FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows

An important challenge for primary or secondary analysis of cytometry data is how to facilitate productive collaboration between domain and quantitative experts. Domain experts in cytometry laboratories and core facilities increasingly recognize the need for automated workflows in the face of increa...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Frontiers in immunology Ročník 12; s. 768541
Hlavní autori: White, Scott, Quinn, John, Enzor, Jennifer, Staats, Janet, Mosier, Sarah M., Almarode, James, Denny, Thomas N., Weinhold, Kent J., Ferrari, Guido, Chan, Cliburn
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Switzerland Frontiers Media S.A 05.11.2021
Predmet:
ISSN:1664-3224, 1664-3224
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract An important challenge for primary or secondary analysis of cytometry data is how to facilitate productive collaboration between domain and quantitative experts. Domain experts in cytometry laboratories and core facilities increasingly recognize the need for automated workflows in the face of increasing data complexity, but by and large, still conduct all analysis using traditional applications, predominantly FlowJo. To a large extent, this cuts domain experts off from the rapidly growing library of Single Cell Data Science algorithms available, curtailing the potential contributions of these experts to the validation and interpretation of results. To address this challenge, we developed FlowKit, a Gating-ML 2.0-compliant Python package that can read and write FCS files and FlowJo workspaces. We present examples of the use of FlowKit for constructing reporting and analysis workflows, including round-tripping results to and from FlowJo for joint analysis by both domain and quantitative experts.
AbstractList An important challenge for primary or secondary analysis of cytometry data is how to facilitate productive collaboration between domain and quantitative experts. Domain experts in cytometry laboratories and core facilities increasingly recognize the need for automated workflows in the face of increasing data complexity, but by and large, still conduct all analysis using traditional applications, predominantly FlowJo. To a large extent, this cuts domain experts off from the rapidly growing library of Single Cell Data Science algorithms available, curtailing the potential contributions of these experts to the validation and interpretation of results. To address this challenge, we developed FlowKit, a Gating-ML 2.0-compliant Python package that can read and write FCS files and FlowJo workspaces. We present examples of the use of FlowKit for constructing reporting and analysis workflows, including round-tripping results to and from FlowJo for joint analysis by both domain and quantitative experts.
An important challenge for primary or secondary analysis of cytometry data is how to facilitate productive collaboration between domain and quantitative experts. Domain experts in cytometry laboratories and core facilities increasingly recognize the need for automated workflows in the face of increasing data complexity, but by and large, still conduct all analysis using traditional applications, predominantly FlowJo. To a large extent, this cuts domain experts off from the rapidly growing library of Single Cell Data Science algorithms available, curtailing the potential contributions of these experts to the validation and interpretation of results. To address this challenge, we developed FlowKit, a Gating-ML 2.0-compliant Python package that can read and write FCS files and FlowJo workspaces. We present examples of the use of FlowKit for constructing reporting and analysis workflows, including round-tripping results to and from FlowJo for joint analysis by both domain and quantitative experts.An important challenge for primary or secondary analysis of cytometry data is how to facilitate productive collaboration between domain and quantitative experts. Domain experts in cytometry laboratories and core facilities increasingly recognize the need for automated workflows in the face of increasing data complexity, but by and large, still conduct all analysis using traditional applications, predominantly FlowJo. To a large extent, this cuts domain experts off from the rapidly growing library of Single Cell Data Science algorithms available, curtailing the potential contributions of these experts to the validation and interpretation of results. To address this challenge, we developed FlowKit, a Gating-ML 2.0-compliant Python package that can read and write FCS files and FlowJo workspaces. We present examples of the use of FlowKit for constructing reporting and analysis workflows, including round-tripping results to and from FlowJo for joint analysis by both domain and quantitative experts.
Author Enzor, Jennifer
Mosier, Sarah M.
Ferrari, Guido
Weinhold, Kent J.
Denny, Thomas N.
Almarode, James
Quinn, John
Staats, Janet
Chan, Cliburn
White, Scott
AuthorAffiliation 6 Department of Surgery, Duke University Medical Center , Durham, NC , United States
5 Duke Immune Profiling Core, Duke University School of Medicine , Durham, NC , United States
1 Duke Center for AIDS Research, Duke University , Durham, NC , United States
2 Department of Biostatistics and Bioinformatics, Duke University Medical Center , Durham, NC , United States
3 Center for Human Systems Immunology, Duke University Medical Center , Durham, NC , United States
4 BD Life Sciences - FlowJo , Ashland, OR , United States
7 Duke Human Vaccine Institute , Durham, NC , United States
AuthorAffiliation_xml – name: 3 Center for Human Systems Immunology, Duke University Medical Center , Durham, NC , United States
– name: 4 BD Life Sciences - FlowJo , Ashland, OR , United States
– name: 6 Department of Surgery, Duke University Medical Center , Durham, NC , United States
– name: 5 Duke Immune Profiling Core, Duke University School of Medicine , Durham, NC , United States
– name: 1 Duke Center for AIDS Research, Duke University , Durham, NC , United States
– name: 2 Department of Biostatistics and Bioinformatics, Duke University Medical Center , Durham, NC , United States
– name: 7 Duke Human Vaccine Institute , Durham, NC , United States
Author_xml – sequence: 1
  givenname: Scott
  surname: White
  fullname: White, Scott
– sequence: 2
  givenname: John
  surname: Quinn
  fullname: Quinn, John
– sequence: 3
  givenname: Jennifer
  surname: Enzor
  fullname: Enzor, Jennifer
– sequence: 4
  givenname: Janet
  surname: Staats
  fullname: Staats, Janet
– sequence: 5
  givenname: Sarah M.
  surname: Mosier
  fullname: Mosier, Sarah M.
– sequence: 6
  givenname: James
  surname: Almarode
  fullname: Almarode, James
– sequence: 7
  givenname: Thomas N.
  surname: Denny
  fullname: Denny, Thomas N.
– sequence: 8
  givenname: Kent J.
  surname: Weinhold
  fullname: Weinhold, Kent J.
– sequence: 9
  givenname: Guido
  surname: Ferrari
  fullname: Ferrari, Guido
– sequence: 10
  givenname: Cliburn
  surname: Chan
  fullname: Chan, Cliburn
BackLink https://www.ncbi.nlm.nih.gov/pubmed/34804056$$D View this record in MEDLINE/PubMed
BookMark eNp1kk9v1DAQxSNUREvpB-CCfOSyi__FSTggrVYUVhTBoQiJizV27K1bxy62A9pvT7LbohYJXzwav_k9jfyeV0chBlNVLwleMtZ2b6wbhnFJMSXLRrQ1J0-qEyIEXzBK-dGD-rg6y_kaT4d3jLH6WXXMeIs5rsVJ9ePcx9-fXHmLVujrrlzFgC5j9DeuIBsT2oRitgmK6dFnCCN4BKFHq7HEYd9c76bKlLRDqwB-l11G32O6sRM0v6ieWvDZnN3dp9W38_eX64-Liy8fNuvVxUJzUZeFNY3oQRNriQDgvKaCAjOd0kqTVoFpWMPAqI5bAkrxnmtuTK26HhPVcs5Oq82B20e4lrfJDZB2MoKT-0ZMWwmpOO2NJKTpMGCmhdbctrpTLSWMKQ66a3BDJ9a7A-t2VIPptQklgX8EffwS3JXcxl-yFZh2eAa8vgOk-HM0ucjBZW28h2DimCUVGLd0WnGWvnro9dfk_nMmQXMQ6BRzTsZK7QoUF2dr5yXBck6C3CdBzkmQhyRMk-SfyXv4_2f-ANaFuTM
CitedBy_id crossref_primary_10_1038_s41586_024_07707_3
crossref_primary_10_1002_cyto_b_22255
crossref_primary_10_1016_j_jbc_2024_107163
crossref_primary_10_1093_bioadv_vbad103
crossref_primary_10_3389_fimmu_2025_1469473
crossref_primary_10_1182_bloodadvances_2023012118
crossref_primary_10_1093_femsyr_foaf032
crossref_primary_10_3389_fenvc_2022_931067
crossref_primary_10_7554_eLife_104276_3
crossref_primary_10_3390_cancers17030483
crossref_primary_10_1038_s41477_025_01973_3
crossref_primary_10_1002_cyto_a_24953
crossref_primary_10_1080_07366205_2025_2505347
crossref_primary_10_1016_j_ccell_2024_04_008
crossref_primary_10_7554_eLife_104276
crossref_primary_10_1002_advs_202207061
crossref_primary_10_1073_pnas_2514178122
crossref_primary_10_1126_science_adr8785
crossref_primary_10_3390_cells13221858
crossref_primary_10_1038_s41526_024_00423_2
crossref_primary_10_1016_j_modpat_2023_100373
Cites_doi 10.1088/1742-5468/2008/10/P10008
10.1371/journal.pcbi.1009071
10.1038/sdata.2018.15
10.1038/s41592-018-0308-4
10.1002/cyto.a.22690
10.1038/s41598-019-41695-z
10.1186/s13059-017-1382-0
10.1016/j.jim.2014.05.021
10.1021/acssynbio.5b00284
10.1186/1471-2105-10-106
10.1007/s12026-014-8516-1
10.1038/nbt.4314
ContentType Journal Article
Copyright Copyright © 2021 White, Quinn, Enzor, Staats, Mosier, Almarode, Denny, Weinhold, Ferrari and Chan.
Copyright © 2021 White, Quinn, Enzor, Staats, Mosier, Almarode, Denny, Weinhold, Ferrari and Chan 2021 White, Quinn, Enzor, Staats, Mosier, Almarode, Denny, Weinhold, Ferrari and Chan
Copyright_xml – notice: Copyright © 2021 White, Quinn, Enzor, Staats, Mosier, Almarode, Denny, Weinhold, Ferrari and Chan.
– notice: Copyright © 2021 White, Quinn, Enzor, Staats, Mosier, Almarode, Denny, Weinhold, Ferrari and Chan 2021 White, Quinn, Enzor, Staats, Mosier, Almarode, Denny, Weinhold, Ferrari and Chan
DBID AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
7X8
5PM
DOA
DOI 10.3389/fimmu.2021.768541
DatabaseName CrossRef
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
MEDLINE - Academic
PubMed Central (Full Participant titles)
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
MEDLINE - Academic
DatabaseTitleList CrossRef
MEDLINE

MEDLINE - Academic

Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: NPM
  name: PubMed
  url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 3
  dbid: 7X8
  name: MEDLINE - Academic
  url: https://search.proquest.com/medline
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Biology
EISSN 1664-3224
ExternalDocumentID oai_doaj_org_article_11790a03c6cc4f8c9b82133b4ac97072
PMC8602902
34804056
10_3389_fimmu_2021_768541
Genre Journal Article
Research Support, N.I.H., Extramural
GrantInformation_xml – fundername: NIAID NIH HHS
  grantid: HHSN272201700061C
– fundername: NIAID NIH HHS
  grantid: P30 AI064518
GroupedDBID 53G
5VS
9T4
AAFWJ
AAKDD
AAYXX
ACGFO
ACGFS
ADBBV
ADRAZ
AENEX
AFPKN
ALMA_UNASSIGNED_HOLDINGS
AOIJS
BAWUL
BCNDV
CITATION
DIK
EBS
EMOBN
GROUPED_DOAJ
GX1
HYE
KQ8
M48
M~E
OK1
PGMZT
RNS
RPM
ACXDI
CGR
CUY
CVF
ECM
EIF
IAO
IEA
IHR
IHW
IPNFZ
NPM
RIG
7X8
5PM
ID FETCH-LOGICAL-c465t-fe76dac1ff16aa445262a3e9bcbc18bae7373aeb94f1abb4d4c4ee5b9d01b8443
IEDL.DBID DOA
ISICitedReferencesCount 20
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001027348300001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1664-3224
IngestDate Fri Oct 03 12:46:28 EDT 2025
Thu Aug 21 18:04:52 EDT 2025
Thu Oct 02 10:58:52 EDT 2025
Thu Jan 02 22:55:29 EST 2025
Sat Nov 29 02:07:20 EST 2025
Tue Nov 18 22:33:33 EST 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Keywords software
python (programming language)
single cell data science
FlowJo
GatingML
flow cytometry
systems immunology
Language English
License Copyright © 2021 White, Quinn, Enzor, Staats, Mosier, Almarode, Denny, Weinhold, Ferrari and Chan.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c465t-fe76dac1ff16aa445262a3e9bcbc18bae7373aeb94f1abb4d4c4ee5b9d01b8443
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Reviewed by: Thomas Myles Ashhurst, The University of Sydney, Australia; Gur Yaari, Bar-Ilan University, Israel
This article was submitted to Systems Immunology, a section of the journal Frontiers in Immunology
Edited by: Juan J. Garcia-Vallejo, Amsterdam University Medical Center, Netherlands
OpenAccessLink https://doaj.org/article/11790a03c6cc4f8c9b82133b4ac97072
PMID 34804056
PQID 2600822622
PQPubID 23479
ParticipantIDs doaj_primary_oai_doaj_org_article_11790a03c6cc4f8c9b82133b4ac97072
pubmedcentral_primary_oai_pubmedcentral_nih_gov_8602902
proquest_miscellaneous_2600822622
pubmed_primary_34804056
crossref_citationtrail_10_3389_fimmu_2021_768541
crossref_primary_10_3389_fimmu_2021_768541
PublicationCentury 2000
PublicationDate 2021-11-05
PublicationDateYYYYMMDD 2021-11-05
PublicationDate_xml – month: 11
  year: 2021
  text: 2021-11-05
  day: 05
PublicationDecade 2020
PublicationPlace Switzerland
PublicationPlace_xml – name: Switzerland
PublicationTitle Frontiers in immunology
PublicationTitleAlternate Front Immunol
PublicationYear 2021
Publisher Frontiers Media S.A
Publisher_xml – name: Frontiers Media S.A
References Linderman (B5) 2019; 16
Blondel (B9) 2008; 2008
B12
Castillo-Hair (B14) 2016; 5
B15
Wang (B7) 2020; 22
Traag (B8) 2019; 9
Finak (B4) 2021
Spidlen (B1) 2015; 87
Becht (B6) 2018; 37
Bhattacharya (B11) 2014; 58
Staats (B2) 2014; 409
Wolf (B16) 2018; 19
Bhattacharya (B10) 2018; 5
Hahne (B3) 2009; 10
Burton (B13) 2021; 17
References_xml – volume: 2008
  start-page: P10008
  year: 2008
  ident: B9
  article-title: Fast Unfolding of Communities in Large Networks
  publication-title: J Stat Mech: Theory Experiment
  doi: 10.1088/1742-5468/2008/10/P10008
– ident: B12
– volume: 17
  start-page: e1009071
  year: 2021
  ident: B13
  article-title: CytoPy: An Autonomous Cytometry Analysis Framework
  publication-title: PloS Comput Biol
  doi: 10.1371/journal.pcbi.1009071
– volume: 5
  start-page: 180015
  year: 2018
  ident: B10
  article-title: ImmPort, Toward Repurposing of Open Access Immunological Assay Data for Translational and Clinical Research
  publication-title: Sci Data
  doi: 10.1038/sdata.2018.15
– volume: 16
  year: 2019
  ident: B5
  article-title: Fast Interpolation-Based T-SNE for Improved Visualization of Single-Cell RNA-Seq Data
  publication-title: Nat Methods
  doi: 10.1038/s41592-018-0308-4
– volume: 87
  year: 2015
  ident: B1
  article-title: Isac’s Gating-ML 2.0 Data Exchange Standard for Gating Description
  publication-title: Cytometry A
  doi: 10.1002/cyto.a.22690
– volume: 9
  start-page: 1
  year: 2019
  ident: B8
  article-title: From Louvain to Leiden: Guaranteeing Well-Connected Communities
  publication-title: Sci Rep
  doi: 10.1038/s41598-019-41695-z
– volume: 19
  start-page: 15
  year: 2018
  ident: B16
  article-title: SCANPY: Large-Scale Single-Cell Gene Expression Data Analysis
  publication-title: Genome Biol
  doi: 10.1186/s13059-017-1382-0
– volume-title: R Package Version 4.4.0
  year: 2021
  ident: B4
  article-title: Flowworkspace: Infrastructure for Representing and Interacting With Gated and Ungated Cytometry Data Sets
– volume: 409
  start-page: 44
  year: 2014
  ident: B2
  article-title: Toward Development of a Comprehensive External Quality Assurance Program for Polyfunctional Intracellular Cytokine Staining Assays
  publication-title: J Immunol Methods
  doi: 10.1016/j.jim.2014.05.021
– volume: 5
  year: 2016
  ident: B14
  article-title: FlowCal: A User-Friendly, Open Source Software Tool for Automatically Converting Flow Cytometry Data From Arbitrary to Calibrated Units
  publication-title: ACS Synth Biol
  doi: 10.1021/acssynbio.5b00284
– volume: 10
  start-page: 106
  year: 2009
  ident: B3
  article-title: Flowcore: A Bioconductor Package for High Throughput Flow Cytometry
  publication-title: BMC Bioinf
  doi: 10.1186/1471-2105-10-106
– volume: 22
  start-page: 1
  year: 2020
  ident: B7
  article-title: Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering T-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization
  publication-title: ArXiv Preprint ArXiv:201204456
– volume: 58
  year: 2014
  ident: B11
  article-title: ImmPort: Disseminating Data to the Public for the Future of Immunology
  publication-title: Immunol Res
  doi: 10.1007/s12026-014-8516-1
– volume: 37
  start-page: 38
  year: 2018
  ident: B6
  article-title: Dimensionality Reduction for Visualizing Single-Cell Data Using UMAP
  publication-title: Nat Biotechnol
  doi: 10.1038/nbt.4314
– ident: B15
SSID ssj0000493335
Score 2.4210517
Snippet An important challenge for primary or secondary analysis of cytometry data is how to facilitate productive collaboration between domain and quantitative...
SourceID doaj
pubmedcentral
proquest
pubmed
crossref
SourceType Open Website
Open Access Repository
Aggregation Database
Index Database
Enrichment Source
StartPage 768541
SubjectTerms Algorithms
Computational Biology
flow cytometry
Flow Cytometry - methods
FlowJo
Humans
Immunology
Machine Learning
python (programming language)
single cell data science
Single-Cell Analysis
Software
systems immunology
Workflow
Title FlowKit: A Python Toolkit for Integrated Manual and Automated Cytometry Analysis Workflows
URI https://www.ncbi.nlm.nih.gov/pubmed/34804056
https://www.proquest.com/docview/2600822622
https://pubmed.ncbi.nlm.nih.gov/PMC8602902
https://doaj.org/article/11790a03c6cc4f8c9b82133b4ac97072
Volume 12
WOSCitedRecordID wos001027348300001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAON
  databaseName: DOAJ Directory of Open Access Journals
  customDbUrl:
  eissn: 1664-3224
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000493335
  issn: 1664-3224
  databaseCode: DOA
  dateStart: 20100101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources
  customDbUrl:
  eissn: 1664-3224
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0000493335
  issn: 1664-3224
  databaseCode: M~E
  dateStart: 20100101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1bb9MwFLZgAokXxJ1uMBmJJ6SwJD7xZW9lWgWCTXsYqOLF8i0i0CaoTTf1hd8-X9qqRQheeIkix4mt75zY34md7yD0mlrwk0DJMieAZkAJZBqMyYij1NN9okjMQ_blEzs_5-OxuNhK9RX2hCV54ATcUZAsy1VODDUGam6E5qWPqzQoI1jO4uibM7EVTH1PvJcQUqVlTB-FiaO6mU4XPh4si7eeYVdQ7ExEUa__TyTz972SW5PP6AG6v2KNeJh6-xDdcu0jdDflkVw-Rl9Hk-76Y9Mf4yG-WAY1AHzZdZMfTY89J8Uf1pIQFp-pIEGKVWvxcNF301h4svRnrp8t8VqiBIdv6LV_6PwJ-jw6vTx5n62SJmQGaNVntWPUKlPUdUGVgpBBvFTECW20KbhWjhFGlNMC6kJpDRYMOFdpYfNCcwDyFO21XeueI-zJtwXGrdOKgWClqiquRG61JxnKcTtA-RpBaVaK4iGxxUT6yCKALiPoMoAuE-gD9GZzy88kp_G3yu-CWTYVgxJ2LPD-IVf-If_lHwP0am1U6d-csByiWtct5jJI83t6REtf51ky8qYpAtyPbhUdILZj_p2-7F5pm29RnTsk9RJ5uf8_On-A7gU84r-P1Qu0188W7iW6Y676Zj47RLfZmB9Gx_fHs1-nN9b7CQE
linkProvider Directory of Open Access Journals
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=FlowKit%3A+A+Python+Toolkit+for+Integrated+Manual+and+Automated+Cytometry+Analysis+Workflows&rft.jtitle=Frontiers+in+immunology&rft.au=Scott+White&rft.au=Scott+White&rft.au=Scott+White&rft.au=John+Quinn&rft.date=2021-11-05&rft.pub=Frontiers+Media+S.A&rft.eissn=1664-3224&rft.volume=12&rft_id=info:doi/10.3389%2Ffimmu.2021.768541&rft.externalDBID=DOA&rft.externalDocID=oai_doaj_org_article_11790a03c6cc4f8c9b82133b4ac97072
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1664-3224&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1664-3224&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1664-3224&client=summon