Mathematical Modeling of Tuberculosis Bacillary Counts and Cellular Populations in the Organs of Infected Mice
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{"title"=>"Mathematical modeling of tuberculosis bacillary counts and cellular populations in the organs of infected mice", "type"=>"journal", "authors"=>[{"first_name"=>"Antonio", "last_name"=>"Bru", "scopus_author_id"=>"7003699413"}, {"first_name"=>"Pere Joan", "last_name"=>"Cardona", "scopus_author_id"=>"54790504400"}], "year"=>2010, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "pui"=>"359839184", "doi"=>"10.1371/journal.pone.0012985", "sgr"=>"77958518502", "scopus"=>"2-s2.0-77958518502", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"20886087"}, "id"=>"aa9ba974-31a4-33fa-b00c-67a7745261f3", "abstract"=>"BACKGROUND: Mycobacterium tuberculosis is a particularly aggressive microorganism and the host's defense is based on the induction of cellular immunity, in which the creation of a granulomatous structure has an important role.\\n\\nMETHODOLOGY: We present here a new 2D cellular automata model based on the concept of a multifunctional process that includes key factors such as the chemokine attraction of the cells; the role of innate immunity triggered by natural killers; the presence of neutrophils; apoptosis and necrosis of infected macrophages; the removal of dead cells by macrophages, which induces the production of foamy macrophages (FMs); the life cycle of the bacilli as a determinant for the evolution of infected macrophages; and the immune response.\\n\\nRESULTS: The results obtained after the inclusion of two degrees of tolerance to the inflammatory response triggered by the infection shows that the model can cover a wide spectrum, ranging from highly-tolerant (i.e. mice) to poorly-tolerant hosts (i.e. mini-pigs or humans).\\n\\nCONCLUSIONS: This model suggest that stopping bacillary growth at the onset of the infection might be difficult and the important role played by FMs in bacillary drainage in poorly-tolerant hosts together with apoptosis and innate lymphocytes. It also shows the poor ability of the cellular immunity to control the infection, provides a clear protective character to the granuloma, due its ability to attract a sufficient number of cells, and explains why an already infected host can be constantly reinfected.", "link"=>"http://www.mendeley.com/research/mathematical-modeling-tuberculosis-bacillary-counts-cellular-populations-organs-infected-mice", "reader_count"=>57, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>6, "Researcher"=>15, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>9, "Student > Postgraduate"=>4, "Student > Master"=>6, "Other"=>3, "Student > Bachelor"=>4, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>6, "Researcher"=>15, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>9, "Student > Postgraduate"=>4, "Student > Master"=>6, "Other"=>3, "Student > Bachelor"=>4, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>4}, "reader_count_by_subject_area"=>{"Engineering"=>4, "Unspecified"=>5, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>3, "Mathematics"=>4, "Medicine and Dentistry"=>19, "Agricultural and Biological Sciences"=>15, "Philosophy"=>1, "Physics and Astronomy"=>1, "Social Sciences"=>2, "Immunology and Microbiology"=>2}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>4}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>19}, "Social Sciences"=>{"Social Sciences"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>15}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}, "Mathematics"=>{"Mathematics"=>4}, "Unspecified"=>{"Unspecified"=>5}, "Environmental Science"=>{"Environmental Science"=>1}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"Argentina"=>1, "United States"=>2, "Japan"=>1, "United Kingdom"=>1, "Germany"=>1}, "group_count"=>4}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/413133", "https://ndownloader.figshare.com/files/413159", "https://ndownloader.figshare.com/files/413189", "https://ndownloader.figshare.com/files/413215", "https://ndownloader.figshare.com/files/413236", "https://ndownloader.figshare.com/files/413260", "https://ndownloader.figshare.com/files/413287", "https://ndownloader.figshare.com/files/413316", "https://ndownloader.figshare.com/files/413344", "https://ndownloader.figshare.com/files/413369", "https://ndownloader.figshare.com/files/413403", "https://ndownloader.figshare.com/files/413429", "https://ndownloader.figshare.com/files/413449", "https://ndownloader.figshare.com/files/413476", "https://ndownloader.figshare.com/files/413505", "https://ndownloader.figshare.com/files/413535"], "description"=>"<div><h3>Background</h3><p><em>Mycobacterium tuberculosis</em> is a particularly aggressive microorganism and the host's defense is based on the induction of cellular immunity, in which the creation of a granulomatous structure has an important role.</p><h3>Methodology</h3><p>We present here a new 2D cellular automata model based on the concept of a multifunctional process that includes key factors such as the chemokine attraction of the cells; the role of innate immunity triggered by natural killers; the presence of neutrophils; apoptosis and necrosis of infected macrophages; the removal of dead cells by macrophages, which induces the production of foamy macrophages (FMs); the life cycle of the bacilli as a determinant for the evolution of infected macrophages; and the immune response.</p><h3>Results</h3><p>The results obtained after the inclusion of two degrees of tolerance to the inflammatory response triggered by the infection shows that the model can cover a wide spectrum, ranging from highly-tolerant (i.e. mice) to poorly-tolerant hosts (i.e. mini-pigs or humans).</p><h3>Conclusions</h3><p>This model suggest that stopping bacillary growth at the onset of the infection might be difficult and the important role played by FMs in bacillary drainage in poorly-tolerant hosts together with apoptosis and innate lymphocytes. It also shows the poor ability of the cellular immunity to control the infection, provides a clear protective character to the granuloma, due its ability to attract a sufficient number of cells, and explains why an already infected host can be constantly reinfected.</p></div>", "links"=>[], "tags"=>["mathematical", "modeling", "tuberculosis", "bacillary", "counts", "cellular", "populations", "organs", "infected", "mice"], "article_id"=>141608, "categories"=>["Cancer", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.s001", "https://dx.doi.org/10.1371/journal.pone.0012985.s002", "https://dx.doi.org/10.1371/journal.pone.0012985.s003", "https://dx.doi.org/10.1371/journal.pone.0012985.s004", "https://dx.doi.org/10.1371/journal.pone.0012985.s005", "https://dx.doi.org/10.1371/journal.pone.0012985.s006", "https://dx.doi.org/10.1371/journal.pone.0012985.s007", "https://dx.doi.org/10.1371/journal.pone.0012985.s008", "https://dx.doi.org/10.1371/journal.pone.0012985.s009", "https://dx.doi.org/10.1371/journal.pone.0012985.s010", "https://dx.doi.org/10.1371/journal.pone.0012985.s011", "https://dx.doi.org/10.1371/journal.pone.0012985.s012", "https://dx.doi.org/10.1371/journal.pone.0012985.s013", "https://dx.doi.org/10.1371/journal.pone.0012985.s014", "https://dx.doi.org/10.1371/journal.pone.0012985.s015", "https://dx.doi.org/10.1371/journal.pone.0012985.s016"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Mathematical_Modeling_of_Tuberculosis_Bacillary_Counts_and_Cellular_Populations_in_the_Organs_of_Infected_Mice/141608", "title"=>"Mathematical Modeling of Tuberculosis Bacillary Counts and Cellular Populations in the Organs of Infected Mice", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2010-09-23 00:26:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/828704"], "description"=>"<p>Evolution of the infection without inducing an adaptative immune response in highly (HT) and poorly tolerant (PT) hosts according to the chemokine threshold above which a new cell can be attracted to a neighboring square (defined as 1000 arbitrary units (a.u.) and 650 a.u., respectively). A and B show the evolution of the bacillary load, and C and D the evolution of the different kind of macrophages. E and F show the evolution of natural killers (NK), neutrophils (PMN), and necrotic (NM) and apoptotic macrophages (APM).</p>", "links"=>[], "tags"=>["adaptative"], "article_id"=>499076, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolution_of_the_infection_without_an_adaptative_immune_response_/499076", "title"=>"Evolution of the infection without an adaptative immune response.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-09-23 02:31:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/828878"], "description"=>"<p>Evolution of the infection, including the presence of an adaptive immune response, in highly (HT) and poorly tolerant (PT) hosts according to the chemokine threshold above which a new cell can be attracted to a neighboring square (defined as 1000 arbitrary units (a.u.) and 650 a.u., respectively). A and B show the evolution of the bacillary load, and C and D the evolution of the different kind of macrophages. E and F show the evolution of natural killers (NK), neutrophils (PMN), and necrotic (NM) and apoptotic macrophages (APM). Appearance of the immune response is marked with a dotted line.</p>", "links"=>[], "tags"=>["adaptative"], "article_id"=>499246, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolution_of_the_infection_with_the_presence_of_an_adaptative_immune_response_/499246", "title"=>"Evolution of the infection with the presence of an adaptative immune response.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-09-23 02:34:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/829039"], "description"=>"<p>Evolution of the cellular infiltration caused by viable macrophages in the four cases analyzed in terms of the host's tolerance and immunological status. Squares represent the whole lattice assayed, and show the evolution every week. Percentages show the ratio between the number of cells occupied by a viable macrophage divided by the total number of cells.</p>", "links"=>[], "tags"=>["biophysics/theory and simulation", "computational biology/ecosystem modeling", "infectious diseases/respiratory infections", "respiratory medicine/respiratory infections"], "article_id"=>499407, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Cellular_infiltration_/499407", "title"=>"Cellular infiltration.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-09-23 02:36:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/829157"], "description"=>"<p>Characteristics of the granulomas taking into account the majority of the cells at week 4 post-infection in the four cases studied in terms of the tolerance and immune status. Squares represent the whole lattice assayed.</p>", "links"=>[], "tags"=>["biophysics/theory and simulation", "computational biology/ecosystem modeling", "infectious diseases/respiratory infections", "respiratory medicine/respiratory infections"], "article_id"=>499525, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Characteristics_of_the_granulomas_/499525", "title"=>"Characteristics of the granulomas.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-09-23 02:38:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/829279"], "description"=>"<p>Evolution of the chemokine concentration in the four cases analyzed in terms of the host's tolerance and immunological status. Squares represent the whole lattice assayed, and show the evolution every week.</p>", "links"=>[], "tags"=>["biophysics/theory and simulation", "computational biology/ecosystem modeling", "infectious diseases/respiratory infections", "respiratory medicine/respiratory infections"], "article_id"=>499652, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Chemokine_concentration_/499652", "title"=>"Chemokine concentration.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-09-23 02:40:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/829386"], "description"=>"<p>Effect of the availability time for specific T lymphocytes for HT and PT hosts (pictures A and B). Appearance of the change in the evolution of CFU counts is marked by a red dotted line; while the beginning of the usual immune response (10000 time-steps or iterations) is marked with a black hashed line.</p>", "links"=>[], "tags"=>["biophysics/theory and simulation", "computational biology/ecosystem modeling", "infectious diseases/respiratory infections", "respiratory medicine/respiratory infections"], "article_id"=>499758, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Availability_time_for_specific_T_lymphocytes_/499758", "title"=>"Availability time for specific T lymphocytes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-09-23 02:42:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/829450"], "description"=>"<p>Importance of the initial bacillary load in the evolution of the infection. Pictures A and B show the evolution of 100 runs for HT and PT hosts with an immune response, respectively, inoculating with one bacillus in 100 naïve scenarios. Pictures C and D show the evolution of the total bacillary load when inoculated with different loads at one unique lattice.</p>", "links"=>[], "tags"=>["bacillary"], "article_id"=>499822, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.g007"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Importance_of_the_initial_bacillary_load_in_the_evolution_of_the_infection_/499822", "title"=>"Importance of the initial bacillary load in the evolution of the infection.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-09-23 02:43:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/829532"], "description"=>"<p>Physical scenario of the cellular automata simulation system. A two-dimensional 100×100 lattice of micro-compartments has been built. As the diameter of an alveolar macrophage is around 20 µm, each of the micro-compartments in the lattice represents a square with dimensions 20×20 µm. A maximum of three live or dead cells can fit in each square, although only one living macrophage can be in a square at any one time (i.e. two living macrophages cannot be in the same square). The following pictures reproduce different phases in the evolution of the model. Picture <b>A</b> shows the very beginning of the infection, namely extracellular bacilli and a resting macrophage; <b>B</b> shows an infected macrophage that has already attracted cells around it; <b>C</b> shows a necrosed macrophage caused by the intracellular growth of the bacilli; <b>D</b> shows the entrance of immune response once the granuloma has been formed and the appearance of foamy macrophages.</p>", "links"=>[], "tags"=>["cellular", "automata", "simulation"], "article_id"=>499903, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.g008"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Physical_scenario_of_the_cellular_automata_simulation_system_/499903", "title"=>"Physical scenario of the cellular automata simulation system.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-09-23 02:45:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/829631"], "description"=>"<p>Characterization of the macrophages according to the most advanced phase of the life cycle of the bacilli inside them. The bacillary life cycle evolution, as monitored using the optical density in a static liquid culture, is represented in the background. (Modified from Buchanan 1918<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0012985#pone.0012985-Buchanan1\" target=\"_blank\">[40]</a>).</p>", "links"=>[], "tags"=>["biophysics/theory and simulation", "computational biology/ecosystem modeling", "infectious diseases/respiratory infections", "respiratory medicine/respiratory infections"], "article_id"=>499998, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.g009"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Characterization_of_the_macrophages_/499998", "title"=>"Characterization of the macrophages.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-09-23 02:46:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/829694"], "description"=>"<p>Representation of the <i>M. tuberculosis</i> infection cycle according to the macrophage phase status (infection, activation, necrosis, apoptosis and foamy macrophage production). Differentiation to dendritic cells is also considered at the very first phase of the evolution.</p>", "links"=>[], "tags"=>["biophysics/theory and simulation", "computational biology/ecosystem modeling", "infectious diseases/respiratory infections", "respiratory medicine/respiratory infections"], "article_id"=>500068, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.g010"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mycobacterium_tuberculosis_infection_cycle_/500068", "title"=>"<i>Mycobacterium tuberculosis</i> infection cycle.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-09-23 00:01:08"}
  • {"files"=>["https://ndownloader.figshare.com/files/829790"], "description"=>"<p>Transformation of the macrophage status according to given probabilities, taking into account the number of cells (C) and bacilli (nB<i>intra</i>) phagocytosed; the time that a bacilli has been in the extracellular milieu (Textra) or inside the macrophage (T<i>intra</i>); and the bacillary life-cycle periods (i.e. T<i>lag</i>, T<i>early-log</i> and T<i>late-log</i>) together with the bacillary duplication time (T<i>dupli</i>). The presence of intra- or extracellular bacilli (B<i>intra</i> and B<i>extra</i> respectively), as well as when a bacteria becomes non-replicating for a long time (B<i>nr</i>) and the time that it maintains this status (T<i>nr</i>), are also indicated.</p>", "links"=>[], "tags"=>["macrophage"], "article_id"=>500159, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.g011"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Transformation_of_the_macrophage_status_/500159", "title"=>"Transformation of the macrophage status.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-09-23 00:02:39"}
  • {"files"=>["https://ndownloader.figshare.com/files/829888"], "description"=>"<p>Macrophages =  resting (RM); infected (MI); infected-consolidated (ICM); infected-at risk (IRM); infected-sentenced (ISM); activated (ACM); necrosed (NM); apoptosed (APM).</p><p>Neutrophils (PMN); Natural killers (NK).</p><p>Specific T lymphocytes (Ts).</p><p>N.A. =  not applicable.</p><p>Iterations =  Time-steps.</p><p>*number of iterations required to move the distance of one micro-compartment of the lattice.</p>", "links"=>[], "tags"=>["cellular"], "article_id"=>500262, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Lifetime_and_speed_of_the_different_cellular_entities_/500262", "title"=>"Lifetime and speed of the different cellular entities.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-09-23 00:04:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/829929"], "description"=>"<p>RM =  resting macrophages; PMN =  neutrophils; NK =  Natural killers; Ts =  specific T lymphocytes.</p>", "links"=>[], "tags"=>["cellular", "compartment", "chemokine"], "article_id"=>500296, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.t003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Probability_in_of_cellular_appearance_in_a_compartment_once_the_chemokine_concentration_is_above_the_cellular_threshold_/500296", "title"=>"Probability (in %) of cellular appearance in a compartment once the chemokine concentration is above the cellular threshold.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-09-23 00:04:56"}
  • {"files"=>["https://ndownloader.figshare.com/files/829966"], "description"=>"<p>Macrophages =  infected-consolidated (ICM); infected-at risk (IRM); infected-sentenced (ISM); activated (ACM); necrosed (NM).</p><p>N.A. =  not applicable.</p>", "links"=>[], "tags"=>["cellular", "entities", "chemokines", "arbitrary"], "article_id"=>500337, "categories"=>["Infectious Diseases", "Medicine", "Biophysics"], "users"=>["Antonio Bru", "Pere-Joan Cardona"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0012985.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Ability_of_the_different_cellular_entities_to_generate_chemokines_in_arbitrary_units_/500337", "title"=>"Ability of the different cellular entities to generate chemokines (in arbitrary units).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-09-23 00:05:37"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"6", "full-text"=>"4", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"7", "full-text"=>"6", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}

Relative Metric

{"start_date"=>"2010-01-01T00:00:00Z", "end_date"=>"2010-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[288, 576, 733, 867, 984, 1087, 1182, 1267, 1346, 1424, 1501, 1577, 1646, 1711, 1778, 1841, 1908, 1970, 2034, 2102, 2162, 2227, 2296, 2359, 2422, 2482, 2550, 2610, 2679, 2747, 2820, 2887, 2955, 3009, 3067, 3130, 3200, 3257, 3322, 3379, 3443, 3507, 3571, 3632, 3683, 3753, 3822, 3877]}, {"subject_area"=>"/Biology and life sciences/Cell biology", "average_usage"=>[280, 562, 725, 863, 974, 1083, 1177, 1268, 1347, 1421, 1489, 1570, 1638, 1706, 1763, 1823, 1890, 1951, 2016, 2076, 2134, 2192, 2257, 2319, 2378, 2438, 2501, 2572, 2634, 2700, 2759, 2825, 2887, 2936, 3007, 3070, 3121, 3184, 3237, 3304, 3363, 3425, 3484, 3531, 3612, 3663, 3718, 3771]}, {"subject_area"=>"/Biology and life sciences/Evolutionary biology", "average_usage"=>[342, 639, 812, 953, 1062, 1178, 1282, 1358, 1452, 1515, 1604, 1668, 1734, 1819, 1896, 1947, 2009, 2062, 2128, 2213, 2269, 2350, 2422, 2490, 2565, 2629, 2699, 2768, 2834, 2909, 2962, 3034, 3097, 3167, 3232, 3321, 3372, 3439, 3496, 3534, 3598, 3659, 3715, 3780, 3845, 3903, 3992, 4051, 4123]}, {"subject_area"=>"/Medicine and health sciences", "average_usage"=>[277, 558, 715, 845, 963, 1070, 1166, 1258, 1336, 1410, 1485, 1561, 1638, 1707, 1767, 1834, 1896, 1960, 2030, 2096, 2165, 2229, 2300, 2368, 2425, 2489, 2553, 2617, 2679, 2743, 2814, 2873, 2941, 2995, 3050, 3111, 3169, 3235, 3300, 3363, 3428, 3487, 3548, 3605, 3670, 3726, 3785, 3844]}]}
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