Search

The effect of different welding heat inputs on the microstructure and mechanical properties of the simulated coarse grained heat affected zone (CGHAZ) of high-strength wind power steel with yield strength of 500 MPa has been investigated using scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). Charpy impact tests have demonstrated that there exists an optimum heat input of ∼20 kJ/cm that allows optimum impact toughness to be obtained for the CGHAZ. It was shown that this is related to the refined bainitic structure and the highest density of high-angle grain boundaries (HAGBs) with misorientation angle of more than 45°. In crystallographic visualization studies, it was shown that the weakest variant selection occurs for the bainite transformation in the optimal heat input, leading to the highest density of HAGBs with each Closed-packet group containing two or three Bain groups and showing a staggered arrangement structure. The contribution that can effectively deflect and prevent crack propagation during impact experiments has to come from the block boundary. However, it was also found that the center segregation induced by C and Mn reduces the low-temperature impact toughness of the core sample before and after simulated welding, and affects the fluctuations of impact toughness and fatigue performance of simulated CGHAZ. Mn segregation can have a genetic effect on the welding heat affected zone, inducing a lower temperature martensitic transformation, which in turn leads to a decrease in low-temperature toughness and fatigue crack arrest performance.

Abstract Background The aim of this study was to assess the microbial variations and biomarkers in the vaginal and oral environments of patients with human papillomavirus (HPV) and cervical cancer (CC) and to develop novel prediction models. Materials and methods This study included 164 samples collected from both the vaginal tract and oral subgingival plaque of 82 women. The participants were divided into four distinct groups based on their vaginal and oral samples: the control group (Z/KZ, n = 22), abortion group (AB/KAB, n = 17), HPV-infected group (HP/KHP, n = 21), and cervical cancer group (CC/KCC, n = 22). Microbiota analysis was conducted using full-length 16S rDNA gene sequencing with the PacBio platform. Results The vaginal bacterial community in the Z and AB groups exhibited a relatively simple structure predominantly dominated by Lactobacillus. However, CC group shows high abundances of anaerobic bacteria and alpha diversity. Biomarkers such as Bacteroides, Mycoplasma, Bacillus, Dialister, Porphyromonas, Anaerococcus, and Prevotella were identified as indicators of CC. Correlations were established between elevated blood C-reactive protein (CRP) levels and local/systemic inflammation, pregnancy, childbirth, and abortion, which contribute to unevenness in the vaginal microenvironment. The altered microbial diversity in the CC group was confirmed by amino acid metabolism. Oral microbial diversity exhibited an inverse pattern to that of the vaginal microbiome, indicating a unique relationship. The microbial diversity of the KCC group was significantly lower than that of the KZ group, indicating a link between oral health and cancer development. Several microbes, including Fusobacterium, Campylobacter, Capnocytophaga, Veillonella, Streptococcus, Lachnoanaerobaculum, Propionibacterium, Prevotella, Lactobacillus, and Neisseria, were identified as CC biomarkers. Moreover, periodontal pathogens were associated with blood CRP levels and oral hygiene conditions. Elevated oral microbial amino acid metabolism in the CC group was closely linked to the presence of pathogens. Positive correlations indicated a synergistic relationship between vaginal and oral bacteria. Conclusion HPV infection and CC impact both the vaginal and oral microenvironments, affecting systemic metabolism and the synergy between bacteria. This suggests that the use of oral flora markers is a potential screening tool for the diagnosis of CC.

Abstract Strain-specific probiotics can present antioxidant activity and reduce damage caused by oxidation. Streptococcus alactolyticus strain FGM (S. alactolyticus strain FGM) isolated from the chicken cecum shows potential probiotic properties which have been previously demonstrated. However, the antioxidant properties of S. alactolyticus strain FGM remain unknown. In this view, cell-free supernatant (CFS), intact cells (IC) and intracellular extracts (CFE) of strain FGM and 3 strains of Lactobacillus (LAB) were prepared, and their scavenging capacities against DPPH, hydroxyl radicals and linoleic acid peroxidation inhibitory were compared in this study. The effects of strain FGM cell-free supernatant (FCFS) on NO production, activity of SOD and GSH-Px in RAW264.7 cells and LPS-induced RAW264.7 cells were analyzed. The metabolites in the supernatant were quantitated by N300 Quantitative Metabolome. It was shown that the physicochemical characteristics of CFS to scavenge DPPH, hydroxyl radicals, and linoleic acid peroxidation inhibitory were significantly stronger than that of IC and CFE in the strain FGM (P

Chinese Artichoke (Stachys sieboldii Miq.), an indigenous vegetable in China, is renowned for its rich nutritional content and medicinal properties. With a significant cultivation history and promising prospects, this vegetable holds great potential for further development. In this study, we investigated changes in gene expression levels and metabolite content within relevant metabolic pathways during the development of Chinese Artichoke tubers. Tubers from three different periods—S1 (6 Aug), S2 (2 Sep), and S3 (1 Oct)—served as materials for the analysis. The results revealed that differentially expressed genes and differentially accumulated metabolites were predominantly enriched in pathways associated with secondary metabolite synthesis, carbohydrate metabolism, amino acid metabolism, and lipid metabolism. These pathways are known to play significant regulatory roles in the development of Chinese Artichoke tubers. Two crucial metabolic pathways identified through a comprehensive analysis of transcriptomics and metabolomics were further investigated. The genes GOLS, STS, AGAL, and INV potentially play crucial roles in stachyose accumulation. Additionally, the genes trpB (Cluster-5100.0), GOT2 (Cluster-7051.0), and TYRAAT (Cluster-4023.14777) potentially influence the aromatic amino acid content at different developmental stages. However, the regulatory mechanisms of these genes and their relationship with metabolites require further investigation. The study findings provide a theoretical foundation for understanding the key pathways that influence the growth of Chinese Artichoke tubers, metabolic mechanisms of stachyose and amino acids, verification of gene functions, and genetic enhancement of Chinese Artichoke cultivars.

The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.

Sestrin proteins, conserved family proteins which mainly induced by ROS, DNA damage, inflammation, and other injuries. Growing evidences proved sestrin proteins exert protective functions in cardiovascular diseases, chronic degenerative osteoarthritis, musculoskeletal diseases, aging and others, sestrin proteins exhibit an anti-inflammatory response, improving metabolism and other valuable character. However, there is no comprehensive and detailed summary and literature research on the intervention methods of sestrin proteins at present. As the advance of research during last several years, exercise training and other interventions are considered to be the potential methods to up-regulate expression level of protein. In view of the physiological function of this protein, a review of the main studies on regulating the expression level of this protein can provide a novel approach for the clinical treatment and scientific research. In present study, all related researches about interventions and potential mechanisms were reviewed and the mainstream methodologies were described.

Abstract The role of m6A modification in the regulation of the immune microenvironment (IME) of ischemic stroke (IS) is barely known. Thus, we aim to investigate the impact of m6A modification on the IME of IS and its diagnostic value in IS. We comprehensively assessed the m6A modification patterns, the relationship between these modification patterns and the characteristics of the IME. The m6A modification patterns of individual IS sample were quantified by m6Ascore. The performance of m6A phenotype-related genes as potential biomarkers was evaluated by the area under the receiver operating characteristic curve. Experimental validation was also performed by qRT-PCR. Six dysregulated m6A regulators were identified and a classification model consisting of four key m6A regulators (METLL3, RBMX, RBM15B, YTDHF3) could distinguish IS and healthy control samples well. METTL3 and YTHDF3 are closely related to circulating neutrophil abundance. Two distinct m6A modification patterns were determined which differed in immunocyte abundance. We also identified six m6A phenotype-related genes (APOBEC3A, PTMA, FCGR3A, LOC440926, LOC649946, and FTH1L11), and further explored their biological function. Among them, APOBEC3A, FCGR3A, and FTH1L11 were positively associated with neutrophil abundance. APOBEC3A and FCGR3A were stable diagnostic m6A-associated genes in both the discovery and validation cohorts. This study reveals that m6A modification plays a non-negligible role in the formation of a diversified and complex IME in IS. The m6A phenotype-related genes could be diagnostic biomarkers of IS.

BackgroundAlthough epidemiological evidence implies a link between exposure to particulate matter (PM) and Alzheimer’s disease (AD), establishing causality remains a complex endeavor. In the present study, we used Mendelian randomization (MR) as a robust analytical approach to explore the potential causal relationship between PM exposure and AD risk. We also explored the potential associations between PM exposure and other neurodegenerative diseases.MethodsDrawing on extensive genome-wide association studies related to PM exposure, we identified the instrumental variables linked to individual susceptibility to PM. Using summary statistics from five distinct neurodegenerative diseases, we conducted two-sample MR analyses to gauge the causal impact of PM on the risk of developing these diseases. Sensitivity analyses were undertaken to evaluate the robustness of our findings. Additionally, we executed multivariable MR (MVMR) to validate the significant causal associations identified in the two-sample MR analyses, by adjusting for potential confounding risk factors.ResultsOur MR analysis identified a notable association between genetically predicted PM2.5 (PM with a diameter of 2.5 μm or less) exposure and an elevated risk of AD (odds ratio, 2.160; 95% confidence interval, 1.481 to 3.149; p

Wetlands provide vital ecological services for both humans and environment, necessitating continuous, refined and up-to-date mapping of wetlands for conservation and management. In this study, we developed an automated and refined wetland mapping framework integrating training sample migration method, supervised machine learning and knowledge-driven rules using Google Earth Engine (GEE) platform and open-source geospatial tools. We applied the framework to temporally dense Sentinel-1/2 imagery to produce annual refined wetland maps of the Dongting Lake Wetland (DLW) during 2015–2021. First, the continuous change detection (CCD) algorithm was utilized to migrate stable training samples. Then, annual 10 m preliminary land cover maps with 9 classes were produced using random forest algorithm and migrated samples. Ultimately, annual 10 m refined wetland maps were generated based on preliminary land cover maps via knowledge-driven rules from geometric features and available water-related inventories, with Overall Accuracy (OA) ranging from 81.82% (2015) to 93.84% (2020) and Kappa Coefficient (KC) between 0.73 (2015) and 0.91 (2020), demonstrating satisfactory performance and substantial potential for accurate, timely and type-refined wetland mapping. Our methodological framework allows rapid and accurate monitoring of wetland dynamics and could provide valuable information and methodological support for monitoring, conservation and sustainable development of wetland ecosystem.

The PYL protein family are crucial sensors of the core signals of abscisic acid (ABA) and significantly influence the plant’s response to ABA-mediated abiotic stresses as well as its growth and development. However, research on the role of the MhPYL4 gene in iron (Fe) deficiency in apple trees is limited. Studies have shown that the MhPYL4 gene, when exposed to Fe-deficiency stress, exhibits more rapid transcriptional upregulation than other genes’ quickly elevated transcription. However, the precise mechanism by which it alleviates this stress remains unclear. The MhPYL4 gene (ID:103432868), isolated from Malus halliana, was analyzed to elucidate its function. Arabidopsis plants engineered to overexpress the MhPYL4 gene exhibited increased leaf chlorosis and slower growth in response to Fe stress compared to the unmodified controls. The transgenic plants also exhibited elevated levels of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) activities, as well as ferric chelate reductase (FCR) activities. Levels of malondialdehyde (MDA), hydrogen peroxide (H2O2), and superoxide anion (O2−) were increased. In addition, these transgenic plants had lower concentrations of proline (Pro) and Fe2+, which indicated that their stress tolerance was reduced. Similarly, the overexpression of MhPYL4 in apple calli resulted in inhibited growth and increased susceptibility under Fe stress conditions. Physiological evaluations indicated that the overexpression of MhPYL4 in Arabidopsis reduced its Fe stress tolerance by inhibiting chlorophyll synthesis. In apple calli, it altered pH levels, antioxidant enzyme activity, and Fe-reducing capabilities under the same stress conditions. In summary, the elevated expression of the MhPYL4 gene reduced the tolerance of both Arabidopsis and apple calli to Fe stress, suggesting that MhPYL4 acts as a negative regulator in response to Fe deficiency.

In order to study the effects of soda residue content, particle size, moisture content, and curing age on the unconfined compressive strength (UCS) of soda residue cement lime soil (SRCLS), a 4-factor, 4-level orthogonal experimental design was employed in this study. Different conditions of SRCLS UCS and their impacts were tested and analyzed. The internal microstructure and hydration products of SRCLS were studied using SEM and XRD to explore the strengthening mechanism of SR in SRCLS. The results indicate that as the soda residue content gradually increased, SRCLS UCS initially increased and then decreased, with a maximum increase of up to 67%. With increasing soda residue particle size and moisture content, the UCS of SRCLS gradually decreased. The optimized mix ratio was determined to be soda residue:cement:lime:soil = 3%:3%:6%:100%, with the soda residue dried naturally and an ideal particle size of 0.15 mm. The factors influencing the unconfined compressive strength (UCS) of SRCLS, in order of importance, are curing age, soda residue content, moisture content, and particle size of SR. Among these, curing age and soda residue content have a significant impact on the UCS. An adequate amount of SR can act as a fine aggregate filler, replace lime, promote cement hydration, and enhance chloride ion binding. This improves the grading of SRCLS materials and facilitates the formation of cementitious products from AFm, AFt, and Friedel’s salt, resulting in denser and stronger SRCLS materials. The research findings provide a reference for the mix design of SRCLS and the large-scale utilization of waste soda residue.

In the Yellow River Basin, the lack of water supplies is now the largest obstacle to both environmental preservation and socioeconomic growth. The fact that inhabitants’ diets may be altered to save water, however, is gravely underappreciated. Based on the water footprint theory, we examined the water footprint structure and the dynamic evolution process of food consumption in the Yellow River Basin from 1999 to 2019 in this study. The key factors affecting the water footprint of food consumption were then identified by using the STIRPAT model modified by the partial least-squares method. The findings indicate the following: (a) There had been an increase in the Yellow River Basin’s overall water footprint of food consumption from 1999 to 2019, with the midstream region having the biggest water footprint of food consumption (410.8 billion m3) and the highest percentage increase (86%). (b) In the Yellow River Basin, the water footprint of meat eating was 36% while the water footprint of grain consumption was 30%. The lower Yellow River had the greatest water impact per person due to food consumption. (c) Urbanization rate played a promoting role in the upper Yellow River provinces, and GDP and irrigated area played a promoting role in the lower Yellow River provinces. The results of this study are expected to provide scientific support for the decision-making of healthy and water-saving diets in the Yellow River basin.

Abstract Ischemic stroke is a neurological disorder caused by vascular stenosis or occlusion, accounting for approximately 87% of strokes. Clinically, the most effective therapy for ischemic stroke is vascular recanalization, which aims to rescue neurons undergoing ischemic insults. Although reperfusion therapy is the most effective treatment for ischemic stroke, it still has limited benefits for many patients, and ischemia-reperfusion (I/R) injury is a widely recognized cause of poor prognosis. Here, we aim to investigate the mechanism of protein phosphatase Mg2+/Mn2+ dependent 1 K (PPM1K) mediates metabolic disorder of branched-chain amino acids (BCAA) by promoting fatty acid oxidation led to ferroptosis after cerebral I/R injury. We established the I/R model in mice and used BT2, a highly specific BCAA dehydrogenase (BCKD) kinase inhibitor to promote BCAA metabolism. It was further verified by lentivirus knocking down PPM1K in neurons. We found that BCAA levels were elevated after I/R injury due to dysfunctional oxidative degradation caused by phosphorylated BCKD E1α subunit (BCKDHA). Additionally, the level of phosphorylated BCKDHA was determined by decreased PPM1K in neurons. We next demonstrated that BCAA could induce oxidative stress, lipid peroxidation, and ferroptosis in primary cultured cortical neurons in vitro. Our results further showed that BT2 could reduce neuronal ferroptosis by enhancing BCAA oxidation through inhibition of BCKDHA phosphorylation. We further found that defective BCAA catabolism could induce neuronal ferroptosis by PPM1K knockdown. Furthermore, BT2 was found to alleviate neurological behavior disorders after I/R injury in mice, and the effect was similar to ferroptosis inhibitor ferrostatin-1. Our findings reveal a novel role of BCAA in neuronal ferroptosis after cerebral ischemia and provide a new potential target for the treatment of ischemic stroke.

The antioxidant properties of butterfly pea flower (BF), which is rich in natural anthocyanins, have garnered significant attention. The impact of digestion and metabolism on BF extracts and evaluate their subsequent antioxidant activities in vivo were explored in the present study. After in vitro digestion, 42.03 ± 2.74% of total anthocyanins from BF extracts remained, indicating a negative influence of the digestion process on the bioaccessibility of phenolic compounds derived from BF. Furthermore, UPLC-LTQ-Orbitrap-MS2 analysis identified a total of four prototypes and twenty-seven metabolites in rat plasma or urine samples following the intake of BF extracts. The kinetics of key metabolites including delphinidin 3-glucoside (D3G), cyanidin-3-glucoside (C3G), and 4-hydroxybenzoic acid were subsequently determined in blood, and the Cmax values were 69.034 ± 8.05 nM and 51.65 ± 3.205 nM. These key metabolites derived from BF anthocyanins, including C3G and D3G, and flavonoid quercetin exhibited main antioxidant attributes that improved the plasmic and hepatic activities of various antioxidant enzymes and the total antioxidant capacity (T-AOC) and malondialdehyde (MDA) in a D-galactose-induced rat model. These findings provide insights into the bioaccessibility and bioavailability of bioactive constitutes derived from BF extracts, which are crucial for determining the actual efficacy of BF as well as developing functional foods based on BF.

The fatigue behavior of a high-strength bearing steel tempered under three different temperatures was investigated with ultrasonic frequency and conventional frequency loading. Three kinds of specimens with various yield strengths exhibited obvious higher fatigue strengths under ultrasonic frequency loading. Then, a 2D crystal plasticity finite element method was adopted to simulate the local stress distribution under different applied loads and loading frequencies. Simulations showed that the maximum residual local stress was much smaller under ultrasonic frequency loading in contrast to that under conventional frequency at the same applied load. It was also revealed that the maximum local stress increases with the applied load under both loading frequencies. The accumulated plastic strain was adopted as a fatigue indicator parameter to characterize the frequency effect, which was several orders smaller than that obtained under conventional loading frequencies when the applied load was fixed. The increment of accumulated plastic strain and the load stress amplitude exhibited a linear relationship in the double logarithmic coordinate system, and an improved fatigue life prediction model was established.

Change detection is crucial for evaluating land use, land cover changes, and sustainable development, constituting a significant component of Earth observation tasks. The difficulty in extracting features from high-resolution images, coupled with the complexity of image content, poses challenges for traditional change detection algorithms in terms of accuracy and applicability. The recent emergence of deep learning methods has led to substantial progress in the field of change detection. However, existing frameworks often involve the simplistic integration of bi-temporal features in specific areas, lacking the fusion of temporal information and semantic details in the images. In this paper, we propose an attention-guided multi-scale fusion network (AMFNet), which effectively integrates bi-temporal image features and diverse semantics at both the encoding and decoding stages. AMFNet utilizes a unique attention-guided mechanism to dynamically adjust feature fusion, enhancing adaptability and accuracy in change detection tasks. Our method intelligently incorporates temporal information into the deep learning model, considering the temporal dependency inherent in these tasks. We decode based on an interactive feature map, which improves the model’s understanding of evolving patterns over time. Additionally, we introduce multi-level supervised training to facilitate the learning of fused features across multiple scales. In comparison with different algorithms, our proposed method achieves F1 values of 0.9079, 0.8225, and 0.8809 in the LEVIR-CD, GZ-CD, and SYSU-CD datasets, respectively. Our model outperforms the SOTA model, SAGNet, by 0.69% in terms of F1 and 1.15% in terms of IoU on the LEVIR-CD dataset, by 2.8% in terms of F1 and 1.79% in terms of IoU on the GZ-CD dataset, and by 0.54% in terms of F1 and 0.38% in terms of IoU on the SYSU-CD dataset. The method proposed in this study can be applied to various complex scenarios, establishing a change detection method with strong model generalization capabilities.

As the second batch of international wetland cities, Wuhan and Nanchang, both provincial capital cities in China, have abundant wetland resources. An important sign of achievement of protecting the urban wetland areas is the international wetland city designation. Understanding the growth and changes of wetlands in international wetland cities is necessary for wetland protection and management. Thus, it is crucial to conduct proper wetland mapping in these international wetland cities. By studying wetland cities, sustainable planning can be provided to promote the coordinated development of wetlands and cities. In this research, Google Earth Engine and random forest machine learning were used. According to the “Data-Information-Knowledge-Wisdom” research framework, we carried out mapping of diverse wetlands in Wuhan and Nanchang with a resolution of 10 m in 2015 and 2020. Then, using the findings of wetland mapping, we examined changes in the wetland landscapes of the two cities. Finally, this study examined changes in international wetland city indicators over this time frame. The research results are as follows. 1) Our wetland mapping results in 2015 and 2020 achieved good accuracy, with an overall accuracy of over 0.90 and a kappa coefficient of over 0.85. 2) The total wetland area in both cities increased. Nanchang grew by 91.11 km2, whereas Wuhan grew by 290.68 km2. Most restored wetland areas were far from urban construction areas. In the two cities, the fragmentation of wetlands decreased, the diversity of wetlands increased, and the growth rate of wetlands was high. 3) Wetland rates rose from 17.79% to 19.07% in Nanchang and from 19.74% to 23.12% in Wuhan, according to mapping results between 2015 and 2020. The wetland protection rate in Nanchang remained unchanged, but the wetland protection rate in Wuhan decreased. Wuhan needs to strengthen the protection of increased wetlands. In addition, the study found that most of the increased areas of wetlands were previously cultivated land. The international wetland mapping framework of this study can be easily implemented in other regions of the world.

Persistent calyx affects the fruit quality of the Korla fragrant pear including increasing fruit hardness. In order to reduce fruit hardness and improve fruit quality, in this study, we used the Korla fragrant pear which has persistent calyx. Korla fragrant pear fruit at different development stages were treated with foliar fertilizers of 101 and calcium–magnesium (Ca–Mg) solutions, and the hardness and pectase, cellulose, lipoxygenase, and amylase activities of persistent calyx fruit were determined and analyzed. We found that the fruit hardness of two foliar fertilizers increased compared with the control after treatment. The fruit hardness of calcium–magnesium foliar fertilizer and 101 foliar fertilizer treatments were increased by 11.7% and 6.8% compared with the control, respectively. Furthermore, the activities of cellulase, pectinase, and lipoxygenase were increased by 30%, 12.7%, and 42% after treatment with calcium–magnesium foliar fertilizer, respectively. The 101 foliar fertilizer inhibited the contents of cellulose and starch. In summary, the internal quality of Korla fragrant pear fruit treated with calcium–magnesium foliar fertilizer was better than 101 foliar fertilizer. It was confirmed that calcium and magnesium foliar fertilizer had a good control effect on the hardness of Korla fragrant pear persistent calyx fruit, and its fruit quality was also improved. This study has great application value in production practice.

This article uses scanning electron microscopy (SEM) and electron back-scattering diffraction (EBSD) to study the effect of C and Mn segregation on the microstructure and mechanical properties of high-strength steel with 20 mm thickness used for wind power before and after simulated welding. A Gleeble-3500 (GTC, Dynamic Systems Inc., Poestenkill, NY, USA) was used to study the microstructure evolution of the simulated coarse-grained heat-affected zone (CGHAZ) of experimental steel under different welding heat inputs (10, 14, 20, 30 and 50 kJ/cm) and its relationship with low-temperature impact toughness (−60 °C). The results indicate that alloy element segregation, especially Mn segregation, significantly affects the impact toughness scatter of the steel matrix, as it induces the formation of low-temperature martensite or hard phase, such as M/A (martensite/austenite) constituent. In addition, segregation also reduces the low-temperature impact toughness of the simulated welding samples and increases the fluctuation range. For high-strength steel with yield strength higher than 460 MPa used for wind power generation, there is an optimal welding heat input (~20 kJ/cm), which enables the simulated coarse-grained heat-affected zone (CGHAZ) to obtain the highest impact toughness due to the formation of lath bainite (LB) and the finest crystallographic block units. Excessive or insufficient heat input can induce the formation of coarse granular bainite (GB) or lath martensite (LM), leading to a larger size of crystallographic block units, reducing the hindering effect of brittle crack propagation and deteriorating low-temperature impact toughness.

Abstract Introduction Sleep abnormalities are highly correlated with neurodevelopmental disorders, such as intellectual disability, attention deficit hyperactivity disorder, and autism spectrum disorders (ASD). The severity of behavioral abnormalities is correlated with the presence of sleep abnormalities. Based on previous research, we investigated that Ctnnd2 gene deletion in mice lead to ASD‐like behaviors and cognitive defects. Given the importance of sleep in individuals with ASD, this study aimed to determine the effects of chronic sleep restriction (SR) on wild‐type (WT) mice and on Ctnnd2 deletion‐induced, neurologically related phenotypes in mice. Method WT and Ctnnd2 knockout (KO) mice were both subjected to manual SR (5 h per day) for 21 consecutively days separately, then we compared neurologically related phenotypes of WT mice, WT mice subjected to SR, KO mice, and KO mice subjected to SR using a three‐chamber assay, direct social interaction test, open‐field test, Morris water maze, Golgi staining, and Western blotting. Results The effects of SR on WT and KO mice were different. After SR, social ability and cognition were impaired in both WT and KO mice. Repetitive behaviors were increased, and exploration abilities were decreased in KO mice but not in WT mice. Moreover, SR reduced the density and area of mushroom‐type dendritic spines in WT rather than KO mice. Finally, the PI3K/Akt‐mTOR pathway was found to be involved in the effects induced by SR‐impaired phenotypes in WT and KO mice. Conclusion Overall, results of the present study may have implications for the role of disrupted sleep in patients with CTNND2 gene‐related autism and the evolution of neurodevelopmental disorders.

Urban wetlands play an important role in sustainable urban development. A wetland city recognized by the Ramsar Convention is a city with a remarkable ecological performance of urban wetlands and can provide an example for urban wetland protection. Therefore identifying the detailed characteristics of wetlands is of great value to the conservation of urban wetlands. However, there is no detailed wetland type extraction for wetland cities using multisource remote sensing data. This paper proposes a framework for fine- urban wetland extraction with multisource and multiperiod remote sensing data, which mainly includes Sentinel 1/2 and Landsat 8 data, and obtains the detailed wetland type data containing 14 wetland categories at a 10-m resolution. The classification methods of random forests were used to extract land cover types, and knowledge rules were used to classify detailed wetland types. The wetland cities, Yinchuan, and Haikou, located in southern and northern China, respectively, were chosen as case studies. The results indicate that the overall accuracy and wetland accuracy of the two cities in 2015 and 2020 were greater than 88% and 87%, respectively. The detailed wetland mapping results were more accurate and had a high resolution, and wetland categories were more diverse compared with other wetland-related products. According to the classification results, the wetland area in Haikou was 326.86 km2 (13.43%) in 2015 and 308.58 km2 (12.66%) in 2020. The wetland area in Yinchuan was 80.39 km2 (4.46%) in 2015 and 74.15 km2 (4.12%) in 2020. The fine urban wetland classification framework we propose and the detailed wetland results could serve for the creation of wetland cities and support the protection and rational use of urban wetlands.

Abstract Solar radiation pressure (SRP) is an extremely critical perturbative force that affects the GNSS satellites’ precise orbit determination (POD). Its imperfect modelling is one of the main error sources of POD, whose magnitude is even to10−9 m/s2. The shadow factor (i.e., eclipse factor) is one crucial parameter of SRP, generally estimated by the cylindrical model, the conical model, or shadow models considering the Earth’s oblateness and the atmospheric effect, such as the Perspective Projection Method atmosphere (PPMatm) model and Solar radiation pressure with Oblateness and Lower Atmospheric Absorption, Refraction, and Scattering Curve Fit (SOLAARS-CF) model. This paper applies the former four shadow models to determine the corresponding precise orbit using BeiDou satellites’ ground-based observation, and then compared and assessed the orbit accuracy through Satellite Laser Ranging (SLR) validation and Inter-Satellite Link (ISL) check. The results show that the PPMatm model’s accuracy is equivalent to the SOLAARS-CF model. Compared with the conical shadow model, SLR validations show the orbit accuracy from the PPMatm and SOLAARS-CF model can be generally improved by 2–10 mm; ISL range check shows that the Root Mean Square (RMS) can be decreased by 2–7 mm. These results show that the shadow model in GNSS POD should fully consider the Earth’s oblateness and the atmospheric effect, especially for the perturbative acceleration higher than 10–10 m/s2. Graphical Abstract

BackgroundContrast-enhanced high-resolution magnetic resonance imaging (CE-HR-MRI) is a useful imaging modality to assess vulnerable plaques in intracranial atherosclerotic stenosis (ICAS) patients. We studied the relationship between the fibrinogen-to-albumin ratio (FAR) and plaque enhancement in patients with ICAS.MethodsWe retrospectively enrolled consecutive ICAS patients who had undergone CE-HR-MRI. The degree of plaque enhancement on CE-HR-MRI was evaluated both qualitatively and quantitatively. Enrolled patients were classified into no enhancement, mild enhancement, and obvious enhancement groups. An independent association of the FAR with plaque enhancement was identified by multivariate logistic regression and receiver operating characteristic (ROC) curve analyses.ResultsOf the 69 enrolled patients, 40 (58%) were classified into the no/mild enhancement group, and 29 (42%) into the obvious enhancement group. The obvious enhancement group had a significantly higher FAR than the no/mild enhancement group (7.36 vs. 6.05, p = 0.001). After adjusting for potential confounders, the FAR was still significantly independently associated with obvious plaque enhancement in multiple regression analysis (odds ratio: 1.399, 95% confidence interval [CI]: 1.080–1.813; p = 0.011). ROC curve analysis revealed that FAR >6.37 predicted obvious plaque enhancement with 75.86% sensitivity and 67.50% specificity (area under the ROC curve = 0.726, 95% CI: 0.606–0.827, p

Wetlands have suffered from considerable degradation due to anthropogenic and natural disturbances in recent decades. Although some advancements have been made, effective methods that can produce large-scale wetland maps with detailed categories are still lacking due to the diversity and complexity of wetland ecosystems. To address this issue, we developed a novel algorithm for detailed wetland types classification integrating k-fold random forest and hierarchical decision tree, and so named two-step classification algorithm. Firstly, the phenology-based features were composited based on time series Sentinel-1/2 images, and the k-fold random forest was used to extract five rough wetland types in Google Earth Engine platform. Secondly, the hierarchical decision tree designed based on geometric features was used to separate the rough wetland types into fourteen detailed types. Application of the two-step classification method in Northern, Central and Southern Asia (NCSA) resulted in a continental-scale wetland map with an overall accuracy of 90.0 ± 0.5%. Wetland types, including inland marsh, lake, river, coastal swamp, estuarine water, lagoon, shallow marine water, reservoir, canal/channel and agricultural pond, had good accuracy with both UA and PA over 77%. The remaining wetland types had moderate accuracy, with both UA and PA over 58%. As we calculated, total wetland areas of NCSA were 1,375,489.27 km2. Among the fourteen wetland categories, the inland marsh had the largest area (544,584.38 km2) and was primarily distributed in subarctic and humid continental climates, while the canal/channel had the smallest area (1,651.57 km2) and was primarily scattered in desert, semiarid and humid subtropical climates. The lake and floodplain shared generally large areas with value of 392,413.55 km2 and 173,255.71 km2 respectively, which were typically distributed across desert and semiarid climates. This study successfully mapped continental-scale wetlands with detailed categories at a 10-m spatial resolution, which can provide valuable information for the management of wetland ecosystems and facilitate the implementation of wetland-related sustainable development goals.

The aim of this study was to investigate the inhibitory effects of Cordyceps militaris solid medium extract (CME) and cordycepin (COR) on LTA-induced inflammation in MH-S cells and their mechanisms of action. In this study, the establishment of an LTA-induced MH-S inflammation model was determined, the CCK-8 method was used to determine the safe concentration range for a drug for COR and CME, the optimal concentration of COR and CME to exert anti-inflammatory effects was further selected, and the expression of inflammatory factors of TNF-α, IL-1β, IL-18, and IL-6 was detected using ELISA. The relative expression of TNF-α, IL-1β, IL-18, IL-6, IL-10, TLR2 and MyD88 mRNA was detected using RT-PCR, and the IL-1β, IL-18, TLR2, MyD88, NF-κB p-p65, NLRP3, pro-caspase-1, Caspase-1 and ASC protein expression in the cells were detected using Western blot; immunofluorescence assay detected the expression of Caspase-1 in MH-S cells. The results revealed that both CME and COR inhibited the levels of IL-1β, IL-18, IL-6, and TNF-α in the supernatants of LTA-induced MH-S cells and the mRNA expression levels of IL-1β, IL-18, IL-6, TNF-α, TLR2 and MyD88, down-regulated the LTA-induced IL-1β, IL-18, TLR2 in MH-S cells, MyD88, NF-κB p-p65/p65, NLRP3, ASC, pro-caspase-1, and caspase-1 protein expression levels, and inhibited LTA-induced caspase-1 activation in MH-S cells. In conclusion, CME can play a therapeutic role in LTA-induced inflammation in MH-S cells via TLR2/NF-κB/NLRP3, and may serve as a potential drug for bacterial pneumonia caused by Gram-positive bacteria.

Abstract Autophagy has been demonstrated to play important roles in the infection and pathogenesis of many viruses. We previously found that porcine parvovirus (PPV) infection can induce autophagy in porcine placental trophoblast cells (PTCs), but its underlying mechanism has not yet been fully revealed. In this study, we showed that PPV infection inhibited the activation of mTORC1 and promoted the expression of Beclin 1 and LC3II in PTCs. Treatment with a mTOR activator inhibited the expression of Beclin 1 and LC3II, as well as autophagy formation, and reduced viral replication in PPV-infected PTCs. Furthermore, we found that inhibition of AMPK expression, but not the inhibition of PI3K/Akt, p53, or MAPK/ERK1/2 pathway activation, can significantly increase mTOR phosphorylation in PPV-infected PTCs. Then, we found that the regulation of mTOR phosphorylation by AMPK was mediated by Raptor. AMPK expression knockout inhibited the activation of Raptor, decreased the expression of Beclin 1 and LC3II, suppressed the formation of autophagosomes, and reduced viral replication during PPV infection. Together, our results showed that PPV infection induces autophagy to promote viral replication by inhibiting the activation of mTORC1 through activation of the AMPK/Raptor pathway. These findings provide information to understand the molecular mechanisms of PPV-induced autophagy.

Abstract Functioning and quality of life (QOL) are typical outcomes assessed in children and adolescents with major depressive disorder (MDD); however, meta-analytical evidence remains scarce. The aim of this meta-analysis was to assess functioning and QOL antidepressant outcomes in this population. Eight electronic databases (PubMed, Cochrane Library, Web of Science, Embase, CINAHL, PsycINFO, LILACS, and ProQuest Dissertation Abstracts) were searched for double-blind randomized controlled trials (RCTs) up to July 31, 2020. RCTs that compared antidepressants with placebo for treating functioning and QOL in children and adolescents with MDD were included. Primary outcomes were mean change scores of functioning and QOL scales from baseline to post-treatment. Subgroup and sensitivity analyses were conducted to examine whether results were affected by moderator variables (e.g., medication type, age, sample size, and treatment duration). From 7284 publications, we included 17 RCTs (all 17 assessed functioning and 4 assessed QOL outcomes) including 2537 participants. Antidepressants showed significant positive effects on functioning (standardized mean difference [SMD] = 0.17, 95% confidence interval [CI] = 0.09–0.25, p

ObjectivesTo identify craniofacial and upper airway morphological characteristics associated with the presence and severity of obstructive sleep apnea (OSA) in children.MethodsThis study consisted of 82 OSA children and 77 controls (age 5–10 years). All subjects underwent cephalograms and were divided into a 5–7 age group and an 8–10 age group. Cephalometric variables were compared between OSA children and controls, and hierarchical regression analysis was performed to examine the relationship between cephalometric variables and OSA severity [expressed by the obstructive apnea–hypopnea index (OAHI)] in different age groups.ResultsIncreased A/N ratio, narrowed posterior airway space, decreased SNA and SNB angles, and shortened ramus height were observed among OSA children in different age groups. In the 5–7 age group, the A/N ratio and a lower gonial angle explained 40.0% and 14.7% of the variance in the OAHI, respectively. In the 8–10 age group, the BMI z-score and A/N ratio explained 25.2% and 6.6% of the variance in the OAHI, followed by a lower gonial angle and the hyoid-retrognathion distance (19.1% in total).ConclusionsAdenoid hypertrophy was a major factor associated with OSA in preschool children, whereas obesity replaced adenoid hypertrophy as the main contributor to OSA in late childhood. Several craniofacial skeletal variables such as the SNB angle, ramus height, lower gonial angle, and hyoid position are also associated with the presence and/or severity of OSA, which could be used to help recognize children at a higher risk for OSA.

BackgroundHearing loss (HL) is one of the main medical complications for Turner Syndrome (TS) patients, with an earlier presentation and higher incidence than normal women. However, the etiology of HL in TS is unclear. The aim of this study was to investigate the hearing status of TS patients in China and the influencing factors, so as to provide a theoretical basis for early intervention treatment for TS patients with HL.MethodsIn total 46 female patients aged 14–32 diagnosed with TS received tympanic membrane and audiological examinations, including pure tone audiometry and tympanometry. In addition, the effects of karyotype, sex hormone levels, thyroid function, insulin, blood lipids, bone mineral density, age and other factors on hearing levels were analyzed, and the possible risk factors associated with HL in TS patients were explored.ResultsIn 9 patients (19.6%) had HL, including 1 (2.2%) with mild conductive hearing loss, 5 (10.9%) with mild sensorineural hearing loss, 3 (6.5%) with moderate sensorineural hearing loss. TS is often associated with age-related mid-frequency and high-frequency HL, and the incidence of HL increases with age. Compared with other karyotypes, patients with 45, X haplotype have an increased risk of mid-frequency HL.ConclusionsTherefore, karyotype may be a predictor of hearing problems in TS.

Wearable devices have been used in the treatment and rehabilitation of ankle injuries. This article systematically reviewed the trials that summarize and evaluate the effectiveness of rehabilitation treatment after an ankle injury. Three databases, PubMed (1974–2021), Embase, and Web of Science (1950–2021), were searched. The intervention was any wearable device, and the outcome measures were Activities Scale for Kids performance (ASKp), Foot and Ankle Outcome Score (FAOS), American Orthopaedic Foot and Ankle Society (AOFAS), Olerud-Molander Ankle Score (OMAS), and Circumference as measured by any validated outcome measure. Two independent authors evaluated the studies with the Cochrane risk-of-bias tool. Four papers were included, involving 476 participants, with a mean age of 29.3 ​± ​6.7 years. The mean duration of wearable devices was 3.83 weeks, and the mean length of training was 3.75 weeks. Wearable devices achieved better results compared with control on the functional performance (standardized mean difference [SMD] 0.66; 95% confidence interval [CI] 0.29 to 1.04; I2 ​= ​76%; P ​

Because of the open property of information sharing in integrated sensing and communication, it is inevitable to face security problems such as user information being tampered, eavesdropped, and copied. Radio frequency (RF) individual identification technology is an important means to solve its security problems at present. Whether using machine learning methods or current deep learning-based target fingerprint identification, its performance is based on how well the radio frequency features (RFF) are extracted. Since the received signal is affected by various factors, we believe that we should first find the intrinsic features that can describe the properties of the target, which is the key to enhance the RF fingerprint recognition. In this paper, we try to analyze the intrinsic characteristics of the components that influenced the signal by the transmitting source and derive a mathematical formula to describe the RF characteristics. We propose a method using dynamic wavelet transform and wavelet spectrum (DWTWS) to enhance RFF features. The performance of the proposed method was evaluated by experimental data. Using a support vector machine classifier, the recognition accuracy is 99.6% for 10 individuals at a signal-to-noise ratio (SNR) of 10 dB. In comparison with the dual-tree complex wavelet transform (DT-CWT) feature extraction method and the wavelet scattering transform method, the DWTWS method has increased the interclass distance of different individuals and enhanced the recognition accuracy. The DWTWS method is superior at low SNR, with performance improvements of 53.1% and 10.7% at 0 dB.

Background: Recently, increasing evidence has implicated methylenetetrahydrofolate reductase (MTHFR) gene mutation as a risk factor for ischemic stroke (IS) in the general population. However, studies have been inconclusive and lack evidence on specific populations. We aim to determine whether the rs1801133 (NC_000001.11 (MTHFR):g. 677C>T (p.Ala222Val) variant, we termed as MTHFR rs1801133 (677 C>T), is linked to an increased risk of IS in different age groups and ancestry groups.Methods: The literature relevant to our study was found by searching the PubMed, Cochrane Library, Web of Science, EMBASE, and CNKI databases. A random effect model analysis was used to calculate the pooled odds ratio (OR) and 95% confidence interval (CI) to evaluate any possible association. We conducted a subgroup analysis based on the age and ancestry groups of the included populations.Results: As of March 2022, 1,925 citations had been identified in electronic databases, of which 96 studies involving 34,814 subjects met our eligibility criteria. A strong link was found between IS and the MTHFR gene rs1801133 (677C>T) polymorphism in all genetic models [dominant genetic model (OR = 1.47; 95%CI = 1.33–1.61; p < 0.001), recessive genetic model (OR = 1.52; 95%CI = 1.36–1.71; p < 0.001), heterozygous model (OR = 1.36; 95%CI = 1.24–1.48; p < 0.001), homozygous model (OR = 1.82; 95%CI = 1.58–2.11; p < 0.001), and T allelic genetic model (OR = 1.37; 95%CI = 1.27–1.48; p < 0.001)]. Further subgroup analyses indicated that the MTHFR rs1801133 (677C>T) variant may increase the risk of IS in Asian, Hispanic, or Latin population, middle-aged, and elderly populations (p < 0.001).Conclusion: Our results implied that mutation of the T allele of MTHFR rs1801133 (677C>T) could be a risk factor for IS. A significant association was found among Asian, Hispanic, or Latin population, middle-aged, and elderly people.

Wetland carbon storage plays an essential role in the global carbon cycle. However, in recent decades, intensive human activities and rapid urbanization have reduced wetland C stocks in the Guangdong–Hong Kong–Macau Greater Bay Area (GBA). Long-term assessment of carbon storage in the wetland ecosystems of the GBA is needed for promoting regional sustainable development. Therefore, we proposed a framework integrating the integrated valuation of ecosystem services and tradeoffs (InVEST) model and water inundation frequency, which was retrieved via multiple index water detection rule based on Google Earth Engine platform, to estimate yearly carbon storage in wetlands across the GBA at a 30-m spatial resolution during 1995–2020. The incorporation of water inundation frequency in estimating carbon storage in wetlands presents features of long time series and higher temporal frequency. The results showed that: first, the carbon storage of wetlands estimated by the InVEST model decreased from 33.38 to 16.64 Tg·C between 1995 and 2020 in the GBA, mainly owning to the loss of paddy fields. Second, there is a significant exponentially decreasing relationship between water inundation frequency and carbon storage density within the potential wetland extent, with the R2 reaching 0.998, which denotes huge potential for estimating wetland carbon storage; third, annual wetland carbon storage estimated were divided into three main stages: a rapidly increasing period (1995–2004), a falling period (2005–2013), and a slightly fluctuating period (2015–2020). This research may provide references for supporting decision-making in implementing wetland-related sustainable development and carbon-neutrality policies in the GBA.

Objective: Estrogen is indispensable in health and disease and mainly functions through its receptors. The protection of the cardiovascular system by estrogen and its receptors has been recognized for decades. Numerous studies with a focus on estrogen and its receptor system have been conducted to elucidate the underlying mechanism. Although nuclear estrogen receptors, including estrogen receptor-α and estrogen receptor-β, have been shown to be classical receptors that mediate genomic effects, studies now show that GPER mainly mediates rapid signaling events as well as transcriptional regulation via binding to estrogen as a membrane receptor. With the discovery of selective synthetic ligands for GPER and the utilization of GPER knockout mice, significant progress has been made in understanding the function of GPER. In this review, the tissue and cellular localizations, endogenous and exogenous ligands, and signaling pathways of GPER are systematically summarized in diverse physiological and diseased conditions. This article further emphasizes the role of GPER in vascular pathology and physiology, focusing on the latest research progress and evidence of GPER as a promising therapeutic target in hypertension, pulmonary hypertension, and atherosclerosis. Thus, selective regulation of GPER by its agonists and antagonists have the potential to be used in clinical practice for treating such diseases.

Pulmonary fibrosis (PF) is a chronic and progressively fatal disease, but clinically available therapeutic drugs are limited due to efficacy and side effects. The possible mechanism of pulmonary fibrosis includes the damage of alveolar epithelial cells II (AEC2), and activation of immune cells such as macrophages. The ions released from bioceramics have shown the activity in stimulating soft tissue derived cells such as fibroblasts, endothelia cells and epithelia cells, and regulating macrophage polarization. Therefore, this study proposes an “ion therapy” approach based on the active ions of bioceramic materials, and investigates the therapeutic effect of bioactive ions derived from calcium silicate (CS) bioceramics on mouse models of pulmonary fibrosis. We demonstrate that silicate ions significantly reduce pulmonary fibrosis by simultaneously regulating the functions of AEC2 and macrophages. This result suggests potential clinical applications of ion therapy for lung fibrosis.

Abstract Background To date, whether the immune response for SARS-CoV-2 infection among people living with HIV(PLWH) is different from HIV-naïve individuals is still not clear. Methods In this cohort study, COVID-19 patients admitted to hospitals in Wuhan between January 15 and April 1, 2020, were enrolled. Patients were categorized into PLWH and HIV-naïve group. All patients were followed up regularly (every 15 days) until November 30, 2020, and the immune response towards SARS-CoV-2 was observed. Results Totally, 18 PLWH and 185 HIV-naïve individuals with COVID-19 were enrolled. The positive conversion rates of IgG were 56% in PLWH and 88% in HIV-naïve patients respectively, and the peak was on the 45th day after COVID-19 onset. However, the positive rate of IgG dropped to 12% in PLWH and 33% among HIV-naïve individuals by the end of the study. The positive conversion rate of IgG among asymptomatic carriers is significantly lower than that among patients with moderate disease (AOR = 0.24, 95% CI 0.07–0.85). PLWH had a lower IgG seroconversion rate (AOR = 0.11, 95% CI 0.03–0.39) and shorter IgG duration (AHR = 3.99, 95% CI 1.43–11.13) compared to HIV-naïve individuals. Patients with higher lymphocyte counts at onset had a lower positive conversion rate (AOR = 0.30, 95% CI 0.10–0.87) and shorter duration for IgG (AHR = 4.01, 95% CI 1.78–9.02). Conclusions The positive conversion rate of IgG for SARS-CoV-2 was relatively lower and quickly lost in PLWH.

Background: Inflammatory bowel disease (IBD) is a global gastrointestinal disease characterized by relapsing and remitting inflammatory conditions. Flos Puerariae (the flower of Pueraria lobata [Willd.] Ohwi and P. thomsonii Benth.) and Hovenia dulcis Thunb. (Rhamnaceae) are traditional Chinese medicines. This medicinal pair has been used to treat various diseases due to its excellent anti-oxidant and anti-inflammatory activity. However, the effects of extracts from these plants on dextran sulfate sodium (DSS)-induced colitis have not been investigated; further study is needed to improve the understanding of their mechanisms of action and potential applications.Methods: The chemical constitution of extracts from Flos Puerariae and Semen Hoveniae (PHE) was analyzed using UPLC-LTQ-Orbitrap-MS/MS. The protective effects of PHE on mice with DSS-induced colitis were evaluated through assessment of body weight loss, disease activity index (DAI) score, colon length shortening, and pathological changes. The levels of inflammatory cytokines were determined by ELISA and RT-qPCR. Biomarkers of oxidative stress (ROS, CAT, SOD, MDA, and T-AOC) were analyzed using biochemical kits. The expression of MAPK proteins was determined by Western blotting analysis. Gut microbiota were analyzed via 16S rRNA sequencing.Results: Chemical composition analysis indicated that PHE contains various bioactive compounds, including puerarin, kakkalide, tectoridin, and genistin. The findings from this study suggest that PHE could effectively modulate histopathological score, inflammatory cell infiltration, and inflammatory factor secretion. Notably, PHE ameliorated oxidative stress by inhibiting activation of the MAPK pathway, leading to decreased inflammatory mediators and restored antioxidant enzyme activity. Furthermore, PHE treatment regulated the composition of the gut microbiota by increasing the abundance of benign bacteria, such as Akkermansia, and reducing the abundance of harmful bacteria, such as Proteobacteria.Conclusion: The findings from this study demonstrate the mechanism underlying the amelioration of DSS-induced intestinal oxidative stress by PHE and its positive impact on the restoration of the composition of gut microbiota.

The time window from stroke onset is critical for the treatment decision. However, in unknown onset stroke, it is often difficult to determine the exact onset time because of the lack of assessment methods, which can result in controversial and random treatment decisions. Previous studies have shown that serum biomarkers, in addition to imaging assessment, are useful for determining the stroke onset time. However, as yet there are no specific biomarkers or corresponding methodologies that are accurate and effective for determining the onset time of unknown onset stroke. Herein, we describe our novel advanced metabolites-based machine learning method (termed extreme gradient boost [XGBoost]) combined with recursive feature elimination, which accurately screened five metabolites from 1124 metabolites detected in serum. These metabolites were capable of both detecting acute ischemic stroke and backtracking the acute ischemic stroke onset time. To further investigate the pathological mechanisms of acute ischemic stroke, we also examined characteristic metabolites in different brain regions, and found two metabolites that could distinguish the core infarct area from the ischemic penumbra. Although this study is based on animal experiments, our machine learning framework and selected metabolites may provide a basis for clinical stroke evaluation and treatment.

Despite pitch being considered the primary cue for discriminating lexical tones, there are secondary cues such as loudness contour and duration, which may allow some cochlear implant (CI) tone discrimination even with severely degraded pitch cues. To isolate pitch cues from other cues, we developed a new disyllabic word stimulus set (Di) whose primary (pitch) and secondary (loudness) cue varied independently. This Di set consists of 270 disyllabic words, each having a distinct meaning depending on the perceived tone. Thus, listeners who hear the primary pitch cue clearly may hear a different meaning from listeners who struggle with the pitch cue and must rely on the secondary loudness contour. A lexical tone recognition experiment was conducted, which compared Di with a monosyllabic set of natural recordings. Seventeen CI users and eight normal-hearing (NH) listeners took part in the experiment. Results showed that CI users had poorer pitch cues encoding and their tone recognition performance was significantly influenced by the “missing” or “confusing” secondary cues with the Di corpus. The pitch-contour-based tone recognition is still far from satisfactory for CI users compared to NH listeners, even if some appear to integrate multiple cues to achieve high scores. This disyllabic corpus could be used to examine the performance of pitch recognition of CI users and the effectiveness of pitch cue enhancement based Mandarin tone enhancement strategies. The Di corpus is freely available online: https://github.com/BetterCI/DiTone.

BackgroundFunctional vitamin B12 deficiency is common in cardiovascular diseases (CVDs), such as heart failure and myocardial infarction. Methylmalonic acid (MMA) is a specific and sensitive marker of vitamin B12 deficiency. However, there are scarce data in regard to the relationship between MMA and CVDs.Materials and methodsIn this cross-sectional study, we analyzed data of 5,313 adult participants of the National Health and Nutrition Examination Survey (NHANES) 2013–2014. Associations between MMA and other variables were assessed with linear regression models. Univariable and multivariable logistic regression models were employed to explore the association between MMA and CVDs.ResultsThe weighted prevalence of CVDs was 8.8% in the general population of the USA. Higher MMA levels were found in participants with CVDs (p < 0.001). Linear regression models revealed positive associations between serum MMA level and age (p < 0.001), glycohemoglobin (p = 0.023), fasting glucose (p = 0.044), mean cell volume (p = 0.038), and hypertension (p = 0.003). In the multivariable logistic model adjusting for age, gender, ethnicity, smoking, hypertension, glycohemoglobin, body mass index (BMI), low-density lipoprotein-cholesterol (LDL-C), renal dysfunction and vitamin B12, serum MMA (adjusted odds ratio, 3.08; 95% confidence interval: 1.63–5.81, p = 0.002, per ln nmol/L increment) was associated with CVDs.ConclusionOur study demonstrated that elevated serum MMA levels were independently associated with the presence of CVDs and may be used to predict the occurrence of CVDs.

Study region: Mu Us Sandy Land, China. Study focus: The groundwater table in unconfined aquifers is often a subdued replica of the topography or land surface. In hilly terrain, spatial interpolation methods are prone to errors such as higher interpolation water level than the ground surface due to sparse observation wells. Meanwhile, in ridge areas, groundwater depth can easily be overestimated with limited groundwater observations. To address these issues, this paper proposes a framework to learn groundwater depth using related groundwater variables based on the extreme gradient boosting (XGB) machine learning method. Moreover, the groundwater level map is drawn based on the predicted groundwater depths and elevation data.New Hydrological Insights for the RegionThe results obtained by the XGB algorithm are compared with those of common interpolation methods (including inverse distance weighting, ordinary kriging, and collaborative ordinary kriging) and machine learning methods (including multiple linear regression, geographically weighted regression, support vector regression, and random forest). The results showed that the XGB using the Tweedie loss function performs best in learning groundwater depth compared with interpolation methods and other machine learning methods, and almost completely overcomes the effects of imbalanced data. The topographic factors such as elevation, topographic position index, and topographic roughness index are key factors for groundwater depth. This study provides a reference for improving regional GL mapping, especially in areas of complex terrain.

Background: The CTNND2 gene which encodes a δ-catenin protein (CTNND2) is associated with multiple severe neurological disorders. However, the specific role of CTNND2 in spatial cognition and related mechanisms remains obscure. Methods: In this study, we generated a new line of Ctnnd2-Knock out (KO) mice with its exon2 deleted, and then characterized their behavioral phenotypes and explore the Biological mechanism. Results: Ctnnd2-KO mice were with typical autism-like behaviors as evidenced by reduced social interaction in three-chamber sociability test, more frequent stereotypic behaviors (self-grooming), and deficits in spatial learning and memory tested by the Morris water maze. Furthermore, the expression of Rictor protein, a core component of the mTORC2 complex, was significantly decreased in the hippocampus of mutant mice. ShRNA-induced knockdown of Rictor protein in the hippocampus of both Ctnnd2-KO mice and wild-type mice exacerbated spatial learning and memory deficits but did not affect their autism-like behaviors. Mechanistically, the hippocampal CA1 neurons of Ctnnd2-KO mice showed decreased actin polymerization, postsynaptic spine density. Down-regulation of Rictor resulted in altered expression of post-synaptic proteins such as GluR1 and ELKS, but not presynaptic protein Synapsin1, implying abnormal synaptic changes in KO mice. Conclusion: The CTNND2 gene is involved in spatial learning and memory via Rictor-mediated actin polymerization and synaptic plasticity. Our study provides a novel insight into the role and mechanisms of the Ctnnd2 gene in cognition at the molecular and synaptic levels. Highlights: 1. Ctnnd2−/− mice exhibited autism-like behaviors and impaired spatial learning and memory. 2. Rictor was involved in the regulation of Ctnnd2-associated spatial cognition but not autism-like behaviors. 3. Rictor played a crucial role in spatial learning and memory by modulating postsynaptic changes in hippocampal neurons of Ctnnd2-⁣/- mice.

Numerous studies have elucidated the neuroprotective effect of 6-gingerol in central nervous system diseases. However, the potential role and mechanism of 6-gingerol on early brain injury (EBI) after subarachnoid hemorrhage (SAH) remains poorly understood. Here, we report that 6-gingerol exerts a neuroprotective effect on SAH-induced EBI through the GBP2/PI3K/AKT pathway. A SAH rat model was established by injecting femoral artery blood into the cisterna magna. 6-gingerol or vehicle was injected intraperitoneally 1 hour post-SAH induction. We found that the neurological function score and brain edema of SAH rats were significantly improved after 6-gingerol treatment, as well as neuronal apoptosis was attenuated in SAH rats by Nissl staining assay and TUNEL assay. To further explore potential molecular mechanisms associated with 6-gingerol, RNA sequencing was implemented to investigate the differences in transcriptomes between SAH rats with and without 6-gingerol treatment; and found that the expression of guanylate-binding protein 2 (GBP2) evidently was suppressed with 6-gingerol treatment compared to vehicle group. In addition, dual immunofluorescence was also employed to investigate changes in neurons, astrocytes, and microglia after 6-gingerol treatment. The results showed that GBP2 was expressed in neurons but not astrocytes or microglia. Western blotting analysis results demonstrated that the PI3K/AKT pathway was activated in the SAH rats treated with 6-gingerol. Furthermore, recombinant GBP2 protein and LY294002 (PI3K inhibitor) treatment reversed the effects of 6-gingerol treatment in SAH rats. These results indicate that 6-gingerol suppressed the expression of GBP2 to activate the PI3K/AKT pathway, improve neurologic outcomes, reduce brain edema and neuronal apoptosis. In summary, our findings suggest that 6-gingerol could attenuate EBI post-SAH in rats, and 6-gingerol may serve as a novel candidate neuroprotective drug for SAH-induced EBI.

BackgroundThe association between glioma risk and body mass index (BMI) remains obscure.MethodsThis study aimed to assess the association between glioma risk and BMI in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Cox proportional hazards regression was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsThe onset of a total of 269 gliomas was observed during a median follow-up period of 12.04 years. Compared with the normal weight, overweight (HR: 1.05; 95% CI: 0.80, 1.39) and obesity (HR: 0.91; 95% CI: 0.56, 1.39) were not significantly associated with glioma risk. Further analysis showed a nonlinear relationship between glioma risk and BMI in men but not women. The multivariable-adjusted HRs per unit increase in BMI were 0.94 (95% CI: 0.89, 1.00; P = 0.037) in men with BMI >25 kg/m2 and 1.16 (95% CI: 0.98, 1.38; P = 0.075) in men with BMI 25 kg/m2. Future studies are needed to validate our observation.

This study investigated the bioaccumulation and transfer of heavy metals including Cd, Cr, Cu, Mn, Ni, Pb and Zn in soil-crop system in Lhasa, and assessed the health risks of the edible part of the crops. The results showed that the average values of Cd, Cr, Cu, Mn, Ni, Pb and Zn were 0.15, 44.55, 24.68, 532.40, 22.47, 38.18 and 73.99 mg kg−1 in natural soil, and 0.16, 46.93, 38.45, 559.13, 23.23, 40.03 and 83.29 mg kg−1 in cultivated soil, respectively. Highland barley and wheat had the strongest ability to accumulate Zn in grain, the BCF values were 0.24 and 0.27, respectively, significant differences in the distribution of metal contents in crop root, stem, leaf and grain were observed. Root presented larger accumulation capacity in most metals, Zn and Cu was easily transferred in the plant organs, most metals in this study presented difficult to migrate from root to grain. The transfer peak of most metals in soil-crop system appeared from stem to leaf. The concentrations of Cr and Mn in crop grains could be predicted according to the multiple linear regression models. THQ and HI values of heavy metals in edible parts of both highland barley and wheat were below the safety threshold of 1, indicating no detrimental effects posed to adults health. This study helps to understand the accumulation and transfer of heavy metals in soil-crop system in plateau region.

BackgroundEpidemiological evidence that glioma has a slight male predominance implies that factors associated with sex hormones may play a role in the development of glioma. The association between oral contraceptive (OC) use and glioma risk remains controversial.MethodIn the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial of 70,516 women in the USA, Cox proportional hazards regression analyses were adopted to calculate the crude and adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). Additionally, a meta-analysis combining the PLCO findings with those of other prospective cohorts was performed.ResultsDuring a mean follow-up of ~11.7 years, 110 of 70,516 women aged 50–78 years at baseline were diagnosed with glioma in PLCO studies. Compared with never users, an inverse association of borderline significance was found for OC users (HR 0.67, 95% CI 0.44–1.04, P = 0.074). Analyses assessing glioma risk according to the duration of OC use yielded no significant association. When PLCO was combined with four other prospective studies, there was an inverse association between OC use and glioma risk (HR 0.85, 95% CI 0.75–0.97, I2 = 0.0%). Further dose-response analysis showed a nonlinear, inverse relationship between OC use and glioma risk (P < 0.001).ConclusionsThis study provided some evidence of a nonlinear, inverse association between OC use and glioma risk. Future larger studies are warranted to validate this finding.

Supercritical carbon dioxide (S-CO2) has the advantages of amphoteric liquid and gas, which possesses many unique characteristics, such as good compressibility, high density, high solubility, good fluidity and low viscosity. The Brayton cycle with S-CO2 is considered to have many promising applications, especially for power conversion industries. However, the corrosion and degradation of structural materials hinder the development and application of the Brayton cycle with S-CO2. Nickel-based alloys have the best corrosion resistance in S-CO2 environments compared to austenitic stainless steels and ferritic/martensitic steels. Thus, the present article mainly reviews the corrosion behaviour of nickel-based alloys in S-CO2 under high temperature and pressure. The effect of alloying elements and environment parameters on the corrosion behaviour of different nickel-based alloys are systematically summarized. The conclusion and outlook are given at the end.

Three-dimensional deformation is an important input to explore seismic mechanisms and geodynamics. The GNSS and InSAR technologies are commonly used to obtain the co-seismic three-dimensional deformation field. This paper focused on the effect of calculation accuracy caused by the deformation correlation between the reference point and the points involved in the solution, to build a high-accuracy three-dimensional deformation field for a detailed geological explanation. Based on the variance component estimation (VCE) method, the InSAR LOS, azimuthal deformation, and the GNSS horizontal and vertical deformation were integrated to solve the three-dimensional displacement of the study area in combination with the elasticity theory. The accuracy of the three-dimensional co-seismic deformation field of the 2021 Maduo MS7.4 earthquake obtained by the method proposed in this paper, was compared with that obtained from the only InSAR measurements obtained using a multi-satellite and multi-technology approach. The results showed the difference in root-mean-square errors (RMSE) of the integration and GNSS displacement was 0.98 cm, 5.64 cm, and 1.37 cm in the east–west, north–south and vertical direction respectively, which was better than the RMSE of the method using only InSAR and GNSS displacement, which was 5.2 cm and 12.2 cm in the east–west, north–south, and no vertical direction. With the geological field survey and aftershocks relocation, the results showed good agreement with the strike and the position of the surface rupture. The maximum slip displacement was about 4 m, which was consistent with the result of the empirical statistical formula. It was firstly found that the pre-existing fault controlled the vertical deformation on the south side of the west end of the main surface rupture caused by the Maduo MS7.4 earthquake, which provided the direct evidence for the theoretical hypothesis that large earthquakes could not only produce surface rupture on seismogenic faults, but also trigger pre-existing faults or new faults to produce surface rupture or weak deformation in areas far from seismogenic faults. An adaptive method was proposed in GNSS and InSAR integration, which could take into account the correlation distance and the efficiency of homogeneous point selection. Meanwhile, deformation information of the decoherent region could be recovered without interpolation of the GNSS displacement. This series of findings formed an essential supplement to the field surface rupture survey and provided a novel idea for the combination of the various spatial measurement technologies to improve the seismic deformation monitoring.

Abstract Wideband Absorbance Immittance (WAI) has been available for more than a decade, however its clinical use still faces the challenges of limited understanding and poor interpretation of WAI results. This study aimed to develop Machine Learning (ML) tools to identify the WAI absorbance characteristics across different frequency-pressure regions in the normal middle ear and ears with otitis media with effusion (OME) to enable diagnosis of middle ear conditions automatically. Data analysis included pre-processing of the WAI data, statistical analysis and classification model development, and key regions extraction from the 2D frequency-pressure WAI images. The experimental results show that ML tools appear to hold great potential for the automated diagnosis of middle ear diseases from WAI data. The identified key regions in the WAI provide guidance to practitioners to better understand and interpret WAI data and offer the prospect of quick and accurate diagnostic decisions.