| 1. |
- Holm, Anders, et al.
(författare)
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The GPER1 Agonist G-1 Attenuates Endothelial Cell Proliferation by Inhibiting DNA Synthesis and Accumulating Cells in the S and G2 Phases of the Cell Cycle.
- 2011
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Ingår i: Journal of Vascular Research. - : S. Karger AG. - 1423-0135 .- 1018-1172. ; 48:4, s. 327-335
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Tidskriftsartikel (refereegranskat)abstract
- G protein-coupled receptor 30 (GPR30) or G protein-coupled estrogen receptor 1 (GPER1) is expressed in the vasculature, but the importance of vascular GPER1 remains to be clarified. Here we investigate effects of the GPER1 agonist G-1 on endothelial cell proliferation using mouse microvascular endothelial bEnd.3 cells. The bEnd.3 cells express mRNA for GPER1. The bEnd.3 cells expressed both ERα and ERβ immunoreactivities. Treatment with G-1 reduced DNA synthesis and cell number with IC(50) values of about 2 μM. GPER1 siRNA prevented G-1-induced attenuation of DNA synthesis. G-1 accumulated cells in S and G2 phases of the cell cycle, suggesting that G-1 blocks transition between G2 and M. G-1 had no effect on DNA synthesis in COS-7 cells only weakly expressing GPER1 mRNA. 17β-Estradiol had no effect on DNA synthesis in physiological concentrations (nM). The ER blocker ICI182780 reduced DNA synthesis with similar potency as G-1. Treatment with the ERK/MAP kinase inhibitor PD98059 had no effect on G-1-induced attenuation of DNA synthesis. G-1- induced antiproliferation was observed not only in bEnd.3 cells but also in human umbilical vein endothelial cells and HMEC-1 endothelial cells. We conclude that the GPER1 agonist G-1 attenuates endothelial cell proliferation via inhibition of DNA synthesis and by accumulation of cells in S and G2.
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| 2. |
- Holmer, Mattias, et al.
(författare)
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Determining Heart Activity Present in the Pressure Sensors of a Dialysis Machine
- 2013
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Ingår i: Computing in Cardiology. - 2325-8861. ; , s. 217-220
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Konferensbidrag (refereegranskat)abstract
- Determination of heart status during dialysis can im- prove patient monitoring. Pressure sensors in the dialysis machine measures the heart pulses that propagates in the body and enter the extracorporeal blood circuit. A peri- staltic blood pump, located in the same circuit, introduces strong periodic pressure pulses that interfere with the much weaker cardiac component. These signal characteristics make the extraction of the heart activity challenging. In the present study, we explore the possibility to extract and analyze the cardiac component using simulated data. The accuracy of the timing of each heartbeat is analyzed. Ad- ditionally, the heart component is extracted from patient pressure recordings, and compared to the heart rate com- puted from a photoplethysmogram. The results show that heart timings can be accurately determined using the pres- sure sensors of a dialysis machine.
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| 3. |
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| 4. |
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| 5. |
- Holmer, Mattias, et al.
(författare)
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On-line Heart Rate Monitoring Using the Extra-corporeal Pressure Sensors of a Dialysis Machine
- 2012
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Ingår i: Biomedical engineering – 2012 : proceedings of international conference. - 2029-3380.
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Konferensbidrag (refereegranskat)abstract
- Heart rate can be extracted from the extracorporeal venous pressure signal of a dialysis machine. The results are of comparable accuracy and reliability to the ones obtained by the PPG reference signal from a pulse oximeter. Difficulties that occur during heart rate estimation were determined, and some can be overcome by a slight adjustment of blood flow rate. The described techniques, after being implemented into the dialysis machines, would help to improve current hemodialysis safety throughout the treatment by on-line monitoring of the cardiac activity.
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| 6. |
- Sandberg, Frida, et al.
(författare)
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Estimation of Respiratory Information from the Built-In Pressure Sensors of a Dialysis Machine
- 2014
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Ingår i: [Host publication title missing]. - 0276-6574. ; 41, s. 853-856
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Konferensbidrag (refereegranskat)abstract
- The purpose of the present study is to determine the feasibility of estimating respiratory information from the built-in pressure sensors of a dialysis machine. The study database consists of simultaneous recordings of pressure signals and capnographic signals from 6 patients during 7 hemodialysis treatment sessions. Respiration rates were estimated using respiratory induced variations in the beat- to-beat interval series of the cardiac component of the pressure signal and respiratory induced baseline varia- tions in the pressure signal, respectively. The estimated respiration rates were compared to a reference respira- tion rate determined from the capnograhpic signal. The root-mean-square error of the estimated respiration rate from the baseline variations of the pressure signal was 2.10 breaths/min; the corresponding error of the estimated res- piration rate from the beat-to-beat interval series of the cardiac component was 4.95 breaths/min. The results sug- gest that it is possible to estimate respiratory information from the pressure sensors.
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| 7. |
- Solem, Kristian, et al.
(författare)
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Prediction of Intradialytic Hypotension Using Photoplethysmography
- 2010
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Ingår i: IEEE Transactions on Biomedical Engineering. - 1558-2531. ; 57:7, s. 1611-1619
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Tidskriftsartikel (refereegranskat)abstract
- Intradialytic hypotension is the most common acute complication during conventional hemodialysis treatment. Prediction of such events is highly desirable in clinical routine for prevention. This paper presents a novel prediction method of acute symptomatic hypotension in which the photoplethysmographic signal is analyzed with respect to changes in amplitude, reflecting vasoconstriction, and cardiac output. The method is based on a statistical model in which the noise is assumed to have Laplacian amplitude distribution. The performance is evaluated on 11 hypotension-prone patients who underwent hemodialysis treatment, resulting in seven events with acute symptomatic hypotension and 17 without. The photoplethysmographic signal was continuously acquired during treatment as was information on blood pressure and oxygen saturation. Using leave-one-out cross validation, the proposed method predicted six out of seven hypotensive events, while producing 1 false prediction out of 17 possible. The performance was achieved when the prediction threshold was chosen to be in the range 57%-65% of the photoplethysmographic envelope at treatment onset.
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