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Abstract Despite the importance of cellular senescence in human health, how damaged cells undergo senescence remains elusive. We have previously shown that promyelocytic leukemia nuclear body (PML-NBs) translocation of the ciliary FBF1 is essential for senescence induction in stressed cells. Here we discover that an early cellular event occurring in stressed cells is the transient assembly of stress-induced nucleus-to-cilium microtubule arrays (sinc-MTs). The sinc-MTs are distinguished by unusual polyglutamylation and unique polarity, with minus-ends nucleating near the nuclear envelope and plus-ends near the ciliary base. KIFC3, a minus-end-directed kinesin, is recruited to plus-ends of sinc-MTs and interacts with the centrosomal protein CENEXIN1. In damaged cells, CENEXIN1 co-translocates with FBF1 to PML-NBs. Deficiency of KIFC3 abolishes PML-NB translocation of FBF1 and CENEXIN1, as well as senescence initiation in damaged cells. Our study reveals that KIFC3-mediated nuclear transport of FBF1 along polyglutamylated sinc-MTs is a prerequisite for senescence induction in mammalian cells.

StreamSAXS is a Python-based small- and wide-angle X-ray scattering (SAXS/WAXS) data analysis workflow platform with graphical user interface (GUI). It aims to provide an interactive and user-friendly tool for analysis of both batch data files and real-time data streams. Users can easily create customizable workflows through the GUI to meet their specific needs. One characteristic of StreamSAXS is its plug-in framework, which enables developers to extend the built-in workflow tasks. Another feature is the support for both already acquired and real-time data sources, allowing StreamSAXS to function as an offline analysis platform or be integrated into large-scale acquisition systems for end-to-end data management. This paper presents the core design of StreamSAXS and provides user cases demonstrating its utilization for SAXS/WAXS data analysis in offline and online scenarios.

Abstract Many lung immune cells are known to respond to inhaled particulate matter. However, current known responses cannot explain how particles induce thrombosis in the lung and how they translocate to distant organs. Here, we demonstrate that lung megakaryocytes (MKs) in the alveolar and interstitial regions display location-determined characteristics and act as crucial responders to inhaled particles. They move rapidly to engulf particles and become activated with upregulation in inflammatory responses and thrombopoiesis. Comprehensive in vivo, in vitro and ex vivo results unraveled that MKs were involved in particle-induced lung damages and shed particle-containing platelets into blood circulation. Moreover, MK-derived platelets exhibited faster clotting, stronger adhesion than normal resting platelets, and inherited the engulfed particles from parent MKs to assist in extrapulmonary particle transportation. Our findings collectively highlight that the specific responses of MKs towards inhaled particles and their roles in facilitating the translocation of particles from the lungs to extrapulmonary organs for clearance.

Abstract Predicting the corrosion rate for soil-buried steel is significant for assessing the service-life performance of structures in soil environments. However, due to the large amount of variables involved, existing corrosion prediction models have limited accuracy for complex soil environment. The present study employs three machine learning (ML) algorithms, i.e., random forest, support vector regression, and multilayer perception, to predict the corrosion current density of soil-buried steel. Steel specimens were embedded in soil samples collected from different regions of the Wisconsin state. Variables including exposure time, moisture content, pH, electrical resistivity, chloride, sulfate content, and mean total organic carbon were measured through laboratory tests and were used as input variables for the model. The current density of steel was measured through polarization technique, and was employed as the output of the model. Of the various ML algorithms, the random forest (RF) model demonstrates the highest predictability (with an RMSE value of 0.01095 A/m2 and an R 2 value of 0.987). In light of the feature selection method, the electrical resistivity is identified as the most significant feature. The combination of three features (resistivity, exposure time, and mean total organic carbon) is the optimal scenario for predicting the corrosion current density of soil-buried steel.

X-ray scattering/diffraction tensor tomography techniques are promising methods to acquire the 3D texture information of heterogeneous biological tissues at micrometre resolution. However, the methods suffer from a long overall acquisition time due to multi-dimensional scanning across real and reciprocal space. Here, a new approach is introduced to obtain 3D reciprocal information of each illuminated scanning volume using mathematic modeling, which is equivalent to a physical scanning procedure for collecting the full reciprocal information required for voxel reconstruction. The virtual reciprocal scanning scheme was validated by a simulated 6D wide-angle X-ray diffraction tomography experiment. The theoretical validation of the method represents an important technological advancement for 6D diffraction tensor tomography and a crucial step towards pervasive applications in the characterization of heterogeneous materials.

Accurate determination of the inverse kinematics for the drilling arm of a drilling and anchoring robot is crucial in achieving automatic support in coal mine roadways. Addressing issues such as poor accuracy, limited real-time performance, and susceptibility to local optima, this study presents a novel approach for solving the inverse kinematics problem of an unconventional mechanical arm by combining Monte Carlo random sampling method and Newton iteration method. Initially, a kinematics model is established based on the structure of the drilling arm, and individual coordinate systems are defined for each joint to enable forward kinematics solutions. The Monte Carlo method is employed to determine the motion space of the drill boom. By subdividing the motion space into smaller cubes with a defined step size, a mapping relationship is established between the spatial coordinates of these cubes and the corresponding joint variable values. Using the transformation matrix associated with a given target space point, an index function is employed to identify the relevant small cubes. The points within these cubes, which are closest to the target space point, are calculated, and their corresponding joint variable values are used as initial values. The Newton iteration method is then introduced, utilizing the iterative formula for multivariate functions to determine the variation of each joint variable. The inverse kinematics solution for the unconventional manipulator is obtained through iterative cycles. The simulation results show that, compared with Newton-Raphson iterative method based on random initial values and the particle swarm optimization algorithm, the corresponding average angle error of the calculation results of this method is reduced by 64.98% and 57.34%, and the average time consumption is reduced by 35.90% and 22.33%, respectively, thereby enhancing solution accuracy and real-time performance. The feasibility and effectiveness of the proposed Monte Carlo and Newton iteration method for solving the inverse kinematics problem in unconventional manipulators are verified. Overall, this research provides evidence supporting the practicality and efficiency of the proposed Monte Carlo random sampling method and Newton iteration method for accurate inverse kinematics solutions in unconventional manipulators.

Recent evidence has pinpointed a key role of the microbiome in human respiratory health and disease. However, significant knowledge gaps still exist regarding the connection between bacterial communities and adverse effects caused by particulate matters (PMs). Here, we characterized the bacterial microbiome along different airway sites in occupational pneumoconiosis (OP) patients. The sequencing data revealed that OP patients exhibited distinct dysbiosis in the composition and function of the respiratory microbiota. To different extents, there was an overall increase in the colonization of microbiota, such as Streptococcus, implying a possible intrusion pathway provided by exogenous PMs. Compared to those of healthy subjects, unhealthy living habits (i.e., smoking) had a greater impact on microbiome changes in OP patients. Importantly, the associations between the bacterial community and disease indicators indicated that specific bacterial species, including Prevotella, Actinobacillus, and Leptotrichia, might be surrogate markers of OP disease progression. Collectively, our results highlighted the potential participation of the bacterial microbiota in the pathogenesis of respiratory diseases and helped in the discovery of microbiome-based diagnostics for PM-induced disorders.

Abstract In next‐generation wireless communications, reconfigurable intelligent surface (RIS) has emerged as a cost‐effective technique for enhancing physical layer security (PLS) in millimeter‐wave (mmWave) communications, especially under challenging scenarios with adversarial entities and obstructions. However, the primary studies for RIS incorporation in mmWave communication systems utilized static deployments, lacking adaptability and efficiency in complex environments. To address this problem, a dynamic RIS deployment design framework is introduced for PLS enhancement in mmWave systems against jamming and eavesdropping attacks. For the design, it is aimed to maximize the secrecy rate by jointly optimizing the RIS selection with the beamforming design. The resulting optimization problem is challenging to solve due to the coupling of the RIS control factor, joint beamforming design, and non‐convex constraints. To tackle these issues, an efficient multi‐RIS‐aided PLS enhancement algorithm is proposed. It transforms the objective into a series of subproblems and employs the fractional programming technique and prox‐linear block coordinate descent updating method to solve them alternatively and obtain the optimal solution. The simulations demonstrate the advantage of the dynamic deployment, which exhibits enhanced security performance with reduced complexity compared with benchmarks. Further examinations also provide insight into optimal RIS activation configurations, achieving optimal balance for securing mmWave communications against emerging threats while maintaining system efficiency.

Multiple DC microgrids are interconnected to form a DC microgrid cluster, which can effectively improve the renewable energy consumption capacity and power supply reliability of the microgrid cluster through sharing of energy storage among the participating DC microgrids. However, the existing methods are not able to flexibly coordinate the power flows between DC microgrids connected by a multiport converter. In this paper, a distributed cooperative control method is proposed for a DC microgrid cluster with multiple voltage levels connected by a multi-port interconnected converter. A multi-active-bridge (MAB) converter acts as a bridge for power exchange among microgrids, enabling the sharing of distributed energy storage among microgrids under a sparse communication network. The improved secondary control overcomes the drawbacks of droop control and achieves deviation-free voltage regulation and accurate load/source sharing of the energy storage converters within the cluster. The proposed secondary control can be used to retrofit the existing DC distribution grids to permit access of renewable energy. In addition, the improved voltage observer provides the voltage information of other nodes in a microgrid in addition to the energy storage information, reducing the voltage estimation error caused by the uneven distribution of energy storages. Finally, hardware-in-the-loop (HiL) experiments of the cluster with three DC microgrids verify the control performance, the flexible plug-and-play capability, and the high tolerance of communication failure.

Background: The role of body mass index (BMI) in basal cell carcinoma (BCC) risk remains controversial, and limited information is available regarding the relationship between other physical measurements and BCC. Several recent studies have found a positive effect of adiposity on improved survival when obesity was determined solely by BMI (the ''obesity paradox''). We hypothesize that body fat percentage (BFP) may serve as a more sensitive risk factor for BCC than BMI. Methods: The study conducted a retrospective analysis of clinical data from two distinct centers in China. Individual patient-level data were obtained from medical record reviews spanning January 1, 2015, to December 31, 2022. Associations with outcomes were analyzed using univariate and stratified analyses and assessed using multiple logistic regression with adjustment for confounding factors. Additionally, we performed a meta-analysis to further test the observations in our study. Results: A total of 337 patients, ranging in age from 50 to 91 years, with a mean age of 66.88 (standard deviation 10.16), were included. We observed no significant association between BMI and BCC after adjusting for confounders (OR: 0.71, 95 % CI: 0.36–1.40, P = 0.3186). There was also no convincing effect in a meta-analysis (n = 158,741) (OR: 0.99, 95 % CI: 0.93–1.06, P = 0.8). Furthermore, BFP was found to be associated with BCC (OR: 2.64, 95 % CI: 1.17–5.97, P = 0.0196), supported by strong clinical evidence. Conclusions: Our study supports the hypothesis that BFP is superior to BMI in assessing BCC risk. Multiple logistic regression analyses, coupled with meta-analysis, provided robust evidence that BFP is a sensitive risk factor for BCC, while BMI appears unrelated to risk. According to these findings, routine healthcare practices could benefit from utilizing BFP measurements. The reduction of body fat percentage in low-fat diets may be beneficial for adjuvant treatment of BCC.

Wire arc additive manufacturing (WAAM) is a metal 3D printing technique that allows large-scale elements to be built in a relatively timely and cost-effective manner, well suited to the cost-sensitive construction sector. Despite the potential of this novel technology, the basic properties of WAAM materials remain elusive. This paper presents a comparative study on the microstructure and corrosion behaviour of WAAM steel plates and the conventionally rolled Q345 steel. The WAAM steel exhibited comparable corrosion performance to the conventionally-produced steel within twelve days exposure in 3.5 wt% NaCl solution, including the corrosion current density, and the characteristics of steel/concrete interface, determined through electrochemical impedance spectroscopy (EIS) analysis. Post-corrosion observations revealed that preferential dissolution occurred at (Si, Mn)-rich oxide inclusions, in addition to the general corrosion of surrounding steel matrix. The much higher content of Si and Mn element in the feedstock material WAAM steel resulted in slightly higher susceptibility to localised corrosion, compared to the Q345 rolled steel.

The utilization of waste glass with micro- and nanoparticles in ultra-high-performance concrete (UHPC) has garnered significant interest due to its potential to enhance sustainability and material performance. This study focuses on the implications of integrating microwaste glass (MG) and nanowaste glass in the presence of waste foundry sand and its impact on the properties of UHPC. The particular emphasis of the current work is on compressive strength, tensile strength, sorptivity, and microstructure. It is found that MG enhances compressive strength, decreased tensile strength, reduced sorptivity, and a more compact microstructure. The results indicate that replacing cement with 20% microglass achieves the optimal compressive strength by increasing up to 11.6% at 7 days, 9.5% at 28 days, and 10.18% at 56 days. Nanowaste glass, owing to its increased reactivity and larger surface area, accelerates calcium silicate hydrate formation and improves compressive strength. At the same time, the effective utilization of nanowaste glass improves long-term resilience with an optimum compressive strength at 1.5% replacement ratios of 17.5, 18.9, and 16% at 7, 28, and 56 days, respectively. Splitting tensile strength increased by 16% at 20% MG and 21% at 1.5% nanowaste glass, respectively. Utilizing MG and nanowaste glass in UHPC with waste foundry sand is a promising method for boosting material performance and minimizing environmental impact.

Due to the heavy burden on human drivers when remotely controlling hexapod robots in complex terrain environments, there is a critical need for robot intelligence to assist in generating control commands. Therefore, this study proposes a mapping process framework that generates a combination of human-robot commands based on decision target values, focusing on the task of robot intelligence assisting drivers in generating human-robot command combinations. Furthermore, human-robot state constraints are quantified as geometric constraints on robot motion and driver fatigue constraints. By optimizing and filtering the feasible set of human-robot commands based on human-robot state constraints, instruction combinations are formed and recommended to the driver in real-time, thereby enhancing the efficiency and safety of human-machine coordination. To validate the effectiveness of the proposed method, a remote human-robot collaborative driving control system based on wearable devices is designed and implemented. Experimental results demonstrate that drivers utilizing the human-robot command recommendation system exhibit significantly improved robot walking stability and reduced collision rates compared to individual driving.

Lightning activity poses threats to human life and property safety. A large volume studies indicate that aerosol plays a significant role in lightning activity. To explore the effect of different types of aerosols on lightning activity in the Yangtze River Delta and its surrounding areas, cloud-to-ground (CG) lightning location data and aerosol optical depth from reanalysis dataset is analyzed in the target area(27.5°-35°N, 115°-122.5°E) during 2015-2021.The spatial distribution of aerosol optical depth (AOD) with CG lightning condition and without CG lightning condition, and monthly variation of aerosol concentration under two conditions are investigated. All the grids in the target region show that sulfate AOD is higher, while dust AOD is lower with CG lightning. In summer there are little differences between the AOD with CG lightning and without CG lightning conditions. In other months, more sulfate aerosol and less dust aerosol are found with CG lightning condition.The spatial distribution of CG lightning density difference under higher and lower AOD conditions is given. The results show that when the sulfate AOD is high, the CG lightning density of most grids is higher. The CG lightning density is significantly lower when the dust AOD is high.The correlation coefficient between CG lightning density and the AOD for different types of aerosols is calculated for the months when CG lightning is active. When the concentration of sulfate aerosol is low, the correlation coefficient between sulfate AOD and CG lightning density is significant. When the sulfate aerosol concentration exceeds a certain threshold, there is no significant correlation between CG lightning density and sulfate AOD. The positive correlation may be due to the fact that the cloud microphysical effect of sulfate aerosols can promote the development of convection. With sufficient water vapors, sulfate aerosols form cloud condensation nuclei and promote CG lightning activity. When the concentration of sulfate aerosols is higher than the threshold value, the cloud microphysical effect and the radiation effect of aerosol may be counterbalanced, which may lead to weak correlation between CG lightning density and aerosol concentration. The results also show a weak negative correlation between dust aerosol and CG lightning density in April, May, June, and no significant correlation in July, August, September. Considering the low concentration of dust aerosols in the Yangtze River Delta and its surrounding areas, the inhibitory effect of dust aerosols on CG lightning activity may not be just explained by the radiation effect. The large particle size of dust aerosol may play a significant role in suppressing CG lightning activity.

Abstract Background Structural variations (SVs) in individual genomes are major determinants of complex traits, including adaptability to environmental variables. The Mongolian and Hainan cattle breeds in East Asia are of taurine and indicine origins that have evolved to adapt to cold and hot environments, respectively. However, few studies have investigated SVs in East Asian cattle genomes and their roles in environmental adaptation, and little is known about adaptively introgressed SVs in East Asian cattle. Results In this study, we examine the roles of SVs in the climate adaptation of these two cattle lineages by generating highly contiguous chromosome-scale genome assemblies. Comparison of the two assemblies along with 18 Mongolian and Hainan cattle genomes obtained by long-read sequencing data provides a catalog of 123,898 nonredundant SVs. Several SVs detected from long reads are in exons of genes associated with epidermal differentiation, skin barrier, and bovine tuberculosis resistance. Functional investigations show that a 108-bp exonic insertion in SPN may affect the uptake of Mycobacterium tuberculosis by macrophages, which might contribute to the low susceptibility of Hainan cattle to bovine tuberculosis. Genotyping of 373 whole genomes from 39 breeds identifies 2610 SVs that are differentiated along a “north–south” gradient in China and overlap with 862 related genes that are enriched in pathways related to environmental adaptation. We identify 1457 Chinese indicine-stratified SVs that possibly originate from banteng and are frequent in Chinese indicine cattle. Conclusions Our findings highlight the unique contribution of SVs in East Asian cattle to environmental adaptation and disease resistance.

Rock bolting is a commonly used method for stabilizing the surrounding rock in coal-mine roadways. It involves installing rock bolts after drilling, which penetrate unstable rock layers, binding loose rocks together, enhancing the stability of the surrounding rock, and controlling its deformation. Although recent progress in drilling and anchoring equipment has significantly enhanced the efficiency of roof support in coal mines and improved safety measures, how to deal with drilling rigs’ misalignment with the through-hole center remains a big issue, which may potentially compromise the quality of drilling and consequently affect the effectiveness of bolt support or even result in failure. To address this challenge, this article presents a robotic teleoperation system alongside a hybrid visual servo control strategy. Addressing the demand for high precision and efficiency in aligning the drilling rigs with the center of the drilling hole, a hybrid control strategy is introduced combining position-based and image-based visual servo control. The former facilitates an effective approach to the target area, while the latter ensures high-precision alignment with the center of the drilling hole. The robot teleoperation system employs the binocular vision measurement system to accurately determine the position and orientation of the drilling-hole center, which serves as the designated target position for the drilling rig. Leveraging the displacement and angle sensor information installed on each joint of the manipulator, the system utilizes the kinematic model of the manipulator to compute the spatial position of the end-effector. It dynamically adjusts the spatial pose of the end-effector in real time, aligning it with the target position relative to its current location. Additionally, it utilizes monocular vision information to fine-tune the movement speed and direction of the end-effector, ensuring rapid and precise alignment with the target drilling-hole center. Experimental results demonstrate that this method can control the maximum alignment error within 7 mm, significantly enhancing the alignment accuracy compared to manual control. Compared with the manual control method, the average error of this method is reduced by 41.2%, and the average duration is reduced by 4.3 s. This study paves a new path for high-precision drilling and anchoring of tunnel roofs, thereby improving the quality and efficiency of roof support while mitigating the challenges associated with significant errors and compromised safety during manual control processes.

Using the cloud top data provided by Fengyun-4A (FY-4A) multi-channel scanning imaging radiometer (AGRI) and lightning observations provided by the ground-based global lightning positioning network (WWLLN) during 2019-2020, combined with the meteorological and oceanographic data from MICAPS and extreme wind data recorded by buoys, the spatial-temporal distribution and convective activity characteristics of 71 thunderstorm and strong wind processes in the South China Sea are studied. Results show that the thunderstorms and strong winds recorded by the observatory are mainly distributed in the northern part of the South China Sea. Thunderstorms and strong winds mainly occur from May to September, with the peak in August and valley in March. Thunderstorms and strong winds mainly occur in the morning (0700-1200 BT), with the highest frequency at 1000 BT, a sharp decrease in the frequency in the afternoon, and the lowest frequency between 2100 BT and 2300 BT. The maximum value area of lightning density is distributed in the offshore area of southern Guangdong, and the lightning concentration occurs in the radius of 40 km to 80 km of the observation station. There is an obvious lightning jump in the isolated thunderstorms and strong winds process, and the occurrence time of the first jump is 30 min to 2 min ahead of the peak time of the wind, showing that the lightning activity is indicative of the peak of thunderstorms and strong winds. In terms of convection characteristics, at the peak moment of thunderstorms and wind speed, the cloud top brightness temperature at the location of the observation station is concentrated at 200-220 K, and the cloud top height is concentrated at 12.5 km to 15 km. The distance between the lowest brightness temperature value of isolated thunderstorms and strong winds cloud cluster (i.e., the location of the strongest convection) and the strong winds observation site (i.e., the location of the thunderstorms and strong winds) is 77.2 km on average, and the average difference of brightness temperature value is 2.6 K.

Abstract Acute kidney injury (AKI) is a major renal disease that affects 13 million people and is associated with almost 1.7 million deaths each year around the world. Previously referred to as acute renal failure, AKI is defined not only by a rapid functional decline of the kidney but also by pathological damages in kidney tissue. This updated definition contributes to modern renal medicine in at least two ways. First, the definition of AKI includes an early, preventable and treatable stage of the disease, which implies an urgent need for sensitive biomarkers for early diagnosis and treatment. Second, the AKI definition is proposed with clear criteria for diagnosis and severity grading, which are beneficial for clinical studies and the meta‐analysis of different datasets.

Abstract The pathogenesis of Diabetic kidney disease(DKD) involves pathological changes in both tubulo‐interstitium and the glomerulus. Surprisingly, tubulo‐interstitial fibrosis (TIF), does not develop significantly until the late stage of DKD. Here, it is demonstrated that PR domain‐containing 16 (PRDM16) is a key to the low level of TIF in DKD. In the experiments, PRDM16 is upregulated in high glucose‐treated renal tubular cells, DKD mouse kidneys, and renal biopsy of human DKD patients via activation of NF‐κB signal pathway. High glucose‐induced expression of fibrotic proteins in renal tubular cells is suppressed by PRDM16. Mechanistically, PRDM16 bound to the promotor region of Transient receptor potential ankyrin 1 (TRPA1) to transactivate its expression and then suppressed MAPK (P38, ERK1/2) activation and downstream expression of TGF‐β1. Knockout of PRDM16 from kidney proximal tubules in mice blocked TRPA1 expression and enhanced MAPK activation, TGF‐β1 production, TIF development, and DKD progression, whereas knock‐in of PRDM16 has opposite effects. In addition, overexpression of PRDM16 or its induction by formononetin ameliorated renal dysfunction and fibrosis in db/db diabetic mice. Finally, the above finding are detected in renal biopsies of DKD patients. Together, these results unveil PRDM16/TRPA1 as the mechanism responsible for the low level of TIF in the early stage of DKD by suppressing and TGF‐β1 expression.

IntroductionIt is crucial to understand the environmental friendly behavior of tourists. The utilization of natural resources by the tourists poses a significant threat to environmental sustainability. Fostering environmental friendly practices within tourism industry will help to protect future generation. The current study will evaluate the influence of values, ascribed responsibility, environmental concern and personal norms on customers’ intention to visit green hotels. Furthermore, it will assess the mediating effect of personal norms via ascribed responsibility and environmental concern.MethodsThe study collected data from Data 347 customers through a questionnaire survey method. Partial least square-structural equation model (PLS-SEM) was employed for the analysis of data.Results and discussionThe findings indicate that values are significant factors affecting ascribed responsibility and environmental concern. Environmental concern direct impact on intention was insignificant. However, the environmental concern significantly affect intention to visit green hotels via personal norms indicating full mediating impact of personal norms.

Synchrotron tomography experiments are transitioning into multifunctional, cross-scale, and dynamic characterizations, enabled by new-generation synchrotron light sources and fast developments in beamline instrumentation. However, with the spatial and temporal resolving power entering a new era, this transition generates vast amounts of data, which imposes a significant burden on the data processing end. Today, as a highly accurate and efficient data processing method, deep learning shows great potential to address the big data challenge being encountered at future synchrotron beamlines. In this review, we discuss recent advances employing deep learning at different stages of the synchrotron tomography data processing pipeline. We also highlight how applications in other data-intensive fields, such as medical imaging and electron tomography, can be migrated to synchrotron tomography. Finally, we provide our thoughts on possible challenges and opportunities as well as the outlook, envisioning selected deep learning methods, curated big models, and customized learning strategies, all through an intelligent scheduling solution. Public summary: • Tomography experiments at future synchrotron beamlines face exascale big data challenges. • Deep learning is employed for various data processing tasks at current synchrotron tomography beamlines. • Future comprehensive and elongated data analysis processes require a full-stack deep learning pipeline. • The data-driven full-stack deep learning pipeline based on an intelligent scheduling center (ISC) holds the key to solve the big data challenges.

Structural disclosure of biological materials can help our understanding of design disciplines in nature and inspire research for artificial materials. Synchrotron microfocus X-ray diffraction is one of the main techniques for characterizing hierarchically structured biological materials, especially the 3D orientation distribution of their interpenetrating nanofiber networks. However, extraction of 3D fiber orientation from X-ray patterns is still carried out by iterative parametric fitting, with disadvantages of time consumption and demand for expertise and initial parameter estimates. When faced with high-throughput experiments, existing analysis methods cannot meet the real time analysis challenges. In this work, using the assumption that the X-ray illuminated volume is dominated by two groups of nanofibers in a gradient biological composite, a machine-learning based method is proposed for fast and automatic fiber orientation metrics prediction from synchrotron X-ray micro-focused diffraction data. The simulated data were corrupted in the training procedure to guarantee the prediction ability of the trained machine-learning algorithm in real-world experimental data predictions. Label transformation was used to resolve the jump discontinuity problem when predicting angle parameters. The proposed method shows promise for application in the automatic data-processing pipeline for fast analysis of the vast data generated from multiscale diffraction-based tomography characterization of textured biomaterials.

Abstract With the advancements in instrumentations of next-generation synchrotron light sources, methodologies for small-angle X-ray scattering (SAXS)/wide-angle X-ray diffraction (WAXD) experiments have dramatically evolved. Such experiments have developed into dynamic and multiscale in situ characterizations, leaving prolonged exposure time as well as radiation-induced damage a serious concern. However, reduction on exposure time or dose may result in noisier images with a lower signal-to-noise ratio, requiring powerful denoising mechanisms for physical information retrieval. Here, we tackle the problem from an algorithmic perspective by proposing a small yet effective machine-learning model for experimental SAXS/WAXD image denoising, allowing more redundancy for exposure time or dose reduction. Compared with classic models developed for natural image scenarios, our model provides a bespoke denoising solution, demonstrating superior performance on highly textured SAXS/WAXD images. The model is versatile and can be applied to denoising in other synchrotron imaging experiments when data volume and image complexity is concerned.

Summary: Tomography experiments generate three-dimensional (3D) reconstructed slices from a series of two-dimensional (2D) projection images. However, the mechanical system generates joint offsets that result in unaligned 2D projections. This misalignment affects the reconstructed images and reduces their actual spatial resolution. In this study, we present a novel method called outer contour-based misalignment correction (OCMC) for correcting image misalignments in tomography. We use the sample’s outer contour structure as auxiliary information to estimate the extent of misalignment in each image. This method is generic and can be used with various tomography imaging techniques. We validated our method with five datasets collected from different samples and across various tomography techniques. The OCMC method demonstrated significant advantages in terms alignment accuracy and time efficiency. As an end-to-end correction method, OCMC can be easily integrated into an online tomography data processing pipeline and facilitate feedback control in future synchrotron tomography experiments.

Infectious diseases caused by Aeromonas hydrophila (AH) have reduced the populations of Rana dybowskii). However, little is known about the immune response of R. dybowskii against AH infections. The toll-like receptor (TLR) signaling pathway has been identified as a critical component in innate immunity, responsible for identifying pathogen-associated molecular patterns in pathogens. Our study used the next-generation sequencing technique and single-molecule long-read sequencing to determine the structures of transcript isoforms and functions of genes in the kidneys of R. dybowskii, as well as identify and validate the related genes in the TLR4 signaling pathway. In total, 628,774 reads of inserts were identified, including 300,053 full-length non-chimeric reads and 233,592 non-full-length reads. Among the transcriptome sequences, 124 genes were identified as homologs of known genes in the TLR4 pathway especially inflammatory cytokines and receptors. Our findings shed light on the structures and functions of R. dybowskii genes exposed to AH and confirm the presence of both MyD88-dependent and independent pathways in R. dybowskii. Our work reveals how various functional proteins in amphibians at the initial stage of immune response are activated and complete their corresponding functions in a short time.

Cisplatin is one of the major causes of acute kidney injury (AKI) in clinical practice, and ferroptosis is an essential form of cell death in cisplatin-induced AKI (CP-AKI). WW domain binding protein-2 (WBP2), a molecular chaperon, is involved in the progression of various malignancies, but its role in renal injuries has not been investigated. Our present study employed bioinformatics analysis to identify WBP2 as a potential modulator of AKI and ferroptosis. Preliminary laboratory investigations showed that WBP2, highly expressed in renal proximal tubular cells, was downregulated in CP-AKI. Further studies demonstrated that WBP2 decelerated ferroptosis to alleviate CP-AKI. Mechanistically, WBP2 interacted with glutathione peroxidase 4 (GPX4, a key detoxicating enzyme for ferroptosis) via its PPXY1 motif to inhibit ferroptosis. Furthermore, the in-depth investigations revealed that WBP2 competed with heat shock cognate protein 70 (HSC70) for the binding with the KEFRQ-like motifs of GPX4, leading to the deceleration of chaperon-mediated autophagy of GPX4. All in all, this study indicated the beneficial effect of WBP2 in CP-AKI and its relevance with ferroptosis, thus providing a novel insight into the modulation of ferroptosis in cisplatin-related nephropathy.

Objective: This study aimed to detect the quality of wheat flour quickly and non-destructively. Methods: The online detection system for wheat flour quality was built in the experiment, which mainly includes the flowing four parts: micro near-infrared spectrometer integrated device, production line adjustable speed simulation device, spectrum online acquisition and control software and online modeling and analysis software. Different modeling algorithms were used to establish quantitative analysis models for moisture, ash and gluten, and the robustness of the online quantitative analysis model was optimized. The influence of different experimental conditions on the modeling results was analyzed. Results: Partial least squares regression （PLSR） algorithm is superior to multiple linear regression （MLR） and principal component regression （PCR） algorithm for quantitative analysis of moisture, ash and gluten. The best modeling effect was obtained by using quartz glass to collect wheat flour samples online, and the best ratio of 15 speed/integration time was 6 000 ms. Conclusion: The wheat flour quality online detection system based on near-infrared spectrum analysis technology realize the nondestructive and rapid online detection of wheat flour quality.

Metal-halide perovskite light-emitting diodes (PeLEDs) are considered as new-generation highly efficient luminescent materials for application in displays and solid-state lighting. Since the first successful demonstration of PeLEDs in 2014, the research on the development of efficient PeLEDs has progressed significantly. Although the device efficiency has significantly improved over a short period of time, their overall performance has not yet reached the levels of mature technologies for practical applications. Various degradation processes are the major impediment to improving the performance and stability of PeLED devices. In this review, we discuss various analysis techniques that are necessary to gain insights into the effects of various degradation mechanisms on the performance and stability of PeLEDs. Based on the causes and effects of external and internal factors, the degradation processes and associated mechanisms are examined in terms of critical physical and chemical parameters. Further, according to the progress of the current research, the challenges faced in studying degradation mechanisms are also elucidated. Given the universality of the degradation behavior, an in-depth understanding of the device degradation may promote the development of optimization strategies and further improve the performance and stability of PeLEDs.

Abstract Aberrant DNA methylation (DNAm) is an important epigenetic regulator in various cancers. Pan-cancer DNAm analyses have investigated the potential common mechanisms of DNAm in tumorigenesis. However, these pan-cancer studies focused on adult cancers rather than pediatric cancers, which may have distinct pathology and treatment responses. Here, we performed a pan-cancer analysis of genome-wide DNAm in over 2,000 samples from nine pediatric cancers to elucidate the DNAm landscape of pediatric cancers. We identified 217,586 differentially methylated CpG sites (DMCs) in pediatric cancers, with a tendency toward hypermethylation as opposed to hypomethylation (P = 0.02). Amongst them, 75.65% also presented DNAm alterations in adult cancers. In nine pediatric cancers, we defined 54 shared DMCs (SDMCs), which were also observed in at least one adult cancer type. Furthermore, methylation patterns in SDMCs influenced the transcription of several genes (MEIS1, MIA3, PCDHAC2, SH3BP4, and ATP8B1) involved in well-known cancer-related pathways and cancer hallmarks (FDR

Reinforcement corrosion significantly impacts the service life of reinforced concrete structures. The present study investigates the circumferential and longitudinal non-uniformity of steel corrosion in concrete subjected to mechanical load. Results indicate that, in the case of steel corrosion in concrete subjected to mechanical load, the distribution of rust layer thickness around the perimeter of the steel bar is fitted well with a Gaussian distribution. As the corrosion rate gradually increases, the uniform coefficient is linearly proportional to the minimum thickness of the rust layer. With respect to the longitudinal non-uniformity of steel corrosion, load-induced transverse cracks have a significant impact on the non-uniformity of corrosion, leading to the formation of rust peaks near the locations of transverse cracks. In the vicinity of each rust peak, the corrosion rate of the steel bar follows a Gaussian distribution. With respect to the non-uniformity of corrosion along the longitudinal rebar, a Gumbel distribution is identified to fit well, both in the cases of the non-stressed section and the pure bending section, although with dissimilar non-uniform parameters. Crack coefficients (α and β) are introduced to describe the influence of transverse cracks on the longitudinal non-uniformity of steel corrosion.

Peanut shells, a major economic and oil crop in China, boast an abundant availability and remarkably high lignin content compared to other agricultural residues. Previous work indicated that the modified hierarchical zeolite (Zn-ZSM-5/MCM41) was effective in promoting the conversion of intermediate macromolecules during the lignin pyrolysis reaction and enhancing the yield and selectivity of liquid products. Thereby, this study aims to improve the quality of liquid products in the ex situ catalytic microwave co-pyrolysis of peanut shells and LDPE by utilizing Zn-ZSM-5/MCM41. Employing a compound center experimental design, we optimized reaction conditions through response surface analysis. The impact of microwave pyrolysis temperature and the catalyst-to-feedstock ratio on yield distribution and liquid product selectivity was explored. Results indicated a marginal increase in liquid product yield with rising pyrolysis temperatures. Moreover, an initial increase followed by a subsequent decrease in liquid product yield was observed with an increase in the catalyst-to-feedstock ratio. Optimal conditions of 450 °C and a catalyst-to-peanut hull ratio of 2.34% yielded the highest bio-oil yield at 34.25%. GC/MS analysis of the bio-oil revealed a peak in hydrocarbon content at 68.36% under conditions of 450 °C and a catalyst-to-feedstock ratio of 13.66%. Additionally, the quadratic model effectively predicted bio-oil yield and the selectivity for major chemical components. This study underscores the potential of Zn-ZSM-5/MCM41 in optimizing liquid product quality during catalytic co-pyrolysis, offering insights into bio-oil production and its chemical composition.

This article reported the clinical features of a rare patient with anti-metabotropic glutamate receptor 5 （mGluR5） encephalitis with mental disorders as the initial symptom， so as to provide references for clinical diagnosis and treatment. The patient was a 38-year-old male， developed pharyngeal pain as prodromal symptoms， and the main clinical manifestations included rapidly progressive memory loss， anxiety and depression， and psychomotor excitement symptoms including irritability and impulsive behaviors. The disease had a progressive deterioration. In the most severe state， the patient became unconscious in a shallow coma， with further cognitive decline， hallucinations and delusions， and lack of self-awareness. Both cerebrospinal fluid and serum anti-mGluR5 antibody were strongly positive （1∶100）. After two sessions of hormone shock therapy， the patient showed significantly improvement in consciousness， cognitive， emotional and psychiatric dimensions.

Plant architecture strongly influences rice grain yield. We report the cloning and characterization of the LTA1 gene, which simultaneously controls tiller angle and yield of rice. LTA1 encodes a chloroplast-localized protein with a conserved YbaB DNA-binding domain, and is highly expressed in photosynthetic tissues including leaves and leaf sheaths. Disrupting the function of LTA1 leads to large tiller angle and yield reduction of rice. LTA1 affects the gravity response by mediating the distribution of endogenous auxin, thereby regulating the tiller angle. An lta1 mutant showed abnormal chloroplast development and decreased chlorophyll content and photosynthetic rate, in turn leading to reduction of rice yield. Our findings shed light on the genetic basis of tiller angle and provide a potential gene resource for the improvement of plant architecture and rice yield.

Cisplatin is a widely used chemotherapy drug; however, it induces both acute and chronic kidney diseases (CKD) in patients with cancer. The pathogenesis of cisplatin-induced CKD is unclear, and effective renoprotective approaches are not available. Here, we report that repeated low-dose cisplatin (RLDC) treatment of C57BL/6 mice induced chronic cellular senescence in kidney tubules, accompanied with tubular degeneration and profibrotic phenotype transformation that culminated in maladaptive repair and renal fibrosis. Suppression of tubular senescence by senolytic drugs ABT-263 and Fisetin attenuated renal fibrosis and improved tubular repair, as indicated by restoration of tubular regeneration and renal function. In vitro, RLDC also induced senescence in mouse proximal tubular (BUMPT) cells. ABT-263 eliminated senescent BUMPT cells following RLDC treatment, reversed the profibrotic phenotype of the cells, and increased their clonogenic activity. Moreover, ABT-263 alleviated the paracrine effect of RLDC-treated BUMPT cells on fibroblasts for fibrosis. Consistently, knockdown of p16 suppressed post-RLDC senescence and fibrotic changes in BUMPT cells and alleviated their paracrine effects on renal fibroblast proliferation. These results indicate that persistent induction of tubular senescence plays an important role in promoting cisplatin-induced CKD. Targeting senescent tubular cells may be efficient for improvement of kidney repair and for the prevention and treatment of cisplatin-induced CKD.

Artificially triggered lightning refers to the lightning that is artificially triggered to the ground under appropriate thunderstorm conditions. The location of artificially triggered lightning can be determined; the occurring time can be precisely stamped, and the channel-base current can be measured directly. Therefore, it's one of the effective methods to evaluate the performance of lightning location system (LLS). From the observations of artificially triggered lightning experiment conducted at the Field Experiment Base on Lightning Sciences, China Meteorological Administration from 2014 to 2019, 50 lightning flashes are selected to evaluate and analyze the performance characteristics of Guangdong-Hongkong-Macau Lightning Location System (GHMLLS).The results show that the lightning detection efficiency and stroke detection efficiency are about 96% (48/50) and 88% (233/265), respectively. The arithmetic mean, geometric mean and median values of location error are 279 m, 193 m and 202 m, respectively. The results show that there is a systematic deviation to the southwest in GHMLLS observations around the triggered lightning experiment site, which is about 170 m to the west and 50 m to the south. After correction, the arithmetic mean, geometric mean and median values of location error are reduced to 198 m, 108 m and 103 m, respectively. The linear fitting result with intercept of 0 shows that the LLS-inferred peak current of GHMLLS is about 65% of the direct measurement value of the channel-base current. Meanwhile, the arithmetic mean (median) value of the LLS-inferred peak current error is -37% (-36%). However, there is a strong positive correlation and the correlation coefficient is 0.93. The arithmetic mean (median) value of the absolute value of the LLS-inferred peak current error is reduced to 15% (12%) when the ratio of 65% is used to correct them. Among 233 return strokes of triggered lightning flashes, 16 return strokes are mistakenly classified as intra-cloud lightning, so the return stroke classification accuracy of GHMLLS is 93%. The peak currents of these mistakenly classified return strokes are lower, the stations available for locating are fewer, and the errors of location and LLS-inferred peak current are larger.In conclusion, GHMLLS have good detection efficiency and location accuracy. The return stroke classification accuracy of GHMLLS is at a high level as well. Nevertheless, there is an obvious systematic deviation in the LLS-inferred peak current of GHMLLS. In order to obtain more reliable analysis results, it's recommended to divide it by 0.65 when using the LLS-inferred peak current of GHMLLS.

The structure and mechanical properties of the stomatopod dactyl club have been studied extensively for its extreme impact tolerance, but a systematic in situ investigation on the multiscale mechanical responses under high-speed impact has not been reported. Here the full dynamic deformation and crack evolution process within projectile-impacted dactyl using combined fast 2D X-ray imaging and high-resolution ex situ tomography are revealed. The results show that hydration states can lead to significantly different toughening mechanisms inside dactyl under dynamic loading. A previously unreported 3D interlocking structural design in the impact surface and impact region is reported using nano X-ray tomography. Experimental results and dynamic finite-element modeling suggest this unique structure plays an important role in resisting catastrophic structural damage and hindering crack propagation. This work is a contribution to understanding the key toughening strategies of biological materials and provides valuable information for biomimetic manufacturing of impact-resistant materials in general.

This work explores correlations between genetic polymorphisms in apolipoprotein E (ApoE) and atrial fibrillation (AF). We detected polymorphisms in the APOE gene in 64 patients with AF and 49 non-AF volunteers at the Department of Cardiology of Lianyungang Second People's Hospital between July 2017 and July 2019. We found significant differences in age, body mass index, left atrial diameter, and left ventricular ejection fraction between the two groups. Six APOE genotypes were observed: ɛ2/ɛ2; ɛ2/ɛ3; ɛ2/ɛ4; ɛ3/ɛ3; ɛ3/ɛ4; and ɛ4/ɛ4. The ɛ3/ɛ3 genotype was significantly less frequent in the AF group than in the control group, while the ɛ3/ɛ4 and ɛ4/ɛ4 genotypes were significantly more frequent in the AF group than in the control group (p

The grid-forming virtual synchronous generator (GFVSG) with large virtual inertia can provide a friendly grid-connected operational mode for power electronic converters, but it may also introduce the active power dynamic oscillation problems similar to traditional synchronous generators. In view of this, the dynamic equivalent circuit model of the GFVSG grid-tied active power-angle is established firstly, and, then, the understanding of the GFVSG active power oscillations under variable disturbances is revealed from the perspective of circuit energy flow in this paper. On this basis, an active power dynamic oscillation damping method based on an energy reshaping mechanism for the GFVSG is proposed, and a parameter design method using the second-order equivalent reduced-order control model is given. The MATLAB 2016a simulation as well as experimental test platforms of a 100 kV·A GFVSG grid-connected system are established, then, both the feasibility and effectiveness of the proposed active power dynamic oscillation damping method are verified by using the simulation and experimental comparison results.

The implementation of roof bolt support within a coal mine roadway has the capacity to bolster the stability of the encompassing rock strata and thereby mitigate the potential for accidents. To enhance the automation of support operations, this paper introduces a binocular vision positioning method for drilling holes, which relies on the adaptive adjustment of parameters. Through the establishment of a predictive model, the correlation between the radius of the target circular hole in the image and the shooting distance is ascertained. Based on the structural model of the anchor drilling robot and the related sensing data, the shooting distance range is defined. Exploiting the geometric constraints inherent to adjacent anchor holes, the precise identification of anchor holes is detected by a Hough transformer with an adaptive parameter-adjusted method. On this basis, the matching of the anchor hole contour is realized by using linear slope and geometric constraints, and the spatial coordinates of the anchor hole center in the camera coordinate system are determined based on the binocular vision positioning principle. The outcomes of the experiments reveal that the method attains a positioning accuracy of 95.2%, with an absolute error of around 1.52 mm. When compared with manual operation, this technique distinctly enhances drilling accuracy and augments support efficiency.

This paper develops and optimizes a non-orthogonal and noncoherent multi-user massive single-input multiple-output (SIMO) framework, with the objective of enabling scalable ultra-reliable low-latency communications (sURLLC) in Beyond-5G (B5G)/6G wireless communication systems. In this framework, the huge diversity gain associated with the large-scale antenna array in the massive SIMO system is leveraged to ensure ultra-high reliability. To reduce the overhead and latency induced by the channel estimation process, we advocate for the noncoherent communication technique, which does not need the knowledge of instantaneous channel state information (CSI) but only relies on large-scale fading coefficients for message decoding. To boost the scalability of noncoherent massive SIMO systems, we enable the non-orthogonal channel access of multiple users by devising a new differential modulation scheme to ensure that each transmitted signal matrix can be uniquely determined in the noise-free case and be reliably estimated in noisy cases when the antenna array size is scaled up. The key idea is to make the transmitted signals from multiple geographically separated users be superimposed properly over the air, such that when the sum signal is correctly detected, the signal sent by each individual user can be uniquely determined. To further enhance the average error performance when the array antenna number is large, we propose a max–min Kullback–Leibler (KL) divergence-based design by jointly optimizing the transmitted powers of all users and the sub-constellation assignments among them. The simulation results show that the proposed design significantly outperforms the existing max–min Euclidean distance-based counterpart in terms of error performance. Moreover, our proposed approach also has a better error performance compared to the conventional coherent zero-forcing (ZF) receiver with orthogonal channel training, particularly for cell-edge users.

ObjectiveTo study whether diatoms can enter the body through the lymphatic system of the digestive tract.MethodsTwenty experimental rabbits were divided into the test group and the control group randomly, and intragastric administration was performed with 20 mL water sample from the Pearl River and 20 mL ultrapure water, respectively. After 30 min, lymph, lungs， livers and kidneys were extracted for the diatom test. The concentration, size and type of diatoms were recorded.ResultsThe concentration of diatoms of the test group was higher than that of the control group （P

ObjectiveTo retrospectively analyze diatom test cases of corpses in water and discuss the value of quantitative analysis of diatoms in the diagnosis of drowning.MethodsA total of 490 cases of water-related death were collected. They were divided into drowning group and postmortem immersion group according to the cause of death. Diatoms in lung, liver, kidney tissue and water sample were analyzed quantitatively by microwave digestion-vacuum filtration-automated scanning electron microscopy （MD-VF-Auto SEM） method. The ratios of content of diatoms in lung tissue and water sample （CL/CD） were calculated.ResultsThe results of diatom test for three organs （lung, liver and kidney） were all positive in 400 cases （85.5%）; the content of diatom in lung, liver, kidney tissues, and water samples of drowning group were （113 235.9±317 868.1）, （26.7±75.6）, （23.3±52.2） and （12 113.3±21 760.0） cells/10 g, respectively; the species of diatom were （7.5±2.8）, （2.6±1.9）, （2.9±2.1） and （8.9±3.0） types, respectively; the CL/CD of drowning group and postmortem immersion group were （100.6±830.7） and （0.3±0.4）, respectively.ConclusionQuantitative analysis of diatoms can provide supportive evidence for the diagnosis of drowning, and the parameter CL/CD can be introduced into the analysis to make a more accurate diagnosis of drowning.

ObjectiveTo study the effects of temperature and time for diatoms digestion and find out suitable digestive temperature and time.MethodsEighty pieces of liver tissues were collected, each piece of tissue was 2 g, and 2 mL Pearl River water was added to each piece of tissue. The digestion temperature was set at 100 ℃, 120 ℃, 140 ℃, 160 ℃, 180 ℃ and the digestion time was set at 40, 50, 60, 70, 80 min. The liver tissue and water mixture were divided into 8 portions in each group. All the samples were tested by microwave digestive - vacuum filtration - automated scanning electron microscopy method. The quantity of diatom recovered and the quality of residue on the membrane were recorded.ResultsWhen the digestion time was set to 60 min, there were statistically significant differences in the number of diatoms recovered at different temperatures （P0.05）.ConclusionThe effect of diatom digestion is related to temperature and time. When the digestion temperature was 140 ℃ and the digestion time was 40, 50 and 60 min, it is favorable for diatom test.

Tropical cyclone is one of the major weather disasters affecting coastal areas, which can produce high winds and heavy rains, posing serious threats to the safety of people's lives and property in coastal areas. China is in the Northwest Pacific, which is affected more frequently by tropical cyclones than any other area in the world. Therefore, it is of great significance to strengthen the research on tropical cyclone in the Northwest Pacific. In recent years, observations and studies have proved that lightning activity often occurs in tropical cyclone, which is closely related to the convective evolution and intensity variation of tropical cyclone. Based on data of lightning imaging sensor (LIS) carried on the TRMM (Tropical Rainfall Measuring Mission) satellite during 1998-2014, the characteristics of lightning properties (including duration, extended distance, channel area and optical radiant energy) of tropical cyclone in the Northwest Pacific are studied by establishing the lightning dataset of tropical cyclone in the region. The results show that all attributes of tropical cyclone lightning present lognormal distribution characteristics, and the distribution of peak values of these attributes is consistent with that of the Northwest Pacific thunderstorm system, but different from that of East Asia land thunderstorm system. The maximum of tropical cyclone lightning tends to occur over the ocean at tropical depression intensity levels. The maximum proportion of lightning in the outer rain belt is the lowest, while the maximum proportion of the duration and optical radiant energy of lightning in the inner core is the highest. The tropical cyclone lightning duration of different intensity levels has no significant difference, but the mean value of lightning spatial scale and optical radiation energy of tropical storm are lower than those of tropical depression and typhoon. For different areas of tropical cyclone, the maximum value of duration and optical radiant energy of core lightning decrease with the increase of distance between lightning and tropical cyclone center. In terms of maritime-continental contrasts, tropical cyclone lightning occurs over the ocean with larger spatial scale and stronger optical radiant energy than that over the land, while lightning duration is roughly the same. After tropical cyclone landing, the spatial scale of lightning decreases and the optical radiant energy of lightning weakens. Compared with non-tropical cyclone lightning, tropical cyclone lightning has shorter extension distance, narrower channel area and weaker optical radiant energy, but the average duration of lightning is longer.

Abstract While urine-based liquid biopsy has expanded to the analyses of extracellular nucleic acids, the potential of transfer RNA (tRNA) encapsulated within extracellular vesicles has not been explored as a new class of urine biomarkers for kidney injury. Using rat kidney and mouse tubular cell injury models, we tested if extracellular vesicle-loaded tRNA and their m1A (N 1-methyladenosine) modification reflect oxidative stress of kidney injury and determined the mechanism of tRNA packaging into extracellular vesicles. We determined a set of extracellular vesicle-loaded, isoaccepting tRNAs differentially released after ischemia–reperfusion injury and oxidative stress. Next, we found that m1A modification of extracellular vesicle tRNAs, despite an increase of the methylated tRNAs in intracellular vesicles, showed little or no change under oxidative stress. Mechanistically, oxidative stress decreases tRNA loading into intracellular vesicles while the tRNA-loaded vesicles are accumulated due to decreased release of the vesicles from the cell surface. Furthermore, Maf1-mediated transcriptional repression of the tRNAs decreases the cargo availability for extracellular vesicle release in response to oxidative stress. Taken together, our data support that release of extracellular vesicle tRNAs reflects oxidative stress of kidney tubules which might be useful to detect ischemic kidney injury and could lead to rebalance protein translation under oxidative stress.

Abstract Objectives Conventional glucocorticoid (GC) treatment poses significant risks for opportunistic infections due to its suppressive impact on CD4+ T cells. This study aimed to explore the mechanisms by which GCs modulate the functionality of CD4+ T cells during infection. Methods We consistently measured FOXP3, inflammatory cytokines and phospho‐S6 ribosomal protein levels in CD4+ T cells from patients undergoing conventional GC treatment. Using Foxp3EGFP animals, we investigated the dynamic activation of the mechanistic target of rapamycin complex 1 (mTORC1) pathway and its correlation with the immunoregulatory function of CD4+ T cells under the influence of GCs. Results GCs dynamically altered the expression pattern of FOXP3 in CD4+ T cells, promoting their acquisition of an active T regulatory (Treg) cell phenotype upon stimulation. Mechanistically, GCs undermined the kinetics of the mTORC1 pathway, which was closely correlated with phenotype conversion and functional properties of CD4+ T cells. Dynamic activation of the mTORC1 signaling modified the GC‐dampened immunoregulatory capacity of CD4+ T cells by phenotypically and functionally bolstering the FOXP3+ Treg cells. Interventions targeting the mTORC1 pathway effectively modulated the GC‐dampened immunoregulatory capacity of CD4+ T cells. Conclusion These findings highlight a novel mTORC1‐mediated mechanism underlying CD4+ T cell immunity in the context of conventional GC treatment.

BackgroundHepatocellular carcinoma (HCC) is the major cause of malignancy-related deaths worldwide, and its incidence is likely to increase in the future as life expectancy increases. Therefore, the management of elderly patients with HCC has become a global issue. Aim of this study was to assess whether elderly patients with small HCC could obtain survival benefit from cryoablation (CRYO) in a real-world.Materials and methodsFrom July 2007 to June 2013, 185 patients with small HCC who underwent curative-intent percutaneous CRYO. All patients were divided into three groups according to age distribution. Overall survival (OS) and tumor-free survival (TFS) were compared between among of groups before and after the 1:1 propensity score matching, respectively. Univariate and multivariate Cox analyses were performed to determine the potential relationships between variables and prognostic outcomes.ResultsOne hundred and eighty-five patients (144 men, 41 women) received CRYO for small HCC, including 59 patients with age 65 years. The three age groups showed significant differences in the terms of underlying chronic liver disease and the number of patients with minor postoperative complications. After propensity score matching, the younger and elderly groups showed significant differences in mean OS (P=0.008) and tumor progression (P=0.050). However, no significant differences were shown in mean progression-free survival (PFS) (P=0.303). The Cox multivariate analysis showed that the Child-Pugh grade (HR=3.1, P

Pathological angiogenesis is a major cause of irreversible blindness in individuals of all age groups with proliferative retinopathy (PR). Mononuclear phagocytes (MPs) within neovascular areas contribute to aberrant retinal angiogenesis. Due to their cellular heterogeneity, defining the roles of MP subsets in PR onset and progression has been challenging. Here, we aimed to investigate the heterogeneity of microglia associated with neovascularization and to characterize the transcriptional profiles and metabolic pathways of proangiogenic microglia in a mouse model of oxygen-induced PR (OIR). Using transcriptional single-cell sorting, we comprehensively mapped all microglia populations in retinas of room air (RA) and OIR mice. We have unveiled several unique types of PR-associated microglia (PRAM) and identified markers, signaling pathways, and regulons associated with these cells. Among these microglia subpopulations, we found a highly proliferative microglia subset with high self-renewal capacity and a hypermetabolic microglia subset that expresses high levels of activating microglia markers, glycolytic enzymes, and proangiogenic Igf1. IHC staining shows that these PRAM were spatially located within or around neovascular tufts. These unique types of microglia have the potential to promote retinal angiogenesis, which may have important implications for future treatment of PR and other pathological ocular angiogenesis–related diseases.