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Abstract RNF214 is an understudied ubiquitin ligase with little knowledge of its biological functions or protein substrates. Here we show that the TEAD transcription factors in the Hippo pathway are substrates of RNF214. RNF214 induces non-proteolytic ubiquitylation at a conserved lysine residue of TEADs, enhances interactions between TEADs and YAP, and promotes transactivation of the downstream genes of the Hippo signaling. Moreover, YAP and TAZ could bind polyubiquitin chains, implying the underlying mechanisms by which RNF214 regulates the Hippo pathway. Furthermore, RNF214 is overexpressed in hepatocellular carcinoma (HCC) and inversely correlates with differentiation status and patient survival. Consistently, RNF214 promotes tumor cell proliferation, migration, and invasion, and HCC tumorigenesis in mice. Collectively, our data reveal RNF214 as a critical component in the Hippo pathway by forming a signaling axis of RNF214-TEAD-YAP and suggest that RNF214 is an oncogene of HCC and could be a potential drug target of HCC therapy.

Abstract The combination of immunotherapy and molecular targeted therapy exhibits promising therapeutic efficacy in hepatocellular carcinoma (HCC), but the underlying mechanism is still unclear. Here, phosphoglycerate mutase 1 (PGAM1) is identified as a novel immunometabolic target by using a bioinformatic algorithm based on multiple HCC datasets. PGAM1 is highly expressed in HCC and associated with a poor prognosis and a poor response to immunotherapy. In vitro and in vivo experiments indicate that targeting PGAM1 inhibited HCC cell growth and promoted the infiltration of CD8+ T‐cells due to decreased enzymatic activity. Mechanistically, inhibition of PGAM1 promotes HCC cell ferroptosis by downregulating Lipocalin (LCN2) by inducing energy stress and ROS‐dependent AKT inhibition, which can also downregulate Programmed death 1‐ligand 1 (PD‐L1). Moreover, an allosteric PGAM1 inhibitor (KH3) exhibits good antitumor effects in patient‐derived xenograft (PDX) models and enhanced the efficacy of anti‐PD‐1 immunotherapy in subcutaneous and orthotopic HCC models. Taken together, the findings demonstrate that PGAM1 inhibition exerts an antitumor effect by promoting ferroptosis and CD8+ T‐cell infiltration and can synergize with anti‐PD‐1 immunotherapy in HCC. Targeting PGAM1 can be a promising new strategy of “killing two birds with one stone” for HCC treatment.

Abstract In this study, a feasibility of γ radiation detection using complementary metal-oxide semiconductor (CMOS) image sensors with a neural network algorithm to extract the γ rays interacted pixels has been investigated. The responses characteristics of the CMOS imaging sensor to γ-ray is studied by placed in a γ fields produced by standard60Co or137Cs isotope sources. The supported preview frame rate of the CMOS image sensor is 25 fps, establishing the functional relationship between the gray level histograms and the dose rate through the neural network, the high energy γ-ray from60Co and137Cs source radiation dose rate in µSv/h level can be detected using the CMOS imaging sensor. The results show that the proposed method can effectively identify the number of photon particles which detected by the radiation monitoring system based on CMOS image sensor, and infer that the CMOS imaging sensor with a radiation signal extraction algorithm can be used as a dose warner for radiation protection purpose.

PurposeAcute Mesenteric Ischemia (AMI) is a critical condition marked by restricted blood flow to the intestine, which can lead to tissue necrosis and fatal outcomes. We aimed to develop a deep learning (DL) model based on CT angiography (CTA) imaging and clinical data to diagnose AMI.MethodsA retrospective study was conducted on 228 patients suspected of AMI, divided into training and test sets. Clinical data (medical history and laboratory indicators) was included in a multivariate logistic regression analysis to identify the independent factors associated with AMI and establish a clinical factors model. The arterial and venous CTA images were utilized to construct DL model. A Fusion Model was constructed by integrating clinical factors into the DL model. The performance of the models was assessed using receiver operating characteristic (ROC) curves and decision curve analysis (DCA).ResultsAlbumin and International Normalized Ratio (INR) were associated with AMI by univariate and multivariate logistic regression (P < 0.05). In the test set, the area under ROC curve (AUC) of the clinical factor model was 0.60 (sensitivity 0.47, specificity 0.86). The AUC of the DL model based on CTA images reached 0.90, which was significantly higher than the AUC values of the clinical factor model, as confirmed by the DeLong test (P < 0.05). The Fusion Model also showed exceptional performance in terms of AUC, accuracy, sensitivity, specificity, and precision, with values of 0.96, 0.94, 0.94, 0.95, and 0.98, respectively. DCA indicated that the Fusion Model provided a greater net benefit than those of models based solely on imaging and clinical information across the majority of the reasonable threshold probabilities.ConclusionThe incorporation of CTA images and clinical information into the model markedly enhances the diagnostic accuracy and efficiency of AMI. This approach provides a reliable tool for the early diagnosis of AMI and the subsequent implementation of appropriate clinical intervention.

The porous structure SnFe3N@carbon materials (SnFe3N@C) and the fibrous structure SnFe3N@carbon materials (SnFe3N@CNFs) were synthesized by the simple sintering method and the electrospinning-sintering method using polyacrylonitrile and dicyandiamide as carbon and nitrogen sources. The XRD results demonstrates that the various structures of the SnFe3N@carbon materials are well crystallized, and TG analysis reveals that all samples contain approximately 60 wt% carbon, providing insights into the composition and the percentage of organic matter present. Raman spectroscopy and X-ray photoelectron spectroscopy further verified the XRD results, and no impurity phases were formed in the prepared products. VSM measurements revealed that the prepared two different structural SnFe3N@carbon materials exhibit superparamagnetic properties.

As a typical tight sandstone gas reservoir in the Ordos Basin, the second member of the Shanxi Formation in the XQ gas field in the Ordos Basin has had rich gas reservoirs and good development effects in the past. On the basis of previous studies, this paper brings new understanding to the sedimentary model of this area. Nine kinds of single lithofacies and seven kinds of lithofacies combinations are determined. Braided fluvial fan deposits in distributive fluvial systems likely developed in this area. The study area is part of the middle subfacies of this sedimentary facies, and five kinds of sedimentary microfacies environments developed. Finally, establishing sedimentary model based on sedimentary characteristics. The braided fluvial fan sedimentary model based on DFS is of great significance for deepening the understanding of terrestrial sedimentary systems and providing guidance for the exploration and development of oil and gas bearing basins.

Abstract In carbonate reservoirs characterized by the fracture‐cavity system as storage spaces, the drilling process is highly prone to the loss of drilling fluid. This not only affects drilling efficiency but can also lead to severe accidents, such as blowouts. Therefore, it is crucial to understand the distribution pattern of these fractures. However, the formation of carbonate rock fracture‐cavity system systems, being controlled by various factors, is difficult to precisely identify. This limitation hampers the efficient development of such types of oil and gas fields. This paper presents a case study of the M55 sub‐section carbonate gas reservoir in the Sulige gasfield, proposing an improved You Only Look Once v5s (YOLOv5s) deep learning algorithm. It utilizes enhanced training with conventional logging data to identify response characteristics of fractures in the carbonate reservoirs. And its identification results have been confirmed to be accurate by various fracture data obtained through different means, such as the core samples, cast thin section photographs, imaging logging data, and seismic attributes. This method incorporates the Ghost convolution module to replace the Conv module in the backbone network of the YOLOv5s model, and modifies the C3 module into a Ghost Bottleneck module, effectively making the model more lightweight. Additionally, a Convolutional Block Attention Module is integrated into the Neck network, enhancing the model's feature extraction capabilities. Finally, the method employs the Efficient Intersection over Union Loss function instead of the Complete Intersection over Union Loss, reducing the network's regression loss. The validation results using actual data demonstrate that this method achieves an average recognition accuracy of 87.3% for the fracture‐cavity system, which is a 3% improvement over the baseline model (YOLOv5s). This enhancement is beneficial for precisely locating the drilling fluid loss positions in carbonate reservoirs.

Serine/arginine-rich splicing factor 7 (SRSF7), a known splicing factor, has been revealed to play oncogenic roles in multiple cancers. However, the mechanisms underlying its oncogenic roles have not been well addressed. Here, based on N6-methyladenosine (m6A) co-methylation network analysis across diverse cell lines, we find that the gene expression of SRSF7 is positively correlated with glioblastoma (GBM) cell-specific m6A methylation. We then indicate that SRSF7 is a novel m6A regulator, which specifically facilitates the m6A methylation near its binding sites on the mRNAs involved in cell proliferation and migration, through recruiting the methyltransferase complex. Moreover, SRSF7 promotes the proliferation and migration of GBM cells largely dependent on the presence of the m6A methyltransferase. The two m6A sites on the mRNA for PDZ-binding kinase (PBK) are regulated by SRSF7 and partially mediate the effects of SRSF7 in GBM cells through recognition by insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2). Together, our discovery reveals a novel role of SRSF7 in regulating m6A and validates the presence and functional importance of temporal- and spatial-specific regulation of m6A mediated by RNA-binding proteins (RBPs).

Although the function of tRNAs in the translational process is well established, it remains controversial whether tRNA abundance is tightly associated with translational efficiency (TE) in mammals. Moreover, how critically the expression of tRNAs contributes to the establishment of tissue-specific proteomes in mammals has not been well addressed. Here, we measured both tRNA expression using demethylase-tRNA sequencing (DM-tRNA-seq) and TE of mRNAs using ribosome-tagging sequencing (RiboTag-seq) in the brain, heart, and testis of mice. Remarkable variation in the expression of tRNA isodecoders was observed among different tissues. When the statistical effect of isodecoder-grouping on reducing variations is considered through permutating the anticodons, we observed an expected reduction in the variation of anticodon expression across all samples, an unexpected smaller variation of anticodon usage bias, and an unexpected larger variation of tRNA isotype expression at amino acid level. Regardless of whether or not they share the same anticodons, the isodecoders encoding the same amino acids are co-expressed across different tissues. Based on the expression of tRNAs and the TE of mRNAs, we find that the tRNA adaptation index (tAI) and TE are significantly correlated in the same tissues but not between tissues; and tRNA expression and the amino acid composition of translating peptides are positively correlated in the same tissues but not between tissues. We therefore hypothesize that the tissue-specific expression of tRNAs might be due to post-transcriptional mechanisms. This study provides a resource for tRNA and translation studies, as well as novel insights into the dynamics of tRNAs and their roles in translational regulation.

Fire hazard assessment on green façade used to be carried out by a window plume. Large amount of fuel was burnt. A small pool fire placed adjacent to the façade can give similar effect on assessing the hazardous consequences. Fire plume characteristics provide important information of fire hazards adjacent to façade. The average flame height of rectangular source fire located against different sidewall materials were investigated in this study.Burning tests were conducted with rectangular burners of different dimensions with adjacent walls of different thermal properties, including steel plate and calcium silicate board. Experimental results of fire source with sidewall were compared with those in open space. Due to sidewall blockage, a deep necking-in structure was observed at the flame base and entrained air for combustion. Effect of aspect ratio of the fire pool and effect of heat loss through a sidewall on the average flame height were investigated. Convection lost would decrease the temperature of the fuel-air mixture and should not be ignored. On average, the mean flame height of the fire source with steel plate was 1.08 times that with calcium silicate board. A model for estimating the average flame height was developed by modifying the mirror model.

N6-methyladenosine (m6A) plays important role in lineage specifications of embryonic stem cells, but its role at specific sites has not been assessed. Here the authors develop an adenine editor-based strategy, and systematically identify functional m6A sites that control lineage decisions in human embryonic stem cells.

Abstract Background Canonical nonsense-mediated decay (NMD) is an important splicing-dependent process for mRNA surveillance in mammals. However, processed pseudogenes are not able to trigger NMD due to their lack of introns. It is largely unknown whether they have evolved other surveillance mechanisms. Results Here, we find that the RNAs of pseudogenes, especially processed pseudogenes, have dramatically higher m6A levels than their cognate protein-coding genes, associated with de novo m6A peaks and motifs in human cells. Furthermore, pseudogenes have rapidly accumulated m6A motifs during evolution. The m6A sites of pseudogenes are evolutionarily younger than neutral sites and their m6A levels are increasing, supporting the idea that m6A on the RNAs of pseudogenes is under positive selection. We then find that the m6A RNA modification of processed, rather than unprocessed, pseudogenes promotes cytosolic RNA degradation and attenuates interference with the RNAs of their cognate protein-coding genes. We experimentally validate the m6A RNA modification of two processed pseudogenes, DSTNP2 and NAP1L4P1, which promotes the RNA degradation of both pseudogenes and their cognate protein-coding genes DSTN and NAP1L4. In addition, the m6A of DSTNP2 regulation of DSTN is partially dependent on the miRNA miR-362-5p. Conclusions Our discovery reveals a novel evolutionary role of m6A RNA modification in cleaning up the unnecessary processed pseudogene transcripts to attenuate their interference with the regulatory network of protein-coding genes.

Latin Hypercube Design (LHD) is widely used in computer simulation to solve large-scale, complex, nonlinear problems. The high-dimensional LHD (HLHD) problem is one of the crucial issues and has been a large concern in the long run. This paper proposes an improved Hybrid Particle Swarm Optimization (IHPSO) algorithm to find the near-optimal HLHD by increasing the particle evolution speed and strengthening the local search. In the proposed algorithm, firstly, the diversity of the population is ensured through comprehensive learning. Secondly, the Minimum Point Distance (MPD) method is adopted to solve the oscillation problem of the PSO algorithm. Thirdly, the Ranked Ordered Value (ROV) rule is used to realize the discretization of the PSO algorithm. Finally, local and global searches are executed to find the near-optimal HLHD. The comparisons show the superiority of the proposed method compared with the existing algorithms in obtaining the near-optimal HLHD.

Abstract Based on a sum of well test interpretation analysis, the flowage characteristics of the gas in reservoir were analyzed from physical parameters and double-logarithm curve characteristics of gas wells. The result showed that the permeability of gas well-fracturing area is greatly improved, which is the main area to provide productivity. The speed of pressure transmission was slow because of extremely low permeability of outside the fracturing area and fluid flow was dominated by a linear flow. And three common well test interpretation models were extracted. The characteristics of bi-zonal compound reservoir of gas wells were specified by combination with peripheral supply and pressure change characteristics of gas wells. Variations of reservoir pressure and flowing bottom-hole pressure with time were simulated and quantified under different physical parameters and daily production. And the rational proration scheme of gas production wells was established by integration with numerical simulation method. Numerical simulation results of 21 sets of well patterns showed that there were two recovery inflection points. And a new model was built to research well interference degree that was defined by a new and original mathematical expression about production. The result showed that the infill well pattern should be controlled at 500 m × (500–600) m.

Abstract Spintronic devices are considered as one of the most promising technologies for non‐volatile memory and computing. However, two crucial drawbacks, that is, lack of intrinsic multi‐level operation and low on/off ratio, greatly hinder their further application for advanced computing concepts, such as deep neural network (DNN) accelerator. In this paper, a spintronic multi‐level memory unit with high on/off ratio is proposed by integrating several series‐connected magnetic tunnel junctions (MTJs) with perpendicular magnetic anisotropy (PMA) and a Schottky diode in parallel. Due to the rectification effect on the PMA MTJ, an on/off ratio over 100, two orders of magnitude higher than intrinsic values, is obtained under proper proportion of alternating current and direct current. Multiple resistance states are stably achieved and can be reconfigured by spin transfer torque effect. A computing‐in‐memory architecture based DNN accelerator for image classification with the experimental parameters of this proposal to evidence its application potential is also evaluated. This work can satisfy the rigorous requirements of DNN for memory unit and promote the development of high‐accuracy and robust artificial intelligence applications.

Abstract An efficient integration of electrochromic and electrochemical devices into one flexible entity enables both energy storage and energy‐saving dual‐functionalities. For this purpose, achieving both high electrochromic and electrochemical performance is the key aspect. Herein, a new 3D architecture is successfully made by knotting W17O47@PEDOT (poly(3,4‐ethylenedioxythiophene)):PSS (poly(styrenesulfonate)) nanowires with NaWO3 nanoknots, and interestingly, the 3D W17O47/(NaWO3‐knots)@PEDOT:PSS cathode thus‐made simultaneously exhibits a large optical modulation (79.7% at 633 nm), an ultra‐long cycling life (76% of original optical modulation retained after 12 400 cycles), and a high areal capacitance (55.1 mF cm−2 at 0.1 mA cm−2). Our density functional theory (DFT) calculations demonstrate that the much improved dual‐functional performance is correlated to the raised electronic conductivity and ion adsorption at the W17O47/(NaWO3 nanoknots) interface, together with the ion adsorption of PEDOT:PSS in the 3D‐knotted architecture. As a proof‐of‐concept application, different‐sized flexible dual‐functional electrochromic/electrochemical devices (FDEDs) were assembled and investigated for various application scenarios, including a smart window (15 cm × 10 cm), a wearable wristband (20 cm × 2.5 cm), and a smart eyeglass. The smart window made of the FDED enables a large temperature difference of 27.6°C confirm‐tested in model houses, where the energy source also powers three light‐emitting diodes (LEDs). The understandings of the key governing principles in the electrodes and dual‐functionalities provide a timely foundation for the new generation flexible multifunctional devices.

Radionuclide dispersion model, which is of critical importance to the emergency response of severe nuclear accident, is used to estimate the consequences arising from accidental or routine releases and to predict areas of high contamination. It is difficult to evaluate the radioactive consequence accurately and rapidly for the accidental release of radionuclides from marine reactor because of the complex mobility feature in the sea. Based on CFD method, a finite-volume, three-dimensional regional oceanic dispersion model was developed in this paper to simulate the dispersion of radionuclides originating from marine reactor. The simulated dose variation of 137Cs presented good agreement with the monitoring data of marine radioactive pollution caused by Fukushima Dai-ichi nuclear accident, which demonstrated the validity of the method. A severe accident scenario of marine reactor was simulated and analyzed, which indicates that the regional oceanic dispersion model can provide dose assessment for nuclear emergency response.

Fusion reactors are expected to be safer, more environmentally friendly, and to have a lower nuclear proliferation risk, compared with other nuclear energy systems. However, it is widely recognized that a large amount of radioactive materials will be produced by a fusion reactor. Therefore, it is important to fully understand the overall radiation risk level of fusion radioactive wastes (radwaste) compared with existing nuclear energy systems. Studies on the treatment of the fusion radwaste have been currently focused on three ultimate options: clearance, recycling, and disposal by activation assessment of radioactive materials from the operation and decommissioning of fusion reactors. However, the radiation risk in the management of fusion radwaste, especially in the final disposal, was seldom studied. Based on the comparative analysis of fusion radioactive waste with ITER and fission reactors (e.g., pressurized water reactor, PWR), this paper tries to discuss how to determine the radiation risk in the process of fusion radwaste management on the premise of the current feasible industrial technology. On this basis, a risk assessment framework for repository disposal under normal degradation and external events is proposed.

Background: Vascular calcification (VC) is an important predictor of prognosis in atherosclerosis, the phenotypic transformation of vascular smooth muscle cells (VSMCs) is thought to be a process of VC. However, the implications and potential mechanisms for VSMCs phenotypic transition remain unknown.Methods: To study the transformation of vascular smooth muscle cells (VSMCs) in the calcification early period, we analyzed single-cell sequencing data from carotid artery calcified core and paracellular tissue, based on the results of enrichment analysis and protein-protein interaction analysis. Upstream transcription factors were tracked and finally the results were validated using the MESA database.Results: We successfully identified a subpopulation of inflammatory macrophage-like VSMCs and determined that MMP9 is an important factor in the phenotypic transformation of VSMCs. We found that RELA regulates MMP9 expression and that knockdown of RELA attenuated MMP9 expression and reduced the expression of BMP2 and the macrophage marker LGALS3 in vascular smooth muscle in inflammatory states, while serum levels of MMP9 correlated significantly with the inflammatory response.Conclusion: This study reveals that the phenotypic transformation of VSMCs can be regulated by modulating MMP9, providing a new idea for the early treatment of VC.

Abstract:The Nenjiang Formation, south of Songliao Basin, has many hydrocarbon bearing units, but currently the understanding of the distribution of viable reservoir sandstones is too limited to support a development strategy. Therefore, a detailed study on the sedimentary microfacies and reservoir properties has been completed in order to reduce uncertainty and improve subsurface predictions. Nine lithofacies and five lithofacies associations were identified supporting the development of a sedimentary model of a river-dominated delta front setting, which could be divided into four sedimentary environments: subaqueous distributary channel-fill, mouth bar, sand sheet, and interdistributary bay. The distribution sandbodies extend to the south in a tongue-like form, and they thin and pinch out. Finally, the influence of sedimentary process on properties was assessed by establishing the correlation between microfacies and reservoir physical parameters, such as porosity, permeability, pore radius, throat radius, and clay minerals. It is revealed that the correspondence between reservoir physical properties and microfacies types is strong; the physical properties of the subaqueous distributary channel and mouth bar are the best.

Thermally conductive and electrically insulating materials have attracted much attention due to their applications in the field of microelectronics, but through-plane thermal conductivity of materials is still low at present. In this paper, a simple and environmentally friendly strategy is proposed to improve the through-plane thermal conductivity of epoxy composites using a 3D boron nitride (3D-BN) framework. In addition, the effect of filler sizes in 3D-BN skeletons on thermal conductivity was investigated. The epoxy composite with larger BN in lateral size showed a higher through-plane thermal conductivity of 2.01 W/m·K and maintained a low dielectric constant of 3.7 and a dielectric loss of 0.006 at 50 Hz, making it desirable for the application in microelectronic devices.

N6-methyladenosine (m6A) is the most abundant internal modification of mRNAs and is implicated in all aspects of post-transcriptional RNA metabolism. However, little is known about m6A modifications to circular (circ) RNAs. We developed a computational pipeline (AutoCirc) that, together with depletion of ribosomal RNA and m6A immunoprecipitation, defined thousands of m6A circRNAs with cell-type-specific expression. The presence of m6A circRNAs is corroborated by interaction between circRNAs and YTHDF1/YTHDF2, proteins that read m6A sites in mRNAs, and by reduced m6A levels upon depletion of METTL3, the m6A writer. Despite sharing m6A readers and writers, m6A circRNAs are frequently derived from exons that are not methylated in mRNAs, whereas mRNAs that are methylated on the same exons that compose m6A circRNAs exhibit less stability in a process regulated by YTHDF2. These results expand our understanding of the breadth of m6A modifications and uncover regulation of circRNAs through m6A modification.

A gas–water two-phase fluid is present in a reservoir before a water-flooded sandstone gas reservoir is rebuilt. Therefore, in the process of injection and production of the rebuilt underground gas storage, the injected gas is easily blocked by the water in the pores, and the efficiency is low, resulting in a significant loss of gas. The study completely utilizes the geological data and dynamic operation monitoring data of a water-flooded sandstone underground gas storage and clarifies the rule of the gas–water three-phase seepage in a high-intensity injection–production process. Moreover, the main control factors of the low efficiency of this type of underground gas storage are clarified. The lost gas generated in the injection–production process is described from two aspects: microcosmic experiment and macroscopic law analysis. The type, mechanism, and occurrence state of the loss gas are clearly defined, its main type is “water trapped gas”, it formed when the gas rushing into the water area under high pressure and surrounded by water, and its occurrence of this kind of lost gas is mainly sporadic or continuous free gas. A gas–water two-phase mathematical model that can simulate the high-intensity injection–production process is set up according to the experimental result, this model is used to simulate the operation process of the Ban 876 underground gas storage. Based on the simulation results, the gas–water macroscopic movement rule and macroscopic accumulation mode of the lost gas are defined, and then the collection area of the lost gas is predicted and quantitatively described. The calculation results show that the lost gas in one cycle is about 775 × 104 m3, which are mainly concentrated in the inner of the gas-water transition zone. According to the numerical simulation result, six new wells have been designed to develop its internal lost gas, they all have good predictions, can increase the working gas volume of 3000 × 104 m3 and reduce the single cycle lost gas by 50%, which is only 326 × 104 m3. This provides guidance for the expansion and exploitation of the same type of water-flooded sandstone underground gas storage.