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Abstract By analyzing the influence of stochastic perturbation matters on vehicle path optimization, a perturbation scheduling model for logistics and distribution with a carbon tax mechanism is established under the premise of time window variation and load capacity constraints. Herein, we propose an enhanced Genetic Algorithm (GA) based on a Gaussian matrix mutation (GMM) operator, which maintains the diversity of the population while speeding up the algorithm’s convergence. The model builds a Gaussian probability matrix using the site positional order distribution characteristics implied in the original site data information, and applies the Gaussian probability matrix to individual gene mutations using a roulette-wheel-selection method; thus, the study guarantees the genetic diversity of the population while guiding it to evolve in the high-fitness direction. Finally, an experimental simulation is performed using data obtained from a commercial supermarket, thereby verifying the effectiveness of the proposed algorithm and comparing it with other algorithms. The results reveal that compared with the classical GA, the average convergence speed of the improved GA can be increased by 50–60% and the consumed algorithm time can be reduced by 48% while maintaining the difference in solution accuracy within 1%.

Abstract Semantic segmentation is significant to realize the scene understanding of autonomous driving. Due to the lack of annotated real-world data, the technology of domain adaptation is applied so that the model is trained on the synthetic data and inferred on the real data. However, this domain gap leads to aleatoric and epistemic uncertainty. These uncertainties link to the potential safety issue of autonomous driving in normal weather and adverse weather. In this study, we explore the scientific problem that has received sparse attention previously. We postulate that the Dual Attention module can mitigate the uncertainty in the task of semantic segmentation and provide some empirical study to validate it. Furthermore, the utilization of Kullback-Leibler divergence (KL divergence) helps the estimation of aleatoric uncertainty and boosts the robustness of the segmentation model. Our empirical study on the diverse datasets of semantic segmentation demonstrates the effectiveness of our method in normal and adverse weather. Our code is available at: https://github.com/liubo629/Seg-Uncertainty-dual-attention .

Chronic pain, such as neuropathic pain, can lead to anxiety, depression, and other negative emotions, thereby forming comorbidities and increasing the risk of chronic pain over time. Both the infralimbic amygdala (IL) and the basolateral amygdala (BLA) are significantly associated with negative emotions and pain, and they are known to have reciprocal connections. However, the role of IL-BLA circuit pathways in neuropathic pain-induced anxiety and depression remains unexplored. Electroacupuncture (EA) is frequently employed in the treatment of chronic pain and emotional disorders. However, The mechanism by which EA mediates its analgesic and emotion-alleviating effects via the IL-BLA circuit remains uncertain. Here, we used chemogenetic manipulation combined with behavioral tests to detect pain induced anxiety-like and depression-like behaviors. We observed that activation of the IL-BLA circuit by chemogenetic activation induced depression-like behavior of mice. Additionally, we discovered that chemogenetic activation of the IL-BLA circuit successfully prevented the beneficial effects of EA on depression-like behavior brought on by chronic pain in mice with spared nerve injury (SNI). We discovered that SNI-induced depression-like behavior could be mitigated by inhibiting the circuit, and EA had a comparable depressive-relieving effect. Furthermore, the IL-BLA circuit's activation or inhibition had no effect on the anxiety-like feelings brought on by SNI. Overall, our findings identify a specific neural circuit that selectively regulates pain-induced depression-like emotions, without affecting pain-induced anxiety-like emotions. This discovery offers a precise target for future treatments of comorbid pain and depression and provides a plausible explanation for the efficacy of EA in treating depression-like emotions associated with chronic pain.

The orientation (including the c axis orientation and crystal direction parallel to rolling direction) evolution of grown recrystallization grains during annealing at 250 °C for 45–180 min in Mg–Zn-Gd alloy was characterized by quasi-in-situ electron backscatter diffraction method. An unusual grain orientation rotation during the process of static recrystallization grain growth, rather than common plastic deformation or recrystallization nucleation process, was observed. Due to the higher storage energy, the growth size in the early stage of annealing (1.41 μm) is larger than that in the late stage of annealing (0.73 μm) for most (∼76%) grains, and corresponding average c-axis rotation angles are 3.65° and 1.39°, respectively, indicating that the larger the increase in grain size, the greater the changing degree in grain orientation. It is speculated that the orientation rotation during grain growth process is mediated by the interaction between dislocations and grain boundaries. The results reported in the current paper can provide a new insight into the study on the relationship between preferential grain growth and non-basal texture formation in rare earth contained Mg alloys.

Abstract Gouty arthritis evokes joint pain and inflammation. Mechanisms driving gout pain and inflammation remain incompletely understood. Here we show that CXCL5 activates CXCR2 expressed on nociceptive sensory neurons to drive gout pain and inflammation. CXCL5 expression was increased in ankle joints of gout arthritis model mice, whereas CXCR2 showed expression in joint-innervating sensory neurons. CXCL5 activates CXCR2 expressed on nociceptive sensory neurons to trigger TRPA1 activation, resulting in hyperexcitability and pain. Neuronal CXCR2 coordinates with neutrophilic CXCR2 to contribute to CXCL5-induced neutrophil chemotaxis via triggering CGRP- and substance P-mediated vasodilation and plasma extravasation. Neuronal Cxcr2 deletion ameliorates joint pain, neutrophil infiltration and gait impairment in model mice. We confirmed CXCR2 expression in human dorsal root ganglion neurons and CXCL5 level upregulation in serum from male patients with gouty arthritis. Our study demonstrates CXCL5-neuronal CXCR2-TRPA1 axis contributes to gouty arthritis pain, neutrophil influx and inflammation that expands our knowledge of immunomodulation capability of nociceptive sensory neurons.

Mg-Y cast alloy shows excellent ductility (elongation to failure > 15%) compared with pure Mg and commercial Mg cast alloys. By monitoring the microstructure evolution during an in situ tensile test of a Mg-2.5 wt%Y alloy, we identify the activation of prismatic slip, which is rare in Mg. Synchrotron X-ray micro-beam Laue diffraction (μ-Laue) and transmission electron microscopy revealed the morphology of prismatic slip bands and individual dislocations. Density functional theory and molecular dynamics calculations indicate that solute Y can significantly reduce the stacking fault energy (SFE) along direction on prismatic plane in Mg lattice and thus facilitate the nucleation of dislocations during deformation. The presence of free dislocations in the Mg lattice can also lead to nucleation of {10–12} twins even under unfavorable geometric conditions.

This study conducted experimental analyses on a 280 Ah single lithium iron phosphate battery using an independently constructed experimental platform to assess the efficacy of compressed nitrogen foam in extinguishing lithium-ion battery fires. Based on theoretical analysis, the fire-extinguishing effects of compressed nitrogen foam at different outlet pressures from foam mixture tanks were analyzed, examining factors such as battery surface temperature, flame temperature, and thermal weight loss. The results indicate that the compressed nitrogen foam can extinguish the open flame of the battery in 14 s at 0.7 MPa, with the battery's surface temperature dropping by approximately 11 % before and after the application of the extinguishing agent. Compared with other commonly used extinguishing agents, the compressed nitrogen foam demonstrates superior extinguishing efficiency, but its cooling efficiency is somewhat lower. At pressures ranging from 0.4 to 0.6 MPa, the foam displays prolonged drainage time and sustained cooling effects, rendering it more suitable for lithium-ion battery fire scenarios. To address the issue of reduced cooling performance during later stages of fire suppression by compressed nitrogen foam, an intermittent injection approach has been proposed to effectively preserve its cooling efficacy.

A Multiscale-Motion Embedding Pseudo-3D (MME-P3D) gesture recognition algorithm has been proposed to tackle the issues of excessive parameters and high computational complexity encountered by existing gesture recognition algorithms deployed in mobile and embedded devices. The algorithm initially takes into account the characteristics of gesture motion information, integrating the channel attention (CE) mechanism into the pseudo-3D (P3D) module, thereby constructing a P3D-C feature extraction network that can efficiently extract spatio-temporal feature information while reducing the complexity of the algorithmic model. To further enhance the understanding and learning of the global gesture movement's dynamic information, a Multiscale Motion Embedding (MME) mechanism is subsequently designed. The experimental findings reveal that the MME-P3D model achieves recognition accuracies reaching up to 91.12% and 83.06% on the self-constructed conference gesture dataset and the publicly available Chalearn 2013 dataset, respectively. In comparison with the conventional 3D convolutional neural network, the MME-P3D model demonstrates a significant advantage in terms of parameter count and computational requirements, which are reduced by as much as 82% and 83%, respectively. This effectively addresses the limitations of the original algorithms, making them more suitable for deployment on embedded and mobile devices and providing a more effective means for the practical application of hand gesture recognition technology.

The successful integration of renewable energy resources into the power grid hinges on the development of energy storage technologies that are both cost-effective and reliable. These storage technologies, capable of storing energy for durations longer than 10 hours, play a crucial role in mitigating the variability inherent in wind and solar-dominant power systems. To shed light on this matter, a transparent, least-cost macro energy model with user-defined constraints has been utilized for a case study of California. The model addresses all included technologies, solving for both hourly dispatch and installed capacities. Real-world historical demand and hourly weather data have been utilized to do this analysis. A novel approach has been introduced to assess the significance of long-duration energy storage technologies (LDS) in terms of their energy and power capacity. This method explores the contributions of pumped hydropower storage (PHS), compressed air energy storage (CAES), and power-to-gas-to-power (PGP) storage toward minimizing the overall balance of system cost. Historical electricity demand, hourly weather data, and current technology costs are used to investigate high-level implications for California’s power system options. Increasing the storage capacity of each technology from 1 to 10 hours results in 29.6%, 14.4%, and 7.5% cost reduction for PHS, CAES, and PGP cases respectively. However, in studied simulations, maximum availability (maximum) of pumped hydropower storage reduces the balance of system costs by 72.3% followed by CAES (60.6%) and PGP (48.6%) and suggests that pumped hydropower storage in combination with CAES/PGP could play an important role in California’s electricity system, provided that suitable sites can be identified and constructed at reasonable costs.

Pyramidal dislocations in magnesium (Mg) and other hexagonal close-packed metals play an important role in accommodating plastic strains along the c-axis. Bulk single crystal Mg only presents very limited plasticity in c-axis compression, and this behavior was attributed to out-of-plane dissociation of pyramidal dislocations onto the basal plane and resulted in an immobile dislocation configuration. In contrast, other simulations and experiments reported in-plane dissociation of pyramidal dislocations on their slip planes. Thus, the core structure and mode of dissociation of pyramidal dislocations are still not well understood. To better understand the dissociation behavior of pyramidal dislocations in Mg at room temperature, in this work, atomistic simulations were conducted to investigate four types of pyramidal dislocations at 300 K: edge and screw Py-I on {101¯1}, edge and screw Py-II on {112¯2} by using a modified embedded atom method (MEAM) potential for Mg and anisotropic elasticity dislocation model. The results show that when energy minimization was performed before relaxation, in-plane dissociation of edge dislocations on respective pyramidal plane could be obtained at room temperature for all four types of dislocation. Without energy minimization, the edge dislocations dissociated out-of-plane onto the basal plane. Calculations of potential energy and hydrostatic stress of individual atoms at the edge dislocation core show that the extraordinarily high energy and atomic stresses in the as-constructed dislocation structures caused the out-of-plane dissociation onto the basal plane. The core structures of all four types of pyramidal dislocation after in-plane dissociation were analyzed by computing the distribution of the Burgers vector.

Stock index fluctuations are characterized by high noise and their accurate prediction is extremely challenging. To address this challenge, this study proposes a spatial–temporal–bidirectional long short-term memory (STBL) model, incorporating spatiotemporal attention mechanisms. The model enhances the analysis of temporal dependencies between data by introducing graph attention networks with multi-hop neighbor nodes while incorporating the temporal attention mechanism of long short-term memory (LSTM) to effectively address the potential interdependencies in the data structure. In addition, by assigning different learning weights to different neighbor nodes, the model can better integrate the correlation between node features. To verify the accuracy of the proposed model, this study utilized the closing prices of the Hong Kong Hang Seng Index (HSI) from 31 December 1986 to 31 December 2023 for analysis. By comparing it with nine other forecasting models, the experimental results show that the STBL model achieves more accurate predictions of the closing prices for short-term, medium-term, and long-term forecasts of the stock index.

Abstract Residual oil zones (ROZs) have high residual oil saturation, which can be produced using CO2 miscible flooding. At the same time, these zones are good candidates for CO2 sequestration. To evaluate the coupled CO2-EOR and storage performance in ROZs for Water-Alternating-CO2 (WAG) flooding, a multi-compositional CO2 miscible model with molecular diffusion was developed. The effects of formation parameters (porosity, permeability, temperature), operation parameters (bottom hole pressure, WAG ratio, pore volume of injected water), and diffusion coefficient on the coupled CO2-EOR and storage were investigated. Five points from the CO2 sequestration curve and the oil recovery factor curve were selected to help better analyze coupled CO2-EOR and storage. The results demonstrate that enhanced performance is observed when formation permeability is higher and a larger volume of water is injected. On the other hand, the performance diminishes with increasing porosity, molecular diffusion of gas, and the WAG ratio. When the temperature is around 100 °C, coupled CO2-EOR and storage performance is the worst. To achieve optimal miscible flooding, it is recommended to maintain the bottom hole pressure (BHP) of the injection well above 1.2 minimum miscibility pressure (MMP), while ensuring that the BHP of the production well remains sufficiently high. Furthermore, the tapered WAG flooding strategy proves to be profitable for enhanced oil recovery, as compared to a WAG ratio of 0.5:1, although it may not be as effective for CO2 sequestration.

A novel method is presented for reproducing kernel of a 2D fractional diffusion equation. The exact solution is expressed as a series, which is then truncated to get an approximate solution. In addition, some techniques to improve existing methods are also proposed. The proposed approach is easy to implement. It is proved that both the approximate solution and its partial derivatives converge to their exact solutions. Numerical results demonstrate that the proposed approach is effective and can provide a high precision global approximate solution.

Microscale laser dynamic forming, as a novel high-speed microforming technique, can overcome the shortcomings of traditional microforming methods. However, in practical applications, laser dynamic microforming technology is often affected by the rebound behavior of the workpiece, limiting the further improvement of processing quality and efficiency. This paper aims to reduce the rebound effect in laser dynamic forming by using multi-pulse laser shock loading. The forming results of workpieces under different laser energies and laser impact numbers were studied using experimental and numerical simulation methods. After multiple laser shocks, numerical simulations of the forming results were conducted using ANSYS/LS-DYNA software. These numerical simulation results were then experimentally validated and compared. The surface morphology of the workpieces was characterized using a confocal microscope and a scanning electron microscope (SEM). Energy-dispersive spectroscopy (EDS) was used to analyze the chemical element content changes in the collision regions at the bottoms of the workpieces after multi-pulse loading. The SEM and EDS results revealed the collision behavior patterns during the forming process. Finally, the forming laws of workpieces under multiple laser shocks were summarized.

Crop straw returning to the field is an effective practice for straw utilization to improve soil fertility and sustain crop productivity. However, little information is available about the long-term effects of paddy straw return on soil properties and rice yield under a double-rice system. The objectives of this study were to test the hypothesis of the effects of different amounts of paddy straw returned to the field on soil physicochemical properties and rice yield, and to clarify the correlation between crop yield and soil physicochemical properties as well as quick-acting nutrients under different straw-returning modes. The experiment, initiated in the 2005 rice season, utilized “Xiang 45” and “Xiang 13” long-grained rice cultivars within a double-season rice cropping system. Three straw-returning treatments were implemented: rotary tillage with full rice straw incorporation (RTS), incorporation of one-third of the rice straw (1/3RTS), and incorporation of two-thirds of the rice straw (2/3RTS). This study found that among the three straw return rates, 2/3RTS had the most significant impact on soil physicochemical properties. Soil nitrogen content was identified as a crucial factor influencing soil organic carbon (SOC) accumulation, while pH levels significantly affected rice yield. Straw incorporation effectively increased the content and stocks of SOC.

Abstract Background Gout results from disturbed uric acid metabolism, which causes urate crystal deposition in joints and surrounding tissues. Gout pain management is largely limited to colchicine and nonsteroidal anti-inflammatory drugs. Constant usage of these medications leads to severe side effects. We previously showed electroacupuncture (EA) is effective for relieving pain in animal model of gout arthritis. Here we continued to study the mechanisms underlying how EA alleviates gout pain. Methods Monosodium urate was injected into ankle joint to establish gout arthritis model in mice. EA or sham EA was applied at ST36 and BL60 acupoints of model animals. Biochemical assays, immunostaining, live cell Ca2+ imaging and behavioral assays were applied. Results Model mice displayed obvious mechanical allodynia, accompanied with gait impairments. EA attenuated mechanical hypersensitivities and improved gait impairments. EA reduced the overexpression of NLRP3 inflammasome signaling molecules in ankle joints of model animals. EA-induced anti-allodynia, as well as inhibition on NLRP3 inflammasome, were mimicked by antagonizing but abolished by activating NLRP3 inflammasome via pharmacological methods. EA attenuated oxidative stress, an upstream signaling of NLRP3 inflammasome in ankle joints of model mice. Exogenously increasing oxidative stress abolished EA’s inhibitory effect on NLRP3 inflammasome and further reversed EA’s anti-allodynic effect. EA reduced neutrophil infiltrations in ankle joint synovium, a major mechanism contributing to oxidative stress in gout. Pharmacological blocking NLRP3 inflammasome or EA reduced TRPV1 channel overexpression in dorsal root ganglion (DRG) neurons. Ca2+ imaging confirmed that EA could reduce functional enhancement in TRPV1 channel in DRG neurons during gout. Conclusions Our results demonstrate that EA reduces gout pain possibly through suppressing ROS-mediated NLRP3 inflammasome activation in inflamed ankle joints and TRPV1 upregulation in sensory neurons, supporting EA as a treatment option for gout pain.

Excessive deposition of monosodium urate (MSU) crystal in the joint results in gout arthritis, which triggers severe pain and affects life quality. Oxidative stress is a pivotal mechanism that contributes to etiology of gout pain and inflammation. Here we investigated whether activating Nrf2, which plays important roles in regulating endogenous antioxidant response, would attenuate gout arthritis via promoting antioxidant signaling in joint tissues. Gout arthritis model was established by intra-articular injection of MSU (500 μg/ankle) into the right ankle joint of mouse. Pharmacologically activating Nrf2 by activator oltipraz (50, 100 or 150 mg/kg, intraperitoneal) at 1 h before and 5, 23, 47 h after model establishment dose-dependently inhibited joint inflammation, mechanical and heat hypersensitivities in model mice. Oltipraz (100 mg/kg) reversed gait impairments without altering locomotor activity and reduced neutrophil infiltrations in ankle joints. In vitro studies revealed oltipraz (25 μM) inhibited MSU-induced ROS production in mouse macrophages and improved mitochondrial bioenergetics impairments caused by MSU. In vivo ROS imaging combined with biochemical assays confirmed the antioxidant effects of oltipraz on model mice. Nrf2 activation inhibited pro-inflammatory cytokine overproduction in ankle joint and attenuated the overexpression and enhancement in TRPV1 channel in DRG neurons innervating hind limb. Therapeutic effects of oltipraz were abolished by inhibiting Nrf2 or in Nrf2 knockout mice. These results suggest pharmacologically activating Nrf2 alleviates gout pain, gait impairments, inflammation and peripheral sensitization via Nrf2-dependent antioxidant mechanism. Targeting Nrf2 may represent a novel treatment option for gout arthritis.

Background Escherichia coli is a commonly used faecal indicator bacterium to assess the level of faecal contamination in aquatic habitats. However, extensive studies have reported that sediment acts as a natural reservoir of E. coli in the extraintestinal environment. E. coli can be released from the sediment, and this may lead to overestimating the level of faecal contamination during water quality surveillance. Thus, we aimed to investigate the effects of E. coli habitat transition from sediment to water on its abundance in the water column. Methods This study enumerated the abundance of E. coli in the water and sediment at five urban lakes in the Kuala Lumpur-Petaling Jaya area, state of Selangor, Malaysia. We developed a novel method for measuring habitat transition rate of sediment E. coli to the water column, and evaluated the effects of habitat transition on E. coli abundance in the water column after accounting for its decay in the water column. Results The abundance of E. coli in the sediment ranged from below detection to 12,000 cfu g–1, and was about one order higher than in the water column (1 to 2,300 cfu mL–1). The habitat transition rates ranged from 0.03 to 0.41 h–1. In contrast, the E. coli decay rates ranged from 0.02 to 0.16 h−1. In most cases (>80%), the habitat transition rates were higher than the decay rates in our study. Discussion Our study provided a possible explanation for the persistence of E. coli in tropical lakes. To the best of our knowledge, this is the first quantitative study on habitat transition of E. coli from sediments to water column.

ABSTRACTRickettsia heilongjiangensis, a tick-borne obligate intracellular bacterium and causative agent of spotted fever in China, has attracted increasing concern regarding its capability in causing human rickettsiosis. Here, we conducted a genomic analysis of a new R. heilongjiangensis strain B8 (B8) isolated from the serum of a patient who had been bitten by a Haemaphysalis longicornis tick in Anhui Province, China. The present study sought to identify exclusive genes that might be associated with the pathogenicity of B8 using comparative genomics. Specifically, the sequences of B8 were assembled into one circular chromosome of 1,275,081 bp and predicted to contain 1447 genes. Comparative genome analyses were performed based on the genome of B8 and 28 spotted fever group (SFG) rickettsial genomes deposited in NCBI. Phylogenomic analyses indicated the B8 strain was clustered within the R. heilongjiangensis species; however, a sum of 112 and 119 B8-unique genes was identified when compared with R. heilongjiangensis and R. japonica strains, respectively. Functional annotation analyses revealed that these B8-unique genes were mainly annotated to defence mechanisms, lipid transport and metabolism, cell wall/membrane/envelope biogenesis. These data indicate B8 rather represents a previously undescribed human-pathogenic SFG rickettsia lineage, which may be an intermediate lineage of R. heilongjiangensis and R. japonica. Overall, this study isolated a new strain of R. heilongjiangensis in East-Central China for the first time, and provided potential B8-unique genetic loci that could be used for the discrimination of B8 from other R. heilongjiangensis and closely related SFG Rickettsial strains.

Abstract Background Complex regional pain syndrome type-I (CRPS-I) causes excruciating pain that affect patients’ life quality. However, the mechanisms underlying CRPS-I are incompletely understood, which hampers the development of target specific therapeutics. Methods The mouse chronic post-ischemic pain (CPIP) model was established to mimic CRPS-I. qPCR, Western blot, immunostaining, behavioral assay and pharmacological methods were used to study mechanisms underlying neuroinflammation and chronic pain in spinal cord dorsal horn (SCDH) of CPIP mice. Results CPIP mice developed robust and long-lasting mechanical allodynia in bilateral hindpaws. The expression of inflammatory chemokine CXCL13 and its receptor CXCR5 was significantly upregulated in ipsilateral SCDH of CPIP mice. Immunostaining revealed CXCL13 and CXCR5 was predominantly expressed in spinal neurons. Neutralization of spinal CXCL13 or genetic deletion of Cxcr5 (Cxcr5 −/−) significantly reduced mechanical allodynia, as well as spinal glial cell overactivation and c-Fos activation in SCDH of CPIP mice. Mechanical pain causes affective disorder in CPIP mice, which was attenuated in Cxcr5 −/− mice. Phosphorylated STAT3 co-expressed with CXCL13 in SCDH neurons and contributed to CXCL13 upregulation and mechanical allodynia in CPIP mice. CXCR5 coupled with NF-κB signaling in SCDH neurons to trigger pro-inflammatory cytokine gene Il6 upregulation, contributing to mechanical allodynia. Intrathecal CXCL13 injection produced mechanical allodynia via CXCR5-dependent NF-κB activation. Specific overexpression of CXCL13 in SCDH neurons is sufficient to induce persistent mechanical allodynia in naïve mice. Conclusions These results demonstrated a previously unidentified role of CXCL13/CXCR5 signaling in mediating spinal neuroinflammation and mechanical pain in an animal model of CRPS-I. Our work suggests that targeting CXCL13/CXCR5 pathway may lead to novel therapeutic approaches for CRPS-I.

2D-3D point or line correspondences are usually used to estimate the camera pose and intrinsic parameters, such as the focal length. There are many point-based methods and line-based methods, i.e., PnP solvers and PnL solvers. However, methods that use both point and line correspondences are not used widely. Hence, this paper proposed a new method to estimate the pose and focal length using a 2D-3D point correspondence and a 2D-3D line correspondence. In addition, the camera position is known as the prior knowledge to simplify the calculating process. In the world frame, the 3D point and camera position can determine a line, and the 2D projection of the 3D point and camera position can also determine a line in the camera frame. In fact, the two lines are the same line in space and their unit direction vectors can convert to each other using the rotation matrix from the world frame to the camera frame. In the world frame, the 3D line and camera position can determine a plane, and the 2D projection of the 3D line and camera position can also determine a plane in the camera frame. In fact, the two planes are the same plane in space and their unit normal vectors can also convert to each other using the rotation matrix from the world frame to the camera frame. Now there are two transformations of the direction vectors and the normal vectors. The transformations of vectors can be regarded as the transformations of 3D-3D point correspondences when the world frame and camera frame have the same origin. This is the key point in this paper and then the pose can be estimated efficiently. What’s more, the angle between the line passing through the 3D point and camera position, and the plane passing through the 3D line and camera position in the world frame, is equal to the angle between the line passing through the 2D projection of the 3D point and camera position, and the plane passing through the 2D projection of the 3D line and camera position in the camera frame. This is another key point to estimate the focal length. Experiments show our proposed method has good performance in numerical stability, noise sensitivity and computational speed with synthetic data and real scenarios. In addition, compared with other SOTA (state-of-the-art) methods, our method has a single solution and performs better.

Dissolution trapping stands as a critical mechanism for the geological carbon storage (GCS) and can be notably improved through density-driven convection. However, to the best of the author’s knowledge, the discussion on density-driven convection of CO2-H2S mixture has been limited to the exclusion of intersected fractures and lithology sequence effects. Therefore, this study aims to systematically investigate the impact of H2S concentration, fractures, and lithology sequence on convective mixing. Four distinct mechanisms that influence convective mixing of CO2-H2S mixtures in the presence of fractures were identified: 1) accelerated downward solute transportation in fractures, 2) coalescence between plumes around fractures and primary down-swelling plumes, 3) high fracture conductivity inhibiting plume migration across fractures, and 4) upward flow in fractures facilitating the transport of high-concentration solute out of the system. Additionally, the effects of lithology sequence on the shape of CO2 plumes and the curve shape of the total flux at the top boundary were described. The results demonstrated that density-driven convection is enhanced with decreasing H2S concentration and increasing fracture interaction angle and fracture conductivity ratio. The magnitudes of density-driven convection, ranked from high to low, are fining downward, uniform, and fining upward lithology sequences. Furthermore, the H2S concentration affects the flow direction within fractures and alters the relative magnitude of the dimensionless concentration in the noise sequences. The findings of this study on a small scale were proven to be applicable on a large scale.

The time series of exchange rate fluctuations are characterized by non-stationary and nonlinear features, and forecasting using traditional linear or single-machine models can cause significant bias. Based on this, the authors propose the combination of the advantages of the EMD and LSTM models to reduce the complexity by analyzing and decomposing the time series and forming a new model, EMD-LSTM-SVR, with a stronger generalization ability. More than 30,000 units of data on the USD/CNY exchange rate opening price from 2 January 2015 to 30 April 2022 were selected for an empirical demonstration of the model’s accuracy. The empirical results showed that the prediction of the exchange rate fluctuation with the EMD-LSTM-SVR model not only had higher accuracy, but also ensured that most of the predicted positions deviated less from the actual positions. The new model had a stronger generalization ability, a concise structure, and a high degree of ability to fit nonlinear features, and it prevented gradient vanishing and overfitting to achieve a higher degree of prediction accuracy.

Azadirachtin is regarded as one of the best botanical pesticides due to its broad spectrum of insecticides and low interference with natural enemies. To enhance the effect of azadirachtin and slow down the generation of resistance, the combined activity was studied. Here, we found that Dodonaea viscosa saponin B (DVSB) isolated from the seeds of Dodonaea viscosa has good combined activity with the azadirachtin. The mixture of DVSB and azadirachtin in a volume ratio of 1:4 had the strongest combined effect against Spodoptera litura, with a co-toxicity coefficient (CTC) of 212.87. DVSB exerted its combined activity by affecting the contact angle, surface tension, maximum retention and cell membrane permeability. When mixed with DVSB, the contact angle and surface tension decreased by 30.38% and 23.68%, and the maximum retention increased by 77.15%. DVSB was screened as an effective combined activity botanical compound of azadirachtin upon the control of S. litura and highlights the potential application of botanical compounds as pesticide adjuvants in the pest management.

IntroductionLateral ankle sprain (LAS) is a very common type of joint injury. It occurred with high incidence among general population and especially among individuals participating sports and outdoor activities. A certain proportion of individuals who once developed LAS may suffer persistent ankle pain that affects daily activities. However, the mechanisms underlying LAS-induced pain still remained largely unknown.MethodsWe established a LAS mouse model and systematically evaluated the pain-related behaviors in this mouse model. RNA sequencing (RNA-Seq), combined with bioinformatics analysis, was undertaken to explore gene expression profiles. Immunostaining was used to study glial cell and neuron activation in ipsilateral spinal cord dorsal horn (SCDH) of LAS model mice. Ibuprofen was used to treat LAS model mice.ResultsThe LAS model mice developed obvious signs of mechanical and heat hypersensitivities as well as gait impairments in ipsilateral hind paws. Besides, LAS model mice developed signs of pain-related emotional disorder, including pain-induced aversion. By RNA-Seq, we were able to identify certain differentially expressed genes and signaling pathways that might contribute to pain mechanisms of LAS mouse model. In addition, LAS model mice showed increased c-Fos and p-ERK immunoreactivity as well as astrocyte and microglia overactivation in ipsilateral spinal cord dorsal horn, indicating central sensitization might occur. Finally, LAS model mice respond to ibuprofen, a drug clinically used to treat ankle sprain pain.ConclusionOur study found LAS model mice may be used as a preclinical animal model for screening novel targets or therapies for ankle sprain. Thus, the study may further help to understand molecular mechanisms contributing to ankle sprain-induced pain.

BackgroundObesity is an increasingly severe global public health issue. This study aims to estimate the cross-sectional association between bone mineral density (BMD) and hyperuricemia (HU) in obesity.MethodA total of 275 obese subjects (126 men and 149 women) participated in this cross-sectional study. Obesity was diagnosed as body mass index (BMI) ≥28 kg/m2, whereas HU was defined as the blood uric acid level of 416 μmol/L in men and 360 μmol/L in women. The BMD of the lumbar spine and right hip was measured by dual-energy X-ray absorptiometry (DXA). The multivariable logistic regressions were employed to examine the relationship between BMD and HU in obesity, with the adjustment of gender, age, fasting blood glucose, fasting insulin, homeostasis model assessment of insulin resistance (HOMA-IR), cholesterol, triglycerides, low-density lipoprotein, high-density lipoprotein, creatinine, blood urea nitrogen, high-sensitivity C-reactive protein (hs-CRP), cigarette smoking, and alcohol drinking status.ResultThe overall prevalence of HU was 66.9% in this obese population. The mean age and BMI of this population were 27.9 ± 9.9 years and 35.2 ± 5.2 kg/m2, respectively. The multivariable-adjusted OR (the highest vs. lowest BMD quartile) demonstrated a negative relationship between BMD and HU in total (OR = 0.415, 95%CI: 0.182–0.946; p = 0.036), L1 (OR = 0.305, 95%CI: 0.127–0.730; p = 0.008), L2 (OR = 0.405, 95%CI: 0.177–0.925; p = 0.032), and L3 (OR = 0.368, 95%CI: 0.159–0.851; p = 0.020) lumbar vertebrae. In the subgroup analysis for the male population, the BMD was also negatively associated with HU in total (OR = 0.077, 95%CI: 0.014–0.427; p = 0.003), L1 (OR = 0.019, 95%CI: 0.002–0.206; p = 0.001), L2 (OR = 0.161, 95%CI: 0.034–0.767; p = 0.022), L3 (OR = 0.186, 95%CI: 0.041–0.858; p = 0.031), and L4 (OR = 0.231, 95%CI: 0.056–0.948; p = 0.042) lumbar vertebrae. However, such findings did not exist in women. In addition, there was no significant relationship between hip BMD and HU in obesity.ConclusionOur results showed that the lumbar BMD was negatively associated with HU in obesity. However, such findings only existed in men, rather than women. In addition, no significant relationship between hip BMD and HU existed in obesity. Due to the limited sample size and nature of the cross-sectional design, further large prospective studies are still needed to clarify the issues.

Abstract Studies have reported that >91.9% of non-syndromic tooth agenesis cases are caused by seven pathogenic genes. Objective To report novel heterozygous PAX9 variants in a Chinese family with non-syndromic oligodontia and summarize the reported genotype-phenotype relationship of PAX9 variants. Methodology We recruited 28 patients with non-syndromic oligodontia who were admitted to the Hospital of Stomatology Hebei Medical University (China) from 2018 to 2021. Peripheral blood was collected from the probands and their core family members for whole-exome sequencing (WES) and variants were verified by Sanger sequencing. Bioinformatics tools were used to predict the pathogenicity of the variants. SWISS-MODEL homology modeling was used to analyze the three-dimensional structural changes of variant proteins. We also analyzed the genotype-phenotype relationships of PAX9 variants. Results We identified novel compound heterozygous PAX9 variants (reference sequence NM_001372076.1) in a Chinese family with non-syndromic oligodontia: a new missense variant c.1010C>A (p.T337K) in exon 4 and a new frameshift variant c.330_331insGT (p.D113Afs*9) in exon 2, which was identified as the pathogenic variant in this family. This discovery expands the known variant spectrum of PAX9; then, we summarized the phenotypes of non-syndromic oligodontia with PAX9 variants. Conclusion We found that PAX9 variants commonly lead to loss of the second molars.

Synthetic Aperture Radar Interferometry (InSAR) has grown significantly over the past few decades, which were mainly used in remote sensing applications. Most InSAR applications (e.g., terrain mapping and monitoring) utilized a key technique called phase unwrapping Phase unwrapping obtained the absolute phase from the wrapped phase for the subsequent application. However, the collected wrapped phase inevitably contains noise due to the influence of factors such as atmosphere and temperature in the InSAR acquisition stage. This noise made it challenging to obtain the absolute phase from the wrapped phase. This study proposed a deep learning framework (PUnet) for phase unwrapping form InSAR data. pUnet was a robust framework using U-net as the basic structure combined with an attention mechanism and positional encoding, facilitating accurate phase unwrapping from the wrapped phase. Through comparative experiments with typical phase unwrapping algorithms, we demonstrated that pUnet could obtain absolute phases with high accuracy and robustness than from the wrapped phase under various levels of noise.

Aims We investigated the incidence and clinical features of venous thromboembolism (VTE) in inpatients with mental illnesses. Methods We retrospectively analyzed records of inpatients with mental illnesses and confirmed VTE at The First Hospital of Hebei Medical University between August 2018 and July 2022. We recorded demographic characteristics, psychosis-related conditions, and thrombus distribution. Results Among 12939 patients diagnosed with mental illness, 156 (1.21%) presented with VTE at the first visit or during the disease course. Crude VTE incidence varied significantly across mental illnesses, being highest in patients with organic mental disorders (5.20%), followed by emotional disorders (1.10%), and others ( P

Objective: Irreversible electroporation (IRE) is a nonthermal ablation technique for the treatment of malignant liver tumors. IRE has demonstrated efficacy and safety in the treatment of malignant liver tumors and its unique advantages in the treatment of nearby vascular lesions. This study aimed to compare the efficacy, safety, and intermediate-term outcomes of IRE and radiofrequency (RF) therapy in malignant liver tumors. Methods: Twenty-four patients with primary or secondary liver malignancies were included in this prospective, double-arm clinical trial. Patients were randomly divided into the IRE and RF groups. The primary outcome was the efficacy (local ablation control evaluation at 90 days). The secondary outcomes were safety (procedure-related complications at ​≤ ​90 days) and intermediate-term survival (at 24 months). Results: The ablation assessment at 90 days after surgery with mRECIST for IRE versus RF were 70%, 20%, 0%, and 10% versus 92.9%, 7.1%, 0%, and 0% (CR, PR, SD, and PD, respectively). The complication rates of IRE versus RF with Clavien-Dindo classification were 16.7%, 25%, 0%, 8.3%, and 8.3% versus 8.3%, 50%, 0%, 0%, and 0% (Grade I, II, III, IV, and V, respectively). The average overall survival (OS) was 17.55 months in the IRE group (95% CI 15.13-22.37) and 18.75 months in the RF group (95% CI 12.48-22.61). There was no statistical difference between the IRE and RF groups in terms of efficacy (p ​= ​0.48), safety(p ​= ​0.887), or 24-month OS (p ​= ​0.959). Conclusions: IRE ablation revealed similar efficacy and safety in a short-term follow-up, and similar OS in mid-term survival as RF ablation in treating malignant hepatic tumors.

As the ownership of electric vehicles (EVs) continues to rise, EVs are becoming an integral part of urban microgrids. Incorporating the charging and discharging processes of EVs into the microgrid’s optimization scheduling process can serve to load leveling, reducing the reliance of the microgrid on external power networks. This paper proposes a novel two-stage, dual-layer distributed optimization operational approach for microgrids with EVs. The lower layer is a distributed control layer, which ensures, through consensus control methods, that every EV maintains a consistent charging/discharging and state of charge (SOC). The upper layer is the optimization scheduling layer, determining the optimal operational strategy of the microgrid using the multiagent reinforcement learning method and providing control reference signals for the lower layer. Additionally, this paper categorizes the charging process of EVs into two stages based on their SOC: the constrained scheduling stage and the free scheduling stage. By employing distinct control methods during these two stages, we ensure that EVs can participate in the microgrid scheduling while fully respecting the charging interests of the EV owners.

(1) Background: In real road scenarios, various complex environmental conditions may occur, including bright lights, nighttime, rain, and snow. In such a complex environment for detecting pole-shaped obstacles, it is easy to lose the feature information. A high rate of leakage detection, false positives, and measurement errors are generated as a result. (2) Methods: The first part of this paper utilizes the improved YOLOv5 algorithm to detect and classify pole-shaped obstacles. Then, the identified target frame information is combined with binocular stereo matching to obtain more accurate distance information. (3) Results: The experimental results demonstrate that this method achieves a mean average precision (mAP) of 97.4% for detecting pole-shaped obstacles, which is 3.1% higher than the original model. The image inference time is only 1.6 ms, which is 1.8 ms faster than the original algorithm. Additionally, the model size is only 19.0 MB. Furthermore, the range error of this system is less than 7% within the range of 3–15 m. (4) Conclusions: Therefore, the algorithm not only achieves real-time and accurate identification and classification but also ensures precise measurement within a specific range. Meanwhile, the model is lightweight and better suited for deploying sensing systems.

Inverting land cover reflectance or derived indices from low-spatial-resolution images to refine the spatial resolution of this data is cost-effective for land surface monitoring applications that face technical or budget limitations. Based on the linear spectral mixing model, many approaches have successfully unmixed coarse mixed pixels using high-spatial-resolution land cover maps in the past decades. However, in some cases, the solutions of linear systems composed of several mixed pixels may not be acquired due to the underdetermined problem. This study presents the causes of this problem and proposes an iterative approximation strategy to address it. An elastic-window-based algorithm was developed, where the initial size of the window was calculated based on the land cover of the mixed pixel. Mixed pixels of neighborhoods with similar land covers were then selected to form the unmixing linear system, which was examined through a simulation test to ensure it was not underdetermined. Otherwise, the window would expand to include more adjacent pixels. This process was repeated until a successful solution was obtained. A statistical analysis of sixty land cover maps from around the globe shows that the underdetermined problem exists at a low level but becomes more serious with an increase in mixed scale. The results demonstrate that the proposed algorithm effectively prevents the underdetermined problem for mixed pixels of different scales and can be integrated into the coarse NDVI downscaling procedure to refine spatial resolution. This study provides a reference for estimating underdetermined mixed pixels and benefits applications that require dealing with the inversion of land cover values directly.

Financial institutions utilize data for the intelligent assessment of personal credit. However, the privacy of financial data is gradually increasing, and the training data of a single financial institution may exhibit problems regarding low data volume and poor data quality. Herein, by fusing federated learning with deep learning (FL-DL), we innovatively propose a dynamic communication algorithm and an adaptive aggregation algorithm as means of effectively solving the following problems, which are associated with personal credit evaluation: data privacy protection, distributed computing, and distributed storage. The dynamic communication algorithm utilizes a combination of fixed communication intervals and constrained variable intervals, which enables the federated system to utilize multiple communication intervals in a single learning task; thus, the performance of personal credit assessment models is enhanced. The adaptive aggregation algorithm proposes a novel aggregation weight formula. This algorithm enables the aggregation weights to be automatically updated, and it enhances the accuracy of individual credit assessment by exploiting the interplay between global and local models, which entails placing an additional but small computational burden on the powerful server side rather than on the resource-constrained client side. Finally, with regard to both algorithms and the FL-DL model, experiments and analyses are conducted using Lending Club financial company data; the results of the analysis indicate that both algorithms outperform the algorithms that are being compared and that the FL-DL model outperforms the advanced learning model.

The recognition of lane line type plays an important role in the perception of advanced driver assistance systems (ADAS). In actual vehicle driving on roads, there are a variety of lane line type and complex road conditions which present significant challenges to ADAS. To address this problem, this paper proposes an improved YOLOv5 method for recognising lane line type. This method can accurately and quickly identify the types of lane lines and can show good recognition results in harsh environments. The main strategy of this method includes the following steps: first, the FasterNet lightweight network is introduced into all the concentrated-comprehensive convolution (C3) modules in the network to accelerate the inference speed and reduce the number of parameters. Then, the efficient channel attention (ECA) mechanism is integrated into the backbone network to extract image feature information and improve the model’s detection accuracy. Finally, the sigmoid intersection over union (SIoU) loss function is used to replace the original generalised intersection over union (GIoU) loss function to further enhance the robustness of the model. Through experiments, the improved YOLOv5s algorithm achieves 95.1% of mAP@0.5 and 95.2 frame·s−1 of FPS, which can satisfy the demand of ADAS for accuracy and real-time performance. And the number of model parameters are only 6M, and the volume is only 11.7 MB, which will be easily embedded into ADAS and does not require huge computing power to support it. Meanwhile, the improved algorithms increase the accuracy and speed of YOLOv5m, YOLOv5l, and YOLOv5x models to different degrees. The appropriate model can be selected according to the actual situation. This plays a practical role in improving the safety of ADAS.

Abstract Background Allergic contact dermatitis (ACD) is a common skin condition characterized by contact hypersensitivity to allergens, accompanied with skin inflammation and a mixed itch and pain sensation. The itch and pain dramatically affects patients’ quality of life. However, still little is known about the mechanisms triggering pain and itch sensations in ACD. Methods We established a mouse model of ACD by sensitization and repetitive challenge with the hapten oxazolone. Skin pathological analysis, transcriptome RNA sequencing (RNA-seq), qPCR, Ca2+ imaging, immunostaining, and behavioral assay were used for identifying gene expression changes in dorsal root ganglion innervating the inflamed skin of ACD model mice and for further functional validations. Results The model mice developed typical ACD symptoms, including skin dryness, erythema, excoriation, edema, epidermal hyperplasia, inflammatory cell infiltration, and scratching behavior, accompanied with development of eczematous lesions. Transcriptome RNA-seq revealed a number of differentially expressed genes (DEGs), including 1436-DEG mRNAs and 374-DEG-long noncoding RNAs (lncRNAs). We identified a number of DEGs specifically related to sensory neuron signal transduction, pain, itch, and neuroinflammation. Comparison of our dataset with another published dataset of atopic dermatitis mouse model identified a core set of genes in peripheral sensory neurons that are exclusively affected by local skin inflammation. We further found that the expression of the pain and itch receptor MrgprD was functionally upregulated in dorsal root ganglia (DRG) neurons innervating the inflamed skin of ACD model mice. MrgprD activation induced by its agonist β-alanine resulted in exaggerated scratching responses in ACD model mice compared with naïve mice. Conclusions We identified the molecular changes and cellular pathways in peripheral sensory ganglia during ACD that might participate in neurogenic inflammation, pain, and itch. We further revealed that the pain and itch receptor MrgprD is functionally upregulated in DRG neurons, which might contribute to peripheral pain and itch sensitization during ACD. Thus, targeting MrgprD may be an effective method for alleviating itch and pain in ACD.

Abstract Background CCCH zinc finger family is one of the largest transcription factor families related to multiple biotic and abiotic stresses. Brassica napus L., an allotetraploid oilseed crop formed by natural hybridization between two diploid progenitors, Brassica rapa and Brassica oleracea. A systematic identification of rapeseed CCCH family genes is missing and their functional characterization is still in infancy. Results In this study, 155 CCCH genes, 81 from its parent B. rapa and 74 from B. oleracea, were identified and divided into 15 subfamilies in B. napus. Organization and syntenic analysis explained the distribution and collinearity relationship of CCCH genes, the selection pressure and evolution of duplication gene pairs in B. napus genome. 44 diploid duplication gene pairs and 4 triple duplication gene groups were found in B. napus of CCCH family and the segmental duplication is attributed to most CCCH gene duplication events in B. napus. Nine types of CCCH motifs exist in B. napus CCCH family members, and motif C-X7/8-C-X5-C-X3-H is the most common and a new conserved CCH motif (C-X5-C-X3-H) has been identified. In addition, abundant stress-related cis-elements exist in promoters of 27 subfamily IX (RR-TZF) genes and their expression profiles indicated that RR-TZF genes could be involved in responses to hormone and abiotic stress. Conclusions The results provided a foundation to understand the basic characterization and genes evolution of CCCH gene family in B. napus, and provided potential targets for genetic engineering in Brassicaceae crops in pursuit of stress-tolerant traits.

Understanding the coordination relationship between ecosystem service (ES) supply and demand and elucidating the impact of driving factors is critical for regional land use planning and ecological sustainability. We use a large watershed area as a case to map and analyze ES supply, demand and the coordination relationship, and identify the associated socio-ecological driving variables. This study assessed the supply and demand of five ESs (crop production, water retention, soil conservation, carbon sequestration, and outdoor recreation) in 2000 and 2020, and evaluated the coordination between them employing the coupling coordination degree model (CCDM). Additionally, we utilized the geo-detector model (GDM) to identify driving determinants and their interactive effects on the spatial pattern of the coupling coordination degree (CCD) between ES supply and demand. The results showed that mountainous regions with abundant forest coverage were high-value areas for ES supply, while the ESs were predominantly required in city center areas within each basin area. From 2000 to 2020, there was a slight decline in ES supply and a significant increase in ES demand. Counties were grouped into four coordination zones in the study area: extreme incoordination, moderate incoordination, reluctant coordination, and moderate coordination. The number of counties with extreme incoordination linked to regions with a mountain ecosystem is increasing, where the ES supply is much greater than the demand. The moderate incoordination counties dominated by a cropland ecosystem exhibited slightly higher levels of ES supply than demand. The moderate and reluctant coordination were linked to counties with distinct ecological characteristics. Construction land played a major role in the characteristics of the CCD, followed by grassland. The interaction between construction land and all other factors significantly increased the influence on the CCD. These findings offered valuable insights for land managers to identify areas characterized by incoordination between ES supply and demand and understand associated factors to develop optimal ES management strategies.

Island microgrids play a crucial role in developing and utilizing offshore renewable energy sources. However, high operation costs and limited operational flexibility are significant challenges. To address these problems, this paper proposes a novel dual−layer distributed optimal operation methodology for islanded microgrids. The lower layer is a distributed control layer that manages multiple controllable distributed fuel−based microturbines (MTs) within the island microgrids. A novel adaptive consensus control method is proposed in this layer to ensure uniform operating status for each MT. Moreover, the proposed method can achieve the total output power of MTs to follow the reference signal provided by the upper layer while ensuring plug−and−play capability for MTs. The upper layer is an optimal scheduling layer that manages various forms of controllable distributed power sources and provides control reference signals for the lower layer. Additionally, a two−stage twin−delayed deterministic policy gradient (MATD3) algorithm is utilized in this layer to minimize the operating costs of island microgrids while ensuring their safe operation. Simulation results demonstrate that the proposed methodology can effectively reduce the operating costs of island microgrids, unify the operational status of MTs, and achieve plug−and−play capability for MTs.

Research shows that across life, the incidence of mental illness is highest in the young. In the context of the COVID-19 pandemic, mental health issues of the young in particular have received global attention. The rostral anterior cingulate cortex (rACC) plays an important role in psychiatric disorders and chronic pain-psychiatric comorbidities. However, it remains unknown whether or how the afferent and efferent circuits of the rACC change with aging. In this study, we microinjected a retrograde tracer virus and an anterograde trans-monosynaptic virus into the rACC of young and middle-aged mice (both male and female), and systematically and quantitatively analyzed the whole-brain afferent and efferent connections of rACC at different ages and sexes. Notably, in young and middle-aged mice, afferents of the rACC belong to four groups of brain structures arising mainly from the amygdala [mainly basolateral amygdaloid nucleus (BLA)] and cerebral cortex (mainly orbital cortex), with a small part originating from the basal forebrain and thalamus. In contrast, efferents of the rACC belong to four groups of brain structures mainly projecting to the thalamus (mainly ventral anterior-lateral/ventromedial thalamic nucleus (VAL/VM)], with a very small part projecting to the amygdala, basal forebrain, and cerebral cortex. Compared with young mice, the BLA-rACC circuit in middle-aged mice (male and female) did not change significantly, while the rACC-VAL/VM circuit in middle-aged mice (male and female) decreased significantly. In conclusion, this study comprehensively analyzed the input-output neural projections of rACC in mice of different ages and sexes and provided preliminary evidence for further targeted research.

Abstract Background Paclitaxel is a widely prescribed chemotherapy drug for treating solid tumors. However, paclitaxel-induced peripheral neuropathy (PIPN) is a common adverse effect during paclitaxel treatment, which results in sensory abnormalities and neuropathic pain among patients. Unfortunately, the mechanisms underlying PIPN still remain poorly understood. Long noncoding RNAs (lncRNAs) are novel and promising targets for chronic pain treatment, but their involvement in PIPN still remains unexplored. Methods We established a rat PIPN model by repetitive paclitaxel application. Immunostaining, RNA sequencing (RNA-Seq) and bioinformatics analysis were performed to study glia cell activation and explore lncRNA/mRNA expression profiles in spinal cord dorsal horn (SCDH) of PIPN model rats. qPCR and protein assay were used for further validation. Results PIPN model rats developed long-lasting mechanical and thermal pain hypersensitivities in hind paws, accompanied with astrocyte and microglia activation in SCDH. RNA-Seq identified a total of 814 differentially expressed mRNAs (DEmRNA) (including 467 upregulated and 347 downregulated) and 412 DElncRNAs (including 145 upregulated and 267 downregulated) in SCDH of PIPN model rats vs. control rats. Functional analysis of DEmRNAs and DElncRNAs identified that the most significantly enriched pathways include immune/inflammatory responses and neurotrophin signaling pathways, which are all important mechanisms mediating neuroinflammation, central sensitization, and chronic pain. We further compared our dataset with other published datasets of neuropathic pain and identified a core set of immune response-related genes extensively involved in PIPN and other neuropathic pain conditions. Lastly, a competing RNA network analysis of DElncRNAs and DEmRNAs was performed to identify potential regulatory networks of lncRNAs on mRNA through miRNA sponging. Conclusions Our study provided the transcriptome profiling of DElncRNAs and DEmRNAs and uncovered immune and inflammatory responses were predominant biological events in SCDH of the rat PIPN model. Thus, our study may help to identify promising genes or signaling pathways for PIPN therapeutics.

Leptospirosis, caused by pathogenic Leptospira species, has emerged as a widespread zoonotic disease worldwide. Macrophages mediate the elimination of pathogens through phagocytosis and cytokine production. Scavenger receptor A1 (SR-A1), one of the critical receptors mediating this process, plays a complicated role in innate immunity. However, the role of SR-A1 in the immune response against pathogenic Leptospira invasion is unknown. In the present study, we found that SR-A1 is an important nonopsonic phagocytic receptor on murine macrophages for Leptospira. However, intraperitoneal injection of leptospires into WT mice presented with more apparent jaundice, subcutaneous hemorrhaging, and higher bacteria burdens in blood and tissues than that of SR-A1-/- mice. Exacerbated cytokine and inflammatory mediator levels were also observed in WT mice and higher recruited macrophages in the liver than those of SR-A1-/- mice. Our findings collectively reveal that although beneficial in the uptake of Leptospira by macrophage, SR-A1 might be exploited by Leptospira to modulate inflammatory activation and increase the susceptibility of infection in the host. These results provide our new insights into the innate immune response during early infection by L. interrogans.

Complex regional pain syndrome type-I (CRPS-I) is a chronic neurological disorder that results in severe pain and affects patients' life quality. Conventional therapies usually lack effectiveness. Electroacupuncture (EA) is an effective physical therapy for relieving CRPS-I pain. However, the mechanism underlying EA-induced analgesia on CRPS-I still remain unknown. Spinal NLRP3 inflammasome was recently identified to contribute to pain and neuroinflammation in a rat model of CRPS-I by our group. Here, we aimed to study whether EA could inhibit spinal NLRP3 inflammasome activation, thus resulting in pain relief and attenuation of spinal neuroinflammation in the rat model of CRPS-I. We established the rat chronic post-ischemic pain (CPIP) model to mimic CRPS-I. CPIP rats developed remarkable mechanical allodynia that could be relieved by daily EA intervention. NLRP3 inflammasome was activated in spinal cord dorsal horn (SCDH) of CPIP rats, accompanied with over-production of pro-inflammatory cytokine IL-1β. Immunostaining revealed that the cellular distribution of NLRP3 was predominantly located in SCDH neurons. Pharmacological activation of NLRP3 inflammasome per se is sufficient to produce persistent mechanical allodynia in naïve animals, whereas blocking NLRP3 inflammasome attenuates mechanical allodynia of CPIP rats. EA exclusively reduced NLRP3 overexpression in SCDH neurons and attenuated spinal glial cell over-activation in CPIP rats. EA-induced anti-allodynia with attenuation of spinal glial cell over-activation were all mimicked by intrathecal blocking NLRP3 inflammasome and reversed by activating NLRP3 inflammasome, respectively, through pharmacological methods. Finally, spinal blocking IL-1β attenuated mechanical allodynia and spinal glial cell over-activation in CPIP rats, resembling the effects of EA. In all, these results demonstrate that spinal NLRP3 inflammasome activation contributes to mechanical allodynia of the rat model of CRPS-I and EA ameliorates mechanical allodynia through inhibiting NLRP3 inflammasome activation in SCDH neurons. Our study further supports EA can be used as an effective treatment for CRPS-I.

Ascorbate peroxidase (APX) plays an important role in scavenging H2O2 and balancing ROS content in plant cells, which is of great significance for the growth and development of life and resistance to external stress. However, up to now, APXs in Brassica napus (B. napus) have not been systematically characterized. In this study, a total of 26 BnaAPX genes were identified, which were distributed on 13 chromosomes and divided into five phylogenetic branches. Gene structure analysis showed that they had a wide varied number of exons while BnaAPXs proteins contained more similar motifs in the same phylogenetic branches. qRT-PCR analysis of 26 BnaAPX gene expression patterns showed that three putative cytosol BnaAPX genes BnaAPX1, BnaAPX2, BnaAPX9, two putatice microsomal genes BnaAPX18 and BnaAPX25 were up-regulated rapidly and robustly under high salt, water shortage and high temperature stresses. In addition, the above three abiotic stresses led to a significant increase in APX activity. The results provide basic and comprehensive information for further functional characterization of APX gene family in B. napus.

Abstract Background Complex regional pain syndrome type-I (CRPS-I) is a progressive and devastating pain condition. The mechanisms of CRPS-I still remain poorly understood. We aim to explore expression profiles of genes relevant to pain and neuroinflammation mechanisms involved in CRPS-I. Methods The rat chronic post-ischemic pain (CPIP) model that mimics human CRPS-I was established. RNA-sequencing (RNA-Seq), qPCR, Western blot, immunostaining, and pharmacological studies were used for profiling gene changes in ipsilateral spinal cord dorsal horn (SCDH) of CPIP model rat and further validation. Results CPIP rats developed persistent mechanical allodynia in bilateral hind paws, accompanied with obvious glial activation in SCDH. RNA-Seq identified a total of 435 differentially expressed genes (DEGs) in ipsilateral SCDH of CPIP rats. qPCR confirmed the expression of several representative genes. Functional analysis of DEGs identified that the most significantly enriched biological processes of upregulated genes include inflammatory and innate immune response. We further identified NLRP3 inflammasome expression to be significantly upregulated in SCDH of CPIP rats. Pharmacological blocking NLRP3 inflammasome reduced IL-1β overproduction, glial activation in SCDH as well as mechanical allodynia of CPIP rats. Conclusion Our study revealed that immune and inflammatory responses are predominant biological events in SCDH of CPIP rats. We further identified NLRP3 inflammasome in SCDH as a key contributor to the pain and inflammation responses in CPIP rats. Thus, our study provided putative novel targets that may help to develop effective therapeutics against CRPS-I.

While IgM and IgG response to SARS-CoV-2 has been extensively studied, relatively little is known about secretory IgA (sIgA) response in respiratory mucosa. Here we report IgA response to the SARS-CoV-2 in sputum, throat swabs, and serum with nucleocapsid protein (NP) enzyme-linked immunosorbent assays (ELISA) in a cohort of 28 COVID-19 patients and 55 vaccine recipients. The assays showed sIgA in respiratory mucosa could be detected on the first day after illness onset (AIO), and the median conversion time for sIgA in sputum, throat swabs, and serum was 3, 4, and 10 days, respectively. The positive rates of sIgA first week AIO were 100% (24/28) and 85.7% (24/28) in sputum and throat swabs, respectively, and were both 100% during the mid-onset (2–3 weeks AIO). During the recovery period, sIgA positive rates in sputum and throat swabs gradually decreased from 60.7% (17/28) and 57.1% (16/28) 1 month AIO and the sIgA antibodies were all undetectable 6 months AIO. However, serum IgA positive rate was still 100% at 4 months and 53.6% (15/28) at 6 months. Throat swabs obtained from volunteers who received inactivated SARS-CoV-2 vaccines by intramuscular delivery all showed negative results in IgA ELISA. These findings will likely improve our understanding of respiratory mucosal immunity of this emerging disease and help in containing the pandemic and developing vaccines.

Neuropathic pain is a common cause of chronic pain and is often accompanied by negative emotions, making it complex and difficult to treat. However, the neural circuit mechanisms underlying these symptoms remain unclear. Herein, we present a novel pathway associated with comorbid chronic pain and anxiety. Using chemogenetic methods, we found that activation of glutamatergic projections from the rostral anterior cingulate cortex (rACCGlu) to the ventrolateral periaqueductal gray (vlPAG) induced both hyperalgesia and anxiety-like behaviors in sham mice. Inhibition of the rACCGlu-vlPAG pathway reduced anxiety-like behaviors and hyperalgesia in the spared nerve injury (SNI) mice model; moreover, electroacupuncture (EA) effectively alleviated these symptoms. Investigation of the related mechanisms revealed that the chemogenetic activation of the rACCGlu-vlPAG circuit effectively blocked the analgesic effect of EA in the SNI mice model but did not affect the chronic pain-induced negative emotions. This study revealed a novel pathway, the rACCGlu-vlPAG pathway, that mediates neuropathic pain and pain-induced anxiety.

Metabolic syndrome (MetS) is an independent risk factor for hepatocellular cancer (HCC). Currently, there is no highly sensitive and specific biomarkers for HCC surveillance in MetS population. Metabolomics has been reported as a powerful technology for biomarker discovery. In the present study, we aimed to explore novel biomarkers with high sensitivity and specificity for MetS-positive [MetS(+)] HCC by metabolomic analysis. At first, many serum metabolites were found dysregulated in MetS(+) HCC individuals. Validation of the dysregulated metabolites by targeted metabolite analyses revealed that serum L-glutamic acid (L-glu), pipecolic acid (PA) and 7-methylguanine (7-mG) were increased in MetS(+) HCC compared to MetS group. Then a biomarker panel including L-glu, PA and alpha-fetoprotein (AFP) was identified as a novel biomarker for the diagnosis of MetS(+) HCC. Receiver operating characteristic (ROC) curve was drawn and the area under the ROC curve (AUC) was 0.87 for discriminating MetS(+) HCC from MetS group. The biomarker panel was capable of detecting small (AUC = 0.82) and early-stage (AUC = 0.78) tumors as well. Moreover, it exhibited great diagnostic performance (AUC = 0.93) for discriminating MetS(+) HCC from other MetS-associated cancers, including colorectal cancer and gastric cancer. Collectively, our study establishes a novel diagnostic tool for MetS(+) HCC.

AZ61 magnesium alloy sheets can be applied as 3C (computer, communication, and consumer) electronic product shells. However, due to their poor plasticity and relatively low strength, the application of AZ61 alloy sheets is limited. The composition modification of AZ61, especially rare earth element alloying, is a good choice to improve the strength and plasticity of AZ61 alloy sheets. In this paper, the strength and plasticity of AZ61 sheets with different contents of Y were studied in detail. We found that the addition of 0.9 wt.% of Y not only improved the strength, but also significantly enhanced the plasticity. As a result, the yield strength of AZ61 increased from 167 MPa to 186 MPa, and the elongation increased from 9.5% to 18%. The reasons can be explained as follows: the Al2Y phase formed by adding Y consumed a large amount of the Al element, thus avoiding the formation of the brittle phases Al8Mn5 and resulting in the improved mechanical properties of the sheets. At the same time, the weakened texture and dispersed grain orientation also effectively improved the plasticity of the sheets. This study will provide a good solution to improve the strength and plasticity of AZ61 sheets without significantly increasing the production cost.

AZ31 magnesium alloy sheets can be applied as 3C electronic product shells. However, AZ31 sheets exhibit obvious anisotropy, which limits their industrial application range. The composition modification of AZ31 is a good choice to improve the anisotropy of the sheets, but the effect of the multi-element micro-alloying on the microstructure and anisotropy of AZ31 alloy sheets is still less investigated. For this aim, the plasticity and anisotropy of AZ31 sheets after adding Ca and rare earth elements such as Y and Gd were investigated in this paper. It is found that, different from the alloying role of single Ca or Ca and Y, the composite addition of 0.2Ca and 0.2Gd can obviously enhance the anisotropy of AZ31 alloy sheets. As a result, the elongation of AZ31 in the rolling direction (RD) direction, 45° direction, and transverse direction (TD) direction is increased from 12.5% to 22%, from 5% to 18.5%, and from 1.5% to 8.5%, respectively. This can be explained as follows: the Al8Mn4Gd phase formed by the addition of Gd consumes a lot of Mn, thus avoiding the formation of brittle phases Al8Mn5 and leading to the improved mechanical properties of the alloy sheets. This study will offer a good solution for enhancing the formability of AZ31 sheets under the condition of not significantly increasing the production costs.