92 research outputs found
Understanding gas transport mechanisms in shale gas reservoir: Pore network modelling approach
This report summarizes the recent findings on gas transport mechanisms in shale gas reservoir by pore network modelling. Multi-scale pore network model was developed to accurately characterize the shale pore structure. The pore network single component gas transport model was established considering the gas slippage and real gas property. The gas transport mechanisms in shale pore systems were elaborated on this basis. A multicomponent hydrocarbon pore network transport model was further proposed considering the influences of capillary pressure and fluid occurrence on fugacity balance. The hydrocarbon composition and pore structure influences on condensate gas transport were analyzed. These results provide valuable insights on gas transport mechanisms in shale gas reservoir.Cited as: Song, W., Yao, J., Zhang, K., Yang, Y., Sun, H. Understanding gas transport mechanisms in shale gas reservoir: Pore network modelling approach. Advances in Geo-Energy Research, 2022, 6(4): 359-360. https://doi.org/10.46690/ager.2022.04.1
Genetic and immunological insights into COVID-19 with acute myocardial infarction: Integrated analysis of mendelian randomization, transcriptomics, and clinical samples
Background: Globally, most deaths result from cardiovascular diseases, particularly ischemic heart disease. COVID-19 affects the heart, worsening existing heart conditions and causing myocardial injury. The mechanistic link between COVID-19 and acute myocardial infarction (AMI) is still being investigated to elucidate the underlying molecular perspectives. Methods: Genetic risk assessment was conducted using two-sample Mendelian randomization (TSMR) to determine the causality between COVID-19 and AMI. Weighted gene co-expression network analysis (WGCNA) and machine learning were used to discover and validate shared hub genes for the two diseases using bulk RNA sequencing (RNA-seq) datasets. Additionally, gene set enrichment analysis (GSEA) and single-cell RNA-seq (scRNA-seq) analyses were performed to characterize immune cell infiltration, communication, and immune correlation of the hub genes. To validate the findings, the expression patterns of hub genes were confirmed in clinical blood samples collected from COVID-19 patients with AMI. Results: TSMR did not find evidence supporting a causal association between COVID-19 or severe COVID-19 and AMI. In the bulk RNA-seq discovery cohorts for both COVID-19 and AMI, WGCNA’s intersection analysis and machine learning identified TLR4 and ABCA1 as significant hub genes, demonstrating high diagnostic and predictive value in the RNA-seq validation cohort. Single-gene GSEA and single-sample GSEA (ssGSEA) revealed immune and inflammatory roles for TLR4 and ABCA1, linked to various immune cell infiltrations. Furthermore, scRNA-seq analysis unveiled significant immune dysregulation in COVID-19 patients, characterized by altered immune cell proportions, phenotypic shifts, enhanced cell-cell communication, and elevated TLR4 and ABCA1 in CD16 monocytes. Lastly, the increased expression of TLR4, but not ABCA1, was validated in clinical blood samples from COVID-19 patients with AMI. Conclusion: No genetic causal link between COVID-19 and AMI and dysregulated TLR4 and ABCA1 may be responsible for the development of immune and inflammatory responses in COVID-19 patients with AMI
Genome-wide identification of heat shock proteins (Hsps) and Hsp interactors in rice: Hsp70s as a case study
BACKGROUND: Heat shock proteins (Hsps) perform a fundamental role in protecting plants against abiotic stresses. Although researchers have made great efforts on the functional analysis of individual family members, Hsps have not been fully characterized in rice (Oryza sativa L.) and little is known about their interactors. RESULTS: In this study, we combined orthology-based approach with expression association data to screen rice Hsps for the expression patterns of which strongly correlated with that of heat responsive probe-sets. Twenty-seven Hsp candidates were identified, including 12 small Hsps, six Hsp70s, three Hsp60s, three Hsp90s, and three clpB/Hsp100s. Then, using a combination of interolog and expression profile-based methods, we inferred 430 interactors of Hsp70s in rice, and validated the interactions by co-localization and function-based methods. Subsequent analysis showed 13 interacting domains and 28 target motifs were over-represented in Hsp70s interactors. Twenty-four GO terms of biological processes and five GO terms of molecular functions were enriched in the positive interactors, whose expression levels were positively associated with Hsp70s. Hsp70s interaction network implied that Hsp70s were involved in macromolecular translocation, carbohydrate metabolism, innate immunity, photosystem II repair and regulation of kinase activities. CONCLUSIONS: Twenty-seven Hsps in rice were identified and 430 interactors of Hsp70s were inferred and validated, then the interacting network of Hsp70s was induced and the function of Hsp70s was analyzed. Furthermore, two databases named Rice Heat Shock Proteins (RiceHsps) and Rice Gene Expression Profile (RGEP), and one online tool named Protein-Protein Interaction Predictor (PPIP), were constructed and could be accessed at http://bioinformatics.fafu.edu.cn/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-344) contains supplementary material, which is available to authorized users
Genetic and immunological insights into COVID-19 with acute myocardial infarction: integrated analysis of mendelian randomization, transcriptomics, and clinical samples
BackgroundGlobally, most deaths result from cardiovascular diseases, particularly ischemic heart disease. COVID-19 affects the heart, worsening existing heart conditions and causing myocardial injury. The mechanistic link between COVID-19 and acute myocardial infarction (AMI) is still being investigated to elucidate the underlying molecular perspectives.MethodsGenetic risk assessment was conducted using two-sample Mendelian randomization (TSMR) to determine the causality between COVID-19 and AMI. Weighted gene co-expression network analysis (WGCNA) and machine learning were used to discover and validate shared hub genes for the two diseases using bulk RNA sequencing (RNA-seq) datasets. Additionally, gene set enrichment analysis (GSEA) and single-cell RNA-seq (scRNA-seq) analyses were performed to characterize immune cell infiltration, communication, and immune correlation of the hub genes. To validate the findings, the expression patterns of hub genes were confirmed in clinical blood samples collected from COVID-19 patients with AMI.ResultsTSMR did not find evidence supporting a causal association between COVID-19 or severe COVID-19 and AMI. In the bulk RNA-seq discovery cohorts for both COVID-19 and AMI, WGCNA’s intersection analysis and machine learning identified TLR4 and ABCA1 as significant hub genes, demonstrating high diagnostic and predictive value in the RNA-seq validation cohort. Single-gene GSEA and single-sample GSEA (ssGSEA) revealed immune and inflammatory roles for TLR4 and ABCA1, linked to various immune cell infiltrations. Furthermore, scRNA-seq analysis unveiled significant immune dysregulation in COVID-19 patients, characterized by altered immune cell proportions, phenotypic shifts, enhanced cell-cell communication, and elevated TLR4 and ABCA1 in CD16 monocytes. Lastly, the increased expression of TLR4, but not ABCA1, was validated in clinical blood samples from COVID-19 patients with AMI.ConclusionNo genetic causal link between COVID-19 and AMI and dysregulated TLR4 and ABCA1 may be responsible for the development of immune and inflammatory responses in COVID-19 patients with AMI
Identification and pathogenicity of a variant porcine epidemic diarrhea virus field strain with reduced virulence
Two ultraviolet radiation datasets that cover China
Ultraviolet (UV) radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization's measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes
TaqMan MGB probe fluorescence real-time quantitative PCR for rapid detection of Chinese Sacbrood virus.
Sacbrood virus (SBV) is a picorna-like virus that affects honey bees (Apis mellifera) and results in the death of the larvae. Several procedures are available to detect Chinese SBV (CSBV) in clinical samples, but not to estimate the level of CSBV infection. The aim of this study was develop an assay for rapid detection and quantification of this virus. Primers and probes were designed that were specific for CSBV structural protein genes. A TaqMan minor groove binder (MGB) probe-based, fluorescence real-time quantitative PCR was established. The specificity, sensitivity and stability of the assay were assessed; specificity was high and there were no cross-reactivity with healthy larvae or other bee viruses. The assay was applied to detect CSBV in 37 clinical samples and its efficiency was compared with clinical diagnosis, electron microscopy observation, and conventional RT-PCR. The TaqMan MGB-based probe fluorescence real-time quantitative PCR for CSBV was more sensitive than other methods tested. This assay was a reliable, fast, and sensitive method that was used successfully to detect CSBV in clinical samples. The technology can provide a useful tool for rapid detection of CSBV. This study has established a useful protocol for CSBV testing, epidemiological investigation, and development of animal models
Neutron/gamma discrimination performance test for self-developed plastic scintillation detectors
BackgroundPlastic scintillators have potential for application in neutron detection. Two sizes (ø2.54 cm×2.54 cm, ø5.08 cm×5.08 cm) of plastic scintillators are self-developed by scientific research team in the school of physics, Sichuan University.PurposeThis study aims to experimental test the neutron/gamma (n-) discrimination performance for two self-developed plastic scintillators.MethodsA photomultiplier tube (PMT) was used to build detection systems, and high speed oscilloscope (LECROY HDO6104A) was employed to sample signal of detector for the energy calibration of the self-developed plastic scintillator. The pulse amplitude spectrum of 137Cs γ radiation source was measured and compared with the MCNP5 simulation spectrum to obtain the position information of the Compton edge and accurately calibrate the energies of γ rays. The data obtained from a 241Am-Be neutron source were analyzed using the charge integration method, and parameters such as the figure of merit (FOM), peak-to-valley ratio for neutrons, and the proportion of leaked neutrons over all neutron events were used to quantify the n-γ discrimination in different energy zones. The detection efficiencies of two self-developed plastic scintillators relative to the Commercial off-the-Shelf (COTS) EJ-299-33A were determined.ResultsThe results show that the FOM of ø2.54 cm×2.54 cm self-developed plastic scintillator is higher that of ø5.08 cm×5.08 cm self-developed plastic scintillator, and the detection efficiency of two self developed plastic scintillators relative to EJ-299-33A is about 0.49 and 1.0, respectively.ConclusionsThe performance of the ø5.08 cm×5.08 cm self-developed plastic scintillator is comparable to that of the COTS plastic scintillator EJ-299-33A with near the same discrimination ability
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