Metabolomics to Unveil and Understand Phenotypic Diversity between Pathogen Populations
Publication Date
November 30, 2010
Journal
PLOS Neglected Tropical Diseases
Authors
Ruben T'kindt, Richard A. Scheltema, Andris Jankevics, Kirstyn Brunker, et al
Volume
4
Issue
11
Pages
e904
DOI
https://dx.plos.org/10.1371/journal.pntd.0000904
Publisher URL
http://journals.plos.org/plosntds/article?id=10.1371%2Fjournal.pntd.0000904
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/21152055
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2994915
Europe PMC
http://europepmc.org/abstract/MED/21152055
Web of Science
000284765900045
Scopus
78649776458
Mendeley
http://www.mendeley.com/research/metabolomics-unveil-understand-phenotypic-diversity-between-pathogen-populations
Events
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Mendeley | Further Information

{"title"=>"Metabolomics to unveil and understand phenotypic diversity between pathogen populations", "type"=>"journal", "authors"=>[{"first_name"=>"Ruben", "last_name"=>"T'Kindt", "scopus_author_id"=>"21234540100"}, {"first_name"=>"Richard A.", "last_name"=>"Scheltema", "scopus_author_id"=>"24463071800"}, {"first_name"=>"Andris", "last_name"=>"Jankevics", "scopus_author_id"=>"24492073500"}, {"first_name"=>"Kirstyn", "last_name"=>"Brunker", "scopus_author_id"=>"36660483700"}, {"first_name"=>"Suman", "last_name"=>"Rijal", "scopus_author_id"=>"6602721336"}, {"first_name"=>"Jean Claude", "last_name"=>"Dujardin", "scopus_author_id"=>"7102125027"}, {"first_name"=>"Rainer", "last_name"=>"Breitling", "scopus_author_id"=>"15757011000"}, {"first_name"=>"David G.", "last_name"=>"Watson", "scopus_author_id"=>"55690150600"}, {"first_name"=>"Graham H.", "last_name"=>"Coombs", "scopus_author_id"=>"7004795922"}, {"first_name"=>"Saskia", "last_name"=>"Decuypere", "scopus_author_id"=>"6507585591"}], "year"=>2010, "source"=>"PLoS Neglected Tropical Diseases", "identifiers"=>{"sgr"=>"78649776458", "scopus"=>"2-s2.0-78649776458", "doi"=>"10.1371/journal.pntd.0000904", "pui"=>"360094645", "issn"=>"1935-2735", "isbn"=>"1935-2735 (Electronic)\\n1935-2727 (Linking)", "pmid"=>"21152055"}, "id"=>"e9342006-21a9-330d-aa18-4d4d8fde93f9", "abstract"=>"Leishmaniasis is a debilitating disease caused by the parasite Leishmania. There is extensive clinical polymorphism, including variable responsiveness to treatment. We study Leishmania donovani parasites isolated from visceral leishmaniasis patients in Nepal that responded differently to antimonial treatment due to differing intrinsic drug sensitivity of the parasites. Here, we present a proof-of-principle study in which we applied a metabolomics pipeline specifically developed for L. donovani to characterize the global metabolic differences between antimonial-sensitive and antimonial-resistant L. donovani isolates. Clones of drug-sensitive and drug-resistant parasite isolates from clinical samples were cultured in vitro and harvested for metabolomics analysis. The relative abundance of 340 metabolites was determined by ZIC-HILIC chromatography coupled to LTQ-Orbitrap mass spectrometry. Our measurements cover approximately 20% of the predicted core metabolome of Leishmania and additionally detected a large number of lipids. Drug-sensitive and drug-resistant parasites showed distinct metabolic profiles, and unsupervised clustering and principal component analysis clearly distinguished the two phenotypes. For 100 metabolites, the detected intensity differed more than three-fold between the 2 phenotypes. Many of these were in specific areas of lipid metabolism, suggesting that the membrane composition of the drug-resistant parasites is extensively modified. Untargeted metabolomics has been applied on clinical Leishmania isolates to uncover major metabolic differences between drug-sensitive and drug-resistant isolates. The identified major differences provide novel insights into the mechanisms involved in resistance to antimonial drugs, and facilitate investigations using targeted approaches to unravel the key changes mediating drug resistance.", "link"=>"http://www.mendeley.com/research/metabolomics-unveil-understand-phenotypic-diversity-between-pathogen-populations", "reader_count"=>108, "reader_count_by_academic_status"=>{"Unspecified"=>4, "Professor > Associate Professor"=>2, "Student > Doctoral Student"=>9, "Researcher"=>31, "Student > Ph. D. Student"=>27, "Student > Postgraduate"=>3, "Student > Master"=>18, "Student > Bachelor"=>8, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2, "Professor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>4, "Professor > Associate Professor"=>2, "Student > Doctoral Student"=>9, "Researcher"=>31, "Student > Ph. D. Student"=>27, "Student > Postgraduate"=>3, "Student > Master"=>18, "Student > Bachelor"=>8, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>2, "Professor"=>3}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>6, "Biochemistry, Genetics and Molecular Biology"=>13, "Agricultural and Biological Sciences"=>62, "Medicine and Dentistry"=>5, "Pharmacology, Toxicology and Pharmaceutical Science"=>2, "Veterinary Science and Veterinary Medicine"=>3, "Physics and Astronomy"=>1, "Chemistry"=>13, "Computer Science"=>1, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>5}, "Chemistry"=>{"Chemistry"=>13}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>62}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>13}, "Unspecified"=>{"Unspecified"=>6}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>2}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>3}}, "reader_count_by_country"=>{"Canada"=>1, "Netherlands"=>1, "Belgium"=>1, "United States"=>1, "Brazil"=>5, "United Kingdom"=>2, "South Africa"=>1, "Mexico"=>1, "Portugal"=>1, "Montenegro"=>1}, "group_count"=>5}

CrossRef

Scopus | Further Information

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  • {"month"=>"11", "year"=>"2020", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"15"}
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  • {"month"=>"1", "year"=>"2021", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"11"}

Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/406579"], "description"=>"<div><p>Leishmaniasis is a debilitating disease caused by the parasite <em>Leishmania</em>. There is extensive clinical polymorphism, including variable responsiveness to treatment. We study <em>Leishmania donovani</em> parasites isolated from visceral leishmaniasis patients in Nepal that responded differently to antimonial treatment due to differing intrinsic drug sensitivity of the parasites. Here, we present a proof-of-principle study in which we applied a metabolomics pipeline specifically developed for <em>L. donovani</em> to characterize the global metabolic differences between antimonial-sensitive and antimonial-resistant <em>L. donovani</em> isolates. Clones of drug-sensitive and drug-resistant parasite isolates from clinical samples were cultured <em>in vitro</em> and harvested for metabolomics analysis. The relative abundance of 340 metabolites was determined by ZIC-HILIC chromatography coupled to LTQ-Orbitrap mass spectrometry. Our measurements cover approximately 20% of the predicted core metabolome of <em>Leishmania</em> and additionally detected a large number of lipids. Drug-sensitive and drug-resistant parasites showed distinct metabolic profiles, and unsupervised clustering and principal component analysis clearly distinguished the two phenotypes. For 100 metabolites, the detected intensity differed more than three-fold between the 2 phenotypes. Many of these were in specific areas of lipid metabolism, suggesting that the membrane composition of the drug-resistant parasites is extensively modified. Untargeted metabolomics has been applied on clinical <em>Leishmania</em> isolates to uncover major metabolic differences between drug-sensitive and drug-resistant isolates. The identified major differences provide novel insights into the mechanisms involved in resistance to antimonial drugs, and facilitate investigations using targeted approaches to unravel the key changes mediating drug resistance.</p> </div>", "links"=>[], "tags"=>["metabolomics", "unveil", "phenotypic", "pathogen", "populations"], "article_id"=>140320, "categories"=>["Cell Biology", "Microbiology", "Physics", "Medicine", "Cancer"], "users"=>["Ruben t'Kindt", "Richard A. Scheltema", "Andris Jankevics", "Kirstyn Brunker", "Suman Rijal", "Jean-Claude Dujardin", "Rainer Breitling", "David G. Watson", "Graham H. Coombs", "Saskia Decuypere"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0000904", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Metabolomics_to_Unveil_and_Understand_Phenotypic_Diversity_between_Pathogen_Populations/140320", "title"=>"Metabolomics to Unveil and Understand Phenotypic Diversity between Pathogen Populations", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-11-30 00:05:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/815248"], "description"=>"<p>Compounds fulfilling the 3 criteria that we used to define metabolites with a significantly different profile in the 2 phenotypes are mapped in red (higher in drug-resistant) and blue (higher in drug-sensitive); compounds that had similar profiles in the 2 phenotypes are mapped in black; compounds that could not be detected are mapped in white. For groups of closely related metabolites, the average difference in abundance was plotted, with the number of metabolites showing the respective abundance pattern noted between brackets; for glycerophospholipids only lipids with 2 acyl/alkyl side chains were included. (The map was derived from the KEGG <i>L. major</i> map <a href=\"http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0000904#pntd.0000904-Ogata1\" target=\"_blank\">[27]</a> and the LeishCyc database <a href=\"http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0000904#pntd.0000904-Doyle1\" target=\"_blank\">[24]</a>.)</p>", "links"=>[], "tags"=>["163", "340", "compounds", "metabolic"], "article_id"=>485604, "categories"=>["Cell Biology", "Microbiology", "Physics", "Medicine", "Virology"], "users"=>["Ruben t'Kindt", "Richard A. Scheltema", "Andris Jankevics", "Kirstyn Brunker", "Suman Rijal", "Jean-Claude Dujardin", "Rainer Breitling", "David G. Watson", "Graham H. Coombs", "Saskia Decuypere"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0000904.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_map_of_163_of_the_340_identified_compounds_onto_the_L_donovani_metabolic_network_/485604", "title"=>"Schematic map of 163 of the 340 identified compounds onto the <i>L. donovani</i> metabolic network.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-11-30 01:33:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/815443"], "description"=>"<p>PCA is an unsupervised cluster method here based on the quantitative measurements of all 340 identified compounds. The first principal component accounts for the highest variability in the dataset, and each succeeding component accounts for as much of the remaining variability as possible. Each set of biological replicates is clustered closely together, indicating that parasite replicate cultures were reproducibly generated and extracted. Principal component 1 clearly separates the two phenotypes (round symbols are antimonial sensitive, square symbols are antimonial resistant) and explains 61.9% of the total variance, while principal component 2 separates the different clonal populations (clones 15, 17 and 18 for BPK275/0 and clones 4 and 9 for BPK282/0) and explains 8.8% of the total variance.</p>", "links"=>[], "tags"=>["distinguishes", "drug-sensitive", "drug-resistant"], "article_id"=>485801, "categories"=>["Cell Biology", "Microbiology", "Physics", "Medicine", "Virology"], "users"=>["Ruben t'Kindt", "Richard A. Scheltema", "Andris Jankevics", "Kirstyn Brunker", "Suman Rijal", "Jean-Claude Dujardin", "Rainer Breitling", "David G. Watson", "Graham H. Coombs", "Saskia Decuypere"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0000904.g003", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Principal_component_analysis_PCA_distinguishes_drug_sensitive_and_drug_resistant_clones_/485801", "title"=>"Principal component analysis (PCA) distinguishes drug-sensitive and drug-resistant clones.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-11-30 01:36:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/815348"], "description"=>"<p>The samples are presented along the x-axis. On the left, the 4 biological replicates are present adjacent to each other for clones 4 and 9 derived from the drug-sensitive clinical isolate BPK282/0. On the right, the 4 biological replicates are present adjacent to each other for clones 15, 17 and 18 derived from the drug-resistant clinical isolate BPK275/0. The 340 detected metabolites are presented along the y-axis; the major classes of metabolites are colour-coded on the left. The intensity of each metabolite detected in the sample set was rescaled between 0 (red) to 100 (green). Unsupervised hierarchical clustering of the samples (the tree above the x-axis) reveals that the metabolite intensity profiles differ sufficiently to clearly and robustly distinguish the separate clones of the drug-resistant and drug-sensitive isolates. Among the samples from the same isolate, the biological replicates from individual clones are also correctly clustered together. Clustering of the metabolites according to similarity in intensity profiles (the tree left of y-axis), reveals several large groups of metabolites that are either significantly higher or lower in the drug-resistant samples (quantitative data and identification/classification of all compounds included in this figure can be found in <a href=\"http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0000904#pntd.0000904.s001\" target=\"_blank\">Table S1</a>).</p>", "links"=>[], "tags"=>["profiles", "340", "compounds", "heatmap"], "article_id"=>485710, "categories"=>["Cell Biology", "Microbiology", "Physics", "Medicine", "Virology"], "users"=>["Ruben t'Kindt", "Richard A. Scheltema", "Andris Jankevics", "Kirstyn Brunker", "Suman Rijal", "Jean-Claude Dujardin", "Rainer Breitling", "David G. Watson", "Graham H. Coombs", "Saskia Decuypere"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0000904.g002", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Metabolic_profiles_of_the_340_identified_compounds_in_heatmap_format_/485710", "title"=>"Metabolic profiles of the 340 identified compounds in heatmap format.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-11-30 01:35:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/815518"], "description"=>"<p>Drug-sensitive and drug-resistant clones had significantly different profiles for 100 compounds (P<0.05). The graph compares the metabolic class distribution of these compounds. The left bar shows the distribution of the 51 compounds more abundant in the drug-sensitive clones and the right bar shows the distribution of the 49 compounds more abundant in the drug-resistant clones. The 100 compounds are generically listed in matching coloured reference-boxes; in which they are further grouped per metabolic sub class (PC  =  phosphatidylcholines; PE  =  phosphatidylethanolamines; * corresponds to masses with multiple identifications but for which only 1 is shown here; further details are available in <a href=\"http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0000904#pntd.0000904.s001\" target=\"_blank\">Table S1</a>.)</p>", "links"=>[], "tags"=>["metabolites", "profiles", "drug-sensitive", "drug-resistant"], "article_id"=>485877, "categories"=>["Cell Biology", "Microbiology", "Physics", "Medicine", "Virology"], "users"=>["Ruben t'Kindt", "Richard A. Scheltema", "Andris Jankevics", "Kirstyn Brunker", "Suman Rijal", "Jean-Claude Dujardin", "Rainer Breitling", "David G. Watson", "Graham H. Coombs", "Saskia Decuypere"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0000904.g004", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overview_of_all_identified_metabolites_with_significant_different_profiles_in_drug_sensitive_and_drug_resistant_clones_/485877", "title"=>"Overview of all identified metabolites with significant different profiles in drug-sensitive and drug-resistant clones.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-11-30 01:37:57"}
  • {"files"=>["https://ndownloader.figshare.com/files/815713"], "description"=>"<p>The heatmaps show a graphical overview of the fatty acyl (FA) structural properties in diacyl ester phosphatidylcholines (left panel) and diacyl ester phosphatidylethanolamines (right panel). The x-axis shows the total number of unsaturated bonds present in the 2 fatty acyl chains, while the y-axis shows the length of the fatty acyl chains in total number of carbon units. The heatmap intensity of a particular lipid species corresponds to the ratio of the detected average abundance in drug-resistant versus drug-sensitive clones of that lipid. Hence, lipids indicated in red are more abundant in drug-sensitive clones, while lipids in green are more abundant in drug-resistant clones.</p>", "links"=>[], "tags"=>["properties", "phosphatidylethanolamines"], "article_id"=>486073, "categories"=>["Cell Biology", "Microbiology", "Physics", "Medicine", "Virology"], "users"=>["Ruben t'Kindt", "Richard A. Scheltema", "Andris Jankevics", "Kirstyn Brunker", "Suman Rijal", "Jean-Claude Dujardin", "Rainer Breitling", "David G. Watson", "Graham H. Coombs", "Saskia Decuypere"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0000904.g006", "stats"=>{"downloads"=>3, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Structural_properties_of_phosphatidylethanolamines_and_phosphatidylcholines_/486073", "title"=>"Structural properties of phosphatidylethanolamines and phosphatidylcholines.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-11-30 01:41:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/815622"], "description"=>"<p>The layout is similar to <a href=\"http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0000904#pntd-0000904-g002\" target=\"_blank\">Figure 2</a>. Unsupervised hierarchical clustering of the samples (the tree above the x-axis) reveals that the lipid intensity profiles differ sufficiently to separate the drug-resistant and drug-sensitive clones. The lipid classes are colour-coded on the left. A shift towards PE content characterises drug-resistant parasites, while sphingolipids and sphingomyelins are less abundant in drug-resistant parasites (For PC and PE, only lipids with 2 acyl/alkyl side chains and an even number of side chain carbon units were included).</p>", "links"=>[], "tags"=>["phosphatidylethanolamines", "phosphatidylcholines", "sphingolipids", "sphingoid", "bases", "heatmap"], "article_id"=>485978, "categories"=>["Cell Biology", "Microbiology", "Physics", "Medicine", "Virology"], "users"=>["Ruben t'Kindt", "Richard A. Scheltema", "Andris Jankevics", "Kirstyn Brunker", "Suman Rijal", "Jean-Claude Dujardin", "Rainer Breitling", "David G. Watson", "Graham H. Coombs", "Saskia Decuypere"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0000904.g005", "stats"=>{"downloads"=>1, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Profiles_of_phosphatidylethanolamines_PE_phosphatidylcholines_PC_sphingolipids_and_sphingoid_bases_in_heatmap_format_/485978", "title"=>"Profiles of phosphatidylethanolamines (PE), phosphatidylcholines (PC), sphingolipids and sphingoid bases in heatmap format.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-11-30 01:39:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/815780"], "description"=>"<p>The antimonial activity index is defined as the ratio of the EC50 of a particular isolate or clone versus the ED50 of <i>L. donovani</i> MHOM/ET/67/HU3, a WHO reference isolate sensitive to sodium stibogluconate. The activity index was used to express the <i>in vitro</i> susceptibility of that tested isolate or clone. Isolates or clones with an activity index between 1 and 2 are considered as sensitive to antimonials, while those showing an activity index between 3 and 6 are considered to be resistant <a href=\"http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0000904#pntd.0000904-Rijal1\" target=\"_blank\">[9]</a>.</p>", "links"=>[], "tags"=>["isolates", "derived", "clones"], "article_id"=>486142, "categories"=>["Cell Biology", "Microbiology", "Physics", "Medicine", "Virology"], "users"=>["Ruben t'Kindt", "Richard A. Scheltema", "Andris Jankevics", "Kirstyn Brunker", "Suman Rijal", "Jean-Claude Dujardin", "Rainer Breitling", "David G. Watson", "Graham H. Coombs", "Saskia Decuypere"], "doi"=>"https://dx.doi.org/10.1371/journal.pntd.0000904.t001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Clinical_and_biological_data_of_the_L_donovani_isolates_and_derived_clones_used_in_the_study_/486142", "title"=>"Clinical and biological data of the <i>L. donovani</i> isolates and derived clones used in the study.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-11-30 01:42:22"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"14", "full-text"=>"15", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2015", "month"=>"11"}
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  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"12"}
  • {"unique-ip"=>"7", "full-text"=>"8", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"1"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"2"}
  • {"unique-ip"=>"5", "full-text"=>"6", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
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  • {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
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  • {"unique-ip"=>"6", "full-text"=>"7", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
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  • {"unique-ip"=>"4", "full-text"=>"5", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
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  • {"unique-ip"=>"10", "full-text"=>"7", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"2"}
  • {"unique-ip"=>"9", "full-text"=>"8", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2020", "month"=>"3"}
  • {"unique-ip"=>"13", "full-text"=>"11", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"4"}
  • {"unique-ip"=>"10", "full-text"=>"6", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"5"}
  • {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"6"}
  • {"unique-ip"=>"8", "full-text"=>"3", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"8"}
  • {"unique-ip"=>"8", "full-text"=>"11", "pdf"=>"6", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"9"}
  • {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"10"}
  • {"unique-ip"=>"8", "full-text"=>"5", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"11"}
  • {"unique-ip"=>"12", "full-text"=>"9", "pdf"=>"7", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"12"}

Relative Metric

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