TMT-based quantitative proteomic profiling of human monocyte-derived macrophages and foam cells View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2022-01-03

AUTHORS

Yali Zhang, Yu Fu, Linying Jia, Chenyang Zhang, Wenbin Cao, Naqash Alam, Rong Wang, Weirong Wang, Liang Bai, Sihai Zhao, Enqi Liu

ABSTRACT

BackgroundCardiovascular diseases remain the leading cause of morbidity and mortality worldwide, most of which are caused by atherosclerosis. Discerning processes that participate in macrophage-to-foam cell formation are critical for understanding the basic mechanisms underlying atherosclerosis. To explore the molecular mechanisms of foam cell formation, differentially expressed proteins were identified.MethodsHuman peripheral blood mononuclear cells were stimulated with macrophage colony-stimulating factor, and obtained macrophages were transformed into foam cells by oxidized low-density lipoprotein. Tandem mass tag (TMT) labeling combined with mass spectrometry was performed to find associations between foam cell transformation and proteome profiles.ResultsTotally, 5146 quantifiable proteins were identified, among which 1515 and 182 differentially expressed proteins (DEPs) were found in macrophage/monocyte and foam cell/macrophage, respectively. Subcellular localization analysis revealed that downregulated DEPs of macrophages/monocytes were mostly located in the nucleus, whereas upregulated DEPs of foam cells/macrophages were mostly extracellular or located in the plasma membrane. Functional analysis of DEPs demonstrated that cholesterol metabolism-related proteins were upregulated in foam cells, whereas immune response-related proteins were downregulated in foam cells. The protein interaction network showed that the DEPs with the highest interaction scores between macrophages and foam cells were mainly concentrated in lysosomes and the endoplasmic reticulum.ConclusionsProteomics analysis suggested that cholesterol metabolism was upregulated, while the immune response was suppressed in foam cells. KEGG enrichment analysis and protein-protein interaction analysis indicated that DEPs located in the endoplasmic reticulum and lysosomes might be key drivers of foam cell formation. These data provide a basis for identifying the potential proteins associated with the molecular mechanism underlying macrophage transformation to foam cells. More... »

PAGES

1

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12953-021-00183-x

DOI

http://dx.doi.org/10.1186/s12953-021-00183-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1144373097

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/34980145


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/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0601", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biochemistry and Cell Biology", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Research Institute of Atherosclerotic Disease, Xi\u2019an Jiaotong University Cardiovascular Research Centre, No. 76, Yanta West Road, 710061, Xi\u2019an, Shaanxi, China", 
            "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Yali", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fu", 
        "givenName": "Yu", 
        "id": "sg:person.010133623605.74", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010133623605.74"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Research Institute of Atherosclerotic Disease, Xi\u2019an Jiaotong University Cardiovascular Research Centre, No. 76, Yanta West Road, 710061, Xi\u2019an, Shaanxi, China", 
            "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Jia", 
        "givenName": "Linying", 
        "id": "sg:person.016224625372.09", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016224625372.09"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Research Institute of Atherosclerotic Disease, Xi\u2019an Jiaotong University Cardiovascular Research Centre, No. 76, Yanta West Road, 710061, Xi\u2019an, Shaanxi, China", 
            "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhang", 
        "givenName": "Chenyang", 
        "id": "sg:person.015427244772.06", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015427244772.06"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Research Institute of Atherosclerotic Disease, Xi\u2019an Jiaotong University Cardiovascular Research Centre, No. 76, Yanta West Road, 710061, Xi\u2019an, Shaanxi, China", 
            "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cao", 
        "givenName": "Wenbin", 
        "id": "sg:person.015672426353.09", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015672426353.09"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Research Institute of Atherosclerotic Disease, Xi\u2019an Jiaotong University Cardiovascular Research Centre, No. 76, Yanta West Road, 710061, Xi\u2019an, Shaanxi, China", 
            "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Alam", 
        "givenName": "Naqash", 
        "id": "sg:person.012123611207.85", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012123611207.85"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Research Institute of Atherosclerotic Disease, Xi\u2019an Jiaotong University Cardiovascular Research Centre, No. 76, Yanta West Road, 710061, Xi\u2019an, Shaanxi, China", 
            "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Rong", 
        "id": "sg:person.01006540224.36", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01006540224.36"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Research Institute of Atherosclerotic Disease, Xi\u2019an Jiaotong University Cardiovascular Research Centre, No. 76, Yanta West Road, 710061, Xi\u2019an, Shaanxi, China", 
            "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Wang", 
        "givenName": "Weirong", 
        "id": "sg:person.01264216545.46", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01264216545.46"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Research Institute of Atherosclerotic Disease, Xi\u2019an Jiaotong University Cardiovascular Research Centre, No. 76, Yanta West Road, 710061, Xi\u2019an, Shaanxi, China", 
            "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bai", 
        "givenName": "Liang", 
        "id": "sg:person.0707217075.15", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0707217075.15"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Research Institute of Atherosclerotic Disease, Xi\u2019an Jiaotong University Cardiovascular Research Centre, No. 76, Yanta West Road, 710061, Xi\u2019an, Shaanxi, China", 
            "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhao", 
        "givenName": "Sihai", 
        "id": "sg:person.01217761561.81", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01217761561.81"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China", 
          "id": "http://www.grid.ac/institutes/grid.43169.39", 
          "name": [
            "Research Institute of Atherosclerotic Disease, Xi\u2019an Jiaotong University Cardiovascular Research Centre, No. 76, Yanta West Road, 710061, Xi\u2019an, Shaanxi, China", 
            "Laboratory Animal Center, Xi\u2019an Jiaotong University Health Science Centre, 710061, Xi\u2019an, Shaanxi, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Liu", 
        "givenName": "Enqi", 
        "id": "sg:person.016446245112.43", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016446245112.43"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/nm1102-1235", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006426096", 
          "https://doi.org/10.1038/nm1102-1235"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/89076", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011575439", 
          "https://doi.org/10.1038/89076"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12265-020-09986-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1126648099", 
          "https://doi.org/10.1007/s12265-020-09986-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/cmi.2011.58", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016176990", 
          "https://doi.org/10.1038/cmi.2011.58"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nri3520", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048331637", 
          "https://doi.org/10.1038/nri3520"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35025203", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007574646", 
          "https://doi.org/10.1038/35025203"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2022-01-03", 
    "datePublishedReg": "2022-01-03", 
    "description": "BackgroundCardiovascular diseases remain the leading cause of morbidity and mortality worldwide, most of which are caused by atherosclerosis. Discerning processes that participate in macrophage-to-foam cell formation are critical for understanding the basic mechanisms underlying atherosclerosis. To explore the molecular mechanisms of foam cell formation, differentially expressed proteins were identified.MethodsHuman peripheral blood mononuclear cells were stimulated with macrophage colony-stimulating factor, and obtained macrophages were transformed into foam cells by oxidized low-density lipoprotein. Tandem mass tag (TMT) labeling combined with mass spectrometry was performed to find associations between foam cell transformation and proteome profiles.ResultsTotally, 5146 quantifiable proteins were identified, among which 1515 and 182 differentially expressed proteins (DEPs) were found in macrophage/monocyte and foam cell/macrophage, respectively. Subcellular localization analysis revealed that downregulated DEPs of macrophages/monocytes were mostly located in the nucleus, whereas upregulated DEPs of foam cells/macrophages were mostly extracellular or located in the plasma membrane. Functional analysis of DEPs demonstrated that cholesterol metabolism-related proteins were upregulated in foam cells, whereas immune response-related proteins were downregulated in foam cells. The protein interaction network showed that the DEPs with the highest interaction scores between macrophages and foam cells were mainly concentrated in lysosomes and the endoplasmic reticulum.ConclusionsProteomics analysis suggested that cholesterol metabolism was upregulated, while the immune response was suppressed in foam cells. KEGG enrichment analysis and protein-protein interaction analysis indicated that DEPs located in the endoplasmic reticulum and lysosomes might be key drivers of foam cell formation. These data provide a basis for identifying the potential proteins associated with the molecular mechanism underlying macrophage transformation to foam cells.", 
    "genre": "article", 
    "id": "sg:pub.10.1186/s12953-021-00183-x", 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1032054", 
        "issn": [
          "1477-5956"
        ], 
        "name": "Proteome Science", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "20"
      }
    ], 
    "keywords": [
      "foam cell formation", 
      "cell formation", 
      "molecular mechanisms", 
      "endoplasmic reticulum", 
      "immune response-related proteins", 
      "tandem mass tag labeling", 
      "protein-protein interaction analysis", 
      "Subcellular localization analysis", 
      "foam cells", 
      "quantitative proteomic profiling", 
      "protein interaction networks", 
      "KEGG enrichment analysis", 
      "metabolism-related proteins", 
      "human monocyte-derived macrophages", 
      "tag labeling", 
      "foam cell transformation", 
      "proteome profiles", 
      "interaction networks", 
      "plasma membrane", 
      "proteomic profiling", 
      "quantifiable proteins", 
      "potential proteins", 
      "upregulated DEPs", 
      "localization analysis", 
      "enrichment analysis", 
      "functional analysis", 
      "macrophage colony-stimulating factor", 
      "cell transformation", 
      "monocyte-derived macrophages", 
      "macrophages/monocytes", 
      "protein", 
      "cholesterol metabolism-related proteins", 
      "macrophage transformation", 
      "DEP", 
      "reticulum", 
      "colony-stimulating factor", 
      "lysosomes", 
      "cells", 
      "peripheral blood mononuclear cells", 
      "cause of morbidity", 
      "cholesterol metabolism", 
      "blood mononuclear cells", 
      "discerning processes", 
      "interaction analysis", 
      "basic mechanisms", 
      "low-density lipoprotein", 
      "macrophages", 
      "mass spectrometry", 
      "highest interaction scores", 
      "interaction scores", 
      "BackgroundCardiovascular disease", 
      "mononuclear cells", 
      "immune response", 
      "key drivers", 
      "mechanism", 
      "profiling", 
      "metabolism", 
      "atherosclerosis", 
      "membrane", 
      "monocytes", 
      "formation", 
      "labeling", 
      "nucleus", 
      "analysis", 
      "morbidity", 
      "mortality", 
      "lipoprotein", 
      "disease", 
      "spectrometry", 
      "response", 
      "drivers", 
      "scores", 
      "cause", 
      "association", 
      "TMT", 
      "basis", 
      "transformation", 
      "factors", 
      "profile", 
      "process", 
      "data", 
      "network"
    ], 
    "name": "TMT-based quantitative proteomic profiling of human monocyte-derived macrophages and foam cells", 
    "pagination": "1", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1144373097"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s12953-021-00183-x"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "34980145"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s12953-021-00183-x", 
      "https://app.dimensions.ai/details/publication/pub.1144373097"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-09-02T16:08", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220902/entities/gbq_results/article/article_937.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1186/s12953-021-00183-x"
  }
]
 

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.10.1186/s12953-021-00183-x'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s12953-021-00183-x'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12953-021-00183-x'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s12953-021-00183-x'


 

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

236 TRIPLES      21 PREDICATES      113 URIs      99 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s12953-021-00183-x schema:about anzsrc-for:06
2 anzsrc-for:0601
3 schema:author N54d52f197d3044a2b24866fb46cf6d47
4 schema:citation sg:pub.10.1007/s12265-020-09986-3
5 sg:pub.10.1038/35025203
6 sg:pub.10.1038/89076
7 sg:pub.10.1038/cmi.2011.58
8 sg:pub.10.1038/nm1102-1235
9 sg:pub.10.1038/nri3520
10 schema:datePublished 2022-01-03
11 schema:datePublishedReg 2022-01-03
12 schema:description BackgroundCardiovascular diseases remain the leading cause of morbidity and mortality worldwide, most of which are caused by atherosclerosis. Discerning processes that participate in macrophage-to-foam cell formation are critical for understanding the basic mechanisms underlying atherosclerosis. To explore the molecular mechanisms of foam cell formation, differentially expressed proteins were identified.MethodsHuman peripheral blood mononuclear cells were stimulated with macrophage colony-stimulating factor, and obtained macrophages were transformed into foam cells by oxidized low-density lipoprotein. Tandem mass tag (TMT) labeling combined with mass spectrometry was performed to find associations between foam cell transformation and proteome profiles.ResultsTotally, 5146 quantifiable proteins were identified, among which 1515 and 182 differentially expressed proteins (DEPs) were found in macrophage/monocyte and foam cell/macrophage, respectively. Subcellular localization analysis revealed that downregulated DEPs of macrophages/monocytes were mostly located in the nucleus, whereas upregulated DEPs of foam cells/macrophages were mostly extracellular or located in the plasma membrane. Functional analysis of DEPs demonstrated that cholesterol metabolism-related proteins were upregulated in foam cells, whereas immune response-related proteins were downregulated in foam cells. The protein interaction network showed that the DEPs with the highest interaction scores between macrophages and foam cells were mainly concentrated in lysosomes and the endoplasmic reticulum.ConclusionsProteomics analysis suggested that cholesterol metabolism was upregulated, while the immune response was suppressed in foam cells. KEGG enrichment analysis and protein-protein interaction analysis indicated that DEPs located in the endoplasmic reticulum and lysosomes might be key drivers of foam cell formation. These data provide a basis for identifying the potential proteins associated with the molecular mechanism underlying macrophage transformation to foam cells.
13 schema:genre article
14 schema:isAccessibleForFree true
15 schema:isPartOf N4015a849b4de4e86b74d8a441dc5a49f
16 N66716603415a419fb32e097f4ae79948
17 sg:journal.1032054
18 schema:keywords BackgroundCardiovascular disease
19 DEP
20 KEGG enrichment analysis
21 Subcellular localization analysis
22 TMT
23 analysis
24 association
25 atherosclerosis
26 basic mechanisms
27 basis
28 blood mononuclear cells
29 cause
30 cause of morbidity
31 cell formation
32 cell transformation
33 cells
34 cholesterol metabolism
35 cholesterol metabolism-related proteins
36 colony-stimulating factor
37 data
38 discerning processes
39 disease
40 drivers
41 endoplasmic reticulum
42 enrichment analysis
43 factors
44 foam cell formation
45 foam cell transformation
46 foam cells
47 formation
48 functional analysis
49 highest interaction scores
50 human monocyte-derived macrophages
51 immune response
52 immune response-related proteins
53 interaction analysis
54 interaction networks
55 interaction scores
56 key drivers
57 labeling
58 lipoprotein
59 localization analysis
60 low-density lipoprotein
61 lysosomes
62 macrophage colony-stimulating factor
63 macrophage transformation
64 macrophages
65 macrophages/monocytes
66 mass spectrometry
67 mechanism
68 membrane
69 metabolism
70 metabolism-related proteins
71 molecular mechanisms
72 monocyte-derived macrophages
73 monocytes
74 mononuclear cells
75 morbidity
76 mortality
77 network
78 nucleus
79 peripheral blood mononuclear cells
80 plasma membrane
81 potential proteins
82 process
83 profile
84 profiling
85 protein
86 protein interaction networks
87 protein-protein interaction analysis
88 proteome profiles
89 proteomic profiling
90 quantifiable proteins
91 quantitative proteomic profiling
92 response
93 reticulum
94 scores
95 spectrometry
96 tag labeling
97 tandem mass tag labeling
98 transformation
99 upregulated DEPs
100 schema:name TMT-based quantitative proteomic profiling of human monocyte-derived macrophages and foam cells
101 schema:pagination 1
102 schema:productId N759d07673e134296bfbf127bebed96b8
103 N7de0888a7a3b49f38ec6f0751eff0db6
104 Nec7adaaea5f243ac98c27ca4e35c2426
105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1144373097
106 https://doi.org/10.1186/s12953-021-00183-x
107 schema:sdDatePublished 2022-09-02T16:08
108 schema:sdLicense https://scigraph.springernature.com/explorer/license/
109 schema:sdPublisher Na7903a0dfeae46f989bed7ec321f68e2
110 schema:url https://doi.org/10.1186/s12953-021-00183-x
111 sgo:license sg:explorer/license/
112 sgo:sdDataset articles
113 rdf:type schema:ScholarlyArticle
114 N109ed2f0aa1e4f6596da5102518e6c97 rdf:first sg:person.010133623605.74
115 rdf:rest N40900ab8290b418094051365b5dca39d
116 N1c383fe00ca64c75b8c811de0b09b5da rdf:first sg:person.015672426353.09
117 rdf:rest Ne2c127ca2e91421fb383174ca34196a2
118 N31adabc7b1c34cbbab5e5c5de5934bda rdf:first sg:person.016446245112.43
119 rdf:rest rdf:nil
120 N4015a849b4de4e86b74d8a441dc5a49f schema:volumeNumber 20
121 rdf:type schema:PublicationVolume
122 N40900ab8290b418094051365b5dca39d rdf:first sg:person.016224625372.09
123 rdf:rest N9404b6c3f0d948e98031c8f7b9562c99
124 N54d52f197d3044a2b24866fb46cf6d47 rdf:first Nfaa99412b9154213bb6a68a987119e5c
125 rdf:rest N109ed2f0aa1e4f6596da5102518e6c97
126 N66716603415a419fb32e097f4ae79948 schema:issueNumber 1
127 rdf:type schema:PublicationIssue
128 N759d07673e134296bfbf127bebed96b8 schema:name doi
129 schema:value 10.1186/s12953-021-00183-x
130 rdf:type schema:PropertyValue
131 N7de0888a7a3b49f38ec6f0751eff0db6 schema:name pubmed_id
132 schema:value 34980145
133 rdf:type schema:PropertyValue
134 N81f000eca1f14fcea0f14346992e0e1d rdf:first sg:person.01264216545.46
135 rdf:rest Nb6bb19a8744047bbb9b63f496fbb111c
136 N90ecf208172d4494801759cd5cf238d4 rdf:first sg:person.01217761561.81
137 rdf:rest N31adabc7b1c34cbbab5e5c5de5934bda
138 N9404b6c3f0d948e98031c8f7b9562c99 rdf:first sg:person.015427244772.06
139 rdf:rest N1c383fe00ca64c75b8c811de0b09b5da
140 Na7903a0dfeae46f989bed7ec321f68e2 schema:name Springer Nature - SN SciGraph project
141 rdf:type schema:Organization
142 Nb6bb19a8744047bbb9b63f496fbb111c rdf:first sg:person.0707217075.15
143 rdf:rest N90ecf208172d4494801759cd5cf238d4
144 Nbed1c58c6f114adc972806de70b38a04 rdf:first sg:person.01006540224.36
145 rdf:rest N81f000eca1f14fcea0f14346992e0e1d
146 Ne2c127ca2e91421fb383174ca34196a2 rdf:first sg:person.012123611207.85
147 rdf:rest Nbed1c58c6f114adc972806de70b38a04
148 Nec7adaaea5f243ac98c27ca4e35c2426 schema:name dimensions_id
149 schema:value pub.1144373097
150 rdf:type schema:PropertyValue
151 Nfaa99412b9154213bb6a68a987119e5c schema:affiliation grid-institutes:grid.43169.39
152 schema:familyName Zhang
153 schema:givenName Yali
154 rdf:type schema:Person
155 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
156 schema:name Biological Sciences
157 rdf:type schema:DefinedTerm
158 anzsrc-for:0601 schema:inDefinedTermSet anzsrc-for:
159 schema:name Biochemistry and Cell Biology
160 rdf:type schema:DefinedTerm
161 sg:journal.1032054 schema:issn 1477-5956
162 schema:name Proteome Science
163 schema:publisher Springer Nature
164 rdf:type schema:Periodical
165 sg:person.01006540224.36 schema:affiliation grid-institutes:grid.43169.39
166 schema:familyName Wang
167 schema:givenName Rong
168 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01006540224.36
169 rdf:type schema:Person
170 sg:person.010133623605.74 schema:affiliation grid-institutes:grid.43169.39
171 schema:familyName Fu
172 schema:givenName Yu
173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010133623605.74
174 rdf:type schema:Person
175 sg:person.012123611207.85 schema:affiliation grid-institutes:grid.43169.39
176 schema:familyName Alam
177 schema:givenName Naqash
178 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012123611207.85
179 rdf:type schema:Person
180 sg:person.01217761561.81 schema:affiliation grid-institutes:grid.43169.39
181 schema:familyName Zhao
182 schema:givenName Sihai
183 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01217761561.81
184 rdf:type schema:Person
185 sg:person.01264216545.46 schema:affiliation grid-institutes:grid.43169.39
186 schema:familyName Wang
187 schema:givenName Weirong
188 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01264216545.46
189 rdf:type schema:Person
190 sg:person.015427244772.06 schema:affiliation grid-institutes:grid.43169.39
191 schema:familyName Zhang
192 schema:givenName Chenyang
193 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015427244772.06
194 rdf:type schema:Person
195 sg:person.015672426353.09 schema:affiliation grid-institutes:grid.43169.39
196 schema:familyName Cao
197 schema:givenName Wenbin
198 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015672426353.09
199 rdf:type schema:Person
200 sg:person.016224625372.09 schema:affiliation grid-institutes:grid.43169.39
201 schema:familyName Jia
202 schema:givenName Linying
203 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016224625372.09
204 rdf:type schema:Person
205 sg:person.016446245112.43 schema:affiliation grid-institutes:grid.43169.39
206 schema:familyName Liu
207 schema:givenName Enqi
208 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016446245112.43
209 rdf:type schema:Person
210 sg:person.0707217075.15 schema:affiliation grid-institutes:grid.43169.39
211 schema:familyName Bai
212 schema:givenName Liang
213 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0707217075.15
214 rdf:type schema:Person
215 sg:pub.10.1007/s12265-020-09986-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1126648099
216 https://doi.org/10.1007/s12265-020-09986-3
217 rdf:type schema:CreativeWork
218 sg:pub.10.1038/35025203 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007574646
219 https://doi.org/10.1038/35025203
220 rdf:type schema:CreativeWork
221 sg:pub.10.1038/89076 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011575439
222 https://doi.org/10.1038/89076
223 rdf:type schema:CreativeWork
224 sg:pub.10.1038/cmi.2011.58 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016176990
225 https://doi.org/10.1038/cmi.2011.58
226 rdf:type schema:CreativeWork
227 sg:pub.10.1038/nm1102-1235 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006426096
228 https://doi.org/10.1038/nm1102-1235
229 rdf:type schema:CreativeWork
230 sg:pub.10.1038/nri3520 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048331637
231 https://doi.org/10.1038/nri3520
232 rdf:type schema:CreativeWork
233 grid-institutes:grid.43169.39 schema:alternateName Laboratory Animal Center, Xi’an Jiaotong University Health Science Centre, 710061, Xi’an, Shaanxi, China
234 schema:name Laboratory Animal Center, Xi’an Jiaotong University Health Science Centre, 710061, Xi’an, Shaanxi, China
235 Research Institute of Atherosclerotic Disease, Xi’an Jiaotong University Cardiovascular Research Centre, No. 76, Yanta West Road, 710061, Xi’an, Shaanxi, China
236 rdf:type schema:Organization
 




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


...