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  • 1
    ISSN: 0021-9541
    Keywords: Life and Medical Sciences ; Cell & Developmental Biology
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Biology , Medicine
    Notes: Studies have shown that, among lipoxygenase metabolites examined, 15(S)-hydroperoxy-5,8,11,13-eicosa-tetraenoic acid (15[S]-HPETE), at micromolar concentrations, selectively causes injury to cultured endothelial cells. We investigated whether physiologically relevant concentrations of lipoxygenase metabolites affected the expression of cell adhesion molecules (CAMs) involved in the adhesion of leukocytes and/or the accumulation of leukocytes in the vascular endothelium, these being the initial events in endothelial cell injury. Among lipoxygenase metabolites, 15(S)-HPETE and 12(S)-HETE, at nanomolar concentrations, induced surface expression of a subset of cell adhesion molecules (CAM), ICAM-1, ELAM-1, and VCAM-1, in human umbilical vein endothelial cells (HUVEC), which is associated with an increased binding activity of the transcription factor, NF-κB, to the consensus motif common to the CAM genes in the HUVEC nuclear extracts. Furthermore, 15(S)-HPETE (1 nM) caused a threefold increase in the rate of transendothelial migration of vitamin D3-differentiated HL-60 monocyte-like cells and showed a thirtyfold increase in the phosphorylation of PECAM-1, an adhesion molecule involved in endothelial cell-cell adhesion. Both an antibody to PECAM-1 and the protein kinase C inhibitor, GF 109203X, reduced 15(S)-HPETE-induced transmigration of monocyte-like HL-60 cells by approximately 75% and 85%, respectively. Treatment of HUVEC with a phosphatase inhibitor, calyculin A, augmented both the phosphorylation of PECAM-1 and transmigration of monocyte-like HL-60 cells induced by 15(S)-HPETE. Our results show that 15(S)-HPETE, at physiological concentrations, induced activation of protein kinase C in HUVEC and leads to the phosphorylation of PECAM-1, thus facilitating the migration of monocyte-like HL-60 cells across the endothelial cell monolayer. It is suggested that phosphorylation/dephosphorylation events in PECAM-1 are important in regulating the trafficking of monocytes across the endothelial cell monolayer. © 1996 Wiley-Liss, Inc.
    Additional Material: 10 Ill.
    Type of Medium: Electronic Resource
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  • 2
    Publication Date: 1998-11-15
    Description: The abnormal adherence of sickle red blood cells (SS RBC) to endothelial cells has been thought to contribute to vascular occlusion, a major cause of morbidity in sickle cell disease (SCD). We determined whether the interaction of SS RBC with cultured endothelial cells induced cellular oxidant stress that would culminate in expression of cell adhesion molecules (CAMs) involved in the adhesion and diapedesis of monocytes and the adherence of SS reticulocytes. We showed that the interaction of SS RBC at 2% concentration in the presence of multimers of von Willebrand factor (vWf), derived from endothelial cell-derived conditioned medium (E-CM) with cultured human umbilical vein endothelial cells (HUVEC), resulted in a fivefold increased formation of thiobarbituric acid-reactive substances (TBARS) and activation of the transcription factor NF-kB, both indicators of cellular oxidant stress. Normal RBC show none of these phenomena. The oxidant stress-induced signaling resulted in an increased surface expression of a subset of CAMs, ICAM-1, E-selectin, and VCAM-1 in HUVEC. The addition of oxygen radical scavenger enzymes (catalase, superoxide dismutase) and antioxidant (probucol) inhibited these events. Additionally, preincubation of HUVEC with a synthetic peptide Arg-Gly-Asp (RGD) that prevents vWf-mediated adhesion of SS RBC reduced the surface expression of VCAM-1 and NF-kB activation. Furthermore, SS RBC-induced oxidant stress resulted in a twofold increase in the transendothelial migration of both monocyte-like HL-60 cells and human peripheral blood monocytes, and approximately a sixfold increase in platelet-endothelial cell adhesion molecule-1 (PECAM-1) phosphorylation, each of which was blocked by protein kinase C inhibitor and antioxidants. These results suggest that the adherence/contact of SS RBC to endothelial cells in large vessel can generate enhanced oxidant stress leading to increased adhesion and diapedesis of monocytes, as well as heightened adherence of SS reticulocytes, indicating that injury/activation of endothelium can contribute to vaso-occlusion in SCD.
    Print ISSN: 0006-4971
    Electronic ISSN: 1528-0020
    Topics: Biology , Medicine
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  • 3
    Publication Date: 1998-11-15
    Description: The abnormal adherence of sickle red blood cells (SS RBC) to endothelial cells has been thought to contribute to vascular occlusion, a major cause of morbidity in sickle cell disease (SCD). We determined whether the interaction of SS RBC with cultured endothelial cells induced cellular oxidant stress that would culminate in expression of cell adhesion molecules (CAMs) involved in the adhesion and diapedesis of monocytes and the adherence of SS reticulocytes. We showed that the interaction of SS RBC at 2% concentration in the presence of multimers of von Willebrand factor (vWf), derived from endothelial cell-derived conditioned medium (E-CM) with cultured human umbilical vein endothelial cells (HUVEC), resulted in a fivefold increased formation of thiobarbituric acid-reactive substances (TBARS) and activation of the transcription factor NF-kB, both indicators of cellular oxidant stress. Normal RBC show none of these phenomena. The oxidant stress-induced signaling resulted in an increased surface expression of a subset of CAMs, ICAM-1, E-selectin, and VCAM-1 in HUVEC. The addition of oxygen radical scavenger enzymes (catalase, superoxide dismutase) and antioxidant (probucol) inhibited these events. Additionally, preincubation of HUVEC with a synthetic peptide Arg-Gly-Asp (RGD) that prevents vWf-mediated adhesion of SS RBC reduced the surface expression of VCAM-1 and NF-kB activation. Furthermore, SS RBC-induced oxidant stress resulted in a twofold increase in the transendothelial migration of both monocyte-like HL-60 cells and human peripheral blood monocytes, and approximately a sixfold increase in platelet-endothelial cell adhesion molecule-1 (PECAM-1) phosphorylation, each of which was blocked by protein kinase C inhibitor and antioxidants. These results suggest that the adherence/contact of SS RBC to endothelial cells in large vessel can generate enhanced oxidant stress leading to increased adhesion and diapedesis of monocytes, as well as heightened adherence of SS reticulocytes, indicating that injury/activation of endothelium can contribute to vaso-occlusion in SCD.
    Print ISSN: 0006-4971
    Electronic ISSN: 1528-0020
    Topics: Biology , Medicine
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  • 4
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  • 6
    Publication Date: 2021-02-04
    Description: Electricity load forecasting is one of the hot concerns of the current electricity market, and many forecasting models are proposed to satisfy the market participants’ needs. Most of the models have the shortcomings of large computation or low precision. To address this problem, a novel deep learning and data processing ensemble model called SELNet is proposed. We performed an experiment with this model; the experiment consisted of two parts: data processing and load forecasting. In the data processing part, the autocorrelation function (ACF) was used to analyze the raw data on the electricity load and determine the data to be input into the model. The variational mode decomposition (VMD) algorithm was used to decompose the electricity load raw-data into a set of relatively stable modes named intrinsic mode functions (IMFs). According to the time distribution and time lag determined using the ACF, the input of the model was reshaped into a 24 × 7 × 8 matrix M, where 24, 7, and 8 represent 24 h, 7 days, and 8 IMFs, respectively. In the load forecasting part, a two-dimensional convolutional neural network (2D-CNN) was used to extract features from the matrix M. The improved reshaped layer was used to reshape the extracted features according to the time order. A temporal convolutional network was then employed to learn the reshaped time-series features and combined with the fully connected layer to complete the prediction. Finally, the performance of the model was verified in the Eastern Electricity Market of Texas. To demonstrate the effectiveness of the proposed model data processing and load forecasting, we compared it with the gated recurrent unit (GRU), TCN, VMD-TCN, and VMD-CNN models. The TCN exhibited better performance than the GRU in load forecasting. The mean absolute percentage error (MAPE) of the TCN, which was over 5%, was less than that of the GRU. Following the addition of VMD to the TCN, the basic performance of the model was 2–3%. A comparison between the SELNet model and the VMD-TCN model indicated that the application of a 2D-CNN improves the forecast performance, with only a few samples having an MAPE of over 4%. The model’s prediction effect in each season is discussed, and it was found that the proposed model can achieve high-precision prediction in each season.
    Electronic ISSN: 2071-1050
    Topics: Energy, Environment Protection, Nuclear Power Engineering
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