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Abstract Renal fibrosis is a common outcome of chronic kidney diseases and glycolysis drives the development of renal fibrosis in damaged kidneys. Ulinastatin (UTI) is a broad-spectrum protease inhibitor with anti-inflammatory and antioxidant properties with anti-fibrosis effects. In this study, we aimed to verify whether UTI could exert anti-renal fibrosis effects by inhibiting glycolysis and explored the potential mechanisms. Renal fibrosis was induced in mice via unilateral ureteral obstruction (UUO). Transforming growth factor-β1 stimulates human kidney proximal tubular epithelial cells to undergo fibrotic changes. Histopathological staining was used to observe the pathological changes in the kidneys. The levels of fibrosis biomarkers, glycolytic enzymes, and key signaling molecules were determined using gene and protein assays. Cellular energy metabolism was measured using Seahorse XF24 analyzer. Modulated the activity of adenylate-activated protein kinase (AMPK) and hypoxia-inducible factor-1α (HIF-1α) to confirm that AMPK can regulate HIF-1α-mediated glycolysis. Furthermore, UTI and AMPK knockdown were combined to verify whether UTI could attenuate glycolysis via the AMPK pathway. UTI pretreatment improved UUO-induced renal injury and fibrosis. The expression of fibrosis biomarkers and glycolytic enzymes was reduced by UTI at both mRNA and protein levels. UTI treatment decreased the rate of glycolysis and the production of glycolytic intermediates in fibrotic cells and tissues. Furthermore, AMPK can regulate HIF-1α-mediated glycolysis in renal tubular epithelial cells. Finally, the attenuation of glycolysis by UTI was related to AMPK/HIF-1α pathway, and this effect was inhibited by knockdown AMPK. UTI can effectively alleviate renal fibrosis, which may be partly attributed to the reduction of glycolysis by regulating AMPK/HIF-1α pathway.

Abstract Hydrogels, characterised as highly hydrophilic three‐dimensional polymer networks, have gained increasing attention due to their unique physicochemical properties, finding applications in various fields. Natural polymer hydrogels exhibit higher biocompatibility and biodegradability compared to traditional synthetic polymer hydrogels. Proteins, being the principal materials of natural polymer hydrogels, bear numerous modifiable functional groups. The resultant hydrogel possesses responsiveness, adjustable degradability, and underway as an excellent biomaterial. Seven common raw materials used to construct protein hydrogels are introduced. In terms of comparing natural polymer hydrogels with traditional synthetic polymer hydrogels, the authors conduct a detailed analysis and comparison, highlighting the advantages of natural polymer hydrogels in terms of biocompatibility and biodegradability, and summarising their characteristics. The authors also address the limitations of various protein hydrogels and list existing strengthening cross‐linking strategies, proposing new insights to overcome the application limits of protein hydrogels. Additionally, the applications of protein hydrogels in drug delivery, biosensing, bio‐inks and tissue engineering are discussed. The authors conclude by summarising the current challenges faced by protein hydrogels and prospecting its future development.

Objective: To conduct a bibliometric analysis of the literature in the field of amino acid radiation protection over the past decade using CiteSpace software, exploring the formation, development, hotspots, and trends in this domain. Methods: The data source is the core collection of the Web of Science database, which include 413 papers on radiation damage of amino acids after deduplication and screening. CiteSpace software is used to visualize these papers, and the keywords and their clusters in this field are summarized from multiple dimensions and perspectives. Results: According to these papers, this field is dynamic and continuously growing, attracting interest from many scholars. Regarding country/institution distribution, China, the United States, and India have higher publication volumes, while the UK and India have more vital centrality in their publications. Keyword analysis reveals that the research hotspots in this field include ultraviolet radiation, oxidative stress, mycotoxin amino acids, and antioxidant activity. In contrast, emerging keywords such as DNA damage, photoprotection, and porphyrin-334 show research potential. Cluster analysis find that ultraviolet radiation protection, mycotoxin amino acids, glutamate, and adjuvant radiotherapy are the main research directions in this field. According to ionizing and non-ionizing radiation classification, the representative papers of the past decade sorted out the amino acids and their derivatives related to radiation protection. Conclusion: The visualization of the current situation, hotspots, and trends in the field of amino acid radiation protection provides valuable guidance and prospects for the development of amino acid food and the research of radiation protection in the future. Since the nuclear leakage accidents caused widespread concern, the demand for natural and harmless radiation protection products has surged, especially the development potential of amino acid radiation protection food. However, the current research on the structure-activity or mechanism of amino acid radiation protection needs to be more in-depth. It is still necessary to strengthen multi-agency cooperation and multi-center communication and focus on research hotspot keywords to help the development of amino acid radiation protection foods. In the context of the continuous spread of nuclear sewage, food technology is used as a shield to safeguard people's health.

The pitting mechanism of 7 series high-strength aluminum (Al) alloys (7xxx) is investigated experimentally and numerically (finite element method, FEM) by comparing the characteristics of passive films and pitting kinetics of two types of 7xxx Al alloys. The point defect model (PDM) is used to evaluate the passive film properties in the two varieties of 7xxx Al alloy, and the FEM is employed to calculate the point defect diffusion process in detail. The results reveal that the two 7xxx Al alloys exhibit various microstructures, particularly the 7xxx-1, characterized by a robust (111) fiber texture and a lower proportion of low-angle grain boundaries than the 7xxx-2. The diffusivity D of point defects in 7xxx-1 (3.85 × 10−18–52.74 × 10−18 cm2 s−1) is lower than that in 7xxx-2 (5.47 × 10−18–66.61 × 10−18 cm2 s−1) and the diffusion duration of 7xxx-1 is longer than 7xxx-2, which is closely associated with the rupture of passive film. Additionally, FEM proved that the initial shapes of pits dictate the progression of pitting, manifesting that the shallow dish shape grows laterally while the deep hole shape grows longitudinally.

Lung cancer is the main cause of cancer-related deaths, with non-small cell lung cancer (NSCLC) being the predominant subtype. At present, immunotherapy represented by immune checkpoint inhibitors (ICIs) of programmed cell death receptor 1 or its ligand has been widely used in the clinical diagnosis and treatment of patients with NSCLC. However, only a few patients can benefit from it, and reliable predictive markers for immunotherapy are lacking. Radiomics is a tool that uses computer software and algorithms to extract a large amount of quantitative information from biomedical images. A large number of studies have confirmed that the radiomic model that predicts the immune efficacy of NSCLC can be used as a new type of immune efficacy predictive marker, which is expected to guide the individualized diagnosis and treatment decisions for patients with lung cancer and has a bright application prospect. This article reviews the research progress of radiomics in predicting the immune therapy response of NSCLC, identifying pseudo-progression and hyperprogression, ICIs-related pneumonia, cachexia risk, and combining with other genomics.

Abstract Background This study aimed to explore the demographic characteristics, diagnostic challenges, treatment patterns, and caregiver burden of mitochondrial diseases. Methods This retrospective cross-sectional study enrolled patients diagnosed with mitochondrial diseases from the Department of Neurology at Peking University First Hospital between January 2010 and December 2021. A questionnaire covering demographic characteristics, diagnostic dilemma, treatment, economic aspects, and caregiver stress was administered, and disability was assessed using the modified Rankin Scale (mRS). Results A total of 183 patients (mean age: 16 (IQR: 12–25), 49.72% males) were enrolled, including 124 pediatric patients and 59 adult patients. MELAS (106. 57.92%) and Leigh syndrome (37, 20.22%) were predominant among the mitochondrial disease subtypes. Among them, 132 (72.13%) patients were initially misdiagnosed with other diseases, 58 (31.69%) patients visited 2 hospitals before confirmed as mitochondrial disease, and 39 (21.31%) patients visited 3 hospitals before confirmed as mitochondrial disease. Metabolic modifiers were the most common type of drugs used, including several dietary supplements such as L-carnitine (117, 63.93%), Coenzyme Q10 (102, 55.74%), idebenone (82, 44.81%), and vitamins (99, 54.10%) for proper mitochondrial function. Mothers are the primary caregivers for both children (36.29%) and adults (38.98%). The mRS score ranged from 0 to 5, 92.35% of the patients had different degrees of disability due to mitochondrial disease. The average monthly treatment cost was 3000 RMB for children and 3100 RMB for adults. Conclusions This study provided valuable insights into the characteristics and challenges of mitochondrial diseases, which underscores the need for improved awareness, diagnostic efficiency, and comprehensive support for patients and caregivers.

Abstract Resistance to chemotherapy has been a major hurdle that limits therapeutic benefits for many types of cancer. Here we systematically identify genetic drivers underlying chemoresistance by performing 30 genome-scale CRISPR knockout screens for seven chemotherapeutic agents in multiple cancer cells. Chemoresistance genes vary between conditions primarily due to distinct genetic background and mechanism of action of drugs, manifesting heterogeneous and multiplexed routes towards chemoresistance. By focusing on oxaliplatin and irinotecan resistance in colorectal cancer, we unravel that evolutionarily distinct chemoresistance can share consensus vulnerabilities identified by 26 second-round CRISPR screens with druggable gene library. We further pinpoint PLK4 as a therapeutic target to overcome oxaliplatin resistance in various models via genetic ablation or pharmacological inhibition, highlighting a single-agent strategy to antagonize evolutionarily distinct chemoresistance. Our study not only provides resources and insights into the molecular basis of chemoresistance, but also proposes potential biomarkers and therapeutic strategies against such resistance.

Abstract The high redox potential of Zn0/2+ leads to low voltage of Zn batteries and therefore low energy density, plaguing deployment of Zn batteries in many energy-demanding applications. Though employing high-voltage cathode like spinel LiNi0.5Mn1.5O4 can increase the voltages of Zn batteries, Zn2+ ions will be immobilized in LiNi0.5Mn1.5O4 once intercalated, resulting in irreversibility. Here, we design a polymer hetero-electrolyte consisting of an anode layer with Zn2+ ions as charge carriers and a cathode layer that blocks the Zn2+ ion shuttle, which allows separated Zn and Li reversibility. As such, the Zn‖LNMO cell exhibits up to 2.4 V discharge voltage and 450 stable cycles with high reversible capacity, which are also attained in a scale-up pouch cell. The pouch cell shows a low self-discharge after resting for 28 days. The designed electrolyte paves the way to develop high-voltage Zn batteries based on reversible lithiated cathodes.

Structural lithium batteries integrated with energy storage and mechanical load‐bearing capabilities hold great promise to revolutionize lightweight transport vehicles. However, the current development of structural batteries faces critical challenges in balancing the electrochemical and mechanical properties of the electrolytes. Herein, a super strong quasi‐solid composite polymer electrolyte (QCPE) is successfully fabricated by reinforcing polyelectrolyte with 3D in situ self‐assembled metal–organic framework‐modified glass fiber (MOF@GF) soaking a small amount of liquid electrolyte, which provides continuous ion conductive pathways for fast Li+ transport and contributes to the high ambient ionic conductivity of 1.47 × 10−3 S cm−1. The micropores and abundant polar functional groups selectively restrict the transport of anions to afford a homogeneous Li+ flux and a high Li+ transference number (0.56). Simultaneously, the MOF@GF provides more effective reinforcement and a remarkably high tensile strength of 48.6 MPa, and Young's modulus of 1.66 GPa is achieved. Furthermore, the lithium metal batteries fabricated with this QCPE exhibit a long, stable operation lifespan of 2000 h and excellent cycling performance with LiFePO4 and NCM811 cathodes. This design strategy generally opens a new avenue for structural batteries with high ionic conductivity and outstanding mechanical properties, which holds great promise for industrial translation.

BackgroundImmunoglobulin A nephropathy (IgAN) is the most prevalent form of chronic kidney disease (CKD), marked by diverse pathological patterns and variable prognostic outcomes. Nutritional indexes are crucial for disease assessment and prognosis prediction. This study investigates associations between nutritional indexes and renal function in patients with IgAN.MethodsA cohort of 736 adults diagnosed with IgAN, who underwent renal biopsy at the First Hospital of Jilin University between January 2010 and October 2022, was examined. Clinical and laboratory data were reviewed, and four nutritional indexes were calculated: controlling nutritional status (CONUT) score, geriatric nutritional risk index (GNRI), body mass index (BMI), and prognostic nutritional index (PNI). Cox-proportional hazard analysis evaluated factors associated with end-stage renal disease (ESRD).ResultsPatients with ESRD showed significantly lower GNRI (91.84 vs. 98.94, p

Various human assistance robots that effectively assist the daily activities of persons with perception deficits have recently been developed. In this paper, a perception assist method with an upper limb power assist exoskeleton robot is proposed for meal activities, which are important in daily living. The proposed robot-based method assists users by appropriately assessing utensil trajectories and posture performance according to the target position of the user. A method to predict the user’s target position based on the user’s motion trajectories and shoulder muscle electromyographic (EMG) signals is also proposed. Two kinds of virtual tunnels (for the utensil trajectory and utensil posture) corresponding to the user’s target position are defined in the proposed method to monitor the accuracy of the executed motion. The spatial relationship between the virtual tunnels is controlled to perform the eating task with the assistance of the power assist robot. The user’s hand motion is automatically modified by the robot in real time if the utensil trajectory and/or posture exits the respective virtual tunnel during meal activities. The effectiveness of the proposed method is evaluated through experiments.

Abstract Functional lipids, primarily derived through the modification of natural lipids by various processes, are widely acknowledged for their potential to impart health benefits. In contrast to chemical methods for lipid modification, enzymatic catalysis offers distinct advantages, including high selectivity, mild operating conditions, and reduced byproduct formation. Nevertheless, enzymes face challenges in industrial applications, such as low activity, stability, and undesired selectivity. To address these challenges, protein engineering techniques have been implemented to enhance enzyme performance in functional lipid synthesis. This article aims to review recent advances in protein engineering, encompassing approaches from directed evolution to rational design, with the goal of improving the properties of lipid-modifying enzymes. Furthermore, the article explores the future prospects and challenges associated with enzyme-catalyzed functional lipid synthesis.

Abstract Curved displays can adjust their shape to accommodate different objects and are used in electronics and decorative lighting. Due to the immutable pixel spacing, existing commercial curved displays are flexible but not compatible with undevelopable surfaces. Inspired by kirigami and auxetic structures, we propose an approach that combines luminescent elements and rotating square tessellations to create a stretchable, arbitrary curve adaptive display. We connect square islands by vertical interconnects to relieve the stress concentration and provide extra deformation patterns. The vertical interconnects are patterned on a flexible printed circuit board (FPCB) using laser cutting and folded up via specially designed molds. Further, the freed-up space by folded interconnects allows the structure to be compressed. A prototype stretchable display is demonstrated that it can maintain electrical performance under biaxial strain and adapt to different Gaussian curvature surfaces, including cylindrical, spherical, saddle and arbitrary surfaces. Theoretical models and finite element calculations are established to describe the tensile behavior of the structures under different boundary conditions and agree with the experimental results. This proposed technology paves a feasible solution of mass production of adaptive curved displays and sets the trend for the next-generation display.

Abstract Most current research is devoted to electrochemical nitrate reduction reaction for ammonia synthesis under alkaline/neutral media while the investigation of nitrate reduction under acidic conditions is rarely reported. In this work, we demonstrate the potential of TiO2 nanosheet with intrinsically poor hydrogen-evolution activity for selective and rapid nitrate reduction to ammonia under acidic conditions. Hybridized with iron phthalocyanine, the resulting catalyst displays remarkably improved efficiency toward ammonia formation owing to the enhanced nitrate adsorption, suppressed hydrogen evolution and lowered energy barrier for the rate-determining step. Then, an alkaline-acid hybrid Zn-nitrate battery was developed with high open-circuit voltage of 1.99 V and power density of 91.4 mW cm–2. Further, the environmental sulfur recovery can be powered by above hybrid battery and the hydrazine-nitrate fuel cell can be developed for simultaneously hydrazine/nitrate conversion and electricity generation. This work demonstrates the attractive potential of acidic nitrate reduction for ammonia electrosynthesis and broadens the field of energy conversion.

Intercropping systems and exogenous microorganism additives are recognized for their potential to influence silage fermentation and quality. This study aims to evaluate the impacts of maize–lablab bean intercropping and lactic acid bacteria (LAB) additives on silage yield, nutritional quality, and economic profitability. A randomized block design was employed with two cropping patterns—maize monocrop (M) and maize–lablab intercrop (ML)—and five additive treatments: No additives (CK), and varying ratios of Lactobacillus Plantarum (LP) and Lactobacillus Buchneri (LB), T1 (100% LP), T2 (9LP:LB), T3 (8LP:2LB), and T4 (100% LB). The silage was analyzed and evaluated for its nutritional quality, fermentation quality, and fermentation effect after 90 days of fermentation. ML intercropping significantly enhanced the fresh matter yields by 8.59% and crude protein content by 8.73% compared to M. From the point of view of inoculation with different lactobacilli, the pH, AA, and NH3-N/TN were lower in the T2 and T3 treatments than in the other treatments, while LA was significantly higher. The V-score, which reflects the overall fermentation quality, was excellent across all treatments, with scores exceeding 80 points; the T2 treatment in ML silage achieved the highest score of 99.58. In addition, intercropping can increase the net income of farmers by 21.67%. In conclusion, maize–lablab intercropping combined with LAB inoculation, particularly with the T2 and T3 treatments, significantly enhances the silage quality and economic returns by reducing pH, increasing the LA content, and improving the CP levels. This study is the first to comprehensively analyze the synergistic effects of altering cropping systems and adding functional microorganisms on forage yield and fermentation quality, offering strategic insights for farms, especially mixed farms, to produce high-quality feed. We recommend adopting these methods to improve feed quality and maximize the profitability of silage production systems.

BackgroundThe morbidity and mortality of chronic kidney disease (CKD) are increasing worldwide, making it a serious public health problem. Although a potential correlation between body water content and CKD progression has been suggested, the presence of a causal association remains uncertain. This study aimed to determine the causal effect of body water content on kidney function.MethodsGenome-wide association study summary data sourced from UK Biobank were used to evaluate single-nucleotide polymorphisms (SNPs) associated with whole-body water mass (BWM). The summary statistics pertaining to kidney function were extracted from the CKDGen consortium. The primary kidney function outcome measures included estimated glomerular filtration rate (eGFR), albuminuria, CKD stages 3–5, and rapid progression to CKD (CKDi25). Two-sample Mendelian randomization (MR) analysis estimated a potential causal relationship between the BWM and kidney function. The inverse variance weighted MR method was used as the primary analysis, accompanied by several sensitive MR analyses.ResultsThe increase of BWM exhibited a correlation with a reduction in eGFR (β = −0.02; P = 6.95 × 10−16). Excluding 13 SNPs responsible for pleiotropy (P = 0.05), the increase of BWM was also associated with the decrease of the ratio of urinary albumin to creatinine (β = −0.16; P = 5.91 × 10−36). For each standard deviation increase in BWM, the risk of CKD stages 3–5 increases by 32% (OR, 1.32; 95% CI, 1.19–1.47; P = 1.43 × 10−7), and the risk of CKDi25 increases by 22% (OR, 1.22; 95% CI, 1.07–1.38; P = 0.002).ConclusionThe increase of BWM is associated with impaired kidney function. Proactively managing body water content is of great significance in preventing the progression of CKD.

Abstract One of the main challenges in small molecule drug discovery is finding novel chemical compounds with desirable activity. Traditional drug development typically begins with target selection, but the correlation between targets and disease remains to be further investigated, and drugs designed based on targets may not always have the desired drug efficacy. The emergence of machine learning provides a powerful tool to overcome the challenge. Herein, a machine learning‐based strategy is developed for de novo generation of novel compounds with drug efficacy termed DTLS (Deep Transfer Learning‐based Strategy) by using dataset of disease‐direct‐related activity as input. DTLS is applied in two kinds of disease: colorectal cancer (CRC) and Alzheimer's disease (AD). In each case, novel compound is discovered and identified in in vitro and in vivo disease models. Their mechanism of actionis further explored. The experimental results reveal that DTLS can not only realize the generation and identification of novel compounds with drug efficacy but also has the advantage of identifying compounds by focusing on protein targets to facilitate the mechanism study. This work highlights the significant impact of machine learning on the design of novel compounds with drug efficacy, which provides a powerful new approach to drug discovery.

Abstract Thermoelectric devices (TEDs) show great potential for waste heat energy recycling and sensing. However, existing TEDs cannot be self‐adapted to the complex quadratic surface, leading to significant heat loss and restricting their working scenario. Here, surface‐conformable origami‐TEDs (o‐TEGs) are developed through programmable crease‐designed origami substrates and the screen‐printing TE legs. Compared with “π” structured TEDs, the origami design (with heat conductive materials) changed the heat‐transferring direction of the laminated TE legs, resulting in an enhancement in enlarging ΔT/THot and Vout by 5.02 and 3.51 times. Four o‐TEDs with different creases designs are fabricated to verify the heat recycling ability on plane and central quadratic surfaces. Demonstrating a high Vout density (up to 0.98 −2at ΔT of 50 K) and good surface conformability, o‐TEDs are further used in thermal touch panels attached to multiple surfaces, allowing information to be wirelessly transferred on a remote display via finger‐writing.

BackgroundOwing to individual heterogeneity, patients with idiopathic membranous nephropathy (IMN) exhibit varying sensitivities to immunotherapy. This study aimed to establish and validate a model incorporating pathological and clinical features using deep learning training to evaluate the response of patients with IMN to immunosuppressive therapy.MethodsThe 291 patients were randomly categorized into training (n = 219) and validation (n = 72) cohorts. Patch-level convolutional neural network training in a weakly supervised manner was utilized to analyze whole-slide histopathological features. We developed a machine-learning model to assess the predictive value of pathological signatures compared to clinical factors. The performance levels of the models were evaluated using the area under the receiver operating characteristic curve (AUC) on the training and validation tests, and the prediction accuracies of the models for immunotherapy response were compared.ResultsMultivariate analysis indicated that diabetes and smoking were independent risk factors affecting the response to immunotherapy in IMN patients. The model integrating pathologic features had a favorable predictive value for determining the response to immunotherapy in IMN patients, with AUCs of 0.85 and 0.77 when employed in the training and test cohorts, respectively. However, when incorporating clinical features into the model, the predictive efficacy diminishes, as evidenced by lower AUC values of 0.75 and 0.62 on the training and testing cohorts, respectively.ConclusionsThe model incorporating pathological signatures demonstrated a superior predictive ability for determining the response to immunosuppressive therapy in IMN patients compared to the integration of clinical factors.

Weak fault detection is still a hotspot in these years. The key of this work is to enhance the ratio of signal to noise (SNR). Then a new extraction method of weak fault impact based on amplification algorithm is proposed. Since the fault impact is related to bigger derivative, the amplification function combined with the derivative of the vibration signal is used to amplify the amplitude of the impact. Then Sparse Spike Deconvolution (SSD) which has been widely used in earthquake for impact detection is able to extract small impact from the signal processed by amplification function. Then, in order to enhance the periodicity of fault impacts, the compression function is used to compress the amplitude of bigger impacts according to different scales. At last, the experiment result shows that the proposed method is more effective than the common envelope analysis.

Abstract Bionic multifunctional structural materials that are lightweight, strong, and perceptible have shown great promise in sports, medicine, and aerospace applications. However, smart monitoring devices with integrated mechanical protection and piezoelectric induction are limited. Herein, we report a strategy to grow the recyclable and healable piezoelectric Rochelle salt crystals in 3D-printed cuttlebone-inspired structures to form a new composite for reinforcement smart monitoring devices. In addition to its remarkable mechanical and piezoelectric performance, the growth mechanisms, the recyclability, the sensitivity, and repairability of the 3D-printed Rochelle salt cuttlebone composite were studied. Furthermore, the versatility of composite has been explored and applied as smart sensor armor for football players and fall alarm knee pads, focusing on incorporated mechanical reinforcement and electrical self-sensing capabilities with data collection of the magnitude and distribution of impact forces, which offers new ideas for the design of next-generation smart monitoring electronics in sports, military, aerospace, and biomedical engineering.

Scutellaria baicalensis Georgi (SB), a plant of the Lamiaceae family, contains flavonoids with potent human health benefits. The full mechanistic details and regulatory networks related to the biosynthesis of these compounds in SB have been the focus of recent research but are still fragmented. Similarly, a complete account of the metabolites produced, specifically flavonoids, and their distribution in different parts of the plant is incomplete. To provide a more complete picture, herein we have explored the SB metabolites and differentially expressed genes in underground and aerial tissues. Of the 947 metabolites identified, 373 were differentially accumulated flavonoids (DAFs), and 147 of these were differentially accumulated in roots relative to other tissues. Interestingly, roots accumulated more baicalin and baicalein than aboveground tissues, but they were low in scutellarein and wogonoside, in contrast to previous reports. These differences may be attributed to either plant variety, age of the plants, or the extraction protocol. Transcriptomics analysis identified 56 key genes from the flavonoid synthesis pathway in all six SB plant tissues. A weighted gene correlation network analysis conducted using four DAFs (baicalin, baicalein, scutellarein and wogonoside) produced 13 modules. Baicalin and baicalein were positively correlated with one of these modules, whereas wogonoside and scutellarein were correlated with three other modules. Gene expression in these modules was consistent with the observed accumulation of these compounds in plant tissues. Fourteen structural genes were highly correlated with baicalin, baicalein and scutellarein, and 241 transcription factors (TFs) associated to these four compounds. The 13 highly correlated structural genes and 21 highly correlated TFs were used to construct correlation networks, where genes were identified to be highly correlated with flavonoid biosynthesis genes. Overexpression of some of these genes, namely, SbMYB8 (Sb02g25620), SbMYB14 (Sb09g00160) and SbbHLH94 (Sb07g11990), in SB callus increased flavonoid content and regulated the expression of genes involved in the flavonoid biosynthesis pathway, confirming their association to flavonoid production. Overall, the present work contributes to delineating the differences in flavonoid biosynthesis among different SB tissues.

Abstract Background Physical activity (PA) is generally encouraged for the treatment of osteoporosis. However, epidemiological statistics on the level of physical activity required for bone health are scarce. The purpose of this research was to analyze the association between PA and total spine bone mineral density (BMD) in postmenopausal women. Methods The research study included postmenopausal women aged ≥ 50 from the National Health and Nutrition Examination Survey. The metabolic equivalent (MET), weekly frequency, and duration of each activity were used to calculate PA. Furthermore, the correlations between BMD and PA were investigated by multivariable weighted logistic regression. Results Eventually, 1681 postmenopausal women were included, with a weighted mean age of 62.27 ± 8.18 years. This study found that performing ≥ 38MET-h/wk was linked to a lower risk of osteoporosis after controlling for several covariates. Furthermore, the subgroup analysis revealed that the connection between total spine BMD and moderate-to-vigorous PA was more obvious among postmenopausal women aged

Background Dysregulation of several inflammatory cytokines including tumour necrosis factor (TNF) in dementia patients has also been identified as a key factor in the pathogenesis of rheumatoid arthritis (RA). We aimed to investigate the association of disease-modifying antirheumatic drugs (DMARDs) therapy for RA with risk of incident dementia.Methods Electronic database searches of PubMed, EMBASE and Cochrane Library were performed. Observational studies that assessed the association of dementia with DMARDs in RA were included. Pooled risk ratios (RRs) with 95% CIs were used as summary statistic. The certainty of evidence was judged by using the Grading of Recommendations Assessment, Development and Evaluation system.Results Overall, 14 studies involving 940 442 patients with RA were included. Pooled RR for developing dementia was 0.76 (95% CI 0.72 to 0.80) in patients taking biological DMARDs overall versus those taking conventional synthetic DMARDs, with 24% for TNF inhibitors (RR 0.76, 95% CI 0.71 to 0.82), 24% for non-TNF biologics (RR 0.76, 95% CI 0.70 to 0.83), separately. There was a significant subgroup effect among different types of TNF inhibitors (RR 0.58 [95%CI 0.53 to 0.65], 0.65 [95% CI 0.59 to 0.72], 0.80 [95% CI 0.72 to 0.88] for etanercept, adalimumab, infliximab, respectively; p value between groups=0.002). However, compared with non-users of DMARDs or investigative treatment, no significant effect on dementia incidence was observed in those receiving conventional synthetic DMARDs overall (RR 0.84, 95% CI 0.59 to 1.20), methotrexate (RR 0.78, 95% CI 0.54 to 1.12), hydroxychloroquine (RR 0.95, 95% CI 0.63 to 1.44), except for sulfasalazine (RR 1.27, 95% CI 1.06 to 1.50).Conclusions Biological DMARDs for RA are associated with decreased dementia risk, while protective effect is not observed in conventional synthetic DMARDs. Controlled clinical trials on TNF inhibitors are necessary to test their neuroprotective potentials.

The road is one of the most important civil infrastructures for serving society, where its service quality and life have direct impacts on the safety and comfort of users. Therefore, road construction, condition detection and monitoring, and timely maintenance are particularly important for engineers. Many engineering applications of industrial informatics approaches, like image processing technology, widely used computer-based algorithms, and advanced sensors, have been initially and gradually applied to roads. This state-of-the-art review first summarized the research on industrial applications of advanced information technologies in recent years, while analyzing and comparing the advantages and disadvantages of each technology. Especially, five topics were focused on road construction, road maintenance with decision strategy, road structure evaluation, smart sensing in the road, and cooperative vehicle infrastructure system. It is expected that advanced industrial informatics can help engineers promote the development of smart, safe, and sustainable roads.

Abstract Global agricultural trade creates multiple telecoupled flows of nitrogen (N) and phosphorus (P). The flows of physical and virtual nutrients along with trade have discrepant effects on natural resources in different countries. However, existing literature has not quantified or analyzed such effects yet. Here we quantified the physical and virtual N and P flows embedded in the global agricultural trade networks from 1997 to 2016 and elaborated components of the telecoupling framework. The N and P flows both increased continuously and more than 25% of global consumption of nutrients in agricultural products were related to physical nutrient flows, while virtual nutrient flows were equivalent to one-third of the nutrients inputs into global agricultural system. These flows have positive telecoupling effects on saving N and P resources at the global scale. Reducing inefficient trade flows will enhance resource conservation, environmental sustainability in the hyper-globalized world.

Sand liquefaction under static and dynamic loading can cause failure of embankments, slopes, bridges and other important infrastructure. Sand liquefaction in the seabed can also cause submarine landslides and tsunamis. Fabric anisotropy related to the internal soil structure such as particle orientation, force network and void space is found to have profound influence on sand liquefaction. A constitutive model accounting for the effect of anisotropy on sand liquefaction is proposed. Evolution of fabric anisotropy during loading is considered according to the anisotropic critical state theory for sand. The model has been validated by extensive test results on Toyoura sand with different initial densities and stress states. The effect of sample preparation method on sand liquefaction is qualitatively analysed. The model has been used to investigate the response of a sand ground under earthquake loading. It is shown that sand with horizontal bedding plane has the highest resistance to liquefaction when the sand deposit is anisotropic, which is consistent with the centrifuge test results. The initial degree of fabric anisotropy has a more significant influence on the liquefaction resistance. Sand with more anisotropic fabric that can be caused by previous loading history or compaction methods has lower liquefaction resistance.

The structure and properties of potato starch were investigated after superfine grinding with a fluidized bed jet mill. The particle size, granular morphology, functional groups, rheological property, thermal and physicochemical properties of the potato starch were characterized using laser particle size analyzer (LPA), scanning electron microscopy (SEM), X-ray photoelectron spectrometer (XPS), simultaneous thermal analyzer and rheometer. It was found that the particle size of potato starch was significantly decreased to 13.59±0.04 μm after superfine grinding. There was no new element peak in the spectrum of X-ray photoelectron spectroscopy (XPS), no new elements were introduced on the surface of starch granules. The amylose content increased, the molecular chain of amylopectin shortened, and the solubility, swelling degree and transparency of starch paste increased. The viscosity resistance decreases, and the apparent viscosity decreased. The hydrogen bonds and molecular chains of starch molecules were broken, and the retrogradation decreased. This study provides a theoretical basis and technical support for improving deep exploitation and utilization of potato starch.

Chicken coccidiosis costs the poultry industry over GBP 10 billion per year. The main method of preventing and controlling coccidiosis in chickens continues to be the use of drugs. Unfortunately, the prevalence of drug resistance in the field reduces or even eliminates the effectiveness of drugs, and drug residues in the food supply chain can also can be harmful to humans. Therefore, safe and effective anticoccidial drugs are urgently needed. Natural products have many advantages such as being safe, effective and inexpensive and are a sustainable way to control coccidiosis. In this study, the anticoccidial effects of six natural compounds were tested by Eimeria tenella infection. Oocyst production, cecum lesion, body weight gain, feed conversion ratio, and intestinal microbiota were measured. The results showed that nerolidol had a moderate effect on maintaining both body weight gain and feed conversion ratio. Silymarin and dihydroartemisinin showed significant anticoccidial effects by reducing total oocyst output. Dihydroartemisinin also significantly reduced the cecum lesion caused by Eimeria infection, but this compound may be toxic to the host at such informed doses because it decreases growth and survival rates. In addition, both silymarin and dihydroartemisinin partly restored the microbiota after challenge. This indicates that silymarin, dihydroartemisinin, and nerolidol are effective in the control of chicken coccidiosis. Our data provide basic knowledge about the anticoccidial effects of such natural compounds/derivates.

Background: With the recent evolution of multidrug-resistant strains, the genetic characteristics of foodborne Salmonella enterica serovar Enteritidis and clinical isolates have changed. ST11 is now the most common genotype associated with S. Enteritidis isolates. Methods: A total of 83 strains of S. Enteritidis were collected at the General Hospital of the People’s Liberation Army. Of these, 37 were from aseptic sites in patients, 11 were from the feces of patients with diarrhea, and the remaining 35 were of chicken-origin. The minimum inhibitory concentration of S. Enteritidis was determined by the broth microdilution method. Genomic DNA was extracted using the QiAamp DNA Mini Kit, and whole-genome sequencing (WGS) was performed using an Illumina X-ten platform. Prokka was used for gene prediction and annotation, and bioinformatic analysis tools included Resfinder, ISFinder, Virulence Factor Database, and PlasmidFinder. IQ-TREE was used to build a maximum likelihood phylogenetic tree. The phylogenetic relationship and distribution of resistance genes was displayed using iTOL. Comparative population genomics was used to analyze the phenotypes and genetic characteristics of antibiotic resistance in clinical and chicken-origin isolates of S. Enteritidis. Results: The chicken-origin S. Enteritidis isolates were more resistant to antibiotics than clinical isolates, and had a broader antibiotic resistance spectrum and higher antibiotic resistance rate. A higher prevalence of antibiotic-resistance genes was observed in chicken-origin S. Enteritidis compared to clinical isolates, along with distinct patterns in the contextual characteristics of these genes. Notably, genes such as blaCTX-M and dfrA17 were exclusive to plasmids in clinical S. Enteritidis, whereas in chicken-origin S. Enteritidis they were found in both plasmids and chromosomes. Additionally, floR was significantly more prevalent in chicken-origin isolates than in clinical isolates. Careful analysis revealed that the delayed isolation of chicken-origin S. Enteritidis contributes to accelerated gene evolution. Of note, certain resistance genes tend to integrate seamlessly and persist steadfastly within the chromosome, thereby expediting the evolution of resistance mechanisms against antibiotics. Our comparative analysis of virulence genes in S. Enteritidis strains from various sources found no substantial disparities in the distribution of other virulence factors. In summary, we propose that chicken-origin S. Enteritidis has the potential to cause clinical infections. Moreover, the ongoing evolution and dissemination of these drug-resistant genes poses a formidable challenge to clinical treatment. Conclusions: Constant vigilance is needed to monitor the dynamic patterns of drug resistance in S. Enteritidis strains sourced from diverse origins.

BackgroundIt aimed to investigate the prevalence of anxiety and depression in recurrent pregnancy loss (RPL) women and the related factors in Northeastern China during the Coronavirus disease 2019 (COVID-19) pandemic.MethodsFrom March to June 2021, we conducted an electronic questionnaire survey of 267 RPL women who attended the recurrent pregnancy loss clinic at Shengjing Hospital of China Medical University. The State–Trait Anxiety Inventory (STAI), Beck Depression Inventory-II (BDI-II), Perceived Stress Scale (PSS), and Medical Outcomes Study Social Support Survey (MOS-SSS-C) were used to screen for anxiety, depression, stress, and social support. Logistic regression was used to explore the related factors of anxiety and depression.ResultsRPL women had severe psychological problems during the pandemic: 56.6% showed state anxiety or trait anxiety, 26.6% showed high levels of stress, and 13.1% showed depression. Economic pressure caused by COVID-19, and high stress were common related factors for anxiety and depression. The interval since last miscarriage 14 weeks was associated with depression. While adequate social support and actively seeking health help were protective factors for trait anxiety. And identifying the etiology was a protective factor for depression.ConclusionThe study revealed the prevalence of anxiety, depression, and the associated factors in RPL women during COVID-19. More attention should be paid to the psychology of RPL women and adequate social support should be provided.

Abstract. Background:. Many studies have emphasized that selective resection of epileptic lesions in temoral lobe is associated with better preservation of cognition function; whether this applies to patients with refractory mesial temporal lobe epilepsy (MTLE) remains unknown. The objective of this study was to evaluate changes in cognitive functions, mood status, and quality of life after anterior temporal lobectomy in patients with refractory MTLE. Methods:. This single-arm cohort study assessed cognitive function, mood status, and quality of life, as well as electroencephalography findings, in patients with refractory MTLE who underwent anterior temporal lobectomy at Xuanwu Hospital from January 2018 to March 2019. Pre- and post-operative characteristics were compared to evaluate the effects of surgery. Results:. Anterior temporal lobectomy significantly reduced the frequencies of epileptiform discharges. The overall success rate of surgery was acceptable. Anterior temporal lobectomy did not result in significant changes in overall cognitive functions (P > 0.05), although changes in certain domains, including visuospatial ability, executive ability, and abstract thinking, were detected. Anterior temporal lobectomy resulted in improvements in anxiety and depression symptoms and quality of life. Conclusions:. Anterior temporal lobectomy reduced epileptiform discharges and incidence of post-operative seizures as well as resulted in improved mood status and quality of life without causing significant changes in cognitive function.

Abstract Background More effective targeted therapy and new combination regimens are needed for Acute myeloid leukemia (AML), owing to the unsatisfactory long-term prognosis of the disease. Here, we investigated the synergistic effect and the mechanism of a histone deacetylase inhibitor, Chidamide in combination with Cladribine, a purine nucleoside antimetabolite analog in the disease. Methods Cell counting kit-8 assays and Chou-Talalay’s combination index were used to examine the synergistic effect of Chidamide and Cladribine on AML cell lines (U937, THP-1, and MV4-11) and primary AML cells. PI and Annexin-V/PI assays were used to detect the cell cycle effect and apoptosis effect, respectively. Global transcriptome analysis, RT-qPCR, c-MYC Knockdown, western blotting, co-immunoprecipitation, and chromatin immunoprecipitation assays were employed to explore the molecule mechanisms. Results The combination of Chidamide with Cladribine showed a significant increase in cell proliferation arrest, the G0/G1 phase arrest, and apoptosis compared to the single drug control in AML cell lines along with upregulated p21Waf1/Cip1 expression and downregulated CDK2/Cyclin E2 complex, and elevated cleaved caspase-9, caspase-3, and PARP. The combination significantly suppresses the c-MYC expression in AML cells, and c-MYC knockdown significantly increased the sensitivity of U937 cells to the combination compared to single drug control. Moreover, we observed HDAC2 interacts with c-Myc in AML cells, and we further identified that c-Myc binds to the promoter region of RCC1 that also could be suppressed by the combination through c-Myc-dependent. Consistently, a positive correlation of RCC1 with c-MYC was observed in the AML patient cohort. Also, RCC1 and HDAC2 high expression are associated with poor survival in AML patients. Finally, we also observed the combination significantly suppresses cell growth and induces the apoptosis of primary cells in AML patients with AML1-ETO fusion, c-KIT mutation, MLL-AF6 fusion, FLT3-ITD mutation, and in a CMML-BP patient with complex karyotype. Conclusions Our results demonstrated the synergistic effect of Chidamide with Cladribine on cell growth arrest, cell cycle arrest, and apoptosis in AML and primary cells with genetic defects by targeting HDAC2/c-Myc/RCC1 signaling in AML. Our data provide experimental evidence for the undergoing clinical trial (Clinical Trial ID: NCT05330364) of Chidamide plus Cladribine as a new potential regimen in AML.

The epigenomic landscape of renal cell carcinoma (RCC) remains to be explored. Here, integrative epigenomic analysis of primary human RCC samples and RCC GWAS risk SNPs identifies transcription-factor specific subtypes and enrichment of risk variants in allelically-imbalanced peaks.

ObjectivesWarship damage flooding is an interactive process between progressive flooding and counter-flooding measures under battle-damaged conditions. Traditional damage stability theory cannot simulate the influence of counter-flooding measures on the damaged warship flooding process, and there is no method for predicting this process in the full-time domain.MethodsBy analyzing a coupling relationship between the damage flooding process and counter-flooding measures, a flooding process time domain model is established and a numerical solving algorithm obtained. Case studies are analyzed on the basis of the model and algorithm, and an interactive visual simulation system is developed.ResultsThe simulation systemcan comprehensively assess the flooding process and various counter-flooding measures, providing an important supplement for warship damage stability theory.ConclusionsThis study can help designers to understand the effectiveness of counter-flooding design schemes on the flooding process and guide the design of counter-flooding systems. In addition, it can be used for shipboard flooding decision-making, giving it high military application value.

Regenerating periodontal bone tissues in the aggravated inflammatory periodontal microenvironment under diabetic conditions is a great challenge. Here, a polydopamine-mediated graphene oxide (PGO) and hydroxyapatite nanoparticle (PHA)-incorporated conductive alginate/gelatin (AG) scaffold is developed to accelerate periodontal bone regeneration by modulating the diabetic inflammatory microenvironment. PHA confers the scaffold with osteoinductivity and PGO provides a conductive pathway for the scaffold. The conductive scaffold promotes bone regeneration by transferring endogenous electrical signals to cells and activating Ca2+ channels. Moreover, the scaffold with polydopamine-mediated nanomaterials has a reactive oxygen species (ROS)-scavenging ability and anti-inflammatory activity. It also exhibits an immunomodulatory ability that suppresses M1 macrophage polarization and activates M2 macrophages to secrete osteogenesis-related cytokines by mediating glycolytic and RhoA/ROCK pathways in macrophages. The scaffold induces excellent bone regeneration in periodontal bone defects of diabetic rats because of the synergistic effects of good conductive, ROS-scavenging, anti-inflammatory, and immunomodulatory abilities. This study provides fundamental insights into the synergistical effects of conductivity, osteoinductivity, and immunomodulatory abilities on bone regeneration and offers a novel strategy to design immunomodulatory biomaterials for treatment of immune-related diseases and tissue regeneration.

Abstract Among the promising batteries for electric vehicles, rechargeable Li‐air (O2) batteries (LABs) have risen keen interest due to their high energy density. However, safety issues of conventional nonaqueous electrolytes remain the bottleneck of practical implementation of LABs. Solid‐state electrolytes (SSEs) with non‐flammable and eco‐friendly properties are expected to alleviate their safety concerns, which have become a research focus in the research field of LABs. Herein, we present a systematic review on the progress of SSEs for rechargeable LABs, mainly focusing on the interfacial issues existing between the SSEs and electrodes. The discussion highlights the challenges and feasible strategies for designing suitable SSEs for LABs.

Ingestion of arsenic interferes with spermatogenesis and increases the risk of male infertility, but the underlying mechanism remines unclear. In this study, we investigated spermatogenic injury with a focus on blood-testis barrier (BTB) disruption by administrating 5 mg/L and 15 mg/L arsenic orally to adult male mice for 60 d. Our results showed that arsenic exposure reduced sperm quality, altered testicular architecture, and impaired Sertoli cell junctions at the BTB. Analysis of BTB junctional proteins revealed that arsenic intake downregulated Claudin-11 expression and increased protein levels of β-catenin, N-cadherin, and Connexin-43. Aberrant localization of these membrane proteins was also observed in arsenic-treated mice. Meanwhile, arsenic exposure altered the components of Rictor/mTORC2 pathway in mouse testis, including inhibition of Rictor expression, reduced phosphorylation of protein kinase Cα (PKCα) and protein kinase B (PKB), and elevated matrix metalloproteinase-9 (MMP-9) levels. Furthermore, arsenic also induced testicular lipid peroxidative damage, inhibited antioxidant enzyme (T-SOD) activity, and caused glutathione (GSH) depletion. Our findings suggest that disruption of BTB integrity is one of the main factors responsible for the decline in sperm quality caused by arsenic. PKCα-mediated rearrangement of actin filaments and PKB/MMP-9-increased barrier permeability jointly contribute to arsenic-induced BTB disruption.

Vasohibin1 (VASH1) is a kind of vasopressor, produced by negative feedback from vascular endothelial growth factor A (VEGFA). Anti-angiogenic therapy targeting VEGFA is currently the first-line treatment for advanced ovarian cancer (OC), but there are still many adverse effects. Regulatory T cells (Tregs) are the main lymphocytes mediating immune escape function in the tumor microenvironment (TME) and have been reported to influence the function of VEGFA. However, whether Tregs are associated with VASH1 and angiogenesis in TME in OC is unclear. We aimed to explore the relationship between angiogenesis and immunosuppression in the TME of OC. We validated the relationship between VEGFA, VASH1, and angiogenesis in ovarian cancer and their prognostic implications. The infiltration level of Tregs and its marker forkhead box protein 3 (FOXP3) were explored in relation to angiogenesis-related molecules. The results showed that VEGFA and VASH1 were associated with clinicopathological stage, microvessel density and poor prognosis of ovarian cancer. Both VEGFA and VASH1 expression were associated with angiogenic pathways and there was a positive correlation between VEGFA and VASH1 expression. Tregs correlated with angiogenesis-related molecules and indicated that high FOXP3 expression is harmful to the prognosis. Gene set enrichment analysis (GSEA) predicted that angiogenesis, IL6/JAK/STAT3 signaling, PI3K/AKT/mTOR signaling, TGF-β signaling, and TNF-α signaling via NF-κB may be common pathways for VEGFA, VASH1, and Tregs to be involved in the development of OC. These findings suggest that Tregs may be involved in the regulation of tumor angiogenesis through VEGFA and VASH1, providing new ideas for synergistic anti-angiogenic therapy and immunotherapy in OC.

Because of their high safety, low cost, and high volumetric specific capacity, zinc-ion batteries (ZIBs) are considered promising next-generation energy storage devices, especially given their high potential for large-scale energy storage. Despite these advantages, many problems remain for ZIBs—such as Zn dendrite growth, hydrogen evolution, and Zn anode corrosion—which significantly reduce the coulomb efficiency and reversibility of the battery and limit its cycle lifespan, resulting in much uncertainty in terms of its practical applications. Numerous electrolyte additives have been proposed in recent years to solve the aforementioned problems. This review focuses on electrolyte additives and discusses the different substances employed as additives to overcome the problems by altering the Zn ^2+ solvation structure, creating a protective layer at the anode–electrolyte interface, and modulating the Zn ^2+ distribution to be even and Zn deposition to be uniform. On the basis of the review, the possible research strategies, future directions of electrolyte additive development, and the existing problems to be solved are also described.

The variation of lake water storage is an important indicator for studying both climate change and ecological environment changes. Previous studies have mainly focused on the lake storage changes in recent decades, and predicting future lake storage changes on the Tibetan Plateau under climate change scenarios remains a crucial gap. We addressed this gap by establishing prediction models for water storage changes in nine lakes using historical water storage and climate data from the past 29 years and predicting the water storage changes for the next 80 years under three scenarios based on Phase 6 of the Coupled Model Intercomparison Project (CMIP6) data. The Quantile-mapping (QM) method was applied to correct the precipitation data of CMIP6 with assimilated data. The results indicated that the prediction model performed well, with high correlation (R2 > 0.7 for the training set) and low mean absolute error (MSE < 0.1 km3). The results suggest that most lakes will experience a slight increase in water storage until 2050, followed by a rapid rise until 2100 under all three SSP (Shared Socioeconomic Pathways) scenarios, including SSP126, SSP245, and SSP585. By the end of the century, the total projected increase in lake water storage is estimated to be 189.676 ± 16.266 km3, 191.762 ± 10.683 km3, and 186.212 ± 6.441 km3 until 2100, respectively.

Background Dysregulation of several inflammatory cytokines including tumor necrosis factor (TNF) in dementia patients has also been identified as a key factor in the pathogenesis of rheumatoid arthritis (RA). We aimed to investigate the association of disease-modifying anti-rheumatic drugs (DMARDs) therapy for RA with risk of incident dementia. Methods Electronic database searches of PubMed, EMBASE and Cochrane Library were performed. Observational studies that assessed the association of dementia with DMARDs in RA were included. Pooled risk ratios (RRs) with 95% confidence intervals (CIs) were used as summary statistic. The certainty of evidence using the GRADE system. Results Fourteen studies involving 940,442 patients with RA were included. Pooled RR for developing dementia was 0.76 (95%CI 0.72-0.80) in patients taking biological DMARDs overall versus those taking conventional synthetic DMARDs, with 24% for TNF inhibitors (RR 0.76, 95%CI 0.71-0.82), 24% for non-TNF biologics (RR 0.76, 95%CI 0.70-0.83), separately. There was a significant subgroup effect among different types of TNF inhibitors (RR 0.58, 0.65, 0.80 for etanercept, adalimumab, infliximab, respectively; P-value between groups=0.002). However, compared with nonusers of DMARDs or investigative treatment, no significant effect on dementia incidence was observed in those receiving conventional synthetic DMARDs overall (RR 0.84, 95%CI 0.59-1.20), methotrexate (RR 0.78, 95%CI 0.54-1.12), hydroxychloroquine (RR 0.95, 95%CI 0.63-1.44), except for sulfasalazine (RR 1.27, 95%CI 1.06-1.50). Conclusions Biological DMARDs for RA are associated with decreased dementia risk, while protective effect is not observed in conventional synthetic DMARDs. Controlled clinical trials on TNF inhibitors is necessary to test their neuroprotective potentials.

ObjectivesThe suddenness and rapidity of modern warship disasters have significantly intensified, and higher requirements have been put forward for the information level of the damage control (DC) command network. Based on the complex network characteristic analysis of a DC command information system, its network topology model is constructed. MethodsAiming at the shortcomings of the current model, based on the stochastic networking method and considering the node attributes of the DC command information network and the cost of increasing network density, a structural optimization method for optimal stochastic networking is proposed, and the specific optimization process is demonstrated by case simulation. ResultsThe results show that the command and facilities subnets have different influences on network performance, and the improved random networking method performs better than the traditional random method in network structure optimization. ConclusionsSubsequent research can start by changing the connection mode between subnets to solve the problem of the terminal node of the command subnet being too high, thereby further improving the comprehensive performance of the DC command information network.

Abstract The impacts of weather forecast uncertainties have not been quantified in current air quality forecasting systems. To address this, we developed an efficient 2‐D convolutional neural network‐surface ozone ensemble forecast (2DCNN‐SOEF) system using 2‐D convolutional neural network and weather ensemble forecasts, and we applied the system to 216‐hr ozone forecasts in Shenzhen, China. The 2DCNN‐SOEF demonstrated comparable performance to current operating forecast systems and met the air quality level forecast accuracies required by the Chinese authorities up to 144‐hr lead time. Uncertainties in weather forecasts contributed 38%–54% of the ozone forecast errors at 24‐hr lead time and beyond. The 2DCNN‐SOEF enabled an “ozone exceedance probability” metric, which better represented the risks of air pollution given the range of possible weather outcomes. Our ensemble forecast framework can be extended to operationally forecast other meteorology‐dependent environmental risks globally, making it a valuable tool for environmental management.

Background Tumor-associated macrophages are mainly polarized into the M2 phenotype, remodeling the tumor microenvironment and promoting tumor progression by secreting various cytokines.Methods Tissue microarray consisting of prostate cancer (PCa), normal prostate, and lymph node metastatic samples from patients with PCa were stained with Yin Yang 1 (YY1) and CD163. Transgenic mice overexpressing YY1 were constructed to observe PCa tumorigenesis. Furthermore, in vivo and in vitro experiments, including CRISPR-Cas9 knock-out, RNA sequencing, chromatin immunoprecipitation (ChIP) sequencing, and liquid–liquid phase separation (LLPS) assays, were performed to investigate the role and mechanism of YY1 in M2 macrophages and PCa tumor microenvironment.Results YY1 was highly expressed in M2 macrophages in PCa and was associated with poorer clinical outcomes. The proportion of tumor-infiltrated M2 macrophages increased in transgenic mice overexpressing YY1. In contrast, the proliferation and activity of anti-tumoral T lymphocytes were suppressed. Treatment targeting YY1 on M2 macrophages using an M2-targeting peptide-modified liposome carrier suppressed PCa cell lung metastasis and generated synergistic anti-tumoral effects with PD-1 blockade. IL-4/STAT6 pathway regulated YY1, and YY1 increased the macrophage-induced PCa progression by upregulating IL-6. Furthermore, by conducting H3K27ac-ChIP-seq in M2 macrophages and THP-1, we found that thousands of enhancers were gained during M2 macrophage polarization, and these M2-specific enhancers were enriched in YY1 ChIP-seq signals. In addition, an M2-specific IL-6 enhancer upregulated IL-6 expression through long-range chromatin interaction with IL-6 promoter in M2 macrophages. During M2 macrophage polarization, YY1 formed an LLPS, in which p300, p65, and CEBPB acted as transcriptional cofactors.Conclusions Phase separation of the YY1 complex in M2 macrophages upregulated IL-6 by promoting IL-6 enhancer–promoter interactions, thereby increasing PCa progression.

BackgroundThe risk factors of progestational anxiety, depression, and sleep disturbance in women with a history of recurrent pregnancy loss (RPL) remain controversial, additional study is needed to investigate the incidence and risk factors of progestational anxiety, depression, and sleep quality in RPL women.MethodsA cross-sectional study was conducted among 663 non-pregnant RPL women in Northeast China from October 2019 to July 2022. We assessed the state of anxiety, depression, and sleep quality before pregnancy using structured questionnaires, including sociodemographic characteristics, state-trait anxiety scale (STAI), center for epidemiological survey, depression scale (CES-D), Pittsburgh sleep quality index (PSQI), and symptom self-rating scale (SCL-90). Logistic regression was used to evaluate the association between sleep quality and anxiety, depression. Pearson’s correlation was used to evaluate the correlation between anxiety and depression. Multivariate logistic regression analysis was used to find the risk factors of depression symptoms. The receiver operating characteristic curve (ROC) was used to evaluate the predictive value of the model.ResultsThe incidence of state anxiety, trait anxiety, depression, and sleep disturbance in RPL women were 60.3, 51.7, 33.9, and 31.2%, respectively. The level of anxiety and depression in RPL women varied at different stages of treatment. In a longitudinal study (25 pairs), we found the level of state anxiety and trait anxiety were significantly lower after the cause was identified. Sleep disturbance is positively correlated with anxiety and depression. Logistic regression showed that the number of miscarriages ≥4 (Odds ratio (OR) = 2.268, 95%CI 1.300–3.956), Low household family income (OR = 1.613, 95%CI 1.036–2.513/OR = 2.361, 95%CI 1.095–5.092), interval since last miscarriage

Insomnia, often associated with anxiety and depression, is a prevalent sleep disorder. Biofeedback (BFB) treatment can help patients gain voluntary control over physiological events such as by utilizing electroencephalography (EEG) and electromyography (EMG) power. Previous studies have rarely predicted biofeedback efficacy by measuring the changes in relative EEG power; therefore, we investigated the clinical efficacy of biofeedback for insomnia and its potential neural mechanisms. We administered biofeedback to 82 patients with insomnia, of whom 68 completed 10 sessions and 14 completed 20 sessions. The average age of the participants was 49.38 ± 12.78 years, with 26 men and 56 women. Each biofeedback session consisted of 5 min of EMG and 30 min of EEG feedback, with 2 min of data recorded before and after the session. Sessions were conducted every other day, and four scale measures were taken before the first, fifth, and tenth sessions and after the twentieth session. After 20 sessions of biofeedback treatment, scores on the Pittsburgh Sleep Quality Index (PSQI) were significantly reduced compared with those before treatment (−5.5 ± 1.43,t = −3.85, p = 0.006), and scores on the Beck Depression Inventory (BDI-II) (−7.15 ± 2.43, t = −2.94, p = 0.012) and the State-Trait Anxiety Inventory (STAI) (STAI-S: −12.36 ± 3.40, t = −3.63, p = 0.003; and STAI-T: −9.86 ± 2.38, t = −4.41, p = 0.001) were significantly lower after treatment than before treatment. Beta and theta power were significantly reduced after treatment, compared with before treatment (F = 6.25, p = 0.014; and F = 11.91, p = 0.001). Alpha power was increased after treatment, compared with before treatment, but the difference was not prominently significant (p > 0.05). EMG activity was significantly decreased after treatment, compared with before treatment (F = 2.11, p = 0.015). Our findings suggest that BFB treatment based on alpha power and prefrontal EMG relieves insomnia as well as anxiety and depression and may be associated with increased alpha power, decreased beta and theta power, and decreased EMG power.

Examining the clustering characteristics and fluctuations within urban areas during peak hours through the lens of bike-sharing is of utmost importance in the optimization of bike-sharing systems and urban transportation planning. This investigation adopts the principles of urban spatial interaction network construction and employs streets as the fundamental units of analysis to model bike-sharing activities during morning and evening peak hours within Beijing’s six central districts. Subsequent to this, a comprehensive analysis of the network’s structural attributes was carried out. A Walktrap method, rooted in modularity analysis, was introduced to discern and scrutinize the clustering patterns and characteristics of communities within the network across different temporal intervals. Empirical findings reveal a predominant usage pattern of shared bicycles for short-distance travel during both morning and evening peak hours. Notably, distinctive community structures manifest during these periods, characterized by two large communities and multiple smaller ones during the morning peak, while the evening peak showcases a single large community alongside several medium-sized and smaller ones. Moreover, the extended interaction radius points to an expanded geographic range of interactions among streets. These findings bear significant implications for the management of urban transportation, bike-sharing enterprises, and urban residents, proffering valuable insights for the optimization of bike-sharing schemes and transportation strategies. These research findings not only contribute to enhancing urban transportation planning and bike-sharing systems but also provide robust guidance for advancing more efficient and sustainable urban transportation solutions, thereby fostering the sustainable development of cities.