Search

This paper presents a comprehensive study based on multiphase-seepage and wellbore multiphase-flow theories. It establishes a model for calculating the rate of gas intrusion that considers various factors, including formation pore permeability, bottomhole pressure difference, rheology of the drilling fluid, and surface tension. Experiments were conducted to investigate the mechanism of gas intrusion under shut-in conditions, and the experimental results were employed to validate the reliability of the proposed method for calculating the gas intrusion rate. Furthermore, this research explores the transportation rates of single bubbles and bubble clusters in drilling fluid under shut-in conditions. Additionally, empirical expressions were derived for the drag coefficient for single bubbles and bubble clusters in the wellbore. These expressions can be used to calculate gas transportation rates for various equivalent radii of single bubbles and bubble clusters. The initial bubble size of intrusive gas, the transportation speed of intrusive gas in the wellbore, the rate of gas intrusion, and variations in the wellbore pressure after gas intrusion were analyzed. Additionally, a method was developed to calculate the rising velocity of bubble clusters in water based on experimental results. The study reveals that the average bubble size in the bubble cluster is significantly smaller than the size of single bubbles generated from the orifice. When the viscosity of the drilling fluid is low, the transportation velocity of the bubble cluster exhibits a positive correlation with the average bubble diameter. When the average bubble diameter exceeds 1 mm, the bubble velocity no longer varies with changes in the bubble-cluster diameter. The research results provide theoretical support for wellbore pressure prediction and pressure control under shutdown conditions. [ABSTRACT FROM AUTHOR]

Congenital heart disease is one of the leading causes of pediatric morbidity and mortality, thus highlighting the importance of deciphering the molecular mechanisms that control heart development. As the terminal transcriptional effectors of the Hippo–YAP pathway, YAP and TEAD1 form a transcriptional complex that regulates the target gene expression and depletes either of these two genes in cardiomyocytes, thus resulting in cardiac hypoplasia. Vestigial-like 4 (VGLL4) is a transcriptional co-factor that interacts with TEAD and suppresses the YAP/TEAD complex by competing against YAP for TEAD binding. To understand the VGLL4 function in the heart, we generated two VGLL4 loss-of-function mouse lines: a germline Vgll4 depletion allele and a cardiomyocyte-specific Vgll4 depletion allele. The whole-body deletion of Vgll4 caused defective embryo development and perinatal lethality. The analysis of the embryos at day 16.5 revealed that Vgll4 knockout embryos had reduced body size, malformed tricuspid valves, and normal myocardium. Few whole-body Vgll4 knockout pups could survive up to 10 days, and none of them showed body weight gain. In contrast to the whole-body Vgll4 knockout mutants, cardiomyocyte-specific Vgll4 knockout mice had no noticeable heart growth defects and had normal heart function. In summary, our data suggest that VGLL4 is required for embryo development but dispensable for myocardial growth. [ABSTRACT FROM AUTHOR]

Functional brain network (FBN) is an intuitive expression of the dynamic neural activity interaction between different neurons, neuron clusters, or cerebral cortex regions. It can characterize the brain network topology and dynamic properties. The method of building an FBN to characterize the features of the brain network accurately and effectively is a challenging subject. Entropy can effectively describe the complexity, non-linearity, and uncertainty of electroencephalogram (EEG) signals. As a relatively new research direction, the research of the FBN construction method based on EEG data of fatigue driving has broad prospects. Therefore, it is of great significance to study the entropy-based FBN construction. We focus on selecting appropriate entropy features to characterize EEG signals and construct an FBN. On the real data set of fatigue driving, FBN models based on different entropies are constructed to identify the state of fatigue driving. Through analyzing network measurement indicators, the experiment shows that the FBN model based on fuzzy entropy can achieve excellent classification recognition rate and good classification stability. In addition, when compared with the other model based on the same data set, our model could obtain a higher accuracy and more stable classification results even if the length of the intercepted EEG signal is different. [ABSTRACT FROM AUTHOR]

Toll-like receptors (TLRs) are a family of pattern recognition receptors (PRRs) that modulate innate immune responses and play essential roles in the pathogenesis of heart diseases. Although important, the molecular mechanisms controlling cardiac TLR genes expression have not been clearly addressed. This study examined the expression pattern of Tlr1, Tlr2, Tlr3, Tlr4, Tlr5, Tlr6, Tlr7, Tlr8, and Tlr9 in normal and disease-stressed mouse hearts. Our results demonstrated that the expression levels of cardiac Tlr3, Tlr7, Tlr8, and Tlr9 increased with age between neonatal and adult developmental stages, whereas the expression of Tlr5 decreased with age. Furthermore, pathological stress increased the expression levels of Tlr2, Tlr4, Tlr5, Tlr7, Tlr8, and Tlr9. Hippo-YAP signaling is essential for heart development and homeostasis maintenance, and YAP/TEAD1 complex is the terminal effector of this pathway. Here we found that TEAD1 directly bound genomic regions adjacent to Tlr1, Tlr2, Tlr3, Tlr4, Tlr5, Tlr6, Tlr7, and Tlr9. In vitro, luciferase reporter data suggest that YAP/TEAD1 repression of Tlr4 depends on a conserved TEAD1 binding motif near Tlr4 transcription start site. In vivo, cardiomyocyte-specific YAP depletion increased the expression of most examined TLR genes, activated the synthesis of pro-inflammatory cytokines, and predisposed the heart to lipopolysaccharide stress. In conclusion, our data indicate that the expression of cardiac TLR genes is associated with age and activated by pathological stress and suggest that YAP/TEAD1 complex is a default repressor of cardiac TLR genes. [ABSTRACT FROM AUTHOR]