Anchored Cobalt Nanoparticles on Layered Perovskites for Rapid Peroxymonosulfate Activation in Antibiotic Degradation.

In the Fenton-like reaction, revealing the dynamic evolution of the active sites is crucial to achieve the activity improvement and stability of the catalyst. This study reports a perovskite oxide in which atomic (Co0) in situ embedded exsolution occurs during the high-temperature phase transition. This unique anchoring strategy significantly improves the Co3+/Co2+ cycling efficiency at the interface and inhibits metal leaching during peroxymonosulfate (PMS) activation. The Co@L-PBMC catalyst exhibits superior PMS activation ability and could achieve 99% degradation of tetracycline within 5 min. The combination of experimental characterization and density functional theory (DFT) calculations elucidates that the electron-deficient oxygen vacancy accepts an electron from the Co 3d-orbital, resulting in a significant electron delocalization of the Co site, thereby facilitating the adsorption of the *HSO5/*OH intermediate onto the "metal-VO bridge" structure. This work provides insights into the PMS activation mechanism at the atomic level, which will guide the rational design of next-generation catalysts for environmental remediation.

The development and external validation of a web-based nomogram for predicting overall survival with Ewing sarcoma in children.

Background: Ewing sarcoma remains the second most prevalent primary aggressive bone tumor in teens and young adults. The aim of our study was to develop and validate a web-based nomogram to predict the overall survival for Ewing sarcoma in children. Methods: A total of 698 patients, with 640 cases from the Surveillance, Epidemiology, and End Results (the training set) and 58 cases (the external validation set), were included in this study. Cox analyses were carried out to determine the independent prognostic indicators, which were further included to establish a web-based nomogram. The predictive abilities were tested through the concordance index, calibration curve, decision curve analysis, and area under the receiver operating characteristic curve. Results: As suggested by univariate and multivariate Cox analyses, age, primary site, tumor size, metastasis stage (M stage), and chemotherapy were included as the independent predictive variables. The area under the receiver operating characteristic curve values, calibration curves, concordance index, and decision curve analysis from training and validation groups suggested the model has great clinical applications. Conclusion: We developed a convenient and precise web-based nomogram to evaluate overall survival for Ewing sarcoma in children. The application of this nomogram would assist physicians and patients in making decisions.

METTL3-mediated m6A modification increases Hspa1a stability to inhibit osteoblast aging.

Senile osteoporosis is mainly caused by osteoblasts attenuation, which results in reduced bone mass and disrupted bone remodeling. Numerous studies have focused on the regulatory role of m6A modification in osteoporosis; however, most of the studies have investigated the differentiation of bone marrow mesenchymal stem cells (BMSCs), while the direct regulatory mechanism of m6A on osteoblasts remains unknown. This study revealed that the progression of senile osteoporosis is closely related to the downregulation of m6A modification and methyltransferase-like 3 (METTL3). Overexpression of METTL3 inhibits osteoblast aging. Methylated RNA immunoprecipitation sequencing (MeRIP-seq) revealed that METTL3 upregulates the stability of Hspa1a mRNA, thereby inhibiting osteoblast aging. Moreover, the results demonstrated that METTL3 enhances the stability of Hspa1a mRNA via m6A modification to regulate osteoblast aging. Notably, YTH N6-methyladenosine RNA binding protein 2 (YTHDF2) participates in stabilizing Hspa1a mRNA in the METTL3-mediated m6A modification process, rather than the well-known degradation function. Mechanistically, METTL3 increases the stability of Hspa1a mRNA in a YTHDF2-dependent manner to inhibit osteoblast aging. Our results confirmed the significant role of METTL3 in osteoblast aging and suggested that METTL3 could be a potential therapeutic target for senile osteoporosis.

Constantly optimized mean teacher for semi-supervised 3D MRI image segmentation.

The mean teacher model and its variants, as important methods in semi-supervised learning, have demonstrated promising performance in magnetic resonance imaging (MRI) data segmentation. However, the superior performance of teacher model through exponential moving average (EMA) is limited by the unreliability of unlabeled image, resulting in potentially unreliable predictions. In this paper, we propose a framework to optimized the teacher model with reliable expert-annotated data while preserving the advantages of EMA. To avoid the tight coupling that results from EMA, we leverage data augmentations to provide two distinct perspectives for the teacher and student models. The teacher model adopts weak data augmentation to provide supervision for the student model and optimizes itself with real annotations, while the student uses strong data augmentation to avoid overfitting on noise information. In addition, double softmax helps the model resist noise and continue learning meaningful information from the images, which is a key component in the proposed model. Extensive experiments show that the proposed method exhibits competitive performance on the Left Atrium segmentation MRI dataset (LA) and the Brain Tumor Segmentation MRI dataset (BraTS2019). For the LA dataset, we achieved a dice of 91.02% using only 20% labeled data, which is close to the dice of 91.14% obtained by the supervised approach using 100% labeled data. For the BraTs2019 dataset, the proposed method achieved 1.02% and 1.92% improvement on 5% and 10% labeled data, respectively, compared to the best baseline method on this dataset. This study demonstrates that the proposed model can be a potential candidate for medical image segmentation in semi-supervised learning scenario.

METTL3-mediated m6A modification of SOX4 regulates osteoblast proliferation and differentiation via YTHDF3 recognition.

N6-methyladenosine (m6A), the most prevalent internal modification in mRNA, is related to the pathogenesis of osteoporosis (OP). Although methyltransferase Like-3 (METTL3), an m6A transferase, has been shown to mitigate OP progression, the mechanisms of METTL3-mediated m6A modification in osteoblast function remain unclear. Here, fluid shear stress (FSS) induced osteoblast proliferation and differentiation, resulting in elevated levels of METTL3 expression and m6A modification. Through Methylated RNA Immunoprecipitation Sequencing (MeRIP-seq) and Transcriptomic RNA Sequencing (RNA-seq), SRY (Sex Determining Region Y)-box 4 (SOX4) was screened as a target of METTL3, whose m6A-modified coding sequence (CDS) regions exhibited binding affinity towards METTL3. Further functional experiments demonstrated that knockdown of METTL3 and SOX4 hampered osteogenesis, and METTL3 knockdown compromised SOX4 mRNA stability. Via RNA immunoprecipitation (RIP) assays, we further confirmed the direct interaction between METTL3 and SOX4. YTH N6-Methyladenosine RNA Binding Protein 3 (YTHDF3) was identified as the m6A reader responsible for modulating SOX4 mRNA and protein levels by affecting its degradation. Furthermore, in vivo experiments demonstrated that bone loss in an ovariectomized (OVX) mouse model was reversed through the overexpression of SOX4 mediated by adeno-associated virus serotype 2 (AAV2). In conclusion, our research demonstrates that METTL3-mediated m6A modification of SOX4 plays a crucial role in regulating osteoblast proliferation and differentiation through its recognition by YTHDF3. Our research confirms METTL3-m6A-SOX4-YTHDF3 as an essential axis and potential mechanism in OP.

Prognostic value of mitochondrial CKMT2 in Pan-cancer and its tumor immune correlation analysis.

Mitochondrial metabolism has been shown to play a key role in immune cell survival and function, but mitochondrial creatine kinase 2 (CKMT2) has been relatively little studied about tumor immunity. We aimed to explore the prognostic value of CKMT2 in 33 cancer types and investigate its potential immune function. We used a range of bioinformatics approaches to explore the potential carcinogenic role of CKMT2 in multiple cancers. CKMT2 was lowly expressed in 14 tumor tissues and highly expressed in 4 tumor tissues. Immunohistochemical assays showed overexpression of CKMT2 in colon cancer and rectal cancer. CKMT2 overexpression was positively correlated with the prognosis of lung adenocarcinoma and prostate cancer. CKMT2 overexpression is mainly enriched in the adaptive immune system and immune regulatory pathways of immunoglobulins. Seven cancers were positively correlated with low CKMT2 expression in tumor microenvironment analysis. Among the five cancers, low expression of CKMT2 resulted in better immunotherapy treatment outcomes. There was a strong correlation between CKMT2 and most immune-related genes in specific cancer types. CKMT2 plays an important role in tumorigenesis and cancer immunity and can be used as a prognostic biomarker and potential target for cancer immunotherapy.

Accelerated deprotonation with a hydroxy-silicon alkali solid for rechargeable zinc-air batteries.

Transition metal oxides are promising electrocatalysts for zinc-air batteries, yet surface reconstruction caused by the adsorbate evolution mechanism, which induces zinc-ion battery behavior in the oxygen evolution reaction, leads to poor cycling performance. In this study, we propose a lattice oxygen mechanism involving proton acceptors to overcome the poor performance of the battery in the OER process. We introduce a stable solid base, hydroxy BaCaSiO4, onto the surfaces of PrBa0.5Ca0.5Co2O5+δ perovskite nanofibers with a one-step exsolution strategy. The HO-Si sites on the hydroxy BaCaSiO4 significantly accelerate proton transfer from the OH* adsorbed on PrBa0.5Ca0.5Co2O5+δ during the OER process. As a proof of concept, a rechargeable zinc-air battery assembled with this composite electrocatalyst is stable in an alkaline environment for over 150 hours at 5 mA cm-2 during galvanostatic charge/discharge tests. Our findings open new avenues for designing efficient OER electrocatalysts for rechargeable zinc-air batteries.

AEAU-Net: an unsupervised end-to-end registration network by combining affine transformation and deformable medical image registration.

Deformable medical image registration plays an essential role in clinical diagnosis and treatment. However, due to the large difference in image deformation, unsupervised convolutional neural network (CNN)-based methods cannot extract global features and local features simultaneously and cannot capture long-distance dependencies to solve the problem of excessive deformation. In this paper, an unsupervised end-to-end registration network is proposed for 3D MRI medical image registration, named AEAU-Net, which includes two-stage operations, i.e., an affine transformation and a deformable registration. These two operations are implemented by an affine transformation subnetwork and a deformable registration subnetwork, respectively. In the deformable registration subnetwork, termed as EAU-Net, we designed an efficient attention mechanism (EAM) module and a recursive residual path (RSP) module. The EAM module is embedded in the bottom layer of the EAU-Net to capture long-distance dependencies. The RSP model is used to obtain effective features by fusing deep and shallow features. Extensive experiments on two datasets, LPBA40 and Mindboggle101, were conducted to verify the effectiveness of the proposed method. Compared with baseline methods, this proposed method could obtain better registration performance. The ablation study further demonstrated the reasonability and validity of the designed architecture of the proposed method.

Contribution of local and surrounding anthropogenic emissions to a particulate matter pollution episode in Zhengzhou, Henan, China.

In this study, we simulated the spatial and temporal processes of a particulate matter (PM) pollution episode from December 10-29, 2019, in Zhengzhou, the provincial capital of Henan, China, which has a large population and severe PM pollution. As winter is the high incidence period of particulate pollution, winter statistical data were selected from the pollutant observation stations in the study area. During this period, the highest concentrations of PM2.5 (atmospheric PM with a diameter of less than 2.5 µm) and PM10 (atmospheric PM with a diameter of less than 10 µm) peaked at 283 µg m-3 and 316 µg m-3, respectively. The contribution rates of local and surrounding regional emissions within Henan (emissions from the regions to the south, northwest, and northeast of Zhengzhou) to PM concentrations in Zhengzhou were quantitatively analyzed based on the regional Weather Research and Forecasting model coupled with Chemistry (WRF/Chem). Model evaluation showed that the WRF/Chem can accurately simulate the spatial and temporal variations in the PM concentrations in Zhengzhou. We found that the anthropogenic emissions south of Zhengzhou were the main causes of high PM concentrations during the studied episode, with contribution rates of 14.39% and 16.34% to PM2.5 and PM10, respectively. The contributions of anthropogenic emissions from Zhengzhou to the PM2.5 and PM10 concentrations in Zhengzhou were 7.94% and 7.29%, respectively. The contributions of anthropogenic emissions from the area northeast of Zhengzhou to the PM2.5 and PM10 concentrations in Zhengzhou were 7.42% and 7.18%, respectively. These two areas had similar contributions to PM pollution in Zhengzhou. The area northeast of Zhengzhou had the lowest contributions to the PM2.5 and PM10 concentrations in Zhengzhou (5.96% and 5.40%, respectively).

Research on the evolution and the driving forces of land use classification for production, living, and ecological space in China's Qilian Mountains Nature Reserve from 2000 to 2020.

With the rapid development of the economy, problems such as resource depletion, environmental degradation, and increasingly strained human-land relations have become increasingly prominent. The rational layout of the production, living, and ecological spaces is the basis for solving the contradiction between economic development and environmental protection. This paper analyzed the spatial distribution pattern and evolution characteristics of the Qilian Mountains Nature Reserve based on the theory of production, living, and ecological space. The results show that the production and living function indexes are rising. The most advantaged areas are in the northern part of the research area, where the terrain is flat and transportation is convenient. The ecological function index rises, falls, then rises again. The high-value area is located in the south of the study area, and its ecological function is intact. The study area is dominated by ecological space. During the study period, the area of production space increased by 858.5 km2 and the living space area increased by 341.12 km2. The intensification of human activities has separated the continuity of ecological space. The area of ecological space has decreased by 233.68 km2. Among geographical factors, altitude has a significant impact on the evolution of living space. Population density is the main socioeconomic factor in changing the areas of production space and ecological space. This study is expected to provide a reference basis for land use planning and sustainable development of resources and environment in nature reserves.

Radiographic OA, bone marrow lesions, higher body mass index and medial meniscal root tears are significantly associated with medial meniscus extrusion with OA or medial meniscal tears: a systematic review and meta-analysis.

PURPOSE: Medial meniscus extrusion (MME) refers to the protrusion of the medial meniscus beyond the tibial edge by more than 3 mm, leading to a deficiency of the hoop strain. MME commonly occurs in conjunction with osteoarthritis (OA) or medial meniscal tears (MMT). However, factors associated with concomitant MME in patients with OA or MMT have not been systematically reviewed. This study aims to perform a systematic review and meta-analysis to identify factors associated with concomitant MME in OA or MMT. METHODS: The systematic review of the literature was performed according to PRISMA. A literature search was conducted in 4 databases. All original human studies that reported the available evidence on factors associated with concomitant MME in patients with OA or MMT were included. Pooled binary variables were analyzed by odds ratios (OR) and 95% CIs, and pooled continuous variables were evaluated by mean difference (MD) and 95% CIs. RESULTS: Ten studies on OA (5993 patients) and eight studies on MMT (872 patients) met the inclusion criteria. The overall pooled incidence of MME was 43% (95% CI, 37-50%) for OA, 61% (95% CI 43-77%) for MMT, and 85% (95% CI 72-94%) for medial meniscal root tears (MMRT). For the population with OA, Factors significantly associated with MME included radiographic OA [OR 4.24; 95% CI 3.07-5.84; P < 0.0001], bone marrow lesions [OR, 3.35; 95% CI 1.61-6.99; P = 0.0013], cartilage damage [OR, 3.25; 95% CI 1.60-6.61; P = 0.0011], and higher body mass index (BMI) [MD, 1.81; 95% CI 1.15-2.48; P < 0.0001]. Factors strongly associated with increased risk of MME for MMT included medial meniscal root [OR, 8.39; 95% CI 2.84-24.82; P < 0.0001] and radial tears [OR, 2.64; 95% CI 1.18-5.92; P < 0.0001]. CONCLUSION: Radiographic OA, bone marrow lesions, cartilage damage, and higher BMI were significantly associated with concomitant MME with OA. Furthermore, medial meniscal root and radial tears were significantly associated with an increased risk of MME in patients with MMT. LEVEL OF EVIDENCE: IV.

Effect of agricultural soil wind erosion on urban PM2.5 concentrations simulated by WRF-Chem and WEPS: A case study in Kaifeng, China.

Dust emission induced by agricultural soil wind erosion is one of the main sources of atmospheric particulate matter (PM) in dryland areas. However, most current air quality models do not consider this emission source, resulting in large uncertainties in PM simulations. Here we estimated the agricultural PM2.5 (particulate matter with an aerodynamic diameter <2.5 µm) emission around Kaifeng, a prefecture-level city in central China, using the Wind Erosion Prediction System (WEPS), with the MEIC (Multi-resolution Emission Inventory for China) as an anthropogenic emission source. We then plugged these estimates into the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to simulate an air pollution episode in Kaifeng, China. Results showed that the addition of agricultural soil PM2.5 emissions significantly improved the ability of WRF-Chem to accurately simulate PM2.5 concentrations. The PM2.5 concentration mean bias and correlation coefficient of not considered and considered agricultural dust emission were -72.35 µg m-|3 and 3.31 µg m-|3 and 0.3 and 0.58, respectively. The PM2.5 emitted by the agricultural soil wind erosion contributed around 37.79% of the PM2.5 in the Kaifeng municipal district during this pollution episode. This study confirmed that the dust emission caused by agricultural soil wind erosion can significantly impact urban PM2.5 concentrations which surrounded by large areas of farmland, and also indicated that coupling dust emissions from farmland with anthropogenic air pollutant emissions can improve the accuracy of air quality models.

A comparative study of environmental responsibility behavior in ecotourism from the perceptions of residents and tourists: A case of Qilian Mountains National Park in China.

The environmentally responsible behaviors of residents and tourists are great significance to the protection of natural resources and sustainable development of ecotourism. This paper takes China's Qilian Mountains National Park as the case place. By constructing a theoretical model of perceived value on environmentally responsible behavior and studying the relationship between residents' and tourists' perceived value, satisfaction and environmentally responsible behavior from both subject and object perspectives, the study shows that. Educational level and occupational distribution have significant effects on residents' and tourists' perceptions of ecotourism environmentally responsible behaviors, but age only has a significant effect on residents' perceptions of ecotourism environmentally responsible behaviors. Gender differences do not affect residents' and tourists' perceptions of ecotourism environmentally responsible behaviors. The theoretical model between residents' perceptions of environmentally responsible behaviors, environmentally responsible behaviors, and satisfaction was basically confirmed. Perceived environmentally responsible behaviors of tourists does not affect satisfaction. Satisfaction has a positive effect on tourists' environmentally responsible behaviors. Perceived environmental responsibility of tourists has a significant positive effect on tourists' environmentally responsible behaviors. The overall level of residents' perception of environmentally responsible behaviors in ecotourism is higher than tourists' perception. Residents and tourists have a poor perception of ecological and environmental protection policies. This paper expects to strengthen residents' and tourists' perceptions of ecologically responsible behaviors. Establishing the sentiment of satisfaction and commitment to environmental protection motivates residents and tourists to implement environmentally responsible behaviors and contribute to the sustainable development of ecotourism.

Screening and identification of potential hub genes and immune cell infiltration in the synovial tissue of rheumatoid arthritis by bioinformatic approach.

Background: Rheumatoid arthritis (RA) is an autoimmune disease that affects individuals of all ages. The basic pathological manifestations are synovial inflammation, pannus formation, and erosion of articular cartilage, bone destruction will eventually lead to joint deformities and loss of function. However, the specific molecular mechanisms of synovitis tissue in RA are still unclear. Therefore, this study aimed to screen and explore the potential hub genes and immune cell infiltration in RA. Methods: Three microarray datasets (GSE12021, GSE55457, and GSE55235), from the Gene Expression Omnibus (GEO) database, have been analyzed to explore the potential hub genes and immune cell infiltration in RA. First, the LIMMA package was used to screen the differentially expression genes (DEGs) after removing the batch effect. Then the clusterProfiler package was used to perform functional enrichment analyses. Second, through weighted coexpression network analysis (WGCNA), the key module was identified in the coexpression network of the gene set. Third, the protein-protein interaction (PPI) network was constructed through STRING website and the module analysis was performed using Cytoscape software. Fourth, the CIBERSORT and ssGSEA algorithm were used to analyze the immune status of RA and healthy synovial tissue, and the associations between immune cell infiltration and RA-related diagnostic biomarkers were evaluated. Fifth, we used the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) to validate the expression levels of the hub genes, and ROC curve analysis of hub genes for discriminating between RA and healthy tissue. Finally, the gene-drug interaction network was constructed using DrugCentral database, and identification of drug molecules based on hub genes using the Drug Signature Database (DSigDB) by Enrichr. Results: A total of 679 DEGs were identified, containing 270 downregulated genes and 409 upregulated genes. DEGs were primarily enriched in immune response and chemokine signaling pathways, according to functional enrichment analysis of DEGs. WGCNA explored the co-expression network of the gene set and identified key modules, the blue module was selected as the key module associated with RA. Seven hub genes are identified when PPI network and WGCNA core modules are intersected. Immune infiltration analysis using CIBERSORT and ssGSEA algorithms revealed that multiple types of immune infiltration were found to be upregulated in RA tissue compared to normal tissue. Furthermore, the levels of 7 hub genes were closely related to the relative proportions of multiple immune cells in RA. The results of the qRT-PCR demonstrated that the relative expression levels of 6 hub genes (CD27, LCK, CD2, GZMB, IL7R, and IL2RG) were up-regulated in RA synovial tissue, compared with normal tissue. Simultaneously, ROC curves indicated that the above 6 hub genes had strong biomarker potential for RA (AUC >0.8). Conclusions: Through bioinformatics analysis and qRT-PCR experiment, our study ultimately discovered 6 hub genes (CD27, LCK, CD2, GZMB, IL7R, and IL2RG) that closely related to RA. These findings may provide valuable direction for future RA clinical diagnosis, treatment, and associated research.

Extraction of honokiol from Artemisia argyi and in vitro and in vivo investigation of its antifungal activity.

Extracts from plants used in Chinese medicine can be good sources of fungicides for agricultural applications. In this study, we separated and identified antifungal compounds from four traditional Chinese medicine extracts and evaluated their antifungal activities in vitro and in vivo. In vitro, honokiol extracted from Artemisia argyi showed broad-spectrum antimicrobial and mycelial inhibitory activity with EC50 in the range 3.56 - 33.85 µg/mL against eight plant pathogens. q-PCR indicated that honokiol might induce cell cancerisation and inhibit cellular respiration, which provided significant insights into honokiol function in tobacco resistance to molecular mechanisms of the phytopathogenic fungus Phytophthora nicotianae. In vivo, honokiol significantly decreased the rate of fungal infection in eggplants, potatoes, grapes, cherry tomatoes, and cucumbers, and enhanced disease resistance in tobacco. Overall, our results indicate that honokiol has the potential to control a variety of fungal and oomycete diseases, and A. argyi could be a source of honokiol.

Tin Nanoclusters Confined in Nitrogenated Carbon for the Oxygen Reduction Reaction.

The oxygen reduction reaction is essential for fuel cells and metal-air batteries in renewable energy technologies. Developing platinum-group-metal (PGM)-free catalysts with comparable catalytic performance is highly desired for cost efficiency. Here, we report a tin (Sn) nanocluster confined catalyst for the electrochemical oxygen reduction. The catalyst was fabricated by confining 1-1.5 nm sized Sn nanoclusters in situ in microporous nitrogen-doped carbon polyhedra (SnxNC) with an average pore size of 0.7 nm. SnxNC exhibited high catalytic performance in acidic media, including positive onset and half-wave potentials, comparable to those of the state-of-the-art Pt/C and far exceeding those of the Sn single-atom catalyst. Combined structural and theoretical analyses reveal that the confined Sn nanoclusters, which have favorable oxygen adsorption behaviors, are responsible for the high catalytic performance, but not Sn single atoms.

Contribution of local and surrounding area anthropogenic emissions to a high ozone episode in Zhengzhou, China.

This study analyzed an ozone pollution episode that occurred in the summer of 2020 in Zhengzhou, the provincial capital of Henan, China, and quantified the contribution of local and surrounding area anthropogenic emissions to this episode based on the Weather Research and Forecasting with Chemistry (WRF/Chem) model. Simulation results showed that the WRF/Chem model is well suited to simulate the ozone concentrations in this area. In addition, four simulation scenarios (removing the emissions from the northern Zhengzhou, southwestern Zhengzhou, Zhengzhou local and southeastern Zhengzhou) were conducted to explore the specific contributions of local emissions and emissions from surrounding areas within Henan to this ozone pollution episode. We found that contributions from the northern, local, southwestern, and southeastern regions were 6.1%, 5.9%, 1.7%, and 1.5%, respectively. The northern and local emissions of Zhengzhou (only emissions from Zhengzhou) were prominent contributors within the simulation areas. In other words, during this episode, most of the ozone pollution in Zhengzhou appeared to be transported in from regions outside Henan Province.