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Abstract Germinal center (GC) formation, which is an integrant part of humoral immunity, involves energy-consuming metabolic reprogramming. Rag-GTPases are known to signal amino acid availability to cellular pathways that regulate nutrient distribution such as the mechanistic target of rapamycin complex 1 (mTORC1) pathway and the transcription factors TFEB and TFE3. However, the contribution of these factors to humoral immunity remains undefined. Here, we show that B cell-intrinsic Rag-GTPases are critical for the development and activation of B cells. RagA/RagB deficient B cells fail to form GCs, produce antibodies, and to generate plasmablasts during both T-dependent (TD) and T-independent (TI) humoral immune responses. Deletion of RagA/RagB in GC B cells leads to abnormal dark zone (DZ) to light zone (LZ) ratio and reduced affinity maturation. Mechanistically, the Rag-GTPase complex constrains TFEB/TFE3 activity to prevent mitophagy dysregulation and maintain mitochondrial fitness in B cells, which are independent of canonical mTORC1 activation. TFEB/TFE3 deletion restores B cell development, GC formation in Peyer’s patches and TI humoral immunity, but not TD humoral immunity in the absence of Rag-GTPases. Collectively, our data establish the Rag GTPase-TFEB/TFE3 pathway as a likely mTORC1 independent mechanism to coordinating nutrient sensing and mitochondrial metabolism in B cells.

Abstract Ubiquitination functions as an important posttranslational modification for orchestrating inflammatory immune responses and cell death during pathogenic infection. The ubiquitination machinery is a major target hijacked by pathogenic bacteria to promote their survival and proliferation. Type I interferon (IFN-I) plays detrimental roles in host defense against Francisella novicida (F. novicida) infection. The effects of IFN-I on the ubiquitination of host proteins during F. novicida infection remain unclear. Herein, we delineate the dynamic ubiquitinome alterations in both wild-type (WT) and interferon-alpha receptor-deficient (Ifnar –/–) primary bone marrow-derived macrophages (BMDMs) during F. novicida infection. Using diGly proteomics and stable isotope labeling (SILAC), we quantified ubiquitination sites in proteins from primary WT and Ifnar –/– BMDMs with and without F. novicida infection. Our mass spectrometry analysis identified 2,491 ubiquitination sites in 1,077 endogenous proteins. Our study revealed that F. novicida infection induces dynamic changes in the ubiquitination of proteins involved in the cell death, phagocytosis, and inflammatory response pathways. IFN-I signaling is essential for both the increase and reduction in ubiquitination in response to F. novicida infection. We identified IFN-I-dependent ubiquitination in proteins involved in glycolysis and vesicle transport processes and highlighted key hub proteins modified by ubiquitination within cell death pathways. These findings underscore the significant influence of IFN-I signaling on modulating ubiquitination during F. novicida infection and provide valuable insights into the complex interplay between the host and F. novicida.

This paper presents the flexural property of damaged steel-concrete composite girders strengthened with CFRP sheet or prestressed CFRP sheet. Test and numerical analysis were used in the girders. The test findings indicated that the damage level had a substantial impact on the stiffness, yield strength, and ultimate load. And because of the CFRP sheet or prestressed CFRP sheet, the ultimate bearing capability could increase. The findings of the numerical analysis indicated that the increase of concrete strength would improve the stiffness and bearing capability. Increasing the web’s thickness and the steel beam’s flange by 1 mm would result in an approximate increase in the carrying capacity of roughly 4% and 3.8%, respectively. The damage level had a substantial impact on the stiffness and ultimate bearing capability. The bearing capacity would increase by about 2.8% with each additional 0.05 mm of thickness in the CFRP sheet. When the prestressed degree increased by per 5%, the bearing capacity would experience a 1.4% rise and the CFRP sheet’s stress would increase.

The static sealing of underground gas storage (UGS), including the integrity of cap rocks and the stability of faults, is analyzed from a macro perspective using a comprehensive geological evaluation method. Changes in pore structure, permeability, and mechanical strength of cap rocks under cyclic loads may impact the rock sealing integrity during the injection and recovery phases of UGS. In this work, the mechanical deformation and failure tests of rocks, as well as rock damage tests under alternating loads, are conducted to analyze the changes in the strength and permeability of rocks under multiple-cycle intense injection and recovery of UGS. Additionally, this study proposes an evaluation method for the dynamic sealing performance of UGS cap rocks under multi-cycle alternating loads. The findings suggest that the failure strength (70%) can be used as the critical value for rock failure, thus providing theoretical support for determining the upper limit of operating pressure and the number of injection-recovery cycles for the safe operation of a UGS system.

The world faces two significant challenges: promoting sustainable economic growth and reaching carbon neutrality. In BRICS countries, these challenges are shaped by renewable energy, green taxes, and trade openness. These countries were selected for their strategic location and the abundance of relevant data collected over the period of 1990–2021, providing a distinctive window into the energy and economic dynamics of the area. The link between renewable energy consumption, green taxes, trade openness, and natural resources and their effects on carbon emissions in BRICS countries is examined in this study using the Fully Modified Ordinary Least Square Method (FMOLS) estimator and the Drisc Kraay estimator for the robustness test. The findings indicate that using renewable energy and green taxes primarily contribute to reducing emissions, particularly at higher emissions levels. The study reveals that various factors, namely financial globalization, trade openness, efficient resource management, and population growth, substantially impact carbon neutrality. Population growth positively impacts carbon neutrality, while using renewable energy sources mitigates it. Furthermore, the empirical findings show a statistically significant positive association between financial globalization, efficient resource management, and carbon neutrality in BRICS nations. Therefore, it is necessary to implement an integrated ecological governance strategy to control and direct financial resources towards sustainable development and green energy.

Based on the engineering background of the wide-width single cable-stayed bridge, the shear lag effects of the cross-section of these bridge box girders under the action of the eccentric load were experimentally studied. The behavior of shear lag effects in the horizontal and longitudinal bridge directions under eccentric load in the operational stage of a single cable-stayed bridge was analyzed by a model testing method and a finite element (FE) analytical method. The results showed that the plane stress calculation under unidirectional live load was similar to the results from spatial FE analysis and structural calculations performed according to the effective flange width described in the design specification. At the position of the main beam near the cable force point of action, the positive stress at its upper wing edge was greatest. At a distance from the cable tension point, the maximum positive stress position trend showed that from the center of the top flange to the junction of the top flange and the middle web to the junction of the top flange and the middle web and the side web. Under eccentric load, the positive and negative shear lag effects on the end fulcrum existed at the same time, and the shear lag coefficient on the web plate was larger than the shear lag coefficient on the unforced side. Due to the influence of constraint at the middle fulcrum near the middle pivot point, positive and negative shear lag effects were significant, and the coefficient variation range was large, resulting in large tensile stress on the roof plate in this area. According to FE analytical results, stress and shear forces of a single box three-chamber box girder under eccentric load were theoretically analyzed, the bending load decomposed into the accumulation of bending moment and axial force, using the bar simulation method, and the overall shear lag effect coefficient λ was obtained and verified.

Abstract The images captured by forest nighttime imaging devices are prone to degradation and noise issues due to environmental constraints. This paper proposes a novel framework based on the self‐calibrating illumination framework to improve image quality. The framework consists of four specific steps: (1) addressing non‐uniform degradation by estimating illuminance components through non‐uniform MaxRGB, (2) extracting rich information using multi‐scale inflationary convolution, (3) analyzing the relationship between different input levels and the initial level and progressively adjusting the luminance components using a channel self‐calibration module to achieve continuous improvement in luminance, and (4) designing a reflectance optimization module that enhances illuminance while suppressing noise through a regularization model. To evaluate the proposed method, a dataset comprising 1000 forest night images is constructed using an image simulation strategy. The effectiveness of this method was validated on both synthetic and real datasets, demonstrating its ability to significantly enhance nighttime forest images. When compared to six other algorithms, this method outperformed them in eight evaluation metrics, including a peak signal‐to‐noise ratio metric of 22.839 and a structural similarity metric of 0.909. The experimental results clearly indicate that this method excels in enhancing image quality and fidelity.

IntroductionThe increasing incidence of stroke globally has led to dysphagia becoming one of the most common complications in stroke patients, with significant impacts on patient outcomes. Accurate early screening for dysphagia is crucial to avoid complications and improve patient quality of life.MethodsIncluded studies involved stroke-diagnosed patients assessed for dysphagia using bedside screening tools. Data was sourced from Embase, PubMed, Web of Science, Scopus, and CINAHL, including publications up to 10 December 2023. The study employed both fixed-effect and random-effects models to analyze sensitivity, specificity, positive predictive value (PPV), and Negative Predictive Value (NPV), each with 95% confidence intervals. The random-effects model was particularly utilized due to observed heterogeneity in study data.ResultsFrom 6,979 records, 21 studies met the inclusion criteria, involving 3,314 participants from 10 countries. The analysis included six assessment tools: GUSS, MASA, V-VST, BSST, WST, and DNTA, compared against gold-standard methods VFSS and FEES. GUSS, MASA, and V-VST showed the highest reliability, with sensitivity and specificity rates of 92% and 85% for GUSS, 89% and 83% for MASA, respectively. Heterogeneity among studies was minimal, and publication bias was low, enhancing the credibility of the findings.ConclusionOur network meta-analysis underscores the effectiveness of GUSS, MASA, and V-VST in dysphagia screening for stroke patients, with high sensitivity and specificity making them suitable for diverse clinical settings. BSST and WST, with lower diagnostic accuracy, require more selective use. Future research should integrate patient-specific outcomes and standardize methodologies to enhance dysphagia screening tools, ultimately improving patient care and reducing complications.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/#recordDetails.

Styxl2, a poorly characterized pseudophosphatase, was identified as a transcriptional target of the Jak1-Stat1 pathway during myoblast differentiation in culture. Styxl2 is specifically expressed in vertebrate striated muscles. By gene knockdown in zebrafish or genetic knockout in mice, we found that Styxl2 plays an essential role in maintaining sarcomere integrity in developing muscles. To further reveal the functions of Styxl2 in adult muscles, we generated two inducible knockout mouse models: one with Styxl2 being deleted in mature myofibers to assess its role in sarcomere maintenance, and the other in adult muscle satellite cells (MuSCs) to assess its role in de novo sarcomere assembly. We find that Styxl2 is not required for sarcomere maintenance but functions in de novo sarcomere assembly during injury-induced muscle regeneration. Mechanistically, Styxl2 interacts with non-muscle myosin IIs, enhances their ubiquitination, and targets them for autophagy-dependent degradation. Without Styxl2, the degradation of non-muscle myosin IIs is delayed, which leads to defective sarcomere assembly and force generation. Thus, Styxl2 promotes de novo sarcomere assembly by interacting with non-muscle myosin IIs and facilitating their autophagic degradation.

Bessel beams have multiple applications owing to their propagation-invariant properties, including particle trapping, optical coherence tomography, and material processing. However, traditional Bessel-beam shaping techniques require bulky components, which limits the development of miniaturized optical systems for integration with other devices. Here, we report a novel femtosecond laser direct writing strategy for fabricating mesoscale (from submicrometer to subcentimeter) binary optical elements with microscale resolution. This strategy utilizes femtosecond beams with a long focal depth to increase throughput while reducing the constraints on critical sample positioning. As a demonstration, we manufactured and characterized a 2.2 mm diameter binary axicon. The experimentally measured quasi-Bessel beam intensity distribution and the numerical results were remarkably consistent, demonstrating a suitable tradeoff between the overall size, efficiency, and structural fidelity. Furthermore, a compact Bessel lens containing binary axicons was constructed and successfully used for femtosecond laser mask-less ablation of periodic grating-type surface plasmon polariton excitation units. The demonstrated approach shows significant potential for fabricating customizable integrated optical components.

The semi-supervised non-negative matrix factorization (NMF) methods have demonstrated their powerful capabilities in fields such as data representation, image clustering, and recommendation systems. However, the semi-supervised NMF methods still have various shortcomings and there is still room for improvement. In this paper, based on concept factorization (CF), a new semi-supervised concept factorization method, called adaptive graph regularized concept factorization with label discrimination (AGCFLD), is proposed. In AGCFLD, the partial label information is embedded into the framework of CF by label discrimination constraint and adaptive graph regularization. Thus, the discriminative abilities of data representations generated by AGCFLD are enhanced in the clustering tasks. Experimental results on several datasets demonstrate the effectiveness of the proposed AGCFLD method compared to the state-of-the-art methods. For the convenience of reproducing the results of this article, the source code can be found on the website: https://github.com/YanfengLi-spec/AGCFLD.

The accurate detection and classification of invisible weld defects is very important to ensure the quality of welding products. A magneto-optical (MO) imaging detection system excited by a rotating magnetic field is proposed for feature extraction and detection classification of invisible natural weld defects. A finite element analysis (FEA) model of multidirectional natural weld cracks is developed to study the distribution of rotating magnetic fields at different transient times, and the distribution of leakage magnetic field for four types of invisible defects is analyzed. The correctness of the finite element model is verified by MO imaging test of multidirectional natural weld defects. The grayscale values and texture features of MO images can reflect the leakage magnetic field characteristics of weld defects. The MO imaging detection system excited by a rotating magnetic field is used to obtain MO images of defects such as non-penetration, pit, subsurface crack, surface crack, and no defect for weld defect diagnosis. The principal component analysis (PCA) method and the Tamura method are used to extract the grayscale values and texture features of natural weld defect’s MO images, respectively. Using backpropagation (BP) neural network as the weak classifier, a strong classification model of BP-Adaboost weld defects is established by the Adaboost algorithm. Experimental results show that the recognition accuracy of the PCA + Tamura- BP-Adaboos model is higher than that of the PCA + Tamura-BP model, and its overall recognition rate reaches 97.8%, and the detection and classification of multidirectional natural weld defects can be realized.

Effective collision detection is crucial for creating a realistic and immersive virtual reality (VR) experience, especially in large and complex VR environments. Collision detection research currently focuses on improving two key aspects: accuracy and real-time performance. This paper proposes a novel collision detection algorithm that uses a mixed layer bounding box approach. The algorithm uses Sphere and EBB (Ellipsoidal Bounding Box) methods to quickly eliminate disjoint objects in the virtual environment and reduce the number of triangular primitives that need to be detected. Tree structures are used to traverse nodes from top to bottom, and then the Devillers & Guigue method is used to calculate accurate triangle-to-triangle primitives, further improving the effectiveness and accuracy of the collision detection. Experimental results show that the proposed algorithm (Sphere-EBB) performs better than traditional hybrid bounding box algorithms like Sphere Axial Aligned Bounding Box (Sphere-AABB) and EBB in terms of mean detection time, detection rate, and frame frequency. This makes the proposed algorithm suitable for large-scale, complex model collision detection tasks in terms of collision detection time and accuracy.

To address the challenges of road extraction in high-resolution remote sensing images, this paper presents an enhanced UNet++ road extraction method that incorporates CBAM. The original UNet++ network is referenced, and the loss function is improved by introducing a new joint loss function. The enhanced UNet++ network utilizes an attention mechanism to enhance the network’s ability to identify road features, thereby improving the accuracy of road extraction. Additionally, a new joint loss function is employed to enhance the network’s stability and further improve its road extraction capability. Experimental validation is performed on the Massachusetts roads dataset and DeepGlobal road dataset. The experimental results demonstrate that this method outperforms U-Net, SegNet, and UNet++ networks in terms of IoU, Recall, OA, and Kappa. Specifically, on the Massachusetts road dataset, the OA and Kappa values are 94.92% and 0.9202, respectively. On the DeepGlobal road dataset, the OA and Kappa values for this algorithm are 98.12% and 0.9515, respectively. The ablation experiment confirms the effectiveness of the proposed enhancements. In conclusion, this paper presents a method that effectively extracts roads from high-resolution remote sensing images, exhibits a certain level of generalization ability, and can provide valuable support for road protection and planning.

Abstract How to ensure dental stability in new positions and reduce the likelihood of relapse is a major clinical concern in the orthodontic field. Occlusal contacts between arches may affect the transmission of masticatory forces, thereby influencing the biological response of the periodontal and the oromandibular system. Occlusion factors that may influence the stability after orthodontic tooth movement (OTM) remain largely unknown. Hence, this research was conducted in order to investigate the influence of different occlusal contact patterns on tooth stability and oromandibular system including the masseter muscle and the temporomandibular joint following OTM. By modifying the occlusal surfaces, in vivo animal study models with distinct occlusal patterns corresponding to clinical circumstances were established. The relapse distance of teeth and the level of inflammatory factors in the gingival cervical fluid were analyzed. We also closely observed the histological remodeling of periodontal tissue, masseter tissue, and joint tissue after one week of relapse. Moreover, genes expression in the alveolar bone was analyzed to illustrate the potential biological mechanisms of relapse under the influence of different occlusal contact patterns following OTM. Different occlusal contact patterns after OTM in rats were established. The intercuspation contact between cusp and fossa group exhibited the lowest level of relapse movement, inflammatory factors and osteoclast activity (P

In extremely dark conditions, low-light imaging may offer spectators a rich visual experience, which is important for both military and civic applications. However, the images taken in ultra-micro light environments usually have inherent defects such as extremely low brightness and contrast, a high noise level, and serious loss of scene details and colors, which leads to great challenges in the research of low-light image and object detection and classification. The low-light night vision image used as the study object in this work has an excessively dim overall picture and very little information about the screen’s features. Three algorithms, HE, AHE, and CLAHE, were used to enhance and highlight the image. The effectiveness of these image enhancement methods is evaluated using metrics such as the peak signal-to-noise ratio and mean square error, and CLAHE was selected after comparison. The target image includes vehicles, people, license plates, and objects. The gray-level co-occurrence matrix (GLCM) was used to extract the texture features of the enhanced images, and the extracted image texture features were used as input to construct a backpropagation (BP) neural network classification model. Then, low-light image classification models were developed based on VGG16 and ResNet50 convolutional neural networks combined with low-light image enhancement algorithms. The experimental results show that the overall classification accuracy of the VGG16 convolutional neural network model is 92.1%. Compared with the BP and ResNet50 neural network models, the classification accuracy was increased by 4.5% and 2.3%, respectively, demonstrating its effectiveness in classifying low-light night vision targets.

Asymmetrical V-shaped tunnels often appear in tunnels crossing the river or urban underground road tunnels. The smoke flow inside is affected by a lot of factors. A full understanding of the smoke flow in this kind of tunnel is the basis of the smoke control. In this study, the effects of slope composition and fire heat release rate (HRR) on the longitudinal induced airflow velocity, the smoke back-layering length at the small slope side, and the maximum ceiling temperature were studied by the numerical method. The results show that when the fire occurs at the slope change point of the V-shaped tunnel, the maximum ceiling temperature decreases with the increase in the slope of the large-slope side tunnel. The longitudinally induced velocity is primarily related to the slope of the large-slope side tunnel and the fire HRR. When the slope difference between the side tunnels or the slope of the large-slope side tunnel is large, the smoke in the small-slope side tunnel flows back toward the fire source after reaching its maximum dispersion distance and then reaches a quasi-steady state. The smoke back-layering length is mainly affected by the slope and length of the large-slope side tunnel. When the slope of the large-slope side tunnel is 9%, the induced airflow velocity from the small-slope side can prevent the spread of smoke. The empirical models of the smoke back-layering length and the longitudinal induced airflow velocity in the small-slope side tunnel are drawn, respectively, by the theoretical analysis and the numerical results. This study can provide technical support for the design and operation of smoke control systems in V-shaped tunnels.

The simulation of human sensory functions is a key trend in the field of sensor development. In taste sensing, taste biosensors emulate taste perception using biorecognition elements that participate in taste transduction, such as taste receptors, cells, tissues, etc. This approach obtains high selectivity and a wide detection range of human taste perception, making taste biosensors widely used in food analysis and taste perception studies. By combining biorecognition elements with suitable data processing and analysis techniques, the taste information generated during the process of taste transduction, obtained by the sensing elements of the sensor, can be accurately captured. In this paper, we explore current available solutions to stability and sensitivity, and other challenges in taste biosensors using taste receptors, cells, and tissues as sensing elements. We also outline the applied signal processing techniques based on the signal characteristics from different types of taste biosensors. Finally, it is proposed that the development of taste biosensing sensors will further promote the application of intelligent sensory evaluation and human perception analysis systems in food, medicine, and other fields.

Modeling the interactive behavior of human drivers is essential for achieving safe and fully autonomous vehicles. Unfortunately, most decision-making systems employed in current autonomous vehicles rely on complex deep neural network models that function as black boxes with opaque reasoning that hampers human interpretation. Drawing upon the needs theories endorsed by psychologists and driving-related psychological research, we summarize five fundamental driving needs underlying the driver’s behavior: safety, dominance, achievement, order, and relatedness. Leveraging the behavior selection module from general cognitive architectures, we propose a decision-making model explicitly tailored for autonomous vehicles, comprising three distinct modules: needs assessment, motivation generation, and behavior selection. We conducted experiments to evaluate the proposed model using a self-developed 2D simulator based on Unity. The results intuitively visualized the motivation and behavior of self-driving vehicles. This model demonstrates remarkable proficiency in handling routine tasks, such as independent and complete driving tasks, intersection navigation, and maneuvering among multiple vehicles.

BackgroundMAPT variants are a known cause of frontotemporal dementia and Parkinsonian syndrome, of which progressive supranuclear palsy syndrome (PSP) is a rare manifestation.ObjectiveTo report a novel MAPT variant in a PSP pedigree with autosomal dominant inheritance pattern, and to produce a literature review of PSP patients with MAPT variants.MethodsA comprehensive clinical, genetic, and molecular neuroimaging investigation was conducted on a 61 years-old female proband diagnosed with PSP. We also collected the clinical presentation data and history of the patient’s pedigree, and performed further genetic analysis of 4 relatives, from two generations, with and without symptoms.ResultsThe proband exhibited typical clinical manifestation of PSP. A cranial MRI revealed midbrain atrophy, and an FDG-PET scan suggested hypo-metabolic changes in caudate nucleus, left prefrontal lobe, both temporal poles, and midbrain. 18F-florzolo-tau-PET revealed tau-protein deposits in the thalamus and brainstem bilaterally. A gene test by whole-exome sequencing identified a novel MAPT variant [NM_005910.6, exon 11, c.1024G > A (p.E342K)], and the same variant was also identified in one affected relative and one asymptomatic relative, a probable pre-symptomatic carrier.ConclusionThe PSP pedigree caused by the novel MAPT (E342K) variant, expanded the mutational spectrum of MAPT.

Varicoceles are a common cause of male infertility, affecting up to 35% of men undergoing fertility evaluations. This study aims to investigate the potential influence of altitude and residence time on the occurrence of varicoceles, as well as on sperm quality and sterility in plateau areas. A total of 168 patients with varicocele were enrolled in the study, and the study population was divided into groups based on their direct exposure to different high altitudes due to their living locations. The internal diameter in Quiet breath (Dr), internal diameter in Valsalva maneuver (Dv), reflux peak value, and reflux time are gradually increased accompanied with altitude elevation and residence time extension. The number of cases above 4,500 m also increased with the severity of varicocele, and the altitude of clinical types was higher than that of subclinical types of varicocele. Especially above 4,500 m, the Dv, Dr, reflux peak value, and reflux time all increased with the severity of varicocele. The severity of varicocele was positively correlated with the residence time in plateau area. Patients with residence time of more than 1 year had higher values of Dr, Dv, differentiation time, reflux peak value, and reflux time than those with residence time of less than 1 year. Compared to 3,650 m, patients with varicocele in 4,500 m also have worse semen quality. Both altitude and residence time are strongly positively related to the severity and incidence rate of varicocele in plateau areas.

Context: Sanchi promotes wound healing by repressing fibroblast proliferation. Objective: This study examined the effect of Sanchi on keratinocytes (KCs) and microvascular endothelial cells (MECs) and rats with skin injury. Materials & methods: Hydrogels containing different concentrations of Sanchi extract were prepared to observe wound closure over 10 days. SD rats were divided into the control, Hydrogel, 5% Hydrogel, 10% Hydrogel, 10% Hydrogel + Ad5-NC, and 10% Hydrogel + Ad5-IL1B groups. KCs and MECs were induced with H2O2 for 24 h. Cell viability, apoptosis, and the levels of inflammation- and oxidative stress-related factors were examined. The effect of IL1B on wound healing was also evaluated. Results: Compared to the Control group (83% ± 7.4%) or Hydrogel without Sanchi extract (84% ± 8.5%), Hydrogel with 5% (95% closure ± 4.0%) or 10% Sanchi extract (98% ± 1.7%) accelerated wound healing in rats and attenuated inflammation and oxidative stress. Hydrogels containing Sanchi extract increased collagen deposition and CD31 expression in tissues. H2O2 (100 μM) induced injury in KCs and MECs, whereas Sanchi rescued the viability of KCs and MECs. Sanchi inhibited cell inflammation and oxidative stress and decreased apoptosis. As Sanchi blocked the NFκB pathway via IL1B, IL1B mitigated the therapeutic effect of Sanchi. Discussion and conclusion: Sanchi demonstrated therapeutic effects on wound healing in rats by promoting KCs and MECs activity. These findings provide valuable information for the clinical application of Sanchi, which needs to be validated in future clinical trials.

Axonal remodeling is a critical aspect of ischemic brain repair processes and contributes to spontaneous functional recovery. Our previous in vitro study demonstrated that exosomes/small extracellular vesicles (sEVs) isolated from cerebral endothelial cells (CEC-sEVs) of ischemic brain promote axonal growth of embryonic cortical neurons and that microRNA 27a (miR-27a) is an elevated miRNA in ischemic CEC-sEVs. In the present study, we investigated whether normal CEC-sEVs engineered to enrich their levels of miR-27a (27a-sEVs) further enhance axonal growth and improve neurological outcomes after ischemic stroke when compared with treatment with non-engineered CEC-sEVs. 27a-sEVs were isolated from the conditioned medium of healthy mouse CECs transfected with a lentiviral miR-27a expression vector. Small EVs isolated from CECs transfected with a scramble vector (Scra-sEVs) were used as a control. Adult male mice were subjected to permanent middle cerebral artery occlusion and then were randomly treated with 27a-sEVs or Scra-sEVs. An array of behavior assays was used to measure neurological function. Compared with treatment of ischemic stroke with Scra-sEVs, treatment with 27a-sEVs significantly augmented axons and spines in the peri-infarct zone and in the corticospinal tract of the spinal grey matter of the denervated side, and significantly improved neurological outcomes. In vitro studies demonstrated that CEC-sEVs carrying reduced miR-27a abolished 27a-sEV-augmented axonal growth. Ultrastructural analysis revealed that 27a-sEVs systemically administered preferentially localized to the pre-synaptic active zone, while quantitative reverse transcription-polymerase chain reaction and Western Blot analysis showed elevated miR-27a, and reduced axonal inhibitory proteins Semaphorin 6A and Ras Homolog Family Member A in the peri-infarct zone. Blockage of the Clathrin-dependent endocytosis pathway substantially reduced neuronal internalization of 27a-sEVs. Our data provide evidence that 27a-sEVs have a therapeutic effect on stroke recovery by promoting axonal remodeling and improving neurological outcomes. Our findings also suggest that suppression of axonal inhibitory proteins such as Semaphorin 6A may contribute to the beneficial effect of 27a-sEVs on axonal remodeling.

Zinc (Zn) alloy porous scaffolds produced by additive manufacturing own customizable structures and biodegradable functions, having a great application potential for repairing bone defect. In this work, a hydroxyapatite (HA)/polydopamine (PDA) composite coating was constructed on the surface of Zn–1Mg porous scaffolds fabricated by laser powder bed fusion, and was loaded with a bioactive factor BMP2 and an antibacterial drug vancomycin. The microstructure, degradation behavior, biocompatibility, antibacterial performance and osteogenic activities were systematically investigated. Compared with as-built Zn–1Mg scaffolds, the rapid increase of Zn2+, which resulted to the deteriorated cell viability and osteogenic differentiation, was inhibited due to the physical barrier of the composite coating. In vitro cellular and bacterial assay indicated that the loaded BMP2 and vancomycin considerably enhanced the cytocompatibility and antibacterial performance. Significantly improved osteogenic and antibacterial functions were also observed according to in vivo implantation in the lateral femoral condyle of rats. The design, influence and mechanism of the composite coating were discussed accordingly. It was concluded that the additively manufactured Zn–1Mg porous scaffolds together with the composite coating could modulate biodegradable performance and contribute to effective promotion of bone recovery and antibacterial function.

Background: Intraoral scans (IOS) provide precise 3D data of dental crowns and gingival structures. This paper explores an application of IOS in human identification. Methods: We propose a dental biometrics framework for human identification using 3D dental point clouds based on machine learning-related algorithms, encompassing three stages: data preprocessing, feature extraction, and registration-based identification. In the data preprocessing stage, we use the curvature principle to extract distinguishable tooth crown contours from the original point clouds as the holistic feature identification samples. Based on these samples, we construct four types of local feature identification samples to evaluate identification performance with severe teeth loss. In the feature extraction stage, we conduct voxel downsampling, then extract the geometric and structural features of the point cloud. In the registration-based identification stage, we construct a coarse-to-fine registration scheme in order to realize the identification task. Results: Experimental results on a dataset of 160 individuals demonstrate that our method achieves a Rank-1 recognition rate of 100% using complete tooth crown contours samples. Utilizing the remaining four types of local feature samples yields a Rank-1 recognition rate exceeding 96.05%. Conclusions: The proposed framework proves effective for human identification, maintaining high identification performance even in extreme cases of partial tooth loss.

In this paper, the effect of size on the wind pressure coefficient on the surface of solar greenhouses is investigated using numerical simulations. The models were designed with consistent ratios of ridge height to span and north wall height to ridge height across different spans. To effectively understand the impact of dimensions on wind pressure distribution, two wind directions—0° (north wind) and 180° (south wind)—which have previously been shown to impose significant overall wind loads on solar greenhouses, are focused on. It was found that the wind load per unit area increases continuously with greenhouse size. Wind-induced suction is particularly concentrated along the ridge, with greater suction on the leeward side compared to the windward side. The wind suction near the ridge is more significantly affected by greenhouse size. This study provides valuable insights for the practical engineering design of solar greenhouses.

This study proposes a model for the quantitative evaluation of the life-cycle carbon footprints of large sporting events and the uncertainties related to them. The model was used to analyze the case of a mega sporting event in Beijing, China. First, the quantitative model for the evaluation of the carbon footprints of mega sporting events includes a preparation stage, a holding stage, and an end stage. These stages consider the energy and resources used for construction, operation, transportation, catering, and accommodation. Second, this study proposes a prediction model using model-based and simulation-based methods to address the difficulty of obtaining traffic activity. Third, a semi-quantitative method that combines a data quality indicator and stochastic simulation is adopted for the uncertainty analysis of mega sporting events. Finally, a case study is used to indicate that the preparation stage of a mega sporting event accounts for the highest CO2 emissions at 92.1%, followed by 7.5% in the holding stage and 0.4% in the end stage. The total life-cycle CO2 emissions of a sustainable scenario of a mega sporting event in Beijing amount to 205,080.3 t CO2e, and the per capita CO2 emissions during the event’s holding stage amount to 0.26 t CO2e/person. The uncertainty in the input parameters is 0.0617, indicating that the uncertainty of the model is low, and the reliability of the results is high.

Coalbed methane (CBM), recognized as a sustainable and environmentally friendly energy source, plays a crucial role in mitigating global climate change and advancing low-carbon energy solutions. However, the prevalence of low-permeability coal seams poses a significant challenge to effective CBM extraction. Improving coal permeability has emerged as a viable strategy to address the issue of low-permeability coal. Conventional CBM stimulation methods fall short in overcoming this obstacle. In contrast, the enhanced technique of CBM extraction by water-based ultrasonic cavitation holds great promise due to its use of high energy intensity, safety, and efficiency. Nevertheless, the inadequate theoretical framework for managing this technology impedes its widespread adoption for large-scale applications. This study investigated the impact of water-based ultrasonic cavitation treatment on coal’s properties and permeability through mechanical testing and permeability measurements conducted before and after treatment. This study also explored the process by which this technology, known as WUC-ECBM, improves coal’s mechanical properties and permeability. The findings suggest a potential stimulation technique (WUC-ECBM) for use in CBM extraction, and its physical mechanism.

This is a paper in the field of mineral processing engineering. Application of ultra-fine grinding technology to treat phosphate ore can change the physical and chemical properties of phosphate containing minerals in phosphate ore, thus improving the dissolution and release of phosphorus in phosphate ore, so that it can be used as phosphate fertilizer. As an ultra-fine grinding equipment, the feasibility of using stirred mill to treat phosphate ore and the research on the influence of process parameters on grinding effect are not perfect. A phosphate ore in Hebei Province was wet ground by a vertical stirring mill in this paper.The particle size distribution of the ground product was detected by NKT6100-D laser particle size analyzer.The effect of grinding process parameters on the particle size composition of product and the content of newly formed particles was explored, and the product particle size was parametrically analyzed by R-R equation to determine the more appropriate operating process parameters. The results showed that under the conditions of agitator speed of 550 r/min, grinding concentration of 65%, filling rate of 60%, feed to ball ratio of 0.5 and grinding time of 30 min, the available phosphorus content and phosphorus solubility in citric acid of 8.75% and 74.03%, particle characteristic parameter b of 0.371 and uniformity coefficient n of 1.426 were obtained. It can be seen that it is feasible to use a vertical stirring mill for ultra-fine grinding of phosphate ore.

Abstract The combination of bioactive Zn‐2Mg alloy and additively manufactured porous scaffold is expected to achieve customizable biodegradable performance and enhanced bone regeneration. Herein, Zn‐2Mg alloy scaffolds with different porosities, including 40% (G‐40‐2), 60% (G‐60‐2), and 80% (G‐80‐2), and different unit sizes, including 1.5 mm (G‐60‐1.5), 2 mm (G‐60‐2), and 2.5 mm (G‐60‐2.5), are manufactured by a triply periodic minimal surface design and a reliable laser powder bed fusion process. With the same unit size, compressive strength (CS) and elastic modulus (EM) of scaffolds substantially decrease with increasing porosities. With the same porosity, CS and EM just slightly decrease with increasing unit sizes. The weight loss after degradation increases with increasing porosities and decreasing unit sizes. In vivo tests indicate that Zn‐2Mg alloy scaffolds exhibit satisfactory biocompatibility and osteogenic ability. The osteogenic ability of scaffolds is mainly determined by their physical and chemical characteristics. Scaffolds with lower porosities and smaller unit sizes show better osteogenesis due to their suitable pore size and larger surface area. The results indicate that the biodegradable performance of scaffolds can be accurately regulated on a large scale by structure design and the additively manufactured Zn‐2Mg alloy scaffolds have improved osteogenic ability for treating bone defects.

Additively manufactured biodegradable zinc (Zn) scaffolds have great potential to repair infected bone defects due to their osteogenic and antibacterial properties. However, the enhancement of antibacterial properties depends on a high concentration of dissolved Zn2+, which in return deteriorates osteogenic activity. In this study, a vancomycin (Van)-loaded polydopamine (PDA) coating was prepared on pure Zn porous scaffolds to solve the above dilemma. Compared with pure Zn scaffolds according to comprehensive in vitro tests, the PDA coating resulted in a slow degradation and inhibited the excessive release of Zn2+ at the early stage, thus improving cytocompatibility and osteogenic activity. Meanwhile, the addition of Van drug substantially suppressed the attachment and proliferation of S. aureus and E. coli bacterial. Furthermore, in vivo implantation confirmed the simultaneously improved osteogenic and antibacterial functions by using the pure Zn scaffolds with Van-loaded PDA coating. Therefore, it is promising to employ biodegradable Zn porous scaffolds with the proposed drug-loaded coating for the treatment of infected bone defects.

Human breathing is crucial for studying indoor environments and human health. Computational Fluid Dynamics (CFD) is a key tool for simulating human respiration. To enhance the accuracy of CFD simulations and reduce computation time, a new simulation strategy for human respiration is proposed in this paper. The effects of steady versus unsteady boundary conditions on simulation results were examined. For the unsteady boundary, sinusoidal exhalation velocities and non-inhalation gas were assumed, while the steady boundary involved constant velocities during both exhalation and inhalation phases. The jet center trajectory under different boundary conditions was analyzed and compared with experimental data. Additionally, variations in pollutant dispersion near the mouth under the two boundary conditions were discussed. Furthermore, the paper compared the calculation accuracy, calculation time and memory occupied by a single turbulence model or switching flow character models in human respiration simulation. Differences in exhaled gas vorticity and jet penetration depth across different flow models were identified. Finally, combined with the non-iterative algorithm, the optimal strategy of human respiration simulation was proposed. Results show that under the comprehensive consideration of calculation accuracy, calculation time and memory occupancy, using sinusoidal expiratory boundary conditions combined with the PISO algorithm, with the RNG k-ε model during expiratory phase, and switching into the laminar flow during inspiratory phase, is the optimal strategy of simulating human breathing.

Sport officials are pivotal to the development of the game at every level. Yet, the exploration of these officials’ job satisfaction and turnover intentions, especially within tennis, remains largely neglected. This study undertakes a cross-cultural adaptation and validation of the Referee Retention Scale (RRS) in a Chinese context (RRS-CN) and uses multilevel models (MLM) to explore the influence of perceived administrator consideration, mentoring, continuing education opportunities, remuneration, stress, and ecological factors on tennis officials’ sense of community and officiating motivation. Data from 523 tennis officials across 26 provinces in China were gathered via an online survey. Through exploratory and confirmatory factor analyses, the RRS-CN was validated as a culturally adaptive 25-item scale. In the following, MLM results revealed that officiating levels, socioeconomic status, perceived administrator consideration, mentoring, and levels of continuing education significantly predict officials’ sense of community. Additionally, we identified that continuing education, mentoring, and remuneration significantly influences officiating motivation. These findings underscore the importance of fair assignments, mentorship, and ongoing professional development in enhancing job satisfaction and retention. Future explorations are encouraged to extend the analysis to more ecological variables and further investigate their potential effects on systematic partial nesting, enhancing the generalizability and precision of measurement in job satisfaction and turnover studies across diverse cultural landscapes.

In this paper, the random and nonlinear mechanical characteristics of the composition distribution of concrete in each phase are investigated to solve the difficulty of fatigue damage test of concrete beam specimens under variable amplitude loading. A three-dimensional (3D) concrete composite random aggregate meso-model of concrete beam specimens is built with Digimat as a composite modeling tool. Subsequently, the bending-tensile strength and fatigue life of the model under four-point bending loading is analyzed and calculated using Abaqus finite element analysis model based on the concrete elastic-plastic damage criterion. The mechanical behaviors of concrete materials under static load failure, multistage fatigue loading, and random fatigue loading are studied. Finally, compared with the test results, the following conclusions are obtained. The random aggregate model and elastoplastic damage mechanics model of concrete composite constructed by concrete in Abaqus and Digimat can better describe the geometric and distribution characteristics of composite structure and aggregate in concrete beams and the mechanical behavior of fatigue and static load failure. The difference is 4.08 % with the experimental results, which verifies the validity and reliability of the numerical simulation model, and the fatigue life of concrete beams under random loading Sra and Srb is 1622 and 164 times, respectively. The research results have certain guiding significance and reference value for accurate calculation of bending and tensile strength of concrete beams under specified raw material and mix ratio and prediction of fatigue damage cracking in airport cement concrete pavement structure.

Abstract Objectives This study was conducted to detect the overall performance of both static and dynamic occlusion in post-orthodontic patients using quantified methods, and to ascertain the correlation between the two states of occlusion. Materials and methods A total of 112 consecutive patients evaluated by ABO-OGS were included in this study. Based on the pre-treatment Angle’s classification of the malocclusion, samples were divided into four groups. After removing orthodontic appliances, each patients underwent the American Board of Orthodontic objective grading system (ABO-OGS) and T-Scan evaluations. All the scores were compared within these groups. Statistical evaluation included reliability tests, multivariate ANOVA, and correlation analyses (p

Abstract Objectives A patient with extensive atrophy of the alveolar ridge in the posterior portion of the maxilla was selected to complete an experimental and clinical case of the robotic zygomatic implant to investigate the viability of an implant robotic system in clinical use. Methods The preoperative digital information was collected, and the implantation position and personalized optimization marks needed for robot surgery were designed in advance in a repair-oriented way. The resin models and marks of the patient’s maxilla and mandible are all printed in 3D. Custom-made special precision drills and handpiece holders for robotic zygomatic implants were used to perform model experiments and compare the accuracy of the robotic zygomatic implant group (implant length = 52.5 mm, n = 10) with the alveolar implant group (implant length = 18 mm, n = 20). Based on the results of extraoral experiments, a clinical case of robotic surgery for zygomatic implant placement and immediate loading of implant-supported full arch prosthesis was carried out. Results In the model experiment, the zygomatic implant group reported an entry point error of 0.78 ± 0.34 mm, an exit point error of 0.80 ± 0.25 mm, and an angle error of 1.33 ± 0.41degrees. In comparison, the alveolar implant group (control group) reported an entry point error of 0.81 ± 0.24 mm, an exit point error of 0.86 ± 0.32 mm, and an angle error of 1.71 ± 0.71 degrees. There was no significant difference between the two groups (p > 0.05). In clinical cases, the average entry point error of two zygomatic implants is 0.83 mm, the average exit point error is 1.10 mm and the angle error is 1.46 degrees. Conclusions The preoperative planning and surgical procedures developed in this study provide enough accuracy for robotic zygomatic implant surgery, and the overall deviation is small, which is not affected by the lateral wall deviation of maxillary sinus.

A quantitative study is performed to determine the performance degradation of Y-shaped reinforced concrete bridge piers owing to long-term freeze-thaw damage. The piers are discretized into spatial solid elements using the ANSYS Workbench finite element analysis software, and a spatial model is established. The analysis addresses the mechanical performance of the piers under monotonic loading, and their seismic performance under low-cycle repeated loading. The influence of the number of freeze-thaw cycles, axial compression ratio, and loading direction on the pier bearing capacity index and seismic performance index is investigated. The results show that freeze-thaw damage has an adverse effect on the ultimate bearing capacity and seismic performance of Y-shaped bridge piers in the transverse and longitudinal directions. The pier peak load and displacement ductility coefficient decrease with increasing number of freeze-thaw cycles. The axial compression ratio is an important factor that affects the pier ultimate bearing capacity and seismic performance. Upon increasing the axial compression ratio, the pier peak load increases and the displacement ductility coefficient decreases, the effects of which are more significant in the longitudinal direction.

The objective of this study was to determine the reasonable flexural functions of ultra-wide box girders, reveal the mechanism of the shear lag effect, and improve the analysis theory of ultra-wide box girders. Considering a single-box three-chamber thin-walled box girder as an example, starting from an uneven transfer of shear flow, the flexural displacement function of the curved box girder under the influence of shear deformation of each plate was derived according to the flexural theory of a thin-walled box girder, balance equation of a thin-walled microelement plate, and theory of plane stress. The energy variational method was used to analyze the flexural displacement function, providing a theoretical solution for the shear lag effect of the curved box girder. A displacement correction of the cantilever plate displacement function was performed by comparing the calculation results for the shear lag coefficients. The results indicated that under the shear deformation of each plate, the flexural displacement functions of the wing and web plates of the box girder no longer satisfy the assumption of plane section. The flexural displacement function is a quadratic function of the transverse wing plate, and the web height is the sum of the first- and third-order functions. The theoretical calculation results agree sufficiently well with the experimental results, proving that the flexural displacement function of the box girder under the influence of the shear deformation of each plate is reliable.

In this research, the influence of confined space size on the temperature distribution characteristics of internal window plumes from well-ventilated compartment fires was studied. Theoretical analysis was firstly used to establish a mathematical model for the smoke after ejecting from the window in the space. The study considered fire heat release rate and vertical height as dependent variables. Numerical simulations and experimental methods were carried out to study the temperature variations. A critical distance L2 was obtained. Results show that when the space D between the vertical retaining wall and the building façade is greater than L2, the variation of D has little influence on radial temperature. Once D is less than L2, the radial temperature distribution inside the confined space will tend to be consistent, and the temperature in the confined space sharply increases as D decreases. In addition, a dimensionless model was derived to quantify the relationship between temperature rise and vertical height. The experimental and numerical simulation results were processed, which are in good agreement with the model. The study can provide a framework for managing building safety.

A systematic study was conducted on the impact of annealing treatments on the microstructure and properties of cold-rolled Ti50Ni47Fe3 alloys using optical microscopy, scanning electron microscopy, electron backscattered diffraction, and an electronic universal testing machine. It was found that, during low-temperature annealing (400 °C and 500 °C), the annealing time had no significant effect on the microstructure or properties of the Ti50Ni47Fe3 alloy. Only elongation (δ) increased with the increase in the annealing time, and the grain orientation of the Ti50Ni47Fe3 alloy was //RD (rolling direction). When annealing at medium–high temperature (600 °C), as the annealing time increased, recrystallization and grain growth processes occurred, resulting in a continuous decrease in strength and an increase in δ. Meanwhile, it was found that the grain orientation of the cold-rolled Ti50Ni47Fe3 alloy changed from //RD during the recovery and recrystallization processes to //RD after the grain growth process. The orientation distribution function cross-section φ2 = 45° results indicate that the texture was mainly distributed along the γ orientation line (φ1 = 0~90°, Φ = 54.7°, φ2 = 45°). When annealed at 400 °C and 500 °C, the texture of the Ti50Ni47Fe3 alloys was (111)[uvw]. When the annealing treatment was 600 °C for 120 min, a (110)[uvw] texture occurred. Additionally, ductile fracture occurred in all specimens, and the crack origin was located on one side of the fracture surface, with obvious “Y”-shaped propagation. This article studied annealing treatments of cold-rolled Ti50Ni47Fe3 alloys, providing corresponding theoretical guidance for subsequent production applications.

The effect of annealing treatment on the microstructure and texture of a Ti50Ni47Fe3 shape memory alloy tube was studied. The results show that the recrystallization process of a cold-rolled Ti50Ni47Fe3 alloy tube occurs at 600 °C. The microstructure changes from long striped grains to equiaxed recrystallized grains. The main texture of the alloy tube is the fiber texture parallel to RD. With the increase in the annealing temperature, the crystal orientation of the alloy gradually turned to (111), and a series of secondary textures were distributed along the γ orientation line when the alloy was annealed at a lower temperature (450~600 °C). When the alloy was annealed at 650 °C, the growth of recrystallized grains made the grain orientation change, which led to the weakening of the γ-fiber texture and the formation of recrystallization textures.

Abstract As a basic component in the field of computer vision, the pedestrian detection plays an essential role in several real‐world applications such as video surveillance. The promising performance has been achieved in pedestrian detection relying on deep learning, but large‐scale variance and small‐scale pedestrian detection remain inherently hard as before. In order to deal with the aforementioned problems, this paper proposes a multi‐scale pedestrian detection method with global–local attention and multi‐scale receptive field context (MRFC). To make the network focus on small‐scale pedestrians, we add a high‐resolution detection branch on the original detector. To better integrate the incongruous semantic feature, the global–local attention module is embedded to highlight the feature representation of pedestrians so as to implement the feature fusion effectively. In order to adapt the receptive field of the network to achieve scale‐variance detection, the MRFC is applied. Based on integrating the above structures, the proposed method achieves competitive results on Caltech and CityPersons datasets. The source code is released in https://github.com/xiaopan999/yolov5‐pedestrian_detection.

An improved modulation method is proposed for two parallel three-level interleaved rectifiers to reduce current harmonics and high-frequency zero-sequence circulating current, which uses sinusoidal pulse width modulation. First, a model of the two parallel rectifiers is constructed, and the main factor affecting the line current performance and zero-sequence circulating current is discussed. Second, the current harmonics are the priority optimization target to guarantee better line current performance. Finally, an exchange of the large common-mode voltage between two converters is made to reduce the high frequency zero-sequence circulating current based on the low current harmonics. Performance comparisons between the proposed method and existing methods in terms of total current harmonics, zero-sequence circulating current value and switching loss are made in the experiment, which confirm the effectiveness of the proposed method.

Scenario vehicles are an important part of the dynamic environment utilized in autonomous-driving simulations. They are required to meet the demands of traffic-scenario diversity and form a larger coverage scale in the road network. However, the current motion planning of scenario vehicles either adheres to the classical microscopic traffic-flow model or follows a predefined path; thus, interacting with the vehicle under test in a dynamic bidirectional fashion is difficult. This study researches a motion-planning method for a broader category of unmanned vehicles and proposes a motion-planning method for scenario vehicles based on Pontryagin’s minimal principle, used in optimal control theory and the closed-form solution of the minimum snap method. The study reclassifies actions received from the behavior layer according to the boundary conditions and final times and derives an analytical solution for each of them. The analytical solution is then experimentally verified. The proposed method not only accomplishes efficient motion planning but also exhibits variant driving styles, which provides a practical solution for the motion planning of scenario vehicles in simulations.

Abstract Semantic segmentation is a classical problem in computer vision, which is important in the field of autonomous driving. Although significant progress has been achieved in semantic segmentation, its generalization ability to unknown domains is still challenging. To effectively solve this problem, a semantic segmentation method ImDeeplabV3plus with instance selective whitening loss is proposed in this paper. DeeplabV3plus is selected as the baseline. In order to enhance the representation of the region of interest, the coordinate attention (CA) mechanism is added. To better integrate multiple low‐level features, the adaptively spatial feature fusion (ASFF) is employed to adaptively learn the importance of features at different levels for each location. For preferably coping with the domain changes, an instance selective whitening (ISW) loss is introduced in the early stage of the backbone. The model is trained with the Cityscapes dataset and then applied to the unknown domain RobotCar dataset. Compared with DeeplabV3plus, the authors’ ImDeeplabV3plus model shows 1.29% mIoU improvement. When ISW loss is added, 2.08% improvement in mIoU is achieved compared with ImDeeplabV3plus. Experimental results show that the proposed method is simple and improves the domain generalization ability.

Lung cancer is the leading cause of cancer death world-wide and its treatment remains a challenge in clinic, especially for non-small cell lung cancer (NSCLC). Thus, more effective therapeutic strategies are required for NSCLC treatment. Quercetin (Que) as a natural flavonoid compound has gained increasing interests due to its anticancer activity. However, poor water solubility, low bioavailability, short half-life, and weak tumor accumulation hinder in vivo applications and antitumor effects of Que. In this study, we developed Que-loaded mixed micelles (Que-MMICs) assembled from 1,2-distearoyl-sn-glycero-3-phosphoethanolamine–poly(ethylene glycol)–biotin (DSPE–PEG–biotin) and poly(ethylene glycol) methyl ether methacrylate–poly[2-(dimethylamino) ethyl acrylate]–polycaprolactone (PEGMA–PDMAEA–PCL) for NSCLC treatment. The results showed that Que was efficiently encapsulated into the mixed micelles and the encapsulation efficiency (EE) was up to 85.7%. Cellular uptake results showed that biotin conjugation significantly improved 1.2-fold internalization of the carrier compared to that of non-targeted mixed micelles. In vitro results demonstrated that Que-MMICs could improve cytotoxicity (IC50 = 7.83 μg/mL) than Que-MICs (16.15 μg/mL) and free Que (44.22 μg/mL) to A549 cells, which efficiently induced apoptosis and arrested cell cycle. Furthermore, Que-MMICs showed satisfactory tumor targeting capability and antitumor efficacy possibly due to the combination of enhanced permeability and retention (EPR) and active targeting effect. Collectively, Que-MMICs demonstrated high accumulation at tumor site and exhibited superior anticancer activity in NSCLC bearing mice model.

IntroductionThe longitudinal responses towards multiple doses of COVID-19 mRNA vaccines in patients with systemic autoimmune diseases remain incompletely understood. While observational studies suggested the safety of COVID-19 mRNA vaccines in rheumatic disease patients, laboratory evidence is lacking.MethodsHere we evaluated seroreactivity, clinical manifestions, and multiple disease biomarkers after 2 or 3 doses of COVID-19 mRNA vaccines in a cohort of patients with rheumatic diseases.ResultsMost patients generated high SARS-CoV-2 spike-specific neutralizing antibodies comparable to those in healthy controls after 2 doses of mRNA vaccines. The antibody level declined over time but recovered after the third dose of the vaccine. Patients with systemic lupus erythematosus (SLE) or psoriatic arthritis (PsA) remained without significant flares post-vaccination. The changes in anti-dsDNA antibody concentration and expression of type I interferon (IFN) signature genes were highly variable but did not show consistent or significant increases. Frequency of double negative 2 (DN2) B cells remained largely stable.DiscussionOur data provide experimental evidences indicating the efficacy and safety of repeated COVID-19 mRNA vaccination in rheumatic disease patients.

Trichinella spiralis (T. spiralis) adult-specific deoxyribonuclease II-7 (TsDNase II-7), a member of the DNase II-like nuclease family with no DNase II activity, was identified in the excretory-secretory (ES) products of adult worms (AWs). However, its biological functions are still unclear. Our previous study revealed that TsDNase II-7 is located around the infection site in the intestinal tissue, speculating that it was involved in the T. spiralis invasion of host intestinal epithelial cells (IECs). This study aimed to use RNA interference to verify our speculation that TsDNase II-7 in 3-day old adult T. spiralis (Ad3) plays a role in intestinal invasion. TsDNase II-7-specific small interfering RNAs (siRNAs) were delivered into muscle larvae (MLs) to knockdown TsDNase II-7 expression by electroporation. Twenty-four hours later, the MLs transfected with 2 μM siRNA-841 exhibited decreased in TsDNase II-7 transcription and expression as compared to the control MLs. The knockdown of TsDNase II-7 expression did not affect ML viability, and the low expression of TsDNase II-7 still maintained in Ad3 recovered from TsDNase II-7-RNAi-ML infected mice, resulting in a weakened ability of Ad3 to invade intestinal epithelial cells (IECs). These results indicated that knockdown of TsDNase II-7 gene expression via RNA interference (RNAi) suppressed adult worm invasion and confirmed that TsDNase II-7 plays a crucial role during the intestinal phase of T. spiralis infections, which provided new candidate for vaccine development of T. spiralis.

Pomegranate (Punica granatum L.) is one of the oldest fruits with edible, medicinal and ornamental values. However, there is no report on the mitochondrial genome of pomegranate. In this study, the mitochondrial genome of P. granatum was sequenced, assembled and analyzed in detail, while the chloroplast genome was assembled using the same set of data. The results showed that the P. granatum mitogenome had a multi branched structure, using BGI + Nanopore mixed assembly strategy. The total genome length was 404,807 bp, with the GC content of 46.09%, and there were 37 protein coding genes, 20 tRNA genes and three rRNA genes. In the whole genome, 146 SSRs were identified. Besides, 400 pairs of dispersed repeats were detected, including 179 palindromic, 220 forward and one reverse. In the P. granatum mitochondrial genome, 14 homologous fragments of chloroplast genome were found, accounting for 0.54% of the total length. Phylogenetic analysis showed that among the published mitochondrial genomes of related genera, P. granatum had the closest genetic relationship with Lagerstroemia indica of Lythraceae. The 580 and 432 RNA editing sites were predicted on 37 protein coding genes of mitochondrial genome using BEDTools software and online website PREPACT respectively, but all were from C to U, of which ccmB and nad4 gene were most frequently edited, with 47 sites. This study provides a theoretical basis for understanding the evolution of higher plants, species classification and identification, and will also be useful for further utilization of pomegranate germplasm resources.