Objective: A subarachnoid hemorrhage is neurologically devastating, with 50% of patients becoming disabled or deceased. Advent of Guglielmi detachable coils in 1995 permitted endovascular treatment of cerebral aneurysms. Coiling is efficacious and safe, but durability needs improvement, as nearly 20% of patients require further invasive intervention secondary to aneurysm recurrence. The aim of this study is to develop an in vitro model of endothelial cell (EC) proliferation and differentiation on four types of platinum-based coils, using gene expression profiling to understand EC biology as they colonize and differentiate on coils.
Methods: Human umbilical vein ECs were grown in vitro on platinum coil segments. Growth patterns were assessed as a function of coil type. Gene expression profiles for coil attached versus coil unattached ECs were determined using immunohistochemistry and gene array analysis.
Results: ECs showed rapid, robust attachment to all coil types. Some detachment occurred within 24-48 hours. Significant growth of remaining attached cells occurred during the next week, creating a confluence on coils and within coil grooves. Similar growth curve results were obtained with human brain ECs on platinum-based coil surfaces. Differentiation markers in attached cells (α(1), α(2), β(1) integrins) were expressed on immunostaining, whereas microarray gene expression revealed 48 up-regulated and 68 down-regulated genes after 24-hour growth on coils. Major pathways affected as a function of time of colonization on coils and coil type included those involved in regulation of cell cycle and cell signaling.
Conclusions: We developed an in vitro model for evaluating endothelialization of platinum coils to optimize coil design to support robust EC colonization and differentiation.
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http://dx.doi.org/10.1016/j.wneu.2013.08.029 | DOI Listing |
Cancer Rep (Hoboken)
January 2025
Department of Medical Biotechnology, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran.
Background: Bioinformatics analysis of hepatocellular carcinoma (HCC) expression profiles can aid in understanding its molecular mechanisms and identifying new targets for diagnosis and treatment.
Aim: In this study, we analyzed expression profile datasets and miRNA expression profiles related to HCC from the GEO using R software to detect differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs).
Methods And Results: Common DEGs were identified, and a PPI network was constructed using the STRING database and Cytoscape software to identify hub genes.
Postgrad Med J
January 2025
Department of Pediatric Metabolic Diseases, University of Health Sciences, Ankara Etlik City Hospital, Ankara 06170, Turkey.
Metabolism is the name given to all of the chemical reactions in the cell involving thousands of proteins, including enzymes, receptors, and transporters. Inborn errors of metabolism (IEM) are caused by defects in the production and breakdown of proteins, fats, and carbohydrates. Micro ribonucleic acids (miRNAs) are short non-coding RNA molecules, ⁓19-25 nucleotides long, hairpin-shaped, produced from DNA.
View Article and Find Full Text PDFCNS Neurosci Ther
January 2025
Department of Neurology, School of Medicine, Guangzhou First People's Hospital, South China University of Technology, Guangzhou, China.
Objective: This study aims to investigate how the E3 ubiquitin ligase LITAF influences mitochondrial autophagy by modulating MCL-1 ubiquitination, and its role in the development of epilepsy.
Methods: Employing single-cell RNA sequencing (scRNA-seq) to analyze brain tissue from epilepsy patients, along with high-throughput transcriptomics, we identified changes in gene expression. This was complemented by in vivo and in vitro experiments, including protein-protein interaction (PPI) network analysis, western blotting, and behavioral assessments in mouse models.
Brief Bioinform
November 2024
Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, No. 15 Shangxiadian Road, Cangshan District, Fuzhou 350002, China.
Spatial transcriptomics (ST) technologies enable dissecting the tissue architecture in spatial context. To perceive the global contextual information of gene expression patterns in tissue, the spatial dependence of cells must be fully considered by integrating both local and non-local features by means of spatial-context-aware. However, the current ST integration algorithm ignores for ST dropouts, which impedes the spatial-aware of ST features, resulting in challenges in the accuracy and robustness of microenvironmental heterogeneity detecting, spatial domain clustering, and batch-effects correction.
View Article and Find Full Text PDFPest Manag Sci
January 2025
Key Laboratory of Plant Protection Resources and Pest Management of the Ministry of Education, Key Laboratory of Integrated Pest Management on the Loess Plateau of Ministry of Agriculture and Rural Affairs, College of Plant Protection, Northwest A&F University, Yangling, China.
Background: The function of some testis-specific genes (TSGs) in model insects have been studied, but their function in non-model insects remains largely unexplored. In the present study, we identified several TSGs in the fall armyworm (FAW), a significant agricultural pest, through comparative transcriptomic analysis. A testis-specific gene cluster (TSGC) comprising multiple functional genes and long non-coding RNAs was found.
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