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Background Microglial activation-mediated neuroinflammation plays an important role in the progression of neurodegenerative diseases. Inflammatory activation of microglial cells is often accompanied by a metabolic switch from oxidative phosphorylation to aerobic glycolysis. However, the roles and molecular mechanisms of glycolysis in microglial activation and neuroinflammation are not yet fully understood. Methods The anti-inflammatory effects and its underlying mechanisms of glycolytic inhibition in vitro were examined in lipopolysaccharide (LPS) activated BV-2 microglial cells or primary microglial cells by enzyme-linked immunosorbent assay (ELISA), quantitative reverse transcriptase-polymerase chain reaction (RT-PCR), Western blot, immunoprecipitation, flow cytometry, and nuclear factor kappa B (NF-κB) luciferase reporter assays. The anti-inflammatory and neuroprotective effects of glycolytic inhibitor, 2-deoxoy- d -glucose (2-DG) in vivo were measured in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-or LPS-induced Parkinson’s disease (PD) models by immunofluorescence staining, behavior tests, and Western blot analysis. Results We found that LPS rapidly increased glycolysis in microglial cells, and glycolysis inhibitors (2-DG and 3-bromopyruvic acid (3-BPA)), siRNA glucose transporter type 1 (Glut-1), and siRNA hexokinase (HK) 2 abolished LPS-induced microglial cell activation. Mechanistic studies demonstrated that glycolysis inhibitors significantly inhibited LPS-induced phosphorylation of mechanistic target of rapamycin (mTOR), an inhibitor of nuclear factor-kappa B kinase subunit beta (IKKβ), and NF-kappa-B inhibitor alpha (IκB-α), degradation of IκBα, nuclear translocation of p65 subunit of NF-κB, and NF-κB transcriptional activity. In addition, 2-DG significantly inhibited LPS-induced acetylation of p65/RelA on lysine 310, which is mediated by NAD-dependent protein deacetylase sirtuin-1 (SIRT1) and is critical for NF-κB activation. A coculture study revealed that 2-DG reduced the cytotoxicity of activated microglia toward MES23.5 dopaminergic neuron cells with no direct protective effect. In an LPS-induced PD model, 2-DG significantly ameliorated neuroinflammation and subsequent tyrosine hydroxylase (TH)-positive cell loss. Furthermore, 2-DG also reduced dopaminergic cell death and microglial activation in the MPTP-induced PD model. Conclusions Collectively, our results suggest that glycolysis is actively involved in microglial activation. Inhibition of glycolysis can ameliorate microglial activation-related neuroinflammatory diseases.

Deep-learning-based object detection algorithms have significantly improved the performance of wheat spike detection. However, UAV images crowned with small-sized, highly dense, and overlapping spikes cause the accuracy to decrease for detection. This paper proposes an improved YOLOv5 (You Look Only Once)-based method to detect wheat spikes accurately in UAV images and solve spike error detection and miss detection caused by occlusion conditions. The proposed method introduces data cleaning and data augmentation to improve the generalization ability of the detection network. The network is rebuilt by adding a microscale detection layer, setting prior anchor boxes, and adapting the confidence loss function of the detection layer based on the IoU (Intersection over Union). These refinements improve the feature extraction for small-sized wheat spikes and lead to better detection accuracy. With the confidence weights, the detection boxes in multiresolution images are fused to increase the accuracy under occlusion conditions. The result shows that the proposed method is better than the existing object detection algorithms, such as Faster RCNN, Single Shot MultiBox Detector (SSD), RetinaNet, and standard YOLOv5. The average accuracy (AP) of wheat spike detection in UAV images is 94.1%, which is 10.8% higher than the standard YOLOv5. Thus, the proposed method is a practical way to handle the spike detection in complex field scenarios and provide technical references for field-level wheat phenotype monitoring.

Surface defect detection is essential for ensuring the quality and safety of steel products. While Transformer-based methods have achieved state-of-the-art performance, they face several limitations, including high computational costs due to the quadratic complexity of the attention mechanism, inadequate detection accuracy for small-scale defects due to substantial downsampling, inconsistencies between classification scores and localization confidence, and feature resolution loss caused by simple upsampling and downsampling strategies. To address these challenges, we propose the HCT-Det model, which incorporates a window-based self-attention residual (WSA-R) block structure. This structure combines window-based self-attention (WSA) blocks to reduce computational overhead and parallel residual convolutional (Res) blocks to enhance local feature continuity. The model’s backbone generates three cross-scale features as encoder inputs, which undergo Intra-Scale Feature Interaction (ISFI) and Cross-Scale Feature Interaction (CSFI) to improve detection accuracy for targets of various sizes. A Soft IoU-Aware mechanism ensures alignment between classification scores and intersection-over-union (IoU) metrics during training. Additionally, Hybrid Downsampling (HDownsample) and Hybrid Upsampling (HUpsample) modules minimize feature degradation. Our experiments demonstrate that HCT-Det achieved a mean average precision (mAP@0.5) of 0.795 on the NEU-DET dataset and 0.733 on the GC10-DET dataset, outperforming other state-of-the-art approaches. These results highlight the model’s effectiveness in improving computational efficiency and detection accuracy for steel surface defect detection.

The role of the built environment in improving public health through fostering physical activity has come under increased scrutiny in recent years. This study investigates relationships between walking activity and the configuration of green spaces in Greater London. Pedestrian activity for N = 54,910 walking trip stages is gathered through the London Travel Demand Survey (LTDS), with routes between origin and destination mapped onto the street network from the Integrated Transport Network of Ordnance Survey. Green spaces were extracted from UKMap and agglomerated to form London’s hundreds of parks. Regressions of pedestrian activity on park configuration, controlling for built environment metrics, revealed that catchments around smaller parks have more walking trips. Irregularity of park shape has the opposite effect. Park density, measured as number of parks inside a catchment, is insignificant in regression. Parks adjacent to retail areas were associated with pronounced increases in walking. The study contributes to landscape, urban management, environmental policy and urban planning and design literature. The evidence provides implications for performance-oriented policy and design decisions that configure a city’s green spaces to improve citizens’ public health through enhancing walkability. 近年来，建筑环境通过促进体育活动改善公共健康的作用受到越来越多的关注。本研究调查了大伦敦步行活动和绿地配置之间的关系。54,910个步行行程路段的行人活动通过伦敦旅行需求调查 (LTDS) 收集，起点和终点之间的路线通过英国地形测量局综合运输网络 (Integrated Transport Network of Ordnance Survey) 映射到街道网络。绿色空间是从英国地图中提取出来的，聚集在一起形成了伦敦的数百个公园。我们对公园配置中的行人活动进行回归分析（控制建筑环境指标的影响），发现较小公园的辐射区域内有更多的步行行程。公园形状的不规则性则有相反的效果。公园密度以辐射区域内公园的数量来衡量，在回归分析中不具有重要性。零售区附近的公园与步行显著增加有关。这项研究为城市绿化、城市管理、环境政策和城市规划和设计文献做出了贡献。这些证据为注重性能的政策和设计决策提供了启示，这些政策和决策通过配置城市绿地来增强可步行性，以改善市民的健康。

The Lightning Mapping Imager (LMI) onboard the geostationary meteorological satelliteFengYun-4A (FY-4A) detects both intra-cloud (IC) and cloud-to-ground (CG) lightning continuously during daytime and nighttime. This study examined, for the first time, the optical characteristics and distribution of the “Event,” “Group,” and “Flash” observed by the LMI in the whole LMI observation domain. The optical properties and spatial distribution of the LMI lightning were compared with those of the Lightning Imaging Sensor on the International Space Station (ISS-LIS) based on the dataset during 2018–2020. Due to the different spatial resolutions and detection efficiencies of these two lightning imagers, the number of ISS-LIS lightning was more than that of LMI lightning. The ISS-LIS Flash duration was also larger than that of the LMI Flash. The duration, radiance, and footprint of LMI lightning in different regions were analyzed in detail based on the LMI lightning dataset in 2019. The duration and radiance of the Flash were generally less than 50–500 ms and 200 Jm−2ster−1μm−1, respectively. The footprint of Flashes was distributed from 200 to 600 km2. The number of Groups per Flash was mostly less than five. Considering the spatial distribution and temporal variations in the LMI lightning compared with the ground-based Lightning Location Network in China (LLNC), it was found that the LMI Group number was close to the LLNC CG (Cloud-to-Ground) Event number. The maximum Flash density was found in the middle and lower south of the Yangtze River and Pearl River Delta region, respectively, while the lower values were in western China, where the mean radiance per Flash was greater. There was more LMI lightning during the nighttime than that during the daytime, indicating the higher detection efficiency of the LMI in the nighttime than in the daytime.

Non-rigid point cloud registration holds significant importance for human body pose analysis in the fields of sports, medicine, gaming, etc. In this paper, we propose a non-rigid point cloud registration algorithm based on geodesic distance measurement, which can improve the accuracy of the registration for matching point pairs during non-rigid deformations. Firstly, a graph is constructed for two sets of point clouds using geodesic distance measurement considering that geodesic distance changes minimally during non-rigid deformation of the human body, which can preserve the point cloud matching information between corresponding points. Furthermore, a maximal clique search is employed to find combinations of matching pairs between point clouds. Finally, by driving the human body model parameters, sparse matching pairs are overlapped as much as possible to achieve non-rigid point cloud registration of the human body. The accuracy of the proposed algorithm is verified with FAUST and CAPE datasets.

This study aimed to construct a novel pelvis-prostate model BPPP which consists of body mass index (BMI), prostate volume (PV), pelvic cavity index (PCI) and prostate-muscle index (PMI) to predict the immediate urinary continence after Retzius-sparing robot assisted laparoscopic radical prostatectomy (RS-RARP). The perioperative data of patients with prostate cancer who underwent RS-RARP in the department of urology of Nanjing Drum Tower Hospital from June 2018 to June 2022 were retrospectively analyzed. 280 patients were eligible for this study in total. Multivariate analysis showed that BMI, PV, PCI, PMI and NVB preservation were significantly associated with immediate urinary continence after RS-RARP. Subgroup analysis showed that patients with low BMI, low PV, high PCI and high PMI had a higher recovery rate of immediate urinary continence. The area under the curve of BPPP (BMI + PV + PCI + PMI) for predicting the immediate recovery of urinary continence after RS-RARP was 0.726. Delong test showed that the area under the curve of the combined test for predicting the immediate urinary continence after RS-RARP was better compared with single parameter ( p  < 0.05). In conclusion the novel pelvis-prostate model BPPP may predict the immediate urinary continence after RS-RARP, providing information for preoperative decision-making.

Background: The Wilms’ tumor suppressor gene (WT1) is a critical regulator in kidney development and disease pathogenesis. With the identification of at least 36 isoforms in mammals, each potentially playing distinct roles, WT1’s complexity is becoming increasingly apparent. The −KTS and +KTS isoforms, in particular, have been implicated in DNA and RNA regulation, respectively. This review consolidates recent insights into WT1’s multifaceted role in renal morphogenesis and its implications in kidney diseases. Summary: Our review highlights WT1’s expression during embryonic kidney development and its maintenance in postnatal kidney function. We discuss the association of WT1 mutations with genetic nephropathies like Denys-Drash and Frasier syndromes, emphasizing its genetic significance. Additionally, we explore the implications of WT1 expression alterations in glomerular diseases, such as IgA nephropathy and lupus nephritis, where its role extends beyond a mere biomarker to a potential therapeutic target. Key Messages: The WT1 gene and its protein products are central to understanding kidney morphogenesis and the molecular basis of renal disorders. As our understanding of WT1’s regulatory mechanisms expands, so does the potential for developing targeted therapies for kidney diseases. This review calls for further research to elucidate the precise functions of WT1 isoforms and to explore the upstream regulators of WT1 that could offer novel treatment strategies for kidney pathologies. The significance of WT1 in intricate signaling pathways governing kidney health and disease is underscored, highlighting the need for continued investigation into this pivotal gene.

Necroptosis is a form of regulated necrosis controlled by receptor-interacting kinase 1 (RIPK1 or RIP1), RIPK3 (RIP3), and pseudokinase mixed lineage kinase domain-like protein (MLKL). Increasing evidence suggests that necroptosis is closely associated with pathologies including inflammatory diseases, neurodegenerative diseases, and cancer metastasis. Herein, we discovered the small-molecule PK6 and its derivatives as a novel class of necroptosis inhibitors that directly block the kinase activity of RIPK1. Optimization of PK6 led to PK68, which has improved efficacy for the inhibition of RIPK1-dependent necroptosis, with an EC 50 of around 14–22 nM in human and mouse cells. PK68 efficiently blocks cellular activation of RIPK1, RIPK3, and MLKL upon necroptosis stimuli. PK68 displays reasonable selectivity for inhibition of RIPK1 kinase activity and favorable pharmacokinetic properties. Importantly, PK68 provides strong protection against TNF-α-induced systemic inflammatory response syndrome in vivo. Moreover, pre-treatment of PK68 significantly represses metastasis of both melanoma cells and lung carcinoma cells in mice. Together, our study demonstrates that PK68 is a potent and selective inhibitor of RIPK1 and also highlights its great potential for use in the treatment of inflammatory disorders and cancer metastasis.

China’s high‐speed rail (HSR) system has expanded rapidly, with stations now serving nearly all major cities across the country. The network is structured around the “Eight Verticals and Eight Horizontals” framework, which possesses several distinct characteristics. This study utilizes train schedule data to extract station information for constructing an origin–destination (O/D) matrix. Methods including centrality measurement, edge strength analysis, correlation analysis, and GIS visualization are employed to examine the hierarchical structure of China’s HSR network at both national and urban agglomeration scales. The findings reveal that (1) most cities have limited train services and low connectivity, while cities with high connectivity are relatively few and concentrated in regions such as Beijing–Tianjin–Hebei (BTH) and the Yangtze River Delta (YRD). The degree distribution follows an exponential pattern and aligns with the “80/20” rule, and the network exhibits small‐world properties. (2) Based on nodal degree, HSR cities are classified into four tiers, which exhibit a pyramid‐shaped distribution in terms of both quantity and proportion. Geographically, these cities are predominantly located southeast of the “Heihe–Tengchong Line,” with notable clusters along the Yangtze River and coastal areas. (3) Network edges are also categorized into four levels. First‐level edges connect economically developed cities such as Beijing, Shanghai, and Shenzhen, while second‐level edges are mainly distributed along the Yangtze River corridor. (4) Among the major urban agglomerations, the YRD and Mid‐Yangtze River (MYR) regions show the highest centrality, followed by BTH and the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). The Chengdu–Chongqing (CC) region ranks the lowest. Relative centrality analysis indicates a clear hierarchical distribution within agglomerations such as YRD, whereas GBA and CC display more fragmented connectivity patterns. The network structures across regions are diverse: YRD is oriented east–west, MYR forms a triangular layout, CC exhibits a radial pattern, BTH resembles a “Z” shape, and GBA is structured like a tree.