Modeling Physiological Processes That Relate Toxicant Exposure and Bacterial Population Dynamics
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Figshare

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  • {"files"=>["https://ndownloader.figshare.com/files/685421"], "description"=>"<p>Bacteria assimilate substrate into energy reserves, which are utilized to fuel growth (linked to increase in cell concentration), maintenance and acclimation. Products related to respiration degrade the environment, reducing the ability of bacteria to utilize energy reserves. Both toxicants and degradation of the supernatant inhibit assimilation of the substrate, and absorbed toxicants bioaccumulate in bacterial cells. Toxicants in the cell, as well as the cell's own metabolism, increase aging acceleration (by creating damage-inducing compounds), thus increasing the hazard rate, and mortality.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "ecology", "marine and aquatic sciences", "Biochemistry", "mathematics"], "article_id"=>355905, "categories"=>["Inorganic Chemistry", "Biochemistry", "Mathematics", "Genetics", "Biological Sciences", "Ecology"], "users"=>["Tin Klanjscek", "Roger M. Nisbet", "John H. Priester", "Patricia A. Holden"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0026955.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Outline_of_the_model_/355905", "title"=>"Outline of the model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-06 01:38:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/685499"], "description"=>"<p>Cell concentration and all state variables of the model except acclimation and bioaccumulation (not applicable for control). Upper left corner: data (circles), best fit of the standard model (dotted line) and best fit of the model extended by including environmental degradation (solid line). See text for discussion.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "ecology", "marine and aquatic sciences", "Biochemistry", "mathematics"], "article_id"=>355983, "categories"=>["Inorganic Chemistry", "Biochemistry", "Mathematics", "Genetics", "Biological Sciences", "Ecology"], "users"=>["Tin Klanjscek", "Roger M. Nisbet", "John H. Priester", "Patricia A. Holden"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0026955.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulating_the_control_/355983", "title"=>"Simulating the control.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-06 01:39:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/685607"], "description"=>"<p>Best fit set of parameter values used (listed in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0026955#pone-0026955-t002\" target=\"_blank\">Table 2</a>). The inset is showing the first 5 hours of the experiment.</p>", "links"=>[], "tags"=>["treatments", "parameter"], "article_id"=>356097, "categories"=>["Inorganic Chemistry", "Biochemistry", "Mathematics", "Genetics", "Biological Sciences", "Ecology"], "users"=>["Tin Klanjscek", "Roger M. Nisbet", "John H. Priester", "Patricia A. Holden"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0026955.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulations_of_all_treatments_with_a_single_parameter_set_/356097", "title"=>"Simulations of all treatments with a single parameter set.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-06 01:41:37"}
  • {"files"=>["https://ndownloader.figshare.com/files/685695"], "description"=>"<p>Top panels show dependence of maximum growth rate (left) and time to maximum growth rate (right) calculated from the model (solid line) and measured by Priester <i>et al.</i> (2009 <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0026955#pone.0026955-Priester1\" target=\"_blank\">[20]</a>) (dotted line). Bottom left panel shows time to maximum energy density as a function of exposure concentration. Bottom right panel shows growth rates for all treatments during the first 30 hours of the experiment.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "ecology", "marine and aquatic sciences", "Biochemistry", "mathematics"], "article_id"=>356179, "categories"=>["Inorganic Chemistry", "Biochemistry", "Mathematics", "Genetics", "Biological Sciences", "Ecology"], "users"=>["Tin Klanjscek", "Roger M. Nisbet", "John H. Priester", "Patricia A. Holden"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0026955.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overview_of_population_dynamics_/356179", "title"=>"Overview of population dynamics.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-06 01:42:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/685776"], "description"=>"<p>Top: aging acceleration (left), and acclimation (right) for select (see legend) treatments. Bottom: aging acceleration for all treatments at 12, 15, and 24 hours (left), and comparison between scaled measured ROS and predicted aging acceleration (right).</p>", "links"=>[], "tags"=>["aging"], "article_id"=>356271, "categories"=>["Inorganic Chemistry", "Biochemistry", "Mathematics", "Genetics", "Biological Sciences", "Ecology"], "users"=>["Tin Klanjscek", "Roger M. Nisbet", "John H. Priester", "Patricia A. Holden"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0026955.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dynamics_of_aging_acceleration_/356271", "title"=>"Dynamics of aging acceleration.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-06 01:44:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/685868"], "description"=>"<p>Exposures of 37.5, 75, 115, and 150 mg/L predicted using fits only of data on control and low exposures (10 and 20 mg/L). Data points marked with ‘x’: data used in fitting; ‘o’: data used for comparison only. Dashed line: fitted treatments (, , , and ). Solid line: predicted treatments.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "ecology", "marine and aquatic sciences", "Biochemistry", "mathematics"], "article_id"=>356352, "categories"=>["Inorganic Chemistry", "Biochemistry", "Mathematics", "Genetics", "Biological Sciences", "Ecology"], "users"=>["Tin Klanjscek", "Roger M. Nisbet", "John H. Priester", "Patricia A. Holden"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0026955.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predicting_high_exposures_/356352", "title"=>"Predicting high exposures.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-06 01:45:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/685963"], "description"=>"<p>Bacterial production rate and scaled functional response () are not state variables, but have been defined separately for brevity. Non-dimensional variables have been labeled ‘n.d.’. Subscript ‘+’ signifies that only positive values of the expression are considered, with the expression set to zero if its value turns out to be negative.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "ecology", "marine and aquatic sciences", "Biochemistry", "mathematics"], "article_id"=>356444, "categories"=>["Inorganic Chemistry", "Biochemistry", "Mathematics", "Genetics", "Biological Sciences", "Ecology"], "users"=>["Tin Klanjscek", "Roger M. Nisbet", "John H. Priester", "Patricia A. Holden"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0026955.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_state_variables_units_and_dynamic_equations_/356444", "title"=>"Summary of state variables, units, and dynamic equations.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-06 01:47:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/685984"], "description"=>"<p>Concentration denotes an amount of per volume of substrate, density denotes an amount per structural volume of bacteria, and n.d. stands for ‘non-dimensional’. Coefficient scales initial substrate C-mol concentration to unity, and structural cell C-mol to calibrated optical density.</p>", "links"=>[], "tags"=>["fitted"], "article_id"=>356476, "categories"=>["Inorganic Chemistry", "Biochemistry", "Mathematics", "Genetics", "Biological Sciences", "Ecology"], "users"=>["Tin Klanjscek", "Roger M. Nisbet", "John H. Priester", "Patricia A. Holden"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0026955.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Parameters_units_and_fitted_values_/356476", "title"=>"Parameters, units, and fitted values.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-06 01:47:56"}

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Relative Metric

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