Concentration-Dependent Diversification Effects of Free Cholesterol Loading on Macrophage Viability and Polarization

Background/Aims: The accumulation of free cholesterol in atherosclerotic lesions has been well documented in both animals and humans. In studying the relevance of free cholesterol buildup in atherosclerosis, contradictory results have been generated, indicating that free cholesterol produces both pro- and anti-atherosclerosis effects in macrophages. This inconsistency might stem from the examination of only select concentrations of free cholesterol. In the present study, we sought to investigate the implication of excess free cholesterol loading in the pathophysiology of atherosclerosis across a broad concentration range from (in µg/ml) 0 to 60. Methods:Macrophage viability was determined by measuring formazan formation and flow cytometry viable cell counting. The polarization of M1 and M2 macrophages was differentiated by FACS (Fluorescence-Activated Cell Sorting) assay. The secretion of IL-1β in macrophage culture medium was measured by ELISA kit. Macrophage apoptosis was detected by flow cytometry using a TUNEL kit. Results: Macrophage viability was increased at the treatment of lower concentrations of free cholesterol from (in µg/ml) 0 to 20, but gradually decreased at higher concentrations from 20 to 60. Lower free cholesterol loading induced anti-inflammatory M2 macrophage polarization. The activation of the PPARγ (Peroxisome Proliferator-Activated Receptor gamma) nuclear factor underscored the stimulation of this M2 phenotype. Nevertheless, higher levels of free cholesterol resulted in pro-inflammatory M1 activation. Moreover, with the application of higher free cholesterol concentrations, macrophage apoptosis and secretion of the inflammatory cytokine IL-1β increased significantly. Conclusion: These results for the first time demonstrate that free cholesterol could render concentration-dependent diversification effects on macrophage viability, polarization, apoptosis and inflammatory cytokine secretions, thereby reconciling the pros and cons of free cholesterol buildup in macrophages to the pathophysiology of atherosclerosis

Recovery and treatment of fracturing flowback fluids in the Sulige Gasfield, Ordos Basin

AbstractCentralized and group well deployment and factory-like fracturing techniques are adopted for low-permeability tight sandstone reservoirs in the Sulige Gasfield, Ordos Basin, so as to realize its efficient and economic development. However, environmental protection is faced with grim situations because fluid delivery rises abruptly on site in a short time due to centralized fracturing of the well group. Based on the characteristics of gas testing after fracturing in this gas field, a fracturing flowback fluid recovery and treatment method suitable for the Sulige Gasfield has been developed with the landform features of this area taken into account. Firstly, a high-efficiency well-to-well fracturing flowback fluid recovery and reutilization technique was developed with multi-effect surfactant polymer recoverable fracturing fluid system as the core, and in virtue of this technique, the treatment efficiency of conventional guar gum fracturing fluid system is increased. Secondly, for recovering and treating the end fluids on the well sites, a fine fracturing flowback fluid recovery and treatment technique has been worked out with “coagulation and precipitation, filtration and disinfection, and sludge dewatering” as the main part. Owing to the application of this method, the on-site water resource utilization ratio has been increased and environmental protection pressure concerned with fracturing operation has been relieved. In 2014, field tests were performed in 62 wells of 10 well groups, with 32980 m3 cumulative treated flowback fluid, 17160 m3 reutilization volume and reutilization ratio over 70%. Obviously, remarkable social and economical benefits are thus realized

Denoising of BOTDR Dynamic Strain Measurement Using Convolutional Neural Networks

The Brillouin optical time domain reflectometry (BOTDR) system measures the distributed strain and temperature information along the optic fibre by detecting the Brillouin gain spectra (BGS) and finding the Brillouin frequency shift profiles. By introducing small gain stimulated Brillouin scattering (SBS), dynamic measurement using BOTDR can be realized, but the performance is limited due to the noise of the detected information. An image denoising method using the convolutional neural network (CNN) is applied to the derived Brillouin gain spectrum images to enhance the performance of the Brillouin frequency shift detection and the strain vibration measurement of the BOTDR system. By reducing the noise of the BGS images along the length of the fibre under test with different network depths and epoch numbers, smaller frequency uncertainties are obtained, and the sine-fitting R-squared values of the detected strain vibration profiles are also higher. The Brillouin frequency uncertainty is improved by 24% and the sine-fitting R-squared value of the obtained strain vibration profile is enhanced to 0.739, with eight layers of total depth and 200 epochs

Denoising of BOTDR Dynamic Strain Measurement Using Convolutional Neural Networks.

The Brillouin optical time domain reflectometry (BOTDR) system measures the distributed strain and temperature information along the optic fibre by detecting the Brillouin gain spectra (BGS) and finding the Brillouin frequency shift profiles. By introducing small gain stimulated Brillouin scattering (SBS), dynamic measurement using BOTDR can be realized, but the performance is limited due to the noise of the detected information. An image denoising method using the convolutional neural network (CNN) is applied to the derived Brillouin gain spectrum images to enhance the performance of the Brillouin frequency shift detection and the strain vibration measurement of the BOTDR system. By reducing the noise of the BGS images along the length of the fibre under test with different network depths and epoch numbers, smaller frequency uncertainties are obtained, and the sine-fitting R-squared values of the detected strain vibration profiles are also higher. The Brillouin frequency uncertainty is improved by 24% and the sine-fitting R-squared value of the obtained strain vibration profile is enhanced to 0.739, with eight layers of total depth and 200 epochs

Denoising of BOTDR Dynamic Strain Measurement Using Convolutional Neural Networks.

Peer reviewed: TrueThe Brillouin optical time domain reflectometry (BOTDR) system measures the distributed strain and temperature information along the optic fibre by detecting the Brillouin gain spectra (BGS) and finding the Brillouin frequency shift profiles. By introducing small gain stimulated Brillouin scattering (SBS), dynamic measurement using BOTDR can be realized, but the performance is limited due to the noise of the detected information. An image denoising method using the convolutional neural network (CNN) is applied to the derived Brillouin gain spectrum images to enhance the performance of the Brillouin frequency shift detection and the strain vibration measurement of the BOTDR system. By reducing the noise of the BGS images along the length of the fibre under test with different network depths and epoch numbers, smaller frequency uncertainties are obtained, and the sine-fitting R-squared values of the detected strain vibration profiles are also higher. The Brillouin frequency uncertainty is improved by 24% and the sine-fitting R-squared value of the obtained strain vibration profile is enhanced to 0.739, with eight layers of total depth and 200 epochs

Denoising of BOTDR Dynamic Strain Measurement Using Convolutional Neural Networks

The Brillouin optical time domain reflectometry (BOTDR) system measures the distributed strain and temperature information along the optic fibre by detecting the Brillouin gain spectra (BGS) and finding the Brillouin frequency shift profiles. By introducing small gain stimulated Brillouin scattering (SBS), dynamic measurement using BOTDR can be realized, but the performance is limited due to the noise of the detected information. An image denoising method using the convolutional neural network (CNN) is applied to the derived Brillouin gain spectrum images to enhance the performance of the Brillouin frequency shift detection and the strain vibration measurement of the BOTDR system. By reducing the noise of the BGS images along the length of the fibre under test with different network depths and epoch numbers, smaller frequency uncertainties are obtained, and the sine-fitting R-squared values of the detected strain vibration profiles are also higher. The Brillouin frequency uncertainty is improved by 24% and the sine-fitting R-squared value of the obtained strain vibration profile is enhanced to 0.739, with eight layers of total depth and 200 epochs

Telemetric signal-driven servocontrol of renal perfusion pressure in acute and chronic rat experiments

The present study was designed to take advantage of telemetry data acquisition and develop an easy and reliable system to servocontrol renal perfusion pressure (RPP). Digitized pressure signals from lower abdominal aorta in rats, reflecting RPP, was obtained by a telemetry device and dynamically exported into an Excel worksheet. A computer program (LabVIEW) compared the RPP data with a preselected pressure range and drove a bidirectional syringe pump to control the inflation of a vascular occluder around the aorta above renal arteries. When RPP was higher than the preselected range, the syringe pump inflated the occluder and decreased RPP, and vice versa. If RPP was within range, there was no action. In this way, RPP was servocontrolled within the desired range. In experiments with norepinephrine- or ANG II-induced acute increases in systemic arterial pressure (120–145 mmHg), the system controlled RPP at a constant range of 100–105 mmHg within 30–50 s and differentiated the pressure-dependent and -independent effects on renal functions. In Dahl S rats with high-salt-induced hypertension, this system maintained RPP at 100–120 mmHg over 10 days, while systemic arterial pressures were 150 ± 5.9 mmHg in uncontrolled animals. This system also has the ability of simultaneity and multiplexing to control multiple animals. Our results suggest that this is an effective and reliable system to servocontrol RPP, which can be easily established with general computer knowledge. This system provides a powerful tool and may greatly facilitate the studies in pressure-dependent/-independent effects of a variety of cardiovascular factors