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Here, we show that NH 2 -MIL-88B(Fe) can be used as a peroxidase-like catalyst for Fenton-like degradation of methylene blue (MB) in water. The iron-based NH 2 -MIL-88B(Fe) metal organic framework (MOF) was synthesized by a facile and rapid microwave heating method. It was characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, powder X-ray diffraction, and the Brunauer–Emmett–Teller method. The NH 2 -MIL-88B(Fe) MOF possesses intrinsic oxidase-like and peroxidase-like activities. The reaction parameters that affect MB degradation were investigated, including the solution pH, NH 2 -MIL-88B(Fe) MOF and H 2 O 2 concentrations, and temperature. The results show that the NH 2 -MIL-88B(Fe) MOF exhibits a wide working pH range (pH 3.0–11.0), temperature tolerance, and good recyclability for MB removal. Under the optimal conditions, complete removal of MB was achieved within 45 min. In addition, removal of MB was above 80% after five cycles, showing the good recyclability of NH 2 -MIL-88B(Fe). The NH 2 -MIL-88B(Fe) MOF has the features of easy preparation, high efficiency, and good recyclability for MB removal in a wide pH range. Electron spin resonance and fluorescence probe results suggest the involvement of hydroxyl radicals in MB degradation. These findings provide new insight into the application of high-efficient MOF-based Fenton-like catalysts for water purification.

The interactions between dislocations (dislocations and deformation twins) and boundaries (grain boundaries, twin boundaries and phase interfaces) during deformation at ambient temperatures are reviewed with focuses on interaction behaviors, boundary resistances and energies during the interactions, transmission mechanisms, grain size effects and other primary influencing factors. The structure of boundaries, interactions between dislocations and boundaries in coarse-grained, ultrafine-grained and nano-grained metals during deformation at ambient temperatures are summarized, and the advantages and drawbacks of different in-situ techniques are briefly discussed based on experimental and simulation results. The latest studies as well as fundamental concepts are presented with the aim that this paper can serve as a reference in the interactions between dislocations and boundaries during deformation.

Developing non-noble catalysts with superior activity and durability for oxygen evolution reaction (OER) in acidic media is paramount for hydrogen production from water. Still, challenges remain due to the inadequate activity and stability of the OER catalyst. Here, we report a cost-effective and stable manganese oxybromide (Mn 7.5 O 10 Br 3 ) catalyst exhibiting an excellent OER activity in acidic electrolytes, with an overpotential of as low as 295 ± 5 mV at a current density of 10 mA cm −2 . Mn 7.5 O 10 Br 3 maintains good stability under operating conditions for at least 500 h. In situ Raman spectroscopy, X ray absorption near edge spectroscopy, and density functional theory calculations confirm that a self-oxidized surface with enhanced electronic transmission capacity forms on Mn 7.5 O 10 Br 3 and is responsible for both the high catalytic activity and long-term stability during catalysis. The development of Mn 7.5 O 10 Br 3 as an OER catalyst provides crucial insights into the design of non-noble metal electrocatalysts for water oxidation. While acidic water splitting offers a renewable means to obtain renewable hydrogen fuel, the catalysts needed to oxidize water often require expensive noble metals. Here, authors show manganese oxyhalides as acidic oxygen evolution electrocatalysts.

Traffic flow forecasting is crucial for improving urban traffic management and reducing resource consumption. Accurate traffic conditions prediction requires capturing the complex spatial-temporal dependencies inherent in traffic data. Traditional spatial-temporal graph modeling methods often rely on fixed road network structures, failing to account for the dynamic spatial correlations that vary over time. To address this, we propose a Transformer-Enhanced Adaptive Graph Convolutional Network (TEA-GCN) that alternately learns temporal and spatial correlations in traffic data layer-by-layer. Specifically, we design an adaptive graph convolutional module to dynamically capture implicit road dependencies at different time levels and a local-global temporal attention module to simultaneously capture long-term and short-term temporal dependencies. Experimental results on two public traffic datasets demonstrate the effectiveness of the proposed model compared to other state-of-the-art traffic flow prediction methods.

The aim of this study was to synthesize and analyze the burden of disease of polycystic ovary syndrome (PCOS) in women of reproductive age globally and in China from 1990 to 2021. The study utilized data from the Global Burden of Disease 2021 database, which contains detailed epidemiologic information from 204 countries and territories. Incidence, prevalence and disability-adjusted life years (DALYs) of polycystic ovary syndrome (PCOS) were assessed. Bayesian age-period cohort modeling was applied to project trends in the burden of disease up to 2035. Global trend: the incidence of polycystic ovary syndrome (PCOS) increased slightly from 58.84/100,000 in 1990 to 60.30/100,000 in 2021. there was a significant increase in prevalence of 29.66% and an increase in disability-adjusted life-years (DALYs) of 28.37%. Trends in China: Despite a slight decrease in prevalence (-1.96%), the prevalence of polycystic ovary syndrome (PCOS) and the number of DALYs in China increased substantially by 86.95% and 86.56%, respectively. Sociodemographic impact: Countries with higher sociodemographic indices tend to face a higher burden of PCOS. Future projections: BAPC model projections suggest that the prevalence of PCOS will continue to increase globally and in China through 2035. These findings highlight the growing public health challenge posed by polycystic ovary syndrome and emphasize the need to strengthen early identification, health management, and lifestyle interventions, especially in areas with high SDI.

The tumor microenvironment (TME) has become a major research focus in recent years. The TME differs from the normal extracellular environment in parameters such as nutrient supply, pH value, oxygen content, and metabolite abundance. Such changes may promote the initiation, growth, invasion, and metastasis of tumor cells, in addition to causing the malfunction of tumor-infiltrating immunocytes. As the neoplasm develops and nutrients become scarce, tumor cells transform their metabolic patterns by reprogramming glucose, lipid, and amino acid metabolism in response to various environmental stressors. Research on carcinoma metabolism reprogramming suggests that like tumor cells, immunocytes also switch their metabolic pathways, named “immunometabolism”, a phenomenon that has drawn increasing attention in the academic community. In this review, we focus on the recent progress in the study of lipid metabolism reprogramming in immunocytes within the TME and highlight the potential target molecules, pathways, and genes implicated. In addition, we discuss hypoxia, one of the vital altered components of the TME that partially contribute to the initiation of abnormal lipid metabolism in immune cells. Finally, we present the current immunotherapies that orchestrate a potent antitumor immune response by mediating the lipid metabolism of immunocytes, highlight the lipid metabolism reprogramming capacity of various immunocytes in the TME, and propose promising new strategies for use in cancer therapy.

The classification of hyperspectral images (HSI) is an important foundation in the field of remote sensing. Mamba architectures based on state space model (SSM) have shown great potential in the field of HSI processing due to their powerful long-range sequence modeling capabilities and the efficiency advantages of linear computing. Based on this theoretical basis, We propose a novel deep learning framework: long-sequence Mamba (EchoMamba), which combines the powerful long sequence processing capabilities of Long Short-Term Memory(LSTM) and Mamba to further explore the spectral dimension of HSI, and carry out more in-depth mining and learning of the spectral dimension of HSI. Compared with the previous HSI classification model, the experimental results show that EchoMamba can significantly reduce the training time cost of HSI and effectively improve the performance of the classification task.This study not only advances the current state of HSI classification but also provides a robust foundation for future research in spectral-spatial feature extraction and large-scale remote sensing applications.

The objective of this research is to assess the effects of seven different exercise therapies (aquatic exercise, aerobic exercise, yoga, Pilates, virtual reality exercise, whole-body vibration exercise, and resistance exercise) on the balance function and functional walking ability of multiple sclerosis disease patients. Materials and Methods: The effects of different exercise interventions on the balance function and functional walking ability in people with multiple sclerosis were assessed by searching five databases: PubMed, Embase, Cochrane Library, Web of Science, and CNKI; only randomized controlled trials were included. The included studies were assessed for risk of bias using the Cochrane assessment tool. Results: The RCTs were collected between the initial date of the electronic databases’ creation and May 2022. We included 31 RCTs with 904 patients. The results of the collected data analysis showed that yoga can significantly improve patients’ BBS scores (SUCRA = 79.7%) and that aquatic exercise can significantly decrease patients’ TUG scores (SUCRA = 78.8%). Conclusion: Based on the network meta-analysis, we suggest that although each type of exercise is useful, yoga, virtual reality training, and aerobic training are more effective in improving the balance function of people with MS; aquatic exercise, virtual reality training, and aerobic training are more effective in improving the functional walking ability of people with MS.

Trehalose plays a critical role in plant response to salinity but the involved regulatory mechanisms remain obscure. Here, this study explored the mechanism of exogenous trehalose-induced salt tolerance in tomato plants by the hydroponic test method. Our results indicated that 10 mM trehalose displayed remarkable plant biomass by improving growth physiology, which were supported by the results of chlorophyll fluorescence and rapid light–response curve. In the salinity environment, trehalose + NaCl treatment could greatly inhibit the decrease of malondialdehyde level, and it increases the contents of other osmotic substances, carbohydrates, K + , and K + /Na + ratio. Meanwhile, trehalose still had similar effects after recovery from salt stress. Furthermore, trehalose pretreatment promoted trehalose metabolism; significantly increased the enzymatic activity of the trehalose metabolic pathway, including trehalose-6-phosphate synthase (TPS), trehalose-6-phosphate phosphatase (TPP), and trehalase (TRE); and upregulated the expression of SlTPS1 , SlTPS5 , SlTPS7 , SlTPPJ , SlTPPH , and SlTRE under saline conditions. However, the transcriptional levels of SlTPS1 , SlTPS5 , and SlTPS7 genes and the activity of TPS enzyme were reversed after recovery. In addition, we found that hydrogen peroxide (H 2 O 2 ) and superoxide anion (O 2 − ) were accumulated in tomato leaves because of salt stress, but these parameters were all recovered by foliar-applied trehalose, and its visualization degree was correspondingly reduced. Antioxidant enzyme activities (SOD, POD, and CAT) and related gene expression ( SlCu/Zn-SOD , SlFe-SOD , SlMn-SOD , SlPOD , and SlCAT ) in salt-stressed tomato leaves were also elevated by trehalose to counteract salt stress. Collectively, exogenous trehalose appeared to be the effective treatment in counteracting the negative effects of salt stress.

In mammals, nonrenewable primordial follicles are activated in an orderly manner to maintain the longevity of reproductive life. Mammalian target of rapamycin (mTOR)-KIT ligand (KITL) signaling in pre-granulosa cells and phosphatidylinositol 3-kinase (PI3K)-protein kinase B (Akt)-forkhead Box O3a (FOXO3a) signaling in oocytes are important for primordial follicle activation. The activation process is accompanied by the enhancement of energy metabolism, but the causal relationship is unclear. In the present study, the levels of glycolysis-related proteins GLUT4, HK1, PFKL, and PKM2 were significantly increased in granulosa cells but were decreased in oocytes during the mouse primordial-to-primary follicle transition. Both short-term pyruvate deprivation in vitro and acute fasting in vivo increased the glycolysis-related gene and protein levels, decreased AMPK activity, and increased mTOR activity in mouse ovaries. The downstream pathways Akt and FOXO3a were phosphorylated, resulting in mouse primordial follicle activation. The blockade of glycolysis by 2-deoxyglucose (2-DG), but not the blockade of the communication network between pre-granulosa cells and oocyte by KIT inhibitor ISCK03, decreased short-term pyruvate deprivation-promoted mTOR activity. Glycolysis was also increased in human granulosa cells during the primordial-to-primary follicle transition, and short-term pyruvate deprivation promoted the activation of human primordial follicles by increasing the glycolysis-related protein levels and mTOR activity in ovarian tissues. Taken together, the enhanced glycolysis in granulosa cells promotes the activation of primordial follicles through mTOR signaling. These findings provide new insight into the relationship between glycolytic disorders and POI/PCOS.