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High-resolution urban climate modeling has faced substantial challenges due to the absence of a globally consistent, spatially continuous, and accurate dataset to represent the spatial heterogeneity of urban surfaces and their biophysical properties. This deficiency has long obstructed the development of urban-resolving Earth System Models (ESMs) and ultra-high-resolution urban climate modeling, particularly at large scales. Here, we present a first-of-its-kind 1km-resolution present-day (circa-2020) global continuous urban surface parameter dataset – U-Surf. Using the urban canopy model (UCM) in the Community Earth System Model as a base model for developing dataset requirements, U-Surf leverages the latest advances in remote sensing, machine learning, and cloud computing to provide the most relevant urban surface biophysical parameters, including radiative, morphological, and thermal properties, for UCMs at the facet- and canopy-level. Our high-resolution U-Surf dataset significantly improves the representation of the urban land heterogeneity both within and across cities globally. U-Surf provides essential, high-fidelity surface biophysical constraints to urban-resolving ESMs, enables detailed city-to-city comparisons across the globe, and supports the next-generation kilometer-resolution Earth system modeling across scales. U-Surf parameters can be easily converted or adapted to various types of UCMs, such as those embedded in weather and regional climate models, as well as air quality models. The fundamental urban surface constraints provided by U-Surf are also relevant as features for machine learning models and can have other broad-scale applications for socioeconomic, public health, and urban planning contexts. We expect U-Surf to promote the research frontier on urban systems science, climate-sensitive urban design, and coupled human-Earth systems in the future. The dataset is publicly available at https://doi.org/10.5281/zenodo.11247599 (Cheng et al., 2024). [ABSTRACT FROM AUTHOR]

The multiway valve is the core control element of the hydraulic system in construction machinery, such as excavators. Its complex internal structure, especially the flow channels, significantly impacts the machine's efficiency and reliability. This study focuses on the boom flow channel of excavator multiway valves and establishes a multi-physical field coupling simulation model. We propose six key flow channel structural parameters and analyze changes in the valve's flow field, temperature field, and structural field using orthogonal test simulation data. The range analysis method identifies the primary and secondary influences of structural parameters on pressure loss, temperature, stress, and strain. A multi-objective optimization model was developed using a neural network and the Non-dominated Sorting Genetic Algorithm II(NSGA-II), with pressure loss and maximum stress as the optimization objectives. The Pareto front solution set for key flow channel parameters was calculated. The optimization results showed a 9.0% reduction in pressure loss and a 40.7% reduction in maximum stress. A test bench verified the simulation model, achieving prediction accuracies of 94.8% for pressure loss in the inlet area and 92.3% in the return area. This method can provide a reference for the optimal design of the dynamic characteristics of high-pressure multiway valves. [ABSTRACT FROM AUTHOR]

Background: Despite the established negative regulatory effects observed in various diseases like cardiovascular disease and diabetes, the distinct impact of red cell distribution width (RDW) to albumin ratio (RAR) on mortality within the realm of rheumatoid arthritis (RA) remains obscure. This study sought to explore the relationship between RAR and mortality in RA patients. Methods: A cohort of 2151 adults with RA from the National Health and Nutrition Examination Survey (NHANES) spanning 2003–2016 was analyzed for RAR levels derived from red cell distribution width and albumin concentrations. Utilizing Cox regression analysis, Kaplan–Meier curves, and Restricted Cubic Spline (RCS) models, we assessed the association between RAR levels and RA mortality while adjusting for potential confounding variables. Results: Participants with higher RAR had a twofold to threefold increased risk of all‐cause (HR = 3.10, 95% CI: 2.26–4.24) and cardiovascular mortality (HR = 2.46, 95%CI: 1.26–4.79) versus lower RAR. Kaplan–Meier analysis revealed that the higher RAR group had a significantly lower survival rate compared to the lower RAR group for both all‐cause and cardiovascular mortality (both p <.0001), with a more pronounced effect observed for all‐cause mortality. Furthermore, the RCS‐fitted Cox regression model illustrated a nonlinear positive correlation between RAR levels and RA mortality. Conclusion: Overall, a higher RAR was associated with an increased risk mortality in RA patients. These findings underscore the potential of RAR as a prognostic biomarker in predicting outcomes in RA. [ABSTRACT FROM AUTHOR]

Histiocytic sarcoma is a rare neoplasm of mature histiocytes with an aggressive clinical course and poor response to treatment. Primary gastric histiocytic sarcoma is rarer and just reported sporadically.Histiocytic sarcoma is a rare neoplasm of mature histiocytes with an aggressive clinical course and poor response to treatment. Primary gastric histiocytic sarcoma is rarer and just reported sporadically. A case of a 71-year-old female admitted with a one-year history of upper abdominal pain exacerbated after meals. After CT scans revealed a bulged mass at the lesser curvature of the gastric body, the patient underwent endoscopic submucosal dissection. Microscopically, non-cohesive neoplastic cells diffusely infiltrated lamina propria and submucosa, and diffusely expressed LCA, CD4, CD163, CD68 (KP1), Cyclin D1, Lysozyme, and Vimentin. PD-L1 (22CS) expression evaluated as CPS 60. The final pathological diagnosis was gastric histiocytic sarcoma. Subsequently, next-generation sequencing identified a nonsense mutation in exon 21 of NF1 gene [c.2446C > T (p.R816*)] and the TUBB3 gene amplification (copy number: 4.55). The patient refused further treatment and died of the tumor half a year later. This case broadens the spectrum of differential diagnosis of gastric cancer and emphasizes the value of immunohistochemical and molecular tests in the accurate diagnosis of histiocytic sarcoma. Furthermore, we performed literature review of 11 cases of gastric histiocytic sarcoma so as to strengthen the understanding of the clinicopathologic features, treatment, and prognosis. [ABSTRACT FROM AUTHOR]

Epidemiological compartmental models, such as SEIR (Susceptible, Exposed, Infectious, and Recovered) models, have been generally used in analyzing epidemiological data and forecasting the trajectory of transmission of infectious diseases such as COVID-19. Experience shows that accurately forecasting the trajectory of COVID-19 transmission curve is a big challenge for researchers in the field of epidemiological modeling because multiple unquantified factors can affect the trajectory of COVID-19 transmission. In the past years, we used a new compartmental model, l-i SEIR model, to analyze the COVID-19 transmission trend in the United States. Unlike the conventional SEIR model and the delayed SEIR model that use or partially use the approximation of temporal homogeneity, the l-i SEIR model takes into account chronological order of infected individuals in both latent (l) period and infectious (i) period, and thus improves the accuracy in forecasting the trajectory of transmission of infectious diseases, especially during periods of rapid rise or fall in the number of infections. This paper describes (1) how to use the new SEIR model (a mechanistic model) combined with fitting methods to simulate or predict trajectory of COVID-19 transmission, (2) how social interventions and new variants of COVID-19 significantly change COVID-19 transmission trends by changing transmission rate coefficient βn, the fraction of susceptible people (Sn/N), and the reinfection rate, (3) why accurately forecasting COVID-19 transmission trends is difficult, (4) what are the strategies that we have used to improve the forecast outcome and (5) what are some successful examples that we have obtained. [ABSTRACT FROM AUTHOR]

Cellular automata (CA) models have been extensively employed to predict and understand the spatiotemporal dynamics of land use. Driving factors play a significant role in shaping and driving land-use changes. Mining land-use transition rules from driving factors and quantifying the contribution of driving factors to land-use dynamics are fundamental aspects of CA simulation. However, existing CA models have limitations in obtaining accurate transition rules and reliable interpretations simultaneously for multiple land-use simulations. In this study, we constructed a CA model based on a tree-based deep learning algorithm, deep cascade forest (DCF), to improve multiple land-use simulations and driving factors analysis. The DCF algorithm was utilized to mine accurate multiple land-use transition rules without overfitting to improve CA simulation accuracy. Additionally, a novel ensemble mean decrease of impurity (MDI) factor importance analysis method (DCF-MDI), which leverages the cascade structure of the DCF model, was proposed to qualify the contribution of each driving factor to land-use dynamics stably and efficiently. To evaluate the effectiveness of the proposed DCF-CA, we applied the model to simulate land-use distributions and explore the driving mechanisms of land-use dynamics in the Pearl River Delta (PRD), China, from 2000 to 2010. Compared to existing models, the proposed DCF-CA model exhibits the highest accuracy (FoM = 23.79%, PA = 39.77%, UA = 36.35%, OA = 91.50%), which demonstrates its superiority in mining accurate transition rules for capturing multiple land-use dynamics. Factor importance analysis reveals that the proposed DCF-MDI method yields more stable ranking orders and lower standard deviation of contribution weights (<0.10%) compared to the traditional method, indicating its robustness to random disturbances and effectiveness in elucidating the driving mechanisms of land-use dynamics. The DCF-CA model proposed in this study, demonstrating high simulation accuracy and reliable interpretability simultaneously, can provide substantial support for sustainable land use management. [ABSTRACT FROM AUTHOR]

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The hydrodynamics of the flow around piers affects the motion of ships navigating near these structures, while the motion of the ships, in turn, affects the distribution of the flow field near the piers. This study investigates the forces exerted on a ship in various ship–pier transverse distances using commercial computational fluid dynamics (CFD) software, Fluent 13.0, based on the RNG k-ε model, complemented by experiments with a physical model. The interaction between the ship's motion and the flow field near the piers was considered. The results indicate that during the encounter between the ship and the pier, the boundary of the approaching ship affects the flow field near the pier, thereby affecting the generation and detachment of vortices behind the pier. The yaw moment of the ship demonstrates a marked "positive peak–negative peak–positive peak" pattern. Moreover, as the ship–pier transverse distance increases, the impact of the pier on the ship's motion decreases, and it becomes negligible when the distance reaches 0.9 times the diameter of the pier (D), suggesting that the pier has a minimal impact on ship navigation if the ship–pier transverse distance exceeds this threshold. [ABSTRACT FROM AUTHOR]

Natural gas hydrate solid fluidization mining technology is a new hydrate mining technology, but due to the lack of combined nozzle design theory and basis, the crushing efficiency of mining tools is low. To solve this problem, the characteristics of the combined jet flow fields of nozzles with diameters from 1 mm to 4 mm and combination angles from 10° to 20° were studied in this paper by means of experiments and simulations. The results show that the maximum velocity at the merging point increases negatively linearly with increases in the combination angle and positively linearly with increase in the nozzle diameter. The position of the merging point changes little with the nozzle diameter and increases exponentially with increases in the combination angle. The effective crushing lengths of nozzles with different diameters all turn (increase first and then decrease) when the combination angle is 12.5°. The optimal combination angle for nozzles with diameter less than 4.5 mm is 12.5°, and 15° is for nozzles with diameter more than 4.5 mm. This study reveals the flow field variation mechanism for the combined nozzle and provides guidance for the design of the combined nozzles of gas hydrate combined nozzles. [ABSTRACT FROM AUTHOR]

This paper presents a novel containment control scheme for multi-agent systems against denial of service attacks. The control goal is to ensure that the follower moves into the convex hull formed by dynamic leaders at any initial position. Different from existing results, the proposed scheme generates a position-adjustable reference signal for each follower. Simultaneously, if the convex hull information is not available, the follower will follow an estimated reference signal to reduce the probability of collision. Additionally, we also implemented adaptive fuzzy control and combined with the command filtered technique to optimize the control scheme. By utilizing Lyapunov theory, the stability analysis is carried out for closed-loop multi-agent systems. Finally, extensive simulations validate the superiority and feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

Background: With the increasing incidence of obesity and the childbearing-age delay among women, a debate over obesity's impacts on pregnancy and neonatal outcomes becomes hot. The potential negative effects of obesity and aging on fertility lead to an idea, whether an obese female pursuing IVF treatment can benefit from an ideal BMI achieved over a long-time weight loss process at the cost of aging? We aimed to assess the association between body mass index (BMI) and clinical or neonatal outcomes in patients undergoing in vitro fertilization (IVF) treatment, for answering whether it is necessary to lose weight first for obese patients, particularly those at advanced age. Methods: A retrospective cohort study was performed using multicentered data from China. The women were stratified into 5 groups in terms of pre-gravid BMI (kg/m2) with the WHO obesity standard (group 1: BMI < 18.5; group 2: 18.5 ≤ BMI < 23.0; group 3: 23.0 ≤ BMI < 25.0; group 4: 25.0 ≤ BMI < 30.0; group 5: BMI ≥ 30.0). The primary outcome was cumulative live birth rate (CLBR), and other clinical and neonatal outcomes were weighed as secondary outcomes. Multivariate logistic regression analyses were carried to evaluate the association between BMI and the CLBR, or between BMI and some neonatal outcomes. Furthermore, we implemented a machine-learning algorithm to predict the CLBR based on age and BMI. Results: A total of 115,287 women who underwent first IVF cycles with autologous oocytes from January 2013 to December 2017 were included in our study. The difference in the CLBR among the five groups was statistically significant (P < 0.001). The multivariate logistic regression analysis showed that BMI had no significant impact on the CLBR, while women's age associated with the CLBR negatively. Further, the calculation of the CLBR in different age stratifications among the five groups revealed that the CLBR lowered with age increasing, quantitatively, it decreased by approximately 2% for each one-year increment after 35 years old, while little difference observed in the CLBR corresponding to the five groups at the same age stratification. The machine-learning algorithm derived model showed that BMI's effect on the CLBR in each age stratification was negligible, but age's impact on the CLBR was overwhelming. The multivariate logistic regression analysis showed that BMI did not affect preterm birth, low birth weight infant, small for gestational age (SGA) and large for gestational age (LGA), while BMI was an independent risk factor for fetal macrosomia, which was positively associated with BMI. Conclusions: Maternal pre-gravid BMI had no association with the CLBR and neonatal outcomes, except for fetal macrosomia. While the CLBR was lowered with age increasing. For the IVF-pursuing women with obesity plus advanced age, rather than losing weight first, the sooner the treatment starts, the better. A multicentered prospective study with a large size of samples is needed to confirm this conclusion in the future. [ABSTRACT FROM AUTHOR]

Purpose: This study evaluates the efficacy of intrauterine hCG perfusion for RIF, as defined by ESHRE 2023 guidelines, highlighting hCG as a cost-effective alternative to other immunotherapies, especially suitable for less developed regions. It aims to clarify treatment guidance amidst previous inconsistencies. Methods: This meta-analysis, registered with PROSPERO (CRD42024443241) and adhering to PRISMA guidelines, assessed the efficacy and safety of intrauterine hCG perfusion in enhancing implantation and pregnancy outcomes in RIF. Comprehensive literature searches were conducted through December 2023 in major databases including PubMed, Web of Science, Embase, the Cochrane Library, and key Chinese databases, without language restrictions. Inclusion and exclusion criteria were strictly aligned with the 2023 ESHRE recommendations, with exclusions for studies lacking robust control, clear outcomes, or adequate data integrity. The risk of bias was evaluated using the Newcastle-Ottawa Scale, ROBINS-I, and RoB2 tools. Data analysis was performed in R using the 'meta' package, employing both fixed and random effect models to account for study variability. Subgroup analyses by dosage, volume, hCG concentration, timing of administration, and type of embryo transfer were conducted to deepen insights, enhancing the reliability and depth of the meta-analysis in elucidating the role of hCG perfusion in RIF treatments. Results: Data from 13 studies, comprising six retrospective and six prospective studies from single centers, along with one multi-center RCT, totaling 2,157 participants, were synthesized to evaluate the effectiveness of intrauterine hCG perfusion in enhancing implantation and pregnancy outcomes in patients with RIF. Significant improvements were observed in clinical pregnancy and embryo implantation rates across various dosages, timing of administration, and embryo developmental stages, without impacting miscarriage rates. Notably, the most significant efficacy within subgroups occurred with a 500 IU dosage and perfusion parameters of ≤ 500µL volume and ≥ 2 IU/µL concentration. Additionally, a limited number of studies showed no significant increases in ectopic pregnancy or multiple pregnancy rates, and a modest improvement in live birth rates, although the small number of these studies precludes definitive conclusions. Conclusions: The analysis suggests that intrauterine hCG perfusion probably enhances embryo implantation, clinical pregnancy, and live birth rates slightly in RIF patients. Benefits are indicated with a dosage of 500 IU and a maximum volume of 500µL at concentrations of at least 2 IU/µL. However, substantial heterogeneity from varying study types and the limited number of studies necessitate cautious interpretation. These findings underscore the need for more rigorously designed RCTs to definitively assess the efficacy and safety. [ABSTRACT FROM AUTHOR]

The yield of sweet potato [Ipomoea batatas (L.) Lam] can be easily threatened by drought stress. Typically, early stages like the seedling stage and tuber-root expansion stage are more vulnerable to drought stress. In this study, a highly drought-tolerant sweet potato cultivar "WanSu 63" was subjected to drought stress at both the seedling stage (15 days after transplanting, 15 DAT) and the tuber-root expansion stage (45 DAT). Twenty-four cDNA libraries were constructed from leaf segments and root tissues at 15 and 45 DAT for Next-Generation Sequencing. A total of 663, 063, and 218 clean reads were obtained and then aligned to the reference genome with a total mapped ratio greater than 82.73%. A sum of 7119, 8811, 5463, and 930 differentially expressed genes were identified from leaves in 15 days (L15), roots in 15 days (R15), leaves in 45 days (L45), and roots in 45 days (R45), respectively, in drought stress versus control. It was found that genes encoding heat shock proteins, sporamin, LEA protein dehydrin, ABA signaling pathway protein gene NCED1, as well as a group of receptor-like protein kinases genes were enriched in differentially expressed genes. ABA content was significantly higher in drought-treated tissues than in the control. The sweet potato biomass declined sharply to nearly one-quarter after drought stress. In conclusion, this study is the first to identify the differentially expressed drought-responsive genes and signaling pathways in the leaves and roots of sweet potato at the seedling and root expansion stages. The results provide potential resources for drought resistance breeding of sweet potato. [ABSTRACT FROM AUTHOR]

The progression of complex diseases often involves abrupt and non-linear changes characterized by sudden shifts that trigger critical transformations. Identifying these critical states or tipping points is crucial for understanding disease progression and developing effective interventions. To address this challenge, we have developed a model-free method named Network Information Entropy of Edges (NIEE). Leveraging dynamic network biomarkers, sample-specific networks, and information entropy theories, NIEE can detect critical states or tipping points in diverse data types, including bulk, single-sample expression data. By applying NIEE to real disease datasets, we successfully identified critical predisease stages and tipping points before disease onset. Our findings underscore NIEE's potential to enhance comprehension of complex disease development. [ABSTRACT FROM AUTHOR]

Background: The Oxidative Balance Score (OBS) is a systematic tool to assess the effects of diet and lifestyle in relation to oxidative stress. The association between OBS and gout has not been reported previously. We conducted a cross‐sectional study to investigate the complex association between OBS and gout in US adults. Methods: In all, 10 492 participants were included in this study. The exposure variable was OBS, which was scored by 16 dietary and four lifestyle factors. Multivariate logistic regression, subgroup analysis, and restricted cubic spline (RCS) regression were used to analyze the association between OBS and gout. Results: Compared with the lowest OBS quartile group (Q1), the multivariate corrected odds ratio (OR) (95% confidence interval [C]) for the highest quartile of OBS (Q4) was 0.72 (0.52–1.00) (p =.13 for trend); furthermore, the RCS showed a negative linear relationship between OBS and gout (p‐nonlinear =.606). Conclusion: In conclusion, the risk of gout is higher with high OBS. The prevalence of gout decreased with higher OBS. Diabetes may alter this negative correlation. [ABSTRACT FROM AUTHOR]

Background: Oxidative stress is associated with risk of pathogenesis between rheumatoid arthritis. The Oxidative Balance Score (OBS) is a systematic tool to assess the effects of diet and lifestyle in relation to oxidative stress. However, the association between OBS and rheumatoid arthritis has not been reported previously. We conducted a cross‐sectional study to investigate the complex association between OBS and rheumatoid arthritis in US adults. Methods: Overall, 9747 participants were included in this cross‐sectional study. The exposure variable was OBS, which was scored by 16 dietary and four lifestyle factors. Multivariate logistic regression, subgroup analysis, and restricted cubic spline (RCS) regression were used to analyze the association between OBS and rheumatoid arthritis. Results: Compared to the lowest OBS quartile group (Q1), the multivariate corrected odds ratio (OR) (95% confidence interval [CI]) for the highest quartile of OBS (Q4) was 0.69 (0.52–0.90) (p =.013 for trend); furthermore, the RCS showed a negative linear relationship between OBS and rheumatoid arthritis. According to subgroup and RCS analyses, there was a significant difference between the association of OBS and with rheumatoid arthritis in terms of gender (p =.049). Conclusion: In conclusion, high OBS was negatively associated with the risk of rheumatoid arthritis. Gender has an effect on OBS in RA. Our results suggest that OBS can be used as a biomarker to predict rheumatoid arthritis. [ABSTRACT FROM AUTHOR]

Understanding urban vertical structures, particularly building heights, is essential for examining the intricate interaction between humans and their environment. Such datasets are indispensable for a variety of applications, including climate modeling, energy consumption analysis, and socioeconomic activities. Despite the importance of this information, previous studies have primarily focused on estimating building heights regionally on a grid scale, often resulting in datasets with limited coverage or spatial resolution. This limitation hampers comprehensive global analyses and the ability to generate actionable insights on finer scales. In this study, we developed a global building height map (3D-GloBFP) at a building footprint scale by leveraging Earth Observation (EO) datasets and advanced machine learning techniques. Our approach integrated multisource remote sensing features and building morphology features to develop height estimation models using the eXtreme Gradient Boosting (XGBoost) regression method across diverse global regions. This methodology allowed us to estimate the heights of individual buildings worldwide, culminating in the creation of the first global three-dimensional (3-D) building footprints (3D-GloBFP). Our evaluation results show that the height estimation models perform exceptionally well on a worldwide scale, with R 2 ranging from 0.66 to 0.96 and root mean square errors (RMSEs) ranging from 1.9 m to 14.6 m across 33 subregions. Comparisons with other datasets demonstrate that our 3D-GloBFP closely matches the distribution and spatial pattern of reference heights. Our derived 3-D global building footprint map shows a distinct spatial pattern of building heights across regions, countries, and cities, with building heights gradually decreasing from the city center to the surrounding rural areas. Furthermore, our findings indicate the disparities in built-up infrastructure (i.e., building volume) across different countries and cities. China is the country with the most intensive total built-up infrastructure (5.28×1011 m3, accounting for 23.9 % of the global total), followed by the United States (3.90×1011 m3, accounting for 17.6 % of the global total). Shanghai has the largest volume of built-up infrastructure (2.1×1010 m3) of all representative cities. The derived building-footprint scale height map (3D-GloBFP) reveals the significant heterogeneity of urban built-up environments, providing valuable insights for studies in urban socioeconomic dynamics and climatology. The 3D-GloBFP dataset is available at https://doi.org/10.5281/zenodo.11319913 (Building height of the Americas, Africa, and Oceania in 3D-GloBFP) (Che et al., 2024a), https://doi.org/10.5281/zenodo.11397015 (Building height of Asia in 3D-GloBFP) (Che et al., 2024b), and https://doi.org/10.5281/zenodo.11391077 (Building height of Europe in 3D-GloBFP) (Che et al., 2024c). [ABSTRACT FROM AUTHOR]

This paper studied the characteristics of the carbon emission of an industrial wastewater treatment plant (IWWTP) and a domestic WWTP (DWWTP) located in a high-tech industrial park of Shaanxi Province, China. The results showed that the total carbon emissions of the IWWTP and DWWTP were 10.13 kg/t and 1.84 kg/t in 2020, respectively. Indirect carbon emissions play a dominant role in the total carbon emission of the IWWTP, which accounts for about 97.6% of the total amount. The direct carbon emissions of greenhouse gases (e.g., CH4, N2O) account for about 62% of the total carbon emissions in the DWWTP, followed by the indirect carbon emissions generated by electricity consumption (31.06%) and chemical consumption (6.94%). Additionally, the centralized recycling and re-utilization of the wastewater could achieve 1.06 kg/t and 1.16 kg/t of carbon emission reduction in the IWWTP and DWWTP, respectively, while the carbon emissions of the DWWTP are inversely proportional to the treatment capacity. Therefore, it is of great value to collect and utilize intensively the recycled water to achieve the goal of regional carbon emission reduction and carbon neutralization of WWTPs in industrial parks. [ABSTRACT FROM AUTHOR]

Recently, geraniin has been identified as a potent antiviral agent targeting SARS-CoV-2 main protease (Mpro). Considering the potential of geraniin in COVID-19 treatment, a stringent validation for its Mpro inhibition is necessary. Herein, we rigorously evaluated the in vitro inhibitory effect of geraniin on Mpro using the fluorescence resonance energy transfer (FRET), fluorescence polarization (FP), and dimerization-dependent red fluorescent protein (ddRFP) assays. Our data indicate that geraniin is not a potential inhibitor against Mpro based on the results from a set of in vitro assays. These results suggest a stringent in vitro validation with diverse biochemical assays is essential for the discovery of Mpro inhibitors, and the fluorescence quenching effect caused by natural products should be considered when evaluating Mpro inhibitors. [ABSTRACT FROM AUTHOR]

In this article, the prescribed‐time global stabilization problem is taken into consideration when it comes to multi‐input‐multi‐output (MIMO) systems with unknown mismatched coupling nonlinear items. It is assumed that the unknown nonlinearities satisfy the linear growth conditions. First, a class of MIMO coupling nonlinear systems with controllable canonical form are considered. Then, by wielding a time‐varying Lyapunov‐like function and properties of parametric Lyapunov equations, a high‐gain linear time‐varying state feedback control law is developed to attenuate the impact of unknown nonlinear terms. Meanwhile, all state signals and control inputs are globally bounded and the target system becomes stable within the prescribed‐time. Finally, the simulation results on an example system with 3 inputs and 11 state variables verify that the developed control mechanism accomplishes the goal of global stabilization in the pre‐defined time. [ABSTRACT FROM AUTHOR]

Inferring causality from observed data is crucial in many scientific fields, but this process is often hindered by incomplete data. The incomplete data can lead to mistakes in understanding how variables affect each other, especially when some influencing factors are not directly observed. To tackle this problem, we've developed a new algorithm called Regression Loss-increased with Causal Intensity (RLCI). This approach uses regression and entropy analysis to uncover hidden variables. Through tests on various real-world datasets, RLCI has been proven to be effective. It can help spot hidden factors that may affect the relationship between variables and determine the direction of causal relationships. [ABSTRACT FROM AUTHOR]

JC polyomavirus (JCPyV) is a human polyomavirus that can establish lifelong persistent infection in the majority of adults. It is typically asymptomatic in immunocompetent individuals. However, there is a risk of developing progressive multifocal leukoencephalopathy (PML) in immunocompromised or immunosuppressed patients. Though JCPyV commonly resides in the kidney-urinary tract, its involvement in urinary system diseases is extremely rare. Here, we reported a case of a 60-year-old male patient with coronavirus disease 2019 (COVID-19) infection who developed hemorrhagic cystitis after receiving treatment with nirmatrelvir 300 mg/ritonavir 100 mg quaque die (QD). Subsequent metagenomic next-generation sequencing (mNGS) confirmed the infection to be caused by JCPyV type 2. Then, human immunoglobulin (PH4) for intravenous injection at a dose of 25 g QD was administered to the patient. Three days later, the hematuria resolved. This case illustrates that in the setting of compromised host immune function, JCPyV is not limited to causing central nervous system diseases but can also exhibit pathogenicity in the urinary system. Moreover, mNGS technology facilitates rapid diagnosis of infectious etiology by clinical practitioners, contributing to precise treatment for patients. [ABSTRACT FROM AUTHOR]

Objective: IR emerges as a feature in the pathophysiology of PCOS, precipitating ovulatory anomalies and endometrial dysfunctions that contribute to the infertility challenges characteristic of this condition. Despite its clinical significance, a consensus on the precise mechanisms by which IR exacerbates PCOS is still lacking. This study aims to harness bioinformatics tools to unearth key IR-associated genes in PCOS patients, providing a platform for future therapeutic research and potential intervention strategies. Methods: We retrieved 4 datasets detailing PCOS from the GEO, and sourced IRGs from the MSigDB. We applied WGCNA to identify gene modules linked to insulin resistance, utilizing IR scores as a phenotypic marker. Gene refinement was executed through the LASSO, SVM, and Boruta feature selection algorithms. qPCR was carried out on selected samples to confirm findings. We predicted both miRNA and lncRNA targets using the ENCORI database, which facilitated the construction of a ceRNA network. Lastly, a drug-target network was derived from the CTD. Results: Thirteen genes related to insulin resistance in PCOS were identified via WGCNA analysis. LASSO, SVM, and Boruta algorithms further isolated CAPN2 as a notably upregulated gene, corroborated by biological verification. The ceRNA network involving lncRNA XIST and hsa-miR-433-3p indicated a possible regulatory link with CAPN2, supported by ENCORI database. Drug prediction analysis uncovered seven pharmacological agents, most being significant regulators of the endocrine system, as potential candidates for addressing insulin resistance in PCOS. Conclusions: This study highlights the pivotal role of CAPN2 in insulin resistance within the context of PCOS, emphasizing its importance as both a critical biomarker and a potential therapeutic target. By identifying CAPN2, our research contributes to the expanding evidence surrounding the CAPN family, particularly CAPN10, in insulin resistance studies beyond PCOS. This work enriches our understanding of the mechanisms underlying insulin resistance, offering insights that bridge gaps in the current scientific landscape. [ABSTRACT FROM AUTHOR]

Formulating ecological restoration strategies requires accurately quantifying how climate and anthropogenic factors influence net primary production (NPP). A Carnegie-Ames-Stanford approach (CASA) model was applied to estimate China's terrestrial NPP from 2001 to 2020. We adopted a random forest (RF) method to identify the main driving forces for NPP change in China. Total NPP in China increased noticeably with a 24.91 Tg C/yr rate, as shown in our results. The significantly increased NPP was mainly attributed to human activities (64.29 ± 0.17%), chiefly due to human management and ecological projects (afforestation or other) fostered vegetation growth. The primary drivers of NPP variation varied in different geographic regions. Climate dominated the NPP dynamic in north China (52.38 ± 0.91%), where the main factor that restricted the increase of NPP was precipitation. Human activities strongly impacted the NPP variation in the remaining regions. Human management measures increased NPP in northwest and southwest China. In the northeast, east, and south-central China, the NPP change resulted from land use change, primarily grassland, cropland, and forest change. Collectively, our study expands the understanding of the driving forces of NPP change, informing different strategies for achieving ecological restoration and carbon neutrality. [ABSTRACT FROM AUTHOR]

Background: Acute lymphoblastic leukemia (ALL) is the most common cancer in children. IKZF3 (IKAROS family zinc finger 3) is a hematopoietic‐specific transcription factor, and it has been validated that it is involved in leukemia. However, the role of IKZF3 single‐nucleotide polymorphisms (SNPs) remains unclear. In this case–control study, the authors investigated the association of IKZF3 SNPs with ALL in children. Methods: Six IKZF3 reference SNPs (rs9635726, rs2060941, rs907092, rs12946510, rs1453559, and rs62066988) were genotyped in 692 patients who had ALL (cases) and in 926 controls. The associations between IKZF3 polymorphisms and ALL risk were determined using odds ratios (ORs) and 95% confidence intervals (CIs). The associations of rs9635726 and rs2060941 with the risk of ALL were further estimated by using false‐positive report probability (FPRP) analysis. Functional analysis in silico was performed to evaluate the probability that rs9635726 and rs2060941 might influence the regulation of IKZF3. Results: The authors observed that rs9635726C>T (adjusted OR, 1.49; 95% CI, 1.06–2.11; p =.023) and rs2060941G>T (adjusted OR, 1.51; 95% CI, 1.24–1.84; p =.001) were related to and increased risk of ALL in the recessive and dominant models, respectively. Furthermore, the associations of both rs9635726 (FPRP =.177) and rs2060941 (FPRP <.001) with ALL were noteworthy in the FPRP analysis. Functional analysis indicated that rs9635726 and rs2060941 might repress the transcription of IKZF3 by disrupting its binding to MLLT1, TAF1, POLR2A, and/or RAD21. Conclusions: This study revealed that IKZF3 polymorphisms were associated with increased ALL susceptibility in children and might influence the expression of IKZF3 by disrupting its binding to MLLT1, TAF1, POLR2A, and/or RAD21. IKZF3 polymorphisms were suggested as a biomarker for childhood ALL. [ABSTRACT FROM AUTHOR]

Background: Southwest China is one of the largest karst regions in the world. Karst environment is relatively fragile and vulnerable to human activities. Due to the discharge of sewage and domestic garbage, the karst system may be polluted by pathogenic bacteria. The detection of bacterial distribution and identification of phage capable of infecting them is an important approach for environmental assessment and resource acquisition. Methods: Bacteria and phages were isolated from karst water in southwest China using the plate scribing and double plate method, respectively. Isolated phage was defined by transmission electron microscopy, one-step growth curve and optimal multiplicity of infection (MOI). Genomic sequencing, phylogenetic analysis, comparative genomic and proteomic analysis were performed. Results: A Klebsiella quasipneumoniae phage was isolated from 32 isolates and named KL01. KL01 is morphologically identified as Caudoviricetes with an optimal MOI of 0.1, an incubation period of 10 min, and a lysis period of 60 min. The genome length of KL01 is about 45 kb, the GC content is 42.5%, and it contains 59 open reading frames. The highest average nucleotide similarity between KL01 and a known Klebsiella phage 6939 was 83.04%. Conclusions: KL01 is a novel phage, belonging to the Autophagoviridae, which has strong lytic ability. This study indicates that there were not only some potential potentially pathogenic bacteria in the karst environment, but also phage resources for exploration and application. [ABSTRACT FROM AUTHOR]

The outbreak of coronavirus disease 2019 (COVID‐19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is a global threat to human health. In parallel with vaccines, efficacious antivirals are urgently needed. SARS‐CoV‐2 main protease (Mpro) is an attractive drug target for antiviral development owing to its key roles in virus replication and host immune evasion. Due to the limitations of currently available methods, the development of novel high‐throughput screening assays is of the highest importance for the discovery of Mpro inhibitors. In this study, we first developed an improved fluorescence‐based assay for rapid screening of Mpro inhibitors from an anti‐infection compound library using a versatile dimerization‐dependent red fluorescent protein (ddRFP) biosensor. Utilizing this assay, we identified MG‐101 as a competitive Mpro inhibitor in vitro. Moreover, our results revealed that ensitrelvir is a potent Mpro inhibitor, but baicalein, chloroquine, ebselen, echinatin, and silibinin are not. Therefore, this robust ddRFP assay provides a faithful avenue for rapid screening and evaluation of Mpro inhibitors to fight against COVID‐19. [ABSTRACT FROM AUTHOR]

Recent advances in spatially resolved transcriptomics (SRT) have brought ever-increasing opportunities to characterize expression landscape in the context of tissue spatiality. Nevertheless, there still exist multiple challenges to accurately detect spatial functional regions in tissue. Here, we present a novel contrastive learning framework, SPAtially Contrastive variational AutoEncoder (SpaCAE), which contrasts transcriptomic signals of each spot and its spatial neighbors to achieve fine-grained tissue structures detection. By employing a graph embedding variational autoencoder and incorporating a deep contrastive strategy, SpaCAE achieves a balance between spatial local information and global information of expression, enabling effective learning of representations with spatial constraints. Particularly, SpaCAE provides a graph deconvolutional decoder to address the smoothing effect of local spatial structure on expression's self-supervised learning, an aspect often overlooked by current graph neural networks. We demonstrated that SpaCAE could achieve effective performance on SRT data generated from multiple technologies for spatial domains identification and data denoising, making it a remarkable tool to obtain novel insights from SRT studies. [ABSTRACT FROM AUTHOR]

Cellular automata (CA) have been prevalently used for the simulation of urban land change. However, how to effectively learn the spatial-temporal dynamics of urban development from time-series data remain an important challenge for CA-based models. To address this issue, we propose a new model for the simulation of urban development based on convolutional long short-term memory (ConvLSTM) neural networks. The core of the proposed model is a sequence of vanilla ConvLSTM cells integrated with the modules of channel attention and contextual embedding. Compared with conventional CA-based models, the proposed ConvLSTM model is more advanced in that it can better leverage the open access annual urban land maps to capture simultaneously the spatial structure and the temporal dependency of historical urban development, and further predict multiple maps of annual development for subsequent years (i.e., Maps-to-Maps). The performance of the ConvLSTM model is evaluated through the case studies in China's three mega-urban regions, and ConvLSTM outperforms other state-of-the-art deep learning architectures at both the pixel level and the coarser grid level. The results also suggest the satisfactory transferability of ConvLSTM in that the model trained in one mega-urban region can be successfully re-used in others without fine tuning. [ABSTRACT FROM AUTHOR]

Purpose: Based on the construal level theory, this research study examines the interactive effect between social crowding and corporate social responsibility (CSR) statement type on consumers' purchase intention. Design/methodology/approach: The authors conducted two empirical experiments on a total of 508 subjects. Findings: There is an interactive effect between social crowding and CSR statement type on consumers' purchase intention. Specifically, in high social crowding situations, concrete CSR statements lead to consumers' higher purchase intention, while in low social crowding situations, abstract CSR statements lead to consumers' higher purchase intention. Self-construal and processing fluency play a moderating and mediating role in the mechanism. Originality/value: This research study contributes to the theoretical understanding of the interaction between social crowding and CSR statements, enriching the field of consumer behavior research on social crowding. Additionally, it offers practical insights for enterprises on how to present CSR information in crowded situations. [ABSTRACT FROM AUTHOR]

Bending deformation of a hollow cylindrical roller (HCR) was calculated by curve bending theory and slice technology. Furthermore, an elastohydrodynamic lubrication (EHL) model involving hollow rollers was established by coupling the finite line EHL model and bending deformation. Measurements of film thickness for hollow rollers were carried out by using a line-contact optical EHL test rig, and the experimental data and theoretical results agreed well with each other. For a roller with a straight-line profile, the hollow structure could reduce pressure peak at the roller ends, but the edge effect was still present. The film thickness at the ends unfortunately could not be improved by such hollow structures, unless a profile modification for the operating surface is designed. [ABSTRACT FROM AUTHOR]

Summary: It is well known that all practical control systems are subject to external disturbances. Therefore, a feedback controller should be designed so that the closed‐loop system has some desired properties such as stability, good tracking performance, at the same time, the impact of external disturbances on the performance of the closed‐loop system is attenuated to some degree. On the other hand, almost all models for real fully actuated systems, which are derived based on the physical laws, are described by a set of high order differential equations. The traditional method for controlling these fully actuated systems is to convert the high order differential equations to first order differential equations, which are called the state equations, and then to design feedback controllers by using the state‐space design methods. Such conversion causes some inconveniences. To overcome such inconveniences, a high‐order fully actuated (HOFA) design method has been proposed to control HOFA systems. The main goal of this paper is to design a weak disturbance decoupling controller for HOFA nonlinear systems to guarantee the stability and desired output tracking performance of the closed‐loop system and to attenuate the impact of disturbances. [ABSTRACT FROM AUTHOR]

Purpose: The main purpose of this paper is to change the structure of the SDP to include more fault information. Furthermore, improve the diagnostic accuracy and anti-noise performance of the bearing fault diagnosis method based on SDP. Methods: First, a multi-interval asymmetric dot pattern (MADP) is proposed by modifying the expression of SDP. Then, the improved SDP (multi-modal multi-interval asymmetric dot pattern, MMADP) is established by the MADP method fused with the multiple effective IMF components which are obtained through CEEMDAN decomposition. Finally, a bearing fault diagnosis model is established based on MMADP and convolutional neural network. Results: The effectiveness of the proposed fault diagnosis method is validated on the CWRU dataset. The results indicate that under Gaussian white noise with a signal-to-noise ratio (SNR) of above 4 dB and − 6 dB, the accuracy of the proposed fault diagnosis method reaches 100 and 93.3%, respectively. Conclusion: In this paper, a method (MADP) transforming time series signals into images is proposed, and a method for fault diagnosis of rolling bearings is formed through combination of CEEMDAN and CNN. The bearing fault diagnosis method has good anti-noise performance, and the MADP has potential value in the processing of sound signals. [ABSTRACT FROM AUTHOR]

This article discusses the use of tofacitinib, an oral Janus kinase (JAK) inhibitor, for the treatment of synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome, a rare autoinflammatory disease. Tofacitinib has shown significant improvements in pain, skin lesions, inflammation, and quality of life in patients with SAPHO syndrome. However, there is limited data on its use during pregnancy. The article presents a case report of an unintended pregnancy in a patient with SAPHO syndrome who was treated with tofacitinib. The patient had a healthy pregnancy and delivered a healthy baby after discontinuing the medication. The article suggests that further monitoring of pregnancy outcomes in tofacitinib-treated patients is needed. [Extracted from the article]

In recent years, atmospheric-pressure plasma jets have emerged as valuable tools in many application areas, including material modification, environmental remediation and biomedicine. Understanding the discharge characteristics of these plasma jets under various operating conditions is crucial for optimizing process outcomes. This paper presents a two-dimensional fluid model for numerical simulation to study the variation in electron density within an atmospheric-pressure helium plasma jet under different operating conditions. The investigated parameters include helium gas flow rate, voltage amplitude, needle-to-ring discharge gap, and relative permittivity of the dielectric tube. The results reveal that the peak electric field and electron density initially occur at the wall of the dielectric tube and subsequently shift towards the head of the propagating jet. Gas flow rate has minimal impact on the electron density throughout the plasma jet, whereas increasing the needle-to-ring discharge gap significantly decreases the average electron density within the jet. In addition, an increase in the voltage amplitude and the relative permittivity of the dielectric tube enhances the electric field within the discharge space, thereby increasing the electron density in the plasma jet. These findings underscore the importance of understanding the correlation between electron density and operating conditions to precisely control plasma jets and enhance material treatment effectiveness for specific applications. [ABSTRACT FROM AUTHOR]

Background: The co‐disease of depression and gout is becoming more common in the modern era. However, the relationship between the severity of depressive symptoms and gout prevalence and treatment rate was still unclear. Objective: This study aimed to determine the relationship between the prevalence, treatment rate of gout, and the severity of depression in the United States. Method: The cross‐sectional analysis of the 2007–2018 National Health and Nutrition Examination Survey (NHANES) for participants with depression was performed. According to their Patient Health Questionnaire‐9 (PHQ‐9) scores, participants were categorized as none, mild, moderate, moderately severe, and severe. To learn the correlation between the severity of depressive symptoms and the prevalence and treatment rate of gout using multivariate logistic regression to control for confounder interference. Results: A total of 25 022 patients were included in this study. As the severity of the depressive symptoms worsened (Mild, Moderate and Moderately severe), the risk of gout increased in non‐adjusted model and model 1,2,3 (p‐value for trend =.01 in non‐adjusted model, <.0001 in model 1, <.01 in models 2 and 3; prevalence group in Model 1, aOR1.71, 95% CI (1.40, 2.08) in the mild group, aOR1.68, 95% CI (1.19, 2.39) in the moderate group, aOR1.31,95% CI (0.82, 2.11) in the moderately severe group, aOR1.21, 95% CI (0.62, 2.38) in the severe group). However, the lower gout prevalence trend has no statistical significance after adjusting all factors in Model 4(p‐value for trend =.98). Compared with patients without depression, only a few patients received treatment, especially patients with severe depression (none, 80.1%; severe, 0.2%). The more severe the depression, the lower the treatment rate (p‐value for trend: non‐adjusted model, p <.001; model 1, p =.05; model 2, p =.02; model 3, p =.03). Conclusion: Compared with patients without depression, the patients with depression had a higher risk of gout. With the aggravation of depression, the prevalence of gout and the rate of treatment both were decreased. Patients with gout and depression need to receive multidisciplinary care after diagnosis. However, currently, treatment cannot meet the needs of the current patients. [ABSTRACT FROM AUTHOR]

The aims of the research were (i) to compare the clinical outcome of IVF using follicular-phase depot gonadotropin-releasing hormone (GnRH) agonist (depot agonist) protocol and GnRH antagonist protocol in patients with repeated IVF failure (RIF), (ii) to discover the optimal ovarian stimulation protocol for this group of low prognosis patients. 801 RIF patients with normal ovarian reserve receiving in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) were included in this retrospective study. Among them, 492 patients were treated with the depot agonist protocol, and the remaining 309 patients with the antagonist protocol. Multivariable logistic regression analysis was used to find the predictor(s) of the chance of live birth. Higher live birth rate (LBR) and clinical pregnancy rate (CPR) in fresh embryo transfer (ET) cycles were associated with the use of depot agonist compared with the antagonist protocols (44.81% vs. 27.27%, 54.64% vs. 34.93%, respectively; both p < 0.01) and depot agonist protocol was a strong predictor of live birth (OR = 2.182, 95% CI 1.355–3.514, p < 0.01). The CPR in thawed ET cycles was not significantly different between the two groups (38.12% vs. 45.26%, p > 0.05). A higher cumulative live birth rate (CLBR) was achieved in the depot agonist group (46.59% vs. 35.21%, p < 0.01). Beneficial endometrial receptivity in the depot agonist protocol contributed to a higher LBR in fresh ET cycles, rendering this protocol the preferred option in the treatment of RIF patients. [ABSTRACT FROM AUTHOR]

The matrix's dielectric constant can be reduced with little quantity of POSS because of its unique cage skeleton structure and remained air in the caves. After epoxied, epoxy polyhedral oligomeric silsesquioxane (EPPOSS) promoted its compatibility with bisphenol A cyanate ester (BADCy) and bisphenol A benzoxazine (BA-a) by a curing processing between BADCy and EPPOSS and further copolymerizing with ring opened BA-a. Consequently, two Tgs were observed in the integrated nanocomposite, attributing to the BADCy homopolymer and the BADCy and BA-a copolymer. The more quantity of EPPOSS, the lower dielectric constants of nanocomposites achieved, as well as the initial storage modulus and Tgs due to the flexible ether bonds generated by EPPOSS. With up to 15 wt.% EPPOSS, the dielectric constant decreased to 2.72 at 1 MHz. The toughness and thermal stability of the nanocomposites also enhanced through increased the crosslinking density and inorganic Si–O–Si framework of EPPOSS. [ABSTRACT FROM AUTHOR]

Low‐temperature (LT) stress threatens cucumber production globally; however, the molecular mechanisms underlying LT tolerance in cucumber remain largely unknown. Here, using a genome‐wide association study (GWAS), we found a naturally occurring single nucleotide polymorphism (SNP) in the STAYGREEN (CsSGR) coding region at the gLTT5.1 locus associated with LT tolerance. Knockout mutants of CsSGR generated by clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR‐associated nuclease 9 exhibit enhanced LT tolerance, in particularly, increased chlorophyll (Chl) content and reduced reactive oxygen species (ROS) accumulation in response to LT. Moreover, the C‐repeat Binding Factor 1 (CsCBF1) transcription factor can directly activate the expression of CsSGR. We demonstrate that the LT‐sensitive haplotype CsSGRHapA, but not the LT‐tolerant haplotype CsSGRHapG could interact with NON‐YELLOW COLORING 1 (CsNYC1) to mediate Chl degradation. Geographic distribution of the CsSGR haplotypes indicated that the CsSGRHapG was selected in cucumber accessions from high latitudes, potentially contributing to LT tolerance during cucumber cold‐adaptation in these regions. CsSGR mutants also showed enhanced tolerance to salinity, water deficit, and Pseudoperonospora cubensis, thus CsSGR is an elite target gene for breeding cucumber varieties with broad‐spectrum stress tolerance. Collectively, our findings provide new insights into LT tolerance and will ultimately facilitate cucumber molecular breeding. [ABSTRACT FROM AUTHOR]

Compelling evidence in animals and humans from a variety of approaches demonstrate that neuropeptide Y (NPY) in the brain can provide resilience to development of many stress‐elicited symptoms. Preclinical experiments demonstrated that delivery of NPY by intranasal infusion to rats shortly after single exposure to traumatic stress in the single prolonged stress (SPS) rodent model of post‐traumatic stress disorder (PTSD) can prevent development of many relevant behavioral alterations weeks later, including heightened anxiety and depressive‐like behavior. Here, we examined responses to intranasal NPY in the absence of stress to evaluate the safety profile. Rats were administered intranasal NPY (150 μg/rat) or equal volume of vehicle (distilled water), and 7 days later they were tested on the elevated plus maze (EPM) and forced swim test (FST). There was no significant difference in the number of entries or duration in the open or closed arms, or in their anxiety index. Defecation on the EPM and immobility on the FST, measures of anxiety and depressive‐like behavior respectively, were similar in both groups. To further characterize potential benefits of intranasal NPY, its effect on fear memory and extinction, important features of PTSD, were examined. Intranasal administration of NPY at the time of the traumatic stress had a profound effect on fear conditioning a week later. It prevented the SPS‐triggered impairment in the retention of extinguished behavior, both contextual and cued. The findings support the translation of non‐invasive intranasal NPY delivery to the brain for PTSD‐behaviors including impairments in sustained extinction of fear memories. [ABSTRACT FROM AUTHOR]

Traffic emissions are a major source of ambient air pollution, and exposure to these emissions has been linked to numerous adverse health effects. Our study investigated the reduction of traffic emissions in downtown Tianjin, China, and assessed its health benefits. Based on the vehicle emission inventory, The Atmospheric Dispersion Modelling System (ADMS) was adopted for simulating the dispersion of traffic-related air pollutants including primary fine particulate matter (PM2.5), and carbon monoxide (CO). The Benefits Mapping and Analysis Program (BenMAP) was then used to quantify the benefits of emission reductions with respect to cardiovascular disease and respiratory disease. We found a downward trend in PM2.5 and CO concentrations from 2015 to 2019 (PM2.5: 17.8 to 10.5μg/m3, CO: 2.3 to 1.3mg/m3). Furthermore, in line with the reduction of average annual PM2.5 and CO attributable to traffic emissions during 2016–2019 compared with 2015, the accumulative deaths from the two diseases mentioned above in these years decreased by 156 and 961 respectively. Our study constructs an integrated framework combining emission inventories, air quality modeling, and population health benefits, which can be used for further health effects of related air quality improvement. [ABSTRACT FROM AUTHOR]

Purpose: Methyltransferase like 1 (METTL1) regulates epitranscriptomes via the m7G modification in mammalian mRNA and microRNA. Systemic lupus erythematosus (SLE) is caused by abnormal immune reactivity and has diverse clinical manifestations. RNA methylation as a mechanism to regulate gene expression is widely implicated in immune regulation. However, the role of m7G in immune response of SLE has not been extensively studied.Patients and Methods: Expression of METTL1 was identified in the public dataset GSE122459 and validated in an independent cohort of SLE patients. We investigated the association between METTL1-expression and clinical manifestations of SLE. Subsequently, differentially expressed genes (DEG) that were correlated with METTL1-expression in GSE122459 were used for functional enrichment analysis. The correlation between infiltrating immune cells and METTL1, as well as candidate biomarkers identified to be correlated with either METTL1 or immune cell infiltration were assessed by single-sample GSEA. Potential mechanisms were explored with Gene ontology and KEGG pathway enrichment. Diagnostic performances of candidate biomarkers in SLE were analyzed.Results: The mRNA and protein expression of METTL1 in SLE patients were significantly decreased in both datasets. METTL1-coexpressed DEGs were enriched in several key immune-related pathways. Activated CD8 T cells, activated CD4 T cells, memory B cells and type 2 helper T cells were different between patients with high and low METTL1 expression. Further, activated CD8 T-cells, activated CD4 T-cells, memory B-cells were correlated with METTL1. The genes of LAMP3, CD83, PDCD1LG2, IGKVD3D-20, IGKV5-2, IGKV2D-30, IGLV3-19 and IGLV4-60 were identified as candidate targets that were correlated with immune cell proportion. Moreover, LAMP3, CD83, and PDCD1LG2 expression were of diagnostic value in SLE as indicated by ROC analysis.Conclusion: Our findings suggested that METTL1 and its candidate targets LAMP3, CD83, PDCD1LG2 may be used for diagnosing SLE and could be explored for developing targeted molecular therapy for SLE. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive technology and the interconnection and damping assignment passivity-based control method are combined to solve the stabilization problem for underactuated mechanical systems with uncertainties (including matched and unmatched). These uncertainties include unknown friction coefficients and unknown terms in kinetic energy and potential energy. A novel adaptive interconnection and damping assignment passivity-based control scheme is proposed and an adaptive stabilization controller is designed to make the closed-loop system locally stable. Verification is conducted on the ball and beam system. The locally asymptotic stability is demonstrated using the LaSalle's invariance principle and approximate linearization. The effectiveness of the proposed control law is verified through numerical simulations. [ABSTRACT FROM AUTHOR]

Synovitis, acne, pustulosis, hyperostosis, and osteitis (SAPHO) syndrome is a rare autoimmune inflammatory disease characterized by osteoarticular and dermatological manifestations. The most common osteoarticular manifestations involve the anterior chest wall, axial skeleton, and long bones. Cranial bone involvement is less reported in SAPHO syndrome. We herein present three cases of SAPHO syndrome with cranial bone involvement, and review the previous literature on similar manifestations. It was revealed that SAPHO syndrome could lead to cranial bone involvement, which could involve the dura mater, leading to hypertrophic pachymeningitis, but the outcome is usually good. Janus kinase inhibitors may be a potential treatment option. [ABSTRACT FROM AUTHOR]