Evidence for differential alternative splicing in blood of young boys with autism spectrum disorders
Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well...
Saved in:
Published in | Molecular autism Vol. 4; no. 1; p. 30 |
---|---|
Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
BioMed Central Ltd
04.09.2013
BioMed Central |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume.
RNA from blood was processed on whole genome exon arrays for 2-4-year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20).
A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. The only pathways significant after multiple comparison corrections (FDR <0.05) were the Nrf2-mediated reactive oxygen species (ROS) oxidative response (superoxide dismutase 2, catalase, peroxiredoxin 1, PIK3C3, DNAJC17, microsomal glutathione S-transferase 3) and superoxide radical degradation (SOD2, CAT).
These data support differences in alternative splicing of mRNA in blood of ASD subjects compared to TD controls that differ related to head size. The findings are preliminary, need to be replicated in independent cohorts, and predicted alternative splicing differences need to be confirmed using direct analytical methods. |
---|---|
AbstractList | BACKGROUND: Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. METHODS: RNA from blood was processed on whole genome exon arrays for 2-4-year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). RESULTS: A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. The only pathways significant after multiple comparison corrections (FDR <0.05) were the Nrf2-mediated reactive oxygen species (ROS) oxidative response (superoxide dismutase 2, catalase, peroxiredoxin 1, PIK3C3, DNAJC17, microsomal glutathione S-transferase 3) and superoxide radical degradation (SOD2, CAT). CONCLUSIONS: These data support differences in alternative splicing of mRNA in blood of ASD subjects compared to TD controls that differ related to head size. The findings are preliminary, need to be replicated in independent cohorts, and predicted alternative splicing differences need to be confirmed using direct analytical methods. Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume.BACKGROUNDSince RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume.RNA from blood was processed on whole genome exon arrays for 2-4-year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20).METHODSRNA from blood was processed on whole genome exon arrays for 2-4-year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20).A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. The only pathways significant after multiple comparison corrections (FDR <0.05) were the Nrf2-mediated reactive oxygen species (ROS) oxidative response (superoxide dismutase 2, catalase, peroxiredoxin 1, PIK3C3, DNAJC17, microsomal glutathione S-transferase 3) and superoxide radical degradation (SOD2, CAT).RESULTSA total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. The only pathways significant after multiple comparison corrections (FDR <0.05) were the Nrf2-mediated reactive oxygen species (ROS) oxidative response (superoxide dismutase 2, catalase, peroxiredoxin 1, PIK3C3, DNAJC17, microsomal glutathione S-transferase 3) and superoxide radical degradation (SOD2, CAT).These data support differences in alternative splicing of mRNA in blood of ASD subjects compared to TD controls that differ related to head size. The findings are preliminary, need to be replicated in independent cohorts, and predicted alternative splicing differences need to be confirmed using direct analytical methods.CONCLUSIONSThese data support differences in alternative splicing of mRNA in blood of ASD subjects compared to TD controls that differ related to head size. The findings are preliminary, need to be replicated in independent cohorts, and predicted alternative splicing differences need to be confirmed using direct analytical methods. Background Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. Methods RNA from blood was processed on whole genome exon arrays for 2-4-year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). Results A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. The only pathways significant after multiple comparison corrections (FDR <0.05) were the Nrf2-mediated reactive oxygen species (ROS) oxidative response (superoxide dismutase 2, catalase, peroxiredoxin 1, PIK3C3, DNAJC17, microsomal glutathione S-transferase 3) and superoxide radical degradation (SOD2, CAT). Conclusions These data support differences in alternative splicing of mRNA in blood of ASD subjects compared to TD controls that differ related to head size. The findings are preliminary, need to be replicated in independent cohorts, and predicted alternative splicing differences need to be confirmed using direct analytical methods. Keywords: Autism, ASD, RNA, Splicing, Head size, Gene expression Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. RNA from blood was processed on whole genome exon arrays for 2-4-year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. The only pathways significant after multiple comparison corrections (FDR <0.05) were the Nrf2-mediated reactive oxygen species (ROS) oxidative response (superoxide dismutase 2, catalase, peroxiredoxin 1, PIK3C3, DNAJC17, microsomal glutathione S-transferase 3) and superoxide radical degradation (SOD2, CAT). These data support differences in alternative splicing of mRNA in blood of ASD subjects compared to TD controls that differ related to head size. The findings are preliminary, need to be replicated in independent cohorts, and predicted alternative splicing differences need to be confirmed using direct analytical methods. Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been reported in ASD brains, we determined if there was DAS in blood mRNA of ASD subjects compared to typically developing (TD) controls, as well as in ASD subgroups related to cerebral volume. RNA from blood was processed on whole genome exon arrays for 2-4-year-old ASD and TD boys. An ANCOVA with age and batch as covariates was used to predict DAS for ALL ASD (n=30), ASD with normal total cerebral volumes (NTCV), and ASD with large total cerebral volumes (LTCV) compared to TD controls (n=20). A total of 53 genes were predicted to have DAS for ALL ASD versus TD, 169 genes for ASD_NTCV versus TD, 1 gene for ASD_LTCV versus TD, and 27 genes for ASD_LTCV versus ASD_NTCV. These differences were significant at P <0.05 after false discovery rate corrections for multiple comparisons (FDR <5% false positives). A number of the genes predicted to have DAS in ASD are known to regulate DAS (SFPQ, SRPK1, SRSF11, SRSF2IP, FUS, LSM14A). In addition, a number of genes with predicted DAS are involved in pathways implicated in previous ASD studies, such as ROS monocyte/macrophage, Natural Killer Cell, mTOR, and NGF signaling. The only pathways significant after multiple comparison corrections (FDR <0.05) were the Nrf2-mediated reactive oxygen species (ROS) oxidative response (superoxide dismutase 2, catalase, peroxiredoxin 1, PIK3C3, DNAJC17, microsomal glutathione S-transferase 3) and superoxide radical degradation (SOD2, CAT). These data support differences in alternative splicing of mRNA in blood of ASD subjects compared to TD controls that differ related to head size. The findings are preliminary, need to be replicated in independent cohorts, and predicted alternative splicing differences need to be confirmed using direct analytical methods. |
Audience | Academic |
Author | Amaral, David G Rogers, Sally Stamova, Boryana S Nordahl, Christine W Shen, Mark D Sharp, Frank R Tian, Yingfang |
AuthorAffiliation | 5 MIND Institute Research Wet Labs, University of California at Davis, Room 2417, 2805 50th Street, Sacramento, CA 95817, USA 2 Department of Neurology, University of California at Davis, Sacramento, CA 95817, USA 3 Department of Psychiatry and Behavioral Sciences, University of California at Davis, Sacramento, CA 95817, USA 1 MIND Institute, University of California at Davis, Sacramento, CA 95817, USA 4 College of Life Sciences, Shaanxi Normal University, Xi’an 710062, China |
AuthorAffiliation_xml | – name: 5 MIND Institute Research Wet Labs, University of California at Davis, Room 2417, 2805 50th Street, Sacramento, CA 95817, USA – name: 3 Department of Psychiatry and Behavioral Sciences, University of California at Davis, Sacramento, CA 95817, USA – name: 4 College of Life Sciences, Shaanxi Normal University, Xi’an 710062, China – name: 2 Department of Neurology, University of California at Davis, Sacramento, CA 95817, USA – name: 1 MIND Institute, University of California at Davis, Sacramento, CA 95817, USA |
Author_xml | – sequence: 1 givenname: Boryana S surname: Stamova fullname: Stamova, Boryana S – sequence: 2 givenname: Yingfang surname: Tian fullname: Tian, Yingfang – sequence: 3 givenname: Christine W surname: Nordahl fullname: Nordahl, Christine W – sequence: 4 givenname: Mark D surname: Shen fullname: Shen, Mark D – sequence: 5 givenname: Sally surname: Rogers fullname: Rogers, Sally – sequence: 6 givenname: David G surname: Amaral fullname: Amaral, David G – sequence: 7 givenname: Frank R surname: Sharp fullname: Sharp, Frank R |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/24007566$$D View this record in MEDLINE/PubMed |
BookMark | eNp1kktrGzEQgJeS0jyaa49loVByWVfv1V4KJqQPCPTSnoVWO7JVtJIr7br431fGSbDbRjpIjL75kEZzWZ2FGKCq3mC0wFiKDwQx1BDakYY1FL2oLp4CZ0f78-o655-oDIoZY-RVdU4YQi0X4qIa7rZugGCgtjHVg7MWEoTJaV9rP0EKenJbqPPGO-PCqnah7n2MQx1tvYtzifRxl-vfblrXep5cHgsLZkrzWGw5pgFSfl29tNpnuH5Yr6ofn-6-335p7r99_nq7vG96zsTUEEx0OwhpiUWGUwyUCtIKxDjm2khhOwEwcMGlJsyaDjNtpZBaDpIjLVt6VX08eDdzP8JgykOS9mqT3KjTTkXt1OlJcGu1iltFJRMt7YpgeRD0Lj4jOD0xcVT7Qqt9oRVTFBXHzcMlUvw1Q57U6LIB73WAOGeFGe8wx4Swgr47oCvtQblgY5GaPa6WnLJWdlySQi3-Q5U5wOhM6QjrSvwk4f1RwhrKR65z9OV3Ysin4Nvjej2987E9CsAOgEkx5wRWGTfpvadcwXmFkdo34r8lWPyV9mh-JuEPa0reDw |
CitedBy_id | crossref_primary_10_1016_j_bbr_2015_06_043 crossref_primary_10_1080_20473869_2023_2185959 crossref_primary_10_1007_s00439_015_1585_y crossref_primary_10_1080_1744666X_2020_1850273 crossref_primary_10_3389_fpsyt_2021_554621 crossref_primary_10_1073_pnas_2206758120 crossref_primary_10_1093_nar_gkv816 crossref_primary_10_1016_j_jhazmat_2025_137214 crossref_primary_10_1016_j_ijdevneu_2016_12_006 crossref_primary_10_1097_MCD_0000000000000160 crossref_primary_10_1016_j_pbb_2021_173312 crossref_primary_10_2217_bmm_13_158 crossref_primary_10_1073_pnas_1912625116 crossref_primary_10_1002_ajmg_a_62173 crossref_primary_10_1038_s41598_018_26093_1 crossref_primary_10_3389_fneur_2020_584695 crossref_primary_10_1016_j_neuron_2017_03_026 crossref_primary_10_1016_j_envres_2023_115769 crossref_primary_10_1096_fj_201902677R crossref_primary_10_1242_jcs_261406 crossref_primary_10_18632_aging_202259 crossref_primary_10_1002_wrna_1280 crossref_primary_10_1186_s13229_015_0029_9 crossref_primary_10_1038_s42003_024_07332_w crossref_primary_10_1111_gbb_12430 crossref_primary_10_1007_s00702_022_02472_x crossref_primary_10_3389_fgene_2019_01186 crossref_primary_10_1093_hmg_ddy199 crossref_primary_10_1177_0271678X251322598 crossref_primary_10_1161_STROKEAHA_114_007482 crossref_primary_10_5853_jos_2016_01368 crossref_primary_10_1177_0883073815602067 crossref_primary_10_1016_j_neurobiolaging_2023_05_001 crossref_primary_10_1038_srep39663 crossref_primary_10_3389_fpsyt_2021_715346 crossref_primary_10_1186_s13229_015_0017_0 crossref_primary_10_1016_j_reprotox_2018_01_008 crossref_primary_10_1016_j_ygeno_2021_05_038 crossref_primary_10_1016_j_celrep_2022_110615 crossref_primary_10_1186_s13229_021_00417_x crossref_primary_10_1002_acn3_652 crossref_primary_10_3390_ijms18040828 crossref_primary_10_1016_j_bbagrm_2017_08_007 crossref_primary_10_1002_aur_3314 crossref_primary_10_1002_humu_24414 crossref_primary_10_3389_fgene_2021_749415 |
Cites_doi | 10.1016/j.neulet.2010.08.031 10.1016/j.bbi.2011.08.007 10.1007/978-0-387-77374-2_11 10.1016/j.conb.2012.04.008 10.1016/j.jchemneu.2011.10.002 10.1074/jbc.273.26.16319 10.1073/pnas.1121120109 10.1002/ana.20315 10.1523/JNEUROSCI.5714-09.2010 10.1016/S1567-133X(02)00019-4 10.1007/BF02172145 10.1074/jbc.M112.378901 10.1038/ng1295-376 10.1016/j.gde.2009.04.004 10.1073/pnas.0605414103 10.1203/PDR.0b013e318212f16b 10.1038/tp.2012.61 10.1111/j.1469-8749.2012.04316.x 10.1038/nature10989 10.1023/A:1023036509476 10.1016/j.bbi.2008.08.001 10.1016/S0006-291X(02)02378-1 10.1016/j.biopsych.2010.05.024 10.1001/jama.2010.1706 10.1073/pnas.0704964104 10.1002/jnr.23189 10.1016/j.bbaexp.2005.06.008 10.1242/jcs.014290 10.1016/j.molcel.2007.07.018 10.1023/A:1015337611258 10.1093/nar/gkn941 10.1038/mp.2008.63 10.1093/hmg/ddi482 10.1016/j.jneuroim.2010.10.025 10.1038/embor.2011.101 10.1158/0008-5472.CAN-12-3082 10.1038/sj.mp.4001953 10.1038/nm1201-1356 10.1016/j.nurt.2010.05.003 10.1136/jmg.2004.024646 10.1038/ng.835 10.1016/S0168-9525(01)02626-9 10.1186/2040-2392-3-12 10.1093/bioinformatics/btf877 10.1016/j.psychres.2010.04.057 10.1016/j.bbabio.2010.04.018 10.1007/s11064-012-0775-4 10.1016/j.cell.2008.10.017 10.1073/pnas.1107560108 10.1016/j.coi.2006.09.005 10.1196/annals.1381.009 10.1111/cge.12101 10.1051/medsci/2012282004 10.1016/j.cell.2008.10.016 10.1016/j.gene.2011.11.038 10.1016/j.cell.2009.03.010 10.1007/s12011-010-8840-9 10.1016/j.ygeno.2007.09.003 10.1016/j.freeradbiomed.2012.03.011 10.1007/s10803-011-1260-7 10.1038/nature10110 10.1093/hmg/ddl004 10.1016/j.conb.2012.05.004 10.1016/j.micinf.2007.06.009 10.1189/jlb.1205707 10.1371/journal.pone.0019076 10.1016/j.bbi.2009.08.001 10.1016/j.molcel.2011.05.027 10.1007/s10803-008-0674-3 10.1016/j.braindev.2012.03.011 10.1023/A:1005592401947 10.1126/science.1227764 10.1126/science.1138659 10.1523/JNEUROSCI.5178-12.2013 10.1038/mp.2011.155 10.1002/dvdy.21132 10.1667/RR1191.1 10.1016/j.tics.2011.07.003 10.1093/bfgp/elr020 10.1212/WNL.57.2.245 10.1002/ana.22673 10.1038/mp.2010.136 10.1007/s12035-011-8192-2 10.1001/archpsyc.62.12.1366 10.1186/gb-2007-8-4-r64 10.1097/WAD.0b013e31819d494e |
ContentType | Journal Article |
Copyright | COPYRIGHT 2013 BioMed Central Ltd. Copyright © 2013 Stamova et al.; licensee BioMed Central Ltd. 2013 Stamova et al.; licensee BioMed Central Ltd. |
Copyright_xml | – notice: COPYRIGHT 2013 BioMed Central Ltd. – notice: Copyright © 2013 Stamova et al.; licensee BioMed Central Ltd. 2013 Stamova et al.; licensee BioMed Central Ltd. |
DBID | AAYXX CITATION NPM 7X8 5PM |
DOI | 10.1186/2040-2392-4-30 |
DatabaseName | CrossRef PubMed MEDLINE - Academic PubMed Central (Full Participant titles) |
DatabaseTitle | CrossRef PubMed MEDLINE - Academic |
DatabaseTitleList | MEDLINE - Academic PubMed |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database |
DeliveryMethod | fulltext_linktorsrc |
EISSN | 2040-2392 |
EndPage | 30 |
ExternalDocumentID | PMC3846739 oai_biomedcentral_com_2040_2392_4_30 A534789582 24007566 10_1186_2040_2392_4_30 |
Genre | Journal Article |
GeographicLocations | United States |
GeographicLocations_xml | – name: United States |
GrantInformation_xml | – fundername: NIH HHS grantid: P51 OD011107 |
GroupedDBID | --- 0R~ 2VQ 4.4 53G 5VS 7RV 7X7 88E 8AO 8C1 8FI 8FJ AAFWJ AAJSJ AASML AAYXX ABDBF ABUWG ACGFS ACIHN ACUHS ADBBV ADRAZ ADUKV AEAQA AENEX AFKRA AFPKN AHBYD AHMBA AHSBF AHYZX ALIPV ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AOIJS AZQEC BAPOH BAWUL BCNDV BENPR BFQNJ BKEYQ BKNYI BMC BPHCQ BVXVI C6C CCPQU CITATION DIK DWQXO E3Z EBD EBLON EBS EJD ESX F5P FYUFA GNUQQ GROUPED_DOAJ GX1 H13 HMCUK HYE IAO IEA IHR IHW INH INR IPNFZ ITC K9- KQ8 M0R M1P M2M M48 M~E NAPCQ O5R O5S OK1 PGMZT PHGZM PHGZT PIMPY PQQKQ PROAC PSQYO PSYQQ RBZ RIG RNS ROL RPM RSV SMD SOJ TR2 TUS UKHRP NPM 7X8 -5E -5G -A0 -BR ABVAZ ACRMQ ADINQ AFGXO AFNRJ C24 5PM |
ID | FETCH-LOGICAL-b546t-212a7d68f2f0c531e33627604515ac86f96eed5658a24fc914af868a8d850a873 |
IEDL.DBID | RBZ |
ISSN | 2040-2392 |
IngestDate | Thu Aug 21 13:36:25 EDT 2025 Wed May 22 07:13:59 EDT 2024 Thu Jul 10 23:04:08 EDT 2025 Tue Jun 17 22:06:36 EDT 2025 Tue Jun 10 21:03:15 EDT 2025 Thu May 22 21:23:55 EDT 2025 Thu Apr 03 07:04:27 EDT 2025 Thu Apr 24 22:57:30 EDT 2025 Tue Jul 01 01:50:05 EDT 2025 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 1 |
Language | English |
License | This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-b546t-212a7d68f2f0c531e33627604515ac86f96eed5658a24fc914af868a8d850a873 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
OpenAccessLink | http://dx.doi.org/10.1186/2040-2392-4-30 |
PMID | 24007566 |
PQID | 1459151224 |
PQPubID | 23479 |
PageCount | 1 |
ParticipantIDs | pubmedcentral_primary_oai_pubmedcentral_nih_gov_3846739 biomedcentral_primary_oai_biomedcentral_com_2040_2392_4_30 proquest_miscellaneous_1459151224 gale_infotracmisc_A534789582 gale_infotracacademiconefile_A534789582 gale_healthsolutions_A534789582 pubmed_primary_24007566 crossref_citationtrail_10_1186_2040_2392_4_30 crossref_primary_10_1186_2040_2392_4_30 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2013-09-04 |
PublicationDateYYYYMMDD | 2013-09-04 |
PublicationDate_xml | – month: 09 year: 2013 text: 2013-09-04 day: 04 |
PublicationDecade | 2010 |
PublicationPlace | England |
PublicationPlace_xml | – name: England |
PublicationTitle | Molecular autism |
PublicationTitleAlternate | Mol Autism |
PublicationYear | 2013 |
Publisher | BioMed Central Ltd BioMed Central |
Publisher_xml | – name: BioMed Central Ltd – name: BioMed Central |
References | 10.1186/2040-2392-4-30-B115 10.1186/2040-2392-4-30-B112 10.1186/2040-2392-4-30-B111 10.1186/2040-2392-4-30-B114 10.1186/2040-2392-4-30-B113 10.1186/2040-2392-4-30-B37 10.1186/2040-2392-4-30-B39 10.1186/2040-2392-4-30-B110 10.1186/2040-2392-4-30-B38 10.1186/2040-2392-4-30-B33 10.1186/2040-2392-4-30-B77 10.1186/2040-2392-4-30-B32 10.1186/2040-2392-4-30-B76 10.1186/2040-2392-4-30-B79 10.1186/2040-2392-4-30-B73 10.1186/2040-2392-4-30-B72 10.1186/2040-2392-4-30-B31 10.1186/2040-2392-4-30-B75 10.1186/2040-2392-4-30-B30 10.1186/2040-2392-4-30-B71 10.1186/2040-2392-4-30-B70 10.1186/2040-2392-4-30-B109 10.1186/2040-2392-4-30-B108 10.1186/2040-2392-4-30-B105 10.1186/2040-2392-4-30-B104 10.1186/2040-2392-4-30-B107 10.1186/2040-2392-4-30-B106 10.1186/2040-2392-4-30-B101 10.1186/2040-2392-4-30-B29 10.1186/2040-2392-4-30-B103 10.1186/2040-2392-4-30-B26 10.1186/2040-2392-4-30-B25 - 10.1186/2040-2392-4-30-B22 10.1186/2040-2392-4-30-B65 10.1186/2040-2392-4-30-B24 10.1186/2040-2392-4-30-B68 10.1186/2040-2392-4-30-B23 10.1186/2040-2392-4-30-B67 10.1186/2040-2392-4-30-B62 10.1186/2040-2392-4-30-B61 10.1186/2040-2392-4-30-B20 10.1186/2040-2392-4-30-B63 10.1186/2040-2392-4-30-B60 10.1186/2040-2392-4-30-B19 10.1186/2040-2392-4-30-B18 10.1186/2040-2392-4-30-B15 10.1186/2040-2392-4-30-B59 10.1186/2040-2392-4-30-B58 10.1186/2040-2392-4-30-B17 10.1186/2040-2392-4-30-B16 10.1186/2040-2392-4-30-B11 10.1186/2040-2392-4-30-B99 10.1186/2040-2392-4-30-B10 10.1186/2040-2392-4-30-B54 10.1186/2040-2392-4-30-B12 10.1186/2040-2392-4-30-B51 10.1186/2040-2392-4-30-B95 10.1186/2040-2392-4-30-B50 10.1186/2040-2392-4-30-B94 10.1186/2040-2392-4-30-B97 10.1186/2040-2392-4-30-B96 10.1186/2040-2392-4-30-B90 10.1186/2040-2392-4-30-B93 10.1186/2040-2392-4-30-B92 10.1186/2040-2392-4-30-B8 10.1186/2040-2392-4-30-B7 10.1186/2040-2392-4-30-B6 10.1186/2040-2392-4-30-B5 10.1186/2040-2392-4-30-B9 10.1186/2040-2392-4-30-B4 10.1186/2040-2392-4-30-B3 10.1186/2040-2392-4-30-B47 10.1186/2040-2392-4-30-B2 10.1186/2040-2392-4-30-B49 10.1186/2040-2392-4-30-B44 10.1186/2040-2392-4-30-B88 10.1186/2040-2392-4-30-B43 10.1186/2040-2392-4-30-B87 10.1186/2040-2392-4-30-B46 10.1186/2040-2392-4-30-B89 10.1186/2040-2392-4-30-B84 10.1186/2040-2392-4-30-B86 10.1186/2040-2392-4-30-B41 10.1186/2040-2392-4-30-B85 10.1186/2040-2392-4-30-B81 |
References_xml | – ident: 10.1186/2040-2392-4-30-B19 doi: 10.1016/j.neulet.2010.08.031 – ident: 10.1186/2040-2392-4-30-B112 doi: 10.1016/j.bbi.2011.08.007 – ident: 10.1186/2040-2392-4-30-B92 doi: 10.1007/978-0-387-77374-2_11 – ident: 10.1186/2040-2392-4-30-B110 doi: 10.1016/j.conb.2012.04.008 – ident: 10.1186/2040-2392-4-30-B76 doi: 10.1016/j.jchemneu.2011.10.002 – ident: 10.1186/2040-2392-4-30-B101 doi: 10.1074/jbc.273.26.16319 – ident: 10.1186/2040-2392-4-30-B86 doi: 10.1073/pnas.1121120109 – ident: 10.1186/2040-2392-4-30-B109 doi: 10.1002/ana.20315 – ident: 10.1186/2040-2392-4-30-B32 doi: 10.1523/JNEUROSCI.5714-09.2010 – ident: 10.1186/2040-2392-4-30-B113 doi: 10.1016/S1567-133X(02)00019-4 – ident: 10.1186/2040-2392-4-30-B50 doi: 10.1007/BF02172145 – ident: 10.1186/2040-2392-4-30-B87 doi: 10.1074/jbc.M112.378901 – ident: 10.1186/2040-2392-4-30-B63 doi: 10.1038/ng1295-376 – ident: 10.1186/2040-2392-4-30-B3 doi: 10.1016/j.gde.2009.04.004 – ident: 10.1186/2040-2392-4-30-B85 doi: 10.1073/pnas.0605414103 – ident: 10.1186/2040-2392-4-30-B11 doi: 10.1203/PDR.0b013e318212f16b – ident: 10.1186/2040-2392-4-30-B67 doi: 10.1038/tp.2012.61 – ident: 10.1186/2040-2392-4-30-B41 doi: 10.1111/j.1469-8749.2012.04316.x – ident: 10.1186/2040-2392-4-30-B97 doi: 10.1038/nature10989 – ident: 10.1186/2040-2392-4-30-B33 doi: 10.1023/A:1023036509476 – ident: 10.1186/2040-2392-4-30-B59 doi: 10.1016/j.bbi.2008.08.001 – ident: 10.1186/2040-2392-4-30-B90 doi: 10.1016/S0006-291X(02)02378-1 – ident: 10.1186/2040-2392-4-30-B22 doi: 10.1016/j.biopsych.2010.05.024 – ident: 10.1186/2040-2392-4-30-B9 doi: 10.1001/jama.2010.1706 – ident: 10.1186/2040-2392-4-30-B15 doi: 10.1073/pnas.0704964104 – ident: 10.1186/2040-2392-4-30-B103 doi: 10.1002/jnr.23189 – ident: 10.1186/2040-2392-4-30-B114 doi: 10.1016/j.bbaexp.2005.06.008 – ident: 10.1186/2040-2392-4-30-B43 doi: 10.1242/jcs.014290 – ident: 10.1186/2040-2392-4-30-B16 doi: 10.1016/j.molcel.2007.07.018 – ident: 10.1186/2040-2392-4-30-B25 doi: 10.1023/A:1015337611258 – ident: 10.1186/2040-2392-4-30-B95 doi: 10.1093/nar/gkn941 – ident: 10.1186/2040-2392-4-30-B8 doi: 10.1038/mp.2008.63 – ident: 10.1186/2040-2392-4-30-B44 doi: 10.1093/hmg/ddi482 – ident: 10.1186/2040-2392-4-30-B54 doi: 10.1016/j.jneuroim.2010.10.025 – ident: 10.1186/2040-2392-4-30-B88 doi: 10.1038/embor.2011.101 – ident: 10.1186/2040-2392-4-30-B77 doi: 10.1158/0008-5472.CAN-12-3082 – ident: 10.1186/2040-2392-4-30-B89 doi: 10.1038/sj.mp.4001953 – ident: 10.1186/2040-2392-4-30-B20 doi: 10.1038/nm1201-1356 – ident: 10.1186/2040-2392-4-30-B23 doi: 10.1016/j.nurt.2010.05.003 – ident: 10.1186/2040-2392-4-30-B39 doi: 10.1136/jmg.2004.024646 – ident: 10.1186/2040-2392-4-30-B96 doi: 10.1038/ng.835 – ident: 10.1186/2040-2392-4-30-B46 doi: 10.1016/S0168-9525(01)02626-9 – ident: 10.1186/2040-2392-4-30-B73 doi: 10.1186/2040-2392-3-12 – ident: 10.1186/2040-2392-4-30-B58 doi: 10.1093/bioinformatics/btf877 – ident: 10.1186/2040-2392-4-30-B93 doi: 10.1016/j.psychres.2010.04.057 – ident: 10.1186/2040-2392-4-30-B7 doi: 10.1016/j.bbabio.2010.04.018 – ident: 10.1186/2040-2392-4-30-B72 doi: 10.1007/s11064-012-0775-4 – ident: 10.1186/2040-2392-4-30-B38 doi: 10.1016/j.cell.2008.10.017 – ident: 10.1186/2040-2392-4-30-B30 doi: 10.1073/pnas.1107560108 – ident: 10.1186/2040-2392-4-30-B108 doi: 10.1016/j.coi.2006.09.005 – ident: 10.1186/2040-2392-4-30-B24 doi: 10.1196/annals.1381.009 – ident: 10.1186/2040-2392-4-30-B4 doi: 10.1111/cge.12101 – ident: - doi: 10.1051/medsci/2012282004 – ident: 10.1186/2040-2392-4-30-B111 doi: 10.1016/j.cell.2008.10.016 – ident: 10.1186/2040-2392-4-30-B79 doi: 10.1016/j.gene.2011.11.038 – ident: 10.1186/2040-2392-4-30-B18 doi: 10.1016/j.cell.2009.03.010 – ident: 10.1186/2040-2392-4-30-B70 doi: 10.1007/s12011-010-8840-9 – ident: 10.1186/2040-2392-4-30-B60 doi: 10.1016/j.ygeno.2007.09.003 – ident: 10.1186/2040-2392-4-30-B71 doi: 10.1016/j.freeradbiomed.2012.03.011 – ident: 10.1186/2040-2392-4-30-B65 doi: 10.1007/s10803-011-1260-7 – ident: 10.1186/2040-2392-4-30-B5 doi: 10.1038/nature10110 – ident: 10.1186/2040-2392-4-30-B94 doi: 10.1093/hmg/ddl004 – ident: 10.1186/2040-2392-4-30-B37 doi: 10.1016/j.conb.2012.05.004 – ident: 10.1186/2040-2392-4-30-B12 doi: 10.1016/j.micinf.2007.06.009 – ident: 10.1186/2040-2392-4-30-B26 doi: 10.1189/jlb.1205707 – ident: 10.1186/2040-2392-4-30-B84 doi: 10.1371/journal.pone.0019076 – ident: 10.1186/2040-2392-4-30-B62 doi: 10.1016/j.bbi.2009.08.001 – ident: 10.1186/2040-2392-4-30-B107 doi: 10.1016/j.molcel.2011.05.027 – ident: 10.1186/2040-2392-4-30-B51 doi: 10.1007/s10803-008-0674-3 – ident: 10.1186/2040-2392-4-30-B68 doi: 10.1016/j.braindev.2012.03.011 – ident: 10.1186/2040-2392-4-30-B49 doi: 10.1023/A:1005592401947 – ident: 10.1186/2040-2392-4-30-B106 doi: 10.1126/science.1227764 – ident: 10.1186/2040-2392-4-30-B115 doi: 10.1126/science.1138659 – ident: 10.1186/2040-2392-4-30-B105 doi: 10.1523/JNEUROSCI.5178-12.2013 – ident: 10.1186/2040-2392-4-30-B61 doi: 10.1038/mp.2011.155 – ident: 10.1186/2040-2392-4-30-B75 doi: 10.1002/dvdy.21132 – ident: 10.1186/2040-2392-4-30-B17 doi: 10.1667/RR1191.1 – ident: 10.1186/2040-2392-4-30-B2 doi: 10.1016/j.tics.2011.07.003 – ident: 10.1186/2040-2392-4-30-B81 doi: 10.1093/bfgp/elr020 – ident: 10.1186/2040-2392-4-30-B29 doi: 10.1212/WNL.57.2.245 – ident: 10.1186/2040-2392-4-30-B104 doi: 10.1002/ana.22673 – ident: 10.1186/2040-2392-4-30-B10 doi: 10.1038/mp.2010.136 – ident: 10.1186/2040-2392-4-30-B6 doi: 10.1007/s12035-011-8192-2 – ident: 10.1186/2040-2392-4-30-B31 doi: 10.1001/archpsyc.62.12.1366 – ident: 10.1186/2040-2392-4-30-B47 doi: 10.1186/gb-2007-8-4-r64 – ident: 10.1186/2040-2392-4-30-B99 doi: 10.1097/WAD.0b013e31819d494e |
SSID | ssj0000314442 |
Score | 2.2044199 |
Snippet | Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing (DAS) has been... Background Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing... BACKGROUND: Since RNA expression differences have been reported in autism spectrum disorder (ASD) for blood and brain, and differential alternative splicing... |
SourceID | pubmedcentral biomedcentral proquest gale pubmed crossref |
SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source |
StartPage | 30 |
SubjectTerms | Autistic children Comparative analysis Computer software industry Gene expression Genes Genetic aspects Genomes Glutathione transferase Medical genetics Molecular genetics Pervasive developmental disorders RNA splicing Superoxide |
SummonAdditionalLinks | – databaseName: Scholars Portal Journals: Open Access dbid: M48 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3fa9swEBZt-rKXstF2zZZ1Ggz2pOJYsiQPxihlJQzSpwb6JmRbooHEaesWlv9-d4qdRk0Lfdb5l3Sn7866-46Q77JwFaCQYC51gokqKZj2GWdOQTThlR1KiYXC40s5moi_19n1U_5TO4HNi6Ed9pOa3M9O_90tf4PB_woGryXE7yJhKQA9w5_8u2QPUElhN4Nx6-qHXZlD6BB66azFWw7H7Vs8K36fRZj1fOfegK44rXIDpy7ek_3WwaRnK434QHZcfUCqrnkoBR-Vdk1RwLhnNByX14H-mzZ4mA1YRqc1DRntdOHpEvcDWiyWDcWfttSCqjZzGko07x_ntGr5O5tDMrn4c3U-Ym1_BVZkQj4wQC2rKql96pMSbNFxQDMlkXEms6WWPpeAoODxaZsKX-ZDYb2W2upKZ4nVih-RXr2o3TGhlVPcFxgNlVYIP8w9khwL8EYTuC5P-uRnNKPmdsWlYZDdOh4BQzO4HAaXwwjD4WLWTb8pW-ZybKAxMyGC0XJL_sdavnvOa5JfcTXNquZ0bezmLONC6TzTKdwrSKACwjNL21YtwGcjcVYkOYgkwUzLaPhbpzEGhzC3rXaLxwaCryxHvysVffJxpUHr18YMXwUed5-oSLei-YtH6ulNYAnn6Fny_NObP-AzeZeGXh94WjYgPdAh9wU8rofiJJjSf_7MKDM priority: 102 providerName: Scholars Portal |
Title | Evidence for differential alternative splicing in blood of young boys with autism spectrum disorders |
URI | https://www.ncbi.nlm.nih.gov/pubmed/24007566 https://www.proquest.com/docview/1459151224 http://dx.doi.org/10.1186/2040-2392-4-30 https://pubmed.ncbi.nlm.nih.gov/PMC3846739 |
Volume | 4 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1NT9wwELUoXHqpQNB2W1iMVKknS9lkYjvcFgRarQQXioR6sZzEVpGWLGrgwL_vjDcJeFc9ccnFk4-1Z_bNjD1vGPshS1cjCoFwqQMBdVIK7fNMOIXRhFd2IiUVCl9dy9ktzO_yu9d8x9oO_kRLjM4hESnCuKAU_ge2kwKGcxSXn_0esilEwg6hU84g3jE0bj5irbR9ESHS-v_yG2CKD02-QaHLXfapcx_5dLXee2zLNfus7luDcvRAed_yBE13wcNmeBPIvXlLW9WIVPy-4eG8Ol96_kLWzsvlS8spJcstKmL7wEMB5t_nB1537JztAbu9vPh1PhNd9wRR5iCfBGKSVbXUPvVJhZbmMsQqJYlPJreVlr6QiI_oz2mbgq-KCVivpba61nlitco-s-1m2bivjNdOZb6kWKeyAH5SeKIwBvQ1E7yvSEbsNJpR87hiyjDEXR2PoBkZWg5Dy2HAZHiz6KffVB0vObXHWJgQn2i5If9zkO_f8z_JY1pNs6ooHUzZTPMMlC5yneKzggQZM76zsl1NAv5sosWKJA8jSTTCKho-6TXG0BCdXGvc8rnF0CovyKtKYcS-rDRo-Gw6v6vQnx4xFelWNH_xSHP_J3CAZ-Q3ZsW398z8d_YxDc09aHvskG2jWrkjdLGeyjHbmU7nN_NxSFHg9Qr0OFjcP9-mJY0 |
linkProvider | BioMedCentral |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LT9wwELYKPcAFgUphW9o1EhIno2ziV3pbqqJtC5xAQr1YTmILpN0sauDAv2fGeWgN4sTZE9sZezwz9sw3hBzJwlWghThzqeOMV0nBtBcZcwq8Ca_sREpMFL64lLNr_udG3HSQQpgLs-iLwlrge7M4WU1Cn4eTuw8Ya-VdS3DfecJS0PMM7_jXyEclhAqpXKf_husWRGnnoZTOQN5BOL7u4kXu-zxSWS8P7hXNFUdVrqips22y1dmXdNpOf4d8cPUnUvW1QymYqLSviQKyPafhtbwO6N-0wbdsUGX0rqYhoJ0uPX3C44AWy6eG4p0tbTlGQ4bm_8cFrTr4zmaXXJ_9uvo5Y115BVYILh8YKC2rKql96pMSRNFloMyURMAZYUstfS5BgYLBp23KfZlPuPVaaqsrLRKrVfaZrNfL2u0TWjmV-QKdodJy7ie5R4xjDsZoAt_lyYj8iDhq7lsoDYPg1nELLLHB5TC4HIabDD5mPftN2QGXY_2MuQkOjJav6I8H-n6ctyjHuJqmTTkdZN1MRcaVzoVOoa9AgdIOY5a2S1qA30bcrIjyIKIEKS2j5sN-xxhswtC22i0fG_C9RI5mV8pHZK_dQcO0McBXgcE9IiraWxH_4pb67jaAhGdoWGb5l_dwfkw2ZlcX5-b89-Xfr2QzDZVA8C3tgKzDFnPfwB57KL4HSXsG6qUyzQ |
linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LT9wwELYoSFUvqAjaLuXhSkg9uc0mfqU3XivoAyFUJNSL5SS2irqbRQ0c-PfMOA-tQZy4RfLkNZ7xzNgz3xCyJwtXgRXizKWOM14lBdNeZMwpiCa8smMpsVD415k8ueTfr8RVl_-EtTCzvimsBb43sy-LRejTsHLDRfnv603lW4XXEuJ3nrAUDD3DTf5XZEUJobCbwcXBn2G_BWHaeeilM5B3GI5PH_Go-H0a2azHK_eC6YrTKhfs1OQtWe0cTLrfSsQaWXL1Oqn65qEUfFTaN0UB5Z7ScFxeB_hv2uBhNtgyel3TkNFO557e43pAi_l9Q3HTlrYso6FE8__djFYdfmezQS4nx78PT1jXX4EVgstbBlbLqkpqn_qkBF10GVgzJRFxRthSS59LsKDg8Wmbcl_mY269ltrqSovEapW9I8v1vHYfCK2cynyB0VBpOffj3CPIMQdvNIH78mREvkUcNTctloZBdOt4BObY4HQYnA7DTQY3s579puyQy7GBxtSECEbLJ_SfB_r-Pc9R7uJsmrbmdFB2sy8yrnQudArPChSo7ih5tqtagN9G4KyIciuiBDUto-FPvcQYHMLcttrN7xoIvkSOflfKR-R9K0HDZ2OGrwKPe0RUJFsR_-KR-vpvQAnP0LPM8s2XcH6XvD4_mpifp2c_PpI3aegEgmdpW2QZJMxtgz92W-wERXsAXXcymA |
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=Evidence+for+differential+alternative+splicing+in+blood+of+young+boys+with+autism+spectrum+disorders&rft.jtitle=Molecular+autism&rft.au=Stamova%2C+Boryana+S&rft.au=Tian%2C+Yingfang&rft.au=Nordahl%2C+Christine+W&rft.au=Shen%2C+Mark+D&rft.date=2013-09-04&rft.pub=BioMed+Central+Ltd&rft.issn=2040-2392&rft.eissn=2040-2392&rft.volume=4&rft_id=info:doi/10.1186%2F2040-2392-4-30&rft.externalDocID=A534789582 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2040-2392&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2040-2392&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2040-2392&client=summon |