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Vascular Endothelial Cells

Vascular endothelial cells are the thin layer of squamous epithelial cells that line the interior surface of blood vessels, forming an interface between circulating blood in the lumen and the vessel wall.
These cells play a crucial role in maintaining vascular homeostasis, regulating blood flow, and facilitating nutrient and waste exchange.
Dysfunction of vascular endothelial cells has been implicated in the pathogenesis of various cardiovascular and metabolic disorders, making them an important target for research and therapeutic interventions.
Undrstanding the biology and behavior of vascular endothelial cells is crucial for advancing our knowledge of vascular physiology and developing effective treatments for vascular-related diseases.

Most cited protocols related to «Vascular Endothelial Cells»

1
Comprehensive DNA Methylation Profiling Across Cell Types
All DNA methylation profiles were determined either on the Illumina Infinium Human Methylation 450K or EPIC BeadChip arrays. DNA methylation data for white blood cells (neutrophils, monocytes, B-cells, CD4+ T-cells, CD8+ T-cells, NK-cells, n = 6 each) were downloaded from GSE110555 (EPIC)38 (link). Data for erythrocyte progenitors (n = 5) were downloaded from GSE63409 (450K)39 (link), and data for left atrium (n = 4) were downloaded from GSE62727 (450K)40 (link). Data for bladder (n = 19), breast (n = 98), cervix (n = 3), colon (n = 38), esophagus (n = 16), oral cavity (n = 34), kidney (n = 160), prostate (n = 50), rectum (n = 7), stomach (n = 2), thyroid (n = 56), and uterus (n = 34) were downloaded from TCGA26 (link). DNA methylation data for adipocytes (n = 3, 450K), hepatocytes (n = 3, 450K and EPIC), alveolar lung cells (n = 3, EPIC), neurons (n = 3, 450K and EPIC), vascular endothelial cells (n = 2, EPIC) pancreatic acinar cells (n = 3, 450K and EPIC), duct cells (n = 3, 450K and EPIC), beta cells (n = 4, 450K and EPIC), colon epithelial cells (n = 3, EPIC) were generated in house and are available from the corresponding authors upon reasonable request. Detailed sample information is available in Supplementary Data 1.
Moss J., Magenheim J., Neiman D., Zemmour H., Loyfer N., Korach A., Samet Y., Maoz M., Druid H., Arner P., Fu K.Y., Kiss E., Spalding K.L., Landesberg G., Zick A., Grinshpun A., Shapiro A.M., Grompe M., Wittenberg A.D., Glaser B., Shemer R., Kaplan T, & Dor Y. (2018). Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease. Nature Communications, 9, 5068.
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Publication 2018
Acinar Cell Adipocytes Alveolar Epithelial Cells Atrium, Left B-Lymphocytes Breast CD4 Positive T Lymphocytes CD8-Positive T-Lymphocytes Cells Cervix Uteri Colon DNA Methylation Epithelial Cells Erythrocytes Esophagus Hepatocyte Homo sapiens Kidney Leukocytes Lung Methylation Monocytes Natural Killer Cells Neurons Neutrophil Oral Cavity Pancreas Pancreatic beta Cells Prostate Rectum Stomach Thyroid Gland Urinary Bladder Uterus Vascular Endothelial Cells
2
Functional Annotation of Coronary Artery Disease Variants
Variants were annotated using the ANNOVAR18 (link) (version Aug 2013) software based on a GRCh/hg19 gene annotation database. Upstream/downstream status was assigned to variants that mapped ≤1kb from the transcript start/end. Variants without intergenic annotation were assigned a genic annotation status (42%). Supplementary Table 8 shows the annotation status of 9.4M variants included in the CAD additive meta-analysis; 86% of the genic variants map to introns.
ENCODE features were downloaded from the Ensembl database using the Funcgen Perl API module release 75. The list of the ENCODE experiments stored in the Ensembl database can be browsed at http://Feb2014.archive.ensembl.org/Homo_sapiens/Experiment/Sources?db=core;ex=project-ENCODE-. This summarized 100 different types of functional evidence in 11 different cell types, a total of 379 ENCODE experiments that revealed 6,099,034 features. Variants that overlaid one or more of these features were cross-tabulated with their ANNOVAR annotation status (Supplementary Table 10); 50% of variants mapped to one or more ENCODE features and variants in ENCODE features were strongly enriched for genic annotation status. Variants were grouped into three functional sets, histone/chromatin modifications (HM), DNase I hypersensitive sites (DHS) and transcription factor binding sites (TFBS) (Supplementary Table 9). Cell types were grouped into CAD relevant and others (Supplementary Table 12) based on their potential roles in CAD pathophysiology; hepatocytes (e.g. lipid metabolism80 ), vascular endothelial cells (atherosclerosis81 ) and myoblasts (injury/repair82 ) were selected as being most relevant to the CAD phenotype. Multi-way contingency tables reporting ENCODE feature and ANNOVAR annotation status with inclusion in the FDR < 5% variant list (FDR202 status) are summarized for 11 ENCODE cell types in Supplementary Table 11 and for the three CAD relevant cell types in Supplementary Table 13. Contingency table counts were modelled by a logistic multiple regression model predicting FDR202 status with independent explanatory variables HM, DHS, TFBS and genic/intergenic status. The ENCODE83 project has previously mapped 4,492 GWAS significant SNPs from the NHGRI (June 2011) catalogue74 to TF (12%) and DHS (34%) features in an extended dataset of 1,640 experiments. The 202 FDR variants were slightly less prevalent in these feature groups (10.4% TF and 19.8% DHS) which could reflect a CAD-specific issue or a more general consequence of our analysis being based on a subset of the ENCODE data retrieved from the Ensembl database.
Nikpay M., Goel A., Won H.H., Hall L.M., Willenborg C., Kanoni S., Saleheen D., Kyriakou T., Nelson C.P., Hopewell J.C., Webb T.R., Zeng L., Dehghan A., Alver M., Armasu S.M., Auro K., Bjonnes A., Chasman D.I., Chen S., Ford I., Franceschini N., Gieger C., Grace C., Gustafsson S., Huang J., Hwang S.J., Kim Y.K., Kleber M.E., Lau K.W., Lu X., Lu Y., Lyytikäinen L.P., Mihailov E., Morrison A.C., Pervjakova N., Qu L., Rose L.M., Salfati E., Saxena R., Scholz M., Smith A.V., Tikkanen E., Uitterlinden A., Yang X., Zhang W., Zhao W., de Andrade M., de Vries P.S., van Zuydam N.R., Anand S.S., Bertram L., Beutner F., Dedoussis G., Frossard P., Gauguier D., Goodall A.H., Gottesman O., Haber M., Han B.G., Huang J., Jalilzadeh S., Kessler T., König I.R., Lannfelt L., Lieb W., Lind L., Lindgren C.M., Lokki M.L., Magnusson P.K., Mallick N.H., Mehra N., Meitinger T., Memon F.U., Morris A.P., Nieminen M.S., Pedersen N.L., Peters A., Rallidis L.S., Rasheed A., Samuel M., Shah S.H., Sinisalo J., Stirrups K.E., Trompet S., Wang L., Zaman K.S., Ardissino D., Boerwinkle E., Borecki I.B., Bottinger E.P., Buring J.E., Chambers J.C., Collins R., Cupples L.A., Danesh J., Demuth I., Elosua R., Epstein S.E., Esko T., Feitosa M.F., Franco O.H., Franzosi M.G., Granger C.B., Gu D., Gudnason V., Hall A.S., Hamsten A., Harris T.B., Hazen S.L., Hengstenberg C., Hofman A., Ingelsson E., Iribarren C., Jukema J.W., Karhunen P.J., Kim B.J., Kooner J.S., Kullo I.J., Lehtimäki T., Loos R.J., Melander O., Metspalu A., März W., Palmer C.N., Perola M., Quertermous T., Rader D.J., Ridker P.M., Ripatti S., Roberts R., Salomaa V., Sanghera D.K., Schwartz S.M., Seedorf U., Stewart A.F., Stott D.J., Thiery J., Zalloua P.A., O’Donnell C.J., Reilly M.P., Assimes T.L., Thompson J.R., Erdmann J., Clarke R., Watkins H., Kathiresan S., McPherson R., Deloukas P., Schunkert H., Samani N.J, & Farrall M. (2015). A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nature genetics, 47(10), 1121-1130.
Publication 2015
Binding Sites Cells Chromatin Deoxyribonuclease I Gene Annotation Genes Genetic Diversity Genome-Wide Association Study Hepatocyte Histone Code Homo sapiens Hypersensitivity Injuries Introns Lipids Myoblasts Phenotype Single Nucleotide Polymorphism Transcription Factor Vascular Endothelial Cells
3
Endothelial-Specific Epac1 Knockout
All animal procedures met the Association for Research in Vision and Ophthalmology requirements, were approved by the Institutional Animal Care and Use Committee of Wayne State University, and conformed to National Institutes of Health (NIH) guidelines. The Epac1 floxed mice (B6;129S2-Rapgef3tm1Geno/J mice) and the B6 FVB-Tg (Cdh5-Cre)7Mlia/J Cre mice were purchased from Jackson Laboratories (Bar Harbor, ME). After two generations, the Epac1 floxed mice were bred with the Cdh5-Cre mice to generate conditional knockout mice in which Epac1 is eliminated in vascular endothelial cells. At 3 months of age, the Epac1 floxed and Epac1 Cre-Lox mice were used for these experiments. Euthanasia was performed with carbon dioxide overdose followed by cervical dislocation.
Liu L., Jiang Y., Chahine A., Curtiss E, & Steinle J.J. (2017). Epac1 agonist decreased inflammatory proteins in retinal endothelial cells, and loss of Epac1 increased inflammatory proteins in the retinal vasculature of mice. Molecular Vision, 23, 1-7.
Publication 2017
Animals Carbon dioxide CDH5 protein, human Drug Overdose Euthanasia Institutional Animal Care and Use Committees Joint Dislocations Mice, Knockout Mice, Laboratory Neck Vascular Endothelial Cells Vision
4
Modeling Heterogeneous Tumor Response to Radiotherapy
The model assumes that a tumour is comprised of many small subsets (‘tumourlets’) that mathematically are considered homogeneous. That is, the variance inside a tumourlet was not considered.
The tumourlet might be identified with a given voxel at the treatment planning phase, based on pre-RT PET images. Here, each tumourlet was considered to be independent from each other and have a variable size over the course of therapy, with a constant number of tumourlets in a tumour. The initial number of cells in a tumourlet generally decreases during RT with volume shrinkage, although the volume might even increase if the treatment is not sufficient to counteract tumour growth. This is therefore not, strictly speaking, a ‘voxel’ simulation, except in the sense that a tumourlet could be identified with a given voxel at the treatment planning phase.
For purposes of modelling, we assume that each tumourlet has a constant blood (oxygen and nutrient) supply over a course of RT. This simplifies the model, and allows us to introduce the fundamental idea of the model, which is that every tumourlet has an inherent blood supply available and therefore, an inherent proliferative cell capacity. It seems likely there is some variation in blood flow during RT, the impact of variations in blood flow in our simulations (reported below) showed that this has only a modest impact. Given that the tumour vasculature (especially larger vessels) is relatively radioresistant and the damage to vascular endothelial cells in conventional RT is manifested in a relatively late phase of RT, the change of blood supply during RT might not be extensive (Park et al 2012 (link)). However, this would not be true for acute (or transient) hypoxia, in which the blood supply changes over a short period of time. It would not be difficult to include temporal changes in blood supply in the model. However, initially we focus on effects from non-transient (diffusion limited) hypoxia in this work.
Jeong J., Shoghi K.I, & Deasy J.O. (2013). Modelling the interplay between hypoxia and proliferation in radiotherapy tumour response. Physics in medicine and biology, 58(14), 4897-4919.
Publication 2013
BLOOD Blood Circulation Blood Vessel Cells Diffusion Hypoxia Neoplasms Nutrients Oxygen Transients Vascular Endothelial Cells
5
Physiologically-Based Pharmacokinetic Model for Protein Therapeutics
The PBPK model for proteins was built as an extension of the PBPK model for small molecule drugs implemented within the software PK-Sim [33 (link)–36 (link)] (http://open-systems-pharmacology.org). As for the PBPK model for small molecules, it contains 15 organs or tissues and distinct blood pool compartments. Specifically, the represented organs/tissues include adipose tissue, brain, bone, gonads, heart, kidneys, large intestine, small intestine, liver, lung, muscle, pancreas, skin, spleen, stomach as well as the blood pool compartments arterial blood, venous blood and portal vein blood. For the substructure of the small and large intestine representation refer to [36 (link)]. Each organ consists of sub-compartments representing the plasma, blood cells (which together form the vascular space), interstitial space and cellular space. All physiologic parameters (organ volumes, fraction of interstitial, vascular and cellular space of the organs, blood flow rates and hematocrit) for the different species were used from the small molecule model without changes [42 (link)–44 (link)].
For the PBPK model for proteins, an additional compartment was added for each organ representing the endosomes and lysosomes within vascular endothelial cells. In this endosomal space compartment, lysosomal degradation and high affinity FcRn binding is located. Since the model was derived from a PBPK model for small molecule drugs, cellular space is explicitly represented. However, the permeability for passive diffusion into cells was neglected for all drugs in the present study, since this process is not relevant for macromolecules or very hydrophilic drugs like inulin. The explicit representation of cellular space is relevant to describe active uptake into cells when necessary (e.g., internalization of protein drug bound to membrane surface receptors). Additionally, organ-specific lymph flow (Lorg) was integrated into the model for protein therapeutics connecting the interstitial space of each organ to the venous blood pool using the rate equation Jip,org=Lorg·Ci,org with Jip,org being the flux rate of drug from the interstitial space of organ org to the central venous blood plasma pool and Ci,org the drug concentration in interstitial space.
A scheme of the PBPK model structure for protein therapeutics showing how organs are connected by blood and lymph flow is given in Fig. 1.

Scheme of the PBPK model for protein therapeutics showing connection of organs by blood and lymph flow. For the substructure of the small and large intestine cf. [36 (link)]

Niederalt C., Kuepfer L., Solodenko J., Eissing T., Siegmund H.U., Block M., Willmann S, & Lippert J. (2017). A generic whole body physiologically based pharmacokinetic model for therapeutic proteins in PK-Sim. Journal of Pharmacokinetics and Pharmacodynamics, 45(2), 235-257.
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Publication 2017
Arteries BLOOD Blood Cells Blood Circulation Blood Vessel Bones Brain Cells Diffusion Endosomes Gonads Heart Intestines, Small Inulin Kidney Large Intestine Liver Lung Lymph Lysosomes Muscle Tissue Organ Volume Pancreas Permeability Pharmaceutical Preparations physiology Plasma Proteins Skin Spleen Stomach Therapeutics Tissue, Adipose Tissue, Membrane Tissues Vascular Endothelial Cells Veins Veins, Portal Volumes, Packed Erythrocyte

Most recents protocols related to «Vascular Endothelial Cells»

1
Assessing Blood-Brain Barrier Integrity
The sections made from rats selected using single-blinding were incubated with anti-occludin (Solarbio) and anti-ZO-1 (Solarbio) antibodies at 4°C overnight (Jin et al., 2021 (link)). After being washed with PBS, they were incubated together with the fluorescence-conjugated secondary antibody (Solarbio) at 25°Cfor for 1 h. In addition, the vascular endothelial cell markers CD31 were co-immunostaining with Zo-1 and occludin to observe the BBB integrity. The histopathological changes in the brain could be observed using a fluorescence microscope. The results were analyzed using ImageJ software.
Xu S., Li X., Li Y., Li X., Lv E., Zhang X., Shi Y, & Wang Y. (2023). Neuroprotective effect of Dl-3-n-butylphthalide against ischemia–reperfusion injury is mediated by ferroptosis regulation via the SLC7A11/GSH/GPX4 pathway and the attenuation of blood–brain barrier disruption. Frontiers in Aging Neuroscience, 15, 1028178.
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Publication 2023
Antibodies Brain Fluorescent Antibody Technique Microscopy, Fluorescence Occludin Rattus Vascular Endothelial Cells
2
Immunofluorescence Analysis of AQP4 and CD31
The rest of the five rats in each group were selected for immunofluorescence. Rats were deeply anesthetized with 50 mg/kg of 10% chloral hydrate intraperitoneally and immobilized by transcardiac perfusion with 200 ml of sterile control saline and 200 ml of 4% paraformaldehyde in 0.1 mol/l PBS (PH, 7.4). After standard fixation, dehydration, transparency, and embedding, 4-μm paraffin sections were prepared. Three sections were sampled from 15 serial sections according to a systematic (equal spaced) manner. After dewaxing, hydration, and antigen repair, the sections were sealed with 5% goat serum for 60 min, and then, antigen staining was carried out. Primary antibody AQP4 (1:150, NBP1-87679, Novus) and CD31 (1:50, sc-376764, Santa Cruz) were incubated overnight at 4 °C, reheated at 37 °C for 30 min, and washed with PBS three times for 15 min each time. Vascular endothelial cells were labeled with CD31. Then, the secondary antibodies conjugated Alexa Fluor 647 (Abcam), AlexaFluor 488 (Abcam) secondary goat anti-rabbit IgG H&L antibodies (1:500, Abcam, ab150079), and goat anti-mouse IgG H&L antibodies (1:500, Abcam, ab150113) were sealed with anti-fluorescence quenching sealing solution with DAPI (DAPI, 4',6-diamidino-2-phenylindole Beyotime, p0131, Shanghai, China). The sections were observed under a laser confocal microscope (Olympus fv1200, Olympus, Tokyo, Japan). Fluorescence quantification was analyzed by the ImageJ software.
Xu C., Wang F., Su C., Guo X., Li J, & Lin J. (2023). Restoration of aquaporin-4 polarization in the spinal glymphatic system by metformin in rats with painful diabetic neuropathy. Neuroreport, 34(3), 190-197.
Publication 2023
Alexa Fluor 647 Anti-Antibodies anti-IgG Antibodies Antigens DAPI Dehydration Fluorescence Fluorescent Antibody Technique Goat Hydrate, Chloral Immunoglobulins Laser Microscopy Mice, House Novus Paraffin paraform Perfusion Rabbits Rattus norvegicus Saline Solution Serum Sterility, Reproductive Vascular Endothelial Cells
3
High Glucose Endothelial Injury Model

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Publication 2023
Endothelium Glucose Homo sapiens Injuries Mannitol Umbilicus Vascular Endothelial Cells
4
Visualization of Renal Autophagy by TEM

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Publication 2023
Autolysosome Autophagosome Buffers Citric Acid Electron Microscopy Kidney Kidney Cortex Microtomy Phosphates Tissues Transmission Electron Microscopy Uranium Vascular Endothelial Cells
5
Skin Wound Healing Evaluation in Rats

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Publication 2023
Anesthetics angiogen Arterioles Asepsis Capillaries Drug Overdose Dyes Eosin Ethanol Fingers Formalin Fracture, Bone Injections, Intraperitoneal Injuries Males Paraffin Embedding Pentobarbital Sodium Rats, Sprague-Dawley Rattus norvegicus Skin Tissues Vascular Endothelial Cells Wounds

Top products related to «Vascular Endothelial Cells»

1
Fetal bovine serum (fbs) by Thermo Fisher Scientific
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Fetal Bovine Serum (FBS) is a cell culture supplement derived from the blood of bovine fetuses. FBS provides a source of proteins, growth factors, and other components that support the growth and maintenance of various cell types in in vitro cell culture applications.
2
Dulbecco modified eagle medium (dmem) by Thermo Fisher Scientific
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DMEM (Dulbecco's Modified Eagle's Medium) is a cell culture medium formulated to support the growth and maintenance of a variety of cell types, including mammalian cells. It provides essential nutrients, amino acids, vitamins, and other components necessary for cell proliferation and survival in an in vitro environment.
3
Penicillin streptomycin by Thermo Fisher Scientific
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Penicillin/streptomycin is a commonly used antibiotic solution for cell culture applications. It contains a combination of penicillin and streptomycin, which are broad-spectrum antibiotics that inhibit the growth of both Gram-positive and Gram-negative bacteria.
4
L glutamine by Thermo Fisher Scientific
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L-glutamine is an amino acid that is commonly used as a dietary supplement and in cell culture media. It serves as a source of nitrogen and supports cellular growth and metabolism.
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Fetal bovine serum (fbs) by Merck Group
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FBS, or Fetal Bovine Serum, is a commonly used cell culture supplement. It is derived from the blood of bovine fetuses and provides essential growth factors, hormones, and other nutrients to support the growth and proliferation of a wide range of cell types in vitro.
6
Penicillin by Thermo Fisher Scientific
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Penicillin is a type of antibiotic used in laboratory settings. It is a broad-spectrum antimicrobial agent effective against a variety of bacteria. Penicillin functions by disrupting the bacterial cell wall, leading to cell death.
7
Streptomycin by Thermo Fisher Scientific
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Streptomycin is a broad-spectrum antibiotic used in laboratory settings. It functions as a protein synthesis inhibitor, targeting the 30S subunit of bacterial ribosomes, which plays a crucial role in the translation of genetic information into proteins. Streptomycin is commonly used in microbiological research and applications that require selective inhibition of bacterial growth.
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Matrigel by BD
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Matrigel is a solubilized basement membrane preparation extracted from the Engelbreth-Holm-Swarm (EHS) mouse sarcoma, a tumor rich in extracellular matrix proteins. It is widely used as a substrate for the in vitro cultivation of cells, particularly those that require a more physiologically relevant microenvironment for growth and differentiation.
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Egm 2 by Lonza
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The EGM-2 is a laboratory instrument designed for the measurement of oxygen concentration in cell culture media. It provides accurate and reliable data on the oxygen levels within the culture environment.
10
B6 fvb tg cdh5 cre 7mlia j cre mice by Jackson ImmunoResearch
Sourced in United States
B6 FVB-Tg (cdh5-cre)7Mlia/J Cre mice express Cre recombinase under the control of the endothelial-specific cadherin 5 (Cdh5) promoter. This allows for Cre-mediated recombination in endothelial cells.

More about "Vascular Endothelial Cells"

Vascular endothelial cells (VECs) are a crucial component of the cardiovascular system, forming a thin, protective layer that lines the interior of blood vessels.
These specialized squamous epithelial cells play a vital role in maintaining vascular homeostasis, regulating blood flow, and facilitating the exchange of nutrients and waste between the circulatory system and surrounding tissues.
Dysfunction or damage to VECs has been implicated in the pathogenesis of various cardiovascular and metabolic disorders, making them an important target for research and therapeutic interventions.
Understanding the biology and behavior of VECs is crucial for advancing our knowledge of vascular physiology and developing effective treatments for vascular-related diseases.
To study VECs, researchers often utilize cell culture models, which may involve the use of specialized media and supplements like fetal bovine serum (FBS), Dulbecco's Modified Eagle Medium (DMEM), penicillin/streptomycin, and L-glutamine.
These components provide the necessary nutrients and growth factors to support the proliferation and maintenance of VECs in vitro.
Additionally, the extracellular matrix protein Matrigel is commonly used to mimic the natural environment of VECs, promoting their attachment, spreading, and differentiation.
Endothelial growth medium-2 (EGM-2) is another useful tool, as it is specifically formulated to support the growth and maintenance of VECs.
For in vivo studies, transgenic mouse models, such as the B6 FVB-Tg (cdh5-cre)7Mlia/J Cre mouse, can be utilized to investigate the role of VECs in various physiological and pathological processes.
These mice express the Cre recombinase enzyme under the control of the VEC-specific cadherin 5 (cdh5) promoter, allowing for the targeted manipulation and observation of VECs in a living organism.
By leveraging the insights gained from the MeSH term description and the metadescription, researchers can optimize their vascular endothelial cell research using the powerful tools and features offered by PubCompare.ai.
This AI-driven platform can help identify the most effective protocols, products, and strategies for studying VECs, ultimately advancing our understanding of vascular biology and paving the way for innovative therapeutic interventions.