PMCID: PMC11243545 DOI: 10.3390/nu16131990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Revised: 06/20/2024] [Accepted: 06/20/2024] [Indexed: 07/14/2024] Open
Abstract
The entero-mammary pathway is a specialized route that selectively translocates bacteria to the newborn's gut, playing a crucial role in neonatal development. Previous studies report shared bacterial and archaeal taxa between human milk and neonatal intestine. However, the functional implications for neonatal development are not fully understood due to limited evidence. This study aimed to identify and characterize the microbiota and metabolome of human milk, mother, and infant stool samples using high-throughput DNA sequencing and FT-ICR MS methodology at delivery and 4 months post-partum. Twenty-one mothers and twenty-five infants were included in this study. Our results on bacterial composition suggest vertical transmission of bacteria through breastfeeding, with major changes occurring during the first 4 months of life. Metabolite chemical characterization sheds light on the growing complexity of the metabolites. Further data integration and network analysis disclosed the interactions between different bacteria and metabolites in the biological system as well as possible unknown pathways. Our findings suggest a shared bacteriome in breastfed mother-neonate pairs, influenced by maternal lifestyle and delivery conditions, serving as probiotic agents in infants for their healthy development. Also, the presence of food biomarkers in infants suggests their origin from breast milk, implying selective vertical transmission of these features.
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Affiliation(s)
- Juan Manuel Vélez-Ixta
- Departamento de Genética y Biología Molecular, Cinvestav, Av. Instituto Politécnico Nacional 2508, Mexico City 07360, Mexico
| | - Carmen Josefina Juárez-Castelán
- Departamento de Genética y Biología Molecular, Cinvestav, Av. Instituto Politécnico Nacional 2508, Mexico City 07360, Mexico
| | - Daniela Ramírez-Sánchez
- Departamento de Genética y Biología Molecular, Cinvestav, Av. Instituto Politécnico Nacional 2508, Mexico City 07360, Mexico
| | - Noemí Del Socorro Lázaro-Pérez
- Departamento de Genética y Biología Molecular, Cinvestav, Av. Instituto Politécnico Nacional 2508, Mexico City 07360, Mexico
| | - José Javier Castro-Arellano
- Laboratorio de Posgrado e Investigación de Operaciones Unitarias, Escuela Superior de Ingeniería Química e Industrias Extractivas, Instituto Politécnico Nacional, Mexico City 07738, Mexico
| | - Silvia Romero-Maldonado
- Unidad de Cuidados Intermedios al Recién Nacido, Instituto Nacional de Perinatología, Secretaría de Salud, Mexico City 11000, Mexico
| | - Enrique Rico-Arzate
- Laboratorio de Posgrado e Investigación de Operaciones Unitarias, Escuela Superior de Ingeniería Química e Industrias Extractivas, Instituto Politécnico Nacional, Mexico City 07738, Mexico
| | - Carlos Hoyo-Vadillo
- Departamento de Farmacología, Cinvestav, Av. Instituto Politécnico Nacional 2508, Mexico City 07360, Mexico
| | - Marisol Salgado-Mancilla
- Laboratorio de Posgrado e Investigación de Operaciones Unitarias, Escuela Superior de Ingeniería Química e Industrias Extractivas, Instituto Politécnico Nacional, Mexico City 07738, Mexico
| | - Carlos Yamel Gómez-Cruz
- Laboratorio de Posgrado e Investigación de Operaciones Unitarias, Escuela Superior de Ingeniería Química e Industrias Extractivas, Instituto Politécnico Nacional, Mexico City 07738, Mexico
| | - Aparna Krishnakumar
- Departamento de Genética y Biología Molecular, Cinvestav, Av. Instituto Politécnico Nacional 2508, Mexico City 07360, Mexico
| | - Alberto Piña-Escobedo
- Departamento de Genética y Biología Molecular, Cinvestav, Av. Instituto Politécnico Nacional 2508, Mexico City 07360, Mexico
| | - Tizziani Benitez-Guerrero
- Departamento de Genética y Biología Molecular, Cinvestav, Av. Instituto Politécnico Nacional 2508, Mexico City 07360, Mexico
| | - María Luisa Pizano-Zárate
- Coordinación de Nutrición y Bioprogramación, Instituto Nacional de Perinatología, Secretaría de Salud, Mexico City 11000, Mexico
- Unidad de Medicina Familiar No. 4, Instituto Mexicano del Seguro Social, Mexico City 06720, Mexico
| | - Yair Cruz-Narváez
- Laboratorio de Posgrado e Investigación de Operaciones Unitarias, Escuela Superior de Ingeniería Química e Industrias Extractivas, Instituto Politécnico Nacional, Mexico City 07738, Mexico
| | - Jaime García-Mena
- Departamento de Genética y Biología Molecular, Cinvestav, Av. Instituto Politécnico Nacional 2508, Mexico City 07360, Mexico
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7
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Wang Z, Chen S, Guo Y, Zhang R, Zhang Q, Jiang X, Li M, Jiang Y, Ye L, Guo X, Li C, Zhang G, Li D, Chen L, Chen W. Intestinal carcinogenicity screening of environmental pollutants using organoid-based cell transformation assay. Arch Toxicol 2024; 98:1937-1951. [PMID: 38563870 DOI: 10.1007/s00204-024-03729-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 03/07/2024] [Indexed: 04/04/2024]
Abstract
The high incidence of colorectal cancer (CRC) is closely associated with environmental pollutant exposure. To identify potential intestinal carcinogens, we developed a cell transformation assay (CTA) using mouse adult stem cell-derived intestinal organoids (mASC-IOs) and assessed the transformation potential on 14 representative chemicals, including Cd, iPb, Cr-VI, iAs-III, Zn, Cu, PFOS, BPA, MEHP, AOM, DMH, MNNG, aspirin, and metformin. We optimized the experimental protocol based on cytotoxicity, amplification, and colony formation of chemical-treated mASC-IOs. In addition, we assessed the accuracy of in vitro study and the human tumor relevance through characterizing interdependence between cell-cell and cell-matrix adhesions, tumorigenicity, pathological feature of subcutaneous tumors, and CRC-related molecular signatures. Remarkably, the results of cell transformation in 14 chemicals showed a strong concordance with epidemiological findings (8/10) and in vivo mouse studies (12/14). In addition, we found that the increase in anchorage-independent growth was positively correlated with the tumorigenicity of tested chemicals. Through analyzing the dose-response relationship of anchorage-independent growth by benchmark dose (BMD) modeling, the potent intestinal carcinogens were identified, with their carcinogenic potency ranked from high to low as AOM, Cd, MEHP, Cr-VI, iAs-III, and DMH. Importantly, the activity of chemical-transformed mASC-IOs was associated with the degree of cellular differentiation of subcutaneous tumors, altered transcription of oncogenic genes, and activated pathways related to CRC development, including Apc, Trp53, Kras, Pik3ca, Smad4 genes, as well as WNT and BMP signaling pathways. Taken together, we successfully developed a mASC-IO-based CTA, which might serve as a potential alternative for intestinal carcinogenicity screening of chemicals.
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Affiliation(s)
- Ziwei Wang
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
- Stony Brook Cancer Center, Department of Pathology, Renaissance School of Medicine, Stony Brook University, Lauterbur Drive, Stony Brook, NY, 11794, USA
| | - Shen Chen
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Yuzhi Guo
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Rui Zhang
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Qi Zhang
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Xinhang Jiang
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Miao Li
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Yue Jiang
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Lizhu Ye
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Xiaoyu Guo
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Chuang Li
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Guangtong Zhang
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Daochuan Li
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Liping Chen
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Wen Chen
- Department of Toxicology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China.
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8
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Tlou M, Ndou B, Mabona N, Khwathisi A, Ateba C, Madala N, Serepa-Dlamini MH. Next generation sequencing-aided screening, isolation, molecular identification, and antimicrobial potential for bacterial endophytes from the medicinal plant, Elephantorrhiza elephantina. Front Microbiol 2024; 15:1383854. [PMID: 38855763 PMCID: PMC11160484 DOI: 10.3389/fmicb.2024.1383854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 05/06/2024] [Indexed: 06/11/2024] Open
Abstract
Elephantorrhiza elephantina, a wild plant in southern Africa, is utilized in traditional medicine for various ailments, leading to its endangerment and listing on the Red List of South African Plants. To date, there have been no reports on bacterial endophytes from this plant, their classes of secondary metabolites, and potential medicinal properties. This study presents (i) taxonomic characterization of bacterial endophytes in leaf and root tissues using 16S rRNA, (ii) bacterial isolation, morphological, and phylogenetic characterization, (iii) bacterial growth, metabolite extraction, and LC-MS-based metabolite fingerprinting, and (iv) antimicrobial testing of bacterial crude extracts. Next-generation sequencing yielded 693 and 2,459 DNA read counts for the rhizomes and leaves, respectively, detecting phyla including Proteobacteria, Bacteroidota, Gemmatimonadota, Actinobacteriota, Verrucomicrobiota, Dependentiae, Firmicutes, and Armatimonodata. At the genus level, Novosphingobium, Mesorhizobium, Methylobacterium, and Ralstonia were the most dominant in both leaves and rhizomes. From root tissues, four bacterial isolates were selected, and 16S rRNA-based phylogenetic characterization identified two closely related Pseudomonas sp. (strain BNWU4 and 5), Microbacterium oxydans BNWU2, and Stenotrophomonas maltophilia BNWU1. The ethyl acetate:chloroform (1:1 v/v) organic extract from each isolate exhibited antimicrobial activity against all selected bacterial pathogens. Strain BNWU5 displayed the highest activity, with minimum inhibitory concentrations ranging from 62.5 μg/mL to 250 μg/mL against diarrhoeagenic Escherichia coli, Escherichia coli O157:H7, Salmonella enterica, antibiotic-resistant Vibrio cholerae, Staphylococcus aureus, Bacillus cereus, and Enterococcus durans. LC-MS analysis of the crude extract revealed common antimicrobial metabolites produced by all isolates, including Phenoxomethylpenicilloyl (penicilloyl V), cis-11-Eicosenamide, 3-Hydroxy-3-phenacyloxindole, and 9-Octadecenamide.
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Affiliation(s)
- Matsobane Tlou
- Department of Biochemistry, School of Physical and Chemical Sciences, North-West University, Mmabatho, South Africa
| | - Benedict Ndou
- Department of Biochemistry, School of Physical and Chemical Sciences, North-West University, Mmabatho, South Africa
| | - Nokufa Mabona
- Department of Biochemistry, School of Physical and Chemical Sciences, North-West University, Mmabatho, South Africa
| | - Adivhaho Khwathisi
- Department of Biochemistry and Microbiology, University of Venda, Thohoyandou, South Africa
| | - Collins Ateba
- Department of Microbiology, Faculty of Natural and Agricultural Sciences, School of Biological Sciences, North-West University, Mmabatho, South Africa
| | - Ntakadzeni Madala
- Department of Biochemistry and Microbiology, University of Venda, Thohoyandou, South Africa
| | - Mahloro Hope Serepa-Dlamini
- Department of Biotechnology and Food Technology, University of Johannesburg, Doornfontein Campus, Johannesburg, South Africa
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9
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He L, Li M, Zhang Y, Li Q, Fang S, Chen G, Xu X. Neuroinflammation Plays a Potential Role in the Medulla Oblongata After Moderate Traumatic Brain Injury in Mice as Revealed by Nontargeted Metabonomics Analysis. J Neurotrauma 2024. [PMID: 38695184 DOI: 10.1089/neu.2023.0536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2024] Open
Abstract
Moderate traumatic brain injury (mTBI) involves a series of complex pathophysiological processes in not only the area in direct contact with mechanical violence but also in other brain regions far from the injury site, which may be important factors influencing subsequent neurological dysfunction or death. The medulla oblongata (MO) is a key area for the maintenance of basic respiratory and circulatory functions, whereas the pathophysiological processes after mTBI have rarely drawn the attention of researchers. In this study, we established a closed-head cortical contusion injury model, identified 6 different time points that covered the acute, subacute, and chronic phases, and then used nontargeted metabolomics to identify and analyze the changes in differential metabolites (DMs) and metabolic pathways in the MO region. Our results showed that the metabolic profile of the MO region underwent specific changes over time: harmaline, riboflavin, and dephospho-coenzyme A were identified as the key DMs and play important roles in reducing inflammation, enhancing antioxidation, and maintaining homeostasis. Choline and glycerophospholipid metabolism was identified as the key pathway related to the changes in MO metabolism at different phases. In addition, we confirmed increases in the levels of inflammatory factors and the activation of astrocytes and microglia by Western blot and immunofluorescence staining, and these findings were consistent with the nontargeted metabolomic results. These findings suggest that neuroinflammation plays a central role in MO neuropathology after mTBI and provide new insights into the complex pathophysiologic mechanisms involved after mTBI.
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Affiliation(s)
- Liangchao He
- School of Forensic Medicine, Wannan Medical College, Wuhu, China
| | - Mingming Li
- School of Forensic Medicine, Wannan Medical College, Wuhu, China
| | - Yonghao Zhang
- School of Forensic Medicine, Wannan Medical College, Wuhu, China
| | - Qianqian Li
- School of Forensic Medicine, Wannan Medical College, Wuhu, China
| | - Shiyong Fang
- School of Forensic Medicine, Wannan Medical College, Wuhu, China
| | - Guang Chen
- School of Forensic Medicine, Wannan Medical College, Wuhu, China
| | - Xiang Xu
- School of Forensic Medicine, Wannan Medical College, Wuhu, China
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10
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Bahameish M, Stockman T, Requena Carrión J. Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features. SENSORS (BASEL, SWITZERLAND) 2024; 24:3210. [PMID: 38794064 PMCID: PMC11126126 DOI: 10.3390/s24103210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 05/11/2024] [Accepted: 05/14/2024] [Indexed: 05/26/2024]
Abstract
Stress recognition, particularly using machine learning (ML) with physiological data such as heart rate variability (HRV), holds promise for mental health interventions. However, limited datasets in affective computing and healthcare research can lead to inaccurate conclusions regarding the ML model performance. This study employed supervised learning algorithms to classify stress and relaxation states using HRV measures. To account for limitations associated with small datasets, robust strategies were implemented based on methodological recommendations for ML with a limited dataset, including data segmentation, feature selection, and model evaluation. Our findings highlight that the random forest model achieved the best performance in distinguishing stress from non-stress states. Notably, it showed higher performance in identifying stress from relaxation (F1-score: 86.3%) compared to neutral states (F1-score: 65.8%). Additionally, the model demonstrated generalizability when tested on independent secondary datasets, showcasing its ability to distinguish between stress and relaxation states. While our performance metrics might be lower than some previous studies, this likely reflects our focus on robust methodologies to enhance the generalizability and interpretability of ML models, which are crucial for real-world applications with limited datasets.
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Affiliation(s)
- Mariam Bahameish
- College of Science and Engineering, Hamad Bin Khalifa University, Doha P.O. Box 34110, Qatar
| | - Tony Stockman
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UK; (T.S.); (J.R.C.)
| | - Jesús Requena Carrión
- School of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UK; (T.S.); (J.R.C.)
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11
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Zhao Q, Yao F, Li W, Liu S, Bi S. Identification of a dCache-type chemoreceptor in Campylobacter jejuni that specifically mediates chemotaxis towards methyl pyruvate. Front Microbiol 2024; 15:1400284. [PMID: 38784811 PMCID: PMC11111895 DOI: 10.3389/fmicb.2024.1400284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 04/25/2024] [Indexed: 05/25/2024] Open
Abstract
The foodborne pathogenic bacterium Campylobacter jejuni utilizes chemotaxis to assist in the colonization of host niches. A key to revealing the relationship among chemotaxis and pathogenicity is the discovery of signaling molecules perceived by the chemoreceptors. The C. jejuni chemoreceptor Tlp11 is encoded by the highly infective C. jejuni strains. In the present study, we report that the dCache-type ligand-binding domain (LBD) of C. jejuni ATCC 33560 Tlp11 binds directly to novel ligands methyl pyruvate, toluene, and quinoline using the same pocket. Methyl pyruvate elicits a strong chemoattractant response, while toluene and quinoline function as the antagonists without triggering chemotaxis. The sensory LBD was used to control heterologous proteins by constructing chimeras, indicating that the signal induced by methyl pyruvate is transmitted across the membrane. In addition, bioinformatics and experiments revealed that the dCache domains with methyl pyruvate-binding sites and ability are widely distributed in the order Campylobacterales. This is the first report to identify the class of dCache chemoreceptors that bind to attractant methyl pyruvate and antagonists toluene and quinoline. Our research provides a foundation for understanding the chemotaxis and virulence of C. jejuni and lays a basis for the control of this foodborne pathogen.
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Affiliation(s)
- Qi Zhao
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China
| | - Fulian Yao
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China
| | - Wei Li
- Department of Clinical Laboratory, Qilu Hospital, Shandong University, Jinan, China
| | - Shuangjiang Liu
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China
- State Key Laboratory of Microbial Resources, and Environmental Microbiology Research Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China
| | - Shuangyu Bi
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China
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12
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Haregu F, Dixon RJ, Porter M, McCulloch M. Pediatric donor heart utilization variability among organ procurement organizations. Pediatr Transplant 2024; 28:e14747. [PMID: 38613143 PMCID: PMC11018341 DOI: 10.1111/petr.14747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 02/20/2024] [Accepted: 03/12/2024] [Indexed: 04/14/2024]
Abstract
BACKGROUND Organ procurement organizations (OPOs) are responsible for the medical management of organ donors. Given the variability in pediatric donor heart utilization among OPOs, we examined factors that may explain this variability, including differences in donor medical management, organ quality, and candidate factors. METHODS The Organ Procurement and Transplant Network database was queried for pediatric (<18 years) heart donors and candidates receiving pediatric donor heart offers from 2010 to 2019. OPOs were stratified by pediatric donor heart utilization rate, and the top and bottom quintiles were compared based on donor management strategies and outcomes. A machine learning algorithm, combining 11 OPO, donor, candidate, and offer variables, was used to determine factors most predictive of whether a heart offer is accepted. RESULTS There was no clinically significant difference between the top and bottom quintile OPOs in baseline donor characteristics, distance between donor and listing center, management strategies, or organ quality. Machine learning modeling suggested neither OPO donor management nor cardiac function is the primary driver of whether an organ is accepted. Instead, number of prior donor offer refusals and individual listing center receiving the offer were two of the most predictive variables of organ acceptance. CONCLUSIONS OPO clinical practice variation does not seem to account for the discrepancy in pediatric donor heart utilization rates among OPOs. Listing center acceptance practice and prior number of donor refusals seem to be the important drivers of heart utilization and may at least partially account for the variation in OPO heart utilization rates given the regional association between OPOs and listing centers.
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Affiliation(s)
- Firezer Haregu
- Pediatric Cardiology, University of Virginia Children’s Hospital, Charlottesville, VA
| | | | - Michael Porter
- Systems Engineering, University of Virginia, Charlottesville, VA
| | - Michael McCulloch
- Pediatric Cardiology, University of Virginia Children’s Hospital, Charlottesville, VA
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13
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Zhou K, Tang M, Zhang W, Chen Y, Guan Y, Huang R, Duan J, Liu Z, Ji X, Jiang Y, Hu Y, Zhang X, Zhou J, Chen M. Exposure to Molybdate Results in Metabolic Disorder: An Integrated Study of the Urine Elementome and Serum Metabolome in Mice. TOXICS 2024; 12:288. [PMID: 38668511 PMCID: PMC11053804 DOI: 10.3390/toxics12040288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 04/04/2024] [Accepted: 04/12/2024] [Indexed: 04/29/2024]
Abstract
The increasing use of molybdate has raised concerns about its potential toxicity in humans. However, the potential toxicity of molybdate under the current level of human exposure remains largely unknown. Endogenous metabolic alterations that are caused in humans by environmental exposure to pollutants are associated with the occurrence and progression of many diseases. This study exposed eight-week-old male C57 mice to sodium molybdate at doses relevant to humans (0.01 and 1 mg/kg/day) for eight weeks. Inductively coupled plasma mass spectrometry (ICP-MS) and ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS) were utilized to assess changes in urine element levels and serum metabolites in mice, respectively. A total of 838 subjects from the NHANES 2017-2018 population database were also included in our study to verify the associations between molybdenum and cadmium found in mice. Analysis of the metabolome in mice revealed that four metabolites in blood serum exhibited significant changes, including 5-aminolevulinic acid, glycolic acid, l-acetylcarnitine, and 2,3-dihydroxypropyl octanoate. Analysis of the elementome revealed a significant increase in urine levels of cadmium after molybdate exposure in mice. Notably, molybdenum also showed a positive correlation with cadmium in humans from the NHANES database. Further analysis identified a positive correlation between cadmium and 2,3-dihydroxypropyl octanoate in mice. In conclusion, these findings suggest that molybdate exposure disrupted amino acid and lipid metabolism, which may be partially mediated by molybdate-altered cadmium levels. The integration of elementome and metabolome data provides sensitive information on molybdate-induced metabolic disorders and associated toxicities at levels relevant to human exposure.
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Affiliation(s)
- Kun Zhou
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; (K.Z.); (M.T.); (Y.C.); (Y.G.); (R.H.); (J.D.); (Z.L.); (X.J.); (Y.J.); (J.Z.)
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Miaomiao Tang
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; (K.Z.); (M.T.); (Y.C.); (Y.G.); (R.H.); (J.D.); (Z.L.); (X.J.); (Y.J.); (J.Z.)
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Wei Zhang
- Sir Run Run Hospital of Nanjing Medical University, Nanjing 211166, China; (W.Z.); (Y.H.)
| | - Yanling Chen
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; (K.Z.); (M.T.); (Y.C.); (Y.G.); (R.H.); (J.D.); (Z.L.); (X.J.); (Y.J.); (J.Z.)
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yusheng Guan
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; (K.Z.); (M.T.); (Y.C.); (Y.G.); (R.H.); (J.D.); (Z.L.); (X.J.); (Y.J.); (J.Z.)
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Rui Huang
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; (K.Z.); (M.T.); (Y.C.); (Y.G.); (R.H.); (J.D.); (Z.L.); (X.J.); (Y.J.); (J.Z.)
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Jiawei Duan
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; (K.Z.); (M.T.); (Y.C.); (Y.G.); (R.H.); (J.D.); (Z.L.); (X.J.); (Y.J.); (J.Z.)
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Zibo Liu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; (K.Z.); (M.T.); (Y.C.); (Y.G.); (R.H.); (J.D.); (Z.L.); (X.J.); (Y.J.); (J.Z.)
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Xiaoming Ji
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; (K.Z.); (M.T.); (Y.C.); (Y.G.); (R.H.); (J.D.); (Z.L.); (X.J.); (Y.J.); (J.Z.)
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yingtong Jiang
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; (K.Z.); (M.T.); (Y.C.); (Y.G.); (R.H.); (J.D.); (Z.L.); (X.J.); (Y.J.); (J.Z.)
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yanhui Hu
- Sir Run Run Hospital of Nanjing Medical University, Nanjing 211166, China; (W.Z.); (Y.H.)
| | - Xiaoling Zhang
- Department of Hygienic Analysis and Detection, Nanjing Medical University, Nanjing 211166, China;
| | - Jingjing Zhou
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; (K.Z.); (M.T.); (Y.C.); (Y.G.); (R.H.); (J.D.); (Z.L.); (X.J.); (Y.J.); (J.Z.)
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Minjian Chen
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; (K.Z.); (M.T.); (Y.C.); (Y.G.); (R.H.); (J.D.); (Z.L.); (X.J.); (Y.J.); (J.Z.)
- Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
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Bao Z, Yu D, Fu J, Gu J, Xu J, Qin L, Hu H, Yang C, Liu W, Chen L, Wu R, Liu H, Xu H, Guo H, Wang L, Zhou Y, Li Q, Wang X. 2-Hydroxy-5-nitro-3-(trifluoromethyl)pyridine as a Novel Matrix for Enhanced MALDI Imaging of Tissue Metabolites. Anal Chem 2024; 96:5160-5169. [PMID: 38470972 DOI: 10.1021/acs.analchem.3c05235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/14/2024]
Abstract
Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), which is a label-free imaging technique, determines the spatial distribution and relative abundance of versatile endogenous metabolites in tissues. Meanwhile, matrix selection is generally regarded as a pivotal step in MALDI tissue imaging. This study presents the first report of a novel MALDI matrix, 2-hydroxy-5-nitro-3-(trifluoromethyl)pyridine (HNTP), for the in situ detection and imaging of endogenous metabolites in rat liver and brain tissues by MALDI-MS in positive-ion mode. The HNTP matrix exhibits excellent characteristics, including strong ultraviolet absorption, μm-scale matrix crystals, high chemical stability, low background ion interference, and high metabolite ionization efficiency. Notably, the HNTP matrix also shows superior detection capabilities, successfully showing 185 detectable metabolites in rat liver tissue sections. This outperforms the commonly used matrices of 2,5-dihydroxybenzoic acid and 2-mercaptobenzothiazole, which detect 145 and 120 metabolites from the rat liver, respectively. Furthermore, a total of 152 metabolites are effectively detected and imaged in rat brain tissue using the HNTP matrix, and the spatial distribution of these compounds clearly shows the heterogeneity of the rat brain. The results demonstrate that HNTP is a new and powerful positive-ion mode matrix to enhance the analysis of metabolites in biological tissues by MALDI-MSI.
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Affiliation(s)
- Zhibin Bao
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Dian Yu
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Jinxiang Fu
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Jianchi Gu
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Jia Xu
- Department of Clinical Laboratory, Xiyuan Hospital, China Academy of Chinese Medical Sciences, #1 Xiyuangcaochang, Beijing 100091, China
| | - Liang Qin
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Hao Hu
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Chenyu Yang
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Wenjuan Liu
- Department of Clinical Laboratory, Xiyuan Hospital, China Academy of Chinese Medical Sciences, #1 Xiyuangcaochang, Beijing 100091, China
| | - Lulu Chen
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Ran Wu
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Haiqiang Liu
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Hualei Xu
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Hua Guo
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Lei Wang
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Yijun Zhou
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
| | - Qi Li
- Department of Clinical Laboratory, Xiyuan Hospital, China Academy of Chinese Medical Sciences, #1 Xiyuangcaochang, Beijing 100091, China
| | - Xiaodong Wang
- Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), State Ethnic Affairs Commission, Beijing 100081, China
- Centre for Imaging & Systems Biology, College of Life and Environmental Sciences, Minzu University of China, #27 Zhongguancun South Avenue, Beijing 100081, China
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15
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Bland GD, Abrahamsson D, Wang M, Zlatnik MG, Morello-Frosch R, Park JS, Sirota M, Woodruff TJ. Exploring applications of non-targeted analysis in the characterization of the prenatal exposome. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169458. [PMID: 38142008 PMCID: PMC10947484 DOI: 10.1016/j.scitotenv.2023.169458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 12/15/2023] [Accepted: 12/15/2023] [Indexed: 12/25/2023]
Abstract
Capturing the breadth of chemical exposures in utero is critical in understanding their long-term health effects for mother and child. We explored methodological adaptations in a Non-Targeted Analysis (NTA) pipeline and evaluated the effects on chemical annotation and discovery for maternal and infant exposure. We focus on lesser-known/underreported chemicals in maternal and umbilical cord serum analyzed with liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS). The samples were collected from a demographically diverse cohort of 296 maternal-cord pairs (n = 592) recruited in San Francisco Bay area. We developed and evaluated two data processing pipelines, primarily differing by detection frequency cut-off, to extract chemical features from non-targeted analysis (NTA). We annotated the detected chemical features by matching with EPA CompTox Chemicals Dashboard (n = 860,000 chemicals) and Human Metabolome Database (n = 3140 chemicals) and applied a Kendrick Mass Defect filter to detect homologous series. We collected fragmentation spectra (MS/MS) on a subset of serum samples and matched to an experimental MS/MS database within the MS-Dial website and other experimental MS/MS spectra collected from standards in our lab. We annotated ~72 % of the features (total features = 32,197, levels 1-4). We confirmed 22 compounds with analytical standards, tentatively identified 88 compounds with MS/MS spectra, and annotated 4862 exogenous chemicals with an in-house developed annotation algorithm. We detected 36 chemicals that appear to not have been previously reported in human blood and 9 chemicals that were reported in less than five studies. Our findings underline the importance of NTA in the discovery of lesser-known/unreported chemicals important to characterize human exposures.
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Affiliation(s)
- Garret D Bland
- Department of Obstetrics, Gynecology and Reproductive Sciences, Program on Reproductive Health and the Environment, University of California San Francisco, San Francisco, CA, United States
| | - Dimitri Abrahamsson
- Department of Obstetrics, Gynecology and Reproductive Sciences, Program on Reproductive Health and the Environment, University of California San Francisco, San Francisco, CA, United States.
| | - Miaomiao Wang
- Department of Toxic Substances Control, California Environmental Protection Agency, Berkeley, CA, United States
| | - Marya G Zlatnik
- Department of Obstetrics, Gynecology and Reproductive Sciences, Program on Reproductive Health and the Environment, University of California San Francisco, San Francisco, CA, United States
| | - Rachel Morello-Frosch
- Department of Environmental Science, Policy and Management, School of Public Health, University of California Berkeley, Berkeley, CA, United States
| | - June-Soo Park
- Department of Obstetrics, Gynecology and Reproductive Sciences, Program on Reproductive Health and the Environment, University of California San Francisco, San Francisco, CA, United States; Department of Toxic Substances Control, California Environmental Protection Agency, Berkeley, CA, United States
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, Department of Pediatrics, University of California San Francisco, San Francisco 94158, CA, United States
| | - Tracey J Woodruff
- Department of Obstetrics, Gynecology and Reproductive Sciences, Program on Reproductive Health and the Environment, University of California San Francisco, San Francisco, CA, United States.
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16
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Chen L, Dai J, Yu G, Pang WW, Rahman ML, Liu X, Fiehn O, Guivarch C, Chen Z, Zhang C. Metabolomic Biomarkers of Dietary Approaches to Stop Hypertension (DASH) Dietary Patterns in Pregnant Women. Nutrients 2024; 16:492. [PMID: 38398816 PMCID: PMC10892314 DOI: 10.3390/nu16040492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 01/29/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
Objective: the aim of this study was to identify plasma metabolomic markers of Dietary Approaches to Stop Hypertension (DASH) dietary patterns in pregnant women. Methods: This study included 186 women who had both dietary intake and metabolome measured from a nested case-control study within the NICHD Fetal Growth Studies-Singletons cohort (FGS). Dietary intakes were ascertained at 8-13 gestational weeks (GW) using the Food Frequency Questionnaire (FFQ) and DASH scores were calculated based on eight food and nutrient components. Fasting plasma samples were collected at 15-26 GW and untargeted metabolomic profiling was performed. Multivariable linear regression models were used to examine the association of individual metabolites with the DASH score. Least absolute shrinkage and selection operator (LASSO) regression was used to select a panel of metabolites jointly associated with the DASH score. Results: Of the total 460 known metabolites, 92 were individually associated with DASH score in linear regressions, 25 were selected as a panel by LASSO regressions, and 18 were identified by both methods. Among the top 18 metabolites, there were 11 lipids and lipid-like molecules (i.e., TG (49:1), TG (52:2), PC (31:0), PC (35:3), PC (36:4) C, PC (36:5) B, PC (38:4) B, PC (42:6), SM (d32:0), gamma-tocopherol, and dodecanoic acid), 5 organic acids and derivatives (i.e., asparagine, beta-alanine, glycine, taurine, and hydroxycarbamate), 1 organic oxygen compound (i.e., xylitol), and 1 organoheterocyclic compound (i.e., maleimide). Conclusions: our study identified plasma metabolomic markers for DASH dietary patterns in pregnant women, with most of being lipids and lipid-like molecules.
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Affiliation(s)
- Liwei Chen
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA; (L.C.); (J.D.); (X.L.)
| | - Jin Dai
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA; (L.C.); (J.D.); (X.L.)
| | - Guoqi Yu
- Global Center for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; (G.Y.); (W.W.P.); (C.G.)
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity and Equality (ACRLE), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
| | - Wei Wei Pang
- Global Center for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; (G.Y.); (W.W.P.); (C.G.)
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity and Equality (ACRLE), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
| | - Mohammad L. Rahman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD 20850, USA;
| | - Xinyue Liu
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA; (L.C.); (J.D.); (X.L.)
| | - Oliver Fiehn
- West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, CA 95616, USA;
| | - Claire Guivarch
- Global Center for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; (G.Y.); (W.W.P.); (C.G.)
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity and Equality (ACRLE), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
| | - Zhen Chen
- Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institute of Health, Bethesda, MD 20892, USA;
| | - Cuilin Zhang
- Global Center for Asian Women’s Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore; (G.Y.); (W.W.P.); (C.G.)
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Bia-Echo Asia Centre for Reproductive Longevity and Equality (ACRLE), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
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17
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Liu E, Manji KP, Kirby MA, Kisenge R, Lauer JM, Fawzi WW, Sudfeld CR, Duggan CP. Effects of Zinc Supplementation on Metabolomic Profiles in Tanzanian Infants: A Randomized Trial. J Nutr 2024; 154:403-411. [PMID: 38092153 PMCID: PMC10900136 DOI: 10.1016/j.tjnut.2023.12.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 11/27/2023] [Accepted: 12/04/2023] [Indexed: 12/31/2023] Open
Abstract
BACKGROUND Provision of zinc supplementation to young children has been associated with reduced infectious morbidity and better growth outcomes. However, the metabolic pathways underlying these outcomes are unclear, and metabolomic data from humans undergoing zinc supplementation, particularly infants, are generally lacking. OBJECTIVES This study aimed to examine the effect of zinc supplementation on metabolic profiles in Tanzanian infants aged 6 wk and 6 mo. METHODS Blood samples were collected at age 6 wk and 6 mo from 50 Tanzanian infants who were enrolled in a randomized placebo-controlled trial of zinc supplementation (5 mg oral daily). Metabolomic analysis using an ultrahigh-performance liquid chromatography/tandem mass spectroscopy platform was performed to identify potential metabolomic profiles and biomarkers associated with zinc supplementation. Principal component analysis (PCA) was used to summarize metabolomic data from all samples. Two-way repeated measures analysis of variance with compound symmetry covariance structures were used to compare metabolome levels over time between infants in the 2 treatment arms. RESULTS In PCA, the samples tended to be more separated by child age (6 wk compared with 6 mo) than by zinc supplementation status. We found that zinc supplementation affected a variety of metabolites associated with amino acid, lipid, nucleotide, and xenobiotic metabolism, including indoleacetate in the tryptophan metabolism pathway; 3-methoxytrosine and 4-hydrxoyphenylphruvate in the tyrosine pathway; eicosanedioate, 2-aminooctanoate, and N-acetyl-2-aminooctanoate in the fatty acid pathway; and N6-succinyladenosine in the purine metabolism pathway. Compared to the relatively small number of metabolites associated with zinc supplements, many infant metabolites changed significantly from age 6 wk to 6 mo. CONCLUSIONS Zinc supplementation, despite having overall clinical benefits, appears to induce limited metabolomic changes in blood metabolites in young infants. Future larger studies may be warranted to further examine metabolic pathways associated with zinc supplementation. The parent trial was registered at clinicaltrials.gov as NCT00421668.
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Affiliation(s)
- Enju Liu
- Institutional Centers for Clinical and Translational Research, Boston Children's Hospital, Boston, MA, United States; Division of Gastroenterology, Hepatology and Nutrition, Boston Children's Hospital, Boston, MA, United States
| | - Karim P Manji
- Department of Pediatrics and Child Health, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - Miles A Kirby
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Rodrick Kisenge
- Department of Pediatrics and Child Health, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - Jacqueline M Lauer
- Department of Health Sciences, College of Health & Rehabilitation Sciences: Sargent College, Boston University, Boston, MA, United States
| | - Wafaie W Fawzi
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Christopher R Sudfeld
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Christopher P Duggan
- Division of Gastroenterology, Hepatology and Nutrition, Boston Children's Hospital, Boston, MA, United States; Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, United States; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, United States.
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18
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Balcells C, Xu Y, Gil-Solsona R, Maitre L, Gago-Ferrero P, Keun HC. Blurred lines: Crossing the boundaries between the chemical exposome and the metabolome. Curr Opin Chem Biol 2024; 78:102407. [PMID: 38086287 DOI: 10.1016/j.cbpa.2023.102407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 10/22/2023] [Accepted: 11/09/2023] [Indexed: 02/09/2024]
Abstract
The aetiology of every human disease lies in a combination of genetic and environmental factors, each contributing in varying proportions. While genomics investigates the former, a comparable holistic paradigm was proposed for environmental exposures in 2005, marking the onset of exposome research. Since then, the exposome definition has broadened to include a wide array of physical, chemical, and psychosocial factors that interact with the human body and potentially alter the epigenome, the transcriptome, the proteome, and the metabolome. The chemical exposome, deeply intertwined with the metabolome, includes all small molecules originating from diet as well as pharmaceuticals, personal care and consumer products, or pollutants in air and water. The set of techniques to interrogate these exposures, primarily mass spectrometry and nuclear magnetic resonance spectroscopy, are also extensively used in metabolomics. Recent advances in untargeted metabolomics using high resolution mass spectrometry have paved the way for the development of methods able to provide in depth characterisation of both the internal chemical exposome and the endogenous metabolome simultaneously. Herein we review the available tools, databases, and workflows currently available for such work, and discuss how these can bridge the gap between the study of the metabolome and the exposome.
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Affiliation(s)
- Cristina Balcells
- Institute of Developmental and Reproductive Biology (IRDB), Division of Cancer, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.
| | - Yitao Xu
- Institute of Developmental and Reproductive Biology (IRDB), Division of Cancer, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
| | - Rubén Gil-Solsona
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Léa Maitre
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Pablo Gago-Ferrero
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Hector C Keun
- Institute of Developmental and Reproductive Biology (IRDB), Division of Cancer, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.
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19
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Phillips KA, Chao A, Church RL, Favela K, Garantziotis S, Isaacs KK, Meyer B, Rice A, Sayre R, Wetmore BA, Yau A, Wambaugh JF. Suspect Screening Analysis of Pooled Human Serum Samples Using GC × GC/TOF-MS. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:1802-1812. [PMID: 38217501 DOI: 10.1021/acs.est.3c05092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2024]
Abstract
Humans interact with thousands of chemicals. This study aims to identify substances of emerging concern and in need of human health risk evaluations. Sixteen pooled human serum samples were constructed from 25 individual samples each from the National Institute of Environmental Health Sciences' Clinical Research Unit. Samples were analyzed using gas chromatography (GC) × GC/time-of-flight (TOF)-mass spectrometry (MS) in a suspect screening analysis, with follow-up confirmation analysis of 19 substances. A standard reference material blood sample was also analyzed through the confirmation process for comparison. The pools were stratified by sex (female and male) and by age (≤45 and >45). Publicly available information on potential exposure sources was aggregated to annotate presence in serum as either endogenous, food/nutrient, drug, commerce, or contaminant. Of the 544 unique substances tentatively identified by spectral matching, 472 were identified in females, while only 271 were identified in males. Surprisingly, 273 of the identified substances were found only in females. It is known that behavior and near-field environments can drive exposures, and this work demonstrates the existence of exposure sources uniquely relevant to females.
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Affiliation(s)
- Katherine A Phillips
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, North Carolina 27711, United States
| | - Alex Chao
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, North Carolina 27711, United States
| | - Rebecca L Church
- U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Environmental Health Sciences, Clinical Research Unit, Durham, North Carolina 27709, United States
| | - Kristin Favela
- Southwest Research Institute, San Antonio, Texas 78238, United States
| | - Stavros Garantziotis
- U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Environmental Health Sciences, Clinical Research Unit, Durham, North Carolina 27709, United States
| | - Kristin K Isaacs
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, North Carolina 27711, United States
| | - Brian Meyer
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, North Carolina 27711, United States
| | - Annette Rice
- U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Environmental Health Sciences, Clinical Research Unit, Durham, North Carolina 27709, United States
| | - Risa Sayre
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, North Carolina 27711, United States
| | - Barbara A Wetmore
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, North Carolina 27711, United States
| | - Alice Yau
- Southwest Research Institute, San Antonio, Texas 78238, United States
| | - John F Wambaugh
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, North Carolina 27711, United States
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20
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Mahajan P, Fiehn O, Barupal D. IDSL.GOA: Gene Ontology Analysis for Interpreting Metabolomic datasets. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.25.534225. [PMID: 37034715 PMCID: PMC10081191 DOI: 10.1101/2023.03.25.534225] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/17/2023]
Abstract
Biological interpretation of metabolomic datasets often ends at a pathway analysis step to find the over-represented metabolic pathways in the list of statistically significant metabolites. However, definitions of biochemical pathways and metabolite coverage vary among different curated databases, leading to missed interpretations. For the lists of genes, transcripts and proteins, Gene Ontology (GO) terms over-presentation analysis has become a standardized approach for biological interpretation. But, GO analysis has not been achieved for metabolomic datasets. We present a new knowledgebase (KB) and the online tool, Gene Ontology Analysis by the Integrated Data Science Laboratory for Metabolomics and Exposomics (IDSL.GOA) to conduct GO over-representation analysis for a metabolite list. The IDSL.GOA KB covers 2,393 metabolic GO terms and associated 3,144 genes, 1,492 EC annotations, and 2,621 metabolites. IDSL.GOA analysis of a case study of older vs young female brain cortex metabolome highlighted 82 GO terms being significantly overrepresented (FDR <0.05). We showed how IDSL.GOA identified key and relevant GO metabolic processes that were not yet covered in other pathway databases. Overall, we suggest that interpretation of metabolite lists should not be limited to only pathway maps and can also leverage GO terms as well. IDSL.GOA provides a useful tool for this purpose, allowing for a more comprehensive and accurate analysis of metabolite pathway data. IDSL.GOA tool can be accessed at https://goa.idsl.me/.
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Affiliation(s)
- Priyanka Mahajan
- Integrated Data Science Laboratory for Metabolomics and Exposomics, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, USA 10954
| | - Oliver Fiehn
- NIH-West Coast Metabolomics Center, University of California, Davis, California, 95616, USA
| | - Dinesh Barupal
- Integrated Data Science Laboratory for Metabolomics and Exposomics, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, USA 10954
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21
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Alvarez-Zapata M, Franco-Vega A, Rondero AG, Guerra RS, Flores BIJ, Comas-García M, Ovalle CO, Schneider B, Ratering S, Schnell S, Martinez-Gutierrez F. Modulation of the Altered Intestinal Microbiota by Use of Antibiotics with a Novel Synbiotic on Wistar Rats. Probiotics Antimicrob Proteins 2023:10.1007/s12602-023-10204-0. [PMID: 38127241 DOI: 10.1007/s12602-023-10204-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/09/2023] [Indexed: 12/23/2023]
Abstract
The use of antibiotics unbalances the intestinal microbiota. Probiotics, prebiotics, and synbiotics are alternatives for these unbalances. The effects of a new synbiotic composed of probiotic Saccharomyces boulardii CNCM I-745 and fructans from Agave salmiana (fAs) as prebiotics were assessed to modulate the intestinal microbiota. Two probiotic presentations, the commercial probiotic (CP) and the microencapsulated probiotic (MP) to improve those effects, were used to prepare the synbiotics and feed Wistar rats subjected to antibiotics (AB). Eight groups were studied, including five controls and three groups to modulate the microbiota after the use of antibiotics: G5: AB + MP-synbiotic, G6: AB + CP-synbiotic, and G8: AB + fAs. All treatments were administered daily for 7 days. On days 7 and 21, euthanasia was performed, cecum tissue was recovered and used to evaluate histological analysis and to study microphotograph by TEM, and finally, bacterial DNA was extracted and 16S rRNA gene metabarcode sequencing was performed. Histological analysis showed less epithelial damage and more abundance of the intestinal microbiota in the groups G5, G6, and G8 in comparison with the AB control group after 7 days. Microphotograph of the cecum at 2 weeks post treatment showed that G5 and G6 presented beneficial effects in epithelial reconstruction. Interestingly, in the groups that used the synbiotic without AB (G3 and G4) in addition to contributing to the recovery of the autochthonous microbiota, it promotes the development of beneficial microorganisms; those results were also achieved in the groups that used the synbiotic with AB enhancing the bacterial diversity and regulating the impact of AB.
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Affiliation(s)
- Miguel Alvarez-Zapata
- Laboratorio de Antimicrobianos, Biopelículas y Microbiota, Facultad de Ciencias Químicas, U.A.S.L.P., Av. Dr. Manuel Nava No. 6 Zona Universitaria, CP 78210, San Luis Potosí, S.L.P., México
| | - Avelina Franco-Vega
- Laboratorio de Tecnologías Emergentes, Facultad de Ciencias Químicas, U.A.S.L.P., San Luis Potosí, México
| | - Adriana Ganem Rondero
- Laboratorio de Investigación y Posgrado en Tecnología Farmacéutica (L-322), Facultad de Estudios Superiores Cuautitlán, Universidad Nacional Autónoma de México, Mexico City, Estado de México, México
| | - Ruth Soria Guerra
- Laboratorio de Biotecnología de plantas, Facultad de Ciencias Químicas, U.A.S.L.P., San Luis Potosí, México
| | | | - Mauricio Comas-García
- Sección de Genómica Médica, Centro de Investigación en Biomedicina y Salud, U.A.S.L.P., San Luis Potosí, México
- Sección de Microscopía de Alta Resolución, Centro de Investigación en Biomedicina y Salud, U.A.S.L.P., San Luis Potosí, Mexico
- Facultad de Ciencias, U.A.S.L.P., San Luis Potosi, Mexico
| | | | - Belinda Schneider
- Institute of Applied Microbiology, Justus Liebig University Giessen, Giessen, Germany
| | - Stefan Ratering
- Institute of Applied Microbiology, Justus Liebig University Giessen, Giessen, Germany
| | - Sylvia Schnell
- Institute of Applied Microbiology, Justus Liebig University Giessen, Giessen, Germany
| | - Fidel Martinez-Gutierrez
- Laboratorio de Antimicrobianos, Biopelículas y Microbiota, Facultad de Ciencias Químicas, U.A.S.L.P., Av. Dr. Manuel Nava No. 6 Zona Universitaria, CP 78210, San Luis Potosí, S.L.P., México.
- Sección de Genómica Médica, Centro de Investigación en Biomedicina y Salud, U.A.S.L.P., San Luis Potosí, México.
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22
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Chaker J, Gilles E, Monfort C, Chevrier C, Lennon S, David A. Scannotation: A Suspect Screening Tool for the Rapid Pre-Annotation of the Human LC-HRMS-Based Chemical Exposome. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:19253-19262. [PMID: 37968235 DOI: 10.1021/acs.est.3c04764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2023]
Abstract
In an increasingly chemically polluted environment, rapidly characterizing the human chemical exposome (i.e., chemical mixtures accumulating in humans) at the population scale is critical to understand its impact on health. High-resolution mass spectrometry (HRMS) profiling of complex biological matrices can theoretically provide a comprehensive picture of chemical exposures. However, annotating the detected chemical features, particularly low-abundant ones, remains a significant obstacle to implementing such approaches at a large scale. We present Scannotation (https://github.com/scannotation/Scannotation_software), an automated and user-friendly suspect screening tool for the rapid pre-annotation of HRMS preprocessed data sets. This software tool combines several MS1 chemical predictors, i.e., m/z, experimental and predicted retention times, isotopic patterns, and neutral loss patterns, to score the proximity between features and suspects, thus efficiently prioritizing tentative annotations to verify. Scannotation and MS-DIAL4 were used to annotate blood serum samples of 75 Breton adolescents. Scannotation's combination of MS1-based chemical predictors allowed us to annotate 89 chemically diverse environmental compounds with high confidence (confirmed by MS2 when available). These compounds included 62% of emerging molecules, for which no toxicological or human biomonitoring data are reported in the literature. The complementarity observed with MS-DIAL4 results demonstrates the relevance of Scannotation for the efficient pre-annotation of large-scale exposomics data sets.
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Affiliation(s)
- Jade Chaker
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France
| | - Erwann Gilles
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France
| | - Christine Monfort
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France
| | - Cécile Chevrier
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France
| | - Sarah Lennon
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France
| | - Arthur David
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France
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23
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Waly DA, Zeid AHA, Attia HN, Ahmed KA, El-Kashoury ESA, El Halawany AM, Mohammed RS. Comprehensive phytochemical characterization of Persea americana Mill. fruit via UPLC/HR-ESI-MS/MS and anti-arthritic evaluation using adjuvant-induced arthritis model. Inflammopharmacology 2023; 31:3243-3262. [PMID: 37936023 PMCID: PMC10692038 DOI: 10.1007/s10787-023-01365-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 10/06/2023] [Indexed: 11/09/2023]
Abstract
Persea americana Mill. (avocado fruit) has many health benefits when added to our diet due to various pharmacological activities, such as preventing bone loss and inflammation, modulating immune response and acting as an antioxidant. In the current study, the total ethanol extract (TEE) of the fruit was investigated for in vitro antioxidant and anti-inflammatory activity via DPPH and cyclooxygenase enzyme inhibition. Biological evaluation of the antiarthritic effect of the fruit extract was further investigated in vivo using Complete Freund's Adjuvant (CFA) arthritis model, where the average percentages of body weight change, inhibition of paw edema, basal paw diameter/weight and spleen index were estimated for all animal groups. Inflammatory mediators such as serum IL-6 and TNF-α were also determined, in addition to histopathological examination of the dissected limbs isolated from all experimental animals. Eighty-one metabolites belonging to different chemical classes were detected in the TEE of P. americana fruit via UPLC/HR-ESI-MS/MS. Two classes of lyso-glycerophospholipids; lyso-glycerophosphoethanolamines and lysoglycerophosphocholines were detected for the first time in avocado fruit in the positive mode. The TEE of fruit exhibited significant antioxidant and anti-inflammatory activity in vitro. In vivo anti-arthritic activity of the fruit TEE improved paw parameters, inflammatory mediators and spleen index. Histopathological findings showed marked improvements in the arthritic condition of the excised limbs. Therefore, avocado fruit could be proposed to be a powerful antioxidant and antiarthritic natural product.
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Affiliation(s)
- Dina Atef Waly
- Department of Pharmacognosy, National Research Centre (ID: 60014618), 33-Elbohouth St (Former El-Tahrir St.), Dokki, P.O. 12622, Giza, Egypt.
| | - Aisha Hussein Abou Zeid
- Department of Pharmacognosy, National Research Centre (ID: 60014618), 33-Elbohouth St (Former El-Tahrir St.), Dokki, P.O. 12622, Giza, Egypt
| | - Hanan Naeim Attia
- Medicinal and Pharmaceutical Chemistry Department (Pharmacology Group), National Research Centre (ID: 60014618), 33-Elbohouth St (Former El-Tahrir St.), Dokki, P.O. 12622, Giza, Egypt
| | - Kawkab A Ahmed
- Department of Pathology, Faculty of Veterinary Medicine, Cairo University, P.O. 12211, Giza, Egypt
| | | | - Ali Mahmoud El Halawany
- Pharmacognosy Department, Faculty of Pharmacy, Cairo University, Kasr-El Ainy Street, Cairo, 11562, Egypt
| | - Reda Sayed Mohammed
- Department of Pharmacognosy, National Research Centre (ID: 60014618), 33-Elbohouth St (Former El-Tahrir St.), Dokki, P.O. 12622, Giza, Egypt.
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24
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Michel ME, Wen CC, Yee SW, Giacomini KM, Hamdoun A, Nicklisch SCT. TICBase: Integrated Resource for Data on Drug and Environmental Chemical Interactions with Mammalian Drug Transporters. Clin Pharmacol Ther 2023; 114:1293-1303. [PMID: 37657924 DOI: 10.1002/cpt.3036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Accepted: 07/28/2023] [Indexed: 09/03/2023]
Abstract
Environmental health science seeks to predict how environmental toxins, chemical toxicants, and prescription drugs accumulate and interact within the body. Xenobiotic transporters of the ATP-binding cassette (ABC) and solute carrier (SLC) superfamilies are major determinants of the uptake and disposition of xenobiotics across the kingdoms of life. The goal of this study was to integrate drug and environmental chemical interactions of mammalian ABC and SLC proteins in a centralized, integrative database. We built upon an existing publicly accessible platform-the "TransPortal"-which was updated with novel data and searchable features on transporter-interfering chemicals from manually curated literature data. The integrated resource TransPortal-TICBase (https://transportal.compbio.ucsf.edu) now contains information on 46 different mammalian xenobiotic transporters of the ABC- and SLC-type superfamilies, including 13 newly added rodent and 2 additional human drug transporters, 126 clinical drug-drug interactions, and a more than quadrupled expansion of the initial in vitro chemical interaction data from 1,402 to 6,296 total interactions. Based on our updated database, environmental interference with major human and rodent drug transporters occurs across the ABC- and SLC-type superfamilies, with kinetics indicating that some chemicals, such as the ionic liquid 1-hexylpyridinium chloride and the antiseptic chlorhexidine, can act as strong inhibitors with potencies similar or even higher than pharmacological model inhibitors. The new integrated web portal serves as a central repository of current and emerging data for interactions of prescription drugs and environmental chemicals with human drug transporters. This archive has important implications for predicting adverse drug-drug and drug-environmental chemical interactions and can serve as a reference website for the broader scientific community of clinicians and researchers.
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Affiliation(s)
- Matthew E Michel
- Department of Environmental Toxicology, University of California, Davis, Davis, California, USA
| | | | - Sook Wah Yee
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA
| | - Kathleen M Giacomini
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA
| | - Amro Hamdoun
- Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, USA
| | - Sascha C T Nicklisch
- Department of Environmental Toxicology, University of California, Davis, Davis, California, USA
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25
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Akutsu H, Na’iem M, Widiyatno, Indrioko S, Sawitri, Purnomo S, Uchiyama K, Tsumura Y, Tani N. Comparing modeling methods of genomic prediction for growth traits of a tropical timber species, Shorea macrophylla. FRONTIERS IN PLANT SCIENCE 2023; 14:1241908. [PMID: 38023878 PMCID: PMC10644202 DOI: 10.3389/fpls.2023.1241908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Accepted: 09/13/2023] [Indexed: 12/01/2023]
Abstract
Introduction Shorea macrophylla is a commercially important tropical tree species grown for timber and oil. It is amenable to plantation forestry due to its fast initial growth. Genomic selection (GS) has been used in tree breeding studies to shorten long breeding cycles but has not previously been applied to S. macrophylla. Methods To build genomic prediction models for GS, leaves and growth trait data were collected from a half-sib progeny population of S. macrophylla in Sari Bumi Kusuma forest concession, central Kalimantan, Indonesia. 18037 SNP markers were identified in two ddRAD-seq libraries. Genomic prediction models based on these SNPs were then generated for diameter at breast height and total height in the 7th year from planting (D7 and H7). Results and discussion These traits were chosen because of their relatively high narrow-sense genomic heritability and because seven years was considered long enough to assess initial growth. Genomic prediction models were built using 6 methods and their derivatives with the full set of identified SNPs and subsets of 48, 96, and 192 SNPs selected based on the results of a genome-wide association study (GWAS). The GBLUP and RKHS methods gave the highest predictive ability for D7 and H7 with the sets of selected SNPs and showed that D7 has an additive genetic architecture while H7 has an epistatic genetic architecture. LightGBM and CNN1D also achieved high predictive abilities for D7 with 48 and 96 selected SNPs, and for H7 with 96 and 192 selected SNPs, showing that gradient boosting decision trees and deep learning can be useful in genomic prediction. Predictive abilities were higher in H7 when smaller number of SNP subsets selected by GWAS p-value was used, However, D7 showed the contrary tendency, which might have originated from the difference in genetic architecture between primary and secondary growth of the species. This study suggests that GS with GWAS-based SNP selection can be used in breeding for non-cultivated tree species to improve initial growth and reduce genotyping costs for next-generation seedlings.
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Affiliation(s)
- Haruto Akutsu
- Graduate School of Science and Technology, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Mohammad Na’iem
- Faculty of Forestry, Gadjah Mada University, Yogyakarta, Indonesia
| | - Widiyatno
- Faculty of Forestry, Gadjah Mada University, Yogyakarta, Indonesia
| | - Sapto Indrioko
- Faculty of Forestry, Gadjah Mada University, Yogyakarta, Indonesia
| | - Sawitri
- Faculty of Forestry, Gadjah Mada University, Yogyakarta, Indonesia
| | - Susilo Purnomo
- PT. Sari Bumi Kusuma, Pontianak, West Kalimantan, Indonesia
| | - Kentaro Uchiyama
- Department of Forest Molecular Genetics and Biotechnology, Forestry and Forest Products Research Institute, Tsukuba, Ibaraki, Japan
| | - Yoshihiko Tsumura
- Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Naoki Tani
- Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki, Japan
- Forestry Division, Japan International Research Center for Agricultural Sciences, Tsukuba, Ibaraki, Japan
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26
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Corvi JO, McKitrick A, Fernández JM, Fuenteslópez CV, Gelpí JL, Ginebra MP, Capella-Gutierrez S, Hakimi O. DEBBIE: The Open Access Database of Experimental Scaffolds and Biomaterials Built Using an Automated Text Mining Pipeline. Adv Healthc Mater 2023; 12:e2300150. [PMID: 37563883 DOI: 10.1002/adhm.202300150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/04/2023] [Indexed: 08/12/2023]
Abstract
Biomaterials research output has experienced an exponential increase over the last three decades. The majority of research is published in the form of scientific articles and is therefore available as unstructured text, making it a challenging input for computational processing. Computational tools are becoming essential to overcome this information overload. Among them, text mining systems present an attractive option for the automated extraction of information from text documents into structured datasets. This work presents the first automated system for biomaterial related information extraction from the National Library of Medicine's premier bibliographic database (MEDLINE) research abstracts into a searchable database. The system is a text mining pipeline that periodically retrieves abstracts from PubMed and identifies research and clinical studies of biomaterials. Thereafter, the pipeline identifies sixteen concept types of interest in the abstract using the Biomaterials Annotator, a tool for biomaterials Named Entity Recognition (NER). These concepts of interest, along with the abstract and relevant metadata are then deposited in DEBBIE, the Database of Experimental Biomaterials and their Biological Effect. DEBBIE is accessible through a web application that provides keyword searches and displays results in an intuitive and meaningful manner, aiming to facilitate an efficient mapping and organization of biomaterials information.
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Affiliation(s)
- Javier O Corvi
- Barcelona Supercomputing Center (BSC), Barcelona, 08034, Spain
| | | | | | - Carla V Fuenteslópez
- Institute of Biomedical Engineering, Botnar Research Centre, University of Oxford, Oxford, OX3 7LD, UK
| | - Josep L Gelpí
- Department of Biochemistry and Molecular Biology, University of Barcelona, Barcelona, 08014, Spain
| | - Maria-Pau Ginebra
- Department of Materials Science and Engineering, The Technical University of Catalonia, 08222, Barcelona, Spain
| | | | - Osnat Hakimi
- Faculty of Medicine and Health Sciences, The International University of Catalonia, Barcelona, 08017, Spain
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27
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Le TTN, Truong HB, Thi Hoa L, Le HS, Tran TTT, Manh TD, Le VT, Dinh QK, Nguyen XC. Cu 2O/Fe 3O 4/UiO-66 nanocomposite as an efficient fenton-like catalyst: Performance in organic pollutant degradation and influencing factors based machinelearning. Heliyon 2023; 9:e20466. [PMID: 37810813 PMCID: PMC10556788 DOI: 10.1016/j.heliyon.2023.e20466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 09/26/2023] [Accepted: 09/26/2023] [Indexed: 10/10/2023] Open
Abstract
The persistent presence of organic pollutants like dyes in water environment necessitates innovative approaches for efficient degradation. In this research, we developed an advanced hybrid catalyst by combining metal oxides (Cu2O, Fe3O4) with UiO-66, serving as a heterogeneous Fenton catalyst for for efficient RB19 breakdown in water with H2O2. The control factors to the catalytic behavior were also quantified by machine learning. Experimental results show that the catalytic performance was much better than its individual components (P < 0.05 & non-zero 95% C.I). The improved catalytic efficiency was linked to the occurrence of active metal centers (Fe, Cu, and Zr), with Cu(I) from Cu2O playing a crucial role in promoting increased production of HO•. Also, UiO-66 served as a catalyst support, attracting pollutants to the reaction center, while magnetic Fe3O4 aids catalyst recovery. The optimal experimental parameters for best performance were pH at 7, catalyst loading of 1.6 g/L, H2O2 strength of 0.16 M, and reaction temperature of 25 °C. The catalyst can be magnetically separated and regenerated after five recycling times without significantly reducing catalytic activity. The reaction time and pH were ranked as the most influencing factors on catalytic efficiency via Random Forest and SHapley Additive exPlanations models. The findings show that developed catalyst is a suitable candidate to remove dyes in water by Fenton heterogeneous reaction.
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Affiliation(s)
- Thi Thanh Nhi Le
- Center for Advanced Chemistry, Institute of Research and Development, Duy Tan University, 03 Quang Trung, Da Nang, Viet Nam
- Faculty of Natural Sciences, Duy Tan University, 03 Quang Trung, Da Nang, Viet Nam
| | - Hai Bang Truong
- Optical Materials Research Group, Science and Technology Advanced Institute, Van Lang University, Ho Chi Minh City, Viet Nam
- Faculty of Applied Technology, School of Technology, Van Lang University, Ho Chi Minh City, Viet Nam
| | - Le Thi Hoa
- University of Sciences, Hue University, 77 Nguyen Hue, Hue, Viet Nam
| | - Hoang Sinh Le
- VN-UK Institute for Research and Executive Education, University of Danang, Danang city, Viet Nam
| | - Thanh Tam Toan Tran
- Institute of Applied Technology, Thu Dau Mot University, Thu Dau Mot city, Viet Nam
| | - Tran Duc Manh
- University of Danang, University of Science and Education, Da Nang, Viet Nam
| | - Van Thuan Le
- Center for Advanced Chemistry, Institute of Research and Development, Duy Tan University, 03 Quang Trung, Da Nang, Viet Nam
- Faculty of Natural Sciences, Duy Tan University, 03 Quang Trung, Da Nang, Viet Nam
| | - Quang Khieu Dinh
- University of Sciences, Hue University, 77 Nguyen Hue, Hue, Viet Nam
| | - Xuan Cuong Nguyen
- Center for Advanced Chemistry, Institute of Research and Development, Duy Tan University, 03 Quang Trung, Da Nang, Viet Nam
- Faculty of Natural Sciences, Duy Tan University, 03 Quang Trung, Da Nang, Viet Nam
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28
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Offner T, Weiss L, Daume D, Berk A, Inderthal TJ, Manzini I, Hassenklöver T. Functional odor map heterogeneity is based on multifaceted glomerular connectivity in larval Xenopus olfactory bulb. iScience 2023; 26:107518. [PMID: 37636047 PMCID: PMC10448113 DOI: 10.1016/j.isci.2023.107518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 07/05/2023] [Accepted: 07/31/2023] [Indexed: 08/29/2023] Open
Abstract
Glomeruli are the functional units of the vertebrate olfactory bulb (OB) connecting olfactory receptor neuron (ORN) axons and mitral/tufted cell (MTC) dendrites. In amphibians, these two circuit elements regularly branch and innervate multiple, spatially distinct glomeruli. Using functional multiphoton-microscopy and single-cell tracing, we investigate the impact of this wiring on glomerular module organization and odor representations on multiple levels of the Xenopus laevis OB network. The glomerular odor map to amino acid odorants is neither stereotypic between animals nor chemotopically organized. Among the morphologically heterogeneous group of uni- and multi-glomerular MTCs, MTCs can selectively innervate glomeruli formed by axonal branches of individual ORNs. We conclude that odor map heterogeneity is caused by the coexistence of different intermingled glomerular modules. This demonstrates that organization of the amphibian main olfactory system is not strictly based on uni-glomerular connectivity.
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Affiliation(s)
- Thomas Offner
- Institute of Animal Physiology, Department of Animal Physiology and Molecular Biomedicine, Justus-Liebig-University Giessen, 35392 Giessen, Germany
| | - Lukas Weiss
- Institute of Animal Physiology, Department of Animal Physiology and Molecular Biomedicine, Justus-Liebig-University Giessen, 35392 Giessen, Germany
| | - Daniela Daume
- Institute of Animal Physiology, Department of Animal Physiology and Molecular Biomedicine, Justus-Liebig-University Giessen, 35392 Giessen, Germany
| | - Anna Berk
- Institute of Animal Physiology, Department of Animal Physiology and Molecular Biomedicine, Justus-Liebig-University Giessen, 35392 Giessen, Germany
| | - Tim Justin Inderthal
- Institute of Animal Physiology, Department of Animal Physiology and Molecular Biomedicine, Justus-Liebig-University Giessen, 35392 Giessen, Germany
| | - Ivan Manzini
- Institute of Animal Physiology, Department of Animal Physiology and Molecular Biomedicine, Justus-Liebig-University Giessen, 35392 Giessen, Germany
| | - Thomas Hassenklöver
- Institute of Animal Physiology, Department of Animal Physiology and Molecular Biomedicine, Justus-Liebig-University Giessen, 35392 Giessen, Germany
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29
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Carvantes-Barrera A, Díaz-González L, Rosales-Rivera M, Chávez-Almazán LA. Risk Factors Associated with COVID-19 Lethality: A Machine Learning Approach Using Mexico Database. J Med Syst 2023; 47:90. [PMID: 37597034 DOI: 10.1007/s10916-023-01979-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 07/21/2023] [Indexed: 08/21/2023]
Abstract
Identifying risk factors associated with COVID-19 lethality is crucial in combating the ongoing pandemic. In this study, we developed lethality predictive models for each epidemiological wave and for the overall dataset using the Extreme Gradient Boosting technique and analyzed them using Shapley values to determine the contribution levels of various features, including demographics, comorbidities, medical units, and recent medical information from confirmed COVID-19 cases in Mexico between February 23, 2020, and April 15, 2022. The results showed that pneumonia and advanced age were the most important factors predicting patient death in all cohorts. Additionally, the medical unit where the patient received care acted as a risk or protective factor. IMSS medical units were identified as high-risk factors in all cohorts, except in wave four, while SSA medical units generally were moderate protective factors. We also found that intubation was a high-risk factor in the first epidemiological wave and a moderate-risk factor in the following waves. Female gender was a protective factor of moderate-high importance in all cohorts, while being between 18 and 29 years old was a moderate protective factor and being between 50 and 59 years old was a moderate risk factor. Additionally, diabetes (all cohorts), obesity (third wave), and hypertension (fourth wave) were identified as moderate risk factors. Finally, residing in municipalities with the lowest Human Development Index level represented a moderate risk factor. In conclusion, this study identified several significant risk factors associated with COVID-19 lethality in Mexico, which could aid policymakers in developing targeted interventions to reduce mortality rates.
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Affiliation(s)
- Alejandro Carvantes-Barrera
- Maestría en Optimización y Cómputo Aplicado, Universidad Autónoma del Estado de Morelos, Cuernavaca, 62209, Morelos, México
| | - Lorena Díaz-González
- Centro de Investigación en Ciencias, Universidad Autónoma del Estado de Morelos, Cuernavaca, 62209, Morelos, México.
| | - Mauricio Rosales-Rivera
- Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, 62209, México
| | - Luis A Chávez-Almazán
- Unidad de Innovación Clínica y Epidemiológica del Estado de Guerrero, Acapulco, Guerrero, 39715, México
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30
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Du Q, Wang X, Chen J, Xiong C, Liu W, Liu J, Liu H, Jiang L, Nie Z. Urine and serum metabolic profiling combined with machine learning for autoimmune disease discrimination and classification. Chem Commun (Camb) 2023; 59:9852-9855. [PMID: 37490058 DOI: 10.1039/d3cc01861j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/26/2023]
Abstract
Precision diagnosis and classification of autoimmune diseases (ADs) is challenging due to the obscure symptoms and pathological causes. Biofluid metabolic analysis has the potential for disease screening, in which high throughput, rapid analysis and minimum sample consumption must be addressed. Herein, we performed metabolomic profiling by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) in urine and serum samples. Combined with machine learning (ML), metabolomic patterns from urine achieved the discrimination and classification of ADs with high accuracy. Furthermore, metabolic disturbances among different ADs were also investigated, and provided information of etiology. These results demonstrated that urine metabolic patterns based on MALDI-MS and ML manifest substantial potential in precision medicine.
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Affiliation(s)
- Qiuyao Du
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiao Wang
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Junyu Chen
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Caiqiao Xiong
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenlan Liu
- The Center for Medical Genetics & Molecular Diagnosis, Shenzhen Second People's Hospital/the First Affiliated Hospital of Shenzhen University Health Sciences Center, Shenzhen 518035, China
| | - Jianfeng Liu
- Department of Laboratory Medicine, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi Province 341000, China
| | - Huihui Liu
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lixia Jiang
- Department of Laboratory Medicine, First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi Province 341000, China
| | - Zongxiu Nie
- Beijing National Laboratory for Molecular Sciences, Key Laboratory of Analytical Chemistry for Living Biosystems, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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Vigderovich H, Eckert W, Elvert M, Gafni A, Rubin-Blum M, Bergman O, Sivan O. Aerobic methanotrophy increases the net iron reduction in methanogenic lake sediments. Front Microbiol 2023; 14:1206414. [PMID: 37577416 PMCID: PMC10415106 DOI: 10.3389/fmicb.2023.1206414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 07/10/2023] [Indexed: 08/15/2023] Open
Abstract
In methane (CH4) generating sediments, methane oxidation coupled with iron reduction was suggested to be catalyzed by archaea and bacterial methanotrophs of the order Methylococcales. However, the co-existence of these aerobic and anaerobic microbes, the link between the processes, and the oxygen requirement for the bacterial methanotrophs have remained unclear. Here, we show how stimulation of aerobic methane oxidation at an energetically low experimental environment influences net iron reduction, accompanied by distinct microbial community changes and lipid biomarker patterns. We performed incubation experiments (between 30 and 120 days long) with methane generating lake sediments amended with 13C-labeled methane, following the additions of hematite and different oxygen levels in nitrogen headspace, and monitored methane turnover by 13C-DIC measurements. Increasing oxygen exposure (up to 1%) promoted aerobic methanotrophy, considerable net iron reduction, and the increase of microbes, such as Methylomonas, Geobacter, and Desulfuromonas, with the latter two being likely candidates for iron recycling. Amendments of 13C-labeled methanol as a potential substrate for the methanotrophs under hypoxia instead of methane indicate that this substrate primarily fuels methylotrophic methanogenesis, identified by high methane concentrations, strongly positive δ13CDIC values, and archaeal lipid stable isotope data. In contrast, the inhibition of methanogenesis by 2-bromoethanesulfonate (BES) led to increased methanol turnover, as suggested by similar 13C enrichment in DIC and high amounts of newly produced bacterial fatty acids, probably derived from heterotrophic bacteria. Our experiments show a complex link between aerobic methanotrophy and iron reduction, which indicates iron recycling as a survival mechanism for microbes under hypoxia.
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Affiliation(s)
- Hanni Vigderovich
- Department of Earth and Environmental Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Werner Eckert
- The Yigal Allon Kinneret Limnological Laboratory, Israel Oceanographic and Limnological Research, Migdal, Israel
| | - Marcus Elvert
- MARUM—Center for Marine Environmental Sciences and Faculty of Geosciences, University of Bremen, Bremen, Germany
| | - Almog Gafni
- Department of Earth and Environmental Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Maxim Rubin-Blum
- Israel Oceanographic and Limnological Research, National Institute of Oceanography, Haifa, Israel
| | - Oded Bergman
- Department of Earth and Environmental Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
- The Yigal Allon Kinneret Limnological Laboratory, Israel Oceanographic and Limnological Research, Migdal, Israel
| | - Orit Sivan
- Department of Earth and Environmental Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel
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32
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McClanahan PD, Golinelli L, Le TA, Temmerman L. Automated scoring of nematode nictation on a textured background. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.16.533066. [PMID: 36993316 PMCID: PMC10055289 DOI: 10.1101/2023.03.16.533066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Entomopathogenic nematodes including Steinernema spp. play an increasingly important role as biological alternatives to chemical pesticides. The infective juveniles of these worms use nictation - a behavior in which animals stand on their tails - as a host-seeking strategy. The developmentally-equivalent dauer larvae of the free-living nematode Caenorhabditis elegans also nictate, but as a means of phoresy or "hitching a ride" to a new food source. Advanced genetic and experimental tools have been developed for C. elegans , but time-consuming manual scoring of nictation slows efforts to understand this behavior, and the textured substrates required for nictation can frustrate traditional machine vision segmentation algorithms. Here we present a Mask R-CNN-based tracker capable of segmenting C. elegans dauers and S. carpocapsae infective juveniles on a textured background suitable for nictation, and a machine learning pipeline that scores nictation behavior. We use our system to show that the nictation propensity of C. elegans from high-density liquid cultures largely mirrors their development into dauers, and to quantify nictation in S. carpocapsae infective juveniles in the presence of a potential host. This system is an improvement upon existing intensity-based tracking algorithms and human scoring which can facilitate large-scale studies of nictation and potentially other nematode behaviors.
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Affiliation(s)
- Patrick D. McClanahan
- Animal Physiology and Neurobiology, Department of Biology, KU Leuven, Leuven, Belgium
| | - Luca Golinelli
- Animal Physiology and Neurobiology, Department of Biology, KU Leuven, Leuven, Belgium
| | - Tuan Anh Le
- Animal Physiology and Neurobiology, Department of Biology, KU Leuven, Leuven, Belgium
| | - Liesbet Temmerman
- Animal Physiology and Neurobiology, Department of Biology, KU Leuven, Leuven, Belgium
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Huang K, Zhou W, Fu J, Zhang Q, Teng Y, Gu L, Fu Y, Hu B, Mei Y, Zhang H, Zhang A, Fu J, Jiang G. Linking Transthyretin-Binding Chemicals and Free Thyroid Hormones: In Vitro to In Vivo Extrapolation Based on a Competitive Binding Model. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:9130-9139. [PMID: 37261382 DOI: 10.1021/acs.est.3c01094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Large numbers of pollutants competitively inhibit the binding between thyroid hormones and transthyretin (TTR) in vitro. However, the impact of this unintended binding on free thyroid hormones in vivo has not yet been characterized. Herein, we established a quantitative in vitro to in vivo extrapolation (QIVIVE) method based on a competitive binding model to quantify the effect of TTR-binding chemicals on free thyroid hormones in human blood. Twenty-five TTR-binding chemicals including 6 hydroxyl polybromodiphenyl ethers (OH-PDBEs), 6 hydroxyl polychlorobiphenyls (OH-PCBs), 4 halogenphenols, 5 per- and polyfluorinated substances (PFASs), and 4 phenols were selected for investigation. Incorporating the in vitro binding parameters and human exposure data, the QIVIVE model could well predict the in vivo effect on free thyroid hormones. Co-exposure to twenty-five typical TTR-binding chemicals resulted in median increases of 0.080 and 0.060% in circulating levels of free thyroxine (FT4) and free triiodothyronine (FT3) in the general population. Individuals with occupational exposure to TTR-binding chemicals suffered 1.88-32.2% increases in free thyroid hormone levels. This study provides a quantitative tool to evaluate the thyroid-disrupting risks of TTR-binding chemicals and proposes a new framework for assessing the in vivo effects of chemical exposures on endogenous molecules.
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Affiliation(s)
- Kai Huang
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Wei Zhou
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Jie Fu
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Qun Zhang
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yunhe Teng
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Luyao Gu
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yilin Fu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Boyuan Hu
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yang Mei
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
| | - Haiyan Zhang
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
| | - Aiqian Zhang
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Institute of Environment and Health, Jianghan University, Wuhan 430056, China
| | - Jianjie Fu
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Institute of Environment and Health, Jianghan University, Wuhan 430056, China
| | - Guibin Jiang
- School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Institute of Environment and Health, Jianghan University, Wuhan 430056, China
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Chen J, Zhou J, Li Q, Li H, Xia Y, Jackson R, Sun G, Zhou G, Deakin G, Jiang D, Zhou J. CropQuant-Air: an AI-powered system to enable phenotypic analysis of yield- and performance-related traits using wheat canopy imagery collected by low-cost drones. FRONTIERS IN PLANT SCIENCE 2023; 14:1219983. [PMID: 37404534 PMCID: PMC10316027 DOI: 10.3389/fpls.2023.1219983] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 05/26/2023] [Indexed: 07/06/2023]
Abstract
As one of the most consumed stable foods around the world, wheat plays a crucial role in ensuring global food security. The ability to quantify key yield components under complex field conditions can help breeders and researchers assess wheat's yield performance effectively. Nevertheless, it is still challenging to conduct large-scale phenotyping to analyse canopy-level wheat spikes and relevant performance traits, in the field and in an automated manner. Here, we present CropQuant-Air, an AI-powered software system that combines state-of-the-art deep learning (DL) models and image processing algorithms to enable the detection of wheat spikes and phenotypic analysis using wheat canopy images acquired by low-cost drones. The system includes the YOLACT-Plot model for plot segmentation, an optimised YOLOv7 model for quantifying the spike number per m2 (SNpM2) trait, and performance-related trait analysis using spectral and texture features at the canopy level. Besides using our labelled dataset for model training, we also employed the Global Wheat Head Detection dataset to incorporate varietal features into the DL models, facilitating us to perform reliable yield-based analysis from hundreds of varieties selected from main wheat production regions in China. Finally, we employed the SNpM2 and performance traits to develop a yield classification model using the Extreme Gradient Boosting (XGBoost) ensemble and obtained significant positive correlations between the computational analysis results and manual scoring, indicating the reliability of CropQuant-Air. To ensure that our work could reach wider researchers, we created a graphical user interface for CropQuant-Air, so that non-expert users could readily use our work. We believe that our work represents valuable advances in yield-based field phenotyping and phenotypic analysis, providing useful and reliable toolkits to enable breeders, researchers, growers, and farmers to assess crop-yield performance in a cost-effective approach.
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Affiliation(s)
- Jiawei Chen
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University, Nanjing, China
- College of Engineering, Nanjing Agricultural University, Nanjing, China
| | - Jie Zhou
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University, Nanjing, China
- College of Engineering, Nanjing Agricultural University, Nanjing, China
| | - Qing Li
- Regional Technique Innovation Center for Wheat Production, Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, China
| | - Hanghang Li
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University, Nanjing, China
| | - Yunpeng Xia
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University, Nanjing, China
| | - Robert Jackson
- Cambridge Crop Research, National Institute of Agricultural Botany (NIAB), Cambridge, United Kingdom
| | - Gang Sun
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University, Nanjing, China
| | - Guodong Zhou
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University, Nanjing, China
| | - Greg Deakin
- Cambridge Crop Research, National Institute of Agricultural Botany (NIAB), Cambridge, United Kingdom
| | - Dong Jiang
- Regional Technique Innovation Center for Wheat Production, Key Laboratory of Crop Physiology and Ecology in Southern China, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, China
| | - Ji Zhou
- State Key Laboratory of Crop Genetics & Germplasm Enhancement, Academy for Advanced Interdisciplinary Studies, Nanjing Agricultural University, Nanjing, China
- Cambridge Crop Research, National Institute of Agricultural Botany (NIAB), Cambridge, United Kingdom
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Fothergill DM, Borras E, McCartney MM, Schelegle E, Davis CE. Exhaled breath condensate profiles of U.S. Navy divers following prolonged hyperbaric oxygen (HBO) and nitrogen-oxygen (Nitrox) chamber exposures. J Breath Res 2023; 17:10.1088/1752-7163/acd715. [PMID: 37207635 PMCID: PMC11057948 DOI: 10.1088/1752-7163/acd715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 05/19/2023] [Indexed: 05/21/2023]
Abstract
Prolonged exposure to hyperbaric hyperoxia can lead to pulmonary oxygen toxicity (PO2tox). PO2tox is a mission limiting factor for special operations forces divers using closed-circuit rebreathing apparatus and a potential side effect for patients undergoing hyperbaric oxygen (HBO) treatment. In this study, we aim to determine if there is a specific breath profile of compounds in exhaled breath condensate (EBC) that is indicative of the early stages of pulmonary hyperoxic stress/PO2tox. Using a double-blind, randomized 'sham' controlled, cross-over design 14 U.S. Navy trained diver volunteers breathed two different gas mixtures at an ambient pressure of 2 ATA (33 fsw, 10 msw) for 6.5 h. One test gas consisted of 100% O2(HBO) and the other was a gas mixture containing 30.6% O2with the balance N2(Nitrox). The high O2stress dive (HBO) and low O2stress dive (Nitrox) were separated by at least seven days and were conducted dry and at rest inside a hyperbaric chamber. EBC samples were taken immediately before and after each dive and subsequently underwent a targeted and untargeted metabolomics analysis using liquid chromatography coupled to mass spectrometry (LC-MS). Following the HBO dive, 10 out of 14 subjects reported symptoms of the early stages of PO2tox and one subject terminated the dive early due to severe symptoms of PO2tox. No symptoms of PO2tox were reported following the nitrox dive. A partial least-squares discriminant analysis of the normalized (relative to pre-dive) untargeted data gave good classification abilities between the HBO and nitrox EBC with an AUC of 0.99 (±2%) and sensitivity and specificity of 0.93 (±10%) and 0.94 (±10%), respectively. The resulting classifications identified specific biomarkers that included human metabolites and lipids and their derivatives from different metabolic pathways that may explain metabolomic changes resulting from prolonged HBO exposure.
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Affiliation(s)
| | - Eva Borras
- Mechanical and Aerospace Engineering, One Shields Avenue, University of California, Davis, Davis, California, USA
- UC Davis Lung Center, One Shields Avenue, University of California, Davis, Davis, California, USA
| | - Mitchell M. McCartney
- Mechanical and Aerospace Engineering, One Shields Avenue, University of California, Davis, Davis, California, USA
- UC Davis Lung Center, One Shields Avenue, University of California, Davis, Davis, California, USA
- VA Northern California Health Care System, Mather, California, USA
| | - Edward Schelegle
- Department of Anatomy, Physiology, and Cell Biology, School of Veterinary Medicine, University of California, Davis, Davis, California, USA
| | - Cristina E. Davis
- Mechanical and Aerospace Engineering, One Shields Avenue, University of California, Davis, Davis, California, USA
- UC Davis Lung Center, One Shields Avenue, University of California, Davis, Davis, California, USA
- VA Northern California Health Care System, Mather, California, USA
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36
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Tăuƫan AM, Casula EP, Pellicciari MC, Borghi I, Maiella M, Bonni S, Minei M, Assogna M, Palmisano A, Smeralda C, Romanella SM, Ionescu B, Koch G, Santarnecchi E. TMS-EEG perturbation biomarkers for Alzheimer's disease patients classification. Sci Rep 2023; 13:7667. [PMID: 37169900 PMCID: PMC10175269 DOI: 10.1038/s41598-022-22978-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 10/21/2022] [Indexed: 05/13/2023] Open
Abstract
The combination of TMS and EEG has the potential to capture relevant features of Alzheimer's disease (AD) pathophysiology. We used a machine learning framework to explore time-domain features characterizing AD patients compared to age-matched healthy controls (HC). More than 150 time-domain features including some related to local and distributed evoked activity were extracted from TMS-EEG data and fed into a Random Forest (RF) classifier using a leave-one-subject out validation approach. The best classification accuracy, sensitivity, specificity and F1 score were of 92.95%, 96.15%, 87.94% and 92.03% respectively when using a balanced dataset of features computed globally across the brain. The feature importance and statistical analysis revealed that the maximum amplitude of the post-TMS signal, its Hjorth complexity and the amplitude of the TEP calculated in the window 45-80 ms after the TMS-pulse were the most relevant features differentiating AD patients from HC. TMS-EEG metrics can be used as a non-invasive tool to further understand the AD pathophysiology and possibly contribute to patients' classification as well as longitudinal disease tracking.
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Affiliation(s)
- Alexandra-Maria Tăuƫan
- Precision Neuroscience and Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- AI Multimedia Lab, Research Center CAMPUS, University Politehnica of Bucharest, 061344, Bucharest, Romania
| | - Elias P Casula
- Santa Lucia Foundation, 00179, Rome, Italy
- Department of Psychology, La Sapienza University, Via dei Marsi 78, 00185, Rome, Italy
| | | | | | | | | | | | | | - Annalisa Palmisano
- Precision Neuroscience and Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Department of Education, Psychology and Communication, University of Bari Aldo Moro, Bari, Italy
| | - Carmelo Smeralda
- Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery, Neurology and Clinical Neurophysiology Section, University of Siena, Siena, Italy
| | - Sara M Romanella
- Precision Neuroscience and Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Siena Brain Investigation & Neuromodulation Lab (Si-BIN Lab), Department of Medicine, Surgery, Neurology and Clinical Neurophysiology Section, University of Siena, Siena, Italy
| | - Bogdan Ionescu
- AI Multimedia Lab, Research Center CAMPUS, University Politehnica of Bucharest, 061344, Bucharest, Romania
| | - Giacomo Koch
- Department of Neuroscience and Rehabilitation, Section of Human Physiology, University of Ferrara, 44121, Ferrara, Italy
- Santa Lucia Foundation, 00179, Rome, Italy
| | - Emiliano Santarnecchi
- Precision Neuroscience and Neuromodulation Program & Network Control Laboratory, Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Berenson-Allen Center for Noninvasive Brain Stimulation, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
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37
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Balachandran K, Ramli R, Karsani SA, Abdul Rahman M. Identification of Potential Biomarkers and Small Molecule Drugs for Bisphosphonate-Related Osteonecrosis of the Jaw (BRONJ): An Integrated Bioinformatics Study Using Big Data. Int J Mol Sci 2023; 24:ijms24108635. [PMID: 37239981 DOI: 10.3390/ijms24108635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 04/18/2023] [Accepted: 04/25/2023] [Indexed: 05/28/2023] Open
Abstract
This study aimed to identify potential molecular mechanisms and therapeutic targets for bisphosphonate-related osteonecrosis of the jaw (BRONJ), a rare but serious side effect of bisphosphonate therapy. This study analyzed a microarray dataset (GSE7116) of multiple myeloma patients with BRONJ (n = 11) and controls (n = 10), and performed gene ontology, a pathway enrichment analysis, and a protein-protein interaction network analysis. A total of 1481 differentially expressed genes were identified, including 381 upregulated and 1100 downregulated genes, with enriched functions and pathways related to apoptosis, RNA splicing, signaling pathways, and lipid metabolism. Seven hub genes (FN1, TNF, JUN, STAT3, ACTB, GAPDH, and PTPRC) were also identified using the cytoHubba plugin in Cytoscape. This study further screened small-molecule drugs using CMap and verified the results using molecular docking methods. This study identified 3-(5-(4-(Cyclopentyloxy)-2-hydroxybenzoyl)-2-((3-hydroxybenzo[d]isoxazol-6-yl) methoxy) phenyl) propanoic acid as a potential drug treatment and prognostic marker for BRONJ. The findings of this study provide reliable molecular insight for biomarker validation and potential drug development for the screening, diagnosis, and treatment of BRONJ. Further research is needed to validate these findings and develop an effective biomarker for BRONJ.
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Affiliation(s)
- Kumarendran Balachandran
- Department of Craniofacial Diagnostics and Biosciences, Faculty of Dentistry, University Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, Kuala Lumpur 50300, Malaysia
| | - Roszalina Ramli
- Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Universiti Kebangsaan Malaysia, Kuala Lumpur 50300, Malaysia
| | - Saiful Anuar Karsani
- Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia
| | - Mariati Abdul Rahman
- Department of Craniofacial Diagnostics and Biosciences, Faculty of Dentistry, University Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, Kuala Lumpur 50300, Malaysia
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Chang CW, Hsu JY, Su YH, Chen YC, Hsiao PZ, Liao PC. Monitoring long-term chemical exposome by characterizing the hair metabolome using a high-resolution mass spectrometry-based suspect screening approach. CHEMOSPHERE 2023; 332:138864. [PMID: 37156292 DOI: 10.1016/j.chemosphere.2023.138864] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 03/20/2023] [Accepted: 05/05/2023] [Indexed: 05/10/2023]
Abstract
Hair has recently emerged as a biospecimen for characterizing the long-term chemical exposome in biomonitoring investigations spanning several months, as chemical compounds circulating in the bloodstream accumulate in hair. Although there has been interest in using human hair as a biospecimen for exposome studies, it has yet to be widely adopted compared to blood and urine. Here, we applied a high-resolution mass spectrometry (HRMS)-based suspect screening strategy to characterize the long-term chemical exposome in human hair. Hair samples were collected from 70 subjects and cut into 3 cm segments, which were then mixed to prepare pooled samples. The pooled hair samples underwent a sample preparation procedure, and the hair extracts were further analyzed using an HRMS-based suspect screening approach. An in-house chemical suspect list containing 1227 chemical entries from National Report on Human Exposure to Environmental Chemicals (Report) published by the U.S. CDC and the Exposome-Explorer 3.0 database developed by the WHO was subsequently used to screen and filter the suspect features against the HRMS dataset. Overall, we matched 587 suspect features in the HRMS dataset to 246 unique chemical formulas in the suspect list, and the structures of 167 chemicals were further identified through a fragmentation analysis. Among these, chemicals such as mono-2-ethylhexyl phthalate, methyl paraben, and 1-naphthol, which have been detected in the urine or blood for exposure assessment, were also identified in human hair. This suggests that hair reflects the accumulation of environmental compounds to which an individual is exposed. Exposure to exogenous chemicals may exert adverse effects on cognitive function, and we discovered 15 chemicals in human hair that may contribute to the pathogenesis of Alzheimer's disease. This finding suggests that human hair may be a promising biospecimen for monitoring long-term exposure to multiple environmental chemicals and perturbations in endogenous chemicals in biomonitoring investigations.
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Affiliation(s)
- Chih-Wei Chang
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Jen-Yi Hsu
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Yu-Hsiang Su
- Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, 60002, Taiwan
| | - Yuan-Chih Chen
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Ping-Zu Hsiao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Pao-Chi Liao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Food Safety/Hygiene and Risk Management, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
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Yi Z, Dong S, Wang X, Xu M, Li Y, Xie L. Exploratory study on noninvasive biomarker of silicosis in exhaled breath by solid-phase microextraction-gas chromatography-mass spectrometry analysis. Int Arch Occup Environ Health 2023:10.1007/s00420-023-01971-y. [PMID: 37067574 DOI: 10.1007/s00420-023-01971-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 03/25/2023] [Indexed: 04/18/2023]
Abstract
BACKGROUND As a chronic occupational disease, silicosis could cause irreversible and incurable impair to the lung. The current diagnosis of silicosis relies on imaging of X-ray or CT, but these methods cannot detect lung lesions in the early stage of silicosis. OBJECTIVE To establish a regular screening and early diagnosis methods for silicosis, which could be helpful for the prevention and treatment of silicosis. METHODS A total of 161 subjects were enrolled in the study, including 69 patients with silicosis (SILs) and 92 healthy controls. The exhaled breath samples of the subjects were collected with breath sampler and Tedlar bag. The analysis of volatile organic compounds (VOCs) in exhaled breath was performed by solid-phase microextraction (SPME) combined with gas chromatography mass spectrometry (GC-MS). RESULTS After excluding the pollutants from sampling bags and instruments, 86 VOCs have been identified in the exhaled breath. The orthogonal partial least squares-discriminant analysis (OPLS-DA) was employed for the screening of potential biomarkers of silicosis. Those components that related to smoking were also excluded from the biomarkers. Finally, nine possible biomarkers for silicosis were screened out, including 2,3-butanedione, ethyl acetate, chlorobenzene, o-cymene, 4-ethylhex-2-ynal, 3,5-dimethyl-3-heptanol, hydroquinone, phthalic anhydride and 5-(2-methylpropyl)nonane. Based on these biomarkers screened, a predicted model for silicosis was generated with the accuracy of 89.61%. CONCLUSION The nine biomarkers in exhaled breath were preliminarily screened out for the early diagnosis of silicosis, which can be helpful to the establishment of a noninvasive screening method for silicosis. Follow-up studies should be conducted to further verify these markers.
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Affiliation(s)
- Zonghui Yi
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Simin Dong
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Xixi Wang
- Chengdu Center for Disease Control and Prevention, Chengdu, 610066, China
| | - Mucen Xu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Yongxin Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China.
- Research Center for Nutrition, Metabolism and Food Safety, West China-PUMC C.C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China.
| | - Linshen Xie
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China.
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Hu J, Lyu Y, Chen H, Cai L, Li J, Cao X, Sun W. Integration of target, suspect, and nontarget screening with risk modeling for per- and polyfluoroalkyl substances prioritization in surface waters. WATER RESEARCH 2023; 233:119735. [PMID: 36801580 DOI: 10.1016/j.watres.2023.119735] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/09/2023] [Accepted: 02/11/2023] [Indexed: 06/18/2023]
Abstract
Though thousands of per- and polyfluoroalkyl substances (PFAS) have been on the global market, most research focused on only a small fraction, potentially resulting in underestimated environmental risks. Here, we used complementary target, suspect, and nontarget screening for quantifying and identifying the target and nontarget PFAS, respectively, and developed a risk model considering their specific properties to prioritize the PFAS in surface waters. Thirty-three PFAS were identified in surface water in the Chaobai river, Beijing. The suspect and nontarget screening by Orbitrap displayed a sensitivity of > 77%, indicating its good performance in identifying the PFAS in samples. We used triple quadrupole (QqQ) under multiple-reaction monitoring for quantifying PFAS with authentic standards due to its potentially high sensitivity. To quantify the nontarget PFAS without authentic standards, we trained a random forest regression model which presented the differences up to only 2.7 times between measured and predicted response factors (RFs). The maximum/minimum RF in each PFAS class was as high as 1.2-10.0 in Orbitrap and 1.7-22.3 in QqQ. A risk-based prioritization approach was developed to rank the identified PFAS, and four PFAS (i.e., perfluorooctanoic acid, hydrogenated perfluorohexanoic acid, bistriflimide, 6:2 fluorotelomer carboxylic acid) were flagged with high priority (risk index > 0.1) for remediation and management. Our study highlighted the importance of a quantification strategy during environmental scrutiny of PFAS, especially for nontarget PFAS without standards.
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Affiliation(s)
- Jingrun Hu
- State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; The Key Laboratory of Water and Sediment Sciences, Ministry of Education, Beijing 100871, China
| | - Yitao Lyu
- State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; The Key Laboratory of Water and Sediment Sciences, Ministry of Education, Beijing 100871, China
| | - Huan Chen
- Department of Environmental Engineering and Earth Sciences, Clemson University, SC 29634, USA.
| | - Leilei Cai
- College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, China
| | - Jie Li
- State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; The Key Laboratory of Water and Sediment Sciences, Ministry of Education, Beijing 100871, China
| | - Xiaoqiang Cao
- College of Safety and Environmental Engineering, Shandong University of Science and Technology, Qingdao, Shandong 266590, China
| | - Weiling Sun
- State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; The Key Laboratory of Water and Sediment Sciences, Ministry of Education, Beijing 100871, China.
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Wang Z, Chen S, Pang Y, Ye L, Zhang Q, Jiang X, Zhang R, Li M, Guo Z, Jiang Y, Li D, Xing X, Chen L, Aschner M, Chen W. Morphological alterations in C57BL/6 mouse intestinal organoids as a tool for predicting chemical-induced toxicity. Arch Toxicol 2023; 97:1133-1146. [PMID: 36806895 PMCID: PMC10045874 DOI: 10.1007/s00204-023-03451-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 01/24/2023] [Indexed: 02/23/2023]
Abstract
Intestinal organoid may serve as an alternative model for toxicity testing. However, the linkage between specific morphological alterations in organoids and chemical-induced toxicity has yet to be defined. Here, we generated C57BL/6 mouse intestinal organoids and conducted a morphology-based analysis on chemical-induced toxicity. Alterations in morphology were characterized by large spheroids, hyperplastic organoids, small spheroids, and protrusion-loss organoids, which responded in a concentration-dependent manner to the treatment of four metal(loid)s including cadmium (Cd), lead (Pb), hexavalent chromium (Cr-VI), and inorganic trivalent arsenic (iAs-III). Notably, alterations in organoid morphology characterized by abnormal morphology rate were correlated with specific intestinal toxic effects, including reduction in cell viability and differentiation, induction of apoptosis, dysfunction of mucus production, and damage to epithelial barrier upon repeated administration. The benchmark dose (BMDL10) values of morphological alterations (0.007-0.195 μM) were lower than those of conventional bioassays (0.010-0.907 μM). We also established that the morphologic features of organoids upon Cd, Pb, Cr-VI, or iAs-III treatment were metal specific, and mediated by Wnt, bone morphogenetic protein, apoptosis induction, and Notch signaling pathways, respectively. Collectively, these findings provide novel insights into the relevance of morphological alterations in organoids to specific toxic endpoints and identify specific morphological alterations as potential indicators of enterotoxicity.
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Affiliation(s)
- Ziwei Wang
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Shen Chen
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Yaqin Pang
- Faculty of Toxicology, School of Public Health, Youjiang Medical College for Nationalities, Guangxi, China
| | - Lizhu Ye
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Qi Zhang
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Xinhang Jiang
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Rui Zhang
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Miao Li
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Zhanyu Guo
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Yue Jiang
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Daochuan Li
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Xiumei Xing
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Liping Chen
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China
| | - Michael Aschner
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY, USA.
| | - Wen Chen
- Department of Toxicology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, China.
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Liu Z, Liu H, Chen Z, Deng C, Zhou L, Chen S, Kang J, Chen Y, He S, Zhou Z. Identification of a novel plasma metabolite panel as diagnostic biomarker for hepatocellular carcinoma. Clin Chim Acta 2023; 543:117302. [PMID: 36940842 DOI: 10.1016/j.cca.2023.117302] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 03/14/2023] [Accepted: 03/16/2023] [Indexed: 03/22/2023]
Abstract
BACKGROUND AND AIMS Metabolic reprogramming is one of the hallmarks of cancer. Hepatocellular carcinoma (HCC) is one of the most lethal malignancy camcer, but the early diagnosis of HCC remains difficult. In this study, we searched for potential plasma metabolite biomarkers of HCC. METHODS A total of plasma samples of 104 HCC, 76 cirrhosis and 10 healthy subjects were assessed and validated through Gas chromatography-Mass spectrometry. Receiver-operating characteristic curves (ROC) combined with multivariate statistical analyses were used to assess the diagnostic performance of metabolites and combinations. RESULTS 10 metabolites in screening cohort were significantly changed in the plasma of HCC patients. Multivariate logistic regression analysis of candidate metabolites in validation cohort showed that N-formylglycine, oxoglutaric acid, citrulline and heptaethylene glycol could distinguish HCC from cirrhosis. The combination of these four metabolites showed a better performance than AFP with the Area Under the Curve (AUC), sensitivity, specificity as 0.940, 84.00%, 97.56%, respectively. In further, the panel of N-formylglycine, heptaethylene glycol and citrulline can more effectively discriminate early stage HCC from cirrhosis than AFP (AUC: 0.835 vs. 0.634). Finally, heptaethylene glycol could significantly inhibit the proliferation, migration and invasion of HCC cells in vitro. CONCLUSION The combination of plasma N-formylglycine, oxoglutaric acid, citrulline, and heptaethylene glycol can be an efficient novel diagnostic biomarker for HCC.
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Affiliation(s)
- Zhiying Liu
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Hongtao Liu
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Zhiji Chen
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Chao Deng
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Li Zhou
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Siyuan Chen
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Juan Kang
- Department of Infectious Disease, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Yao Chen
- Physical examination center, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Song He
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China.
| | - Zhihang Zhou
- Department of Gastroenterology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China.
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Yang J, Niu H, Pang S, Liu M, Chen F, Li Z, He L, Mo J, Yi H, Xiao J, Huang Y. MARK3 kinase: Regulation and physiologic roles. Cell Signal 2023; 103:110578. [PMID: 36581219 DOI: 10.1016/j.cellsig.2022.110578] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 12/14/2022] [Accepted: 12/20/2022] [Indexed: 12/27/2022]
Abstract
Microtubule affinity-regulating kinase 3 (MARK3), a member of the MARK family, regulates several essential pathways, including the cell cycle, ciliated cell differentiation, and osteoclast differentiation. It is important to understand the control of their activities as MARK3 contains an N-terminal serine/threonine kinase domain, ubiquitin-associated domain, and C-terminal kinase-associated domain, which perform multiple regulatory functions. These functions include post-translational modification (e.g., phosphorylation) and interaction with scaffolding and other proteins. Differences in the amino acid sequence and domain position result in different three-dimensional protein structures and affect the function of MARK3, which distinguish it from the other MARK family members. Recent data indicate a potential role of MARK3 in several pathological conditions, including congenital blepharophimosis syndrome, osteoporosis, and tumorigenesis. The present review focuses on the physiological and pathological role of MARK3, its regulation, and recent developments in the small molecule inhibitors of the MARK3 signalling cascade.
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Affiliation(s)
- Jingyu Yang
- Surgery of Mammary Gland and Thyroid Gland, the First People's Hospital of Yunnan Province, Panlong Campus, 157 Jinbi Road, Kunming 650032, Yunnan, People's Republic of China
| | - Heng Niu
- Surgery of Mammary Gland and Thyroid Gland, the First People's Hospital of Yunnan Province, Panlong Campus, 157 Jinbi Road, Kunming 650032, Yunnan, People's Republic of China
| | - ShiGui Pang
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Mignlong Liu
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Feng Chen
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Zhaoxin Li
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Lifei He
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Jianmei Mo
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Huijun Yi
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Juanjuan Xiao
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China
| | - Yingze Huang
- Cancer Research Institute, The Affiliated Hospital of Guilin Medical University, Xiufeng Campus, 15 Lequn Road, Guilin 541001, Guangxi, People's Republic of China.
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Romijn M, van Kaam AH, Fenn D, Bos LD, van den Akker CHP, Finken MJJ, Rotteveel J, Cerullo J, Brinkman P, Onland W. Exhaled Volatile Organic Compounds for Early Prediction of Bronchopulmonary Dysplasia in Infants Born Preterm. J Pediatr 2023:113368. [PMID: 36868304 DOI: 10.1016/j.jpeds.2023.02.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 02/10/2023] [Accepted: 02/12/2023] [Indexed: 03/05/2023]
Abstract
OBJECTIVE(S) To investigate the predictive performances of exhaled breath volatile organic compounds (VOCs) for development of bronchopulmonary dysplasia (BPD) in infants born preterm. METHODS Exhaled breath was collected from infants born <30 weeks' gestation at days 3 and 7 of life. Ion-fragments detected by gas-Chromatography-mass-spectrometry analysis were used to derive and internally validate a VOC prediction model for moderate or severe BPD at 36 weeks postmenstrual age. We tested the predictive performance of the National Institute of Child Health and Human Development (NICHD) clinical BPD prediction model with and without VOCs. RESULTS Breath samples were collected from 117 infants (mean gestation 26.8 [±1.5] weeks). Thirty-three percent of the infants developed moderate or severe BPD. The VOC model showed a c-statistic of 0.89 (95% confidence interval [CI] 0.80-0.97) and 0.92 (95% CI 0.84-0.99)) for the prediction of BPD at days 3 and 7, respectively. Adding the VOCs to the clinical prediction model in non-invasive supported infants resulted in significant improvement in discriminative power on both days (day 3: c-statistic 0.83 versus 0.92, p-value 0.04; day 7: c-statistic 0.82 versus 0.94, p-value 0.03). CONCLUSIONS This study showed that VOC profiles in exhaled breath of preterm infants on non-invasive support in the first week of life differ between those developing and not developing BPD. Adding VOCs to a clinical prediction model significantly improved its discriminative performance.
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Affiliation(s)
- Michelle Romijn
- Amsterdam UMC location University of Amsterdam, Department of Pediatrics-Neonatology, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Reproduction and Development Research Institute, Amsterdam, the Netherlands; Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Pediatric-Endocrinology, Boelelaan 1117, Amsterdam, the Netherlands
| | - Anton H van Kaam
- Amsterdam UMC location University of Amsterdam, Department of Pediatrics-Neonatology, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Reproduction and Development Research Institute, Amsterdam, the Netherlands
| | - Dominic Fenn
- Amsterdam UMC location University of Amsterdam, Department of Respiratory Medicine, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam UMC location University of Amsterdam, Department of laboratory of Experimental Intensive Care and Anaesthesiology, Meibergdreef 9, Amsterdam, the Netherlands
| | - Lieuwe D Bos
- Amsterdam UMC location University of Amsterdam, Department of Respiratory Medicine, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam UMC location University of Amsterdam, Department of laboratory of Experimental Intensive Care and Anaesthesiology, Meibergdreef 9, Amsterdam, the Netherlands
| | - Chris H P van den Akker
- Amsterdam UMC location University of Amsterdam, Department of Pediatrics-Neonatology, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Reproduction and Development Research Institute, Amsterdam, the Netherlands
| | - Martijn J J Finken
- Amsterdam Reproduction and Development Research Institute, Amsterdam, the Netherlands; Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Pediatric-Endocrinology, Boelelaan 1117, Amsterdam, the Netherlands
| | - Joost Rotteveel
- Amsterdam Reproduction and Development Research Institute, Amsterdam, the Netherlands; Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Pediatric-Endocrinology, Boelelaan 1117, Amsterdam, the Netherlands
| | - Julia Cerullo
- Division of Neonatolgy "Villa dei Fiori" Hospital, Acerra, Naples, Italy
| | - Paul Brinkman
- Amsterdam UMC location University of Amsterdam, Department of Respiratory Medicine, Meibergdreef 9, Amsterdam, the Netherlands
| | - Wes Onland
- Amsterdam UMC location University of Amsterdam, Department of Pediatrics-Neonatology, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Reproduction and Development Research Institute, Amsterdam, the Netherlands.
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He C, Kalafut NC, Sandoval SO, Risgaard R, Sirois CL, Yang C, Khullar S, Suzuki M, Huang X, Chang Q, Zhao X, Sousa AM, Wang D. BOMA, a machine-learning framework for comparative gene expression analysis across brains and organoids. CELL REPORTS METHODS 2023; 3:100409. [PMID: 36936070 PMCID: PMC10014309 DOI: 10.1016/j.crmeth.2023.100409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 11/21/2022] [Accepted: 01/25/2023] [Indexed: 02/17/2023]
Abstract
Our machine-learning framework, brain and organoid manifold alignment (BOMA), first performs a global alignment of developmental gene expression data between brains and organoids. It then applies manifold learning to locally refine the alignment, revealing conserved and specific developmental trajectories across brains and organoids. Using BOMA, we found that human cortical organoids better align with certain brain cortical regions than with other non-cortical regions, implying organoid-preserved developmental gene expression programs specific to brain regions. Additionally, our alignment of non-human primate and human brains reveals highly conserved gene expression around birth. Also, we integrated and analyzed developmental single-cell RNA sequencing (scRNA-seq) data of human brains and organoids, showing conserved and specific cell trajectories and clusters. Further identification of expressed genes of such clusters and enrichment analyses reveal brain- or organoid-specific developmental functions and pathways. Finally, we experimentally validated important specific expressed genes through the use of immunofluorescence. BOMA is open-source available as a web tool for community use.
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Affiliation(s)
- Chenfeng He
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Noah Cohen Kalafut
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Soraya O. Sandoval
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Ryan Risgaard
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Carissa L. Sirois
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Chen Yang
- Department of Mathematics, University of Wisconsin-Madison, Madison, WI, USA
| | - Saniya Khullar
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Marin Suzuki
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Xiang Huang
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Qiang Chang
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Departments of Medical Genetics and Neurology, University of Wisconsin-Madison, Madison, WI, USA
| | - Xinyu Zhao
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Andre M.M. Sousa
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neuroscience, University of Wisconsin-Madison, Madison, WI, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, USA
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Su YH, Chang CW, Hsu JY, Li SW, Sung PS, Wang RH, Wu CH, Liao PC. Discovering Hair Biomarkers of Alzheimer's Disease Using High Resolution Mass Spectrometry-Based Untargeted Metabolomics. Molecules 2023; 28:molecules28052166. [PMID: 36903413 PMCID: PMC10004788 DOI: 10.3390/molecules28052166] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/20/2023] [Accepted: 02/23/2023] [Indexed: 03/02/2023] Open
Abstract
Hair may be a potential biospecimen to discover biomarkers for Alzheimer's disease (AD) since it reflects the integral metabolic profiles of body burden over several months. Here, we described the AD biomarker discovery in the hair using a high-resolution mass spectrometry (HRMS)-based untargeted metabolomics approach. A total of 24 patients with AD and 24 age- and sex-matched cognitively healthy controls were recruited. The hair samples were collected 0.1-cm away from the scalp and further cut into 3-cm segments. Hair metabolites were extracted by ultrasonication with methanol/phosphate-buffered saline 50/50 (v/v) for 4 h. A total of 25 discriminatory chemicals in hair between the patients with AD and controls were discovered and identified. The AUC value achieved 0.85 (95% CI: 0.72~0.97) in patients with very mild AD compared to healthy controls using a composite panel of the 9 biomarker candidates, indicating high potential for the initiation or promotion phase of AD dementia in the early stage. A metabolic panel combined with the nine metabolites may be used as biomarkers for the early detection of AD. The hair metabolome can be used to reveal metabolic perturbations for biomarker discovery. Investigating perturbations of the metabolites will offer insight into the pathogenesis of AD.
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Affiliation(s)
- Yu-Hsiang Su
- Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City 60002, Taiwan
| | - Chih-Wei Chang
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Jen-Yi Hsu
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Shih-Wen Li
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Pi-Shan Sung
- Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Ru-Hsueh Wang
- Department of Family Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
| | - Chih-Hsing Wu
- Department of Family Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
- Institute of Gerontology, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
| | - Pao-Chi Liao
- Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan
- Department of Food Safety/Hygiene and Risk Management, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan
- Correspondence:
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Wei J, Dai W, Pan X, Zhong Y, Xu N, Ye P, Wang J, Li J, Yang F, Luo J, Luo M. Identifying the Novel Gut Microbial Metabolite Contributing to Metabolic Syndrome in Children Based on Integrative Analyses of Microbiome-Metabolome Signatures. Microbiol Spectr 2023; 11:e0377122. [PMID: 36794949 PMCID: PMC10101147 DOI: 10.1128/spectrum.03771-22] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 01/30/2023] [Indexed: 02/17/2023] Open
Abstract
The pathogenesis of gut microbiota and their metabolites in the development of metabolic syndrome (MS) remains unclear. This study aimed to evaluate the signatures of gut microbiota and metabolites as well as their functions in obese children with MS. A case-control study was conducted based on 23 MS children and 31 obese controls. The gut microbiome and metabolome were measured using 16S rRNA gene amplicon sequencing and liquid chromatography-mass spectrometry. An integrative analysis was conducted, combining the results of the gut microbiome and metabolome with extensive clinical indicators. The biological functions of the candidate microbial metabolites were validated in vitro. We identified 9 microbiota and 26 metabolites that were significantly different from the MS and the control group. The clinical indicators of MS were correlated with the altered microbiota Lachnoclostridium, Dialister, and Bacteroides, as well as with the altered metabolites all-trans-13,14-dihydroretinol, DL-dipalmitoylphosphatidylcholine (DPPC), LPC 24: 1, PC (14:1e/10:0), and 4-phenyl-3-buten-2-one, etc. The association network analysis further identified three MS-linked metabolites, including all-trans-13,14-dihydroretinol, DPPC, and 4-phenyl-3-buten-2-one, that were significantly correlated with the altered microbiota. Bio-functional validation showed that all-trans-13, 14-dihydroretinol could significantly upregulate the expression of lipid synthesis genes and inflammatory genes. This study identified a new biomarker that may contribute to MS development. These findings provided new insights regarding the development of efficient therapeutic strategies for MS. IMPORTANCE Metabolic syndrome (MS) has become a health concern worldwide. Gut microbiota and metabolites play an important role in human health. We first endeavored to comprehensively analyze the microbiome and metabolome signatures in obese children and found the novel microbial metabolites in MS. We further validated the biological functions of the metabolites in vitro and illustrated the effects of the microbial metabolites on lipid synthesis and inflammation. The microbial metabolite all-trans-13, 14-dihydroretinol may be a new biomarker in the pathogenesis of MS, especially in obese children. These findings were not available in previous studies, and they provide new insights regarding the management of metabolic syndrome.
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Affiliation(s)
- Jia Wei
- Xiangya School of Public Health, Central South University, Changsha, Hunan, China
- Hunan Provincial Key Laboratory of Clinical Epidemiology, Central South University, Changsha, Hunan, China
| | - Wen Dai
- Xiangya School of Public Health, Central South University, Changsha, Hunan, China
- Hunan Provincial Key Laboratory of Clinical Epidemiology, Central South University, Changsha, Hunan, China
| | - Xiongfeng Pan
- Xiangya School of Public Health, Central South University, Changsha, Hunan, China
- Hunan Provincial Key Laboratory of Clinical Epidemiology, Central South University, Changsha, Hunan, China
| | - Yan Zhong
- Institute of Children Health, Hunan Children’s Hospital, Changsha, Hunan, China
| | - Ningan Xu
- Institute of Children Health, Hunan Children’s Hospital, Changsha, Hunan, China
| | - Ping Ye
- Xiangya School of Public Health, Central South University, Changsha, Hunan, China
- Hunan Provincial Key Laboratory of Clinical Epidemiology, Central South University, Changsha, Hunan, China
| | - Jie Wang
- Xiangya School of Public Health, Central South University, Changsha, Hunan, China
- Hunan Provincial Key Laboratory of Clinical Epidemiology, Central South University, Changsha, Hunan, China
| | - Jina Li
- Xiangya School of Public Health, Central South University, Changsha, Hunan, China
- Hunan Provincial Key Laboratory of Clinical Epidemiology, Central South University, Changsha, Hunan, China
| | - Fei Yang
- Xiangya School of Public Health, Central South University, Changsha, Hunan, China
- Hunan Provincial Key Laboratory of Clinical Epidemiology, Central South University, Changsha, Hunan, China
- Hunan Province Key Laboratory of Typical Environmental Pollution and Health Hazards, School of Public Health, University of South China, Hengyang, Hunan, China
| | - Jiayou Luo
- Xiangya School of Public Health, Central South University, Changsha, Hunan, China
- Hunan Provincial Key Laboratory of Clinical Epidemiology, Central South University, Changsha, Hunan, China
| | - Miyang Luo
- Xiangya School of Public Health, Central South University, Changsha, Hunan, China
- Hunan Provincial Key Laboratory of Clinical Epidemiology, Central South University, Changsha, Hunan, China
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Supianto AA, Nurdiansyah R, Weng CW, Zilvan V, Yuwana RS, Arisal A, Pardede HF, Lee MM, Huang CH, Ng KL. Cluster-based text mining for extracting drug candidates for the prevention of COVID-19 from the biomedical literature. J Taibah Univ Med Sci 2023; 18:787-801. [PMID: 36618881 PMCID: PMC9810500 DOI: 10.1016/j.jtumed.2022.12.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 10/14/2022] [Accepted: 12/12/2022] [Indexed: 01/05/2023] Open
Abstract
Objective The coronavirus disease 2019 (COVID-19) health crisis that began at the end of 2019 made researchers around the world quickly race to find effective solutions. Related literature exploded and it was inevitable that an automated approach was needed to find useful information, namely text mining, to overcome COVID-19, especially in terms of drug candidate discovery. While text mining methods for finding drug candidates mostly try to extract bioentity associations from PubMed, very few of them mine with a clustering approach. The purpose of this study was to demonstrate the effectiveness of our approach to identify drugs for the prevention of COVID-19 through literature review, cluster analysis, drug docking calculations, and clinical trial data. Methods This research was conducted in four main stages. First, the text mining stage was carried out by involving Bidirectional Encoder Representations from Transformers for Biomedical to obtain vector representation of each word in the sentence from texts. The next stage generated the disease-drug associations, which were obtained from the correlation between disease and drug. Next, the clustering stage grouped the rules through the similarity of diseases by utilizing Term Frequency-Inverse Document Frequency as its feature. Finally, the drug candidate extraction stage was processed through leveraging PubChem and DrugBank databases. We further used the drug docking package AUTODOCK VINA in PyRx software to verify the results. Results Comparative analyses showed that the percentage of findings using mining with clustering outperformed mining without clustering in all experimental settings. In addition, we suggest that the top three drugs/phytochemicals by drug docking analysis may be effective in preventing COVID-19. Conclusions The proposed method for text mining utilizing the clustering method is quite promising in the discovery of drug candidates for the prevention of COVID-19 through the biomedical literature.
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Affiliation(s)
- Ahmad Afif Supianto
- Research Center for Data and Information Sciences, National Research and Innovation Agency, Indonesia
| | - Rizky Nurdiansyah
- Department of Bioinformatics, Indonesia International Institute for Life Sciences, Indonesia
| | - Chia-Wei Weng
- Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan
| | - Vicky Zilvan
- Research Center for Data and Information Sciences, National Research and Innovation Agency, Indonesia
| | - Raden Sandra Yuwana
- Research Center for Data and Information Sciences, National Research and Innovation Agency, Indonesia
| | - Andria Arisal
- Research Center for Data and Information Sciences, National Research and Innovation Agency, Indonesia
| | | | - Min-Min Lee
- Department of Food Nutrition and Health Biotechnology, Asia University, Taiwan
| | - Chien-Hung Huang
- Department of Computer Science and Information Engineering, National Formosa University, Taiwan
| | - Ka-Lok Ng
- Department of Bioinformatics and Medical Engineering, Asia University, Taiwan,Department of Medical Research, China Medical University Hospital, China Medical University, Taiwan,Center for Artificial Intelligence and Precision Medicine Research, Asia University, Taiwan,Corresponding address: Department of Bioinformatics and Medical Engineering, No. 500, LiuFeng Rd., WuFeng Dist., Taichung City, 41354, Taiwan.
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49
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Hazare SR, Vala SV, Patil CS, Joshi AJ, Joshi JB, Vitankar VS, Patwardhan AW. Correlating Interfacial Area and Volumetric Mass Transfer Coefficient in Bubble Column with the Help of Machine Learning Methods. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c02820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
- Sumit R. Hazare
- Department of Chemical Engineering, Institute of Chemical Technology, Mumbai400019, India
| | - Shivam V. Vala
- Reliable Process Design Solutions Pvt. Ltd., 411057, Hinjewadi, Pune, India
| | - Chinmay S. Patil
- Department of Chemical Engineering, Institute of Chemical Technology, Mumbai400019, India
| | - Aniruddha J. Joshi
- Reliable Process Design Solutions Pvt. Ltd., 411057, Hinjewadi, Pune, India
| | - Jyeshtharaj B. Joshi
- Department of Chemical Engineering, Institute of Chemical Technology, Mumbai400019, India
- Homi Bhabha National Institute, Anushaktinagar, Mumbai400085, India
| | | | - Ashwin W. Patwardhan
- Department of Chemical Engineering, Institute of Chemical Technology, Mumbai400019, India
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Gątarek P, Sekulska-Nalewajko J, Bobrowska-Korczaka B, Pawełczyk M, Jastrzębski K, Głąbiński A, Kałużna-Czaplińska J. Plasma Metabolic Disturbances in Parkinson's Disease Patients. Biomedicines 2022; 10:biomedicines10123005. [PMID: 36551761 PMCID: PMC9775245 DOI: 10.3390/biomedicines10123005] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 11/15/2022] [Accepted: 11/18/2022] [Indexed: 11/24/2022] Open
Abstract
Plasma from patients with Parkinson's disease (PD) is a valuable source of information indicating altered metabolites associated with the risk or progression of the disease. Neurotoxicity of dopaminergic neurons, which is triggered by aggregation of α-synuclein, is the main pathogenic feature of PD. However, a growing body of scientific reports indicates that metabolic changes may precede and directly contribute to neurodegeneration. Identification and characterization of the abnormal metabolic pattern in patients' plasma are therefore crucial for the search for potential PD biomarkers. The aims of the present study were (1) to identify metabolic alterations in plasma metabolome in subjects with PD as compared with the controls; (2) to find new potential markers, some correlations among them; (3) to identify metabolic pathways relevant to the pathophysiology of PD. Plasma samples from patients with PD (n = 25) and control group (n = 12) were collected and the gas chromatography-time-of-flight-mass spectrometry GC-TOFMS-based metabolomics approach was used to evaluate the metabolic changes based on the identified 14 metabolites with significantly altered levels using univariate and multivariate statistical analysis. The panel, including 6 metabolites (L-3-methoxytyrosine, aconitic acid, L-methionine, 13-docosenamide, hippuric acid, 9,12-octadecadienoic acid), was identified to discriminate PD from controls with the area under the curve (AUC) of 0.975, with an accuracy of 92%. We also used statistical criteria to identify the significantly altered level of metabolites. The metabolic pathways involved were associated with linoleic acid metabolism, mitochondrial electron transport chain, glycerolipid metabolism, and bile acid biosynthesis. These abnormal metabolic changes in the plasma of patients with PD were mainly related to the amino acid metabolism, TCA cycle metabolism, and mitochondrial function.
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Affiliation(s)
- Paulina Gątarek
- Institute of General and Ecological Chemistry, Faculty of Chemistry, Lodz University of Technology, 90-924 Lodz, Poland
- CONEM Poland Chemistry and Nutrition Research Group, Lodz University of Technology, 90-924 Lodz, Poland
- Correspondence: (P.G.); (J.K.-C.); Tel.: +48-426-313-091 (J.K.-C.); Fax: +48-426-313-128 (J.K.-C.)
| | | | | | - Małgorzata Pawełczyk
- Department of Neurology and Stroke, Medical University of Lodz, 90-549 Lodz, Poland
| | - Karol Jastrzębski
- Department of Neurology and Stroke, Medical University of Lodz, 90-549 Lodz, Poland
| | - Andrzej Głąbiński
- Department of Neurology and Stroke, Medical University of Lodz, 90-549 Lodz, Poland
| | - Joanna Kałużna-Czaplińska
- Institute of General and Ecological Chemistry, Faculty of Chemistry, Lodz University of Technology, 90-924 Lodz, Poland
- CONEM Poland Chemistry and Nutrition Research Group, Lodz University of Technology, 90-924 Lodz, Poland
- Correspondence: (P.G.); (J.K.-C.); Tel.: +48-426-313-091 (J.K.-C.); Fax: +48-426-313-128 (J.K.-C.)
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