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Abstract Background Diabetic kidney disease (DKD) is a prevalent and severe complication of diabetes and plays a pivotal role in the pathogenesis and progression of DKD. However, the current clinical application of the treatment methods does not yield effective results. Tacrolimus has been utilized in the management of immune-mediated and genetic-mediated nephropathy, with an emphasis on the restoration of podocyte cytoskeletal integrity and inhibition of apoptosis. The clinical management of diabetic nephropathy with tacrolimus remains challenging because of the risk of worsening hyperglycemia and infection. Results We developed two RGD-HSA-TAC nanoparticles designed for targeted delivery of tacrolimus to podocytes. Administration of SANPs and CNPs resulted in elevated levels of tacrolimus in podocytes, leading to a reduction in podocyte damage and albuminuria in diabetic nephropathy mice. Furthermore, the use of SANPs and CNPs resulted in a decrease in tacrolimus accumulation in the pancreas, lymph nodes, and thymus, thereby reducing the potential to exacerbate hyperglycemia and infection. Importantly, compared to tacrolimus alone, both SANPs and CNPs demonstrated superior therapeutic efficacy, with CNPs exhibiting a greater advantage over SANPs. Conclusions Compared to tacrolimus, SANPs and CNPs demonstrated superior therapeutic efficacy and a reduced incidence of adverse effects in the treatment of diabetic nephropathy. Graphical abstract

Abstract Inaccurate characterization of complex topography leads to the wet bias in climate models, particularly affecting terrain effects in regions like the Tibetan Plateau (TP). This study utilizes the Weather Research and Forecasting (WRF) model with multiple terrain datasets and introduces the terrain complexity index (TCI) to quantify the degree of terrain changes, aiming to evaluate how terrain complexity affects the cloud and precipitation processes over the TP. The results indicate that fine terrain complexity primarily causes earlier cloud formation and precipitation, resulting in more heavy precipitation on the southern slope of the TP (SSTP) and more light precipitation on the TP platform. The structure of moisture transport and microphysical processes further reveals that this promotes the formation of more medium and high clouds, increasing the proportion of solid precipitation over the SSTP. Over the TP platform, the restriction of medium and high cloud development with enhancing the proportion of low clouds for more liquid precipitation. These findings deepen the understanding of the TP’s complex terrain effect on cloud and precipitation changes in the Asian water cycle.

Abstract Background In high-throughput sequencing studies, sequencing depth, which quantifies the total number of reads, varies across samples. Unequal sequencing depth can obscure true biological signals of interest and prevent direct comparisons between samples. To remove variability due to differential sequencing depth, taxa counts are usually normalized before downstream analysis. However, most existing normalization methods scale counts using size factors that are sample specific but not taxa specific, which can result in over- or under-correction for some taxa. Results We developed TaxaNorm, a novel normalization method based on a zero-inflated negative binomial model. This method assumes the effects of sequencing depth on mean and dispersion vary across taxa. Incorporating the zero-inflation part can better capture the nature of microbiome data. We also propose two corresponding diagnosis tests on the varying sequencing depth effect for validation. We find that TaxaNorm achieves comparable performance to existing methods in most simulation scenarios in downstream analysis and reaches a higher power for some cases. Specifically, it balances power and false discovery control well. When applying the method in a real dataset, TaxaNorm has improved performance when correcting technical bias. Conclusion TaxaNorm both sample- and taxon- specific bias by introducing an appropriate regression framework in the microbiome data, which aids in data interpretation and visualization. The ‘TaxaNorm’ R package is freely available through the CRAN repository https://CRAN.R-project.org/package=TaxaNorm and the source code can be downloaded at https://github.com/wangziyue57/TaxaNorm .

Autologous vein grafts have attracted widespread attention for their high transplantation success rate and low risk of immune rejection. However, this technique is limited by the postoperative neointimal hyperplasia, recurrent stenosis and vein graft occlusion. Hence, we propose the platelet membrane-coated Poly(lactic-co-glycolic acid) (PLGA) containing sildenafil (PPS). Platelet membrane (PM) is characterised by actively targeting damaged blood vessels. The PPS can effectively target the vein grafts and then slowly release sildenafil to treat intimal hyperplasia in the vein grafts, thereby preventing the progression of vein graft restenosis. PPS effectively inhibits the proliferation and migration of vascular smooth muscle cell (VSMCs) and promotes the migration and vascularisation of human umbilical vein endothelial cells (HUVECs). In a New Zealand rabbit model of intimal hyperplasia in vein grafts, the PPS significantly suppressed vascular stenosis and intimal hyperplasia at 14 and 28 days after surgery. Thus, PPS represents a nanomedicine with therapeutic potential for treating intimal hyperplasia of vein grafts.

In the field of security, intelligent surveillance tasks often involve a large number of dense and small objects, with severe occlusion between them, making detection particularly challenging. To address this significant challenge, Dense and Small YOLO (DS-YOLO), a dense small object detection algorithm based on YOLOv8s, is proposed in this paper. Firstly, to enhance the dense small objects’ feature extraction capability of backbone network, the paper proposes a lightweight backbone. The improved C2fUIB is employed to create a lightweight model and expand the receptive field, enabling the capture of richer contextual information and reducing the impact of occlusion on detection accuracy. Secondly, to enhance the feature fusion capability of model, a multi-scale feature fusion network, Light-weight Full Scale PAFPN (LFS-PAFPN), combined with the DO-C2f module, is introduced. The new module successfully reduces the miss rate of dense small objects while ensuring the accuracy of detecting large objects. Finally, to minimize feature loss of dense objects during network transmission, a dynamic upsampling module, DySample, is implemented. DS-YOLO was trained and tested on the CrowdHuman and VisDrone2019 datasets, which contain a large number of densely populated pedestrians, vehicles and other objects. Experimental evaluations demonstrated that DS-YOLO has advantages in dense small object detection tasks. Compared with YOLOv8s, the Recall and mAP@0.5 are increased by 4.9% and 4.2% on CrowdHuman dataset, 4.6% and 5% on VisDrone2019, respectively. Simultaneously, DS-YOLO does not introduce a substantial amount of computing overhead, maintaining low hardware requirements.

Abstract Purpose Strong primary health care (PHC) systems require well‐established PHC education systems to enhance the skills of general practitioners (GPs). However, the literature on the experiences of international collaboration in primary care education in low‐ and middle‐income countries remains limited. The purpose of this study was to evaluate the implementation and perceived impact of the McGill‐Tongji Blended Education Program for Teacher Leaders in General Practice (referred to as the “Tongji Program”). Methods In 2020–2021, the McGill Department of Family Medicine (Montreal, Canada) and Tongji University School of Medicine (TUSM, Shanghai, China) jointly implemented the Tongji Program in Shanghai, China to improve the teaching capacity of PHC teachers. We conducted an exploratory longitudinal case study with a mixed methods design for the evaluation. Quantitative (QUAN) data was collected through questionnaire surveys and qualitative (QUAL) data was collected through focus group discussions. Results The evaluation showed that learners in Tongji Program were primarily female GPs (21/22，95%) with less than 4 years of experience in teaching (16/22，73%). This program was considered a successful learning experience by most participants (19/22, 86%) with higher order learning tasks such as critical thinking and problem‐solving. They also agreed that this program helped them feel more prepared to teach (21/22，95%), and developed a positive attitude toward primary care (21/22，95%). The QUAL interview revealed that both the Tongji and McGill organizers noted that TUSM showed strong leadership in organization, education, and coordination. Both students and teachers agreed that by adapting training content into contextualized delivery formats and settings, the Tongji Program successfully overcame language and technology barriers. Conclusions Committed partnerships and contextualization were key to the success of the Tongji Program. Future research should focus on how international primary care education programs affect learners' behavior in their practice settings, and explore barriers and facilitators to change.

Abstract Background Chronic exposure to microorganisms inside homes can impact respiratory health. Few studies have used advanced sequencing methods to examine adult respiratory outcomes, especially continuous measures. We aimed to identify metagenomic profiles in house dust related to the quantitative traits of pulmonary function and airway inflammation in adults. Microbial communities, 1264 species (389 genera), in vacuumed bedroom dust from 779 homes in a US cohort were characterized by whole metagenome shotgun sequencing. We examined two overall microbial diversity measures: richness (the number of individual microbial species) and Shannon index (reflecting both richness and relative abundance). To identify specific differentially abundant genera, we applied the Lasso estimator with high-dimensional inference methods, a novel framework for analyzing microbiome data in relation to continuous traits after accounting for all taxa examined together. Results Pulmonary function measures (forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio) were not associated with overall dust microbial diversity. However, many individual microbial genera were differentially abundant (p-value < 0.05 controlling for all other microbial taxa examined) in relation to FEV1, FVC, or FEV1/FVC. Similarly, fractional exhaled nitric oxide (FeNO), a marker of airway inflammation, was unrelated to overall microbial diversity but associated with differential abundance for many individual genera. Several genera, including Limosilactobacillus, were associated with a pulmonary function measure and FeNO, while others, including Moraxella to FEV1/FVC and Stenotrophomonas to FeNO, were associated with a single trait. Conclusions Using state-of-the-art metagenomic sequencing, we identified specific microorganisms in indoor dust related to pulmonary function and airway inflammation. Some were previously associated with respiratory conditions; others were novel, suggesting specific environmental microbial components contribute to various respiratory outcomes. The methods used are applicable to studying microbiome in relation to other continuous outcomes. Video Abstract

This is an article in the field of process mineralogy. In order to solve the problem of color spot impurity sorting in high-purity mica, a sorting method of mica containing impurities based on image processing is proposed in this article. According to the state of color spot impurities of mica under different light sources, the influence of image illumination environment is studied. On this basis, the processing methods such as Gaussian filtering and Canny edge detection are studied. Finally, the image recognition and discrimination of mica ores are realized accurately, and good results are obtained in the recognition of three different types of mica ores.

BackgroundDeep Brain Stimulation (DBS) has been widely applied and accepted in the treatment of neurological and psychiatric disorders. Despite numerous studies exploring the effects of DBS on the progression of neurodegenerative diseases and the treatment of advanced Parkinson’s disease (PD), there is a limited number of articles summarizing this research. The purpose of this study is to investigate the current trends, hot topics, and potential in research surrounding DBS therapy for PD, as well as to anticipate the challenges of such research.MethodsWe searched the Web of Science Core Collection database (WoSCC) for DBS research literature related to PD published from January 2014 to January 2024, utilized CiteSpace, VOS viewer, the bibliometric online analysis platform, Scimago Graphica, Microsoft Excel 2021, and R software version 4.2.3 for data analysis. And we conducted quantitative research on publications, citations, journals, authors, countries, institutions, keywords, and references, visualized the results in network graphs.ResultsFrom 2014 to 2024, papers from 39 journals from 11 countries were among the top 100 cited. Most papers were published in Neurology, with the highest average citations per paper in Nature Neuroscience. The United States (US) contributed the most publications, followed by the United Kingdom (UK) and Germany. In terms of total publications, University College London (UCL) contributed the most papers. The primary classifications of articles were Clinical Neurology, Neurosciences, and Surgery. The top five keywords were subthalamic nucleus, DBS, PD, medical therapy, and basal ganglia. Cluster analysis indicates that DBS research focus on improving quality of life and applying computational models.ConclusionThrough bibliometric analysis, researchers could quickly and clearly understand the hotspots and boundaries of their research field, thus guiding their research direction and scope to improve research efficiency and the quality of outcomes. Although studies indicate that DBS is currently a crucial method for treating advanced PD, in the long run, creating a personalized, low-cost treatment regimen with precise targeting and long-term efficacy poses a challenge.

With the rapid development of intermittent renewable energy, large-scale compressed air energy storage technology represented by Adiabatic Compressed Air Energy Storage (A-CAES) has attracted much attention. In order to simultaneously solve the problems of reuse of decommissioned oil wells and low efficiency of A-CAES system, a compressed air energy storage system incorporating abandoned oil wells as Air Storage Tank (AST) is proposed in this paper. The system performance of underground Oil Well CAES (OW-CAES), aboveground Steel Pipeline CAES (SP-CAES), and aboveground Storage Tank CAES (ST-CAES) is comparatively analyzed based on a thermodynamic model, focusing on the impact of heat transfer characteristic parameters of the AST wall on the system performance. The results show that recoverable heat and round-trip efficiency are significantly affected by the heat transfer characteristics of the AST wall. More recoverable heat and higher round-trip efficiency can be achieved by increasing the wall temperature and the surface area of the AST, respectively. The round-trip efficiency and energy storage density of the OW-CAES system are higher than those of the ST-CAES system, which are increased by 8.3 % and 18.45 % respectively. This study provides theoretical support for the feasibility of the OW-CAES system and has certain engineering guiding significance.

This paper analyzes the current situation and existing problems of coal roadway driving technologies and equipment, introduces the new mode, technology, equipment of coal roadway rapid driving with integrated drilling and anchoring and its underground applications. The bolting technologies and equipment with integrated drilling and anchoring are developed which include the integrated drilling and anchoring bolt, pumpable resin, drilling boom and drill rig as well as bolts cartridge with integrated drilling and anchoring, pump unit and intelligence control system. The new technology simplifies the traditional six-step rock bolting process to one continuous step. Rock bolting can be realized automatically by pressing button once and the operation time for installing a single bolt can be reduced from 5 to 6 minutes to 3 minutes. The technologies and equipment of automatic spraying support are developed which include high-strength, rapid setting, and deformable surface supporting spraying materials with a tensile strength exceeding 9 MPa, elongation at break exceeding 100%, and a bonding strength exceeding 3 MPa. The spraying system with 6-degree-of-freedom manipulator is developed which can automatically and rapidly spray during roadway driving. The dynamic monitoring technology and system for roadway surrounding rock deformation are developed during driving which can achieve a surface deformation monitoring of roadway in environments with dust, multiple interference, and low illumination. The monitoring accuracy can meet the requirements of the surrounding rock stability evaluation. A new partitioned parallel collaborative rapid driving mode of excavation, spraying, bolting and transport is proposed and a complete set of roadway rapid driving equipment with integrated drilling and anchoring is developed. The displacement and stability of the surrounding rock during the driving process at the Caojiatan Coal Mine in Shaanxi Province are monitored. In terms of time, more than 80% of the surrounding rock displacement had already occurred in 2 to 3 hours after the excavation of the roadway. In terms of space, more than 90% of the surrounding rock displacement had already occurred at a distance equivalent to twice the width of the roadway from the excavation face. Therefore, the roadway surrounding rock displacement caused by rapid driving can be completed in a short time, requiring timely and rapid support. The nearly 6 000 m roadway driving project has been completed in the 10-metre-extra-high fully mechanized mining face of the Caojiatan Coal Mine, and over 60 000 bolts with integrated drilling and anchoring are installed. The time for installing a single bolt, the number of supporting workers, and the labor intensity of workers have been significantly reduced. The driving speed, efficiency, and automation level have been significantly improved. The displacement of the experimental roadway roof is small. The roadway surrounding rock stability is good as well as the support effect. The coal roadway rapid driving technology and equipment with integrated drilling and anchoring have achieved a success in underground field test. It has the ability to achieve a monthly driving footage of 1500 to 2000 m for ultra-large cross-section coal roadways.

Using a convective scale WRF-GSI system and a reflectivity observation operator based on the double-moment microphysics (Thompson) scheme, simulated radar reflectivity data are produced and then directly assimilated with EnKF through Observing System Simulation Experiments (OSSEs) for the case of typhoon In-Fa (2021). We examined the ability of the EnKF to simultaneously estimate state variables and conducted sensitivity tests to evaluate the impact of updating different state variables. The results show that updating a full set of analysis variables can help obtain highly precise initial fields in the model and improve typhoon forecast skills. Excluding the horizontal wind update will affect the adjustment of the temperature field and the sea level pressure field during the cyclic assimilation process. Updating the variables directly related to the reflectivity operator alone could adjust hydrometers well, but the positive impact arising from the assimilation quickly vanishes during the forecast. In addition, this study also includes a quantitative RMSE analysis for each variable during the assimilation cycle and compares the effect of each schemes on different variables.

The food and agriculture sector is a cornerstone of critical infrastructure (CI), underpinning global food security, public health, and economic stability. However, the increasing digitalization and connectivity of operational technologies (OTs) in this sector expose it to significant cybersecurity risks. Blockchain technology (BT) has emerged as a transformative solution for addressing these challenges by enhancing network security, traceability, and system resilience. This study presents a comprehensive review of BT applications in OT security for food and agriculture CI, employing bibliometric and content analysis methods. A total of 124 relevant articles were identified from six databases, including the Web of Science Core Collection and MEDLINE®. Bibliometric analysis was conducted across five dimensions: publication year, literature type, journal distribution, country contributions, and keyword trends. The findings are meticulously organized through tables, charts, and graphs. The year 2018 marked a surge in research within this domain, with the IEEE Internet of Things Journal and IEEE ACESS emerging as the most prolific journals, each boasting nine publications. The United States, China, and India are at the forefront in terms of journal citation counts. Our analysis determined that a reference count of 37 serves as an appropriate threshold. Otoum Safa stands out as the author with the highest number of published articles, totaling four. Keywords such as “blockchain”, “internet of things”, “smart contract”, “security”, and “critical infrastructure” appear with significant frequency. The statistics, trends, and insights gleaned from this bibliometric analysis can guide researchers in the OTCI field to forge a coherent and logical research trajectory. Content analysis further identified six key research areas within this domain: identity authentication and data verification, secure access control, attack detection and perception, data security and protection, data backup and recovery, and attack assessment and attribution. Based on these insights, a general framework is proposed to guide future research and practical applications of BT in securing OT within food and agriculture CI. This study systematically analyzes the current research landscape, challenges, and opportunities for BT in securing the OT critical to food and agriculture CI. By bridging the gap between blockchain innovations and the operational needs of the food and agriculture sector, this work contributes to advancing strategic implementation and improving the security of CI systems.

ABSTRACT: The recent emergence of hepatitis-hydropericardium syndrome caused by highly pathogenic fowl adenovirus serotype 4 (FAdV-4) has resulted in significant economic losses to the poultry industry. However, the early innate immune response of immune organs within 24 hpi and the induction of autophagy in vivo after FAdV-4 infection have not been fully elucidated. In this study, 35-day-old specific pathogen-free (SPF) chickens were artificially infected with hypervirulent FAdV-4, which resulted in a mortality rate of up to 90%. The results showed that FAdV-4 infection rapidly triggered the innate immune response in vivo of chickens, with the spleen eliciting a stronger innate immune response than the thymus and bursa. During the early stage of viral infection within 24 hpi, the main receptors TLR3/7/21, MDA5, and cGAS were activated via the NF-κB and TBK1/IRF7-dependent signaling pathways, which up-regulated production of inflammatory cytokines and type I interferons. Additionally, the expression levels of the autophagy-related molecules LC3B, Beclin1, and ATG5 were significantly up-regulated at 24 hpi, while degradation of SQSTM1/p62 was observed, suggesting that FAdV-4 infection elicits a complete autophagy response in the spleen. Besides, the colocalization of Fiber2 and LC3B suggested that FAdV-4 infection induced autophagy which benefits FAdV-4 replication in vivo. This study provides new insights into the immunoregulation signal pathways of the early innate immunity in response to hypervirulent FAdV-4 infection in vivo within 24 hpi and the close relationship between viral replication and autophagy.

Elaidic acid (EA) stimulation can lead to endoplasmic reticulum stress (ERS), accompanied by a large release of Ca2+, and ultimately the activation of NLRP3 inflammasome in Kupffer cells (KCs). Mitochondrial instability or dysfunction may be the key stimulating factors to activate NLRP3 inflammasome, and sustained Ca2+ transfer can result in mitochondrial dysfunction. We focused on KCs to explore the damage to mitochondria by EA. After EA stimulation, cells produced an oxidative stress (OS) response with a significant increase in ROS release. Immunoprecipitation experiments and the addition of inhibitors revealed that the increase in the level of intracellular Ca2+ led to Ca2+ accumulation in the mitochondrial matrix via mitochondria-associated membranes (MAMs). This was accompanied by a significant release of mROS, loss of MMP and ATP, and a significant increase in mitochondrial permeability transition pore opening, ultimately leading to mitochondrial instability. These findings confirmed the mechanism that EA induced mitochondrial Ca2+ imbalance in KCs via MAM, ultimately leading to mitochondrial dysfunction. Meanwhile, EA induced OS and the decrease of MMP and ATP in rat liver, and significant lesions were found in liver mitochondria. Swelling of the inner mitochondrial cristae and mitochondrial vacuolization occurred, with a marked increase in lipid droplets.

Abstract Objectives The aim of this study was to use deep learning (DL) of intraoperative images of urinary stones to predict the composition of urinary stones. In this way, the laser frequency and intensity can be adjusted in real time to reduce operation time and surgical trauma. Materials and methods A total of 490 patients who underwent holmium laser surgery during the two-year period from March 2021 to March 2023 and had stone analysis results were collected by the stone laboratory. A total of 1658 intraoperative stone images were obtained. The eight stone categories with the highest number of stones were selected by sorting. Single component stones include calcium oxalate monohydrate (W1), calcium oxalate dihydrate (W2), magnesium ammonium phosphate hexahydrate, apatite carbonate (CH) and anhydrous uric acid (U). Mixed stones include W2 + U, W1 + W2 and W1 + CH. All stones have intraoperative videos. More than 20 intraoperative high-resolution images of the stones, including the surface and core of the stones, were available for each patient via FFmpeg command screenshots. The deep convolutional neural network (CNN) ResNet-101 (ResNet, Microsoft) was applied to each image as a multiclass classification model. Results The composition prediction rates for each component were as follows: calcium oxalate monohydrate 99% (n = 142), calcium oxalate dihydrate 100% (n = 29), apatite carbonate 100% (n = 131), anhydrous uric acid 98% (n = 57), W1 + W2 100% (n = 82), W1 + CH 100% ( n = 20) and W2 + U 100% (n = 24). The overall weighted recall of the cellular neural network component analysis for the entire cohort was 99%. Conclusion This preliminary study suggests that DL is a promising method for identifying urinary stone components from intraoperative endoscopic images. Compared to intraoperative identification of stone components by the human eye, DL can discriminate single and mixed stone components more accurately and quickly. At the same time, based on the training of stone images in vitro, it is closer to the clinical application of stone images in vivo. This technology can be used to identify the composition of stones in real time and to adjust the frequency and energy intensity of the holmium laser in time. The prediction of stone composition can significantly shorten the operation time, improve the efficiency of stone surgery and prevent the risk of postoperative infection.

Multimodal aspect term extraction (MATE) and multimodal aspect-oriented sentiment classification (MASC) are two crucial subtasks in multimodal sentiment analysis. The use of pretrained generative models has attracted increasing attention in aspect-based sentiment analysis (ABSA). However, the inherent semantic gap between textual and visual modalities poses a challenge in transferring text-based generative pretraining models to image-text multimodal sentiment analysis tasks. To tackle this issue, this paper proposes a self-adaptive cross-modal attention fusion architecture for joint multimodal aspect-based sentiment analysis (JMABSA), which is a generative model based on an image-text selective fusion mechanism that aims to bridge the semantic gap between text and image representations and adaptively transfer a textual-based pretraining model to the multimodal JMASA task. We conducted extensive experiments on two benchmark datasets, and the experimental results show that our model significantly outperforms other state of the art approaches by a significant margin.

Reconfigurable metasurface, also known as Reconfigurable Intelligent Surfaces (RIS), with its flexible beamforming, low-cost, and easy industrial deployment characteristics, presents many interesting solutions in wireless application scenarios. This paper presents a sophisticated reconfigurable metasurface architecture that introduces an advanced concept of flexible full-array space-time wavefront manipulation with enhanced dynamic capabilities. The practical 2-bit phase-shifting unit cell on the RIS is distinguished by its ability to maintain four stable phase states, each with 90° differences, and features an insertion loss of less than 0.6 dB across a bandwidth of 200 MHz. All reconfigurable unit cells are equipped with meticulously designed control circuits, governed by an intelligent core composed of multiple Micro-Controller Units (MCUs), enabling rapid control response across the entire RIS array. Owing to the capability of each unit cell on the metasurface to independently switch states, the entire RIS is not limited to controlling general beams with specific directional patterns but also generates beams with more complex structures, including multi-focus 3D spot beams and vortex beams. This development substantially broadens its applicability across various industrial wireless transmission scenarios. Moreover, by leveraging the rapid-respond space-time coding and the full-array independent programmability of the RIS prototyping operating at 10.7 GHz, we have demonstrated that: 1) The implementation of 3D spot beams scanning facilitates dynamic beam tracking and real-time communication under the indoor near-field scenario; 2) The rapid wavefront rotation of vortex beams enables precise modulation of signals within the Doppler domain, showcasing an innovative approach to wireless signal manipulation; 3) The beam steering experiments for blocking users under outdoor far-field scenarios, verifying the beamforming capability of the RIS board.

AbstractSorafenib (SRF) presents undesirable effects in clinical treatment, due to the lack of targeting, poor water solubility, and obvious side effects. In this study, we constructed a novel nanodrug carrier system for accurate and efficient delivery of SRF, improving its therapeutic effects and achieving tumor-specific imaging. The hollow mesoporous MnO2 (H-MnO2) nanoparticles equipped with target substance aptamers (APT) on the surface were used to load SRF for the first time. The resulting H-MnO2-SRF-APT could specifically bound to glypican-3 (GPC3) receptors on the surface of hepatocellular carcinoma (HCC), rapidly undergoing subsequent degradation under decreased pH conditions in the tumor microenvironment (TME) and releasing the loaded SRF. In this process, Mn2+ ions were used for T1-weighted magnetic resonance imaging simultaneously. The in vitro cell experiments indicated that H-MnO2-SRF-APT showed much more effects on the inhibition in the proliferation of Huh7 and HepG2 HCC cells than that of the non-targeted H-MnO2-SRF and free SRF. Besides, the in vivo results further confirmed that H-MnO2-SRF-APT could effectively inhibit the growth of xenograft tumors Huh7 in the naked mouse with good biosafety. In conclusion, H-MnO2-SRF-APT could significantly enhance the therapeutic effect of SRF and is expected to be a new way of diagnosis and treatment of HCC.

Despite the well-known importance of radar data assimilation, there are limited studies on landfalling typhoons in terms of directly assimilating radar reflectivity data, especially using a reflectivity operator based on double-moment microphysics. In this study, radar reflectivity data assimilation experiments are conducted with an ensemble Kalman filter (EnKF), using simulated observations in an Observing System Simulation Experiment (OSSE) framework for the landfalling typhoon In-Fa. With an OSSE, it is convenient to analyze the impact of assimilation of radar reflectivity on analysis and forecast for various state variables, especially for hydrometeors. Our results show that the direct assimilation of radar reflectivity with EnKF does not introduce non-physical hydrometeors and is able to adjust well, not only to hydrometers, but also to some large-scale variables which are not directly related to reflectivity, especially in terms of temperature and vertical velocity. Though the most notable reduction in the Root Mean Square Errors (RMSEs) is observed through mixing the ratio of rainwater and snow, the analysis of other variables is also significantly improved with the accumulation of assimilation cycles. The correlation analysis reveals the strongest correlation between radar reflectivity data and hydrometeor-related variables as well as the correlation with certain large-scale variables, indicating that these cross-variables are updated well through the reliable multivariate ensemble covariance in the EnKF. As a result, an obvious improvement in typhoon intensity and precipitation forecast is obtained in the data assimilation experiment. The impact of assimilation on radar reflectivity can last for up to 15–16 h.

Micro-stereolithography (μSL) is an advanced additive manufacturing technique that enables the fabrication of highly precise microstructures with fine feature resolution. One of the primary challenges in μSL is achieving and maintaining precise focus throughout the fabrication process. For the successful application of μSL, it is essential to maintain the sample surface within a focal depth of several microns. Despite the growing interest in auto-focus devices, limited attention has been directed towards auto-focus systems in image-based auto-focus microscope systems for precision μSL. To address this challenge, we propose an image-based auto-focus microscope system incorporating visual servo control. In the optical design, a transflective beam splitter is employed, allowing the laser beam to pass through for fabrication while reflecting the focused beam on the sample surface to the microscope and camera. Utilizing captured spot images and the Foucault knife-edge test, a deep learning-based laser spot image processing algorithm is developed to determine the focus position based on spot size and the number of spot pixels on both sides. Experimental results demonstrate that the proposed auto-focus system effectively determines the relative position of the focal point using the laser spot image and achieves auto-focusing through visual servo control.

Skin tissue-resident memory T (Trm) cells are produced by antigenic stimulation and remain in the skin for a long time without entering the peripheral circulation. In the healthy state Trm cells can play a patrolling and surveillance role, but in the disease state Trm cells differentiate into various phenotypes associated with different diseases, exhibit different localizations, and consequently have local protective or pathogenic roles, such as disease recurrence in vitiligo and maintenance of immune homeostasis in melanoma. The most common surface marker of Trm cells is CD69/CD103. However, the plasticity of tissue-resident memory T cells after colonization remains somewhat uncertain. This ambiguity is largely due to the variation in the functionality and ultimate destination of Trm cells produced from memory cells differentiated from diverse precursors. Notably, the presence of Trm cells is not stationary across numerous non-lymphoid tissues, most notably in the skin. These cells may reenter the blood and distant tissue sites during the recall response, revealing the recycling and migration potential of the Trm cell progeny. This review focuses on the origin and function of skin Trm cells, and provides new insights into the role of skin Trm cells in the treatment of autoimmune skin diseases, infectious skin diseases, and tumors.

The spatial accessibility of emergency shelters, indicating the difficulty of evacuation and rescue, is crucial for disaster mitigation and emergency management. To analyze accessibility, an effective approach is to evaluate the service capacity of emergency shelters. Multifaceted factors were employed to enhance the quantitative accuracy of accessibility indicators. However, scenario-specific analysis has not been emphasized. Considering the devastating potential of great earthquake disasters, we cannot ignore the impact of these scenarios on emergency shelter accessibility, especially in areas with high seismic risk. In this study, we developed an earthquake scenario-specific framework for spatial accessibility analysis (SAA), which integrates the service capacity of emergency shelters and the impact of strong ground motion and fault rupturing. We applied this framework to the urban area of Xichang City in Sichuan Province, western China. Xichang City, located in the linked area of the Anninghe fault and Zemuhe fault with many extreme historical earthquake disaster records, is prone to high seismic risk. We firstly collected emergency shelter and road network data in Xichang City. We then applied SAA based on the road network, using the network analysis method. After that, we analyzed the impact of strong ground motion on accessibility and generated the setback zone of fault rupturing. We integrated the effect of strong ground motion on accessibility within the setback zone of active faults. Finally, we generated a comprehensive accessibility map, considering both the predicted strong ground motion and potential fault rupturing. Our results show that the accessibility level changed in several towns of urban Xichang City due to strong ground motion and fault rupturing. The accessibility level decreased in Lizhou, Xingsheng, and Anning Towns. For areas with mapped fault lines, the accessibility level is Very-Low. Our results demonstrate the impact of earthquake damage on the accessibility of emergency shelters and the complexity of evacuation in earthquake scenarios. In general, we added earthquake rupturing and ground motion characteristics into the SAA framework. This framework will help us enhance the reliability of SAA and the feasibility of seismic vulnerability evaluation.

ABSTRACTβ-Si3N4 whiskers were synthesized by using a moderately low-temperature heat-treatment process, with the aid of a low weight fraction of multiple aids (Y2O3-MgO). The synthesis conditions and aspect ratio of the whiskers were adjusted by changing the MgO content in the composite additive system, heat treatment temperature and holding time. The phase composition and morphology of the whiskers were analyzed by XRD and SEM, respectively. The phase transformation could be completed at 1700°C by introducing only 0.5 wt% MgO. The heat-treated temperature was successfully further reduced to 1650°C by extending the holding time to 5 h. The introduction of MgO can make the whiskers form rapidly at a lower temperature. By introducing a small amount of MgO and appropriately extending the holding time at a lower treatment temperature has been proved to be an effective method to obtain β-Si3N4 whiskers with higher aspect ratio under mild conditions.

Due to the complexity of the missile air data system (ADS) and the harshness of the environment in which its sensors operate, the effectiveness of traditional fault diagnosis methods is significantly reduced. To this end, this paper proposes a method fusing the model and neural network based on unscented Kalman filter (UKF) and Inception V3 to enhance fault diagnosis performance. Initially, the unscented Kalman filter model is established based on an atmospheric system model to accurately estimate normal states. Subsequently, in order to solve the difficulties such as threshold setting in existing fault diagnosis methods based on residual observers, the UKF model is combined with a neural network, where innovation and residual sequences of the UKF model are extracted as inputs for the neural network model to amplify fault characteristics. Then, multi-scale features are extracted by the Inception V3 network, combined with the efficient channel attention (ECA) mechanism to improve diagnostic results. Finally, the proposed algorithm is validated on a missile simulation platform. The results show that, compared to traditional methods, the proposed method achieves higher accuracy and maintains its lightweight nature simultaneously, which demonstrates its efficiency and potential of fault diagnosis in missile air data systems.

Layered composite roofs are characterized by developed bedding fissures, resulting in severe deformation and damage of rock bolts at the top of the roadway, as well as a poor roadway support effect. Increasing pretension force is an effective way to enhance the stiffness of the rock bolt support system. To clarify the influence and mechanism of the pretension force on the support effect of rock bolts in the layered roof, a roadway model of the layered roof was established using the interface unit of FLAC3D, and the simulation rock bolts were constructed using the pile unit, which can simulate the mechanical behaviors of rock bolts, such as tension, shear, bending, fracture, and anchor failure, and the pretension force was applied. On this basis, the deformation and failure characteristics and influencing factors of rock bolts in the layered roadway roof under different surrounding rock conditions were simulated and analyzed. The research shows the following: ① Field measurements showed minor shear deformation in the rock bolts at the center of the roadway roof, with lateral displacements of 5.7 cm and 5.3 cm. Significant shear deformation occurred in the rock bolts at the roof corners, with lateral displacements of 18.2 cm and 17.6 cm. ② Simulations of rock bolt deformation characteristics matched the field measurements closely, confirming the reliability of the simulation method, parameter selection, and calculation sequence. ③ The primary factors affecting rock bolt deformation are the structural plane strength and surrounding rock strength. Rock bolts are most susceptible to lateral displacement when the structural plane strength is low, the strength difference between rock layers is large, and the weaker layer is below the structural plane. The presented research can provide a reference for the instability mechanism and support treatment of the layered composite roof roadway.

To improve the deteriorated performance caused by CO2 release during the curing process of traditional moisture-crosslinked polyurethane or polyurea and poor flame retardancy, this work realized an effective in situ crosslinking technique triggered by moisture for poly(urethane-urea) with intrinsic flame retardancy, through the incorporation of trimethoxysilane and phosphorus groups via a continuous two-stage process. Moisture-triggered crosslinking reaction of trimethoxysilane groups resulted in the establishment of a robust Si─O─Si network, as confirmed by Fourier transform infrared spectroscopy (FTIR) test. The structure transformation considerably enhanced the material’s strength, with the stress at break increasing from 1.0 to 3.2 MPa and modulus from 32.9 to 46.9 MPa. The flame retardant properties of PUUS1 (poly(urethane-urea) sample) were investigated through limiting oxygen index (LOI) and cone calorimeter (CCT) analysis, demonstrating satisfactory flame resistance, as evidenced by high LOI value of 29%, high char yield of 46.2%, and controlled smoke production. Combining thermogravimetric analysis-infrared spectrometry (TG-IR), X-ray photoelectron spectroscopy (XPS), and flame retardant performance, it is speculated that the generation of phosphorus-free radical scavengers in gas phase from diethyl bis(2-hydroxyethyl) aminomethyl phosphonate (DBHAP), coupled with the barrier effects of charred layer and distinctive Si─O─Si framework in condensed phase inhibited combustion and toxic gas emission. The results highlight the successful synthesis of a moisture-crosslinkable poly(urethane-urea) with intrinsic flame retardancy, promising for applications necessitating moisture-crosslinkable materials with superior flame resistance.

Vibrio is a prevalent bacterial genus in aquatic environments and exhibits diverse metabolic capabilities, playing a vital role in marine biogeochemical cycles. This study isolated a novel virus infecting Vibrio cyclitrophicus, vB_VviC_ZQ26, from coastal waters near Qingdao, China. The vB_VviC_ZQ26 comprises a linear double-stranded DNA genome with a length of 42,982 bp and a G + C content of 43.21 %, encoding 72 putative open reading frames (ORFs). Transmission electron microscope characterization indicates a siphoviral-morphology of vB_VviC_ZQ26. Nucleic-acids-wide analysis indicates a tetranucleotide frequency deviation for genomic segments encoding putative gene transfer agent protein (GTA) and coil-containing protein, implying divergent origins occurred in different parts of viral genomes. Phylogenetic and genome-content-based analysis suggest that vB_VviC_ZQ26 represents a novel vibriophage-specific family designated as Coheviridae. From the result of biogeographic analysis, Coheviridae is mainly colonized in the temperate and tropical epipelagic zones. This study describes a novel vibriophage infecting V. cyclitrophicus, shedding light on the evolutionary divergence of different parts of the viral genome and its ecological footprint in marine environments.

BackgroundPrevious observational studies have provided cumulative data linking gut microbiota to myasthenia gravis (MG). However, the causal link between the two remains unexplored. Hence, the current study was performed to explore the causal link between them.MethodsMendelian randomization (MR) analysis was conducted using the summary statistics of 211 gut microbiota taxa and the largest genome-wide association studies (GWAS) for MG currently available. The inverse variance-weighted (IVW), MR-Egger, weighted median, and weighted mode methods were employed to ascertain the causal influence. Sensitivity studies utilizing several methodologies were then used to assess the robustness of the findings. Lastly, to evaluate reverse causality, a reverse MR analysis was performed.ResultsSeven suggestive causal associations between the gastrointestinal microbiota and MG were identified based on the outcomes of the MR analysis. Specifically, phylum Actinobacteria (OR: 0.602, 95% CI: 0.405–0.896, p = 0.012), class Gammaproteobacteria (OR: 0.587, 95% CI: 0.357–0.968, p = 0.037), and families Defluviitaleaceae (OR: 0.695, 95% CI: 0.485–0.996, p = 0.047), Family XIII (OR: 0.614, 95% CI: 0.412–0.916, p = 0.017), and Peptococcaceae (OR: 0.698, 95% CI: 0.505–0.964, p = 0.029) had suggestive protective effects on MG, while order Mollicutes RF9 (OR: 1.424, 95% CI: 1.015–1.998, p = 0.041) and genus Faecalibacterium (OR: 1.763, 95% CI: 1.220–2.547, p = 0.003) were suggestive risk factors for MG. The outcomes indicate that neither heterogeneity nor horizontal pleiotropy had any discernible impact. Nevertheless, this reverse analysis did not reveal any apparent effect of MG on the gut microbiota composition.ConclusionThe MR investigation has substantiated the suggestive causal connection between gut microbiota and MG, which may provide helpful insights for innovative therapeutic and preventative approaches for MG. Further randomized controlled trials are needed to elucidate the gut microbiota’s precise role and therapeutic potential in the pathogenesis of MG.

Ziyuglycoside I and ziyuglycoside II are important active components of Sanguisorba officinalis L., which have excellent pharmacological effects, such as antioxidant and anticancer effects. However, the bioavailability of ziyuglycoside I and ziyuglycoside II has not been reported. This work aims to establish a UPLC-MS/MS method to study the pharmacokinetics of ziyuglycoside I and ziyuglycoside II in rats under different administration routes (intragastric and intravenous administration) and to calculate the bioavailability. The concentration of ziyuglycoside I and ziyuglycoside II in rat plasma in the range of 2–2000 ng/mL showed a good linear relationship (r > 0.99). The intra-day accuracies of ziyuglycoside I and ziyuglycoside II ranged from 87% to 110%, and the inter-day accuracies ranged from 97% to 109%. The intra-day precision was less than 15% and the inter-day precision was less than 14%. The matrix effects ranged from 88% to 113%. The recoveries were all above 84%. The developed UPLC-MS/MS method for the determination of ziyuglycoside I and ziyuglycoside II in rat plasma was applied to pharmacokinetics. The bioavailability of ziyuglycoside I and ziyuglycoside II was measured at 2.6% and 4.6%, respectively.

BackgroundIncreasing ownership of smartphones among Americans provides an opportunity to use these technologies to manage medical conditions. We examine the influence of baseline smartwatch ownership on changes in self-reported anxiety, patient engagement, and health-related quality of life when prescribed smartwatch for AF detection.MethodWe performed a post-hoc secondary analysis of the Pulsewatch study (NCT03761394), a clinical trial in which 120 participants were randomized to receive a smartwatch-smartphone app dyad and ECG patch monitor compared to an ECG patch monitor alone to establish the accuracy of the smartwatch-smartphone app dyad for detection of AF. At baseline, 14 days, and 44 days, participants completed the Generalized Anxiety Disorder-7 survey, the Health Survey SF-12, and the Consumer Health Activation Index. Mixed-effects linear regression models using repeated measures with anxiety, patient activation, physical and mental health status as outcomes were used to examine their association with smartwatch ownership at baseline.ResultsNinety-six participants, primarily White with high income and tertiary education, were randomized to receive a study smartwatch-smartphone dyad. Twenty-four (25%) participants previously owned a smartwatch. Compared to those who did not previously own a smartwatch, smartwatch owners reported significant greater increase in their self-reported physical health (β = 5.07, P

Abstract Nuclear decoupling and softening are the main cellular mechanisms to resist mechanical stress-induced nuclear/DNA damage, however, its molecular mechanisms remain much unknown. Our recent study of Hutchinson-Gilford progeria syndrome (HGPS) disease revealed the role of nuclear membrane protein Sun2 in mediating nuclear damages and cellular senescence in progeria cells. However, the potential role of Sun2 in mechanical stress-induced nuclear damage and its correlation with nuclear decoupling and softening is still not clear. By applying cyclic mechanical stretch to mesenchymal stromal cells (MSCs) of WT and Zmpset24−/− mice (Z24−/−, a model for HGPS), we observed much increased nuclear damage in Z24−/− MSCs, which also featured elevated Sun2 expression, RhoA activation, F-actin polymerization and nuclear stiffness, indicating the compromised nuclear decoupling capacity. Suppression of Sun2 with siRNA effectively reduced nuclear/DNA damages caused by mechanical stretch, which was mediated by increased nuclear decoupling and softening, and consequently improved nuclear deformability. Our results reveal that Sun2 is greatly involved in mediating mechanical stress-induced nuclear damage by regulating nuclear mechanical properties, and Sun2 suppression can be a novel therapeutic target for treating progeria aging or aging-related diseases.

Abstract The degradation of photovoltaic modules has an impact on various parameters of photovoltaic modules. Ignoring the degradation of photovoltaic modules or inaccurate estimation of the degradation will lead to wrong power dispatching strategies and lead to economic losses. For PV module life estimation or reliability estimation, it is necessary to first establish an accurate statistical degradation model of PV module. The main goal of this paper is to analyze a selection of explicit PV module degradation model based on distribution. Since the degradation is related to time, the study assumed that those parameters in Gamma or Gaussian distributions are related to time. Five models are calculated based on maximum likelihood estimation and particle swarm optimization. Through verification and comparison on the measured PV module degradation data, the performance of these models in four cases: long‐term data fitting, long‐term data prediction, single‐module short‐term data fitting, and multimodule short‐term data fitting are evaluated. The results show that the model proposed in this paper has a great improvement over the original model, and the constant‐σ Gaussian distribution degradation model achieves the best performance.

Abstract We aimed to identify the molecular biomarkers of MDD disease progression to uncover potential mechanisms of major depressive disorder (MDD). In this study, three microarray data sets, GSE44593, GSE12654, and GSE54563, were cited from the Gene Expression Omnibus database for performance evaluation. To perform molecular functional enrichment analyses, differentially expressed genes (DEGs) were identified, and a protein–protein interaction network was configured using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. To assess multi-purpose functions and pathways, such as signal transduction, plasma membrane, protein binding, and cancer pathways, a total of 220 DEGs, including 143 upregulated and 77 downregulated genes, were selected. Additionally, six central genes were observed, including electron transport system variant transcription factor 6, FMS-related receptor tyrosine kinase 3, carnosine synthetase 1, solute carrier family 22 member 13, prostaglandin endoperoxide synthetase 2, and protein serine kinase H1, which had a significant impact on cell proliferation, extracellular exosome, protein binding, and hypoxia-inducible factor 1 signaling pathway. This study enhances our understanding of the molecular mechanism of the occurrence and progression of MDD and provides candidate targets for its diagnosis and treatment.

Abstract Astrocytes play a crucial role in regulating sleep–wake behavior, and adenosine signaling is generally thought to be involved. Here we show multiple lines of evidence supporting that modulation of the sleep–wake behavior by astrocyte Ca2+ activity could occur without adenosine signaling. In the basal forebrain and the brainstem, two brain regions that are known to be essential for sleep–wake regulation, chemogenetically-induced astrocyte Ca2+ elevation significantly modulated the sleep–wake cycle. Although astrocyte Ca2+ level positively correlated with the amount of extracellular adenosine, as revealed by a genetically encoded adenosine sensor, we found no detectable change in adenosine level after suppressing astrocyte Ca2+ elevation, and transgenic mice lacking one of the major extracellular ATP-adenosine conversion enzymes showed similar extracellular adenosine level and astrocyte Ca2+-induced sleep modulation. Furthermore, astrocyte Ca2+ is dependent primarily on local neuronal activity, causing brain region-specific regulation of the sleep–wake cycle. Thus, neural activity-dependent astrocyte activity could regulate the sleep–wake behavior independent of adenosine signaling.

Abstract Background Osteosarcoma has been the most common primary bone malignant tumor in children and adolescents. Despite the considerable improvement in the understanding of genetic events attributing to the rapid development of molecular pathology, the current information is still lacking, partly due to the comprehensive and highly heterogeneous nature of osteosarcoma. The study is to identify more potential responsible genes during the development of osteosarcoma, thus identifying promising gene indicators and aiding more precise interpretation of the disease. Methods Firstly, from GEO database, osteosarcoma transcriptome microarrays were used to screen the differential expression genes (DEGS) in cancer comparing to normal bone samples, followed by GO/KEGG interpretation, risk score assessment and survival analysis of the genes, for the purpose of selecting a credible key gene. Further, the basic physicochemical properties, predicted cellular location, gene expression in human cancers, the association with clinical pathological features and potential signaling pathways involved in the key gene’s regulation on osteosarcoma development were in succession explored. Results Based on the selected GEO osteosarcoma expression profiles, we identified the differential expression genes in osteosarcoma versus normal bone samples, and the genes were classified into four groups based on the difference level, further genes interpretation indicated that the high differently level (> 8 fold) genes were mainly located extracellular and related to matrix structural constituent regulation. Meanwhile, module function analysis of the 67 high differential level (> 8 fold) DEGS revealed a 22-gene containing extracellular matrix regulation associated hub gene cluster. Further survival analysis of the 22 genes revealed that STC2 was an independent prognosis indicator in osteosarcoma. Moreover, after validating the differential expression of STC2 in cancer vs. normal tissues using local hospital osteosarcoma samples by IHC and qRT-PCR experiment, the gene’s physicochemical property revealed STC2 as a cellular stable and hydrophilic protein, and the gene’s association with osteosarcoma clinical pathological parameters, expression in pan-cancers and the probable biological functions and signaling pathways it involved were explored. Conclusion Using multiple bioinformatic analysis and local hospital samples validation, we revealed the gain of expression of STC2 in osteosarcoma, which associated statistical significantly with patients survival, and the gene’s clinical features and potential biological functions were also explored. Although the results shall provide inspiring insights into further understanding of the disease, further experiments and detailed rigorous clinical trials are needed to reveal its potential drug-target role in clinical medical use.

Photodynamic therapy (PDT) has been extensively investigated as a spatiotemporally noninvasive and controllable modality for cancer treatment. However, the intracellular antioxidant systems mainly consisting of thioredoxin (Trx) and glutathione (GSH) significantly counteract and prevent reactive oxygen species (ROS) accumulation, resulting in a serious loss of PDT efficiency. To address this challenge, we propose that PDT can be improved by precisely blocking antioxidant systems. After molecular engineering and synergistic cytotoxic optimization, a DSPE-PEG2K-modified dual-drug nanoassembly (PPa@GA/DSPE-PEG2K NPs) of pyropheophorbide a (PPa) and gambogic acid (GA) is successfully constructed. Interestingly, GA can effectively destroy intracellular antioxidant systems by simultaneously inhibiting Trx and GSH. Under laser irradiation, the cell-killing effects of PPa is significantly enhanced by GA-induced inhibition of the antioxidant systems. As expected, PPa@GA/DSPE-PEG2K nanoparticles demonstrate potent antitumor activity in a 4T1 breast tumor-bearing BALB/c mouse xenograft model. Such a carrier-free self-sensitized nanotherapeutic offers a novel co-delivery strategy for effective PDT.

Abstract It has been realized that thermal shear plays a similar role as thermal vorticity in polarizing spin of particles in heavy ion collisions. We point out that shear has a funda- mental difference that it leads to particle redistribution in the medium. The redistribution gives rise to an additional contribution to spin polarization through the self-energy, which is parametrically the same order as the one considered so far in the literature. The self-energy contribution is in general gauge dependent. We introduce double gauge links stretching along the Schwinger-Keldysh contour to restore gauge invariance. We also generalize the straight path to adapt to the Schwinger-Keldysh contour. We find another contribution associated with the gauge link, which is also parametrically the same order. We illustrate the two contributions with a massive probe fermion in massless QED plasma with shear. A modest suppression of spin polarization is found from the combined contributions when the probe fermion has momentum much greater than the temperature.

BackgroundAtrial fibrillation (AF) is a common cause of stroke, and timely diagnosis is critical for secondary prevention. Little is known about smartwatches for AF detection among stroke survivors. We aimed to examine accuracy, usability, and adherence to a smartwatch-based AF monitoring system designed by older stroke survivors and their caregivers. ObjectiveThis study aims to examine the feasibility of smartwatches for AF detection in older stroke survivors. MethodsPulsewatch is a randomized controlled trial (RCT) in which stroke survivors received either a smartwatch-smartphone dyad for AF detection (Pulsewatch system) plus an electrocardiogram patch or the patch alone for 14 days to assess the accuracy and usability of the system (phase 1). Participants were subsequently rerandomized to potentially 30 additional days of system use to examine adherence to watch wear (phase 2). Participants were aged 50 years or older, had survived an ischemic stroke, and had no major contraindications to oral anticoagulants. The accuracy for AF detection was determined by comparing it to cardiologist-overread electrocardiogram patch, and the usability was assessed with the System Usability Scale (SUS). Adherence was operationalized as daily watch wear time over the 30-day monitoring period. ResultsA total of 120 participants were enrolled (mean age 65 years; 50/120, 41% female; 106/120, 88% White). The Pulsewatch system demonstrated 92.9% (95% CI 85.3%-97.4%) accuracy for AF detection. Mean usability score was 65 out of 100, and on average, participants wore the watch for 21.2 (SD 8.3) of the 30 days. ConclusionsOur findings demonstrate that a smartwatch system designed by and for stroke survivors is a viable option for long-term arrhythmia detection among older adults at risk for AF, though it may benefit from strategies to enhance adherence to watch wear. Trial RegistrationClinicalTrials.gov NCT03761394; https://clinicaltrials.gov/study/NCT03761394 International Registered Report Identifier (IRRID)RR2-10.1016/j.cvdhj.2021.07.002

The flow and temperature properties of the magnetic fluid are the primary elements impacting the seal stability in the main shaft magnetic fluid seal of the turbine. This study investigated the eddy current and heat field of the magnetic fluid at the seal gap using a mix of numerical computation and experiment and came to the following conclusions: Under the pole tooth groove and the permanent magnet, the magnetic fluid creates symmetrical vortices in the clearance of the magnetic fluid seal device. Below the pole tooth, the magnetic fluid velocity is minimal and essentially constant. The pole shoe and spindle next to the air side of the magnetic fluid seal device have the lowest temperature, and the device’s core has the greatest temperature.

The nano drug delivery system MnO2/CDDP@PDA-Cy5.5 was synthesized in this study to increase the efficacy of Cisplatin (CDDP) on thyroid cancer and alleviate the damage to normal tissue, with the aim of enhancing the anti-cancer efficacy, increasing the drug load, optimizing the control of drug release, and alleviating the systemic toxicity arising from drug off-target. On that basis, high efficacy and low toxicity win-win can be obtained. In this study, hollow manganese dioxide nanoparticles (MnO2 NPs) were prepared based on the template method. CDDP was loaded into the hollow cavity and then modified with polydopamine (PDA) and Cy5.5, with the aim of obtaining the nano-drug loading system MnO2/CDDP@PDA-Cy5.5 NPs. The NPs precisely delivered drugs by intelligently responding to the tumor microenvironment (TME). As indicated by the release curves, the NPs release CDDP rapidly by inducing the decomposition of PDA and MnO2 under acidic or redox conditions, and Magnetic resonance imaging (MRI) contrast agent Mn2+ was generated. The results of the in vivo MRI studies suggested that T1 contrast at the tumor site was notably enhanced under the Enhanced permeability and retention (EPR) effect. After the intravenous administration, the effective tumor accumulation exhibited by the NPs was confirmed by magnetic resonance imaging as a function of time. Compared with free CDDP, the in vivo therapeutic effect was remarkably increased. As indicated by the above-described results, MnO2/CDDP@PDA-Cy5.5 NPs is a drug delivery system exhibiting diagnostic and therapeutic functions.

Background It remains unclear whether neuroimaging markers of cerebral small‐vessel disease (CSVD) affect the outcomes of patients with acute ischemic stroke receiving endovascular treatment (EVT). The aim of this systematic review and meta‐analysis was to evaluate the association between CSVD neuroimaging markers and outcomes in patients with acute ischemic stroke undergoing EVT. Methods We conducted a systematic search of PubMed and EMBASE databases up to July 2022 using keywords or Medical Subject Heading terms (“cerebral small‐vessel diseases,” “leukoaraiosis,” “microbleed,” “enlarged perivascular space,” “recent small subcortical infarct,” “atrophy,” “lacune,” and “thrombectomy”). The assessed clinical outcomes were a good functional outcome, 90‐day mortality, symptomatic intracranial hemorrhage, and early neurologic improvement after EVT. Results Overall, 30 studies on patients with acute ischemic stroke undergoing EVT were included. Patients with absent or mild white matter hyperintensities had higher good functional outcomes (odds ratio [OR], 2.94 [95% CI, 2.44–3.53]; P

Heavy metal (loid) pollution poses a serious threat to the health and habitability of ecosystems worldwide. This study aims to investigate the concentration, pollution degree, pollution sources, and health risks of heavy metal (loid)s (HMs) in soil of Shanxi Province, China. The concentrations of Cu, Ni, Cd, Pb, Hg and As were measured by ICP-MS in 146 soil samples collected from agricultural land. The pollution degree and ecological risks of HMs were analyzed by variety of indexes, and the human health risks were assessed using the USEPA model. Results showed the average concentrations of Cu, Cd, Pb, Hg and As were 1.08, 1.15, 1.44, 1.50 and 1.25 times higher than the background values in the soil of investigated areas, respectively. The contamination factors revealed moderate pollution of Hg, Pb, As, Cd and Cu in the investigated areas, and the pollution load index indicated considerable contamination. The Nemerow index revealed low to severe contamination with HMs. The potential ecological risk of HMs indicates that Hg and Cd pose a moderate risk threat to the soil ecology. Coal mining was the primary sources of soil HMs identified by ACPS-MLR. Soil As (75.1%) and Ni (62.3%) were mainly derived from coal mining, Pb (73.1%) was from traffic emissions, and Hg (38.6%) originated from coal combustion. The health risks associated with these HMs due to soil exposure were within the acceptable levels for adults. The As concentration imposes the strongest effect based on the non-carcinogenic risk analysis in different exposed populations. In conclusion, the higher concentration of soil HMs moderately threatens soil ecology, but there was no significant human health risk found in the study. Furthermore, this study reveals the potential risk and sources of HMs in Shanxi Province, which is helpful for managing contaminated soil in the region.

Previous studies have demonstrated that thinking dispositions and working memory are closely related to students’ critical thinking ability. However, little is known about whether bidirectionality between thinking dispositions, working memory, and critical thinking ability exists in adolescence. This study, therefore, explored this aspect across two time points. Participants were 509 Chinese adolescents (mean age at Time 1 = 14.09 years; 59.7% girls). At Time 1, adolescents were administered the measures of thinking dispositions, working memory, and critical thinking ability. They were reassessed using these measures at Time 2 one year later. The results revealed a bidirectional longitudinal relationship between adolescents’ thinking dispositions and critical thinking ability, suggesting that thinking dispositions at Time 1 predicted critical thinking ability at Time 2; critical thinking ability at Time 1 also predicted subsequent thinking dispositions in adolescents. Furthermore, working memory at Time 1 showed a larger predictive effect on critical thinking ability at Time 2 compared with thinking dispositions at Time 1. These findings underscore the role of early thinking dispositions and working memory in promoting adolescents’ critical thinking ability.

Cerebral small vessel disease (CSVD), which is a group of pathological processes affecting cerebral microvessels, leads to functional loss in the elderly population and mostly presents as cognitive impairment and gait decline. CSVD is diagnosed based on brain imaging biomarkers, but blood biomarkers are of great significance for the early diagnosis and progression prediction of CSVD and have become a research focus because of their noninvasiveness and easy accessibility. Notably, many blood biomarkers have been reported to be associated with CSVD in a relatively large population, particularly serum neurofilament light chain (NfL), which has been regarded as a promising biomarker to track the variation trend in WMH and to predict the further status of white matter hyperintensities (WMH) and lacunar infarcts. And neuro-glio-vascular unit structure and blood–brain barrier function have been proposed as underlying mechanisms of CSVD. The article starts from the neuroimaging markers of CSVD, including recent small subcortical infarcts (RSSI), white matter hyperintensities (WMH), lacunes, cerebral microbleeds (CMB), enlarged perivascular spaces (EPVS), cerebral atrophy, and the combined small vessel disease score, and attempts to systematically review and summarize the research progress regarding the blood biomarkers of CSVD that form the changes in the neuro-glio-vascular unit structure and blood–brain barrier function.

The cortex is very active during sleep. Wang et al. used macroscopic Ca2+ imaging to record the global cortical activity from the entire dorsal cortex of mice during sleep and uncover an unexpected role of the cortex in controlling REM sleep.

Background China started a national program in 2010 to train qualified general practitioners with compulsory services program (CSP) in rural and remote areas. While the program has shown positive effects on staffing primary healthcare (PHC) in rural areas, very little is known about how well they perform. This study aims to evaluate the job performance of medical graduates from this program and the influence of program design on job performance.Methods A cohort study was conducted with graduates from CSP and non-CSP (NCSP) from four medical universities in central and western China. Baseline and three waves of follow-up surveys were conducted from 2015-2020. The pass rate of China National Medical Licensing Examinations (NMLE) and self-reported job performance were used as measurements. Multivariable regressions were used to identify factors affecting job performance.Results 2154 medical graduates were included, with 1586 CSP and 568 NCSP graduates. CSP (90.6%) and NCSP (87.5%) graduates showed no difference in passing the NMLE (P = .153). CSP graduates reported similar job performance with NCSP graduates (CSP, 63.7; NCSP, 64.2); in the multivariable regression, CSP graduates scored 0.32 and 1.36 points lower in the total sample and graduates of 2015-2017, respectively, but not significantly. Having formally funded positions improved the job performance of CSP (β coefficient = 4.87, P < .05). After controlling for Qinghai which adopted a different contracting strategy, “working in hometown” showed significant influence on job performance (β coefficient = 1.48, P < .05).Conclusion CSP graduates have demonstrated as good job performance as NCSP, proving the competency to provide high-quality care for remote and rural areas. The contracted township health centers (THCs) should provide guidance for CSP graduates, especially in the first few years after graduation. The local government should provide formally funded positions on time and prioritize signing contracts with hometowns or places nearby.

Abstract The rapid rise of monkeypox (MPX) cases outside previously endemic areas prompts for a better understanding of the disease. We studied the plasma proteome of a group of MPX patients with a similar infection history and clinical manifestation typical for the current outbreak. We report that MPX in this case series is associated with a strong plasma proteomic response among nutritional and acute phase response proteins. Moreover, we report a correlation between plasma proteins and disease severity. Contrasting the MPX host response with that of COVID‐19, we find a range of similarities, but also important differences. For instance, CFHR1 is induced in COVID‐19, but suppressed in MPX, reflecting the different roles of the complement system in the two infectious diseases. Of note, the spatial overlap in response proteins suggested that a COVID‐19 biomarker panel assay could be repurposed for MPX. Applying a targeted protein panel assay provided encouraging results and distinguished MPX cases from healthy controls. Hence, our results provide a first proteomic characterization of the MPX human host response and encourage further research on protein‐panel assays in emerging infectious diseases.

PurposeType A behavior pattern (TABP) is a personality type characterized by rapid speech, impatience, competition, and hostility. Asymptomatic cerebral small vessel disease (CSVD) is often endemic in older adults. Individuals with TABP commonly experience suboptimal sleep quality, and a correlation exists between sleep disturbances and CSVD. We investigated the relationship between TABP and CSVD markers and further explored the mediating role of sleep quality in the relationship between TABP and CSVD.MethodsA cross-sectional survey included 764 community-dwelling adults aged 55–85 years. The TABP Scale and the Pittsburgh Sleep Quality Index (PSQI) were used to assess personality and sleep quality, respectively. Linear and logistic regression analyses were used to examine relationships between variables of interest. In addition, mediation analyses with bootstrapping were used to test whether sleep quality mediated the relationship between TABP and CSVD.ResultsOf the 764 participants [median age 65 (61–69) years, 59.9% female], the population with type A personality accounted for 44.8%. After adjusting for covariates, TABP scores (p = 0.03) and PSQI scores (p < 0.001) were significantly correlated with CSVD. In addition, sleep quality partially mediated the association between type A behavior and CSVD, and the mediating effect was 10.67%.ConclusionThis study showed that type A behavior was a risk factor for CSVD among older community-dwelling adults and that sleep quality mediated the relationship between type A behavior and CSVD. Changing type A behavior may help improve sleep quality, which may in turn reduce the prevalence of CSVD.