40 research outputs found
Total ginsenosides suppress monocrotaline-induced pulmonary hypertension in rats: involvement of nitric oxide and mitogen-activated protein kinase pathways
AbstractBackgroundGinsenosides have been shown to exert beneficial pharmacological effects on the central nervous, cardiovascular, and endocrine systems. We sought to determine whether total ginsenosides (TG) inhibit monocrotaline (MCT)-induced pulmonary hypertension and to elucidate the underlying mechanism.MethodsMCT-intoxicated rats were treated with gradient doses of TG, with or without NG-nitro-l-arginine methyl ester. The levels of molecules involving the regulation of nitric oxide and mitogen-activated protein kinase pathways were determined.ResultsTG ameliorated MCT-induced pulmonary hypertension in a dose-dependent manner, as assessed by the right ventricular systolic pressure, the right ventricular hypertrophy index, and pulmonary arterial remodeling. Furthermore, TG increased the levels of pulmonary nitric oxide, endothelial nitric oxide synthase, and cyclic guanosine monophosphate. Lastly, TG increased mitogen-activated protein kinase phosphatase-1 expression and promoted the dephosphorylation of extracellular signal-regulated protein kinases 1/2, p38 mitogen-activated protein kinase, and c-Jun NH2-terminal kinase 1/2.ConclusionTG attenuates MCT-induced pulmonary hypertension, which may involve in part the regulation of nitric oxide and mitogen-activated protein kinase pathways
Unveiling the role of regulatory T cells in the tumor microenvironment of pancreatic cancer through single-cell transcriptomics and in vitro experiments
BackgroundIn order to investigate the impact of Treg cell infiltration on the immune response against pancreatic cancer within the tumor microenvironment (TME), and identify crucial mRNA markers associated with Treg cells in pancreatic cancer, our study aims to delve into the role of Treg cells in the anti-tumor immune response of pancreatic cancer.MethodsThe ordinary transcriptome data for this study was sourced from the GEO and TCGA databases. It was analyzed using single-cell sequencing analysis and machine learning. To assess the infiltration level of Treg cells in pancreatic cancer tissues, we employed the CIBERSORT method. The identification of genes most closely associated with Treg cells was accomplished through the implementation of weighted gene co-expression network analysis (WGCNA). Our analysis of single-cell sequencing data involved various quality control methods, followed by annotation and advanced analyses such as cell trajectory analysis and cell communication analysis to elucidate the role of Treg cells within the pancreatic cancer microenvironment. Additionally, we categorized the Treg cells into two subsets: Treg1 associated with favorable prognosis, and Treg2 associated with poor prognosis, based on the enrichment scores of the key genes. Employing the hdWGCNA method, we analyzed these two subsets to identify the critical signaling pathways governing their mutual transformation. Finally, we conducted PCR and immunofluorescence staining in vitro to validate the identified key genes.ResultsBased on the results of immune infiltration analysis, we observed significant infiltration of Treg cells in the pancreatic cancer microenvironment. Subsequently, utilizing the WGCNA and machine learning algorithms, we ultimately identified four Treg cell-related genes (TRGs), among which four genes exhibited significant correlations with the occurrence and progression of pancreatic cancer. Among them, CASP4, TOB1, and CLEC2B were associated with poorer prognosis in pancreatic cancer patients, while FYN showed a correlation with better prognosis. Notably, significant differences were found in the HIF-1 signaling pathway between Treg1 and Treg2 cells identified by the four genes. These conclusions were further validated through in vitro experiments.ConclusionTreg cells played a crucial role in the pancreatic cancer microenvironment, and their presence held a dual significance. Recognizing this characteristic was vital for understanding the limitations of Treg cell-targeted therapies. CASP4, FYN, TOB1, and CLEC2B exhibited close associations with infiltrating Treg cells in pancreatic cancer, suggesting their involvement in Treg cell functions. Further investigation was warranted to uncover the mechanisms underlying these associations. Notably, the HIF-1 signaling pathway emerged as a significant pathway contributing to the duality of Treg cells. Targeting this pathway could potentially revolutionize the existing treatment approaches for pancreatic cancer
Reservoir Temperature Calculation and Modeling for Convective Geothermal Systems: Case Study of Five Major Hot Springs in Lushan, Henan, China
The thermal storage temperature and water-rock interaction process of the Lushan convective geothermal system (Qinling stratigraphic zonation fracture zone in China) are clarified by using surface cold water and geothermal fluid as the research objects. In this study, a conceptual model of the temperature profile of the geothermal system in the study area was developed using surface temperature inversion, the cation temperature scale, the SiO2 temperature scale method, the mineral equilibrium phase method, the silicon-enthalpy model, the FixAl method, and the Cl-enthalpy model. The inversion temperature at the surface is in the range of 33-39°C, and the temperature difference indicates the direction of the Checun-Lushan fracture. The study area is recharged from atmospheric precipitation, and the temperature of the recharge area is approximately 5.8–7.7°C (the temperature of the alkali field is approximately 10°C), and the recharge elevation is approximately 1200 m. The thermal storage pattern in the study area is near-surface hydrothermal thermal storage transferred to shallow thermal storage and then to deep thermal storage. The near-surface hydrothermal thermal storage temperature is at a constant temperature of 60°C, and the shallow thermal storage temperature is calculated by K-Mg and Li-Mg geothermometers to be between 99 and 112°C. The thermal storage temperature is simulated using the FixAl method, with deviation values ranging from 2.9% to 15.0%. The silicon-enthalpy model calculates the deep thermal storage temperature to be between 181 and 230°C. The mixing ratio of geothermal water in the study area is extremely high, with a cold water mixing ratio of 85.4–94.8%. The home ground fluid temperature was estimated to be approximately 282°C using the Cl-enthalpy model. The main thermally controlled conductivity channel in the study area is the Checun-Lushan fracture zone. The water vapor formed by convection at depth moves upward to approximately 5 km to form a deep thermal reservoir, and this convection and upward movement cause it to mix with cold water from the fracture zone to form a shallow thermal reservoir, which moves to the near-surface, forming a hydrothermal-type reservoir, which is later discharged in the form of a spring. The conceptual model of geothermal system temperature established in this study provides a basis for further development and utilization of Lushan hot springs and provides guidance for future thermal storage temperature calculations of convection-type geothermal systems in uplifted mountains
Multi-zone coupling productivity of horizontal well fracturing with complex fracture networks in shale gas reservoirs
In this paper, a series of specific studies were carried out to investigate the complex form of fracture networks and figure out the multi-scale flowing laws of nano/micro pores–complex fracture networks–wellbore during the development of shale reservoirs by means of horizontal well fracturing. First, hydraulic fractures were induced by means of Brazilian splitting tests. Second, the forms of the hydraulic fractures inside the rock samples were observed by means of X-ray CT scanning to measure the opening of hydraulic fractures. Third, based on the multi-scale unified flowing model, morphological description of fractures and gas flowing mechanism in the matrix–complex fracture network–wellbore, the productivity equation of single-stage horizontal well fracturing which includes diffusion, slipping and desorption was established. And fourthly, a productivity prediction model of horizontal well multi-stage fracturing in the shale reservoir was established considering the interference between the multi-stage fracturing zones and the pressure drop in the horizontal wellbore. The following results were obtained. First, hydraulic fractures are in the form of a complex network. Second, the measured opening of hydraulic fractures is in the range of 4.25–453 μm, averaging 112 μm. Third, shale gas flowing in different shapes of fracture networks follows different nonlinear flowing laws. Forth, as the fracture density in the strongly stimulated zones rises and the distribution range of the hydraulic fractures in strongly/weakly stimulated zones enlarges, gas production increases gradually. As the interference occurs in the flowing zones of fracture networks between fractured sections, the increasing amplitude of gas production rates decreases. Fifth, when the length of a simulated horizontal well is 1500 m and the half length of a fracture network in the strongly stimulated zone is 100 m, the productivity effect of stage 10 fracturing is the best. Therefore, it is necessary to control fracturing degree reasonably and optimize fracturing parameters, so as to provide a theoretical support for the optimization design of shale gas reservoir fracturing. Keywords: Shale gas, Reservoir, Fracturing, Horizontal well, Complex fracture network, Multi-zone coupling, Multi-scale, Interference, Productivity capacit