Approximation for Cooperative Interactions of a Spatially-Detailed Cardiac Sarcomere Model View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-12-28

AUTHORS

Takumi Washio, Jun-ichi Okada, Seiryo Sugiura, Toshiaki Hisada

ABSTRACT

We developed a novel ordinary differential equation (ODE) model, which produced results that correlated well with the Monte Carlo (MC) simulation when applied to a spatially-detailed model of the cardiac sarcomere. Configuration of the novel ODE model was based on the Ising model of myofilaments, with the "co-operative activation" effect introduced to incorporate nearest-neighbor interactions. First, a set of parameters was estimated using arbitrary Ca transient data to reproduce the combinational probability for the states of three consecutive regulatory units, using single unit probabilities for central and neighboring units in the MC simulation. The parameter set thus obtained enabled the calculation of the state transition of each unit using the ODE model with reference to the neighboring states. The present ODE model not only provided good agreement with the MC simulation results but was also capable of reproducing a wide range of experimental results under both steady-state and dynamic conditions including shortening twitch. The simulation results suggested that the nearest-neighbor interaction is a reasonable approximation of the cooperativity based on end-to-end interactions. Utilizing the modified ODE model resulted in a reduction in computational costs but maintained spatial integrity and co-operative effects, making it a powerful tool in cardiac modeling. More... »

PAGES

113-126

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12195-011-0219-2

DOI

http://dx.doi.org/10.1007/s12195-011-0219-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1008451149

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22448201


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/09", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0903", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biomedical Engineering", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Graduate School of Frontier Sciences, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba 277-0882 Japan", 
          "id": "http://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Graduate School of Frontier Sciences, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba 277-0882 Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Washio", 
        "givenName": "Takumi", 
        "id": "sg:person.01163254214.58", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163254214.58"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Graduate School of Frontier Sciences, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba 277-0882 Japan", 
          "id": "http://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Graduate School of Frontier Sciences, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba 277-0882 Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Okada", 
        "givenName": "Jun-ichi", 
        "id": "sg:person.01220732456.98", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01220732456.98"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Graduate School of Frontier Sciences, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033 Japan", 
          "id": "http://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Graduate School of Frontier Sciences, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033 Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sugiura", 
        "givenName": "Seiryo", 
        "id": "sg:person.01277502614.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01277502614.69"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Graduate School of Frontier Sciences, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033 Japan", 
          "id": "http://www.grid.ac/institutes/grid.26999.3d", 
          "name": [
            "Graduate School of Frontier Sciences, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033 Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hisada", 
        "givenName": "Toshiaki", 
        "id": "sg:person.01231367414.61", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01231367414.61"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1134/s0006350909010072", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047568612", 
          "https://doi.org/10.1134/s0006350909010072"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2011-12-28", 
    "datePublishedReg": "2011-12-28", 
    "description": "We developed a novel ordinary differential equation (ODE) model, which produced results that correlated well with the Monte Carlo (MC) simulation when applied to a spatially-detailed model of the cardiac sarcomere. Configuration of the novel ODE model was based on the Ising model of myofilaments, with the \"co-operative activation\" effect introduced to incorporate nearest-neighbor interactions. First, a set of parameters was estimated using arbitrary Ca transient data to reproduce the combinational probability for the states of three consecutive regulatory units, using single unit probabilities for central and neighboring units in the MC simulation. The parameter set thus obtained enabled the calculation of the state transition of each unit using the ODE model with reference to the neighboring states. The present ODE model not only provided good agreement with the MC simulation results but was also capable of reproducing a wide range of experimental results under both steady-state and dynamic conditions including shortening twitch. The simulation results suggested that the nearest-neighbor interaction is a reasonable approximation of the cooperativity based on end-to-end interactions. Utilizing the modified ODE model resulted in a reduction in computational costs but maintained spatial integrity and co-operative effects, making it a powerful tool in cardiac modeling.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/s12195-011-0219-2", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1039755", 
        "issn": [
          "1865-5025", 
          "1865-5033"
        ], 
        "name": "Cellular and Molecular Bioengineering", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "5"
      }
    ], 
    "keywords": [
      "ODE model", 
      "nearest-neighbor interactions", 
      "ordinary differential equation model", 
      "differential equation model", 
      "novel ordinary differential equation model", 
      "Monte Carlo simulations", 
      "Ising model", 
      "simulation results", 
      "MC simulation results", 
      "set of parameters", 
      "computational cost", 
      "Carlo simulations", 
      "MC simulations", 
      "reasonable approximation", 
      "cardiac modeling", 
      "approximation", 
      "detailed model", 
      "transient data", 
      "equation model", 
      "state transitions", 
      "good agreement", 
      "simulations", 
      "powerful tool", 
      "model", 
      "neighboring units", 
      "parameters", 
      "experimental results", 
      "wide range", 
      "probability", 
      "calculations", 
      "modeling", 
      "end interactions", 
      "set", 
      "state", 
      "results", 
      "transition", 
      "co-operative effect", 
      "agreement", 
      "configuration", 
      "dynamic conditions", 
      "interaction", 
      "co-operative activation", 
      "neighboring states", 
      "tool", 
      "conditions", 
      "cost", 
      "range", 
      "units", 
      "reference", 
      "effect", 
      "data", 
      "single unit", 
      "regulatory unit", 
      "cooperative interactions", 
      "end", 
      "reduction", 
      "spatial integrity", 
      "cooperativity", 
      "integrity", 
      "sarcomeres", 
      "cardiac sarcomere", 
      "myofilaments", 
      "twitch", 
      "activation", 
      "novel ODE model", 
      "arbitrary Ca transient data", 
      "Ca transient data", 
      "combinational probability", 
      "consecutive regulatory units", 
      "present ODE model", 
      "Spatially-Detailed Cardiac Sarcomere Model", 
      "Cardiac Sarcomere Model", 
      "Sarcomere Model"
    ], 
    "name": "Approximation for Cooperative Interactions of a Spatially-Detailed Cardiac Sarcomere Model", 
    "pagination": "113-126", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1008451149"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12195-011-0219-2"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "22448201"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12195-011-0219-2", 
      "https://app.dimensions.ai/details/publication/pub.1008451149"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-01-01T18:25", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/article/article_548.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/s12195-011-0219-2"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s12195-011-0219-2'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s12195-011-0219-2'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12195-011-0219-2'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12195-011-0219-2'


 

This table displays all metadata directly associated to this object as RDF triples.

162 TRIPLES      22 PREDICATES      100 URIs      91 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12195-011-0219-2 schema:about anzsrc-for:09
2 anzsrc-for:0903
3 schema:author Nfcc94e8ad9d847c79c2e777faf5c042e
4 schema:citation sg:pub.10.1134/s0006350909010072
5 schema:datePublished 2011-12-28
6 schema:datePublishedReg 2011-12-28
7 schema:description We developed a novel ordinary differential equation (ODE) model, which produced results that correlated well with the Monte Carlo (MC) simulation when applied to a spatially-detailed model of the cardiac sarcomere. Configuration of the novel ODE model was based on the Ising model of myofilaments, with the "co-operative activation" effect introduced to incorporate nearest-neighbor interactions. First, a set of parameters was estimated using arbitrary Ca transient data to reproduce the combinational probability for the states of three consecutive regulatory units, using single unit probabilities for central and neighboring units in the MC simulation. The parameter set thus obtained enabled the calculation of the state transition of each unit using the ODE model with reference to the neighboring states. The present ODE model not only provided good agreement with the MC simulation results but was also capable of reproducing a wide range of experimental results under both steady-state and dynamic conditions including shortening twitch. The simulation results suggested that the nearest-neighbor interaction is a reasonable approximation of the cooperativity based on end-to-end interactions. Utilizing the modified ODE model resulted in a reduction in computational costs but maintained spatial integrity and co-operative effects, making it a powerful tool in cardiac modeling.
8 schema:genre article
9 schema:inLanguage en
10 schema:isAccessibleForFree true
11 schema:isPartOf N425ddb0cd5c743f68419d58fa7633d86
12 N70d702a04dcf41d3bfae9ab8079a3d85
13 sg:journal.1039755
14 schema:keywords Ca transient data
15 Cardiac Sarcomere Model
16 Carlo simulations
17 Ising model
18 MC simulation results
19 MC simulations
20 Monte Carlo simulations
21 ODE model
22 Sarcomere Model
23 Spatially-Detailed Cardiac Sarcomere Model
24 activation
25 agreement
26 approximation
27 arbitrary Ca transient data
28 calculations
29 cardiac modeling
30 cardiac sarcomere
31 co-operative activation
32 co-operative effect
33 combinational probability
34 computational cost
35 conditions
36 configuration
37 consecutive regulatory units
38 cooperative interactions
39 cooperativity
40 cost
41 data
42 detailed model
43 differential equation model
44 dynamic conditions
45 effect
46 end
47 end interactions
48 equation model
49 experimental results
50 good agreement
51 integrity
52 interaction
53 model
54 modeling
55 myofilaments
56 nearest-neighbor interactions
57 neighboring states
58 neighboring units
59 novel ODE model
60 novel ordinary differential equation model
61 ordinary differential equation model
62 parameters
63 powerful tool
64 present ODE model
65 probability
66 range
67 reasonable approximation
68 reduction
69 reference
70 regulatory unit
71 results
72 sarcomeres
73 set
74 set of parameters
75 simulation results
76 simulations
77 single unit
78 spatial integrity
79 state
80 state transitions
81 tool
82 transient data
83 transition
84 twitch
85 units
86 wide range
87 schema:name Approximation for Cooperative Interactions of a Spatially-Detailed Cardiac Sarcomere Model
88 schema:pagination 113-126
89 schema:productId N109a02f24f574a478829829abd277fff
90 Nb92f24c171f6453e90d1546427c66a5b
91 Nec4f182e49154ff7b91c42f4349f4155
92 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008451149
93 https://doi.org/10.1007/s12195-011-0219-2
94 schema:sdDatePublished 2022-01-01T18:25
95 schema:sdLicense https://scigraph.springernature.com/explorer/license/
96 schema:sdPublisher Ne3919bdb6c1a4d02961c8168af7e74f1
97 schema:url https://doi.org/10.1007/s12195-011-0219-2
98 sgo:license sg:explorer/license/
99 sgo:sdDataset articles
100 rdf:type schema:ScholarlyArticle
101 N109a02f24f574a478829829abd277fff schema:name pubmed_id
102 schema:value 22448201
103 rdf:type schema:PropertyValue
104 N35aa834532f6436da5da9947b60bfdb0 rdf:first sg:person.01231367414.61
105 rdf:rest rdf:nil
106 N425ddb0cd5c743f68419d58fa7633d86 schema:issueNumber 1
107 rdf:type schema:PublicationIssue
108 N70d702a04dcf41d3bfae9ab8079a3d85 schema:volumeNumber 5
109 rdf:type schema:PublicationVolume
110 N89be3061d04b469cb8a7f322d0118cc1 rdf:first sg:person.01220732456.98
111 rdf:rest N9301f5fcc5a7420b95f198142c3a4f29
112 N9301f5fcc5a7420b95f198142c3a4f29 rdf:first sg:person.01277502614.69
113 rdf:rest N35aa834532f6436da5da9947b60bfdb0
114 Nb92f24c171f6453e90d1546427c66a5b schema:name dimensions_id
115 schema:value pub.1008451149
116 rdf:type schema:PropertyValue
117 Ne3919bdb6c1a4d02961c8168af7e74f1 schema:name Springer Nature - SN SciGraph project
118 rdf:type schema:Organization
119 Nec4f182e49154ff7b91c42f4349f4155 schema:name doi
120 schema:value 10.1007/s12195-011-0219-2
121 rdf:type schema:PropertyValue
122 Nfcc94e8ad9d847c79c2e777faf5c042e rdf:first sg:person.01163254214.58
123 rdf:rest N89be3061d04b469cb8a7f322d0118cc1
124 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
125 schema:name Engineering
126 rdf:type schema:DefinedTerm
127 anzsrc-for:0903 schema:inDefinedTermSet anzsrc-for:
128 schema:name Biomedical Engineering
129 rdf:type schema:DefinedTerm
130 sg:journal.1039755 schema:issn 1865-5025
131 1865-5033
132 schema:name Cellular and Molecular Bioengineering
133 schema:publisher Springer Nature
134 rdf:type schema:Periodical
135 sg:person.01163254214.58 schema:affiliation grid-institutes:grid.26999.3d
136 schema:familyName Washio
137 schema:givenName Takumi
138 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01163254214.58
139 rdf:type schema:Person
140 sg:person.01220732456.98 schema:affiliation grid-institutes:grid.26999.3d
141 schema:familyName Okada
142 schema:givenName Jun-ichi
143 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01220732456.98
144 rdf:type schema:Person
145 sg:person.01231367414.61 schema:affiliation grid-institutes:grid.26999.3d
146 schema:familyName Hisada
147 schema:givenName Toshiaki
148 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01231367414.61
149 rdf:type schema:Person
150 sg:person.01277502614.69 schema:affiliation grid-institutes:grid.26999.3d
151 schema:familyName Sugiura
152 schema:givenName Seiryo
153 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01277502614.69
154 rdf:type schema:Person
155 sg:pub.10.1134/s0006350909010072 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047568612
156 https://doi.org/10.1134/s0006350909010072
157 rdf:type schema:CreativeWork
158 grid-institutes:grid.26999.3d schema:alternateName Graduate School of Frontier Sciences, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba 277-0882 Japan
159 Graduate School of Frontier Sciences, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033 Japan
160 schema:name Graduate School of Frontier Sciences, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa, Chiba 277-0882 Japan
161 Graduate School of Frontier Sciences, University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033 Japan
162 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...