The Poultry-Associated Microbiome: Network Analysis and Farm-to-Fork Characterizations
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{"title"=>"The Poultry-Associated Microbiome: Network Analysis and Farm-to-Fork Characterizations", "type"=>"journal", "authors"=>[{"first_name"=>"Brian B.", "last_name"=>"Oakley", "scopus_author_id"=>"8095414200"}, {"first_name"=>"Cesar A.", "last_name"=>"Morales", "scopus_author_id"=>"8722367000"}, {"first_name"=>"J.", "last_name"=>"Line", "scopus_author_id"=>"24775956400"}, {"first_name"=>"Mark E.", "last_name"=>"Berrang", "scopus_author_id"=>"7004712829"}, {"first_name"=>"Richard J.", "last_name"=>"Meinersmann", "scopus_author_id"=>"6701342929"}, {"first_name"=>"Glenn E.", "last_name"=>"Tillman", "scopus_author_id"=>"35171777200"}, {"first_name"=>"Mark G.", "last_name"=>"Wise", "scopus_author_id"=>"7202820839"}, {"first_name"=>"Gregory R.", "last_name"=>"Siragusa", "scopus_author_id"=>"7005328403"}, {"first_name"=>"Kelli L.", "last_name"=>"Hiett", "scopus_author_id"=>"24775782300"}, {"first_name"=>"Bruce S.", "last_name"=>"Seal", "scopus_author_id"=>"7007059221"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84874538737", "sgr"=>"84874538737", "pui"=>"368445593", "isbn"=>"6612414200", "pmid"=>"23468931", "doi"=>"10.1371/journal.pone.0057190"}, "id"=>"a3a21c23-790d-3eeb-85da-7d9ec136557a", "abstract"=>"Microbial communities associated with agricultural animals are important for animal health, food safety, and public health. Here we combine high-throughput sequencing (HTS), quantitative-PCR assays, and network analysis to profile the poultry-associated microbiome and important pathogens at various stages of commercial poultry production from the farm to the consumer. Analysis of longitudinal data following two flocks from the farm through processing showed a core microbiome containing multiple sequence types most closely related to genera known to be pathogenic for animals and/or humans, including Campylobacter, Clostridium, and Shigella. After the final stage of commercial poultry processing, taxonomic richness was ca. 2-4 times lower than the richness of fecal samples from the same flocks and Campylobacter abundance was significantly reduced. Interestingly, however, carcasses sampled at 48 hr after processing harboured the greatest proportion of unique taxa (those not encountered in other samples), significantly more than expected by chance. Among these were anaerobes such as Prevotella, Veillonella, Leptrotrichia, and multiple Campylobacter sequence types. Retail products were dominated by Pseudomonas, but also contained 27 other genera, most of which were potentially metabolically active and encountered in on-farm samples. Network analysis was focused on the foodborne pathogen Campylobacter and revealed a majority of sequence types with no significant interactions with other taxa, perhaps explaining the limited efficacy of previous attempts at competitive exclusion of Campylobacter. These data represent the first use of HTS to characterize the poultry microbiome across a series of farm-to-fork samples and demonstrate the utility of HTS in monitoring the food supply chain and identifying sources of potential zoonoses and interactions among taxa in complex communities.", "link"=>"http://www.mendeley.com/research/poultryassociated-microbiome-network-analysis-farmtofork-characterizations", "reader_count"=>90, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>6, "Researcher"=>23, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>1, "Student > Master"=>13, "Other"=>3, "Student > Bachelor"=>6, "Lecturer"=>1, "Professor"=>8}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>6, "Researcher"=>23, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>22, "Student > Postgraduate"=>1, "Student > Master"=>13, "Other"=>3, "Student > Bachelor"=>6, "Lecturer"=>1, "Professor"=>8}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Agricultural and Biological Sciences"=>55, "Veterinary Science and Veterinary Medicine"=>4, "Business, Management and Accounting"=>2, "Chemistry"=>1, "Computer Science"=>1, "Economics, Econometrics and Finance"=>1, "Environmental Science"=>2, "Biochemistry, Genetics and Molecular Biology"=>6, "Medicine and Dentistry"=>6, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>2, "Social Sciences"=>2, "Immunology and Microbiology"=>3}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>6}, "Social Sciences"=>{"Social Sciences"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>2}, "Unspecified"=>{"Unspecified"=>4}, "Environmental Science"=>{"Environmental Science"=>2}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Chemistry"=>{"Chemistry"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>55}, "Computer Science"=>{"Computer Science"=>1}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>6}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>4}}, "reader_count_by_country"=>{"United States"=>2, "South Africa"=>1, "Germany"=>1, "Spain"=>1}, "group_count"=>1}

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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/971911"], "description"=>"<p>A) Number of shared and unique taxa for each of the five sample types shown. The relative abundance of the 52 taxa belonging to a core microbiome common to all samples is shown for B) Feces, C) Wet litter, D) Dry litter, E) Carcass Rinses, and F) Carcass Weeps.</p>", "links"=>[], "tags"=>["microbiome", "classified", "usearch", "silva"], "article_id"=>640720, "categories"=>["Microbiology", "Biological Sciences", "Infectious Diseases"], "users"=>["Brian B. Oakley", "Cesar A. Morales", "J. Line", "Mark E. Berrang", "Richard J. Meinersmann", "Glenn E. Tillman", "Mark G. Wise", "Gregory R. Siragusa", "Kelli L. Hiett", "Bruce S. Seal"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0057190.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Core_microbiome_as_classified_to_the_species_level_with_usearch_against_the_Silva_reference_database_as_described_in_the_methods_/640720", "title"=>"Core microbiome as classified to the species level with usearch against the Silva reference database as described in the methods.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-28 09:15:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/971915"], "description"=>"<p>A) Number of shared and unique taxa for each of the five sample types shown. The relative abundance of the taxa unique to each sample type is shown for B) Fecal samples (blue), C) Wet litter (none), D) Dry litter (none), E) Carcass Rinses (black), and F) Carcass Weeps (red).</p>", "links"=>[], "tags"=>["classified", "usearch", "silva", "methods", "taxa"], "article_id"=>640724, "categories"=>["Microbiology", "Biological Sciences", "Infectious Diseases"], "users"=>["Brian B. Oakley", "Cesar A. Morales", "J. Line", "Mark E. Berrang", "Richard J. Meinersmann", "Glenn E. Tillman", "Mark G. Wise", "Gregory R. Siragusa", "Kelli L. Hiett", "Bruce S. Seal"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0057190.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Taxa_unique_to_each_sample_type_as_classified_to_the_species_level_with_usearch_against_the_Silva_reference_database_as_described_in_the_methods_for_taxa_representing_greater_than_0_1_of_all_sequences_/640724", "title"=>"Taxa unique to each sample type as classified to the species level with usearch against the Silva reference database as described in the methods for taxa representing greater than 0.1% of all sequences.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-28 09:16:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/971919"], "description"=>"<p>Number of 16S rRNA gene copies by sample type and farm for A) <i>Clostridium</i> group I assay, and B) <i>Campylobacter</i> genus-level-assay, and C) <i>C. jejuni</i>-specific cdtB assay. Horizontal bars represent means for sample types for all points within range. Letters denote statistical significance (p<0.05) of pairwise t tests performed in R with the Holm correction for multiple comparisons.</p>", "links"=>[], "tags"=>["abundance", "types", "quantitative-pcr"], "article_id"=>640728, "categories"=>["Microbiology", "Biological Sciences", "Infectious Diseases"], "users"=>["Brian B. Oakley", "Cesar A. Morales", "J. Line", "Mark E. Berrang", "Richard J. Meinersmann", "Glenn E. Tillman", "Mark G. Wise", "Gregory R. Siragusa", "Kelli L. Hiett", "Bruce S. Seal"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0057190.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Clostridium_and_Campylobacter_abundance_across_sample_types_as_determined_by_quantitative_PCR_for_Farm_2_grey_symbols_and_Farm_3_white_symbols_/640728", "title"=>"<i>Clostridium</i> and <i>Campylobacter</i> abundance across sample types as determined by quantitative-PCR for Farm 2 (grey symbols) and Farm 3 (white symbols).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-28 09:16:37"}
  • {"files"=>["https://ndownloader.figshare.com/files/971922"], "description"=>"<p>A) PCR results for amplification from total nucleic acids (lane 1), DNase treated reverse-transcriptase negative control (lane 2), and reverse-transcribed cDNA (lane 3). PCR reactions were performed with the broad-range primers 104F/530R as described in the text. Figure shows pooled products obtained from six retail packages of uncooked chicken parts; MW marker is NEB 100 bp ladder. B) Relative abundance of sequence types recovered from total nucleic acids (upper graph) as compared to sequence types present in the presumed potentially metabolically active fraction of the community (lower graph) classified to the genus level. Genera marked in bold (21 of 28) were designated potentially metabolically active as determined by sequence detection in the cDNA fraction. Genera marked with vertical arrows were also present in the carcass rinse or weep samples of the longitudinal data set. Genera marked with black circles were present in the fecal or litter samples of the longitudinal data set. Note break in Y axis for <i>Pseudomonas</i> which comprised 98% of both fractions. C) Comparison of species-level classification of sequences for <i>Pseudomonas</i> in DNA (upper graph) and cDNA (lower graph) fractions.</p>", "links"=>[], "tags"=>["bacterial", "poultry"], "article_id"=>640731, "categories"=>["Microbiology", "Biological Sciences", "Infectious Diseases"], "users"=>["Brian B. Oakley", "Cesar A. Morales", "J. Line", "Mark E. Berrang", "Richard J. Meinersmann", "Glenn E. Tillman", "Mark G. Wise", "Gregory R. Siragusa", "Kelli L. Hiett", "Bruce S. Seal"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0057190.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Characterization_of_bacterial_community_present_in_retail_poultry_products_/640731", "title"=>"Characterization of bacterial community present in retail poultry products.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-28 09:16:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/971925"], "description"=>"<p>A) Significant network associations for OTUs classified as <i>C. jejuni</i> and <i>C. coli</i> shown in detail, and B) in context of entire network. C) <i>C. jejuni</i> OTUs with connections only to other <i>Campylobacter</i> as shown in orange accounted for a majority of <i>Campylobacter</i> sequences. D) Two <i>Campylobacter</i> OTUs, Clstr3618 and Clstr97, shown in yellow and denoted by arrows, were connected to a much larger suite of taxa including <i>Megamonas hypermegale</i> and <i>Faecalibacterium prausnitzii</i> as discussed in the text.</p>", "links"=>[], "tags"=>["otus", "poultry-associated"], "article_id"=>640734, "categories"=>["Microbiology", "Biological Sciences", "Infectious Diseases"], "users"=>["Brian B. Oakley", "Cesar A. Morales", "J. Line", "Mark E. Berrang", "Richard J. Meinersmann", "Glenn E. Tillman", "Mark G. Wise", "Gregory R. Siragusa", "Kelli L. Hiett", "Bruce S. Seal"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0057190.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Network_analysis_of_Campylobacter_OTUs_within_poultry_associated_microbiomes_/640734", "title"=>"Network analysis of <i>Campylobacter</i> OTUs within poultry-associated microbiomes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-28 09:17:44"}
  • {"files"=>["https://ndownloader.figshare.com/files/971935", "https://ndownloader.figshare.com/files/971941", "https://ndownloader.figshare.com/files/971949", "https://ndownloader.figshare.com/files/971953", "https://ndownloader.figshare.com/files/971958"], "description"=>"<div><p>Microbial communities associated with agricultural animals are important for animal health, food safety, and public health. Here we combine high-throughput sequencing (HTS), quantitative-PCR assays, and network analysis to profile the poultry-associated microbiome and important pathogens at various stages of commercial poultry production from the farm to the consumer. Analysis of longitudinal data following two flocks from the farm through processing showed a core microbiome containing multiple sequence types most closely related to genera known to be pathogenic for animals and/or humans, including <i>Campylobacter, Clostridium</i>, and <i>Shigella</i>. After the final stage of commercial poultry processing, taxonomic richness was ca. 2–4 times lower than the richness of fecal samples from the same flocks and <i>Campylobacter</i> abundance was significantly reduced. Interestingly, however, carcasses sampled at 48 hr after processing harboured the greatest proportion of unique taxa (those not encountered in other samples), significantly more than expected by chance. Among these were anaerobes such as <i>Prevotella</i>, <i>Veillonella</i>, <i>Leptrotrichia</i>, and multiple <i>Campylobacter</i> sequence types. Retail products were dominated by <i>Pseudomonas</i>, but also contained 27 other genera, most of which were potentially metabolically active and encountered in on-farm samples. Network analysis was focused on the foodborne pathogen <i>Campylobacter</i> and revealed a majority of sequence types with no significant interactions with other taxa, perhaps explaining the limited efficacy of previous attempts at competitive exclusion of <i>Campylobacter</i>. These data represent the first use of HTS to characterize the poultry microbiome across a series of farm-to-fork samples and demonstrate the utility of HTS in monitoring the food supply chain and identifying sources of potential zoonoses and interactions among taxa in complex communities.</p> </div>", "links"=>[], "tags"=>["poultry-associated", "farm-to-fork", "characterizations"], "article_id"=>640740, "categories"=>["Microbiology", "Biological Sciences", "Infectious Diseases"], "users"=>["Brian B. Oakley", "Cesar A. Morales", "J. Line", "Mark E. Berrang", "Richard J. Meinersmann", "Glenn E. Tillman", "Mark G. Wise", "Gregory R. Siragusa", "Kelli L. Hiett", "Bruce S. Seal"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0057190.s001", "https://dx.doi.org/10.1371/journal.pone.0057190.s002", "https://dx.doi.org/10.1371/journal.pone.0057190.s003", "https://dx.doi.org/10.1371/journal.pone.0057190.s004", "https://dx.doi.org/10.1371/journal.pone.0057190.s005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/The_Poultry_Associated_Microbiome_Network_Analysis_and_Farm_to_Fork_Characterizations__/640740", "title"=>"The Poultry-Associated Microbiome: Network Analysis and Farm-to-Fork Characterizations", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-02-28 09:20:01"}

PMC Usage Stats | Further Information

  • {"unique-ip"=>"31", "full-text"=>"33", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"25", "cited-by"=>"0", "year"=>"2013", "month"=>"3"}
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  • {"unique-ip"=>"25", "full-text"=>"31", "pdf"=>"16", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"9", "supp-data"=>"15", "cited-by"=>"0", "year"=>"2013", "month"=>"6"}
  • {"unique-ip"=>"16", "full-text"=>"17", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"5", "cited-by"=>"0", "year"=>"2013", "month"=>"7"}
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  • {"unique-ip"=>"18", "full-text"=>"22", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"9", "supp-data"=>"5", "cited-by"=>"0", "year"=>"2013", "month"=>"9"}
  • {"unique-ip"=>"28", "full-text"=>"35", "pdf"=>"15", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"10"}
  • {"unique-ip"=>"19", "full-text"=>"20", "pdf"=>"12", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"11"}
  • {"unique-ip"=>"24", "full-text"=>"24", "pdf"=>"12", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2013", "month"=>"12"}
  • {"unique-ip"=>"12", "full-text"=>"13", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"1"}
  • {"unique-ip"=>"12", "full-text"=>"11", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2014", "month"=>"2"}
  • {"unique-ip"=>"14", "full-text"=>"15", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"3"}
  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"5"}
  • {"unique-ip"=>"6", "full-text"=>"5", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"6"}
  • {"unique-ip"=>"19", "full-text"=>"20", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"4"}
  • {"unique-ip"=>"9", "full-text"=>"10", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"7", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2015", "month"=>"4"}
  • {"unique-ip"=>"13", "full-text"=>"16", "pdf"=>"12", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"5"}
  • {"unique-ip"=>"14", "full-text"=>"14", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"6"}
  • {"unique-ip"=>"11", "full-text"=>"10", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"7"}
  • {"unique-ip"=>"15", "full-text"=>"18", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"3"}
  • {"unique-ip"=>"15", "full-text"=>"12", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"2"}
  • {"unique-ip"=>"11", "full-text"=>"11", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"8"}
  • {"unique-ip"=>"10", "full-text"=>"10", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"9"}
  • {"unique-ip"=>"14", "full-text"=>"21", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"10"}
  • {"unique-ip"=>"8", "full-text"=>"10", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"7"}
  • {"unique-ip"=>"11", "full-text"=>"10", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
  • {"unique-ip"=>"14", "full-text"=>"10", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2014", "month"=>"9"}
  • {"unique-ip"=>"16", "full-text"=>"11", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2014", "month"=>"10"}
  • {"unique-ip"=>"15", "full-text"=>"16", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2016", "month"=>"1"}
  • {"unique-ip"=>"20", "full-text"=>"18", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"2"}
  • {"unique-ip"=>"11", "full-text"=>"9", "pdf"=>"5", "abstract"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"11"}
  • {"unique-ip"=>"10", "full-text"=>"9", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"12"}
  • {"unique-ip"=>"13", "full-text"=>"11", "pdf"=>"9", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2015", "month"=>"1"}
  • {"unique-ip"=>"27", "full-text"=>"25", "pdf"=>"10", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"2", "year"=>"2015", "month"=>"11"}
  • {"unique-ip"=>"12", "full-text"=>"12", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"8", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2015", "month"=>"12"}
  • {"unique-ip"=>"20", "full-text"=>"24", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"0", "cited-by"=>"1", "year"=>"2016", "month"=>"3"}
  • {"unique-ip"=>"14", "full-text"=>"13", "pdf"=>"10", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"4"}
  • {"unique-ip"=>"17", "full-text"=>"17", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"6", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"5"}
  • {"unique-ip"=>"14", "full-text"=>"11", "pdf"=>"8", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"13", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
  • {"unique-ip"=>"17", "full-text"=>"33", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"6", "year"=>"2016", "month"=>"8"}
  • {"unique-ip"=>"11", "full-text"=>"16", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"15", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"12", "full-text"=>"11", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
  • {"unique-ip"=>"16", "full-text"=>"15", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"unique-ip"=>"15", "full-text"=>"16", "pdf"=>"10", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"12"}
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Relative Metric

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