A combined method for gas-bearing layer identification in a complex sandstone reservoir

Langgu Depression is a mature oil and gas exploration area with complicated lithological and physical properties. The varying formation fluid, low-resistivity hydrocarbon-bearing reservoirs, and non-uniform logging series greatly increase the difficulty of gas reservoir identification. The Monte Carlo method is employed to simulate the neutron–gamma logging responses to gas saturation and the influential factors. According to the result, a new gas identification chart eliminating the influence of porosity and formation water salinity is proposed to identify gas reservoirs in the old wells. At the same time, a fluid factor extracted from array acoustic logging and core measurement data is sensitive to the development of gas-bearing layers and useful for the identification of gas reservoirs in the new wells with array acoustic logging. The field examples show that the new combined method greatly improves the ability to identify gas-bearing layers and works well in old well reexamination and new well interpretation

Upregulation of Endogenous HMOX1 Expression by a Computer-Designed Artificial Transcription Factor

Heme oxygenase-1 (HO-1) is well known as a cytoprotective factor. Research has revealed that it is a promising therapeutic target for cardiovascular diseases. In the current study, an HMOX1 (HO-1 gene) enhancer-specific artificial zinc-finger protein (AZP) was designed using bioinformatical methods. Then, an artificial transcription factor (ATF) was constructed based on the AZP. In the ATF, the p65 functional domain was used as the effector domain (ED), and a nuclear localization sequence (NLS) was also included. We next analyzed the affinity of the ATF to the HMOX1 enhancer and the effect of the ATF on endogenous HMOX1 expression. The results suggest that the ATF could effectively upregulate endogenous HMOX1 expression in ECV304 cells. With further research, the ATF could be developed as a potential drug for cardiovascular diseases

Hydrate dissociation induced by gas diffusion from pore water to drilling fluid in a cold wellbore

It is a common view that the high temperature of the drilling fluid can lead to the dissociation of gas hydrate during drilling through hydrate-bearing sediments. This study indicates that the hydrate dissociation in wellbore can also be induced by gas diffusion from pore water to drilling fluid even if the temperature (and the pressure if necessary) of the drilling fluid is well controlled to keep the conditions of hydrate-bearing sediments along the hydrate equilibrium boundary. The dissociation of gas hydrate was modelled based on Fick's first law. It was found that the dissociation rate mainly depended on the temperature of the sediments. The locations of dissociation front of CH4 hydrate and CO2 hydrate in wellbore were calculated as a function of time. The impacts of the hydrate dissociation on the wellbore stability and the resistivity well logging in sediments were evaluated.Cited as: Sun, Y., Lu, H., Lu, C., Li, S., Lv, X. Hydrate dissociation induced by gas diffusion from pore water to drilling fluid in a cold wellbore. Advances in Geo-Energy Research, 2018, 2(4): 410-417, doi: 10.26804/ager.2018.04.0

Practical Quantum Simulation of Non-Hermitian Dynamics

Non-Hermitian quantum systems have recently attracted considerable attentions due to their exotic properties. Though many experimental realizations of non-Hermitian systems have been reported, the non-Hermiticity usually resorts to the hard-to-control environments. An alternative approach is to use quantum simulation with the closed system, whereas how to simulate general non-Hermitian Hamiltonian dynamics remains a great challenge. To tackle this problem, we propose a protocol by combining a dilation method with the variational quantum algorithm. The dilation method is used to transform a non-Hermitian Hamiltonian into a Hermitian one through an exquisite quantum circuit, while the variational quantum algorithm is for efficiently approximating the complex entangled gates in this circuit. As a demonstration, we apply our protocol to simulate the dynamics of an Ising chain with nonlocal non-Hermitian perturbations, which is an important model to study quantum phase transition at nonzero temperatures. The numerical simulation results are highly consistent with the theoretical predictions, revealing the effectiveness of our protocol. The presented protocol paves the way for practically simulating general non-Hermitian dynamics in the multi-qubit case.Comment: 9 pages, 5 figure

Upregulation of Endogenous HMOX1 Expression by a Computer-Designed Artificial Transcription Factor

Heme oxygenase-1 (HO-1) is well known as a cytoprotective factor. Research has revealed that it is a promising therapeutic target for cardiovascular diseases. In the current study, an HMOX1 (HO-1 gene) enhancer-specific artificial zinc-finger protein (AZP) was designed using bioinformatical methods. Then, an artificial transcription factor (ATF) was constructed based on the AZP. In the ATF, the p65 functional domain was used as the effector domain (ED), and a nuclear localization sequence (NLS) was also included. We next analyzed the affinity of the ATF to the HMOX1 enhancer and the effect of the ATF on endogenous HMOX1 expression. The results suggest that the ATF could effectively upregulate endogenous HMOX1 expression in ECV304 cells. With further research, the ATF could be developed as a potential drug for cardiovascular diseases

SIRT1-mediated downregulation of p27(Kip1) is essential for overcoming contact inhibition of Kaposi's sarcoma-associated herpesvirus transformed cells

Kaposi's sarcoma-associated herpesvirus (KSHV) is an oncogenic virus associated with Kaposi's sarcoma (KS), a malignancy commonly found in AIDS patients. Despite intensive studies in the last two decades, the mechanism of KSHV-induced cellular transformation and tumorigenesis remains unclear. In this study, we found that the expression of SIRT1, a metabolic sensor, was upregulated in a variety of KSHV-infected cells. In a model of KSHV-induced cellular transformation, SIRT1 knockdown with shRNAs or knockout by CRISPR/Cas9 gene editing dramatically suppressed cell proliferation and colony formation in soft agar of KSHV-transformed cells by inducing cell cycle arrest and contact inhibition. SIRT1 knockdown or knockout induced the expression of cyclin-dependent kinase inhibitor 1B (p27(Kip1)). Consequently, p27 knockdown rescued the inhibitory effect of SIRT1 knockdown or knockout on cell proliferation and colony formation. Furthermore, treatment of KSHV-transformed cells with a SIRT1 inhibitor, nicotinamide (NAM), had the same effect as SIRT1 knockdown and knockout. NAM significantly inhibited cell proliferation in culture and colony formation in soft agar, and induced cell cycle arrest. Significantly, NAM inhibited the progression of tumors and extended the survival of mice in a KSHV-induced tumor model. Collectively, these results demonstrate that SIRT1 suppression of p27 is required for KSHV-induced tumorigenesis and identify a potential therapeutic target for KS.

Classifying the surrounding rock of tunnel face using machine learning

Accurately classifying the surrounding rock of tunnel face is essential. In this paper, we propose a machine learning-based automatic classification and dynamic prediction method of the surrounding rocks of tunnel face using the data monitored by a computerized rock drilling trolley based on the intelligent mechanized construction process for drilling and blasting tunnels. This method provides auxiliary support for the intelligent decision of dynamic support at the construction site. First, this method solves the imbalance in the classification of the surrounding rock samples by constructing the Synthetic Minority Oversampling Technique (SMOTE) algorithm using 500 samples of drilling parameters covering different levels and lithologies of a tunnel. Second, it filters the importance of the characteristic samples based on the random forest method. Third, it uses the XGBoost algorithm to model the processed data and compare it with AdaBoost and BP neural network models. The results show that the XGBoost model achieves a higher accuracy of 87.5% when the sample size is small. Finally, we validate the application scenarios of the above algorithm/model regarding the key aspects of the tunnel construction process, such as surrounding rock identification, design interaction, construction supervision, and quality evaluation, which facilitates the upgrading of intelligent tunnel construction

Fc fragment of IgG binding protein is correlated with immune infiltration levels in hepatocellular carcinoma

The Fc fragment of IgG binding protein (FCGBP) has been confirmed to play an important role in various cancers. However, the specific role of FCGBP in hepatocellular carcinoma (HCC) remains undefined. Thus, in this study, the enrichment analyses (Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis) of FCGBP in HCC and extensive bioinformatic analyses using data of clinicopathologic characteristics, genetic expression and alterations, and immune cell infiltration were perfomed. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of FCGBP in both HCC tissues and cell lines. The subsequent results confirmed thatFCGBP overexpression positively correlated with poor prognosis in patients with HCC. Additionally, FCGBP expression could effectively distinguish tumor tissues from normal tissues, which was verified by qRT-PCR. The result was further confirmed by using HCC cell lines. The time-dependent survival receiver operator characteristic curve exhibited the strong ability of FCGBP to predict survival in patients with HCC. Additionally, we revealed the strong relationship between FCGBP expression and a number of classic regulatory targets and classical oncogenic signaling pathways of tumors. Finally, FCGBP was involved in the regulation of immune infiltration in HCC. Therefore, FCGBP has potential value in the diagnosis, treatment, and prognosis of HCC and may be a potential biomarker or therapeutic target

The deubiquitinase USP6 affects memory and synaptic plasticity through modulating NMDA receptor stability

人类与其他动物相比的重要区别在于人类拥有高等认知能力，这种能力集中体现在学习记忆和语言表达方面。厦门大学医学院神经科学研究所王鑫教授团队发现人科动物特异性基因USP6作为一个新的NMDA受体调控因子，可通过去泛素化途径调节NMDA型谷氨酸受体的降解和稳定性，进而调控突触可塑性和学习记忆能力。 本研究工作由王鑫教授指导完成，博士生曾凡伟、马学海与硕士生朱琳为共同第一作者，王鑫教授为通讯作者。Ubiquitin-specific protease (USP) 6 is a hominoid deubiquitinating enzyme previously implicated in intellectual disability and autism spectrum disorder. Although these findings link USP6 to higher brain function, potential roles for USP6 in cognition have not been investigated. Here, we report that USP6 is highly expressed in induced human neurons and that neuron-specific expression of USP6 enhances learning and memory in a transgenic mouse model. Similarly, USP6 expression regulates N-methyl-D-aspartate-type glutamate receptor (NMDAR)-dependent long-term potentiation and long-term depression in USP6 transgenic mouse hippocampi. Proteomic characterization of transgenic USP6 mouse cortex reveals attenuated NMDAR ubiquitination, with concomitant elevation in NMDAR expression, stability, and cell surface distribution with USP6 overexpression. USP6 positively modulates GluN1 expression in transfected cells, and USP6 down-regulation impedes focal GluN1 distribution at postsynaptic densities and impairs synaptic function in neurons derived from human embryonic stem cells. Together, these results indicate that USP6 enhances NMDAR stability to promote synaptic function and cognition.This work was partially supported by the National Natural Science Foundation of China (31871077, 81822014, 81571176 to XW; 81701349 to Hongfeng Z.; 81701130 to QZ; and 81471160 to HS), the National Key R&D Program of China (2016YFC1305900 to XW and HS), the Natural Science Foundation of Fujian Province of China (2017J06021 to XW), the Fundamental Research Funds for the Chinese Central Universities (20720150061 to XW and 20720180040 to ZS), Open Research Fund of State Key Laboratory of Cellular Stress Biology, Xiamen University (SKLCSB2019KF012 to QZ), and China Postdoctoral Science Foundation (2017M612130 to QZ).该研究得到了国家自然科学基金面上项目和优秀青年基金项目的支持