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MicroRNAs (miRNAs) are widely involved in various biological processes of plants and contribute to plant resistance against various pathogens. In this study, upon sugarcane mosaic virus (SCMV) infection, the accumulation of maize (Zea mays) miR398b (ZmmiR398b) was significantly reduced in resistant inbred line Chang7‐2, while it was increased in susceptible inbred line Mo17. Degradome sequencing analysis coupled with transient co‐expression assays revealed that ZmmiR398b can target Cu/Zn‐superoxidase dismutase2 (ZmCSD2), ZmCSD4, and ZmCSD9 in vivo, of which the expression levels were all upregulated by SCMV infection in Chang7‐2 and Mo17. Moreover, overexpressing ZmmiR398b (OE398b) exhibited increased susceptibility to SCMV infection, probably by increasing reactive oxygen species (ROS) accumulation, which were consistent with ZmCSD2/4/9‐silenced maize plants. By contrast, silencing ZmmiR398b (STTM398b) through short tandem target mimic (STTM) technology enhanced maize resistance to SCMV infection and decreased ROS levels. Interestingly, copper (Cu)‐gradient hydroponic experiments demonstrated that Cu deficiency promoted SCMV infection while Cu sufficiency inhibited SCMV infection by regulating accumulations of ZmmiR398b and ZmCSD2/4/9 in maize. These results revealed that manipulating the ZmmiR398b‐ZmCSD2/4/9‐ROS module provides a prospective strategy for developing SCMV‐tolerant maize varieties. [ABSTRACT FROM AUTHOR]

In the present work, the herb (Poria cocos (Schw.) Wolf) residue, as an environmentally friendly and renewable biomass source, was converted into novel biochar. Biochar/sodium alginate mixed matrix membrane was fabricated. On this basis, a biochar/sodium alginate mixed matrix membrane‐based in‐syringe solid‐phase extraction was developed combined with ultra‐high performance liquid chromatography‐tandem mass spectrometry to determine nitroimidazoles in water samples. The factors including times of exaction, type, and volume of elution solvent, and sample solution pH were thoroughly optimized. Then the correlation coefficient was 0.9995–0.9997. The limit of detection of four analytes was between 0.006 and 0.014 ng/mL, and the recovery was between 79.02% and 99.1%. Consequently, the established method would provide a new perspective on monitoring nitroimidazoles in water samples. [ABSTRACT FROM AUTHOR]

This article explores the origin and evolution of the Y chromosome in kiwifruit. The sex determination of kiwifruit is genetically controlled by an XY system, and two Y-linked sex-determining genes, Shy Girl (SyGl) and Friendly Boy (FrBy), have been identified. The study examines the structural reorganization of the kiwifruit Y chromosome and identifies the sex-determining region (SDR) on chromosome 25 in A. chinensis and chromosome 12 in A. eriantha. The research also investigates the genomic diversity and evolutionary trajectories of the Y chromosome in kiwifruit. [Extracted from the article]

The recovery of critical metals from spent lithium‐ion batteries (LIBs) is important to sustainable development and environment protection. In this paper, sec‐octylphenoxyacetic acid (CA‐12) was first used to recover valuable metals in LIBs. The effects of phase modifier, initial feed pH, extraction kinetics and thermodynamics, CA‐12 concentration and saponification degree were studied and optimized. Under the optimal conditions, 99 % of nickel, cobalt and manganese were co‐extracted to the organic phase, and the loss of lithium was 7 %. The extracted metal ions could be stripped with 0.04 mol/L HCl equivalently. In the spent LIBs powder leaching experiment, leaching efficiencies of all components were greater than 95 %. In the impurity removal stage, extractant N902 was used to remove copper, while iron and aluminum were eliminated by hydrolysis. After two‐stage extraction, the total extraction efficiencies of nickel, cobalt and manganese reached 99.7 %, 99.4 %, 98.45 %, respectively. Finally, lithium in the raffinate was precipitated by saturated Na2CO3, the purity of recovered Li2CO3 was up to 97.7 %. After 5 times cycles, CA‐12 still maintained excellent extraction capacity, showing its potential application prospects for recovering critical metals form spent LIBs. [ABSTRACT FROM AUTHOR]

Vesicles, also known as "microparticles", are vesicle‐like structures that are released outside the cell in a "sprouting" manner when the cytoskeleton is changed during cell activation or apoptosis, with a diameter of about 100–1000 nm, and are carriers of material information exchange between cells. Tumor‐derived extracellular vesicles can effectively deliver drugs to the nucleus of tumor stem cells, thus effectively killing them without toxic side effects. The underlying mechanism involves the soft nature of tumor stem cells that allows better uptake of vesicles, and the entry of drug‐carrying vesicles into lysosomes and facilitation of lysosomal movement toward the nucleus to deliver drugs to the nucleus. Drug‐loaded vesicles have unique advantages, such as low immunogenicity, homing targeting ability, and the ability to break through the physiological barrier to tumor therapy. Tumor‐derived drug‐delivery vesicles have entered clinical trials for the treatment of malignant pleural effusions. In this review, we summarized the progress of basic and clinical research on tumor cell‐derived drug‐loaded vesicles for the treatment of malignant pleural effusion in recent years. [ABSTRACT FROM AUTHOR]

Aims: Stroke has a high incidence and is a disabling condition that can lead to severe cognitive, motor, and sensory dysfunction. In this study, we employed a drug repurposing strategy to investigate the neuroprotective effect of lomitapide on focal ischemic brain injury and explore its potential mechanism of action. Methods: Experimental cerebral ischemia was induced by middle cerebral artery occlusion (MCAO) in adult male C57BL/6 mice and simulated by oxygen–glucose deprivation in N2a‐BV2 cells in co‐cultivation. Results: Lomitapide significantly increased the survival rate, reduced the neuronal tissue loss, and improved the neurological function after MCAO. Furthermore, lomitapide could increase the expression of LC3‐II, reduce the expression of P62 and LAMP2, promote autophagic flux, and inhibit apoptosis by increasing and inhibiting the expression of the apoptosis‐associated proteins Bcl‐2 and Bax, respectively. In addition, lomitapide inhibited the migration of pro‐inflammatory microglia. Conclusion: Lomitapide is a lipid‐lowering drug, and this is the first study to explore its protective effect on ischemic nerve injury in vitro and in vivo. Our results suggest that lomitapide can be repositioned as a potential therapeutic drug for the treatment of stroke. [ABSTRACT FROM AUTHOR]

The protein kinase casein kinase 2 (CK2) exerts its influence on the metabolism of three major cellular substances by phosphorylating essential protein molecules involved in various cellular metabolic pathways. These substances include hormones, especially insulin, rate‐limiting enzymes, transcription factors of key genes, and cytokines. This regulatory role of CK2 is closely tied to important cellular processes such as cell proliferation and apoptosis. Additionally, tumor cells undergo metabolic reprogramming characterized by aerobic glycolysis, accelerated lipid β‐oxidation, and abnormally active glutamine metabolism. In this context, CK2, which is overexpressed in various tumors, also plays a pivotal role. Hence, this review aims to summarize the regulatory mechanisms of CK2 in diverse metabolic pathways and tumor development, providing novel insights for the diagnosis, treatment, and prognosis of metabolism‐related diseases and cancers. [ABSTRACT FROM AUTHOR]

Network‐wide short‐term passenger flow prediction is critical for the operation and management of metro systems. However, it is challenging due to the inherent non‐stationarity, nonlinearity, and spatial–temporal dependencies within passenger flow. To tackle these challenges, this paper introduces a hybrid model called multi‐scale dynamic propagation spatial–temporal network (MSDPSTN). Specifically, the model employs multivariate empirical mode decomposition to jointly decompose the multivariate passenger flow into multi‐scale intrinsic mode functions. Then, a set of dynamic graphs is developed to reveal the passenger propagation law in metro networks. Based on the representation, a deep learning model is proposed to achieve multistep passenger flow prediction, which employs the dynamic propagation graph attention network with long short‐term memory to extract the spatial–temporal dependencies. Extensive experiments conducted on a real‐world dataset from Chengdu, China, validate the superiority of the proposed model. Compared to state‐of‐the‐art baselines, MSDPSTN reduces the mean absolute error, root mean squared error, and mean absolute percentage error by at least 3.243%, 4.451%, and 4.139%, respectively. Further quantitative analyses confirm the effectiveness of the components in MSDPSTN. This paper contributes to addressing inherent features of passenger flow to enhance prediction performance, offering critical insights for decision‐makers in implementing real‐time operational strategies. [ABSTRACT FROM AUTHOR]