Simulation of counter-current imbibition in water-wet fractured reservoirs based on discrete-fracture model

Isolated fractures usually exist in fractured media systems, where the capillary pressure in the fracture is lower than that of the matrix, causing the discrepancy in oil recoveries between fractured and non-fractured porous media. Experiments, analytical solutions and conventional simulation methods based on the continuum model approach are incompetent or insufficient in describing media containing isolated fractures. In this paper, the simulation of the counter-current imbibition in fractured media is based on the discrete-fracture model (DFM). The interlocking or arrangement of matrix and fracture system within the model resembles the traditional discrete fracture network model and the hybrid-mixed-finite-element method is employed to solve the associated equations. The Behbahani experimental data validates our simulation solution for consistency. The simulation results of the fractured media show that the isolated-fractures affect the imbibition in the matrix block. Moreover, the isolated fracture parameters such as fracture length and fracture location influence the trend of the recovery curves. Thus, the counter-current imbibition behavior of media with isolated fractures can be predicted using this method based on the discrete-fracture model

Coal and Gas Outburst Risk Prediction and Management Based on WOA-ELM

A gas outburst risk level prediction method, based on the Whale Optimization Algorithm (WOA) Improved Extreme Learning Machine (ELM), is proposed to predict the coal and gas outburst hazard level more accurately. Based on this method, recommendations are given according to the gas outburst risk level with the help of the Case-Based Reasoning (CBR) method. Firstly, we analyze the accident reports of gas outburst accidents, select the gas outburst risk prediction index, and construct the gas outburst risk prediction index system by combining the gas outburst prevention and control process. The WOA-ELM model was used to predict the gas outburst risk level by selecting data from 150 accident reports from 2008 to 2021. Again, based on the coal and gas outburst risk level, CBR is used to match the cases and give corresponding suggestions for different levels of gas outburst risk conditions to help reduce the gas outburst risk. The results show that the WOA-ELM algorithm has better performance and faster convergence than the ELM algorithm, when compared in terms of accuracy and the error of gas outburst hazard prediction. The use of CBR to manage prediction results can be helpful for decision-makers

Coal and Gas Outburst Risk Prediction and Management Based on WOA-ELM

A gas outburst risk level prediction method, based on the Whale Optimization Algorithm (WOA) Improved Extreme Learning Machine (ELM), is proposed to predict the coal and gas outburst hazard level more accurately. Based on this method, recommendations are given according to the gas outburst risk level with the help of the Case-Based Reasoning (CBR) method. Firstly, we analyze the accident reports of gas outburst accidents, select the gas outburst risk prediction index, and construct the gas outburst risk prediction index system by combining the gas outburst prevention and control process. The WOA-ELM model was used to predict the gas outburst risk level by selecting data from 150 accident reports from 2008 to 2021. Again, based on the coal and gas outburst risk level, CBR is used to match the cases and give corresponding suggestions for different levels of gas outburst risk conditions to help reduce the gas outburst risk. The results show that the WOA-ELM algorithm has better performance and faster convergence than the ELM algorithm, when compared in terms of accuracy and the error of gas outburst hazard prediction. The use of CBR to manage prediction results can be helpful for decision-makers

A Novel Bioswitchable miRNA Mimic Delivery System: Therapeutic Strategies Upgraded from Tetrahedral Framework Nucleic Acid System for Fibrotic Disease Treatment and Pyroptosis Pathway Inhibition

Abstract There has been considerable interest in gene vectors and their role in regulating cellular activities and treating diseases since the advent of nucleic acid drugs. MicroRNA (miR) therapeutic strategies are research hotspots as they regulate gene expression post‐transcriptionally and treat a range of diseases. An original tetrahedral framework nucleic acid (tFNA) analog, a bioswitchable miR inhibitor delivery system (BiRDS) carrying miR inhibitors, is previously established; however, it remains unknown whether BiRDS can be equipped with miR mimics. Taking advantage of the transport capacity of tetrahedral framework nucleic acid (tFNA) and upgrading it further, the treatment outcomes of a traditional tFNA and BiRDS at different concentrations on TGF‐β‐ and bleomycin‐induced fibrosis simultaneously in vitro and in vivo are compared. An upgraded traditional tFNA is designed by successfully synthesizing a novel BiRDS, carrying a miR mimic, miR‐27a, for treating skin fibrosis and inhibiting the pyroptosis pathway, which exhibits stability and biocompatibility. BiRDS has three times higher efficiency in delivering miRNAs than the conventional tFNA with sticky ends. Moreover, BiRDS is more potent against fibrosis and pyroptosis‐related diseases than tFNAs. These findings indicate that the BiRDS can be applied as a drug delivery system for disease treatment

Transcriptional Dysregulations of Seven Non-Differentially Expressed Genes as Biomarkers of Metastatic Colon Cancer

Background: Colon cancer (CC) is common, and the mortality rate greatly increases as the disease progresses to the metastatic stage. Early detection of metastatic colon cancer (mCC) is crucial for reducing the mortality rate. Most previous studies have focused on the top-ranked differentially expressed transcriptomic biomarkers between mCC and primary CC while ignoring non-differentially expressed genes. Results: This study proposed that the complicated inter-feature correlations could be quantitatively formulated as a complementary transcriptomic view. We used a regression model to formulate the correlation between the expression levels of a messenger RNA (mRNA) and its regulatory transcription factors (TFs). The change between the predicted and real expression levels of a query mRNA was defined as the mqTrans value in the given sample, reflecting transcription regulatory changes compared with the model-training samples. A dark biomarker in mCC is defined as an mRNA gene that is non-differentially expressed in mCC but demonstrates mqTrans values significantly associated with mCC. This study detected seven dark biomarkers using 805 samples from three independent datasets. Evidence from the literature supports the role of some of these dark biomarkers. Conclusions: This study presented a complementary high-dimensional analysis procedure for transcriptome-based biomarker investigations with a case study on mCC

Genome-wide identification of the bHLH transcription factor family in Rosa persica and response to low-temperature stress

Background Basic helix-loop-helix (bHLH) transcription factors are involved in plant growth and development, secondary metabolism, and abiotic stress responses have been studied in a variety of plants. Despite their importance in plant biology, the roles and expression patterns of bHLH family genes in Rosa persica have not been determined. Methods In this study, the RbebHLH family genes were systematically analyzed using bioinformatics methods, and their expression patterns under low-temperature stress were analyzed by transcriptome and related physiological index measurements. Results In total, 142 RbebHLHs were identified in the genome of R. persica, distributed on seven chromosomes. Phylogenetic analysis including orthologous genes in Arabidopsis divided RbebHLHs into 21 subfamilies, with similar structures and motifs within a subfamily. A collinearity analysis revealed seven tandem duplications and 118 segmental duplications in R. persica and 127, 150, 151, 172, and 164 segmental duplications between R. persica and Arabidopsis thaliana, Prunus mume, Fragaria vesca, Rosa chinensis, and Prunus persica, respectively. A number of cis-regulatory elements associated with abiotic stress response and hormone response were identified in RbebHLHs, and 21 RbebHLHs have potential interactions with the CBF family. In addition, the expression results showed that part of bHLH may regulate the tolerance of R. persica to low-temperature stress through the jasmonic acid and pathway. Transcriptomic data showed that the expression levels of different RbebHLHs varied during overwintering, and the expression of some RbebHLHs was significantly correlated with relative conductivity and MDA content, implying that RbebHLHs play important regulatory roles in R. persica response to low-temperature stress. Overall, this study provides valuable insights into the study of RbebHLHs associated with low-temperature stress

Effect of Gegen Qinlian Decoction on Cardiac Gene Expression in Diabetic Mice

The aim of this research is to investigate the therapeutic effect of GGQL decoction on cardiac dysfunction and elucidate the pharmacological mechanisms. db/db mice were divided into DB group or GGQL group, and WT mice were used as control. All mice were accessed by echocardiography. And the total RNA of LV tissue samples was sequenced, then differential expression genes were analyzed. The RNA-seq results were validated by the results of RT-qPCR of 4 genes identified as differentially expressed. The content of pyruvate and ceramide in myocardial tissue was also measured. The results showed that GGQL decoction could significantly improve the diastolic dysfunction, increase the content of pyruvate, and had the trend to reduce the ceramide content. The results of RNA-seq showed that 2958 genes were differentially expressed when comparing the DB group with the WT group. Among them, compared with the DB group, 26 genes were differentially regulated in the GGQL group. The expression results of 4 genes were consistent with the RNA-seq results. Our study reveals that GGQL decoction has a therapeutic effect on diastolic dysfunction of the left ventricular and the effect may be related to its role in promoting myocardial glycolysis and decreasing the content of ceramide

A multi-vehicle longitudinal trajectory collision avoidance strategy using AEBS with vehicle-infrastructure communication

Shortening inter-vehicle distance can increase traffic throughput on roads for increasing volume of vehicles. In the process, traffic accidents occur more frequently, especially for multi-car accidents. Furthermore, it is difficult for drivers to drive safely under such complex driving conditions. This paper investigates multi-vehicle longitudinal collision avoidance issue under such traffic conditions based on the Advanced Emergency Braking System (AEBS). AEBS is used to avoid collisions or mitigate the impact during critical situations by applying brake automatically. Hierarchical multi-vehicle longitudinal collision avoidance controller is proposed to guarantee safety of multi-cars using Vehicle-to-Infrastructure (V2I) communication. High-level controller is designed to ensure safety of multi-cars and optimize total energy by calculating the target braking force. Vehicle network is used to get the key vehicle-road interaction data and constrained hybrid genetic algorithm (CHGA) is adopted to decouple the vehicle-road interactive system. Lower level non-singular Fractional Terminal Sliding Mode(NFTSM) Controller is built to achieve control goals of high-level controller. Simulations are carried out under typical driving conditions. Results verify that the proposed system in this paper can avoid or mitigate the collision risk compared to the vehicle without this system

Role of A2B adenosine receptor-dependent adenosine signaling in multi-walled carbon nanotube-triggered lung fibrosis in mice

Abstract Background Multi-walled carbon nanotube (MWCNT)-induced lung fibrosis leads to health concerns in human. However, the mechanisms underlying fibrosis pathogenesis remains unclear. The adenosine (ADO) is produced in response to injury and serves a detrimental role in lung fibrosis. In this study, we aimed to explore the ADO signaling in the progression of lung fibrosis induced by MWCNT. Results MWCNT exposure markedly increased A2B adenosine receptor (A2BAR) expression in the lungs and ADO level in bronchoalveolar lavage fluid, combined with elevation of blood neutrophils, collagen fiber deposition, and activation of myeloperoxidase (MPO) activity in the lungs. Furthermore, MWCNT exposure elicited an activation of transforming growth factor (TGF)-β1 and follistatin-like 1 (Fstl1), leading to fibroblasts recruitment and differentiation into myofibroblasts in the lungs in an A2BAR-dependent manner. Conversely, treatment of the selective A2BAR antagonist CVT-6883 exhibited a significant reduction in levels of fibrosis mediators and efficiently decreased cytotoxicity and inflammatory in MWCNT treated mice. Conclusion Our results reveal that accumulation of extracellular ADO promotes the process of the fibroblast-to-myofibroblast transition via A2BAR/TGF-β1/Fstl1 signaling in MWCNT-induced lung fibrosis