Search

Summary: Infrared and visible image fusion aims to produce images that highlight key targets and offer distinct textures, by merging the thermal radiation infrared images with the detailed texture visible images. Traditional auto encoder-decoder-based fusion methods often rely on manually designed fusion strategies, which lack flexibility across different scenarios. Addressing this limitation, we introduce EMAFusion, a fusion approach featuring an enhanced multiscale encoder and a learnable, lightweight fusion network. Our method incorporates skip connections, the convolutional block attention module (CBAM), and nest architecture within the auto encoder-decoder framework to adeptly extract and preserve multiscale features for fusion tasks. Furthermore, a fusion network driven by spatial and channel attention mechanisms is proposed, designed to precisely capture and integrate essential features from both image types. Comprehensive evaluations of the TNO image fusion dataset affirm the proposed method’s superiority over existing state-of-the-art techniques, demonstrating its potential for advancing infrared and visible image fusion.

Abdominal Aortic Aneurysm (AAA) is a disease characterized by localized dilation of the abdominal aorta, involving multiple factors in its occurrence and development, ultimately leading to vessel rupture and severe bleeding. AAA has a high mortality rate, and there is a lack of targeted therapeutic drugs. Epigenetic regulation plays a crucial role in AAA, and the treatment of AAA in the epigenetic field may involve a series of related genes and pathways. Abnormal expression of these genes may be a key factor in the occurrence of the disease and could potentially serve as promising therapeutic targets. Understanding the epigenetic regulation of AAA is of significant importance in revealing the mechanisms underlying the disease and identifying new therapeutic targets. This knowledge can contribute to offering AAA patients better clinical treatment options beyond surgery. This review systematically explores various aspects of epigenetic regulation in AAA, including DNA methylation, histone modification, non-coding RNA, and RNA modification. The analysis of the roles of these regulatory mechanisms, along with the identification of relevant genes and pathways associated with AAA, is discussed comprehensively. Additionally, a comprehensive discussion is provided on existing treatment strategies and prospects for epigenetics-based treatments, offering insights for future clinical interventions.

The off-line discharge between the pantograph and catenary (PAC) occurs frequently in the actual operation of an electric locomotive, which affects the quality of the received current and the service life of the pantograph. The current experiments on the off-line discharge between the PAC are mainly low-power ones and the models established are static. To study the electrical behaviors during the PAC relative motion under the actual working conditions, in this paper, the voltage and current of the contact wire (CW) during its motion are measured. And the electrical behaviors during the rise, fall and reciprocating motions of the pantograph are investigated by combining a finite element method (FEM) model based on the magnetohydrodynamics with the auto transformer (AT) traction network circuit and moving mesh method. It is found that the harmonic frequencies are mainly in the range of 0-30 MHz. The voltage distortion is more obvious during the fall of the pantograph. And the negative polarity spike pulse has a larger amplitude and occurs more frequently. The novelty of this paper lies in the experimental test with the high current and high power, as well as the systematic analysis of the electrical behaviors and multi-physical field evolution during the motion of the pantograph under the working conditions. Its contribution is to present an effective method to study the dynamic behaviors of the PAC. The research results can provide an important reference for the identification of the electrical characteristics of the PAC and the protection of the PAC equipment.

Abstract Traditional statistical methods (TSM) and machine learning (ML) methods have been widely used to separate the effects of emissions and meteorology on air pollutant concentrations, while their performance compared to the chemistry transport model has been less fully investigated. Using the Community Multiscale Air Quality Model (CMAQ) as a reference, a series of experiments was conducted to comprehensively investigate the performance of TSM (e.g., multiple linear regression and Kolmogorov–Zurbenko filter) and ML (e.g., random forest and extreme gradient boosting) approaches in quantifying the effects of emissions and meteorology on the trends of fine particulate matter (PM2.5) during 2013−2017. Model performance evaluation metrics suggested that the TSM and ML methods can explain the variations of PM2.5 with the highest performance from ML. The trends of PM2.5 showed insignificant differences (p > 0.05) for both the emission-related ( $${{\rm{PM}}}_{2.5}^{{\rm{EMI}}}$$ PM 2.5 EMI ) and meteorology-related components between TSM, ML, and CMAQ modeling results. $${{\rm{PM}}}_{2.5}^{{\rm{EMI}}}$$ PM 2.5 EMI estimated from ML showed the least difference to that from CMAQ. Considering the medium computing resources and low model biases, the ML method is recommended for weather normalization of PM2.5. Sensitivity analysis further suggested that the ML model with optimized hyperparameters and the exclusion of temporal variables in weather normalization can further produce reasonable results in emission-related trends of PM2.5.

Fusarium head blight (FHB) is a destructive disease that affects wheat production. Detecting FHB accurately and rapidly is crucial for improving wheat yield. Traditional models are difficult to apply to mobile devices due to large parameters, high computation, and resource requirements. Therefore, this article proposes a lightweight detection method based on an improved YOLOv8s to facilitate the rapid deployment of the model on mobile terminals and improve the detection efficiency of wheat FHB. The proposed method introduced a C-FasterNet module, which replaced the C2f module in the backbone network. It helps reduce the number of parameters and the computational volume of the model. Additionally, the Conv in the backbone network is replaced with GhostConv, further reducing parameters and computation without significantly affecting detection accuracy. Thirdly, the introduction of the Focal CIoU loss function reduces the impact of sample imbalance on the detection results and accelerates the model convergence. Lastly, the large target detection head was removed from the model for lightweight. The experimental results show that the size of the improved model (YOLOv8s-CGF) is only 11.7 M, which accounts for 52.0% of the original model (YOLOv8s). The number of parameters is only 5.7 × 106 M, equivalent to 51.4% of the original model. The computational volume is only 21.1 GFLOPs, representing 74.3% of the original model. Moreover, the mean average precision (mAP@0.5) of the model is 99.492%, which is 0.003% higher than the original model, and the mAP@0.5:0.95 is 0.269% higher than the original model. Compared to other YOLO models, the improved lightweight model not only achieved the highest detection precision but also significantly reduced the number of parameters and model size. This provides a valuable reference for FHB detection in wheat ears and deployment on mobile terminals in field environments.

Anchor bolt corrosion is a complex and dynamic system, and the prediction and identification of its corrosion degree are of significant importance for engineering safety. Currently, non-destructive testing using ultrasonic guided waves can be employed for its detection. Building upon the analysis of anchor bolt corrosion mechanisms, this paper proposes a method for evaluating the corrosion degree of anchor bolts based on multi-scale convolutional neural networks (MS-CNNs) that address the multi-mode propagation and dispersion effects of ultrasonic guided wave signals in non-destructive testing. Electrochemical experiments were conducted to simulate anchor bolt corrosion, and ultrasonic guided wave non-destructive testing was performed every 12 h to obtain waveform data. An MS-CNN was then utilized to accurately diagnose the corrosion degree of the anchor bolts. The test results demonstrate that this method effectively detects and diagnoses the extent of anchor bolt corrosion, facilitating timely troubleshooting and preventing potential safety accidents.

The dynamic recrystallization (DRX) behavior and microstructure evolution of medium-Mn (0.15C–10Mn) steel were investigated through isothermal hot compression tests. The flow stress–strain curves and microstructure analysis, in wide ranges of temperatures (900–1150 °C) and strain rates (10−3 - 1 s−1), were employed to establish constitutive equations and a grain size evolution model. Since the material constants were calculated based on polynomial function of strains, strain compensation was introduced into constitutive analysis. Comparison and verification showed that the constitutive equation had a high predictive ability. The correlation coefficient and average absolute relative error were 0.99 and 4.46%, respectively, which confirm the accuracy and guidance of the model. Metallographic observation was used to implement the grain size evolution analysis of the medium-Mn steel. Microstructure evolution was characterized with a gradual increase in average recrystallized grain size and an obvious expansion in the range of grain size distribution with both deformation temperature and strain rate, which were attributed to the competition between nucleation and grain boundary migration. Besides, a grain size evolution model was established to analyze the microstructure evolution.

Summary: The POGZ gene has been found frequently mutated in neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD) and intellectual disability (ID). We have recently shown that POGZ maintains mouse embryonic stem cells (ESCs). However, the exact mechanisms remain unclear. Here, we show that POGZ plays an important role in the maintenance of ESCs by silencing Dux and endogenous retroviruses (ERVs). POGZ maintains a silent chromatin state at Dux and ERVs by associating with and recruiting TRIM28 and SETDB1, and its loss leads to decreased levels of H3K9me3/H4K20me3, resulting in up-regulation of 2C transcripts and ESC transition to a 2C-like state. POGZ suppresses different classes of ERVs through direct (IAPEy, the intracisternal A-type particle elements) and indirect regulation (MERVL). Activation of POGZ-bound ERVs is associated with up-regulation of nearby neural disease genes such as Serpina3m. Our findings provide important insights into understanding the disease mechanism caused by POGZ dysfunction.

Master Regulator proteins, controlling the transcriptional identity of infected cells, can serve as drug targets for inhibiting virus replication, here demonstrated in a SARSCoV-2 infection model.

Abstract Background The POGZ gene has been found frequently mutated in neurodevelopmental disorders (NDDs), particularly autism spectrum disorder (ASD) and intellectual disability (ID). However, little is known about its roles in embryonic stem cells (ESCs), neural development and diseases. Methods We generated Pogz−/− ESCs and directed ESC differentiation toward a neural fate. We performed biochemistry, ChIP-seq, ATAC-seq, and bioinformatics analyses to understand the role of POGZ. Results We show that POGZ is required for the maintenance of ESC identity and the up-regulation of neural genes during ESC differentiation toward a neural fate. Genome-wide binding analysis shows that POGZ is primarily localized to gene promoter and enhancer regions. POGZ functions as both a transcriptional activator and repressor, and its loss leads to deregulation of differentiation genes, including neural genes. POGZ physically associates with the SWI-SNF (esBAF) chromatin remodeler complex, and together they modulate enhancer activities via epigenetic modifications such as chromatin remodeling and histone modification. During ESC neural induction, POGZ-mediated recruitment of esBAF/BRG1 and H3K27ac are important for proper expression of neural progenitor genes. Limitations The genotype and allele relevant to human neurodevelopmental disorders is heterozygous loss of function. This work is designed to study the effects of loss of POGZ function on ESCs and during ESC neural induction. Also, this work lacks of in vivo validation using animal models. Conclusions The data suggest that POGZ is both a transcription factor and a genome regulator, and its loss leads to defects in neural induction and neurogenesis.

BackgroundSnail family transcriptional repressor 2 (SNAI2) is a transcription factor that induces epithelial to mesenchymal transition in neoplastic epithelial cells. It is closely related to the progression of various malignancies. However, the significance of SNAI2 in human pan-cancer is still largely unknown.MethodsThe Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) databases were taken to examine the SNAI2 expression pattern in tissues and cancer cells. The link between SNAI2 gene expression levels and prognosis, as well as immune cell infiltration, was investigated using the Kaplan-Meier technique and Spearman correlation analysis. We also explored the expression and distribution of SNAI2 in various tumor tissues and cells by the THPA (Human Protein Atlas) database. We further investigated the relationship between SNAI2 expression levels and immunotherapy response in various clinical immunotherapy cohorts. Finally, the immunoblot was used to quantify the SNAI2 expression levels, and the proliferative and invasive ability of pancreatic cancer cells was determined by colony formation and transwell assays.ResultsWe discovered heterogeneity in SNAI2 expression in different tumor tissues and cancer cell lines by exploring public datasets. The genomic alteration of SNAI2 existed in most cancers. Also, SNAI2 exhibits prognosis predictive ability in various cancers. SNAI2 was significantly correlated with immune-activated hallmarks, cancer immune cell infiltrations, and immunoregulators. It’s worth noting that SNAI2 expression is significantly related to the effectiveness of clinical immunotherapy. SNAI2 expression was also found to have a high correlation with the DNA mismatch repair (MMR) genes and DNA methylation in many cancers. Finally, the knockdown of SNAI2 significantly weakened the proliferative and invasive ability of pancreatic cancer cells.ConclusionThese findings suggested that SNAI2 could be used as a biomarker in human pan-cancer to detect immune infiltration and poor prognosis, which provides a new idea for cancer treatment.

Epiretinal membranes (ERMs) are the result of fibro-cellular proliferation that cause distortion and impairment of central vision. We hypothesized that select microRNAs (miRs) regulate retinal fibro-proliferation and ERM formation. Following IRB approval, a pilot study was performed in patients presenting for retina surgery with and without clinical ERMs. Total RNA was isolated from ERM tissue and controls from non-ERM vitreous and subjected to miR profiling via microarray analysis. MiR-494 was identified as the only miR selectively expressed at significantly greater levels, and in silico analysis identified p27 as a putative fibroproliferative gene target of miR-494. In vitro testing of miR-494 and p27 in fibrotic transformation was assessed in spontaneously immortalized human retinal pigment epithelial (RPE) and human Müller cell lines, stimulated to transform into a fibroproliferative state via transforming growth factor beta (TGFβ). Fibroproliferative transformation was characterized by de novo cellular expression of alpha smooth muscle actin (αSMA). In both RPE and Müller cells, both TGFβ and miR-494 mimic decreased p27 expression. In parallel experiments, transfection with p27 siRNA augmented TGFβ-induced αSMA expression, while only in RPE cells did co-transfection with miR-494 inhibitor decrease αSMA levels. These results demonstrate that miR-494 augments fibrotic transformation in both Müller cells and RPEs, however only in RPEs does miR-494 mediate fibrotic transformation via p27. As p27 is known to regulate cellular proliferation and differentiation, future studies should extend clinical testing of miR-494 and/or p27 as a potential novel non-surgical therapy for ERMs, as well as identify relevant miR-494 targets in Müller cells.

Abstract In the past few decades, quantum computation has become increasingly attractive due to its remarkable performance. Quantum image scaling is considered a common geometric transformation in quantum image processing, however, the quantum floating-point data version of which does not exist. Is there a corresponding scaling for 2-D and 3-D floating-point data? The answer is yes. In this paper, we present a quantum scaling up and down scheme for floating-point data by using trilinear interpolation method in 3-D space. This scheme offers better performance (in terms of the precision of floating-point numbers) for realizing the quantum floating-point algorithms than previously classical approaches. The Converter module we proposed can solve the conversion of fixed-point numbers to floating-point numbers of arbitrary size data with $$p+q$$ p + q qubits based on IEEE-754 format, instead of 32-bit single-precision, 64-bit double-precision and 128-bit extended-precision. Usually, we use nearest-neighbor interpolation and bilinear interpolation to achieve quantum image scaling algorithms, which are not applicable in high-dimensional space. This paper proposes trilinear interpolation of floating-point data in 3-D space to achieve quantum algorithms of scaling up and down for 3-D floating-point data. Finally, the quantum scaling circuits of 3-D floating-point data are designed.

Memory impairment remains a leading disability in survivors of global cerebral ischemia, occurring secondary to delayed neurodegeneration of hippocampal cornu ammonis-1 (CA1) neurons. MicroRNA-200c (miR-200c) is induced following ischemic stress and we have previously demonstrated that pre-treatment with anti-miR-200c is protective against embolic stroke in mice. In the present study we assessed the role of miR-200c on CA1 neurodegeneration, sirtuin-1 (SIRT1), and mitochondrial dynamic protein expression in a mouse model of transient global cerebral ischemia and in vitro in primary mouse astrocyte cultures after simulated ischemia. Mice were subjected to 10 min bilateral common carotid artery occlusion plus hypotension with 5% isoflurane. After 2 h recovery mice were treated with intravenous injection of either anti-miR-200c or mismatch control. Memory function was assessed by Barnes maze at post-injury days 3 and 7. Mice were sacrificed at post-injury day 7 for assessment of brain cell-type specific expression of miR-200c, SIRT1, and the mitochondrial fusion proteins mitofusin-2 (MFN2) and OPA1 via complexed fluorescent in situ hybridization and fluorescent immunohistochemistry. Global cerebral ischemia induced significant loss of CA1 neurons, impaired memory performance and decreased expression of CA1 SIRT1, MFN2, and OPA1. Post-injury treatment with anti-miR-200c significantly improved survival, prevented CA1 neuronal loss, improved post-injury performance in Barnes maze, and was associated with increased post-injury expression of CA1 SIRT1 and MFN2 in astrocytes. In vitro, primary mouse astrocyte cultures pre-treated with miR-200c inhibitor prior to oxygen/glucose deprivation preserved expression of SIRT1 and MFN2, and decreased reactive oxygen species generation, whereas pre-treatment with miR-200c mimic had opposite effects that could be reversed by co-treatment with SIRT1 activator. These results suggest that miR-200c regulates astrocyte mitochondrial homeostasis via targeting SIRT1, and that CA1 astrocyte mitochondria and SIRT1 represent potential post-injury therapeutic targets to preserve cognitive function in survivors of global cerebral ischemia.

Health concerns and financial losses caused by mushroom poisoning have been reported worldwide. Amanita citrinoannulata, a poisonous mushroom commonly found in China, results in a toxic reaction in humans after mistaken ingestion. To reduce the mistaken ingestion of poisonous mushrooms and to improve clinical diagnosis of mushroom poisoning, a rapid mushroom species identification method is required. Such identification methods could be advantageous in the identification of other poisonous mushroom species. This study developed two rapid and sensitive methods for the detection of A. citrinoannulata utilizing colorimetric and real-time loop-mediated isothermal amplification (LAMP) technology and specifically designed primers for the internal transcribed spacer (ITS) genes of A. citrinoannulata. The methods demonstrated high sensitivity as 0.2 ng of A. citrinoannulata DNA could be detected, with no cross-reaction with 41 non-target mushroom species. The entire detection process could be completed within 40 min without requiring complex instruments and can be observed by the naked eye. Therefore, these novel methods can be used for the identification of fresh and cooked mushroom samples and vomit samples, which contain only 1% A. citrinoannulata. Furthermore, these methods facilitate the detection of mushroom poisoning, and thus, have potential to reduce the number of mushroom poisoning-related deaths worldwide.

Utilizing image data for yield estimation is a key topic in modern agriculture. This paper addresses the difficulty of counting wheat spikelets using images, to improve yield estimation in wheat fields. A wheat spikelet image dataset was constructed with images obtained by a smartphone, including wheat ears in the flowering, filling, and mature stages of reproduction. Furthermore, a modified lightweight object detection method, YOLOv5s-T, was incorporated. The experimental results show that the coefficient of determination (R2) between the predicted and true values of wheat spikelets was 0.97 for the flowering stage, 0.85 for the grain filling stage, and 0.78 for the mature stage. The R2 in all three fertility stages was 0.87, and the root mean square error (RMSE) was 0.70. Compared with the original YOLOv5s algorithm, the spikelet detection counting effect of YOLOv5s-T was not reduced. Meanwhile, the model size was reduced by 36.8% (only 9.1 M), the GPU memory usage during the training process was reduced by 0.82 GB, the inference time was reduced by 2.3 ms, the processing time was reduced by 10 ms, and the calculation amount was also reduced. The proposed YOLOv5s-T algorithm significantly reduces the model size and hardware resource requirements while guaranteeing high detection and counting accuracy, which indicates the potential for wheat spikelet counting in highly responsive wheat yield estimation.

ADNP has been connected to neural developmental disorders. Here, the authors uncover a role for ADNP in neural induction and differentiation via β-Catenin stabilization, with ADNP disruption in zebrafish leading to defective neurogenesis and decreased Wnt signaling.

Aiming at the problems that the speed balance overshoot is large, the adjustment time is long, and the speed balance effect is poor during the walking process of a wheeled robot, a four-wheel differential motion model of a wheeled robot is established with Matlab/Simulink and Carsim simulation software, and for the brushless direct current motor system(BLDCM) system, based on the original fuzzy PID, combining with the anti-integration saturation algorithm and the variable speed integral algorithm, an speed regulation method based on improved fuzzy PID is proposed. The simulation results show that compared with the traditional fuzzy PID controller, the fuzzy PID controller improved by the anti-integral saturation and variable speed integration algorithm reduces the overshoot by 30% and the adjustment time by 33%. The response time is short and the speed response curve has small fluctuations. The wheeled robot experimental verification platform is built. The experimental results show that the speed regulation method based on improved fuzzy PID has fast speed response and meets the requirements of wheeled robot speed control. The proposed design may provide some theoretical reference for speed stable system debugging of wheeled detection robot, and can be used in control systems with speed control as main purpose.

Abstract Atmospheric turbulence and the planetary boundary layer (PBL) can significantly modulate the fine particulate matter (PM2.5) concentration near the ground surface. However, the mechanism by which they affect the variation in PM2.5 is poorly understood. Using surface‐based meteorological and PM2.5 observations, turbulence measurements, and high‐resolution soundings, this study analyzed the properties of turbulence and PBL stratification during a severe regional pollution transport event in Xiangyang, a city in the middle reaches of the Yangtze River, from January 3 to January 9, 2019. During the growth stage, PM2.5 was observed to increase continuously under a northerly wind of 2–4 m s−1 that brought a polluted air mass to central China. During the entire pollution event, the turbulent kinetic energy and sensible heat flux tended to be lower at high PM2.5 concentrations. This correlation varied greatly depending on the stage of the event. A negative correlation existed in the initial and maintenance stages, whereas the relationship was positive during the growth stage, when regional transport dominated the variation in PM2.5. There was no obvious inversion layer below 500 m during the entire pollution episode, and a weak inversion layer appeared at higher altitudes in the initial and maintenance stages. Vertically homogeneous northerly winds favored the transboundary transport of pollutants, causing a significant increase in ground‐level PM2.5 concentration. By contrast, the presence of wind shear in the prevailing northerly winds suppressed pollutant transport to the ground, resulting in a low‐value gap in PM2.5 concentration between high altitudes and the ground surface.

The influence of the underlying surface on the atmospheric environment over rivers and lakes is not fully understood. To improve our understanding, this study targeted the Twain-Hu Basin (THB) in central China, with a unique underlying surface comprising a dense “water network” over rivers and lakes. In this study, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) was used to simulate the impact of this dense “water network” on a wintertime heavy PM2.5 pollution event in the THB. On this basis, the regulating effects of density and area of the lake groups, with centralized big lakes (CBLs) and discrete small lakes (DSLs), on PM2.5 concentrations over the underlying surface of the dense “water network” in the THB were clarified, and the relative contributions of thermal factors and water vapor factors in the atmospheric boundary layer to the variation of PM2.5 concentrations were evaluated. The results show that the underlying surface of dense “water networks” in the THB generally decreases the PM2.5 concentrations, but the influences of different lake-group types are not uniform in spatial distribution. The CBLs can reduce the PM2.5 concentrations over the lake and its surroundings by 4.90–17.68% during the day and night. The ability of DSLs in reducing PM2.5 pollution is relatively weak, with the reversed contribution between −5.63% and 1.56%. Thermal factors and water vapor–related factors are the key meteorological drivers affecting the variation of PM2.5 concentrations over the underlying surface of dense “water networks”. The warming and humidification effects of such underlying surfaces contribute positively and negatively to the “purification” of air pollution, respectively. The relative contributions of thermal factors and water vapor–related factors are 52.48% and 43.91% for CBLs and 65.96% and 27.31% for DSLs, respectively. The “purification” effect of the underlying surface with a dense “water network” in the THB on regional air pollution highlights the importance of environmental protection of inland rivers and lakes in regional environmental governance. In further studies on the atmospheric environment, long-term studies are necessary, including fine measurements in terms of meteorology and the environment and more comprehensive simulations under different scenarios.

In order to improve the flight quality of UAV, study the hardware-in-the-loop simulation application of UAV control, and form a set of universal UAV flight control law design and hardware-in-the-loop simulation method, the Z-shaped aircraft with complex aerodynamic characteristics is studied. The Z-shaped aircraft can be folded in the direction of the fuselage for easy storage and transportation. According to the shape parameters of Z-shaped aircraft, the aerodynamic data are obtained. On this basis, the longitudinal linear model is established by using the principle of small disturbance linearization. The longitudinal static stability of the model is studied by adding disturbance pulses. The transfer function of each link is selected, the pitch control loop is established, the PID parameters are adjusted, the longitudinal control law is designed, and simulation is conducted by using Simulink and hardware-in-the-loop simulator. The simulation results show that UAV has good static stability, reasonable selection of PID control parameters, small system overshoot and short adjustment time, which can improve the flight quality of UAV. Hardware-in-the-loop simulation can more truly and intuitively reflect the advantages of UAV attitude. The modeling and simulation methods have certain universality and can be applied to other fixed-wing UAVs.

To improve the accuracy of terrain classification during mobile robot operation, an adaptive online terrain classification method based on vibration signals is proposed. First, the time domain and the combined features of the time, frequency, and time–frequency domains in the original vibration signal are extracted. These are adopted as the input of the random forest algorithm to generate classification models with different dimensions. Then, by judging the relationship between the current speed of the mobile robot and its critical speed, the classification model of different dimensions is adaptively selected for online classification. Offline and online experiments are conducted for four different terrains. The experimental results show that the proposed method can effectively avoid the self-vibration interference caused by an increase in the robot’s moving speed and achieve higher terrain classification accuracy.

The impact of structural variations in the atmospheric boundary layer (ABL) during the regional transport of air pollutants on its local pollution changes deserves attention. Based on multi-source ABL detection and numerical simulation of air pollutants over the Twain-Hu Basin (THB) during 4–6 January 2019, the mechanism of the rapid growth of atmospheric pollutant concentrations in Xianning by the synergistic effect of regional transport and ABL evolution is explored, and the main conclusions are obtained as follows. The vertically stratified atmosphere is noticeable at nighttime, and the heavy humidity of near-surface fog within the stable boundary layer (SBL) promoted the generation and cumulative growth of secondary PM2.5 components during the pollution formation stage. The horizontal transport characteristics of atmospheric pollutant concentration peak were observed in the residual layer (RL) of 500–600 m. At the pollution maintenance stage, the convective boundary layer (CBL) developed during the daytime, and northerly wind transported high-concentration pollutants from the north to the THB. Under the combined action of horizontal transport and turbulent mixing, the high-concentration atmospheric pollutants in the mixing layer (ML) from the ground to the 500 m height were mixed uniformly and maintained accumulation growth. The next day, the strong vertical turbulent mixing caused the downward transport of high-concentration pollutants in the RL during nighttime due to the development of the CBL again, resulting in a doubling of near-surface pollutant concentration in a short time. With the development of ABL turbulence, local pollution dissipated rapidly without the continuous input of pollutants from external regions. This study emphasizes the importance of multi-scale processes impact on pollution variation, that is, regional transport of atmospheric pollutants at the CBL development stage for the rapid growth of PM2.5 concentration in the ML.

Feedforward neural network (FNN) is an information processing system that simulates human brain function to a certain extent by referring to the structure of a biological neural network and the working mechanism of biological neurons. As the most important part, the architecture of FNN essentially influences its application performance. This paper proposed a structure self-adaptive algorithm for FNN (SSAFNN) based on biological mechanism. First, self-adaptive neuron growing and pruning indexes are proposed based on the idea of biological neuron grow factor and neuron competition, respectively. The FNN structure is dynamically adjusted according to the growing and pruning indexes of hidden neurons. Second, the connect weights of FNN are automatically adjusted during the self-organizing process and trained by gradient descent method during the learning process. Third, the theoretical analysis is given that this proposed algorithm not only optimized the network structure but also ensured the convergence and performance of FNN. The proposed SSAFNN is tested on the benchmark problems in the field of classification and prediction and is applied in the engineering problems of anchor bolt non-destructive testing and wastewater effluent ammonia nitrogen predicting. The experiment results reveal the good performance and potentiality of SSAFNN in industrial applications.

Vertical wind shear (VWS) significantly impacts the vertical mixing of air pollutants and leads to changes in near-surface air pollutants. We focused on Changsha (CS) and Jingmen (JM), the upstream and downstream urban sites of a receptor region in central China, to explore the impact of VWS on surface PM2.5 changes using 5-year wintertime observations and simulations from 2016–2020. The surface PM2.5 concentration was lower in CS with higher anthropogenic PM2.5 emissions than in JM, and the correlation between wind speed and PM2.5 was negative for clean conditions and positive for polluted conditions in both two sites. The difference in the correlation pattern of surface PM2.5 and VWS between CS and JM might be due to the different influences of regional PM2.5 transport and boundary layer dynamics. In downstream CS, the weak wind and VWS in the height of 1–2 km stabilized the ABL under polluted conditions, and strong northerly wind accompanied by enhanced VWS above 2 km favored the long-range transport of air pollutants. In upstream JM, local circulation and long-range PM2.5 transport co-determined the positive correlation between VWS and PM2.5 concentrations. Prevailed northerly wind disrupted the local circulation and enhanced the surface PM2.5 concentrations under polluted conditions, which tend to be an indicator of regional transport of air pollutants. The potential contribution source maps calculated from WRF-FLEXPART simulations also confirmed the more significant contribution of regional PM2.5 transport to the PM2.5 pollution in upstream region JM. By comparing the vertical profiles of meteorological parameters for typical transport- and local-type pollution days, the northerly wind prevailed throughout the ABL with stronger wind speed and VWS in transport-type pollution days, favoring the vertical mixing of transported air pollutants, in sharp contrast to the weak wind conditions in local-type pollution days. This study provided the evidence that PM2.5 pollution in the Twain-Hu Basin was affected by long-distance transport with different features at upstream and downstream sites, improving the understanding of the air pollutant source–receptor relationship in air quality changes with regional transport of air pollutants.

Metabolic syndrome is a chronic metabolic disorder that has turned into a severe health problem worldwide. A previous study reported that large yellow tea exhibited better anti-diabetic and lipid-lowering effects than green tea. Nevertheless, the potential mechanisms are not yet understood. In this study, we examined the prevention effects and mechanisms of large yellow tea water extract (LWE) on metabolic syndrome using leptin receptor knockout (Lepr−/−) rats. Seven-week-old male Lepr−/− and wild type (WT) littermate rats were divided into Lepr−/− control group (KO) (n = 5), Lepr−/− with LWE-treated group (KL) (n = 5), WT control group (WT) (n = 6), and WT with LWE intervention group (WL) (n = 6). Then, the rats were administered water or LWE (700 mg/kg BW) daily by oral gavage for 24 weeks, respectively. The results showed that the administration of LWE significantly reduced the serum concentrations of random blood glucose, total cholesterol, triglyceride, and free fatty acids, and increased glucose tolerance in Lepr−/− rats. Moreover, LWE remarkably reduced hepatic lipid accumulation and alleviated fatty liver formation in Lepr−/− rats. A mechanistic study showed that LWE obviously activated SIRT6 and decreased the expression of key lipogenesis-related molecules SREBP1, FAS, and DGAT1 in the livers of Lepr−/− rats. Furthermore, LWE significantly improved microbiota dysbiosis via an increase in gut microbiota diversity and an abundance of the microbiota that produce short chain fatty acids (SCFAs), such as Ruminococcaceae, Faecalibaculum, Intestinimonas, and Alistipes. Finally, LWE supplementation increased the concentrations of SCFAs in the feces of Lepr−/− rats. These results revealed that LWE attenuated metabolic syndrome of Lepr−/− rats via the reduction of hepatic lipid synthesis through the SIRT6/SREBP1 pathway and the modulation of gut microbiota.

Abstract The variation and interplay of westerlies and the Asian summer monsoon (ASM) are important for understanding climate change in the Northern Hemisphere. Yet their spatial and temporal evolution is still debatable. Here, we present a stable isotopic record from the center of the Badain Jaran Desert, in Northwestern China, which records the variations and interplay of the two climate systems during the past 1200 ka. The results indicate that the westerlies dominated the Badain Jaran area at least from 1200 to 600 ka, and possibly earlier. Associated with ASM enhancement since 600 ka, the westerlies and ASM alternatively dominated the regional warm season precipitation during glacial‐interglacial cycles, respectively. Meanwhile, the δ18Ocarb of the Badain Jaran area showed high‐frequency fluctuations which may reveal the joint impact of ASM and westerlies on regional hydrology after 450 ka. Affected by the westerlies and ASM changes, the C4 plants stepwise expanded at 600, 450, and 300 ka. These stepwise variations of westerlies and ASM are response to the global climate change which significantly influenced the ASM at 600 and 450 ka, and westerlies at 300 ka, respectively. In addition, the uplift of the Pamir‐Tibetan Plateau during the middle Pleistocene also exerts a profound effect on westerlies and ASM pattern across the East Asia on a long‐term time scale.

ADNP (Activity Dependent Neuroprotective Protein) is proposed as a neuroprotective protein whose aberrant expression has been frequently linked to rare neural developmental disorders and cancers, including the recently described neurodevelopmental Helsmoortel-Van der Aa syndrome. Recent studies have suggested that ADNP functions as an important chromatin regulator. However, how ADNP-regulated chromatin mechanisms control gene expression and stem cell fate commitment remains unclear. Here we show that ADNP interacts with two chromatin remodelers, BRG1 and CHD4. ADNP is required for proper establishment of chromatin accessibility, nucleosome configuration, and bivalent histone modifications of developmental genes. Loss of ADNP leads to enhancer over-activation and increased ratio of H3K4me3/H3K27me3 at key primitive endoderm (PrE) gene promoters, resulting in prominent up-regulation of these genes and priming ES cell differentiation toward endodermal cell types. Thus, our work revealed a key role of ADNP in the establishment of local chromatin landscape and structure of developmental genes by association with BRG1 and CHD4. These findings provide further insights into the role of ADNP in the pathology of the Helsmoortel-Van der Aa syndrome.

Microseismic source location is the essential factor in microseismic monitoring technology, and its location precision has a large impact on the performance of the technique. Here, we discuss the problem of low-precision location identification for microseismic events in a mine, as may be obtained using conventional location methods that are based on arrival time. In this paper, microseismic location characteristics in mining are analyzed according to the characteristics of the mine’s microseismic wavefield. We review research progress in mine-related microseismic source location methods in recent years, including the combination of the Geiger method with the linear method, combined microseismic event location method, optimization of relative location method, location method without pre-measured velocity, and location method without arrival time picking. The advantages and disadvantages of these methods are discussed, along with their feasible conditions. The influences of geophone distribution, first arrival time picking, and the velocity model on microseismic source location are analyzed, and measures are proposed to influence these factors. Approaches to solve the problem under study include adopting information fusion, combining and optimizing existing methods, and creating new methods to realize high-precision microseismic source location. Optimization of the velocity structure, along with applications of the time-reversal imaging technique, passive time-reversal mirror, and relative interferometric imaging, are expected to greatly improve microseismic location precision in mines. This paper also discusses the potential application of information fusion and deep learning methods in microseismic source location in mines. These new and innovative location methods for microseismic source location have extensive prospects for development. Keywords: Microseismic source location, Influencing factors, Time-reversal imaging, Research progress, Prospects for development

Atypical habituation to repetitive information has been commonly reported in Autism Spectrum Disorder (ASD) but it is not yet clear whether similar abnormalities are present in Neurofibromatosis Type 1 (NF1). We employed a cross-syndrome design using a novel eye tracking paradigm to measure habituation in preschoolers with NF1, children with idiopathic ASD and typically developing (TD) children. Eye movements were recorded to examine fixation duration to simultaneously presented repeating and novel stimuli. Children with NF1 showed a bias for longer look durations to repeating stimuli at the expense of novel stimuli, and slower habituation in NF1 was associated with elevated ASD traits. These findings could indicate aberrant modulation of bottom-up attentional networks that interact with the emergence of ASD phenotypes.

Tissue-resident memory T cells (TRMs) in mice mediate optimal protective immunity to infection and vaccination, while in humans, the existence and properties of TRMs remain unclear. Here, we use a unique human tissue resource to determine whether human tissue memory T cells constitute a distinct subset in diverse mucosal and lymphoid tissues. We identify a core transcriptional profile within the CD69+ subset of memory CD4+ and CD8+ T cells in lung and spleen that is distinct from that of CD69− TEM cells in tissues and circulation and defines human TRMs based on homology to the transcriptional profile of mouse CD8+ TRMs. Human TRMs in diverse sites exhibit increased expression of adhesion and inhibitory molecules, produce both pro-inflammatory and regulatory cytokines, and have reduced turnover compared with circulating TEM, suggesting unique adaptations for in situ immunity. Together, our results provide a unifying signature for human TRM and a blueprint for designing tissue-targeted immunotherapies.

In the present study, we assessed efficacy of exosomes harvested from human and mouse stem cell cultures in protection of mouse primary astrocyte and neuronal cell cultures following in vitro ischemia, and against ischemic stroke in vivo. Cell media was collected from primary mouse neural stem cell (NSC) cultures or from human induced pluripotent stem cell-derived cardiomyocyte (iCM) cultures. Exosomes were extracted and purified by polyethylene glycol complexing and centrifugation, and exosome size and concentration were determined with a NanoSiteTM particle analyzer. Exosomes were applied to primary mouse cortical astrocyte or neuronal cultures prior to, and/or during, combined oxygen-glucose deprivation (OGD) injury. Cell death was assessed via lactate dehydrogenase (LHD) and propidium iodide staining 24 h after injury. NSC-derived exosomes afforded marked protection to astrocytes following OGD. A more modest (but significant) level of protection was observed with human iCM-derived exosomes applied to astrocytes, and with NSC-derived exosomes applied to primary neuronal cultures. In subsequent experiments, NSC-derived exosomes were injected intravenously into adult male mice 2 h after transient (1 h) middle cerebral artery occlusion (MCAO). Gross motor function was assessed 1 day after reperfusion and infarct volume was assessed 4 days after reperfusion. Mice treated post-stroke with intravenous NSC-derived exosomes exhibited significantly reduced infarct volumes. Together, these results suggest that exosomes isolated from mouse NSCs provide neuroprotection against experimental stroke possibly via preservation of astrocyte function. Intravenous NSC-derived exosome treatment may therefore provide a novel clinical adjuvant for stroke in the immediate post-injury period.

The underlying mechanisms of isoflurane neurotoxicity in the developing brain remain unclear. Ferroptosis is a recently characterized form of programmed cell death distinct from apoptosis or autophagy, characterized by iron-dependent reactive oxygen species (ROS) generation secondary to failure of glutathione-dependent antioxidant defenses. The results of the present study are the first to demonstrate in vitro that ferroptosis is a central mechanism contributing to isoflurane neurotoxicity. We observed in embryonic mouse primary cortical neuronal cultures (day-in-vitro 7) that 6 h of 2% isoflurane exposure was associated with decreased transcription and protein expression of the lipid repair enzyme glutathione peroxidase 4. In parallel, isoflurane exposure resulted in increased ROS generation, disruption in mitochondrial membrane potential, and cell death. These effects were significantly attenuated by pre-treatment with the selective ferroptosis inhibitor ferrostatin-1 (Fer-1). Collectively, these observations provide a novel mechanism for isoflurane-induced injury in the developing brain and suggest that pre-treatment with Fer-1 may be a potential clinical intervention for neuroprotection.

The chemical composition dataset of Aerosol Reanalysis of NASA’s Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRAero) has not been thoroughly evaluated with observation data in mainland China due to the lack of long-term chemical components data. Using the 5-year data of PM10 mass concentrations and chemical compositions obtained from the routine sampling measurements at the World Meteorological Organization the Global Atmosphere Watch Programme regional background stations, Jing Sha (JS) and Lin’An (LA), in central and eastern China, we comprehensively evaluate the surface PM10 concentrations and chemical compositions such as sulfate (SO42−), organic carbon (OC) and black carbon (BC) derived from MERRAero. Overall, the concentrations of PM10, SO42−, OC and BC from the MERRAero agreed well with the measurements, despite a slight and consistent overestimation of BC concentrations and a moderate and persistent underestimation of PM10 concentrations throughout the study period. The MERRAero reanalysis of aerosol compositions performs better during the summertime than wintertime. By considering the nitrate particles in PM10 reconstruction, MERRAero performance can be significantly improved. The unreasonable seasonal variations of PM10 chemical compositions at station LA by MERRAero could be causative factors for the larger MERRAero discrepancies during 2016–2017 than the period of 2011–2013.

Insulin regulates an essential conserved signaling pathway affecting growth, proliferation, and metabolism. To expand our understanding of the insulin pathway, we combine biochemical, genetic, and computational approaches to build a comprehensive Drosophila InR/PI3K/Akt network. First, we map the dynamic protein-protein interaction network surrounding the insulin core pathway using bait-prey interactions connecting 566 proteins. Combining RNAi screening and phospho-specific antibodies, we find that 47% of interacting proteins affect pathway activity, and, using quantitative phosphoproteomics, we demonstrate that ∼10% of interacting proteins are regulated by insulin stimulation at the level of phosphorylation. Next, we integrate these orthogonal datasets to characterize the structure and dynamics of the insulin network at the level of protein complexes and validate our method by identifying regulatory roles for the Protein Phosphatase 2A (PP2A) and Reptin-Pontin chromatin-remodeling complexes as negative and positive regulators of ribosome biogenesis, respectively. Altogether, our study represents a comprehensive resource for the study of the evolutionary conserved insulin network.

The tail-sitter Vertical Takeoff and Landing (VTOL) Unmanned Aerial Vehicle(UAV), flying in a fixed-wing model, overcomes many shortcomings of traditional fixed-wing UAVs, and inherits the advantage of high overall efficiency, which means it has great development potential and very broad application prospects. The attitude of tail-sitter VTOL UAV shows a wide change range in its takeoff and landing stages, and when the attitude sensor changes more than 90 degrees in pitch direction, the Euler angles converted by the Quaternions will have singular points, which means gimbal deadlock appears. From the solution algorithm, this paper provides a method of changing the order of rotation to avoid the appearance of singular points. The results show that this method can be well applied to the attitude solution of the VTOL UAV.

The Twain-Hu basin (THB), covering the lower plain of Hubei and Hunan provinces in Central China, has experienced severe air pollution in recent years. However, the terrain effects of such sub-basin on air quality over the THB have been incomprehensibly understood. A heavy PM2.5 pollution event occurred over the THB during 4–10 January 2019. By using the observations and WRF-Chem simulations, we investigated the underlying mechanisms of sub-basin effects on the air pollution with several sensitivity experiments. Observationally, air pollution in the western THB urban area with an average PM2.5 concentration of 189.8 μg m−3, which was more serious than the eastern urban area with the average PM2.5 concentration of 106.3 μg m−3, reflecting a different influence of topography on air pollution over the THB. Simulation results revealed that the terrain effect can contribute 12.0% to increasing the PM2.5 concentrations in the western THB, but slightly mitigate the pollution extent in the eastern THB with the contribution of −4.6% to PM2.5 during the heavy pollution episode. In particular, the sub-basin terrain was conducive to the accumulation of PM2.5 by regional transport with the contribution of 39.1 %, and contrarily lowered its local pollution by −57.0% via the enhanced atmospheric boundary layer height and ventilation coefficients. Given a heavy air pollution episode occurring over the THB, such inverse contribution of terrain effects reflected a unique importance of sub-basin topography in regional transport of air pollutants for air pollution in central China.

Fine particulate matters (PM2.5) and relative humidity (RH) in the ambient atmosphere are the leading anthropogenic and natural factors changing atmospheric horizontal visibility. Based on the analysis of environmental and meteorological data observed over 2013–2019 in Nanjing, an urban area in East China, this study investigated the influences of PM2.5 and RH on atmospheric visibility changes over recent years. The visibility had significantly negative correlations with the PM2.5 concentrations and RH changes. The nonlinear relationships existed between PM2.5 concentrations and visibility, as well as between RH and visibility, with the inflection points in the atmospheric visibility changes. The PM2.5 inflection concentrations were 81.0 μg m−3, 76.0 μg m−3, 49.0 μg m−3, and 33.0 μg m−3, respectively, for the RH ranges of RH < 60%, 60% ≤ RH < 80%, 80% ≤ RH < 90%, and RH ≥ 90%, indicating that the improvement of visibility with reducing PM2.5 concentrations could be more difficult under the humid meteorological condition. The visibility changes were most sensitive to PM2.5 concentrations in the RH range of 60–80% in this urban area of East China. The relative contributions of natural factor RH and anthropogenic factor PM2.5 to variations of wintertime atmospheric visibility were quantified with 54.3% and 45.7%, respectively, revealing an important role of natural factor RH in the change of atmospheric visibility in the urban area of East Asian monsoon region.

MAX giant associated protein (MGA) is a dual transcriptional factor containing both T-box and bHLHzip DNA binding domains. In vitro studies have shown that MGA functions as a transcriptional repressor or activator to regulate transcription of promotors containing either E-box or T-box binding sites. BS69 (ZMYND11), a multidomain-containing (i.e., PHD, BROMO, PWWP, and MYND) protein, has been shown to selectively recognizes histone variant H3.3 lysine 36 trimethylation (H3.3K36me3), modulates RNA Polymerase II elongation, and functions as RNA splicing regulator. Mutations in MGA or BS69 have been linked to multiple cancers or neural developmental disorders. Here, by TALEN and CRISPR/Cas9-mediated loss of gene function assays, we show that zebrafish Mga and Bs69 are required to maintain proper Bmp signaling during early embryogenesis. We found that Mga protein localized in the cytoplasm modulates Bmpr1a activity by physical association with Zmynd11/Bs69. The Mynd domain of Bs69 specifically binds the kinase domain of Bmpr1a and interferes with its phosphorylation and activation of Smad1/5/8. Mga acts to antagonize Bs69 and facilitate the Bmp signaling pathway by disrupting the Bs69–Bmpr1a association. Functionally, Bmp signaling under control of Mga and Bs69 is required for properly specifying the ventral tailfin cell fate.

An online video edge detection device for bottle caps is designed and implemented using OV7670 video module and FPGA based control unit. By Verilog language programming, the device realizes the menu type parametric setting of the external VGA display, and completes the Roberts edge detection of real-time video image, which improves the speed of image processing. By improving the detection algorithm, the noise is effectively suppressed, and clear and coherent edge images are derived. The design improves the working environment, and avoids the harm to human body.

Background/Aims: Age-related macular degeneration (AMD) appears to be a disease with increasing incidence in Western countries and may develop into acquired blindness. Choroidal neovascularization (CNV) is the most frequent cause for AMD, and is commonly induced by regional inflammation. Past studies have highlighted vascular endothelial growth factor A (VEGF-A) as a major trigger for CNV. However, studies on the associated angiogenic factors other than VEGF-A are lacking. Methods: Here, we used a well-established laser burn (LB)-induced experimental CNV mouse model to study the molecular mechanisms underlying the development of CNV after ocular injury. We analyzed vessel density by lectin labeling. We isolated macrophages, endothelial cells and other cell types by flow cytometry, and analyzed levels of different angiogenic factors in these populations. We used antisera against VEGF-A (aVEGF) and/or antisera against placental growth factor (PLGF; aPLGF) to antagonize CNV. We used an antibody-driven toxin to selectively eliminate macrophages to evaluate the role of macrophages in CNV. We also examined expression of PLGF in macrophage subtypes. Results: The choroidal vessel density increased significantly 7 days after LB. LB increased significantly the levels of VEGF-A and PLGF in mouse eyes. Treatment with aVEGF significantly blunted increases in vessel density by LB. Treatment with aPLGF alone did not significantly reduce increases in vessel density. However, aPLGF significantly increased the inhibitory effects of aVEGF on vessel density increases. While VEGF-A was produced by endothelial cells, macrophages and other types at similar levels, PLGF seemed to be predominantly produced by macrophages. Selective macrophage depletion significantly reduced CNV. M2, but M1 macrophages produced high levels of PLGF. Conclusions: Together, our data suggest a previously unappreciated role of PLGF in coordination with VEGF-A to regulate CNV during ocular injury. Our study highlights macrophages and their production of PLGF as novel targets for CNV therapy.

MicroRNAs (miRNA) are short (~22 nt) single stranded RNAs that downregulate gene expression. Although recent studies indicate extensive miRNA changes in response to ischemic brain injury, there is currently little information on the roles of specific miRNAs in this setting. Heat shock proteins (HSP) of the HSP70 family have been extensively studied for their multiple roles in cellular protection, but there is little information on their regulation by miRNAs. We used bioinformatics to identify miR-181 as a possible regulator of several HSP70 family members. We validated GRP78/BIP as a target by dual luciferase assay. In response to stroke in the mouse we find that miR-181 increases in the core, where cells die, but decreases in the penumbra, where cells survive. Increased levels of miR-181a are associated with decreased GRP78 protein levels, but increased levels of mRNA, implicating translational arrest. We manipulated levels of miR-181a using plasmid overexpression of pri-miR-181ab or mimic to increase, and antagomir or inhibitor to reduce levels. Increased miR-181a exacerbated injury both in vitro and in the mouse stroke model. Conversely, reduced levels were associated with reduced injury and increased GRP78 protein levels. Studies in C6 cells show that if GRP78 levels are maintained miR-181a no longer exerts a toxic effect. These data demonstrate that miR-181 levels change in response to stroke and inversely correlate with levels of GRP78. Importantly, reducing or blocking miR-181a protects the brain from stroke.

Overexpression of the inducible heat shock protein 70, Hsp72, has broadly cytoprotective effects and improves outcome following stroke. A full understanding of how Hsp72 protects cells against injury is elusive, though several distinct mechanisms are implicated. One mechanism is its anti-inflammatory effects. We study the effects of Hsp72 overexpression on activation of the transcription factor NF-κB in microglia combining experimentation and mathematical modeling, using TNFα to stimulate a microglial cell line stably overexpressing Hsp72. We find that Hsp72 overexpression reduces the amount of NF-κB DNA binding activity, activity of the upstream kinase IKK, and amount of IκBα inhibitor phosphorylated following TNFα application. Simulations evaluating several proposed mechanisms suggest that inhibition of IKK activation is an essential component of its regulatory activities. Unexpectedly we find that Hsp72 overexpression reduces the initial amount of the RelA/p65 NF-κB subunit in cells, contributing to the attenuated response. Neither mechanism in isolation, however, is sufficient to attenuate the response, providing evidence that Hsp72 relies upon multiple mechanisms to attenuate NF-κB activation. An additional observation from our study is that the induced expression of IκBα is altered significantly in Hsp72 expressing cells. While the mechanism responsible for this observation is not known, it points to yet another means by which Hsp72 may alter the NF-κB response. This study illustrates the multi-faceted nature of Hsp72 regulation of NF-κB activation in microglia and offers further clues to a novel mechanism by which Hsp72 may protect cells against injury.

Reactive gliosis is a hallmark of brain pathology and the injury response, yet the extent to which astrocytes proliferate, and whether this is central to astrogliosis is still controversial. We determined the fraction of mature astrocytes that proliferate in a mouse stroke model using unbiased stereology as a function of distance from the infarct edge. Cumulatively 11.1±1.2% of Aldh1l1(+) astrocytes within 400 µm in the cortical penumbra incorporate BrdU in the first week following stroke, while the overall number of astrocytes does not change. The number of astrocytes proliferating fell sharply with distance with more than half of all proliferating astrocytes found within 100 µm of the edge of the infarct. Despite extensive cell proliferation primarily of microglia and neutrophils/monocytes in the week following stroke, few mature astrocytes re-enter cell cycle, and these are concentrated close to the infarct boundary.

Due to the unbalanced emission reductions in ozone precursors in recent years, ozone trends and the causes of their variations in eastern China remain insufficiently understood. To explore the factors controlling ozone trends in eastern China, the long-term ozone precursors observation experiment was conducted. Combined with the satellite and surface measurements, the trend of low, typical and peak ozone concentrations in eastern China was evaluated in detail. Observation results show that the surface peak ozone concentrations significantly decreased (-0.5% per year) while low ozone concentrations increased (0.3% per year) in eastern China during May-September 2017-2022. The underlying cause of surface low and peak ozone trends in eastern China is anthropogenic emission. Ozone formation sensitivity is in VOC-limited regime or transition regime during periods (8:00-11:00) of sharp increases in ozone concentrations, and it is usually in NOx-limited regime when the ozone concentration reaches its peak (~14:00). Substantial reductions in nitrogen oxides (NOx) emissions have diametrically opposed effects on peak (decreasing) and low (increasing) ozone concentrations, and reducing volatile organic compounds (VOCs) concentrations is the key to reversing the current high ozone level situation in eastern China. In addition, there are obvious interannual variations of surface O3 formation sensitivity on spatial scales through long-term satellite observations, in which area proportion of VOC-limited regime is decreasing while the area proportion of NOx-limited regime is increasing. Our results highlight the positive impacts of NOx reduction in controlling peak O3 levels, and regular changes in the ozone formation sensitivity throughout the day should be taken into account when formulating ozone control policies. [ABSTRACT FROM AUTHOR]