Learning Theories Reveal Loss of Pancreatic Electrical Connectivity in Diabetes as an Adaptive Response
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{"title"=>"Learning Theories Reveal Loss of Pancreatic Electrical Connectivity in Diabetes as an Adaptive Response", "type"=>"journal", "authors"=>[{"first_name"=>"Pranay", "last_name"=>"Goel", "scopus_author_id"=>"57080879000"}, {"first_name"=>"Anita", "last_name"=>"Mehta", "scopus_author_id"=>"7402755085"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84881018902", "issn"=>"19326203", "pui"=>"369474095", "sgr"=>"84881018902", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"23936417", "doi"=>"10.1371/journal.pone.0070366", "arxiv"=>"arXiv:1307.0131v1"}, "id"=>"6eb25d99-4070-3d8a-8bed-16fd64a4bdbd", "abstract"=>"Cells of almost all solid tissues are connected with gap junctions which permit the direct transfer of ions and small molecules, integral to regulating coordinated function in the tissue. The pancreatic islets of Langerhans are responsible for secreting the hormone insulin in response to glucose stimulation. Gap junctions are the only electrical contacts between the beta-cells in the tissue of these excitable islets. It is generally believed that they are responsible for synchrony of the membrane voltage oscillations among beta-cells, and thereby pulsatility of insulin secretion. Most attempts to understand connectivity in islets are often interpreted, bottom-up, in terms of measurements of gap junctional conductance. This does not, however, explain systematic changes, such as a diminished junctional conductance in type 2 diabetes. We attempt to address this deficit via the model presented here, which is a learning theory of gap junctional adaptation derived with analogy to neural systems. Here, gap junctions are modelled as bonds in a beta-cell network, that are altered according to homeostatic rules of plasticity. Our analysis reveals that it is nearly impossible to view gap junctions as homogeneous across a tissue. A modified view that accommodates heterogeneity of junction strengths in the islet can explain why, for example, a loss of gap junction conductance in diabetes is necessary for an increase in plasma insulin levels following hyperglycemia.", "link"=>"http://www.mendeley.com/research/learning-theories-reveal-loss-pancreatic-electrical-connectivity-diabetes-adaptive-response", "reader_count"=>24, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>3, "Librarian"=>2, "Researcher"=>4, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Student > Master"=>2, "Other"=>1, "Student > Bachelor"=>2}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>3, "Librarian"=>2, "Researcher"=>4, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>1, "Student > Master"=>2, "Other"=>1, "Student > Bachelor"=>2}, "reader_count_by_subject_area"=>{"Engineering"=>5, "Biochemistry, Genetics and Molecular Biology"=>3, "Materials Science"=>1, "Mathematics"=>1, "Agricultural and Biological Sciences"=>6, "Medicine and Dentistry"=>3, "Physics and Astronomy"=>3, "Computer Science"=>1, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>5}, "Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Physics and Astronomy"=>{"Physics and Astronomy"=>3}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>6}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}, "Mathematics"=>{"Mathematics"=>1}}, "reader_count_by_country"=>{"United Kingdom"=>1, "Portugal"=>1}, "group_count"=>0}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1140271"], "description"=>"<p>Figure credit: Mariana Ruiz LadyofHats, <a href=\"http://en.wikipedia.org/wiki/File:Gap_cell_junction_en.svg\" target=\"_blank\">http://en.wikipedia.org/wiki/File:Gap_cell_junction_en.svg</a>.</p>", "links"=>[], "tags"=>["Computing methods", "Mathematical computing", "Applied mathematics", "game theory", "Nonlinear dynamics", "Endocrinology", "Diabetic endocrinology", "Diabetes mellitus type 2", "Gastroenterology and hepatology", "pancreas", "Statistical mechanics", "junctions", "cells", "intercellular"], "article_id"=>762292, "categories"=>["Information And Computing Sciences", "Mathematics", "Medicine", "Physics"], "users"=>["Pranay Goel", "Anita Mehta"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0070366.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Gap_junctions_between_cells_permit_intercellular_communication_/762292", "title"=>"Gap junctions between cells permit intercellular communication.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-01 04:06:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/1140272"], "description"=>"<p>Steady-state junctional currents from HeLa-Cx36 cell pairs indicate conductance, , varies with transjunctional potential difference, . If two neighboring coupled cells fire nearly together, or do not simultaneously fire, trans-junctional conductance is high, but when one fires and the other does not conductance is low. This compensatory behavior inspires our <i>homeostatic</i> learning rule, see text.</p>", "links"=>[], "tags"=>["Computing methods", "Mathematical computing", "Applied mathematics", "game theory", "Nonlinear dynamics", "Endocrinology", "Diabetic endocrinology", "Diabetes mellitus type 2", "Gastroenterology and hepatology", "pancreas", "Statistical mechanics", "gating", "cx36", "adapted"], "article_id"=>762293, "categories"=>["Information And Computing Sciences", "Mathematics", "Medicine", "Physics"], "users"=>["Pranay Goel", "Anita Mehta"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0070366.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Voltage_gating_of_Cx36_gap_junctions_adapted_from_32_/762293", "title"=>"Voltage gating of Cx36 gap junctions, adapted from [32].", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-01 04:06:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/1140273"], "description"=>"<p>-cells, A and B, are dominated by gap junctions and respectively. Each junction ( and ) can be in either strong (with probability ) or weak state (with probability ). A weak (strong) junction is likely to fire with a probability (). The central gap junction is altered in response to the average potential difference of cells A and B, , across it, according to a specified learning rule, such as the homeostatic rule of Fig. 2 that is considered here. For example, if cell A (red) here is assumed to fire in response to a strong (this occurs with probability ) while cell B is silent (the probability with which it could have been active is ) in response to a weak , then the bond, g, will be weakened since .</p>", "links"=>[], "tags"=>["Computing methods", "Mathematical computing", "Applied mathematics", "game theory", "Nonlinear dynamics", "Endocrinology", "Diabetic endocrinology", "Diabetes mellitus type 2", "Gastroenterology and hepatology", "pancreas", "Statistical mechanics", "bonds", "formalism"], "article_id"=>762294, "categories"=>["Information And Computing Sciences", "Mathematics", "Medicine", "Physics"], "users"=>["Pranay Goel", "Anita Mehta"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0070366.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_bonds_formalism_of_an_islet_/762294", "title"=>"The bonds formalism of an islet.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-01 04:06:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/1140274"], "description"=>"<p>The physically relevant () region is the triangle ABC above the line . along BD, . The region near A where is close to 1 represents healthy individuals while diabetics are assumed to lie along BD where .</p>", "links"=>[], "tags"=>["Computing methods", "Mathematical computing", "Applied mathematics", "game theory", "Nonlinear dynamics", "Endocrinology", "Diabetic endocrinology", "Diabetes mellitus type 2", "Gastroenterology and hepatology", "pancreas", "Statistical mechanics", "contour"], "article_id"=>762295, "categories"=>["Information And Computing Sciences", "Mathematics", "Medicine", "Physics"], "users"=>["Pranay Goel", "Anita Mehta"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0070366.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_contour_plot_in_the__plane_/762295", "title"=>"The contour plot in the – plane.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-01 04:06:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/1140275"], "description"=>"<p>Beta-cells were initialized as firing (1) or not (0), and gap junctions as weak (0) or strong (1) with equal probability. 5000 beta-cell–gap junction pairs (Fig. 3) were iterated according to the learning rules described in the text. The legend indicates the () values for a computation. The top panel shows the evolution of the fraction of strong gap junctions, , in the network. The bottom panel shows the corresponding fraction of beta-cells that are active. Note that as well as firing rate in the simulation are both 0.5 along as expected from the theory, Fig. 4. A transition from health with low firing and high proportion of strong gap junctions (black curves) to diabetes takes place with degrading the gap junctions to increase firing rates (red curves).</p>", "links"=>[], "tags"=>["Computing methods", "Mathematical computing", "Applied mathematics", "game theory", "Nonlinear dynamics", "Endocrinology", "Diabetic endocrinology", "Diabetes mellitus type 2", "Gastroenterology and hepatology", "pancreas", "Statistical mechanics", "junctions"], "article_id"=>762296, "categories"=>["Information And Computing Sciences", "Mathematics", "Medicine", "Physics"], "users"=>["Pranay Goel", "Anita Mehta"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0070366.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolution_of_gap_junctions_with_network_activity_/762296", "title"=>"Evolution of gap junctions with network activity.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-01 04:06:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/1140276"], "description"=>"<p>The probability of a gap junction adapting to a strong, high conductance state is determined by the current state of the bonds and (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0070366#pone-0070366-g003\" target=\"_blank\">Fig. 3</a>).</p>", "links"=>[], "tags"=>["Computing methods", "Mathematical computing", "Applied mathematics", "game theory", "Nonlinear dynamics", "Endocrinology", "Diabetic endocrinology", "Diabetes mellitus type 2", "Gastroenterology and hepatology", "pancreas", "Statistical mechanics", "probability", "junction", "adapting", "conductance", "bonds"], "article_id"=>762297, "categories"=>["Information And Computing Sciences", "Mathematics", "Medicine", "Physics"], "users"=>["Pranay Goel", "Anita Mehta"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0070366.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_probability_of_a_gap_junction_adapting_to_a_strong_high_conductance_state_is_determined_by_the_current_state_of_the_bonds_and_Fig_3_/762297", "title"=>"The probability of a gap junction adapting to a strong, high conductance state is determined by the current state of the bonds and (Fig. 3).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-08-01 04:06:59"}

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  • {"unique-ip"=>"3", "full-text"=>"2", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"6"}
  • {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"9"}

Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[269, 466, 588, 697, 800, 896, 988, 1076, 1165, 1254, 1340, 1417]}, {"subject_area"=>"/Biology and life sciences/Anatomy and physiology", "average_usage"=>[256, 428]}, {"subject_area"=>"/Biology and life sciences/Biochemistry", "average_usage"=>[266, 468, 593, 703, 804, 903, 993, 1084, 1171, 1256, 1339, 1422, 1492]}, {"subject_area"=>"/Biology and life sciences/Neuroscience", "average_usage"=>[261, 444, 554, 655, 748, 834, 923, 1004, 1089, 1170, 1244, 1315, 1380]}, {"subject_area"=>"/Biology and life sciences/Physiology", "average_usage"=>[256, 449, 572, 676, 775, 866, 955, 1041, 1127, 1213, 1290, 1370, 1437]}, {"subject_area"=>"/Ecology and environmental sciences", "average_usage"=>[284, 475, 603, 722, 826, 928, 1026, 1129, 1225, 1310, 1390, 1468, 1549]}, {"subject_area"=>"/Ecology and environmental sciences/Fires", "average_usage"=>[221, 360]}, {"subject_area"=>"/Ecology and environmental sciences/Wildfires", "average_usage"=>[221, 352, 400, 481, 536, 649, 733, 777, 831, 909, 1013, 1067, 1115, 1154]}, {"subject_area"=>"/Medicine and health sciences", "average_usage"=>[264, 460, 584, 692, 794, 887, 978, 1067, 1154, 1241, 1328, 1408, 1474]}, {"subject_area"=>"/Medicine and health sciences/Metabolic disorders", "average_usage"=>[254, 466, 587, 690, 790, 885, 983, 1063, 1139, 1216, 1297, 1373, 1442]}, {"subject_area"=>"/Physical sciences", "average_usage"=>[254, 431, 547, 651, 748, 842, 932, 1017, 1098, 1178, 1259, 1336, 1404]}, {"subject_area"=>"/Physical sciences/Chemistry", "average_usage"=>[247, 429, 544, 647, 747, 842, 929, 1012, 1099, 1179, 1263, 1339, 1409]}]}
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