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High-voltage lithium metal batteries based on high-nickel layered oxide cathodes are attractive due to their high energy density. However, they suffer from a severe decline in capacity at low temperatures, and the limited voltage range of low-temperature electrolytes fails to meet their application. To address this issue, we developed low-temperature carbonated electrolytes for lithium metal batteries with robust LiPxOyFz- and LiF-rich Li+-conductive electrode–electrolyte interphases. The dual interphases with a LiPO2F2 additive could accelerate Li+ migration, reduce impedance, prevent electrolyte consumption, alleviate cathode degradation, and even mitigate the severe polarization of the Li anode at −50 °C. As a result, a 4.6-V Li||NCM811 cell with an optimized electrolyte sustained 160 cycles before reaching the 80% threshold and sustained a 92% capacity retention rate (139.9 mAh g−1) at 20 mA g−1/−30 °C after 50 cycles. Moreover, it could deliver 118 mAh g−1 even at 20 mA g−1/−50 °C.

As the global economy expands, waterway transportation has become increasingly crucial to the logistics sector. This growth presents both significant challenges and opportunities for enhancing the accuracy of ship detection and tracking through the application of artificial intelligence. This article introduces a multi-object tracking system designed for unmanned aerial vehicles (UAVs), utilizing the YOLOv7 and Deep SORT algorithms for detection and tracking, respectively. To mitigate the impact of limited ship data on model training, transfer learning techniques are employed to enhance the YOLOv7 model's performance. Additionally, the integration of the SimAM attention mechanism within the YOLOv7 detection model improves feature representation by emphasizing salient features and suppressing irrelevant information, thereby boosting detection capabilities. The inclusion of the partial convolution (PConv) module further enhances the detection of irregularly shaped or partially occluded targets. This module minimizes the influence of invalid regions during feature extraction, resulting in more accurate and stable features. The implementation of PConv not only improves detection accuracy and speed but also reduces the model's parameters and computational demands, making it more suitable for deployment on computationally constrained UAV platforms. Furthermore, to address issues of false negatives during clustering in the Deep SORT algorithm, the IOU metric is replaced with the DIOU metric at the matching stage. This adjustment enhances the matching of unlinked tracks with detected objects, reducing missed detections and improving the accuracy of target tracking. Compared to the original YOLOv7+Deep SORT model, which achieved an MOTA of 58.4% and an MOTP of 78.9%, the enhanced system achieves a MOTA of 65.3% and a MOTP of 81.9%. This represents an increase of 6.9% in MOTA and 3.0% in MOTP. After extensive evaluation and analysis, the system has demonstrated robust performance in ship monitoring scenarios, offering valuable insights and serving as a critical reference for ship surveillance tasks.

Summary: To understand heart aging at the single-cell level, we employed single-cell dual omics (scRNA-seq and scATAC-seq) in profiling non-myocytes (non-CMs) from young, middle-aged, and elderly mice. Non-CMs, vital in heart development, physiology, and pathology, are understudied compared to cardiomyocytes. Our analysis revealed aging response heterogeneity and its dynamics over time. Immune cells, notably macrophages and neutrophils, showed significant aging alterations, while endothelial cells displayed moderate changes. We identified distinct aging signatures within the cell type, including differential gene expression, transcription factor activity, and motif variation. Sub-cluster analysis revealed intra-cell type heterogeneity, characterized by diverse aging patterns. The senescence-associated secretory phenotype emerged as a key aging-related phenotype. Moreover, aging significantly influenced cell-cell communication, especially impacting a fibroblast sub-cluster with high expression of ERBB4. This study elucidates the complex cellular and molecular landscape of cardiac aging and offers guidance for potential therapeutic avenues to treat aging-related heart diseases.

Direct cardiac reprogramming of fibroblasts into induced cardiomyocytes (iCMs) can be achieved by ectopic expression of cardiac transcription factors (TFs) via viral vectors. However, risks like genomic mutations, viral toxicity, and immune response limited its clinical application. Transactivation of endogenous TFs emerges as an alternative approach that may partially mitigate some of the risks. In this study, we utilized a modified CRISPRa/dCas9 strategy to transactivate endogenous reprogramming factors MEF2C, GATA4, and TBX5 (MGT) to induce iCMs from both mouse and human fibroblasts. We identified single-guide RNAs (sgRNAs) targeting promoters and enhancers of the TFs capable of activating various degrees of endogenous gene expression. CRISPRa-mediated Gata4 activation, combined with exogenous expression of Mef2c and Tbx5, successfully converted fibroblasts into iCMs. Despite extensive sgRNA screening, transactivation of Mef2c and Tbx5 via CRISPRa remained less effective, potentially due to de novo epigenetic barriers. While future work and refined technologies are needed to determine whether cardiac reprogramming could be achieved solely through CRISPRa activation of endogenous factors, our findings provide proof of concept that reliance on exogenous TFs for reprogramming can be reduced through CRISPRa-mediated activation of endogenous factors, particularly Gata4, offering a novel strategy to convert scar-forming fibroblasts into iCMs for regenerative purposes.

Abstract It is a challenging and meaningful task to carry out UAV-based livestock monitoring in high-altitude (more than 4500 m on average) and cold regions (annual average – 4 °C) on the Qinghai Tibet Plateau. The purpose of artificial intelligence (AI) is to execute automated tasks and to solve practical problems in actual applications by combining the software technology with the hardware carrier to create integrated advanced devices. Only in this way, the maximum value of AI could be realized. In this paper, a real-time tracking system with dynamic target tracking ability is proposed. It is developed based on the tracking-by-detection architecture using YOLOv7 and Deep SORT algorithms for target detection and tracking, respectively. In response to the problems encountered in the tracking process of complex and dense scenes, our work (1) Uses optical flow to compensate the Kalman filter, to solve the problem of mismatch between the target bounding box predicted by the Kalman filter (KF) and the input when the target detection in the current frame is complex, thereby improving the prediction accuracy; (2) Using a low confidence trajectory filtering method to reduce false positive trajectories generated by Deep SORT, thereby mitigating the impact of unreliable detection on target tracking. (3) A visual servo controller has been designed for the Unmanned Aerial Vehicle (UAV) to reduce the impact of rapid movement on tracking and ensure that the target is always within the field of view of the UAV camera, thereby achieving automatic tracking tasks. Finally, the system was tested using Tibetan yaks on the Qinghai Tibet Plateau as tracking targets, and the results showed that the system has real-time multi tracking ability and ideal visual servo effect in complex and dense scenes.

Abstract Endothelial cells are a heterogeneous population with various organ-specific and conserved functions that are critical to organ development, function, and regeneration. Here we report a Sox17-Erg direct reprogramming approach that uses cardiac fibroblasts to create differentiated endothelial cells that demonstrate endothelial-like molecular and physiological functions in vitro and in vivo. Injection of these induced endothelial cells into myocardial infarct sites after injury results in improved vascular perfusion of the scar region. Furthermore, we use genomic analyses to illustrate that Sox17-Erg reprogramming instructs cardiac fibroblasts toward an arterial-like identity. This results in a more efficient direct conversion of fibroblasts into endothelial-like cells when compared to traditional Etv2-based reprogramming. Overall, this Sox17-Erg direct reprogramming strategy offers a robust tool to generate endothelial cells both in vitro and in vivo, and has the potential to be used in repairing injured tissue.

This study proposes a method of autonomous navigation UAV for oil and gas pipeline (OGP) dial detection based on the improved YOLOv7 model. The canny edge detection algorithm is applied in identifying the edges of the pipeline, and the Hough transform algorithm is used to detect the pipeline in a straight line. The intelligent UAV P600 is guided to patrol the oil and gas dials (OGD) along the pipeline, and the trained improved YOLOv7-based model is adopted to identify the OGD data. Dial recognition is divided into two stages, that is, dial contour detection and dial reading recognition. For the dial recognition rate (RR), the Levenstein distance, a commonly used method, is introduced, thereby calculating the distance between two character sequences. Meanwhile, an integrated global attention mechanism (GAM) is proposed based on the YOLOv7 model, aiming at extracting more informative features. With this mechanism, the channel and spatial aspects of the features are effectively captured, and the importance of cross-dimensional interactions is increased. By introducing GAM attention mechanism in the backbone and head of YOLOv7, the network’s ability in efficiently extracting depth and primary features is enhanced. ACmix (a hybrid model combining the advantages of self-attentiveness and convolution) is also included, with ACmix module improved. The improved ACmix module has the objectives of enhancing feature extraction capability of backbone network and accelerating network convergence. By substituting 3 × 3 convolutional block with 3 × 3 ACmixBlock and adding a jump connection and a 1 × 1 convolutional structure between the ACmixBlock modules, E-ELAN module in YOLOv7 network is also improved, thus optimizing E-ELAN network, enriching features extracted by E-ELAN network, and reducing inference time of YOLOv7 model. As indicated by comparing the experimental results of the six model algorithms (improved YOLOv7, YOLOv7, YOLOX, YOLOv5, YOLOv6 and Faster R-CNN), the improved YOLOv7 model has higher mAP, faster RR, faster network convergence, and higher IOU. In addition, a generic real dataset, called custom dial reading dataset, is presented. With well-defined evaluation protocol, this dataset allows for a fair comparison of various methods in future work.

Unmanned aerial vehicles (UAVs) have made significant advances in autonomous sensing, particularly in the field of precision agriculture. Effective path planning is critical for autonomous navigation in large orchards to ensure that UAVs are able to recognize the optimal route between the start and end points. When UAVs perform tasks such as crop protection, monitoring, and data collection in orchard environments, they must be able to adapt to dynamic conditions. To address these challenges, this study proposes an enhanced Q-learning algorithm designed to optimize UAV path planning by combining static and dynamic obstacle avoidance features. A shortest distance priority (SDP) strategy is integrated into the learning process to minimize the distance the UAV must travel to reach the target. In addition, the root mean square propagation (RMSP) method is used to dynamically adjust the learning rate according to gradient changes, which accelerates the learning process and improves path planning efficiency. In this study, firstly, the proposed method was compared with state-of-the-art path planning techniques (including A-star, Dijkstra, and traditional Q-learning) in terms of learning time and path length through a grid-based 2D simulation environment. The results showed that the proposed method significantly improved performance compared to existing methods. In addition, 3D simulation experiments were conducted in the AirSim virtual environment. Due to the complexity of the 3D state, a deep neural network was used to calculate the Q-value based on the proposed algorithm. The results indicate that the proposed method can achieve the shortest path planning and obstacle avoidance operations in an orchard 3D simulation environment. Therefore, drones equipped with this algorithm are expected to make outstanding contributions to the development of precision agriculture through intelligent navigation and obstacle avoidance.

Abstract The serine/threonine kinase, PINK1, and the E3 ubiquitin ligase, Parkin, are known to facilitate LC3-dependent autophagosomal encasement and lysosomal clearance of dysfunctional mitochondria, and defects in this process contribute to a variety of cardiometabolic and neurological diseases. Although recent evidence indicates that dynamic actin remodeling plays an important role in PINK1/Parkin-mediated mitochondrial autophagy (mitophagy), the underlying signaling mechanisms remain unknown. Here, we identify the RhoGAP GRAF1 (Arhgap26) as a PINK1 substrate that regulates mitophagy. GRAF1 promotes the release of damaged mitochondria from F-actin anchors, regulates mitochondrial-associated Arp2/3-mediated actin remodeling and facilitates Parkin-LC3 interactions to enhance mitochondria capture by autophagosomes. Graf1 phosphorylation on PINK1-dependent sites is dysregulated in human heart failure, and cardiomyocyte-restricted Graf1 depletion in mice blunts mitochondrial clearance and attenuates compensatory metabolic adaptations to stress. Overall, we identify GRAF1 as an enzyme that coordinates cytoskeletal and metabolic remodeling to promote cardioprotection.

The FAO56 Penman–Monteith model (FAO56-PM) is widely used for estimating reference crop evapotranspiration (ET0). However, key variables such as shortwave radiation (Rs) and net longwave radiation (Rln) are often unavailable at most weather stations. While previous studies have focused on calibrating Rs, the influence of large Rln, particularly in high-altitude regions with thin air, remains unexplored. This study investigates this issue by using observed data from Bange in central Tibet to identify the optimal methods for estimating Rs and Rln to accurately calculate ET0. The findings reveal that the average daily Rln was 8.172 MJ m−2 d−1 at Bange, much larger than that at the same latitude. The original FAO56-PM model may produce seemingly accurate ET0 estimates due to compensating errors: underestimated Rln offsetting underestimated net shortwave radiation (Rsn). Merely calibrating Rs does not improve ET0 accuracy but may exacerbate errors. The Liu-S was the empirical model for Rs estimation calibrated by parameterization over the Tibetan Plateau and the Allen-LC was the empirical model for Rln estimation calibrated by local measurements in central Tibet. The combination of the Liu-S and Allen-LC methods showed much-improved performance in ET0 estimation, yielding a high Nash–Sutcliffe Efficiency (NSE) of 0.889 and a low relative error of −5.7%. This strategy is indicated as optimal for ET0 estimation in central Tibet. Trend analysis based on this optimal strategy indicates significant increases in ET0 in central Tibet from 2000 to 2020, with projections suggesting a continued rise through 2100 under climate change scenarios, though with increasing uncertainty over time. However, the rapidly increasing trends in precipitation will lead to decreasing trends in agricultural water use for highland parley production in central Tibet under climate change scenarios. The findings in this study provide critical information for irrigation planning to achieve sustainable agricultural production over the Tibetan Plateau.

Cardiovascular diseases are a leading cause of mortality worldwide, and the risks of both developing a disease and receiving a poor prognosis increase with age. With increasing life expectancy, understanding the mechanisms underlying heart aging has become critical. Traditional techniques have supported research into finding the physiological changes and hallmarks of cardiovascular aging, including oxidative stress, disabled macroautophagy, loss of proteostasis, and epigenetic alterations, among others. The advent of high-throughput multi-omics techniques offers new perspectives on the molecular mechanisms and cellular processes in the heart, guiding the development of therapeutic targets. This review explores the contributions and characteristics of these high-throughput techniques to unraveling heart aging. We discuss how different high-throughput omics approaches, both alone and in combination, produce robust and exciting new findings and outline future directions and prospects in studying heart aging in this new era.

Heart disease continues to be one of the most fatal conditions worldwide. This is in part due to the maladaptive remodeling process by which ischemic cardiac tissue is replaced with a fibrotic scar. Direct cardiac reprogramming presents a unique solution for restoring injured cardiac tissue through the direct conversion of fibroblasts into induced cardiomyocytes, bypassing the transition through a pluripotent state. Since its inception in 2010, direct cardiac reprogramming using the transcription factors Gata4, Mef2c, and Tbx5 has revolutionized the field of cardiac regenerative medicine. Just over a decade later, the field has rapidly evolved through the expansion of identified molecular and genetic factors that can be used to optimize reprogramming efficiency. The integration of computational tools into the study of direct cardiac reprogramming has been critical to this progress. Advancements in transcriptomics, epigenetics, proteomics, genome editing, and machine learning have not only enhanced our understanding of the underlying mechanisms driving this cell fate transition, but have also driven innovations that push direct cardiac reprogramming closer to clinical application. This review article explores how these computational advancements have impacted and continue to shape the field of direct cardiac reprogramming.

To explore the association and the underlying process between meaning in life and psychological health, a stratified random sampling was conducted on undergraduate students from five universities in Fujian Province from March to April 2022, with the Meaning in Life Questionnaire, the Self-Esteem Scale, the Interpersonal Trust Scale, and the Kessler10 Scale. The results indicated that 34.5% of Chinese undergraduates were in poor or worse mental health. There were significant positive correlations among meaning in life, self-esteem, and interpersonal trust; meaning in life, self-esteem, and interpersonal trust were all significantly and positively correlated with mental health. Self-esteem and interpersonal trust played a chain mediating role between meaning in life and mental health. Schools and families should conduct appropriate activities to help them enhance meaning in life so as to improve the level of mental health.

The impact of high temperature environments on the physical and mechanical properties of rocks is a significant factor to consider. The investigation into the impact of elevated temperatures on the physical and mechanical characteristics of rocks holds great importance in the advancement and exploitation of deep-seated mineral reserves, as well as in ensuring the safety and stability of subterranean engineering projects. This study utilizes the state-of-the-art GCTS Mechanical Loading Test System to conduct uniaxial and triaxial compression tests on sandstone after thermal treatment from 25°C to 650°C. In addition, XRD, SEM and nuclear magnetic resonance experiments were carried out on the sandstone after thermal treatment. The aim of the experiments is to provide a quantitative characterization of mechanical properties and behaviors of the rock samples. The results show that the mass, density, and wave velocity of sandstone decrease with increasing temperature, while volume and porosity increase. The mass, volume, and rate of density change of sandstone exhibit a significant increase when subjected to temperatures above 500°C. The uniaxial compressive strength and elastic modulus exhibit an initial increase followed by a subsequent decrease as the temperature rises, with 300°C serving as the critical turning point. The axial peak strain and Poisson’s ratio increase with increasing temperature. The cohesion decreases with increasing temperature, while the internal friction angle increases. Additionally, it is observed that the rate of change for both properties exhibits an increase beyond the temperature threshold of 400°C.

Abstract High‐voltage nickel (Ni)‐rich layered oxide‐based lithium metal batteries (LMBs) exhibit a great potential in advanced batteries due to the ultra‐high energy density. However, it is still necessary to deal with the challenges in poor cyclic and thermal stability before realizing practical application where cycling life is considered. Among many improved strategies, mechanical and chemical stability for the electrode electrolyte interface plays a key role in addressing these challenges. Therefore, extensive effort has been made to address the challenges of electrode‐electrolyte interface. In this progress, the failure mechanism of Ni‐rich cathode, lithium metal anode and electrolytes are reviewed, and the latest breakthrough in stabilizing electrode‐electrolyte interface is also summarized. Finally, the challenges and future research directions of Ni‐rich LMBs are put forward.

The unique seasonal surface dust storms on Mars have a significant impact on the Martian atmosphere. However, due to the lack of observations, semi-empirical models are difficult to simulate the density changes in the thermosphere with the existence of dust storms in detail. Data from multiple Mars probes now offer new opportunities to study the detailed response of Martian dust storms to the upper atmosphere. In this paper, we use MAVEN accelerometer and mass spectrometer to study the variations of the Martian thermosphere density in autumn between MY 32 and MY34 (The corresponding Earth dates: February 11, 2015 to February 28, 2019), and use the seasonal model with dust storm index to fit the annual data of the above three Martian years. The results show that the thermosphere density has a clear response to the surface dust storm activity. Furthermore, the spatial distribution of measured data in autumn (northern hemisphere) is compared with the atmospheric density distribution simulated by the general circulation model (GCM) under specific initial conditions. The model simulation results agree well with the thermospheric density distribution characteristics of each Martian year under the initial strong dust storm conditions. It proves the important role of global dust storm in changing the structure of the Martian thermospheric atmosphere.

Abstract Hepatic cysts are fluid‐filled lesions in the liver that are estimated to occur in 5% of the population. They may cause hepatomegaly and abdominal pain. Progression to secondary fibrosis, cirrhosis, or cholangiocarcinoma can lead to morbidity and mortality. Previous studies of patients and rodent models have associated hepatic cyst formation with increased proliferation and fluid secretion in cholangiocytes, which are partially due to impaired primary cilia. Congenital hepatic cysts are thought to originate from faulty bile duct development, but the underlying mechanisms are not fully understood. In a forward genetic screen, we identified a zebrafish mutant that developed hepatic cysts during larval stages. The cyst formation was not due to changes in biliary cell proliferation, bile secretion, or impairment of primary cilia. Instead, time‐lapse live imaging data showed that the mutant biliary cells failed to form interconnecting bile ducts because of defects in motility and protrusive activity. Accordingly, immunostaining revealed a disorganized actin and microtubule cytoskeleton in the mutant biliary cells. By whole‐genome sequencing, we determined that the cystic phenotype in the mutant was caused by a missense mutation in the furinb gene, which encodes a proprotein convertase. The mutation altered Furinb localization and caused endoplasmic reticulum (ER) stress. The cystic phenotype could be suppressed by treatment with the ER stress inhibitor 4‐phenylbutyric acid and exacerbated by treatment with the ER stress inducer tunicamycin. The mutant liver also exhibited increased mammalian target of rapamycin (mTOR) signaling. Treatment with mTOR inhibitors halted cyst formation at least partially through reducing ER stress. Conclusion: Our study has established a vertebrate model for studying hepatic cystogenesis and illustrated the contribution of ER stress in the disease pathogenesis.

Obtaining accurate basic parameters for long hole blasting is challenging, and the resulting vibration damage significantly impacts key surface facilities. Predicting ground vibration velocity accurately and mitigating the harmful effects of blasting are crucial aspects of controlled blasting technology. This study focuses on the prediction of ground vibration velocity induced by underground long hole blasting tests. Utilizing the fitting equation based on the US Bureau of Mines (USBM) formula as a baseline for predicting peak particle velocity, two machine learning models suitable for small sample data, Support Vector Regression (SVR) machine and Random Forest (RF), were employed. The models were optimized using the particle swarm optimization algorithm (PSO) to predict peak particle velocity with multiple parameters specific to long hole blasting. Mean absolute error (MAE), mean Squared error (MSE), and coefficient of determination (R2) were used to assess the model predictions. Compared with the fitting equation based on the USBM model, both the Support Vector Regression (SVR) and Random Forest (RF) models accurately and effectively predict peak particle velocity, enhancing prediction accuracy and efficiency. The SVR model exhibited slightly superior predictive performance compared to the RF model.

Lithium metal batteries suffer from short lifespans and low Coulombic efficiency (CE) due to the high reactivity of Li and the poor stability of the solid electrolyte interphase (SEI). Herein, we propose the concept of a pseudo-concentrated electrolyte (PCE) induced by an electron-deficient additive (4-pyridylboronic acid; 4-PBA) to form a robust, LiF-rich SEI, thus addressing the above issues. Molecular dynamics simulations confirm that 4-PBA can increase the coordination number of PF6- anions in the Li+ solvation sheath to achieve pseudo-concentrated LiPF6 in the electrolyte. Moreover, the 4-PBA can scavenge harmful PF5 decomposed from LiPF6 to stabilize the LiF-rich SEI. The resulting robust LiF-rich SEI promotes Li growth along the SEI/Li interface and represses the growth of Li dendrites. Thus, excellent performance is achieved, with a high CE of 97.1% for a Li||Cu cell at 1.0 ​mA ​cm−2, and over 950 cycles at 0.5 ​mA ​cm−2 for Li||Li symmetric cells with 1.0 ​wt% 4-PBA electrolyte. Meanwhile, the resulting stable boron-containing cathode electrolyte interphase enables Li||LiNi0·6Co0·2Mn0·2O2 (NCM622) cells to achieve excellent stability, with a capacity retention of 86.9% after 200 cycles.

Utilizing the digital economy’s contribution to green total factor productivity is a key strategy for accelerating China’s green growth, although more research is still needed to understand the mechanism of this influence. This study uses panel data from 282 Chinese prefecture-level cities from 2011 to 2019 to empirically assess the impact of the digital economy and city size on GTFP. First, GTFP overall exhibits an upward trend with excellent spatial correlation and minimal regional variation. Second, the findings demonstrate that, while surrounding locations’ GTFP is not affected by the digital economy, local productivity can be improved. Third, the heterogeneity study demonstrates that the digital economy contributes more to local GTFP in the eastern region compared to the central and western regions, with the central region making the largest contribution to GTFP in the surrounding regions; the first, second, and third tier cities have more contributions from the digital economy to local and neighboring GTFP than the fourth and fifth tier cities. Fourth, city size positively modifies the relationship between the green total factor productivity and the digital economy. The western region is where the positive moderating effect of city size expansion is greatest. Moreover, compared to first-, second-, and third-tier cities, the fourth- and fifth-tier cities have a stronger beneficial moderating effect of city size increase. In light of this, we should focus on the growth of the digital economy, optimize city scale, and fully exploit the scale effect produced by the concentration of the digital industries and the spillover effect produced by the spread of the digital technology.

Summary: Direct cardiac reprogramming refers to the conversion of fibroblasts into cardiomyocyte-like cells (iCMs) without going through an intermediate progenitor stage. Here, we present a protocol for direct cardiac reprogramming in mice using Ascl1 and Mef2c. We describe steps for isolating primary neonatal mouse cardiac fibroblast, preparing retrovirus encoding reprogramming factors, and efficient cardiac reprogramming with Ascl1 and Mef2c. The resulting iCMs display cardiomyocyte-like sarcomere structure, gene expression, and calcium flux.For complete details on the use and execution of this protocol, please refer to Wang et al. (2022).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

N6-Methyladenosine (m6A) methylation is one of the most extremely examined RNA modifications. M6A modification evidently impacts cancer development by effecting RNA metabolism. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) are involved in multiple essential biological processes by regulating gene expression at the transcriptional and post-transcriptional levels. Accumulated evidences indicated that m6A is involved in regulating the cleavage, stability, structure, transcription, and transport of lncRNAs or miRNAs. Additionally, ncRNAs also play significant roles in modulating m6A levels of malignant cells by participating in the regulation of m6A methyltransferases, the m6A demethylases and the m6A binding proteins. In this review, we systematically summarize the new insight on the interactions between m6A and lncRNAs or miRNAs, as well as their impacts on gastrointestinal cancer progression. Although there are still extensive studies on genome-wide screening of crucial lncRNAs or miRNAs involved in regulating m6A levels of mRNAs and disclosing differences on mechanisms of regulating m6A modification of lncRNAs, miRNAs or mRNAs in cancer cells, we believe that targeting m6A-related lncRNAs and miRNAs may provide novel options for gastrointestinal cancer treatments.

Objective To explore the relationship between the serum concentration of IL-17 and the pathogenesis of psoriasis. Methods ampere database was established through literature search, and meta-analysis was used to evaluate the effect indicator of the included literatures. Results 5 articles were included in the study, and the quality evaluation score was 6–7 points by the Newcastle-Ottawa Scale (NOS) criteria. There was heterogeneity in the standardized mean difference (SMD) between the two groups (I 2 = 98.63%). The random effect model analysis showed that the combined SMD = 2.11, 95%CI (0.79, 3.43), the effect size between studies was statistically significant (z = 3.13, p = 0.00). Conclusion There was a statistical difference in serum IL-17 concentration between the case group and the control group. The serum concentration of IL-17 in the case group was higher than that in the control group.

Abstract SARS-CoV-2 and SARS-CoV are genetically related coronavirus and share the same cellular receptor ACE2. By replacing the VSV glycoprotein with the spikes (S) of SARS-CoV-2 and SARS-CoV, we generated two replication-competent recombinant viruses, rVSV-SARS-CoV-2 and rVSV-SARS-CoV. Using wild-type and human ACE2 (hACE2) knock-in mouse models, we found a single dose of rVSV-SARS-CoV could elicit strong humoral immune response via both intranasal (i.n.) and intramuscular (i.m.) routes. Despite the high genetic similarity between SARS-CoV-2 and SARS-CoV, no obvious cross-neutralizing activity was observed in the immunized mice sera. In macaques, neutralizing antibody (NAb) titers induced by one i.n. dose of rVSV-SARS-CoV-2 were eight-fold higher than those by a single i.m. dose. Thus, our data indicates that rVSV-SARS-CoV-2 might be suitable for i.n. administration instead of the traditional i.m. immunization in human. Because rVSV-SARS-CoV elicited significantly stronger NAb responses than rVSV-SARS-CoV-2 in a route-independent manner, we generated a chimeric antigen by replacing the receptor binding domain (RBD) of SARS-CoV S with that from the SARS-CoV-2. rVSV expressing the chimera (rVSV-SARS-CoV/2-RBD) induced significantly increased NAbs against SARS-CoV-2 in mice and macaques than rVSV-SARS-CoV-2, with a safe Th1-biased response. Serum immunized with rVSV-SARS-CoV/2-RBD showed no cross-reactivity with SARS-CoV. hACE2 mice receiving a single i.m. dose of either rVSV-SARS-CoV-2 or rVSV-SARS-CoV/2-RBD were fully protected against SARS-CoV-2 challenge without obvious lesions in the lungs. Our results suggest that transplantation of SARS-CoV-2 RBD into the S protein of SARS-CoV might be a promising antigen design for COVID-19 vaccines.

The stress-strain relationship in shales is generally time-dependent. This concerns their long-term deformation in unconventional reservoirs, and its influence on the in situ stress state therein. This paper presents an experimental investigation on the time-dependent deformation of the Longmaxi shale gas shale. A series of creep experiments subject the shale samples to long-term, multi-step triaxial compression. It is found that the shale samples exhibit varying degrees of time-dependent deformation, which can be adequately described by a power-law function of time. The experimental results establish the relationship between the elastic Young’s modulus and viscoplastic constitutive parameters, which are different from previous those derived from North American shales. Based on this viscoplastic constitutive model, the stress relaxation and the differential stress accumulation over geologic time scales can be estimated. It is found that linear elasticity substantially overestimates the differential stress accumulation predicted in the context of viscoplastic relaxation. The characterized viscoplasticity and stress relaxation are of vital importance for various geomechanical problems in shale reservoirs.

Abstract A coupled soil temperature (ST) and moisture (SM) balance reflects a synthetic climate regime, having huge ecological impacts. This paper used ST and SM data from the European Center for Medium‐Range Weather Forecasts climate reanalysis‐Land and the Coupled Model Intercomparison Project Phase 6 and leaf area index (LAI) data from the Global Land Surface Satellite Product Suite. The focus was on understanding joint ST‐SM changes and the resulting ecological response across China. The results show that during 2000–2020, 24.5% of the land area in China experienced a warming‐drying trend resulting in a 9.7% LAI decrease, while 6.4% of the area experienced a warming‐wetting trend leading to an 8.6% LAI increase. During 2015–2100, 30.6% of the land area in China will be warmer and drier, while 55.2% of the area will be warmer but wetter across three shared socioeconomic pathways (SSP126, 245, and 585). Superimposed on the long‐term trends, there are also significant spatiotemporal variabilities in ST and SM on annual to decadal timescales. The LAI also showed substantial short‐term fluctuations in both typical regions and ecosystems despite consistent long‐term increases. Our findings suggest that ecosystems could be impaired on annual to decadal scales by adverse soil conditions in the twenty‐first century, but in terms of long‐term trends, ecosystems may be resilient partly because of the compensating effects of global warming and regional hydrological changes. Impact studies should thus focus more on annual to decadal soil‐ecosystem anomalous events.

Abstract Background Hepatocellular carcinoma (HCC) ranks fourth among the malignancies leading to cancer‐related deaths all around the world. It is increasingly evident that long non‐coding RNAs (lncRNAs) are a key mode of hepatocarcinogenesis. As the most prevalent mRNA modification form, N6‐methyladenosine (m6A) regulates gene expression by impacting multiple aspects of mRNA metabolism. However, there are still no reports on genome‐wide screening and functional annotation of m6A‐methylated lncRNAs in HCC. Methods The m6A modification and biologic functions of ARHGAP5‐AS1 in HCC were investigated through a series of biochemical assays. Clinical implications of ARHGAP5‐AS1 were examined in tissues from HCC patients. Results After systematically analysing the m6A‐seq data of HCC cells, we identified 22 candidate lncRNAs with evidently dysregulated m6A levels. Among these lncRNAs, we found that ARHGAP5‐AS1 is the lncRNA with the highest levels of m6A modification and significantly increased expression in HCC specimens. METTL14 acts as the m6A writer of ARHGAP5‐AS1 and IGF2BP2 stabilises the lncRNA as its m6A reader. ARHGAP5‐AS1 remarkably promotes malignant behaviours of HCC cells ex vivo and in vivo. We identified oncoprotein CSDE1 working as the interacting protein of the lncRNA and TRIM28 as the E3 ligase of CSDE1 in HCC. Interestingly, ARHGAP5‐AS1 could attenuate interactions between CSDE1 and TRIM28, which prevents the degradation of CSDE1 via the ubiquitin‐proteasome pathway. Elevated levels of CSDE1 coordinate oncogenic RNA regulons, promote translation of VIM and RAC1 and activate the ERK pathway, which contributes to HCC prognosis. Conclusions Our study reveals a new paradigm in m6A‐modified lncRNAs controlling CSDE1‐mediated oncogenic RNA regulons and highlights lncRNAs as potential targets for future therapeutics against HCC.

As the coefficients of the Ångström–Prescott model is site-dependent, the sparsity of radiation stations in regions like the Tibetan Plateau (TP) presents challenges for model calibration. Due to the unique climate and the clean air conditions over the TP, it might be feasible to calibrate the Ångström–Prescott model with short-term observations from scientific expeditions. To test this hypothesis, we used various datasets with different lengths at four stations, together with 435 daily radiations measured during a scientific expedition at Banga in the central TP from 2014 to 2015, to calibrate the Ångström–Prescott model. We found that calibration with a 1-year data length resulted in model performances comparable to those with a 20-year data length. Analysis of the expedition observations showed that the monthly average daily radiation ranged from 15.2 MJ/m2d in December 2014 to 26.5 MJ/m2d in July 2015, with an average value of 20.6 MJ/m2d. When this set of expedition data was used for calibration, the Ångström–Prescott model performed well with an NSE (Nash–Sutcliffe efficiency) of 0.820. If no data were available for calibration, the coefficients of the Ångström–Prescott model could also be directly calculated by parameterization methods established with calibrations at the other radiation stations. In this situation, the LiuJD method performed the best with the highest NSE of 0.792, followed by the LiuXY method with an NSE of 0.764. The FAO method performed poorly with an NSE of 0.578, while the Gopinathan method performed the worst with the lowest NSE of 0.218. Thus, the best strategy to calibrate the Ångström–Prescott model in the Tibetan Plateau is to use data from local observations, even if collected over short periods. When these are not available, the coefficients of the Ångström–Prescott model should be calculated using the parameterization method established with calibrations over the Tibetan Plateau.

Satellite internet, as a new infrastructure, is an important part of China's future information infrastructure, and its security importance is self-evident.Based on the typical architecture of satellite internet system, the security risks faced by satellite platform control, satellite digital transmission and satellite communication were analyzed, the satellite internet security protection architecture based on zero trust was put forward.The implementation process of zero trust security protection architecture in satellite control, digital transmission and communication typical application scenarios, and its advantages compared with the traditional security protection architecture were described.

TFE3-translocation renal cell carcinoma (TFE3-tRCC) is a rare subtype of kidney cancer with no standard treatment options for the advanced disease. Here, the authors perform genomic and transcriptomic profiling of 63 untreated primary TFE3-tRCC tumours and reveal potential therapeutic targets.

Abstract Temperature profiles retrieved using the first set of data of the Emirates Mars InfraRed Spectrometer obtained during the science phase of the Emirates Mars Mission are used for the analysis of migrating thermal tides in the Martian atmosphere. The selected data cover a solar longitude (LS) range of 60°–90° of Martian Year 36. The novel orbit design of the Hope Probe leads to a good geographic and local time coverage that significantly improves the analysis. Wave mode decomposition suggests dominant diurnal tide and important semi‐diurnal tide with maximal amplitudes of 6 and 2 K, respectively, as well as the existence of ∼0.5 K ter‐diurnal tide. The results agree well with predictions by the Mars Planetary Climate Model, but the observed diurnal tide has an earlier phase (3 hr), and the semi‐diurnal tide has an unexpectedly large wavelength (∼200 km).

Abstract Cellular reprogramming has rapidly become a promising methodology to generate new cardiomyocytes from non-cardiomyocyte cell types. Using the transient expression of OSKM factors, Chen et al. demonstrate a unique reprogramming strategy involving the modulation of the resident adult cardiomyocyte identity to an immature proliferative state (Science 373:1537–40, 2021). This OSKM-mediated reversion results in the adoption by adult murine cardiomyocytes of a transcriptional profile similar to cardiomyocytes found in developing hearts, as well as increased proliferative capacity of these reprogrammed cardiomyocytes compared to mature cardiomyocytes. Furthermore, this novel approach enhances the regeneration of adult murine hearts post-myocardial injury. Although concerns and questions remain, the encouraging results of this study advance the field of cardiac regeneration by providing a new technique to generate cardiomyocytes as well as insights into cardiomyocyte dedifferentiation and its relation to proliferation.

Abstract The performance of lithium metal batteries (LMBs) is determined by many factors from the bulk electrolyte to the electrode‐electrolyte interphases, which are crucially affected by electrolyte additives. Herein, the authors develop the heptafluorobutyrylimidazole (HFBMZ) as a hexa‐functional additive to inhibit the dendrite growth on the surface of lithium (Li) anode, and then improve the cycling performance and rate capabilities of Li||LiNi0.6Co0.2Mn0.2O2 (NCM622). The HFBMZ can remove the trace H2O and HF from the electrolyte, reducing the by‐products on the surface of solid electrolyte interphase (SEI) and inhibiting the dissolution of metal ions from NCM622. Also, the HFBMZ can enhance the wettability of the separator to promote uniform Li deposition. HFBMZ can make Li+ easy to be desolvated, resulting in the increase of Li+ flux on Li anode surface. Moreover, the HFBMZ can optimize the composition and structure of SEI. Therefore, the Li||Li symmetrical cells with 1 wt% HFBMZ‐contained electrolyte can achieve stable cycling for more than 1200 h at 0.5 mA cm–2. In addition, the capacity retention rate of the Li||NCM622 can reach 92% after 150 cycles at 100 mA g–1.

Celastrol plays a significant role in cerebral ischemia-reperfusion injury. Although previous studies have confirmed that celastrol post-treatment has a protective effect on ischemic stroke, the therapeutic effect of celastrol on ischemic stroke and the underlying molecular mechanism remain unclear. In the present study, focal transient cerebral ischemia was induced by transient middle cerebral artery occlusion (tMCAO) in mice and celastrol was administered immediately after reperfusion. We performed lncRNA and mRNA analysis in the ischemic hemisphere of adult mice with celastrol post-treatment through RNA-Sequencing (RNA-Seq). A total of 50 differentially expressed lncRNAs (DE lncRNAs) and 696 differentially expressed mRNAs (DE mRNAs) were identified between the sham and tMCAO group, and a total of 544 DE lncRNAs and 324 DE mRNAs were identified between the tMCAO and tMCAO + celastrol group. Bioinformatic analysis was done on the identified deregulated genes through gene ontology (GO) analysis, KEGG pathway analysis and network analysis. Pathway analysis indicated that inflammation-related signaling pathways played vital roles in the treatment of ischemic stroke by celastrol. Four DE lncRNAs and 5 DE mRNAs were selected for further validation by qRT-PCR in brain tissue, primary neurons, primary astrocytes, and BV2 cells. The results of qRT-PCR suggested that most of selected differentially expressed genes showed the same fold change patterns as those in RNA-Seq results. Our study suggests celastrol treatment can effectively reduce cerebral ischemia-reperfusion injury. The bioinformatics analysis of lnRNAs and mRNAs profiles in the ischemic hemisphere of adult mice provides a new perspective in the neuroprotective effects of celastrol, particularly with regards to ischemic stroke.

Whole-life-cycle integrity management of underground gas storages (UGSs) has been an important link to ensure its long-term safe and efficient operation. At present, the integrity of UGSs in oil/gas fields and its evaluation techniques focus on surface facilities and injection/withdrawal wells, but its geological integrity lacks clear definition and evaluation object and systematic evaluation techniques. In this paper, relevant research achievements were firstly summarized. Then, the concept of geological integrity with the gas-storage geological body as the evaluation object was put forward, and the evaluation system for the geological integrity of such UGSs was established. Finally, UGS geological integrity evaluation was carried out with the Hutubi Underground Gas Storage in Xinjiang as an example. And the following research results were obtained. First, UGS geological integrity is defined as the integrity degree of each component of a gas-storage geological body to meet operation requirements and fulfill seasonal and emergency peak shaving safely and economically during the operation of a UGS. Its connotation is that reservoir of geological body, caprock, fault and trap can supply the customers with gas continuously and stably and ensure the safe operation of the UGS in its service life. And its core lies in keeping the reliability, safety and economy of natural gas storage in the service life of a UGS. Second, the geological integrity evaluation system is composed of four evaluation techniques, including trap effectiveness, caprock integrity, fault stability and reservoir stability. Third, the evaluation results show that the Hutubi Underground Gas Storage has the potential of peak-shaving capacity enhancement by increasing the maximum operation pressure. In conclusion, the establishment of the geological integrity evaluation system for such UGSs improves the UGS integrity evaluation technique system and plays an instructive and practical role in ensuring the long-term safe and efficient operation of UGSs, increasing the maximum operation pressure and improving the peak shaving capacity.

Abstract Gastric cancer is the fourth most common malignancy and the third leading cause of cancer-related deaths worldwide. Advanced gastric cancer patients can notably benefit from chemotherapy including adriamycin, platinum drugs, 5-fluorouracil, vincristine, and paclitaxel as well as targeted therapy drugs. Nevertheless, primary drug resistance or acquisition drug resistance eventually lead to treatment failure and poor outcomes of the gastric cancer patients. The detailed mechanisms involved in gastric cancer drug resistance have been revealed. Interestingly, different noncoding RNAs (ncRNAs), such as microRNAs (miRNAs), long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs), are critically involved in gastric cancer development. Multiple lines of evidences demonstrated that ncRNAs play a vital role in gastric cancer resistance to chemotherapy reagents and targeted therapy drugs. In this review, we systematically summarized the emerging role and detailed molecular mechanisms of ncRNAs impact drug resistance of gastric cancer. Additionally, we propose the potential clinical implications of ncRNAs as novel therapeutic targets and prognostic biomarkers for gastric cancer.

Tissue factor (TF) is crucial for embryogenesis, as mice lacking TF are embryonically lethal (E10.5). This lethality may be attributed to defects in vascular development and circulatory failure, suggesting additional roles for TF in embryonic development beyond coagulation. In this study, we characterized the role of one of the TF paralogs (f3a) using a zebrafish model. The expression of f3a during embryonic developmental stages was determined by RT-PCR. Spatiotemporal expression pattern of f3a revealed (high expression from 28 to 36 hpf) the role of in the development of the yolk sac, circulation, and fins. Morpholinos (MO), an antisense-based oligonucleotide strategy, was used to knockdown f3a and examined for defects in morphological appearance, bleeding, and vascular patterning. f3a MO-injected embryos showed morphological abnormalities, including shorter body lengths and crooked tails. O-dianisidine staining showed f3a MO-injected embryos exhibited bleeding in the trunk (5.44%) and head (9.52%) regions. Imaging of endothelial-specific transgenic lines (flk1:egfp-NLS/kdrl:mCherry-CAAX) showed a 3-fold decreased caudal vein plexus (CVP) in f3a morphants versus controls at 48 hpf, suggesting a potential role for f3a in angiogenesis. These findings confirm that f3a is essential for angiogenesis, in addition to its involvement in hemostasis.

The in situ conversion process (ICP) is a retorting method pyrolyzing the kerogen in shale into oil and gas products, which shows great potential to promote the recovery of oil shale resources. In this work, a thermo-hydro-chemical-coupled model for the in situ conversion process is established, considering the temperature dependence of key properties and the transverse isotropy caused by the layered characteristics of oil shale. Based on the proposed model, a series of simulations is conducted to evaluate the production performance of the in situ conversion process of oil shale reservoirs. The results indicate that energy efficiency reaches a maximum of 2.7 around the fifth year of the heating process, indicating the feasibility of in situ conversion technology. Furthermore, the sensitivity analysis shows that the heating temperature should be higher than 300 °C to avoid the energy output being less than the energy input, and the oil/gas ratio decreases with increasing heating temperature. Moreover, thermal conductivity is positively with production while heat capacity is negatively correlated, and the energy efficiency decreases with increasing thermal conductivity and matrix heat capacity. Finally, the heating period should be no longer than 4 years to maximize the heating efficiency.

Abstract Background Bone marrow mesenchymal stem cells (MSCs) are among the most common cell types to be used and studied for cardiac regeneration. Low survival rate and difficult retention of delivered MSCs in infarcted heart remain as major challenges in the field. Co-delivery of stem cell-derived exosomes (Exo) is expected to improve the recruitment and survival of transplanted MSCs. Methods Exo was isolated from MSCs and delivered to an acute myocardial infarction (AMI) rat heart through intramyocardial injection with or without intravenous infusion of atrovastatin-pretreated MSCs on day 1, day 3, or day 7 after infarction. Echocardiography was performed to evaluate cardiac function. Histological analysis and ELISA test were performed to assess angiogenesis, SDF-1, and inflammatory factor expression in the infarct border zone. The anti-apoptosis effect of Exo on MSCs was evaluated using flow cytometry and Hoechst 33342 staining assay. Results We found that intramyocardial delivery of Exo followed by MSC transplantation (in brief, Exo+MSC treatment) into MI hearts further improved cardiac function, reduced infarct size, and increased neovascularization when compared to controls treated with Exo or MSCs alone. Of note, comparing the three co-transplanting groups, intramyocardially injecting Exo 30 min after AMI combined with MSCs transplantation at day 3 after AMI achieved the highest improvement in heart function. The observed enhanced heart function is likely due to an improved microenvironment via Exo injection, which is exemplified as reduced inflammatory responses and better MSC recruitment and retention. Furthermore, we demonstrated that pre-transplantation injection of Exo enhanced survival of MSCs and reduced their apoptosis both in vitro and in vivo. Conclusions Combinatorial delivery of exosomes and stem cells in a sequential manner effectively reduces scar size and restores heart function after AMI. This approach may represent as an alternative promising strategy for stem cell-based heart repair and therapy.

The survival of patients diagnosed with metastatic renal cell carcinoma (RCC) is still limited and the current targeted therapies are only partially effective. Herein, we investigated the clinical value and functions of adiponectin receptors (AdipoR1 and AdipoR2) in metastatic renal cell carcinoma (RCC) patients treated with tyrosine kinase inhibitors (TKIs). A total of 127 mRCC patients treated with first-line TKIs between 2008 and 2017 at a single institution were collected. AdipoR1 and AdipoR2 expression was assessed by immunohistochemistry. AdipoR1 was positively expressed in 87.4% (111/127) of tumors, especially, highly expressed in pulmonary and bone lesions. Patients with low-AdipoR1 expression in primary tumor tissues were more likely to suffer from progressive disease during TKIs treatment (40.0% vs. 11.1%, P = 0 .02), and with decreased progression-free survival (PFS: 19.5 vs. 37.8 mo, P = .001) and overall survival (OS: 62.3 vs 101.1 mo, P = .004) compared to those with high-AdipoR1 expression. Moreover, low-AdipoR1 expression in metastatic tissues was also associated with poor PFS (P = .006) and OS (P = .037). In contrast, AdipoR2 expression was neither associated with sunitinib response nor patient survival. In vitro, we found that adiponectin inhibited migration, invasion and sensitized RCC cells to sunitinib though interacting with AdipoR1, but not AdipoR2. Furthermore, we demonstrated that adiponentin-AdipoR1 axis inhibits tumor cells migration and invasion by blocking the GSK3β/β-Catenin pathway and enhances sunitinib sensitivity via abrogating PI3K/AKT/NF-κB signaling. Our results suggest that adiponentin-AdipoR1 axis may serve as a predictor of TKIs response and could be a potential therapeutic target in the future treatment for metastatic RCC.

Abstract Background In clinical practice, the detection of biomarkers is mostly based on primary tumors for its convenience in acquisition. However, immune checkpoints may express differently between primary and metastatic tumor. Therefore, we aimed to compare the differential expressions of PD-1, PD-L1 and PD-L2 between the primary and metastatic sites of renal cell carcinoma (RCC). Methods Patients diagnosed with RCC by resection or fine needle aspiration of metastasis were included. Immunohistochemistry (IHC) was applied to detect PD-1, PD-L1 and PD-L2 expressions. SPSS 22.0 was applied to conduct Chi-square, consistency tests and Cox’s proportional hazards regression models. GraphPad Prism 6 was used to plot survival curves and R software was used to calculate Predictive accuracy (PA). Results In the whole cohort (N = 163), IHC results suggested a higher detection rate of PD-L1 in the metastasis than that of the primary site (χ2 = 4.66, p = 0.03), with a low consistent rate of 32.5%. Among different metastatic tumors, PD-1 was highly expressed in the lung/lymph node (65.3%) and poorly expressed in the brain (10.5%) and visceral metastases (12.5%). PD-L1 was highly expressed in lung/lymph node (37.5%) and the bone metastases (12.2%) on the contrary. In terms of survival analysis, patients with PD-1 expression either in the primary or metastasis had a shorter overall survival (OS) (HR: 1.59, 95% CI 1.08–2.36, p = 0.02). Also, PD-L1 expression in the primary was associated with a shorter OS (HR 2.55, 95% CI 1.06–6.15, p = 0.04). In the multivariate analysis, the predictive accuracy of the whole model for PFS was increased from 0.683 to 0.699 after adding PD-1. Conclusion PD-1, PD-L1 and PD-L2 were differentially expressed between primary and metastatic tumors. Histopathological examination of these immune check points in metastatic lesions of mRCC should be noticed, and its accurate diagnosis may be one of the effective ways to realize the individualized treatment.

Due to its sedimentary characteristics and natural fractures, oil shale shows anisotropy in heat transfer characteristics. Moreover, the anisotropic thermal conductivity will change with the temperature. This change in the anisotropic thermal conductivity coefficient affects the temperature field distribution and heating efficiency during the in situ electric heating pyrolysis of oil shale. Therefore, it is very important to study the evolution of the anisotropy thermal conductivity coefficient of oil shale with temperature. In this study, the variation of weight loss and the specific heat of an oil shale with temperature is investigated using a differential scanning calorimeter. The variation of the anisotropic pore and fracture structure of the oil shale with temperature is studied through CT scanning technology. The variation of the anisotropic thermal conductivity with temperature is studied through the hot disk method. Finally, the relationship between the change in the anisotropic heat conductivity of the oil shale and the evolution of the anisotropic pore and fracture structure is discussed. The results show that the mass loss of oil shale mainly occurs after 400 °C. The thermal conductivity of both perpendicular and parallel to bedding directions decreases linearly with the increase of temperature. The research results of this study can serve as an important reference in the study of the in situ pyrolysis of oil shale.

To estimate the compressive strength of cement-based materials with mining waste, the dataset based on a series of experimental studies was constructed. The support vector machine (SVM), decision tree (DT), and random forest (RF) models were developed and compared. The beetle antennae search (BAS) algorithm was employed to tune the hyperparameters of the developed machine learning models. The predictive performances of the three models were compared by the evaluation of the values of correlation coefficient (R) and root mean square error (RMSE). The results showed that the BAS algorithm can effectively tune these artificial intelligence models. The SVM model can obtain the minimum RMSE, while the BAS algorithm is inefficient in DT and RF models. The SVM, DT, and RF models can be used to predict the compressive strength of cement-based materials using solid mining waste as aggregate effectively and accurately, with high R values and lower RMSE values. The RF algorithm can obtain the highest value of R and the lowest value of RMSE, demonstrating the highest accuracy. The solid mining waste to cement ratio is the most important variable to affect the compressive strength. Curing time was also an important parameter in the compressive strength of cemented materials, followed by the water-solid ratio of mining waste and fine sand ratio.

The optimal resource allocation in the large-scale intelligent device-to-device (D2D) communication system is of great importance for improving system spectrum efficiency and ensuring communication quality. In this study, the D2D resource allocation is modelled as an ultrahigh-dimensional optimization (UHDO) problem with thousands of binary dimensionalities. Then, for efficiently optimizing this UHDO problem, the coupling relationships among those dimensionalities are comprehensively analysed, and several efficient variable-grouping strategies are developed, i.e., cellular user grouping (CU-grouping), D2D pair grouping (DP-grouping), and random grouping (R-grouping). In addition, a novel evolutionary algorithm called the cooperatively coevolving particle swarm optimization with variable-grouping (VGCC-PSO) is developed, in which a novel mutation operation is introduced for ensuring fast satisfaction of constraints. Finally, the proposed UHDO-based allocation model and VGCC-PSO algorithm as well as the grouping and mutation strategies are verified by a comprehensive set of case studies. Simulation results show that the developed VGCC-PSO algorithm performs the best in optimizing the UHDO model with up to 6000 dimensionalities. According to our study, the proposed methodology can effectively overcome the “curse of dimensionality” and optimally allocate the resources with high accuracy and robustness.

Light-sheet fluorescence microscopy (LSFM) provides access to multi-dimensional and multi-scale in vivo imaging of animal models with highly coherent volumetric reconstruction of the tissue morphology, via a focused laser light sheet. The orthogonal illumination and detection LSFM pathways account for minimal photobleaching and deep tissue optical sectioning through different perspective views. Although rotation of the sample and deep tissue scanning constitutes major advantages of LSFM, images may suffer from intrinsic problems within the modality, such as light mismatch of refractive indices between the sample and mounting media and varying quantum efficiency across different depths. To overcome these challenges, we hereby introduce an illumination correction technique integrated with depth detail amelioration to achieve symmetric contrast in large field-of-view images acquired using a low power objective lens. Due to an increase in angular dispersion of emitted light flux with the depth, we combined the dehazing algorithm with morphological operations to enhance poorly separated overlapping structures with subdued intensity. The proposed method was tested on different LSFM modalities to illustrate its applicability on correcting anisotropic illumination affecting the volumetric reconstruction of the fluorescently tagged region of interest.

Summary: Direct cardiac reprogramming, the conversion of fibroblasts into cardiomyocyte-like cells (iCMs), is an attractive approach to heal the injured heart. Here we present a new approach to human cardiac reprogramming that utilizes a polycistronic three-factor reprogramming cocktail and one microRNA. Our protocol produces cardiac Troponin T positive human iCMs (hiCMs) at an efficiency of 40%–60%, approximately double that of previous protocols, within just 2 weeks. The resulting hiCMs display cardiomyocyte-like sarcomere structure, gene expression, and calcium oscillation.For complete details on the use and execution of this protocol, please refer to Zhou et al. (2019).

Stereotactic ablative radiotherapy (SABR/SBRT) is a revolutionary technique for tumor therapy. Its advantages are especially beneficial for the treatment spinal tumors. It has a wide range of indications in radiotherapy alone and in preoperative and postoperative treatments for spinal tumor. The mechanism of stereotactic radiotherapy for spinal tumors is special, and completely different from traditional radiotherapy. Compared with traditional radiotherapy, SBRT creates more DNA double-strand breaks, leads to less DNA damage repair, and also has anti-vascular effects, in situ vaccine effects and abscopal effect. In the present study, the literature regarding SABR for the treatment of spinal tumors is summarized, and we reviewed characteristics of SABR and spinal tumors, as well as the clinical efficacy and toxicity of SABR in treating spinal tumors. In addition, we proposed several issues around the SABR treatment of spinal tumor, the standard of treatment dose, and the post-treatment follow-up. We also made predictions with respect to future management of spinal tumors, SABR development, multi-modality integration between SABR and other treatments, and other future development trends, thereby providing future research directions as a contribution to the field.

Vegetation greening in China has been extensively examined, but little is known about its seasonal characteristics and its association with soil moisture (SM) and temperature changes. Using high-resolution (0.1°, 8 d) datasets of leaf area index (LAI), together with SM, soil temperature (ST) datasets, and the dominance analysis method, this study is designed to detect seasonal vegetation changes across China during 1981–2018 and its links to climate change. The results show that 56.8% of land area across China experienced a greening trend while 6.6% browning trend through 1981–2018. LAI increasing area expanded to a maximum of 59.3% in spring and the decreasing area reached a maximum of 10.6% in autumn. Spring increases in LAI in main vegetation regions were significantly correlated with positive ST anomalies, while autumn decreases in LAI except sparsely vegetated regions were correlated with negative SM anomalies. Combined SM and temperature anomalies explain 10.9% of the observed LAI changes, which is 4 times larger than that directly explained by precipitation and surface air temperature (2.7%). The warming of soil under climate change was driving the LAI increases, while drying was largely responsible for LAI decreases. These findings provide further evidence of climate change impacts on regional ecosystems and highlight the importance of soil heat and water conditions in translating global warming signals.