A Dynamic View of Trauma/Hemorrhage-Induced Inflammation in Mice: Principal Drivers and Networks
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{"title"=>"A dynamic view of trauma/hemorrhage-induced inflammation in mice: Principal drivers and networks", "type"=>"journal", "authors"=>[{"first_name"=>"Qi", "last_name"=>"Mi", "scopus_author_id"=>"22135368300"}, {"first_name"=>"Gregory", "last_name"=>"Constantine", "scopus_author_id"=>"7006841346"}, {"first_name"=>"Cordelia", "last_name"=>"Ziraldo", "scopus_author_id"=>"36605603200"}, {"first_name"=>"Alexey", "last_name"=>"Solovyev", "scopus_author_id"=>"36702266400"}, {"first_name"=>"Andres", "last_name"=>"Torres", "scopus_author_id"=>"7401786282"}, {"first_name"=>"Rajaie", "last_name"=>"Namas", "scopus_author_id"=>"24481691600"}, {"first_name"=>"Timothy", "last_name"=>"Bentley", "scopus_author_id"=>"57197584995"}, {"first_name"=>"Timothy R.", "last_name"=>"Billiar", "scopus_author_id"=>"35353765300"}, {"first_name"=>"Ruben", "last_name"=>"Zamora", "scopus_author_id"=>"7103323600"}, {"first_name"=>"Juan Carlos", "last_name"=>"Puyana", "scopus_author_id"=>"7004461915"}, {"first_name"=>"Yoram", "last_name"=>"Vodovotz", "scopus_author_id"=>"7005298726"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"21573002", "sgr"=>"79955904927", "doi"=>"10.1371/journal.pone.0019424", "scopus"=>"2-s2.0-79955904927", "pui"=>"361753392", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "issn"=>"19326203"}, "id"=>"722e4d50-8fd4-3591-b915-aa0a03531a96", "abstract"=>"BACKGROUND: Complex biological processes such as acute inflammation induced by trauma/hemorrhagic shock/ (T/HS) are dynamic and multi-dimensional. We utilized multiplexing cytokine analysis coupled with data-driven modeling to gain a systems perspective into T/HS.\\n\\nMETHODOLOGY/PRINCIPAL FINDINGS: Mice were subjected to surgical cannulation trauma (ST) ± hemorrhagic shock (HS; 25 mmHg), and followed for 1, 2, 3, or 4 h in each case. Serum was assayed for 20 cytokines and NO(2) (-)/NO(3) (-). These data were analyzed using four data-driven methods (Hierarchical Clustering Analysis [HCA], multivariate analysis [MA], Principal Component Analysis [PCA], and Dynamic Network Analysis [DyNA]). Using HCA, animals subjected to ST vs. ST + HS could be partially segregated based on inflammatory mediator profiles, despite a large overlap. Based on MA, interleukin [IL]-12p40/p70 (IL-12.total), monokine induced by interferon-γ (CXCL-9) [MIG], and IP-10 were the best discriminators between ST and ST/HS. PCA suggested that the inflammatory mediators found in the three main principal components in animals subjected to ST were IL-6, IL-10, and IL-13, while the three principal components in ST + HS included a large number of cytokines including IL-6, IL-10, keratinocyte-derived cytokine (CXCL-1) [KC], and tumor necrosis factor-α [TNF-α]. DyNA suggested that the circulating mediators produced in response to ST were characterized by a high degree of interconnection/complexity at all time points; the response to ST + HS consisted of different central nodes, and exhibited zero network density over the first 2 h with lesser connectivity vs. ST at all time points. DyNA also helped link the conclusions from MA and PCA, in that central nodes consisting of IP-10 and IL-12 were seen in ST, while MIG and IL-6 were central nodes in ST + HS.\\n\\nCONCLUSIONS/SIGNIFICANCE: These studies help elucidate the dynamics of T/HS-induced inflammation, complementing other forms of dynamic mechanistic modeling. These methods should be applicable to the analysis of other complex biological processes.", "link"=>"http://www.mendeley.com/research/dynamic-view-traumahemorrhageinduced-inflammation-mice-principal-drivers-networks", "reader_count"=>42, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>7, "Researcher"=>9, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>2, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>4, "Professor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>7, "Researcher"=>9, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>2, "Student > Master"=>3, "Other"=>1, "Student > Bachelor"=>4, "Professor"=>3}, "reader_count_by_subject_area"=>{"Engineering"=>6, "Unspecified"=>3, "Biochemistry, Genetics and Molecular Biology"=>1, "Medicine and Dentistry"=>16, "Agricultural and Biological Sciences"=>10, "Neuroscience"=>1, "Arts and Humanities"=>1, "Chemistry"=>1, "Computer Science"=>3}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>6}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>16}, "Neuroscience"=>{"Neuroscience"=>1}, "Chemistry"=>{"Chemistry"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>10}, "Computer Science"=>{"Computer Science"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>3}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"United States"=>2, "Denmark"=>1, "Portugal"=>1}, "group_count"=>0}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/776978"], "description"=>"<p>Mice were subjected to ST ± HS followed by measurement of cytokines, chemokines, and NO<sub>2</sub><sup>−</sup>/NO<sub>3</sub><sup>−</sup> as described in the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019424#s2\" target=\"_blank\"><i>Materials and Methods</i></a>. The figure shows the sorted overall PCA score for each inflammatory mediator.</p>", "links"=>[], "tags"=>["circulating", "inflammatory", "mediators", "induced", "st"], "article_id"=>447337, "categories"=>["Biological Sciences", "Immunology"], "users"=>["Qi Mi", "Gregory Constantine", "Cordelia Ziraldo", "Alexey Solovyev", "Andres Torres", "Rajaie Namas", "Timothy Bentley", "Timothy R. Billiar", "Ruben Zamora", "Juan Carlos Puyana", "Yoram Vodovotz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0019424.g004", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Principal_Component_Analysis_of_circulating_inflammatory_mediators_induced_by_ST_177_HS_/447337", "title"=>"Principal Component Analysis of circulating inflammatory mediators induced by ST ± HS.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-10 02:02:17"}
  • {"files"=>["https://ndownloader.figshare.com/files/389443", "https://ndownloader.figshare.com/files/389475", "https://ndownloader.figshare.com/files/389497", "https://ndownloader.figshare.com/files/389544", "https://ndownloader.figshare.com/files/389594", "https://ndownloader.figshare.com/files/389626", "https://ndownloader.figshare.com/files/389658", "https://ndownloader.figshare.com/files/389708", "https://ndownloader.figshare.com/files/389742", "https://ndownloader.figshare.com/files/389760", "https://ndownloader.figshare.com/files/389782", "https://ndownloader.figshare.com/files/389807", "https://ndownloader.figshare.com/files/389861", "https://ndownloader.figshare.com/files/389874"], "description"=>"<div><h3>Background</h3><p>Complex biological processes such as acute inflammation induced by trauma/hemorrhagic shock/ (T/HS) are dynamic and multi-dimensional. We utilized multiplexing cytokine analysis coupled with data-driven modeling to gain a systems perspective into T/HS.</p> <h3>Methodology/Principal Findings</h3><p>Mice were subjected to surgical cannulation trauma (ST) ± hemorrhagic shock (HS; 25 mmHg), and followed for 1, 2, 3, or 4 h in each case. Serum was assayed for 20 cytokines and NO<sub>2</sub><sup>−</sup>/NO<sub>3</sub><sup>−</sup>. These data were analyzed using four data-driven methods (Hierarchical Clustering Analysis [HCA], multivariate analysis [MA], Principal Component Analysis [PCA], and Dynamic Network Analysis [DyNA]). Using HCA, animals subjected to ST vs. ST + HS could be partially segregated based on inflammatory mediator profiles, despite a large overlap. Based on MA, interleukin [IL]-12p40/p70 (IL-12.total), monokine induced by interferon-γ (CXCL-9) [MIG], and IP-10 were the best discriminators between ST and ST/HS. PCA suggested that the inflammatory mediators found in the three main principal components in animals subjected to ST were IL-6, IL-10, and IL-13, while the three principal components in ST + HS included a large number of cytokines including IL-6, IL-10, keratinocyte-derived cytokine (CXCL-1) [KC], and tumor necrosis factor-α [TNF-α]. DyNA suggested that the circulating mediators produced in response to ST were characterized by a high degree of interconnection/complexity at all time points; the response to ST + HS consisted of different central nodes, and exhibited zero network density over the first 2 h with lesser connectivity vs. ST at all time points. DyNA also helped link the conclusions from MA and PCA, in that central nodes consisting of IP-10 and IL-12 were seen in ST, while MIG and IL-6 were central nodes in ST + HS.</p> <h3>Conclusions/Significance</h3><p>These studies help elucidate the dynamics of T/HS-induced inflammation, complementing other forms of dynamic mechanistic modeling. These methods should be applicable to the analysis of other complex biological processes.</p> </div>", "links"=>[], "tags"=>["inflammation", "drivers", "networks"], "article_id"=>136902, "categories"=>["Biological Sciences", "Immunology"], "users"=>["Qi Mi", "Gregory Constantine", "Cordelia Ziraldo", "Alexey Solovyev", "Andres Torres", "Rajaie Namas", "Timothy Bentley", "Timothy R. Billiar", "Ruben Zamora", "Juan Carlos Puyana", "Yoram Vodovotz"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0019424.s001", "https://dx.doi.org/10.1371/journal.pone.0019424.s002", "https://dx.doi.org/10.1371/journal.pone.0019424.s003", "https://dx.doi.org/10.1371/journal.pone.0019424.s004", "https://dx.doi.org/10.1371/journal.pone.0019424.s005", "https://dx.doi.org/10.1371/journal.pone.0019424.s006", "https://dx.doi.org/10.1371/journal.pone.0019424.s007", "https://dx.doi.org/10.1371/journal.pone.0019424.s008", "https://dx.doi.org/10.1371/journal.pone.0019424.s009", "https://dx.doi.org/10.1371/journal.pone.0019424.s010", "https://dx.doi.org/10.1371/journal.pone.0019424.s011", "https://dx.doi.org/10.1371/journal.pone.0019424.s012", "https://dx.doi.org/10.1371/journal.pone.0019424.s013", "https://dx.doi.org/10.1371/journal.pone.0019424.s014"], "stats"=>{"downloads"=>24, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/A_Dynamic_View_of_Trauma_Hemorrhage_Induced_Inflammation_in_Mice_Principal_Drivers_and_Networks/136902", "title"=>"A Dynamic View of Trauma/Hemorrhage-Induced Inflammation in Mice: Principal Drivers and Networks", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2011-05-10 01:55:02"}
  • {"files"=>["https://ndownloader.figshare.com/files/776870"], "description"=>"<p>Mice were subjected to ST ± HS followed by measurement of cytokines, chemokines, and NO<sub>2</sub><sup>−</sup>/NO<sub>3</sub><sup>−</sup> as described in the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019424#s2\" target=\"_blank\"><i>Materials and Methods</i></a>. Group 1, depicted in blue, 93% of Group 1 samples are ST and 7% are ST + HS; in Group 2, 32% samples are ST and 68% are ST + HS. A Chi-square test with P<0.001 suggests that the distribution of ST vs. ST+HS animals between Groups 1 and 2 is not random.</p>", "links"=>[], "tags"=>["clustering", "circulating", "inflammation", "biomarkers", "st"], "article_id"=>447235, "categories"=>["Biological Sciences", "Immunology"], "users"=>["Qi Mi", "Gregory Constantine", "Cordelia Ziraldo", "Alexey Solovyev", "Andres Torres", "Rajaie Namas", "Timothy Bentley", "Timothy R. Billiar", "Ruben Zamora", "Juan Carlos Puyana", "Yoram Vodovotz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0019424.g003", "stats"=>{"downloads"=>2, "page_views"=>37, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Hierarchical_Clustering_Analysis_of_circulating_inflammation_biomarkers_in_ST_177_HS_/447235", "title"=>"Hierarchical Clustering Analysis of circulating inflammation biomarkers in ST ± HS.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-10 02:00:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/777092"], "description"=>"<p>Mice were subjected to ST ± HS followed by measurement of cytokines, chemokines, and NO<sub>2</sub><sup>−</sup>/NO<sub>3</sub><sup>−</sup> as described in the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019424#s2\" target=\"_blank\"><i>Materials and Methods</i></a>. DyNA was carried out using these data as described in the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019424#s2\" target=\"_blank\"><i>Materials and Methods</i></a><i>. Panel A:</i> DyNA for ST, during each of the following four time frames: 0–1 h, 1–2 h, 2–3 h, and 3–4 h. <i>Panel B:</i> DyNA for ST + HS. In both <i>Panels A</i> and <i>B</i>, the most connected inflammatory mediators (nodes) are depicted in blue, and the inflammatory mediators linked directly to each central node are depicted in red. The mediators depicted in green are statistically significantly different from their own baseline values (p<0.05), but not correlated with any other mediators. <i>Panel C:</i> Network density plot for ST and ST + HS during each of the four time frames (0–1 h, 1–2 h, 2–3 h, and 3–4 h).</p>", "links"=>[], "tags"=>["st"], "article_id"=>447458, "categories"=>["Biological Sciences", "Immunology"], "users"=>["Qi Mi", "Gregory Constantine", "Cordelia Ziraldo", "Alexey Solovyev", "Andres Torres", "Rajaie Namas", "Timothy Bentley", "Timothy R. Billiar", "Ruben Zamora", "Juan Carlos Puyana", "Yoram Vodovotz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0019424.g005", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dynamic_Network_Analysis_summary_for_ST_177_HS_/447458", "title"=>"Dynamic Network Analysis summary for ST ± HS.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-10 02:04:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/776804"], "description"=>"<p>Mice were subjected to ST ± HS followed by measurement of cytokines, chemokines, and NO<sub>2</sub><sup>−</sup>/NO<sub>3</sub><sup>−</sup> as described in the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019424#s2\" target=\"_blank\"><i>Materials and Methods</i></a>. In each adjacent 1–h time period (0–1 h, 1–2 h, 2–3 h, and 3–4 h), the statistically significantly altered inflammatory analytes (p<0.05 by Student's t-test) were selected out of the total 21 mediators by comparing the level of a given mediator with its baseline value (no treatment [time  = 0]).</p>", "links"=>[], "tags"=>["inflammatory", "analytes", "modulated"], "article_id"=>447164, "categories"=>["Biological Sciences", "Immunology"], "users"=>["Qi Mi", "Gregory Constantine", "Cordelia Ziraldo", "Alexey Solovyev", "Andres Torres", "Rajaie Namas", "Timothy Bentley", "Timothy R. Billiar", "Ruben Zamora", "Juan Carlos Puyana", "Yoram Vodovotz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0019424.g002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Percent_of_inflammatory_analytes_modulated_as_a_function_of_time_and_procedure_/447164", "title"=>"Percent of inflammatory analytes modulated as a function of time and procedure.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-10 01:59:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/777198"], "description"=>"<p>Mice were subjected to ST ± HS followed by measurement of cytokines, chemokines, and NO<sub>2</sub><sup>−</sup>/NO<sub>3</sub><sup>−</sup> as described in the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019424#s2\" target=\"_blank\"><i>Materials and Methods</i></a>. The data were subjected to univariate analysis as described in the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019424#s2\" target=\"_blank\">Materials and Methods</a>; the top five inflammatory mediators most significantly different between ST and ST + HS are depicted.</p>", "links"=>[], "tags"=>["cytokine", "st"], "article_id"=>447557, "categories"=>["Biological Sciences", "Immunology"], "users"=>["Qi Mi", "Gregory Constantine", "Cordelia Ziraldo", "Alexey Solovyev", "Andres Torres", "Rajaie Namas", "Timothy Bentley", "Timothy R. Billiar", "Ruben Zamora", "Juan Carlos Puyana", "Yoram Vodovotz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0019424.t001", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Top_five_significantly_different_cytokine_in_ST_vs_ST_HS_/447557", "title"=>"Top five significantly different cytokine in ST vs. ST + HS.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2011-05-10 02:05:57"}
  • {"files"=>["https://ndownloader.figshare.com/files/776639"], "description"=>"<p>Mice were subjected to ST ± HS followed by measurement of cytokines, chemokines, and NO<sub>2</sub><sup>−</sup>/NO<sub>3</sub><sup>−</sup> as described in the <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0019424#s2\" target=\"_blank\"><i>Materials and Methods</i></a>.</p>", "links"=>[], "tags"=>["analyses"], "article_id"=>446998, "categories"=>["Biological Sciences", "Immunology"], "users"=>["Qi Mi", "Gregory Constantine", "Cordelia Ziraldo", "Alexey Solovyev", "Andres Torres", "Rajaie Namas", "Timothy Bentley", "Timothy R. Billiar", "Ruben Zamora", "Juan Carlos Puyana", "Yoram Vodovotz"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0019424.g001", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_of_analyses_utilized_in_the_present_study_/446998", "title"=>"Schematic of analyses utilized in the present study.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2011-05-10 01:56:38"}

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