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{"title"=>"The Colonization dynamics of the gut microbiota in tilapia larvae", "type"=>"journal", "authors"=>[{"first_name"=>"Christos", "last_name"=>"Giatsis", "scopus_author_id"=>"56297245700"}, {"first_name"=>"Detmer", "last_name"=>"Sipkema", "scopus_author_id"=>"6603312047"}, {"first_name"=>"Hauke", "last_name"=>"Smidt", "scopus_author_id"=>"6701505536"}, {"first_name"=>"Johan", "last_name"=>"Verreth", "scopus_author_id"=>"6701827837"}, {"first_name"=>"Marc", "last_name"=>"Verdegem", "scopus_author_id"=>"6603859301"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84904961479", "doi"=>"10.1371/journal.pone.0103641", "pui"=>"373644933", "pmid"=>"25072852", "scopus"=>"2-s2.0-84904961479", "issn"=>"19326203", "isbn"=>"1932-6203"}, "id"=>"27fdf666-7010-3fad-ad6c-0ffcafe6840b", "abstract"=>"The gut microbiota of fish larvae evolves fast towards a complex community. Both host and environment affect the development of the gut microbiota; however, the relative importance of both is poorly understood. Determining specific changes in gut microbial populations in response to a change in an environmental factor is very complicated. Interactions between factors are difficult to separate and any response could be masked due to high inter-individual variation even for individuals that share a common environment. In this study we characterized and quantified the spatio-temporal variation in the gut microbiota of tilapia larvae, reared in recirculating aquaculture systems (RAS) or active suspension tanks (AS). Our results showed that variation in gut microbiota between replicate tanks was not significantly higher than within tank variation, suggesting that there is no tank effect on water and gut microbiota. However, when individuals were reared in replicate RAS, gut microbiota differed significantly. The highest variation was observed between individuals reared in different types of system (RAS vs. AS). Our data suggest that under experimental conditions in which the roles of deterministic and stochastic factors have not been precisely determined, compositional replication of the microbial communities of an ecosystem is not predictable.", "link"=>"http://www.mendeley.com/research/colonization-dynamics-gut-microbiota-tilapia-larvae", "reader_count"=>91, "reader_count_by_academic_status"=>{"Unspecified"=>5, "Professor > Associate Professor"=>5, "Researcher"=>10, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>28, "Student > Postgraduate"=>2, "Student > Master"=>18, "Other"=>4, "Student > Bachelor"=>6, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>5, "Professor > Associate Professor"=>5, "Researcher"=>10, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>28, "Student > Postgraduate"=>2, "Student > Master"=>18, "Other"=>4, "Student > Bachelor"=>6, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>9, "Environmental Science"=>7, "Biochemistry, Genetics and Molecular Biology"=>6, "Agricultural and Biological Sciences"=>63, "Veterinary Science and Veterinary Medicine"=>1, "Chemistry"=>1, "Immunology and Microbiology"=>4}, "reader_count_by_subdiscipline"=>{"Chemistry"=>{"Chemistry"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>4}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>63}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>6}, "Unspecified"=>{"Unspecified"=>9}, "Environmental Science"=>{"Environmental Science"=>7}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Netherlands"=>1, "Belgium"=>1, "United States"=>2, "Mexico"=>1, "Germany"=>1}, "group_count"=>3}

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• http://doi.org/10.1093/femsec/fix161
• http://doi.org/10.1016/j.envpol.2016.10.028
• http://doi.org/10.1007/s12088-017-0641-9
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• http://doi.org/10.1111/jfb.13496
• http://doi.org/10.1371/journal.pone.0236601
• http://doi.org/10.3389/fmicb.2018.00851
• http://doi.org/10.3389/fmicb.2018.01073
• http://doi.org/10.3390/md19010006
• http://doi.org/10.1111/1462-2920.12888
• http://doi.org/10.1038/srep33965
• http://doi.org/10.1016/j.gendis.2017.06.001
• http://doi.org/10.3390/ani10061055
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• http://doi.org/10.1186/s40168-020-00938-2
• http://doi.org/10.1016/j.aqrep.2020.100372

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• {"files"=>["https://ndownloader.figshare.com/files/1613124"], "description"=>"<p>P values are based on 9999 Monte Carlo (MC) permutations. Effects of the interaction terms are not shown in the table.</p>", "links"=>[], "tags"=>["agriculture", "aquaculture", "Fish farming", "ecology", "Coastal ecology", "Freshwater ecology", "Marine ecology", "microbial ecology", "Marine biology", "Fisheries science", "microbiology", "Gastroenterology and hepatology", "Infectious diseases", "Bacterial diseases", "permanova", "dgge"], "article_id"=>1120841, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Christos Giatsis", "Detmer Sipkema", "Hauke Smidt", "Johan Verreth", "Marc Verdegem"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0103641.t001", "stats"=>{"downloads"=>4, "page_views"=>37, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overall_PERMANOVA_test_based_on_DGGE_data_for_main_experimental_factors_/1120841", "title"=>"Overall PERMANOVA test based on DGGE data for main experimental factors.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-07-29 02:51:12"}
• {"files"=>["https://ndownloader.figshare.com/files/1613123"], "description"=>"<p>Tests were performed by sample type per sampling day, with P values for each comparison from two different statistical tests (PERMANOVA and ANOSIM). ANOSIM results are complementary to the PERMANOVA to provide information on the degree of separation between groups, suggested by R statistic. The 2/10, 6/10 & 7/10 indicate the number of significant out of the total available comparisons. D00, 07, 14, 28, 42: sampling day 0,7,14,28 & 42 respectively, AS1-5: replicate active suspension system 1 till 5, Ra & Rb: replicate recirculating system a & b. P values are based on 9999 Monte Carlo permutations.</p>", "links"=>[], "tags"=>["agriculture", "aquaculture", "Fish farming", "ecology", "Coastal ecology", "Freshwater ecology", "Marine ecology", "microbial ecology", "Marine biology", "Fisheries science", "microbiology", "Gastroenterology and hepatology", "Infectious diseases", "Bacterial diseases", "comparisons", "replicate", "systems", "ras", "dgge", "454", "pyrosequencing"], "article_id"=>1120840, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Christos Giatsis", "Detmer Sipkema", "Hauke Smidt", "Johan Verreth", "Marc Verdegem"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0103641.t002", "stats"=>{"downloads"=>5, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Pairwise_comparisons_between_replicate_systems_for_RAS_and_AS_separately_based_on_DGGE_and_454_pyrosequencing_data_sets_/1120840", "title"=>"Pairwise comparisons between replicate systems for RAS and AS separately, based on DGGE and 454 pyrosequencing data sets.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-07-29 02:51:12"}
• {"files"=>["https://ndownloader.figshare.com/files/1613122"], "description"=>"<p>Tests were performed by sample type per sampling day, with P values for each comparison from two different statistical tests (PERMANOVA and ANOSIM). ANOSIM analysis is complementary to PERMANOVA as it provides information on the degree of separation between groups, suggested by R statistic. N.A.: No pyrosequencing data available for that day. D00, 07, 14, 28, 42: sampling day 0,7,14,28 & 42 respectively, AS1-5: replicate active suspension system 1 till 5, Ra & Rb: replicate recirculating system a & b. P values are based on 9999 Monte Carlo permutations.</p>", "links"=>[], "tags"=>["agriculture", "aquaculture", "Fish farming", "ecology", "Coastal ecology", "Freshwater ecology", "Marine ecology", "microbial ecology", "Marine biology", "Fisheries science", "microbiology", "Gastroenterology and hepatology", "Infectious diseases", "Bacterial diseases", "comparisons", "ras", "systems", "dgge", "454", "pyrosequencing"], "article_id"=>1120838, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Christos Giatsis", "Detmer Sipkema", "Hauke Smidt", "Johan Verreth", "Marc Verdegem"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0103641.t003", "stats"=>{"downloads"=>2, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Pairwise_comparisons_between_RAS_and_AS_systems_based_on_DGGE_and_454_pyrosequencing_data_sets_/1120838", "title"=>"Pairwise comparisons between RAS and AS systems based on DGGE and 454 pyrosequencing data sets.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-07-29 02:51:12"}
• {"files"=>["https://ndownloader.figshare.com/files/1613118"], "description"=>"<p>Each point represents the water microbiota from each tank. Plots are based on Bray Curtis distance after square root transformation of relative abundance DGGE data. D00, 07, 14, 28, 42: sampling days 0, 7, 14, 28 & 42 respectively, AS1-5: replicate active suspension system 1 to 5, Ra & Rb: replicate recirculating system a & b. Stress values are reported for the two dimensions and are indicative of the goodness of fit of data into the plot.</p>", "links"=>[], "tags"=>["agriculture", "aquaculture", "Fish farming", "ecology", "Coastal ecology", "Freshwater ecology", "Marine ecology", "microbial ecology", "Marine biology", "Fisheries science", "microbiology", "Gastroenterology and hepatology", "Infectious diseases", "Bacterial diseases", "metric", "dimensional", "scaling", "microbiota", "systems"], "article_id"=>1120835, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Christos Giatsis", "Detmer Sipkema", "Hauke Smidt", "Johan Verreth", "Marc Verdegem"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0103641.g003", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Non_metric_dimensional_scaling_nMDS_of_water_microbiota_from_different_systems_over_time_/1120835", "title"=>"Non metric dimensional scaling (nMDS) of water microbiota from different systems over time.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-07-29 02:51:12"}
• {"files"=>["https://ndownloader.figshare.com/files/1613117"], "description"=>"<p>Each point represents the gut microbiota of one individual. Plots are based on Bray Curtis distance after square root transformation of relative abundance DGGE data. D00, 07, 14, 28, 42: sampling days 0, 7, 14, 28 & 42 respectively, AS1-5: replicate active suspension system 1 to 5, Ra & Rb: replicate recirculating system a & b. Stress values are reported for the two dimension and are indicative of the goodness of fit of data into the plot.</p>", "links"=>[], "tags"=>["agriculture", "aquaculture", "Fish farming", "ecology", "Coastal ecology", "Freshwater ecology", "Marine ecology", "microbial ecology", "Marine biology", "Fisheries science", "microbiology", "Gastroenterology and hepatology", "Infectious diseases", "Bacterial diseases", "metric", "dimensional", "scaling", "microbiota", "individuals", "reared", "systems"], "article_id"=>1120834, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Christos Giatsis", "Detmer Sipkema", "Hauke Smidt", "Johan Verreth", "Marc Verdegem"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0103641.g002", "stats"=>{"downloads"=>1, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Non_metric_dimensional_scaling_nMDS_of_gut_microbiota_from_individuals_reared_in_different_systems_over_time_/1120834", "title"=>"Non metric dimensional scaling (nMDS) of gut microbiota from individuals reared in different systems over time.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-07-29 02:51:12"}
• {"files"=>["https://ndownloader.figshare.com/files/1613130", "https://ndownloader.figshare.com/files/1613131", "https://ndownloader.figshare.com/files/1613132", "https://ndownloader.figshare.com/files/1613134"], "description"=>"<div><p>The gut microbiota of fish larvae evolves fast towards a complex community. Both host and environment affect the development of the gut microbiota; however, the relative importance of both is poorly understood. Determining specific changes in gut microbial populations in response to a change in an environmental factor is very complicated. Interactions between factors are difficult to separate and any response could be masked due to high inter-individual variation even for individuals that share a common environment. In this study we characterized and quantified the spatio-temporal variation in the gut microbiota of tilapia larvae, reared in recirculating aquaculture systems (RAS) or active suspension tanks (AS). Our results showed that variation in gut microbiota between replicate tanks was not significantly higher than within tank variation, suggesting that there is no tank effect on water and gut microbiota. However, when individuals were reared in replicate RAS, gut microbiota differed significantly. The highest variation was observed between individuals reared in different types of system (RAS vs. AS). Our data suggest that under experimental conditions in which the roles of deterministic and stochastic factors have not been precisely determined, compositional replication of the microbial communities of an ecosystem is not predictable.</p></div>", "links"=>[], "tags"=>["agriculture", "aquaculture", "Fish farming", "ecology", "Coastal ecology", "Freshwater ecology", "Marine ecology", "microbial ecology", "Marine biology", "Fisheries science", "microbiology", "Gastroenterology and hepatology", "Infectious diseases", "Bacterial diseases", "colonization", "microbiota", "tilapia"], "article_id"=>1120847, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Christos Giatsis", "Detmer Sipkema", "Hauke Smidt", "Johan Verreth", "Marc Verdegem"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0103641.s001", "https://dx.doi.org/10.1371/journal.pone.0103641.s002", "https://dx.doi.org/10.1371/journal.pone.0103641.s003", "https://dx.doi.org/10.1371/journal.pone.0103641.s004"], "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_Colonization_Dynamics_of_the_Gut_Microbiota_in_Tilapia_Larvae_/1120847", "title"=>"The Colonization Dynamics of the Gut Microbiota in Tilapia Larvae", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-07-29 02:51:12"}
• {"files"=>["https://ndownloader.figshare.com/files/1613112"], "description"=>"<p>On y-axis: similarity percentage based on Bray Curtis similarity, on x-axis: all individual samples of gut (left) and water (right). D07 and 42: sampling day 7 & 42, AS 4 & 5: replicate active suspension systems 4 & 5, Ra and Rb: replicate recirculating system a and b. Numbers 2, 4 & 3, 4: replicate tanks from Ra and Rb respectively. Last digits following the tank number indicate the number of replicate fish in each tank. Since only one water sample was taken from each tank, the last digits were omitted from water sample’s ID. (e.g. 42Rb.3.10: Gut of day 42, from recirculating system b, tank 3, fish 10 whereas 07Ra.2: Water of day 7, from recirculating system a, tank 2).</p>", "links"=>[], "tags"=>["agriculture", "aquaculture", "Fish farming", "ecology", "Coastal ecology", "Freshwater ecology", "Marine ecology", "microbial ecology", "Marine biology", "Fisheries science", "microbiology", "Gastroenterology and hepatology", "Infectious diseases", "Bacterial diseases", "clustering", "unweighted", "arithmetic", "linkage", "samples", "454"], "article_id"=>1120829, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Christos Giatsis", "Detmer Sipkema", "Hauke Smidt", "Johan Verreth", "Marc Verdegem"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0103641.g001", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Hierarchical_clustering_with_Unweighted_Pair_Group_with_Arithmetic_Mean_UPGMA_linkage_of_gut_and_water_samples_based_on_454_data_/1120829", "title"=>"Hierarchical clustering with Unweighted Pair Group with Arithmetic Mean (UPGMA) linkage of gut and water samples based on 454 data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-07-29 02:51:12"}
• {"files"=>["https://ndownloader.figshare.com/files/1613126"], "description"=>"<p>Analysis was performed both on DGGE and 454 pyrosequencing data sets. D00, 07, 14, 28, 42: sampling day 0,7,14,28 & 42 respectively, Ra & Rb: replicate recirculating system a & b. Tank numbers 6–10 & 11–15, refer to replicate tanks of Ra and Rb, respectively. P values are based on 9999 Monte Carlo permutations. P values<0.05 are highlighted in bold.</p>", "links"=>[], "tags"=>["agriculture", "aquaculture", "Fish farming", "ecology", "Coastal ecology", "Freshwater ecology", "Marine ecology", "microbial ecology", "Marine biology", "Fisheries science", "microbiology", "Gastroenterology and hepatology", "Infectious diseases", "Bacterial diseases", "comparisons", "individuals", "reared", "replicate", "tanks"], "article_id"=>1120843, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Christos Giatsis", "Detmer Sipkema", "Hauke Smidt", "Johan Verreth", "Marc Verdegem"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0103641.t004", "stats"=>{"downloads"=>8, "page_views"=>23, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Pairwise_comparisons_between_individuals_reared_in_replicate_tanks_of_the_same_system_/1120843", "title"=>"Pairwise comparisons between individuals reared in replicate tanks of the same system.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-07-29 02:51:12"}
• {"files"=>["https://ndownloader.figshare.com/files/1613125"], "description"=>"<p>Analysis is based on DGGE data sets. Tests were performed by sample type, with P values for each comparison from two different statistical tests (PERMANOVA and ANOSIM). ANOSIM results are complementary to the PERMANOVA as they provide information on the degree of separation between groups, suggested by R statistic. D00, 07, 14, 28, 42: sampling day 0, 7, 14, 28 & 42 respectively, AS1-5: replicate active suspension system 1 till 5, Ra & Rb: replicate recirculating system a & b. P values are based on 9999 Monte Carlo permutations.</p>", "links"=>[], "tags"=>["agriculture", "aquaculture", "Fish farming", "ecology", "Coastal ecology", "Freshwater ecology", "Marine ecology", "microbial ecology", "Marine biology", "Fisheries science", "microbiology", "Gastroenterology and hepatology", "Infectious diseases", "Bacterial diseases", "comparisons", "days", "ras", "replicate", "systems"], "article_id"=>1120842, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Christos Giatsis", "Detmer Sipkema", "Hauke Smidt", "Johan Verreth", "Marc Verdegem"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0103641.t005", "stats"=>{"downloads"=>4, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Pairwise_comparisons_between_consecutive_days_for_RAS_and_AS_replicate_systems_separately_/1120842", "title"=>"Pairwise comparisons between consecutive days for RAS and AS replicate systems separately.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-07-29 02:51:12"}
• {"files"=>["https://ndownloader.figshare.com/files/1613120"], "description"=>"<p>Plots are based on Bray Curtis distance after square root transformation of relative abundance DGGE data. D00, 07, 14, 28, 42: sampling days 0, 7, 14, 28 & 42 respectively. Each point in the plots represents the group centroid and the shift of group average microbiota in time. Zero stress values for each plot are indicative of the fit due to the representation of the centroids. AS and RAS: active suspension and recirculating system, Ra & Rb: replicate recirculating system a & b.</p>", "links"=>[], "tags"=>["agriculture", "aquaculture", "Fish farming", "ecology", "Coastal ecology", "Freshwater ecology", "Marine ecology", "microbial ecology", "Marine biology", "Fisheries science", "microbiology", "Gastroenterology and hepatology", "Infectious diseases", "Bacterial diseases", "dimensional", "nmds", "microbiota", "systems"], "article_id"=>1120837, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Christos Giatsis", "Detmer Sipkema", "Hauke Smidt", "Johan Verreth", "Marc Verdegem"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0103641.g005", "stats"=>{"downloads"=>0, "page_views"=>44, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Three_dimensional_nMDS_plots_of_gut_microbiota_from_different_systems_over_time_trajectory_/1120837", "title"=>"Three dimensional nMDS plots of gut microbiota from different systems over time (trajectory).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-07-29 02:51:12"}
• {"files"=>["https://ndownloader.figshare.com/files/1613119"], "description"=>"<p>Points represent mean values of gut microbiota between individuals reared either in the same tank (Within tank), replicate tanks (Between tank) or between systems (Between System). (A): Comparison for Recirculating Aquaculture Systems (RAS). (B) Comparison for Active Suspension (AS). (C) Comparison between RAS and AS Systems & (D) Dispersion of samples from group centroid in RAS and AS systems. Error bars show standard error. Different data labels (a, b and c) per sampling day indicated significant difference (P<0.05) based on one-way ANOVA and Bonferroni ranking test for A, B & C and permutation dispersion test for D, (P(perm)<0.05).</p>", "links"=>[], "tags"=>["agriculture", "aquaculture", "Fish farming", "ecology", "Coastal ecology", "Freshwater ecology", "Marine ecology", "microbial ecology", "Marine biology", "Fisheries science", "microbiology", "Gastroenterology and hepatology", "Infectious diseases", "Bacterial diseases", "curtis", "dispersion", "centroid", "euclidian", "sampling"], "article_id"=>1120836, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Christos Giatsis", "Detmer Sipkema", "Hauke Smidt", "Johan Verreth", "Marc Verdegem"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0103641.g004", "stats"=>{"downloads"=>0, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Bray_Curtis_similarity_A_B_amp_C_and_dispersion_from_centroid_based_on_Euclidian_distance_D_for_each_sampling_day_/1120836", "title"=>"Bray Curtis similarity (%) (A, B & C) and dispersion from centroid based on Euclidian distance (D) for each sampling day.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-07-29 02:51:12"}

PMC Usage Stats | Further Information

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• {"unique-ip"=>"7", "full-text"=>"3", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"9"}
• {"unique-ip"=>"15", "full-text"=>"24", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2015", "month"=>"10"}
• {"unique-ip"=>"15", "full-text"=>"12", "pdf"=>"12", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2014", "month"=>"8"}
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Relative Metric

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F1000Prime