Search

Abstract Background New-onset atrial fibrillation (NOAF) is a common adverse outcome in acute ST-segment elevation myocardial infarction (STEMI) patients following percutaneous coronary intervention (PCI) and is associated with a worse prognosis. The platelet-to-albumin ratio (PAR) has been utilized to predict the severity and prognosis of cardiovascular diseases. This study aims to investigate the predictive value of PAR combined with the C2HEST score for NOAF in the elderly population with STEMI undergoing PCI. Methods 445 elderly STEMI patients without a history of atrial fibrillation (AF) who underwent PCI were consecutively enrolled in this study. Multivariate logistic regression analysis was used to identify independent risk factors for NOAF after PCI. Results 50 patients (11.2%) developed NOAF after PCI. Multivariate logistic regression analysis revealed that heart rate (HR), systemic immune-inflammation index (SII), uric acid (UA), PAR, and C2HEST score were independent risk factors for NOAF. The area under the curve (AUC) of the combined PAR and C2HEST score was 0.839, and Delong’s test indicated that the combined model had superior predictive value compared to individual markers (AUC of PAR: 0.738; AUC of C2HEST score: 0.752) (P

In recent years, the Industrial Internet and Industry 4.0 came into being. With the development of modern industrial intelligent manufacturing technology, digital twins, Web3 and many other digital entity applications are also proposed. These applications apply architectures such as distributed learning, resource sharing, and arithmetic trading, which make high demands on identity authentication, asset authentication, resource addressing, and service location. Therefore, an efficient, secure, and trustworthy Industrial Internet identity resolution system is needed. However, most of the traditional identity resolution systems follow DNS architecture or tree structure, which has the risk of a single point of failure and DDoS attack. And they cannot guarantee the security and privacy of digital identity, personal assets, and device information. So we consider a decentralized approach for identity management, identity authentication, and asset verification. In this paper, we propose a distributed trusted active identity resolution system based on the inter-planetary file system (IPFS) and non-fungible token (NFT), which can provide distributed identity resolution services. And we have designed the system architecture, identity service process, load balancing strategy and smart contract service. In addition, we use Jmeter to verify the performance of the system, and the results show that the system has good high concurrent performance and robustness.

Abstract Background Airway epithelial cell (AEC) necroptosis contributes to airway allergic inflammation and asthma exacerbation. Targeting the tumor necrosis factor-like ligand 1 A (TL1A)/death receptor 3 (DR3) axis has a therapeutic effect on asthmatic airway inflammation. The role of TL1A in mediating necroptosis of AECs challenged with ovalbumin (OVA) and its contribution to airway inflammation remains unclear. Methods We evaluated the expression of the receptor-interacting serine/threonine-protein kinase 3(RIPK3) and the mixed lineage kinase domain-like protein (MLKL) in human serum and lung, and histologically verified the level of MLKL phosphorylation in lung tissue from asthmatics and OVA-induced mice. Next, using MLKL knockout mice and the RIPK3 inhibitor GSK872, we investigated the effects of TL1A on airway inflammation and airway barrier function through the activation of necroptosis in experimental asthma. Results High expression of necroptosis marker proteins was observed in the serum of asthmatics, and necroptosis was activated in the airway epithelium of both asthmatics and OVA-induced mice. Blocking necroptosis through MLKL knockout or RIPK3 inhibition effectively attenuated parabronchial inflammation, mucus hypersecretion, and airway collagen fiber accumulation, while also suppressing type 2 inflammatory factors secretion. In addition, TL1A/ DR3 was shown to act as a death trigger for necroptosis in the absence of caspases by silencing or overexpressing TL1A in HBE cells. Furthermore, the recombinant TL1A protein was found to induce necroptosis in vivo, and knockout of MLKL partially reversed the pathological changes induced by TL1A. The necroptosis induced by TL1A disrupted the airway barrier function by decreasing the expression of tight junction proteins zonula occludens-1 (ZO-1) and occludin, possibly through the activation of the NF-κB signaling pathway. Conclusions TL1A-induced airway epithelial necroptosis plays a significant role in promoting airway inflammation and barrier dysfunction in asthma. Inhibition of the TL1A-induced necroptosis pathway could be a promising therapeutic strategy.

Abstract Aims/Introduction Diabetic cardiomyopathy (DCM) is a prevalent condition among individuals with diabetes, and is associated with a high mortality rate. The anti‐oxidant properties of Jing Huang or Polygonatum sibiricum polysaccharide (PSP) have been extensively used to treat diabetes‐related disorders; however, its potential effectiveness against DCM remains unknown. This study aimed to investigate PSP's therapeutic effects on DCM in an experimental diabetic mouse model. Materials and Methods To induce insulin resistance, mice were fed a high‐fat diet for 3 months, followed by intraperitoneal streptozotocin injection to induce slight hyperglycemia and develop DCM. Both DCM and control mice were given PSP orally for 3 weeks. Western blotting was used to detect the protein expressions of protein kinase G, C/EBP homologous protein, glucose‐regulated protein 78, phosphodiesterase type 5, protein kinase R‐like endoplasmic reticulum (ER) kinase, and phospho‐protein kinase R‐like endoplasmic reticulum kinase in heart tissue. Results The results showed a reduction in bodyweight and blood glucose levels in the PSP therapy group compared with DCM group. PSP also improved cardiac function and had a negligible effect on malondialdehyde activity. Furthermore, the findings showed that PSP alleviated ER and oxidative stress observed in DCM mice hearts, leading to the inhibition of cyclic guanosine monophosphate‐specific phosphodiesterase type 5 and cardiac cyclic guanosine monophosphate reactivation. Phosphodiesterase type 5 inhibition reduced high‐fat diet‐induced cardiac dysfunction and decreased ER stress. Conclusions PSP could effectively protect diabetic myocardium by inhibiting endoplasmic reticulum stress. These findings provide crucial insights into the potential of PSP to ameliorate DCM conditions in diabetic mice by decreasing ER and oxidative stress, and enhancing cyclic guanosine monophosphate protein kinase G signaling.

Abstract The introduction of single-atom catalysts (SACs) into Fenton-like oxidation promises ultrafast water pollutant elimination, but the limited access to pollutants and oxidant by surface catalytic sites and the intensive oxidant consumption still severely restrict the decontamination performance. While nanoconfinement of SACs allows drastically enhanced decontamination reaction kinetics, the detailed regulatory mechanisms remain elusive. Here, we unveil that, apart from local enrichment of reactants, the catalytic pathway shift is also an important cause for the reactivity enhancement of nanoconfined SACs. The surface electronic structure of cobalt site is altered by confining it within the nanopores of mesostructured silica particles, which triggers a fundamental transition from singlet oxygen to electron transfer pathway for 4-chlorophenol oxidation. The changed pathway and accelerated interfacial mass transfer render the nanoconfined system up to 34.7-fold higher pollutant degradation rate and drastically raised peroxymonosulfate utilization efficiency (from 61.8% to 96.6%) relative to the unconfined control. It also demonstrates superior reactivity for the degradation of other electron-rich phenolic compounds, good environment robustness, and high stability for treating real lake water. Our findings deepen the knowledge of nanoconfined catalysis and may inspire innovations in low-carbon water purification technologies and other heterogeneous catalytic applications.

Abstract Emerging evidence demonstrates that pyroptosis has been implicated in the pathogenesis of asthma. Gasdermin D (GSDMD) is the pyroptosis executioner. The mechanism of GSDMD in asthma remains unclear. The aim of this study was to elucidate the potential role of GSDMD in asthmatic airway inflammation and remodeling. Immunofluorescence staining was conducted on airway epithelial tissues obtained from both asthma patients and healthy controls (HCs) to evaluate the expression level of N-GSDMD. ELISA was used to measure concentrations of cytokines (IL-1β, IL-18, IL-17A, and IL-10) in serum samples collected from asthma patients and healthy individuals. We demonstrated that N-GSDMD, IL-18, and IL-1β were significantly increased in samples with mild asthma compared with those from the controls. Then, wild type and Gsdmd-knockout (Gsdmd −/−) mice were used to establish asthma model. We performed histopathological staining, ELISA, and flow cytometry to explore the function of GSDMD in allergic airway inflammation and tissue remodeling in vivo. We observed that the expression of N-GSDMD, IL-18, and IL-1β was enhanced in OVA-induced asthma mouse model. Gsdmd knockout resulted in attenuated IL-18, and IL-1β production in both bronchoalveolar lavage fluid (BALF) and lung tissue in asthmatic mice. In addition, Gsdmd −/− mice exhibit a significant reduction in airway inflammation and remodeling, which might be associated with reduced Th17 inflammatory response and M2 polarization of macrophages. Further, we found that GSDMD knockout may improve asthmatic airway inflammation and remodeling through regulating macrophage adhesion, migration, and macrophage M2 polarization by targeting Notch signaling pathway. These findings demonstrate that GSDMD deficiency profoundly alleviates allergic inflammation and tissue remodeling. Therefore, GSDMD may serve as a potential therapeutic target against asthma.

Abstract Background Airway epithelium is an important component of airway structure and the initiator of airway remodeling in asthma. The changes of extracellular matrix (ECM), such as collagen deposition and structural disturbance, are typical pathological features of airway remodeling. Thus, identifying key mediators that derived from airway epithelium and capable of modulating ECM may provide valuable insights for targeted therapy of asthma. Methods The datasets from Gene Expression Omnibus database were analyzed to screen differentially expressed genes in airway epithelium of asthma. We collected bronchoscopic biopsies and serum samples from asthmatic and healthy subjects to assess lysyl oxidase like 2 (LOXL2) expression. RNA sequencing and various experiments were performed to determine the influences of LOXL2 knockdown in ovalbumin (OVA)-induced mouse models. The roles and mechanisms of LOXL2 in bronchial epithelial cells were explored using LOXL2 small interfering RNA, overexpression plasmid and AKT inhibitor. Results Both bioinformatics analysis and further experiments revealed that LOXL2 is highly expressed in airway epithelium of asthmatics. In vivo, LOXL2 knockdown significantly inhibited OVA-induced ECM deposition and epithelial-mesenchymal transition (EMT) in mice. In vitro, the transfection experiments on 16HBE cells demonstrated that LOXL2 overexpression increases the expression of N-cadherin and fibronectin and reduces the expression of E-cadherin. Conversely, after silencing LOXL2, the expression of E-cadherin is up-regulated. In addition, the remodeling and EMT process that induced by transforming growth factor-β1 could be enhanced and weakened after LOXL2 overexpression and silencing in 16HBE cells. Combining the RNA sequencing of mouse lung tissues and experiments in vitro, LOXL2 was involved in the regulation of AKT signaling pathway. Moreover, the treatment with AKT inhibitor in vitro partially alleviated the consequences associated with LOXL2 overexpression. Conclusions Taken together, the results demonstrated that epithelial LOXL2 plays a role in asthmatic airway remodeling partly via the AKT signaling pathway and highlighted the potential of LOXL2 as a therapeutic target for airway remodeling in asthma.

BackgroundObservational studies have suggested a link between rheumatic diseases and arrhythmias. However, these studies have been limited by confounding factors and reverse causality, leaving the causal relationship between rheumatic diseases and arrhythmias uncertain. This study addresses this inquiry using genetic evidence.MethodsSelected single nucleotide polymorphisms (SNPs) from genome-wide association study (GWAS) data were employed as instrumental variables. Inverse variance weighting (IVW), MR-Egger regression, and the weighted median method were utilized in the two-sample Mendelian randomization analysis. Horizontal pleiotropy was identified and rectified through the MR-PRESSO test and MR-Egger regression. The stability and reliability of the Mendelian randomization results were appraised using the remain-one method, Cochran Q-test, and funnel plot. Odds ratios (OR) were utilized to assess the causal relationship between six rheumatic diseases and five types of arrhythmias.ResultsThe Inverse Variance Weighted (IVW) method indicated a significant association between rheumatoid arthritis (RA) and an elevated risk of right bundle branch block (RBBB) (OR: 1.10, 95% CI: 1.02–1.18, p = 0.009). Additionally, gout was significantly correlated with an augmented risk of RBBB (OR: 1.28, 95% CI: 1.09–1.51, p = 0.003). Conversely, dermatomyositis (DM) exhibited a negative association with the risk of atrioventricular block (AVB) (OR: 0.94, 95% CI: 0.90–0.99, p = 0.020). No significant associations were observed between other rheumatic diseases and arrhythmias.ConclusionA two-sample Mendelian Randomization (MR) study provides data indicating that in European populations, a genetically predicted gout or rheumatoid arthritis (RA) may increase the incidence of right bundle branch block (RBBB). To clarify and investigate the processes behind these causal links, more research is necessary. Because racial genetic variability exists, care should be used when interpreting our findings.

Leaf area index (LAI) is one of key variables for depicting vegetation structures in land ecosystems. Land surface models necessitate uniform LAI inputs at varying spatial scales to ensure accurate outputs at multiscale levels, however, operational satellite LAI products are acquired only at low spatial resolutions, inhibiting their application at finer spatial scales. Spatial downscaling methods are beneficial for the spatial enhancement of LAI products, and the emergence of deep learning methods has provided promising options for land surface parameter downscaling. However, the potential of deep learning has not been well explored in LAI downscaling. To address this research gap, this study designed an original hierarchical downscaling approach facilitated by generative adversarial network (GAN), transfer learning (TL), and data augmentation techniques to retrieve LAI at fine spatial resolutions, leveraging multiscale satellite images, and cascading from 500-m to 250-m and then to 30-m scales. First, an improved super-resolution GAN (ISRGAN) model was pre-trained using the GLASS LAI and MOD09Q1 products to bridge the general non-linear relationships of LAI between the 500-m and 250-m resolutions. Subsequently, limited reference LAI images were applied to fine-tune this pre-trained ISRGAN model to address the domain shift in the 250-m resolution LAI estimations. Then, the fine-tuned LAI values and the 30-m resolution LAI reference images were utilized as the ISRGAN inputs to produce fine-resolution LAI maps. Finally, the downscaled LAI values derived from the proposed approach were separately validated against reference LAI maps and field measurements across the 250-m and 30-m resolutions. Results show that the fine-tuned transfer learning technique outperforms the pre-trained ISRGAN model and GLASS LAI, with a lower RMSE (0.78) and higher R2 (0.83) at the 250-m resolution. Moreover, the proposed hierarchical downscaling framework achieves better performances for 30-m resolution LAI estimations, regardless of the validation accuracy (R2 = 0.76; RMSE=0.95) and spatiotemporal distributions, than the ISRGAN model which was directly trained by the 500-m and 30-m resolution images. This study highlights that a hierarchical downscaling is valuable for fine-resolution LAI estimations, which leverages multiscale and multisource satellite observations via deep learning.

Abstract Magnetic Resonance Imaging (MRI) is increasingly being used in treatment planning due to its superior soft tissue contrast, which is useful for tumor and soft tissue delineation compared to computed tomography (CT). However, MRI cannot directly provide mass density or relative stopping power (RSP) maps, which are required for calculating proton radiotherapy doses. Therefore, the integration of artificial intelligence (AI) into MRI-based treatment planning to estimate mass density and RSP directly from MRI has generated significant interest. A deep learning (DL) based framework was developed to establish a voxel-wise correlation between MR images and mass density as well as RSP. To facilitate the study, five tissue substitute phantoms were created, representing different tissues such as skin, muscle, adipose tissue, 45% hydroxyapatite (HA), and spongiosa bone. The composition of these phantoms was based on information from ICRP reports. Additionally, two animal tissue phantoms, simulating pig brain and liver, were prepared for DL training purposes. The phantom study involved the development of two DL models. The first model utilized clinical T1 and T2 MRI scans as input, while the second model incorporated zero echo time (ZTE) MRI scans. In the patient application study, two more DL models were trained: one using T1 and T2 MRI scans as input, and another model incorporating synthetic dual-energy computed tomography (sDECT) images to provide accurate bone tissue information. The DECT empirical model was used as a reference to evaluate the proposed models in both phantom and patient application studies. The DECT empirical model was selected as the reference for evaluating the proposed models in both phantom and patient application studies. In the phantom study, the DL model based on T1, and T2 MRI scans demonstrated higher accuracy in estimating mass density and RSP for skin, muscle, adipose tissue, brain, and liver. The mean absolute percentage errors (MAPE) were 0.42%, 0.14%, 0.19%, 0.78%, and 0.26% for mass density, and 0.30%, 0.11%, 0.16%, 0.61%, and 0.23% for RSP, respectively. The DL model incorporating ZTE MRI further improved the accuracy of mass density and RSP estimation for 45% HA and spongiosa bone, with MAPE values of 0.23% and 0.09% for mass density, and 0.19% and 0.07% for RSP, respectively. These results demonstrate the feasibility of using an MRI-only approach combined with DL methods for mass density and RSP estimation in proton therapy treatment planning. By employing this approach, it is possible to obtain the necessary information for proton radiotherapy directly from MRI scans, eliminating the need for additional imaging modalities.

Background/Aims: The occurrence and development of hepatitis B virus-associated acute-on-chronic liver failure (HBV-ACLF) is closely related to the immune pathway. We explored the heterogeneity of peripheral blood T cell subsets and the characteristics of exhausted T lymphocytes, in an attempt to identify potential therapeutic target molecules for immune dysfunction in ACLF patients.Methods: A total of 83,577 T cells from HBV-ACLF patients and healthy controls were screened for heterogeneity by single-cell RNA sequencing. In addition, exhausted T-lymphocyte subsets were screened to analyze their gene expression profiles, and their developmental trajectories were investigated. Subsequently, the expression of exhausted T cells and their capacity in secreting cytokines (interleukin 2, interferon γ, and tumor necrosis factor α) were validated by flow cytometry.Results: A total of eight stable clusters were identified, among which CD4+ TIGIT+ subset and CD8+ LAG-3+ subset, with high expression of exhaust genes, were significantly higher in the HBV-ACLF patients than in normal controls. As shown by pseudotime analysis, T cells experienced a transition from naïve T cells to effector T cells and then exhausted T cells. Flow cytometry confirmed that the CD4+TIGIT+ subset and CD8+LAG-3+ subset in the peripheral blood of the ACLF patients were significantly higher than those in the healthy controls. Moreover, in vitro cultured CD8+LAG-3+ T cells were significantly fewer capable of secreting cytokines than CD8+LAG-3- subset.Conclusions: Peripheral blood T cells are heterogeneous in HBV-ACLF. The exhausted T cells markedly increase during the pathogenesis of ACLF, suggesting that T-cell exhaustion is involved in the immune dysfunction of HBV-ACLF patients.

Determining gallic acid in honey can provide information for assessing the nutritional value and tracing the source of honey. However, the complex matrix of honey and the low content of gallic acid may hamper the detection. Therefore, it is important to select an appropriate sample preparation method. This work established an air-assisted dispersive micro-solid phase extraction combined with a high-performance liquid chromatography method to determine gallic acid in honey. Zinc/nickel/aluminium layered double hydroxides were selected as the adsorbent to extract gallic acids in diluted honey samples. Under air-assisted extraction, the adsorbents adsorbed gallic acid in honey via anion exchange. Subsequently, the isolated adsorbents were dissolved in a 1% phosphoric acid solution. A high-performance liquid chromatography-UV-Vis detector was used for gallic acid detection. Under the optimised conditions, gallic acid showed good linearity over the concentration range of 0.005-10.0 mg.L-1 with a coefficient of determination greater than 0.999. The detection limit and quantification limit were 13.5 and 45 ng.g-1, respectively. The recoveries were 89.8-93.4%, with the intra-day and inter-day relative standard deviations in the range of 0.71-1.17% and 0.76-1.27%, respectively. The method possesses the advantages of simplicity, rapidity, economy and environmental friendliness and is suitable for detecting gallic acid in honey.

Abstract Background Autoimmune responses have been suggested to involvement in patients with Behcet’s syndrome (BS). There has been growing attention towards the roles of cutaneous lymphocyte antigen (CLA)+ regular T cells (Tregs) in autoimmune diseases. The role of CLA+ Tregs in BS is still uncertain. This study aims to clarify the impact of CLA+ Tregs on BS. Methods We collected peripheral blood from a total of 107 patients with BS and 114 healthy controls (HCs). The number of CLA+ Tregs, natural killer (NK) cells, B cells, and several subtypes of CD4+ T cells were detected using flow cytometry and compared between patients and HCs. Results The absolute number and proportion of CLA+ Tregs among CD4+ T lymphocytes and CD4+ Tregs were lower in patients with BS than in HCs. CLA+ Tregs were positively related with NK cells (r = 0.500, P

The self-assembly prodrugs are usually consisted of drug modules, activation modules, and assembly modules. Keeping the balance between efficacy and safety by selecting suitable modules remains a challenge for developing prodrug nanoassemblies. This study designed four docetaxel (DTX) prodrugs using disulfide bonds as activation modules and different lengths of branched-chain fatty alcohols as assembly modules (C16, C18, C20, and C24). The lengths of the assembly modules determined the self-assembly ability of prodrugs and affected the activation modules' sensitivity. The extension of the carbon chains improved the prodrugs’ self-assembly ability and pharmacokinetic behavior while reducing the cytotoxicity and increased cumulative toxicity. The use of C20 can balance efficacy and safety. These results provide a great reference for the rational design of prodrug nanoassemblies.

Abstract Background and Aims Burn and scald injuries are the fourth most common type of trauma. Pediatric burns account for a high proportion of the total number of burn patients and impose a high burden on public health. Understanding the epidemiology of pediatric burns can help improve science education and reduce the incidence of burn injuries. Methods This study is a single‐center retrospective study. One thousand five hundred and twenty‐seven pediatric burn patients admitted to our burn center from January 2016 to December 2020 were included. Demographic and epidemiological data of included patients were extracted and analyzed. The correlations of categorical data were tested by the Chi‐square tests, and differences of continuous data were tested by the Kruskal–Wallis tests. A p‐value of less than 0.05 was considered to be statistically significant. Results The results showed that children under 3 years of age were most susceptible to burn and scald injuries. Burn injuries were most likely to occur in the season of winter and at the place of home. 56.6% of included patients did receive first aid measures, while 1.8% received gold‐standard first aid. Clinical variables related to the severity of injuries were statistically different between patients with and without cooling measures in first aid. Linear regression models showed that emergency treatment of burns in children and adolescents was associated with outcome indicators, including number of operations, total operation duration per total burn surface area (TBSA), cost per TBSA, and length of stay per TBSA. Conclusions This study summarized the epidemiology and outcomes of pediatric burn patients admitted to a burn center in northern China. Adopting cooling measures in first aid can reduce the severity of injuries and reduce the burden on the medical system. Education on burn prevention and first aid measures to caregivers of children, especially preschool children, should be strengthened.

Abstract Single atomic catalysts have shown great potential in efficiently electro‐converting O2 to H2O2 with high selectivity. However, the impact of coordination environment and introduction of extra metallic aggregates on catalytic performance still remains unclear. Herein, first a series of carbon‐based catalysts with embedded coupling Ni single atomic sites and corresponding metallic nanoparticles at adjacent geometry is synthesized. Careful performance evaluation reveals NiSA/NiNP‐NSCNT catalyst with precisely controlled active centers of synergetic adjacent Ni‐N4S single sites and crystalline Ni nanoparticles exhibits a high H2O2 selectivity over 92.7% within a wide potential range (maximum selectivity can reach 98.4%). Theoretical studies uncover that spatially coupling single atomic NiN4S sites with metallic Ni aggregates in close proximity can optimize the adsorption behavior of key intermediates *OOH to achieve a nearly ideal binding strength, which thus affording a kinetically favorable pathway for H2O2 production. This strategy of manipulating the interaction between single atoms and metallic aggregates offers a promising direction to design new high‐performance catalysts for practical H2O2 electrosynthesis.

Exserolides are isocoumarin derivatives containing lactone moiety. Recently, some isocoumarins have been demonstrated to ameliorate hyperlipidemia, a major factor for inducing cardiovascular diseases. However, the effects and mechanisms of action of exserolides on hyperlipidemia are not known. The aim of this study is to investigate whether the marine fungus Setosphaeria sp.-derived exserolides (compounds I, J, E, and F) exert lipid-lowering effects via improving reverse cholesterol transport (RCT) in vitro. RAW264.7 macrophages and HepG2 cells were used to establish lipid-laden models, and the levels of intracellular lipids and RCT-related proteins were determined by assay kits and Western blotting, respectively. We observed that exserolides (at a 5 μM concentration) significantly decreased intracellular cholesterol and triglyceride levels in oxidized low-density lipoprotein-laden RAW264.7 cells and markedly improved [3H]-cholesterol efflux. Among the four tested compounds, exserolide J increased the protein levels of ATP-binding cassette transporter A1, peroxisome proliferator-activated receptor α (PPARα), and liver X receptor α (LXRα). Furthermore, treatment with exserolides significantly decreased oleic acid-laden lipid accumulation in HepG2 hepatocytes. Mechanistically, exserolides enhance PPARα protein levels; furthermore, compound J increases cholesterol 7 alpha-hydroxylase A1 and LXRα protein levels. Molecular docking revealed that exserolides, particularly compound J, can interact with PPARα and LXRα proteins. These data suggest that the terminal carboxyl group of compound J plays a key role in lowering lipid levels by stimulating LXRα and PPARα proteins. In conclusion, compound J exhibits powerful lipid-lowering effects in vitro. However, its hypolipidemic effects in vivo should be investigated in the future.

Protecting ecosystem integrity and maintaining ecosystem service (ES) supply–demand process through ecological connectivity (EC) is crucial for achieving sustainable development of metropolitan area. Currently, EC research focuses more on the combination of protecting the ES supply and maintaining ecosystem integrity, and less on effectively meeting human needs. To bridge this gap, we integrated the theory of ES supply–demand process, connectivity research methods to form a demand-oriented EC research framework, and conducted empirical research on the Wuhan metropolitan area (WHA). Firstly, we evaluated the supply–demand matches status of the key four ESs; And then, from the aspects of flow quantity, flow direction, flow boundary, and allocation principles, the spatial process of ESs flow were decomposed, and the ecological sources that meet demand while supporting the ESs supply–demand process were identified; Finally, based on the comprehensive resistance surface, connected corridors and important strategic points that are crucial for ecological protection were extracted, and an EC network was constructed. The results were the following:(1) the supply and demand of the key ESs in the study area showed a significant spatial mismatch, especially for water conservation (WC) and carbon sequestration (CS); (2)55 ecological sources, 84 ecological corridors and 25 strategic points were identified, and a stable structurally EC network was constructed; (3) The ecological sources were also crucial for ESs supply while meeting human demand and supporting the spatial process of ESs supply–demand. This research is beneficial for deepening the understanding of the supply–demand status of ESs, and providing a support for ecological lands protection planning.

Abstract Type 2 diabetes mellitus (T2DM) is a progressive disease. We utilized bioinformatics analysis and experimental research to identify biomarkers indicative of the progression of T2DM, aiming for early detection of the disease and timely clinical intervention. Integrating Mfuzz analysis with differential expression analysis, we identified 76 genes associated with the progression of T2DM, which were primarily enriched in signaling pathways such as apoptosis, p53 signaling, and necroptosis. Subsequently, using various analytical methods, including machine learning, we further narrowed down the hub genes to STK17A and CCT5. Based on the hub genes, we calculated the risk score for samples and interestingly found that the score correlated with multiple programmed cell death (PCD) pathways. Animal experiments revealed that the diabetes model exhibited higher levels of MDA and LDH, with lower expression of SOD, accompanied by islet cell apoptosis. In conclusion, our study suggests that during the progression of diabetes, STK17A and CCT5 may contribute to the advancement of the disease by regulating oxidative stress, programmed cell death pathways, and critical signaling pathways such as p53 and MAPK, thereby promoting the death of islet cells. This provides substantial evidence in support of further disease prevention and treatment strategies.

The accurate prediction of climate patterns is crucial for effective environmental management and strategic planning, particularly in the face of increasing climate variability and extreme weather events. This study focuses on enhancing the predictive accuracy of global climate models by integrating a random forest algorithm with seasonal bias correction, which is aimed at forecasting changes in precipitation and temperature across various climate scenarios. Our approach significantly improves the precision of climate forecasts by using a comprehensive dataset that includes historical climate data and future projections under Representative Concentration Pathways. For precipitation, after implementing seasonal bias correction, the Correlation Coefficient improved from 0.826 to 0.860, and the Nash–Sutcliffe Efficiency increased from 0.633 to 0.735. In addition, the Mean Absolute Error and Root Mean Square Error decreased, thereby enhancing the model's reliability in predicting extreme precipitation events. Temperature forecasts also benefited from the Random Forest model, achieving a Correlation Coefficient of up to 0.987, indicating a strong predictive performance. These improvements highlight the potential of machine learning methods in refining climate models, thus providing more accurate tools for policymakers and planners to manage climate risks. Furthermore, the successful application of these advanced statistical techniques underscores the importance of continuous innovation in climate science, ensuring that climate projections remain relevant and reliable in informing global climate resilience and adaptation strategies.

Abstract Glial cell-mediated neuroinflammation and neuronal attrition are highly correlated with cognitive impairment in Alzheimer’s disease. YKL-40 is a secreted astrocytic glycoprotein that serves as a diagnostic biomarker of Alzheimer’s disease. High levels of YKL-40 are associated with either advanced Alzheimer’s disease or the normal aging process. However, the functional role of YKL-40 in Alzheimer’s disease development has not been firmly established. In a 5xFAD mouse model of Alzheimer’s disease, we observed increased YKL-40 expression in the cerebrospinal fluid of 7-month-old mice and was correlated with activated astrocytes. In primary astrocytes, Aβ1-42 upregulated YKL-40 in a dose-dependent manner and was correlated with PI3-K signaling pathway activation. Furthermore, primary neurons treated with YKL-40 and/or Aβ1-42 resulted in significant synaptic degeneration, reduced dendritic complexity, and impaired electrical parameters. More importantly, astrocyte-specific knockout of YKL-40 over a period of 7 days in symptomatic 5xFAD mice could effectively reduce amyloid plaque deposition in multiple brain regions. This was also associated with attenuated glial activation, reduced neuronal attrition, and restored memory function. These biological phenotypes could be explained by enhanced uptake of Aβ1-42 peptides, increased rate of Aβ1-42 degradation and acidification of lysosomal compartment in YKL-40 knockout astrocytes. Our results provide new insights into the role of YKL-40 in Alzheimer’s disease pathogenesis and demonstrate the potential of targeting this soluble biomarker to alleviate cognitive defects in symptomatic Alzheimer’s disease patients.

Multitarget insecticides are more likely to achieve comprehensive regulation of insects with a low risk of resistance. Insect chitinolytic enzymes, including GH18 chitinases and GH20 β-N-acetyl-d-hexosaminidase, are attractive targets for multitarget insecticide design by virtue of their similar substrate binding mode and catalytic mechanism. On the other hand, natural products with diverse skeletal structures are potential repositories of chitinolytic enzyme inhibitors. This minireview first presents the theoretical basis of developing multitargeted inhibitors against insect chitinolytic enzymes and then focuses on the progress in developing multitarget inhibitors derived from natural products. These may provide ideas for the exploitation of novel pesticide leads from natural products by targeting multiple targets.

Abstract Background While xanthine oxidase inhibitors target uric acid production, renal urate underexcretion is the predominant subtypes in gout. This study was to compare treatment response to the XOI febuxostat in a gout cohort according to clinical subtypes of hyperuricemia. Methods A prospective cohort study was conducted to compare the efficacy and safety of febuxostat (initially 20 mg daily, escalating to 40 mg daily if not at target) in 644 gout patients with the three major clinical subtypes for 12 weeks. Hyperuricemia was defined as the renal overload subtype, the renal underexcretion subtype, or the combined subtype based on UUE > or ≤ 600 mg/d/1.73 m2 and FEUA

AbstractContext Hawthorn leaves are a kind of widely used medicinal plant in China. The major ingredient, hawthorn leaves flavonoids (HLF), have cardiotonic, cardioprotective, and vascular protective effects.Objective The study evaluated the protective role of HLF in cardiac remodelling and the underlying mechanisms under simulated microgravity by hindlimb unloading rats.Materials and methods Adult male Sprague-Dawley rats were divided into control, HLF, HU (hindlimb unloading) and HU + HLF groups (n = 8). After HU and daily intragastric administration at the dose of 100 mg/kg/d for 8 weeks, cardiac function and structure were evaluated by biochemical indices and histopathology. We identified the main active compounds and mechanisms involved in the cardioprotective effects of HLF via bioinformatics and molecular docking analysis, and relative signalling pathway activity was verified by Western blot.Results HLF treatment could reverse the HU-induced decline in LV-EF (HU, 55.13% ± 0.98% vs. HU + HLF, 71.16% ± 5.08%), LV-FS (HU, 29.44% ± 0.67% vs. HU + HLF, 41.62% ± 4.34%) and LV mass (HU, 667.99 ± 65.69 mg vs. HU + HLF, 840.02 ± 73.00 mg). Furthermore, HLF treatment significantly increased NPRA expression by 135.39%, PKG by 51.27%, decreased PDE5A by 20.03%, NFATc1 by 41.68% and Rcan1.4 by 54.22%.Conclusions HLF plays a protective effect on HU-induced cardiac remodelling by enhancing NPRA-cGMP-PKG pathway and suppressing the calcineurin-NFAT pathway, which provides a theoretical basis for use in clinical therapies.

Background: Transcranial Direct Current Stimulation (tDCS) is a non-invasive brain stimulation technique. Constant electric current is passed through the patient's scalp with the aim of modulating cortical excitability. Stroke is a cerebrovascular disease characterized by hemorrhage or cerebral ischemia. This systematic review and meta-analysis are aimed at comparing the efficacy of motor cortex stimulation with that of cerebellar stimulation by using transcranial direct current stimulation. Method: Google Scholar, PubMed, EMBASE, Cochrane CENTRAL, and Physiotherapy Evidence Database (Pedro) databases were searched for studies. The extracted qualitative data was synthesized systematically. Cochrane RevMan software was used to conduct a meta-analysis of quantitative data. The fixed effects mean difference of the collected data was calculated at a 95% confidence interval (CI) for the changes in balance and side effects. Results: This research included 10 articles with seven studies assessing changes in balance (outcome measured in CoP and FMA scores) and side effects (tingling and itching were the most prevalent). There was no significant difference between the efficacy levels of m1-tDCS versus ctDCS (P = 0.18), m1-tDCS versus sham (P = 0.92), and ctDCS versus sham (P = 0.19). Itching and tingling sensation were the most common and were significantly prevalent in sham interventions (P

Ticks are primary vectors for many tick-borne pathogens (TBPs) and pose a serious threat to veterinary and public health. Information on the presence of TBPs in Chinese Milu deer (Elaphurus davidianus) is limited. In this study, a total of 102 Chinese Milu deer blood samples were examined for Anaplasma spp., Theileria spp., Babesia spp., Rickettsia spp., and Borrelia spp., and three TBPs were identified: Anaplasma phagocytophilum (48; 47.1 %), Candidatus Anaplasma boleense (47; 46.1%), and Theileria capreoli (8; 7.8 %). Genetic and phylogenetic analysis of the 16S rRNA and 18S rRNA confirmed their identity with corresponding TBPs. To our knowledge, this is the first report on Candidatus A. boleense and T. capreoli detection in Chinese Milu deer. A high prevalence of A. phagocytophilum with veterinary and medical significance was identified in endangered Chinese Milu deer, which could act as potential zoonotic reservoirs. The identification of the TBPs in Chinese Milu deer provides useful information for the prevention and control of tick-borne diseases.

Abstract In recent years, ground‐based aerospace tracking, telemetry and control (TT&C) systems have been shifting towards an IP‐based cloud TT&C network architecture to improve signal transmission efficiency and system flexibility. However, this new architecture presents new challenges for the performance of tracking loops in the cloud‐based TT&C receiver. The authors present a predictive compensation tracking loop that addresses the problem of packet loss. The loop utilises radial basis function (RBF) online network identification for robust carrier and code frequency offset tracking. To account for packet loss, the phenomenon is modelled as a Bernoulli random process, and the predictive compensation loop uses the trained RBF network to maintain the system's tracking state. When normal data are received again, the loop can track the received information well and align the frequency offset locking state. The authors compare the performance of the proposed predictive compensation tracking loop with traditional loop tracking performance using data hold strategies under different packet loss rates. The results demonstrate the effectiveness of the proposed approach in maintaining stable tracking and solving in the discontinuous reception of the loop under packet loss environments. The proposed predictive compensation tracking loop offers a practical solution for addressing packet loss, which is a common issue in real‐world applications.

Abstract Chongqing was seriously affected by hand, foot, and mouth disease (HFMD), but the relationships between daily mean temperature and the incidence of HFMD remain unclear. This study used distributed lag nonlinear model to evaluate the effect of daily mean temperature on the incidence of HFMD in children aged

PURPOSETo assess the quantification accuracy of pulmonary nodules using virtual monoenergetic images (VMIs) derived from spectral-detector computed tomography (CT) under an ultra-low-dose scan protocol.METHODSA chest phantom consisting of 12 pulmonary nodules was scanned using spectral-detector CT at 100 kVp/10 mAs, 100 kVp/20 mAs, 120 kVp/10 mAs, and 120 kVp/30 mAs. Each scanning protocol was repeated three times. Each CT scan was reconstructed utilizing filtered back projection, hybrid iterative reconstruction, iterative model reconstruction (IMR), and VMIs of 40–100 keV. The signal-to-noise ratio and air noise of images, absolute differences, and absolute percentage measurement errors (APEs) of the diameter, density, and volume of the four scan protocols and ten reconstruction images were compared.RESULTSWith each fixed reconstruction image, the four scanning protocols exhibited no significant differences in APEs for diameter and density (all P > 0.05). Of the four scan protocols and ten reconstruction images, APEs for nodule volume had no significant differences (all P > 0.05). At 100 kVp/10 mAs, APEs for density using IMR were the lowest (APE-mean: 6.69), but no significant difference was detected between VMIs at 50 keV (APE-mean: 11.69) and IMR (P = 0.666). In the subgroup analysis, at 100 kVp/10 mAs, there were no significant differences between VMIs at 50 keV and IMR in diameter and density (all P > 0.05). The radiation dose at 100 kVp/10 mAs was reduced by 77.8% compared with that at 120 kVp/30 mAs.CONCLUSIONCompared with IMR, reconstruction at 100 kVp/10 mAs and 50 keV provides a more accurate quantification of pulmonary nodules, and the radiation dose is reduced by 77.8% compared with that at 120 kVp/30 mAs, demonstrating great potential for ultra-low-dose spectral-detector CT.

In order to predict the hot workability of the material more accurately, this paper takes the hot deformation of IN617B as the example. The activation energy (Q) map, Zener-Hollomon parameter (Z) map, and hot processing map were established based on the hot compression tests conducted at 950–1200 °C and 0.01–5 s−1. It was found that the area with high power dissipation values (denoted by η) in the hot processing map did not match the complete dynamic recrystallization (DRX) region completely. However, the microstructure corresponding to the high η area and low Z and Q area exhibited higher DRX. Therefore, the optimal hot processing region for this alloy was determined to be 1200 °C/0.1 s−1/0.8. Under this parameter, the DRX mechanism of IN617B alloy was dominated by discontinuous dynamic recrystallization (DDRX), supplemented by small amounts of continuous dynamic recrystallization (CDRX) and twinning dynamic recrystallization (TDRX).

Plantaginis semen is the dried ripe seed of Plantago asiatica L. or Plantago depressa Willd., which has a long history in alleviating hyperuricemia (HUA) and chronic kidney diseases. While the major chemical ingredients and mechanism remained to be illustrated. Therefore, this work aimed to elucidate the chemicals and working mechanisms of PS for HUA. UPLC-QE-Orbitrap-MS was applied to identify the main components of PS in vitro and in vivo. RNA sequencing (RNA-seq) was conducted to explore the gene expression profile, and the genes involved were further confirmed by real-time quantitative PCR (RT-qPCR). A total of 39 components were identified from PS, and 13 of them were detected in the rat serum after treating the rat with PS. The kidney tissue injury and serum uric acid (UA), xanthine oxidase (XOD), and cytokine levels were reversed by PS. Meanwhile, renal urate anion transporter 1 (Urat1) and glucose transporter 9 (Glut9) levels were reversed with PS treatment. RNA-seq analysis showed that the PPAR signaling pathway; glycine, serine, and threonine metabolism signaling pathway; and fatty acid metabolism signaling pathway were significantly modified by PS treatment. Further, the gene expression of Slc7a8, Pck1, Mgll, and Bhmt were significantly elevated, and Fkbp5 was downregulated, consistent with RNA-seq results. The PPAR signaling pathway involved Pparα, Pparγ, Lpl, Plin5, Atgl, and Hsl were elevated by PS treatment. URAT1 and PPARα proteins levels were confirmed by Western blotting. In conclusion, this study elucidates the chemical profile and working mechanisms of PS for prevention and therapy of HUA and provides a promising traditional Chinese medicine agency for HUA prophylaxis.

Thanks to the development of aerospace technology and the rise of concepts such as cloud computing and edge computing, cloud network convergence networks based on giant constellations are expected to become an important part of the integrated construction of star-ground and 6G global communication networks.Unlike terrestrial communication networks, constellation network topology is highly dynamic and time-varying, with strong resource and link heterogeneity, and other characteristics that pose challenges for cloud network convergence.The characteristics of giant constellations and the development status of terrestrial cloud network convergence was summarized, the urgent needs and challenges of cloud network convergence in giant constellations were analyzed, and the innovation of satellite internet cloud network convergence architecture, the use of resource virtualization technology, information sensing and routing path planning based on artificial intelligence algorithms, and cloud computing and edge collaborative computing were potential directions for future satellite-based cloud network convergence technology development direction were further pointed out.

Abstract Introduction Thrombocytopenia, a common noncriteria manifestation of antiphospholipid syndrome (APS), is severe in approximately one‐third of patients with APS. However, there are no guidelines for treating such thrombocytopenia. B‐cell‐targeting therapy may be an option in refractory cases; however, its efficacy has not been firmly established. Here, we report on two patients with refractory antiphospholipid antibodies (aPLs)‐associated thrombocytopenia treated with telitacicept. Case Description Case 1, a 39‐year‐old woman, presented with systemic lupus erythematosus (SLE) and APS with diffuse alveolar hemorrhage, persistent thrombocytopenia, and recurrent miscarriages. The thrombocytopenia had been refractory to multiple lines of treatments, the most recent being mycophenolate mofetil and prednisone (5 mg/day). After receiving telitacicept (160 mg/week) for 3 months, she had presented with decreased titers of aPLs and a slight increase in platelet counts (14 × 109 to 35 × 109/L). Case 2, a 51‐year‐old woman, presented with SLE and APS with refractory thrombocytopenia. She had been diagnosed with pulmonary tuberculosis 4.5 years ago and received antituberculosis therapy for 2 years. She had also undergone pulmonary lobectomy 4 years ago for lung adenocarcinoma. Her thrombocytopenia relapsed (lowest 14 × 109/L) when prednisone was tapered to

Cordycepin has the potential to be an alternative to the disputed herbicide glyphosate. However, current laborious and time-consuming production strategies at low yields based on Cordyceps militaris lead to extremely high cost and restrict its application in the field of agriculture. In this study, Komagataella phaffii (syn. Pichia pastoris) was engineered to biosynthesize cordycepin from methanol, which could be converted from CO2. Combined with fermentation optimization, cordycepin content in broth reached as high as 2.68 ± 0.04 g/L within 168 h, around 15.95 mg/(L·h) in productivity. Additionally, a deaminated product of cordycepin was identified at neutral or weakly alkaline starting pH during fermentation. Transcriptome analysis found the yeast producing cordycepin was experiencing severe inhibition in methanol assimilation and peroxisome biogenesis, responsible for delayed growth and decreased carbon flux to pentose phosphate pathway (PPP) which led to lack of precursor supply. Amino acid interconversion and disruption in RNA metabolism were also due to accumulation of cordycepin. The study provided a unique platform for the manufacture of cordycepin based on the emerging non-conventional yeast and gave practical strategies for further optimization of the microbial cell factory.

Although cytochrome P450 enzymes are the most versatile biocatalysts in nature, there is insufficient comprehension of the molecular mechanism underlying their functional innovation process. Here, by combining ancestral sequence reconstruction, reverse mutation assay, and progressive forward accumulation, we identified 5 founder residues in the catalytic pocket of flavone 6-hydroxylase (F6H) and proposed a “3-point fixation” model to elucidate the functional innovation mechanisms of P450s in nature. According to this design principle of catalytic pocket, we further developed a de novo diffusion model (P450Diffusion) to generate artificial P450s. Ultimately, among the 17 non-natural P450s we generated, 10 designs exhibited significant F6H activity and 6 exhibited a 1.3- to 3.5-fold increase in catalytic capacity compared to the natural CYP706X1. This work not only explores the design principle of catalytic pockets of P450s, but also provides an insight into the artificial design of P450 enzymes with desired functions.

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide, and hyperlipidemia is one major inducing factor of CVD. It is worthy to note that fucoidans are reported to have hypolipidemic activity with species specificity; however, the underlying mechanisms of action are far from clarification. This study is aimed at investigating the plasma lipid-lowering mechanisms of the fucoidan from L. japonica Aresch by detecting the levels of hepatic genes that are involved in lipid metabolism. Our results demonstrated that the fucoidan F3 significantly lowered total cholesterol and triglyceride in C57BL/6J mice fed a high-fat diet. In the mouse liver, fucoidan F3 intervention significantly increased the gene expression of peroxisome proliferator-activated receptor (PPAR) α, liver X receptor (LXR) α and β, and ATP-binding cassette transporter (ABC) G1 and G8 and decreased the expression of proprotein convertase subtilisin/kexin type 9 (PCSK9), low-density lipoprotein receptor, cholesterol 7 alpha-hydroxylase A1, and sterol regulatory element-binding protein (SREBP) 1c and SREBP-2. These results demonstrated that the antihyperlipidemic effects of fucoidan F3 are related to its activation of PPARα and LXR/ABC signaling pathways and inactivation of SREBPs. In conclusion, fucoidan F3 may be explored as a potential compound for prevention or treatment of lipid disorders.

Objectives: To explore the features, treatment, and outcomes of primary urothelial carcinoma of the prostate (PUCP) in a multicenter study. Methods: The clinical and imaging features, pathological findings, treatment, and outcomes of patients diagnosed with PUCP from January 2011 to April 2022 at three institutions were collected and analyzed. The Kaplan–Meier method and log-rank test were used to assess survival rates of the overall group and survival differences between groups according to TNM stage. Results: The study cohort comprised 18 patients with PUCP of mean age 72.4±7.8 years. Dysuria and urinary frequency were the most common symptoms (77.8 %). Sixteen (88.9 %) patients had normal serum total PSA concentrations. Most patients showed abnormalities on urinalysis. MRI was the most accurate diagnostic imaging method (88.9 %). As to immunohistochemistry findings, GATA-3 (81.8 %) and P63 (84.6 %) were positive in most examined patients; however, no lesions were positive for PSA. Three (17.6 %) patients with T1N0M0 and T2N0M0 tumors underwent radical cystectomy. Eleven (64.7 %) patients which almost all had T4 tumors received systematic therapy, most of them receiving chemotherapy with gemcitabine and cisplatin, and radiotherapy. The median overall survival was 42 months, and the median progression-free survival 25 months, the latter being significantly longer in patients with T1–2 than in those with T3–4 disease (p=0.035). Conclusion: PUCP, a rare but highly aggressive type of prostate cancer, should be considered in men with abnormalities on MRI and normal serum PSA concentrations. Positive GATA-3, P63, and negative PSA are typical immunohistochemistry features. Radical cystectomy and systematic therapies can be effective.

Cardiometabolic disorders encompass a broad range of cardiovascular complications associated with metabolic dysfunction. These conditions have an increasing share in the health burden worldwide due to worsening endemic of hypertension, obesity, and diabetes. Previous studies have identified Tumor Protein p53-inducible Nuclear Protein 2 (Trp53inp2) as a molecular link between hyperglycemia and cardiac hypertrophy. However, its role in cardiac pathology has never been determined in vivo. In this study, we generated a cardiac specific knockout model of Trp53inp2 (Trp53inp2-cKO) and investigated the impact of Trp53inp2 inactivation on the pathogenesis of heart failure under mechanic or/and metabolic stresses. Based on echocardiography assessment, inactivation of Trp53inp2 in heart led to accelerated onset of HFrEF in response to pressure-overload, with significantly reduced ejection fraction and elevated heart failure marker genes comparing to the control mice. In contrast, inactivation of Trp53inp2 ameliorated cardiac dysfunction induced by combined stresses of high fat diet and moderate pressure overload (Cardiometabolic Disorder Model). Moreover, Trp53inp2 inactivation led to reduced expression of glucose metabolism genes in lean, pressure-overloaded hearts. However, the same set of genes were significantly induced in the Trp53inp2-cKO hearts under both mechanical and metabolic stresses. In summary, we have demonstrated for the first time that cardiomyocyte Trp53inp2 has diametrically differential roles in the pathogenesis of heart failure and glucose regulation under mechanical vs. mechanical plus metabolic stresses. This insight suggests that Trp53inp2 may exacerbate the cardiac dysfunction during pressure overload injury but have a protective effect in cardiac diastolic function in cardiometabolic disease.

AbstractObjective The purpose of this study was to determine whether a single session of trans-cranial direct current stimulation (tDCS) of the cerebellum and M1 has any advantages over one another or sham stimulation in terms of balance, gait and lower limb function.Methods A total of 66 patients who had experienced their first ever stroke were recruited into three groups for this double-blinded, parallel, randomized, sham-controlled trial: cerebellar stimulation group (CbSG), M1 stimulation group (MSG) and sham stimulation group (SSG). A single session of anodal tDCS with an intensity of 2 mA for a duration of 20 min was administered in addition to gait and balance training based on virtual reality using an Xbox 360 with Kinect. Balance, gait, cognition and risk of fall were assessed using outcome measures before intervention (T0), immediately after intervention (T1) and an hour after intervention (T2).Results Across group analysis of all outcome measures showed statistically non-significant results (p > .05) except for Six Minute Walk Test (p value T0 = .003, p value T1 = .025, p value T2 = .016). The training effect difference showed a significant difference in balance, gait and cognition, as well as cerebral and cerebellar stimulation, in comparison to sham stimulation (p .05).Conclusions In addition to Xbox Kinect-based rehabilitation training, a single session of anodal tDCS to the M1 or cerebellum may be beneficial for improving lower limb function, balance and gait performance.

Background and purposeA novel radiotracer, 18F-fluciclovine (anti-3-18F-FACBC), has been demonstrated to be associated with significantly improved survival when it is used in PET/CT imaging to guide postprostatectomy salvage radiotherapy for prostate cancer. We aimed to investigate the feasibility of using a deep learning method to automatically detect and segment lesions on 18F-fluciclovine PET/CT images.Materials and methodsWe retrospectively identified 84 patients who are enrolled in Arm B of the Emory Molecular Prostate Imaging for Radiotherapy Enhancement (EMPIRE-1) trial. All 84 patients had prostate adenocarcinoma and underwent prostatectomy and 18F-fluciclovine PET/CT imaging with lesions identified and delineated by physicians. Three different neural networks with increasing levels of complexity (U-net, Cascaded U-net, and a cascaded detection segmentation network) were trained and tested on the 84 patients with a fivefold cross-validation strategy and a hold-out test, using manual contours as the ground truth. We also investigated using both PET and CT or using PET only as input to the neural network. Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95), center-of-mass distance (CMD), and volume difference (VD) were used to quantify the quality of segmentation results against ground truth contours provided by physicians.ResultsAll three deep learning methods were able to detect 144/155 lesions and 153/155 lesions successfully when PET+CT and PET only, respectively, served as input. Quantitative results demonstrated that the neural network with the best performance was able to segment lesions with an average DSC of 0.68 ± 0.15 and HD95 of 4 ± 2 mm. The center of mass of the segmented contours deviated from physician contours by approximately 2 mm on average, and the volume difference was less than 1 cc. The novel network proposed by us achieves the best performance compared to current networks. The addition of CT as input to the neural network contributed to more cases of failure (DSC = 0), and among those cases of DSC > 0, it was shown to produce no statistically significant difference with the use of only PET as input for our proposed method.ConclusionQuantitative results demonstrated the feasibility of the deep learning methods in automatically segmenting lesions on 18F-fluciclovine PET/CT images. This indicates the great potential of 18F-fluciclovine PET/CT combined with deep learning for providing a second check in identifying lesions as well as saving time and effort for physicians in contouring.

Abstract Background Chronic stress exposure increases the risk of mental health problems such as anxiety and depression. The medial prefrontal cortex (mPFC) is a hub for controlling stress responses through communicating with multiple limbic structures, including the basolateral amygdala (BLA) and nucleus accumbens (NAc). However, considering the complex topographical organization of the mPFC neurons in different subregions (dmPFC vs. vmPFC) and across multiple layers (Layer II/III vs. Layer V), the exact effects of chronic stress on these distinct mPFC output neurons remain largely unknown. Results We first characterized the topographical organization of mPFC neurons projecting to BLA and NAc. Then, by using a typical mouse model of chronic restraint stress (CRS), we investigated the effects of chronic stress on the synaptic activity and intrinsic properties of the two mPFC neuronal populations. Our results showed that there was limited collateralization of the BLA- and NAc-projecting pyramidal neurons, regardless of the subregion or layer they were situated in. CRS significantly reduced the inhibitory synaptic transmission onto the BLA-projecting neurons in dmPFC layer V without any effect on the excitatory synaptic transmission, thus leading to a shift of the excitation-inhibition (E-I) balance toward excitation. However, CRS did not affect the E-I balance in NAc-projecting neurons in any subregions or layers of mPFC. Moreover, CRS also preferentially increased the intrinsic excitability of the BLA-projecting neurons in dmPFC layer V. By contrast, it even caused a decreasing tendency in the excitability of NAc-projecting neurons in vmPFC layer II/III. Conclusion Our findings indicate that chronic stress exposure preferentially modulates the activity of the mPFC-BLA circuit in a subregion (dmPFC) and laminar (layer V) -dependent manner.

Photocatalysis promises green production of chemicals by using the inexhaustible solar energy, but the low photocatalytic activity of most semiconductors due to charge recombination remains a key barrier to their application. Recently, facet engineering of single semiconductor particles has emerged as an effective strategy to precisely tune the energetic structure, thereby lowering the charge recombination and enhance solar fuel production. Multiple approaches for facet engineering have been developed to construct efficient photocatalysts. In this review, the fundamental principles and the common facet-engineering approaches for improving the photo-charge separation and solar fuel production of semiconductors are summarized, focusing on how the various faceted particles modification strategies tune the inbuilt electric field and reaction kinetics. Additionally, the challenges and future trends in development of facet-engineered photocatalysts were discussed.

BackgroundThe number of patients undergoing proton therapy has increased in recent years. Current treatment planning systems (TPS) calculate dose maps using three-dimensional (3D) maps of relative stopping power (RSP) and mass density. The patient-specific maps of RSP and mass density were obtained by translating the CT number (HU) acquired using single-energy computed tomography (SECT) with appropriate conversions and coefficients. The proton dose calculation uncertainty of this approach is 2.5%-3.5% plus 1 mm margin. SECT is the major clinical modality for proton therapy treatment planning. It would be intriguing to enhance proton dose calculation accuracy using a deep learning (DL) approach centered on SECT.ObjectivesThe purpose of this work is to develop a deep learning method to generate mass density and relative stopping power (RSP) maps based on clinical single-energy CT (SECT) data for proton dose calculation in proton therapy treatment.MethodsArtificial neural networks (ANN), fully convolutional neural networks (FCNN), and residual neural networks (ResNet) were used to learn the correlation between voxel-specific mass density, RSP, and SECT CT number (HU). A stoichiometric calibration method based on SECT data and an empirical model based on dual-energy CT (DECT) images were chosen as reference models to evaluate the performance of deep learning neural networks. SECT images of a CIRS 062M electron density phantom were used as the training dataset for deep learning models. CIRS anthropomorphic M701 and M702 phantoms were used to test the performance of deep learning models.ResultsFor M701, the mean absolute percentage errors (MAPE) of the mass density map by FCNN are 0.39%, 0.92%, 0.68%, 0.92%, and 1.57% on the brain, spinal cord, soft tissue, bone, and lung, respectively, whereas with the SECT stoichiometric method, they are 0.99%, 2.34%, 1.87%, 2.90%, and 12.96%. For RSP maps, the MAPE of FCNN on M701 are 0.85%, 2.32%, 0.75%, 1.22%, and 1.25%, whereas with the SECT reference model, they are 0.95%, 2.61%, 2.08%, 7.74%, and 8.62%. ConclusionThe results show that deep learning neural networks have the potential to generate accurate voxel-specific material property information, which can be used to improve the accuracy of proton dose calculation.Advances in knowledgeDeep learning-based frameworks are proposed to estimate material mass density and RSP from SECT with improved accuracy compared with conventional methods.

In recent years, radar cross section (RCS) reduction techniques based on electromagnetic absorption materials have become a hot research topic in the field of electromagnetic stealth. This paper proposes a transparent conformal encoded metasurface based on polarization rotation units. The metasurface array is optimized using the whale optimization algorithm to construct a 1-bit polarization rotation encoded unit array. The proposed metasurface array exhibits good RCS reduction and electromagnetic wave polarization conversion performance in the frequency range of 13.2–20.7 GHz. The RCS reduction effect of the metasurface array is effective at different angles and polarization states. The metasurface is composed of transparent and flexible materials, namely ITO, PET, and PVC plastic. It exhibits conformal properties while maintaining a high physical transmittance of up to 83.6%. The RCS reduction performance of the metasurface is studied under different curvatures and demonstrates good conformal scattering characteristics. The RCS variation of ITO material compared to traditional metallic materials was also analyzed. It was found that ITO with low surface resistance is an effective means to broaden the RCS bandwidth. This makes it suitable for theoretical research and the design of electromagnetic stealth for electronic devices such as radars and antennas with different curvatures.