Conservation of total synaptic weight through balanced synaptic depression and potentiation View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2003-04

AUTHORS

Sébastien Royer, Denis Paré

ABSTRACT

Memory is believed to depend on activity-dependent changes in the strength of synapses1. In part, this view is based on evidence that the efficacy of synapses can be enhanced or depressed depending on the timing of pre- and postsynaptic activity2,3,4,5. However, when such plastic synapses are incorporated into neural network models, stability problems may develop because the potentiation or depression of synapses increases the likelihood that they will be further strengthened or weakened6. Here we report biological evidence for a homeostatic mechanism that reconciles the apparently opposite requirements of plasticity and stability. We show that, in intercalated neurons of the amygdala, activity-dependent potentiation or depression of particular glutamatergic inputs leads to opposite changes in the strength of inputs ending at other dendritic sites. As a result, little change in total synaptic weight occurs, even though the relative strength of inputs is modified. Furthermore, hetero- but not homosynaptic alterations are blocked by intracellular dialysis of drugs that prevent Ca2+ release from intracellular stores. Thus, in intercalated neurons at least, inverse heterosynaptic plasticity tends to compensate for homosynaptic long-term potentiation and depression, thus stabilizing total synaptic weight. More... »

PAGES

518-522

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nature01530

DOI

http://dx.doi.org/10.1038/nature01530

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018642805

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/12673250


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/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1109", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Neurosciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Amygdala", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Animals", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Calcium", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Excitatory Postsynaptic Potentials", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Guinea Pigs", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "In Vitro Techniques", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Long-Term Potentiation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Membrane Potentials", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Memory", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Neuronal Plasticity", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Synapses", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Behavioral Neuroscience, Rutgers State University, 197 University Avenue", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Center for Molecular & Behavioral Neuroscience, Rutgers State University, 197 University Avenue, 07102, Newark, New Jersey, USA", 
            "Behavioral Neuroscience, Rutgers State University, 197 University Avenue"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Royer", 
        "givenName": "S\u00e9bastien", 
        "id": "sg:person.07664077545.65", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07664077545.65"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Behavioral Neuroscience, Rutgers State University, 197 University Avenue", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Center for Molecular & Behavioral Neuroscience, Rutgers State University, 197 University Avenue, 07102, Newark, New Jersey, USA", 
            "Behavioral Neuroscience, Rutgers State University, 197 University Avenue"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Par\u00e9", 
        "givenName": "Denis", 
        "id": "sg:person.01257456553.12", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01257456553.12"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/266737a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003287611", 
          "https://doi.org/10.1038/266737a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/78829", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009745377", 
          "https://doi.org/10.1038/78829"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/361031a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042608618", 
          "https://doi.org/10.1038/361031a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35046067", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036201169", 
          "https://doi.org/10.1038/35046067"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/81453", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001869026", 
          "https://doi.org/10.1038/81453"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35081514", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025356716", 
          "https://doi.org/10.1038/35081514"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/380446a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050727319", 
          "https://doi.org/10.1038/380446a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/382807a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011717289", 
          "https://doi.org/10.1038/382807a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35072500", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001709602", 
          "https://doi.org/10.1038/35072500"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2003-04", 
    "datePublishedReg": "2003-04-01", 
    "description": "Memory is believed to depend on activity-dependent changes in the strength of synapses1. In part, this view is based on evidence that the efficacy of synapses can be enhanced or depressed depending on the timing of pre- and postsynaptic activity2,3,4,5. However, when such plastic synapses are incorporated into neural network models, stability problems may develop because the potentiation or depression of synapses increases the likelihood that they will be further strengthened or weakened6. Here we report biological evidence for a homeostatic mechanism that reconciles the apparently opposite requirements of plasticity and stability. We show that, in intercalated neurons of the amygdala, activity-dependent potentiation or depression of particular glutamatergic inputs leads to opposite changes in the strength of inputs ending at other dendritic sites. As a result, little change in total synaptic weight occurs, even though the relative strength of inputs is modified. Furthermore, hetero- but not homosynaptic alterations are blocked by intracellular dialysis of drugs that prevent Ca2+ release from intracellular stores. Thus, in intercalated neurons at least, inverse heterosynaptic plasticity tends to compensate for homosynaptic long-term potentiation and depression, thus stabilizing total synaptic weight.", 
    "genre": "article", 
    "id": "sg:pub.10.1038/nature01530", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1018957", 
        "issn": [
          "0028-0836", 
          "1476-4687"
        ], 
        "name": "Nature", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "6931", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "422"
      }
    ], 
    "keywords": [
      "total synaptic weight", 
      "homosynaptic long-term potentiation", 
      "activity-dependent potentiation", 
      "long-term potentiation", 
      "activity-dependent changes", 
      "depression of synapses", 
      "efficacy of synapses", 
      "glutamatergic inputs", 
      "intercalated neurons", 
      "dendritic sites", 
      "intracellular dialysis", 
      "synaptic depression", 
      "strength of input", 
      "intracellular stores", 
      "timing of pre", 
      "potentiation", 
      "homeostatic mechanisms", 
      "depression", 
      "synapses", 
      "heterosynaptic plasticity", 
      "neurons", 
      "opposite changes", 
      "plastic synapses", 
      "biological evidence", 
      "amygdala", 
      "synaptic weights", 
      "weight", 
      "dialysis", 
      "drugs", 
      "evidence", 
      "efficacy", 
      "plasticity", 
      "little change", 
      "alterations", 
      "changes", 
      "pre", 
      "Ca2", 
      "release", 
      "likelihood", 
      "timing", 
      "stores", 
      "mechanism", 
      "sites", 
      "memory", 
      "results", 
      "part", 
      "strength", 
      "model", 
      "input", 
      "view", 
      "relative strength", 
      "hetero", 
      "opposite requirements", 
      "requirements", 
      "problem", 
      "stability", 
      "neural network model", 
      "network model", 
      "conservation", 
      "stability problem"
    ], 
    "name": "Conservation of total synaptic weight through balanced synaptic depression and potentiation", 
    "pagination": "518-522", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1018642805"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/nature01530"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "12673250"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/nature01530", 
      "https://app.dimensions.ai/details/publication/pub.1018642805"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-10-01T06:32", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20221001/entities/gbq_results/article/article_377.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1038/nature01530"
  }
]
 

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.10.1038/nature01530'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/nature01530'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/nature01530'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/nature01530'


 

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

209 TRIPLES      21 PREDICATES      106 URIs      89 LITERALS      18 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/nature01530 schema:about N003827a315a54b1d80e84467fc574f26
2 N290c4f2bf6fe4dca848ae810051cf842
3 N3a2593a39d5743758816a36097909cb6
4 N51701f986360414299e92e7e9077d71c
5 N69d0270521a6493c850d24a5262cd876
6 N91117496768f400b924cb9db117b1eb5
7 Na876ad22f20743fba2a47d14d2623cec
8 Na8cd5fa81e8c4115954764d0bbd6271c
9 Nbeb228fd417a45fcb68d1ec673cf2686
10 Nc34d34a882ae45c5a996a573f94668fa
11 Nc9effa99f44b4e38aa4e49c611661369
12 anzsrc-for:11
13 anzsrc-for:1109
14 schema:author N1efd774ad4db44fc94570036770524e2
15 schema:citation sg:pub.10.1038/266737a0
16 sg:pub.10.1038/35046067
17 sg:pub.10.1038/35072500
18 sg:pub.10.1038/35081514
19 sg:pub.10.1038/361031a0
20 sg:pub.10.1038/380446a0
21 sg:pub.10.1038/382807a0
22 sg:pub.10.1038/78829
23 sg:pub.10.1038/81453
24 schema:datePublished 2003-04
25 schema:datePublishedReg 2003-04-01
26 schema:description Memory is believed to depend on activity-dependent changes in the strength of synapses1. In part, this view is based on evidence that the efficacy of synapses can be enhanced or depressed depending on the timing of pre- and postsynaptic activity2,3,4,5. However, when such plastic synapses are incorporated into neural network models, stability problems may develop because the potentiation or depression of synapses increases the likelihood that they will be further strengthened or weakened6. Here we report biological evidence for a homeostatic mechanism that reconciles the apparently opposite requirements of plasticity and stability. We show that, in intercalated neurons of the amygdala, activity-dependent potentiation or depression of particular glutamatergic inputs leads to opposite changes in the strength of inputs ending at other dendritic sites. As a result, little change in total synaptic weight occurs, even though the relative strength of inputs is modified. Furthermore, hetero- but not homosynaptic alterations are blocked by intracellular dialysis of drugs that prevent Ca2+ release from intracellular stores. Thus, in intercalated neurons at least, inverse heterosynaptic plasticity tends to compensate for homosynaptic long-term potentiation and depression, thus stabilizing total synaptic weight.
27 schema:genre article
28 schema:isAccessibleForFree false
29 schema:isPartOf Na5b21ee14e9544af8ac74a11af78c124
30 Nbf25a1b82e084dc0bf599f225b0953ee
31 sg:journal.1018957
32 schema:keywords Ca2
33 activity-dependent changes
34 activity-dependent potentiation
35 alterations
36 amygdala
37 biological evidence
38 changes
39 conservation
40 dendritic sites
41 depression
42 depression of synapses
43 dialysis
44 drugs
45 efficacy
46 efficacy of synapses
47 evidence
48 glutamatergic inputs
49 hetero
50 heterosynaptic plasticity
51 homeostatic mechanisms
52 homosynaptic long-term potentiation
53 input
54 intercalated neurons
55 intracellular dialysis
56 intracellular stores
57 likelihood
58 little change
59 long-term potentiation
60 mechanism
61 memory
62 model
63 network model
64 neural network model
65 neurons
66 opposite changes
67 opposite requirements
68 part
69 plastic synapses
70 plasticity
71 potentiation
72 pre
73 problem
74 relative strength
75 release
76 requirements
77 results
78 sites
79 stability
80 stability problem
81 stores
82 strength
83 strength of input
84 synapses
85 synaptic depression
86 synaptic weights
87 timing
88 timing of pre
89 total synaptic weight
90 view
91 weight
92 schema:name Conservation of total synaptic weight through balanced synaptic depression and potentiation
93 schema:pagination 518-522
94 schema:productId N27b7d2f8057d40d7bd47a1e0f0d6303e
95 N78714c7513824116bc631d145fcbc520
96 Nbf51d85d80e2444e9b79570d84fce22c
97 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018642805
98 https://doi.org/10.1038/nature01530
99 schema:sdDatePublished 2022-10-01T06:32
100 schema:sdLicense https://scigraph.springernature.com/explorer/license/
101 schema:sdPublisher N55c92036d0c74b2e940fd7910fbc6b9d
102 schema:url https://doi.org/10.1038/nature01530
103 sgo:license sg:explorer/license/
104 sgo:sdDataset articles
105 rdf:type schema:ScholarlyArticle
106 N003827a315a54b1d80e84467fc574f26 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
107 schema:name Memory
108 rdf:type schema:DefinedTerm
109 N1efd774ad4db44fc94570036770524e2 rdf:first sg:person.07664077545.65
110 rdf:rest N68144b7ea0d74cd78815d14a3b2c8fa1
111 N27b7d2f8057d40d7bd47a1e0f0d6303e schema:name pubmed_id
112 schema:value 12673250
113 rdf:type schema:PropertyValue
114 N290c4f2bf6fe4dca848ae810051cf842 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Guinea Pigs
116 rdf:type schema:DefinedTerm
117 N3a2593a39d5743758816a36097909cb6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
118 schema:name Calcium
119 rdf:type schema:DefinedTerm
120 N51701f986360414299e92e7e9077d71c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
121 schema:name Synapses
122 rdf:type schema:DefinedTerm
123 N55c92036d0c74b2e940fd7910fbc6b9d schema:name Springer Nature - SN SciGraph project
124 rdf:type schema:Organization
125 N68144b7ea0d74cd78815d14a3b2c8fa1 rdf:first sg:person.01257456553.12
126 rdf:rest rdf:nil
127 N69d0270521a6493c850d24a5262cd876 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
128 schema:name Membrane Potentials
129 rdf:type schema:DefinedTerm
130 N78714c7513824116bc631d145fcbc520 schema:name doi
131 schema:value 10.1038/nature01530
132 rdf:type schema:PropertyValue
133 N91117496768f400b924cb9db117b1eb5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
134 schema:name Amygdala
135 rdf:type schema:DefinedTerm
136 Na5b21ee14e9544af8ac74a11af78c124 schema:issueNumber 6931
137 rdf:type schema:PublicationIssue
138 Na876ad22f20743fba2a47d14d2623cec schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
139 schema:name Animals
140 rdf:type schema:DefinedTerm
141 Na8cd5fa81e8c4115954764d0bbd6271c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
142 schema:name Neuronal Plasticity
143 rdf:type schema:DefinedTerm
144 Nbeb228fd417a45fcb68d1ec673cf2686 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
145 schema:name In Vitro Techniques
146 rdf:type schema:DefinedTerm
147 Nbf25a1b82e084dc0bf599f225b0953ee schema:volumeNumber 422
148 rdf:type schema:PublicationVolume
149 Nbf51d85d80e2444e9b79570d84fce22c schema:name dimensions_id
150 schema:value pub.1018642805
151 rdf:type schema:PropertyValue
152 Nc34d34a882ae45c5a996a573f94668fa schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
153 schema:name Excitatory Postsynaptic Potentials
154 rdf:type schema:DefinedTerm
155 Nc9effa99f44b4e38aa4e49c611661369 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
156 schema:name Long-Term Potentiation
157 rdf:type schema:DefinedTerm
158 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
159 schema:name Medical and Health Sciences
160 rdf:type schema:DefinedTerm
161 anzsrc-for:1109 schema:inDefinedTermSet anzsrc-for:
162 schema:name Neurosciences
163 rdf:type schema:DefinedTerm
164 sg:journal.1018957 schema:issn 0028-0836
165 1476-4687
166 schema:name Nature
167 schema:publisher Springer Nature
168 rdf:type schema:Periodical
169 sg:person.01257456553.12 schema:affiliation grid-institutes:None
170 schema:familyName Paré
171 schema:givenName Denis
172 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01257456553.12
173 rdf:type schema:Person
174 sg:person.07664077545.65 schema:affiliation grid-institutes:None
175 schema:familyName Royer
176 schema:givenName Sébastien
177 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07664077545.65
178 rdf:type schema:Person
179 sg:pub.10.1038/266737a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003287611
180 https://doi.org/10.1038/266737a0
181 rdf:type schema:CreativeWork
182 sg:pub.10.1038/35046067 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036201169
183 https://doi.org/10.1038/35046067
184 rdf:type schema:CreativeWork
185 sg:pub.10.1038/35072500 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001709602
186 https://doi.org/10.1038/35072500
187 rdf:type schema:CreativeWork
188 sg:pub.10.1038/35081514 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025356716
189 https://doi.org/10.1038/35081514
190 rdf:type schema:CreativeWork
191 sg:pub.10.1038/361031a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042608618
192 https://doi.org/10.1038/361031a0
193 rdf:type schema:CreativeWork
194 sg:pub.10.1038/380446a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050727319
195 https://doi.org/10.1038/380446a0
196 rdf:type schema:CreativeWork
197 sg:pub.10.1038/382807a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011717289
198 https://doi.org/10.1038/382807a0
199 rdf:type schema:CreativeWork
200 sg:pub.10.1038/78829 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009745377
201 https://doi.org/10.1038/78829
202 rdf:type schema:CreativeWork
203 sg:pub.10.1038/81453 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001869026
204 https://doi.org/10.1038/81453
205 rdf:type schema:CreativeWork
206 grid-institutes:None schema:alternateName Behavioral Neuroscience, Rutgers State University, 197 University Avenue
207 schema:name Behavioral Neuroscience, Rutgers State University, 197 University Avenue
208 Center for Molecular & Behavioral Neuroscience, Rutgers State University, 197 University Avenue, 07102, Newark, New Jersey, USA
209 rdf:type schema:Organization
 




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


...