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Article: Integrated analysis of gait parameters and gene expression profiles in a murine model of subarachnoid hemorrhage

TitleIntegrated analysis of gait parameters and gene expression profiles in a murine model of subarachnoid hemorrhage
Authors
KeywordsCatWalk
gait variability
SP1
stroke
subarachnoid hemorrhage
Issue Date2021
Citation
Genes, Brain and Behavior, 2021, v. 20, n. 5, article no. e12728 How to Cite?
AbstractGait analysis has been widely used to examine the behavioral presentation of numerous neurological disorders. Thorough murine model evaluation of the subarachnoid hemorrhage (SAH)-associated gait deficits is missing. This study measures gait deficits using a clinically relevant murine model of SAH to examine associations between gait variability and SAH-associated gene expressions. A total of 159 dynamic and static gait parameters from the endovascular perforation murine model for simulating clinical human SAH were determined using the CatWalk system. Eighty gait parameters and the mRNA expression levels of 35 of the 88 SAH-associated genes were differentially regulated in the diseased models. Totals of 42 and 38 gait parameters correlated with the 35 SAH-associated genes positively and negatively with Pearson's correlation coefficients of >0.7 and <−0.7, respectively. p-SP1453 expression in the motor cortex in SAH animal models displays a significant correlation with a subset of gait parameters associated with muscular strength and coordination of limb movements. Our data highlights a strong correlation between gait variability and SAH-associated gene expression. p-SP1453 expression could act as a biomarker to monitor SAH pathological development and a therapeutic target for SAH.
Persistent Identifierhttp://hdl.handle.net/10722/325518
ISSN
2021 Impact Factor: 3.708
2020 SCImago Journal Rankings: 1.315

 

DC FieldValueLanguage
dc.contributor.authorZheng, Zhi Yuan-
dc.contributor.authorLu, Gang-
dc.contributor.authorXiong, Zhi Qiang-
dc.contributor.authorLeung, Chi Kwan-
dc.contributor.authorSu, Xian Wei-
dc.contributor.authorLi, Tu-
dc.contributor.authorPoon, Wai Sang-
dc.contributor.authorChan, Wai Yee-
dc.contributor.authorWong, George Kwok Chu-
dc.date.accessioned2023-02-27T07:33:57Z-
dc.date.available2023-02-27T07:33:57Z-
dc.date.issued2021-
dc.identifier.citationGenes, Brain and Behavior, 2021, v. 20, n. 5, article no. e12728-
dc.identifier.issn1601-1848-
dc.identifier.urihttp://hdl.handle.net/10722/325518-
dc.description.abstractGait analysis has been widely used to examine the behavioral presentation of numerous neurological disorders. Thorough murine model evaluation of the subarachnoid hemorrhage (SAH)-associated gait deficits is missing. This study measures gait deficits using a clinically relevant murine model of SAH to examine associations between gait variability and SAH-associated gene expressions. A total of 159 dynamic and static gait parameters from the endovascular perforation murine model for simulating clinical human SAH were determined using the CatWalk system. Eighty gait parameters and the mRNA expression levels of 35 of the 88 SAH-associated genes were differentially regulated in the diseased models. Totals of 42 and 38 gait parameters correlated with the 35 SAH-associated genes positively and negatively with Pearson's correlation coefficients of >0.7 and <−0.7, respectively. p-SP1453 expression in the motor cortex in SAH animal models displays a significant correlation with a subset of gait parameters associated with muscular strength and coordination of limb movements. Our data highlights a strong correlation between gait variability and SAH-associated gene expression. p-SP1453 expression could act as a biomarker to monitor SAH pathological development and a therapeutic target for SAH.-
dc.languageeng-
dc.relation.ispartofGenes, Brain and Behavior-
dc.subjectCatWalk-
dc.subjectgait variability-
dc.subjectSP1-
dc.subjectstroke-
dc.subjectsubarachnoid hemorrhage-
dc.titleIntegrated analysis of gait parameters and gene expression profiles in a murine model of subarachnoid hemorrhage-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/gbb.12728-
dc.identifier.pmid33641236-
dc.identifier.scopuseid_2-s2.0-85102176029-
dc.identifier.volume20-
dc.identifier.issue5-
dc.identifier.spagearticle no. e12728-
dc.identifier.epagearticle no. e12728-
dc.identifier.eissn1601-183X-

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