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The further development of lightweight and energy-saving engineering materials is a great challenge for scientists in the 21st century. Magnesium and its composites, as the metal materials with the lowest density among metal structural materials, have good thermal conductivity, good dimensional stability, high specific strength, good biocompatibility, which can meet the requirements of energy-saving, emission reduction, environmental protection. In recent years, magnesium and its composites have found the major applications in various fields such as aerospace, automotive industry, electronics and medical industry. However, the fabrication of magnesium matrix composites is difficult, and the deformation behaviors and strengthening mechanisms of particulate reinforced magnesium matrix composites have unique characteristics. This article reviews the recent research progress of the magnesium matrix composites, including different fabrication methods and strengthening mechanisms. According to the classification of solidification rate, the advantages and disadvantages of various techniques used to fabricate magnesium matrix composites were introduced. The traditional and novel fabrication techniques were discussed. The influence mechanisms of particulates on solidification microstructures, recrystallization behaviors, texture strength and twin behaviors of magnesium matrix composites during solidification and extrusion were summarized, and the roles of particulates in solidification and extrusion of magnesium matrix composites were analyzed. The strengthening mechanisms of particulates on the mechanical properties, corrosion resistance, fatigue resistance and creep resistance of magnesium matrix composites were revealed. Finally, the development prospect and research direction of magnesium matrix composites were prospected. It is hoped that this paper can provide a reference for the further development of magnesium matrix composites.

Reliable monitoring and thorough spatiotemporal prediction of meteorological drought are crucial for early warning and decision-making regarding drought-related disasters. The utilisation of multiscale methods is effective for a comprehensive evaluation of drought occurrence and progression, given the complex nature of meteorological drought. Nevertheless, the nonlinear spatiotemporal features of meteorological droughts, influenced by various climatological, physical and environmental factors, pose significant challenges to integrated prediction that considers multiple indicators and time scales. To address these constraints, we introduce an innovative deep learning framework based on the shifted window transformer, designed for executing spatiotemporal prediction of meteorological drought across multiple scales. We formulate four prediction indicators using the standardized precipitation index and the standard precipitation evaporation index as core methods for drought definition using the ERA5 reanalysis dataset. These indicators span time scales of approximately 30 d and one season. Short-term indicators capture more anomalous variations, whereas long-term indicators attain comparatively higher accuracy in predicting future trends. We focus on the East Asian region, notable for its diverse climate conditions and intricate terrains, to validate the model's efficacy in addressing the complexities of nonlinear spatiotemporal prediction. The model's performance is evaluated from diverse spatiotemporal viewpoints, and practical application values are analysed by representative drought events. Experimental results substantiate the effectiveness of our proposed model in providing accurate multiscale predictions and capturing the spatiotemporal evolution characteristics of drought. Each of the four drought indicators accurately delineates specific facets of the meteorological drought trend. Moreover, three representative drought events, namely flash drought, sustained drought and severe drought, underscore the significance of selecting appropriate prediction indicators to effectively denote different types of drought events. This study provides methodological and technological support for using a deep learning approach in meteorological drought prediction. Such findings also demonstrate prediction issues related to natural hazards in regions with scarce observational data, complex topography and diverse microclimate systems.

Highlights MXene/TiO2 hybrids are prepared by a simple calcination treatment, and their electromagnetic response is customized by in situ atomic reconstruction engineering. Based on the excellent electromagnetic response of MXene/TiO2 hybrids, a series of electromagnetic devices are constructed. Multi-spectrum stealth is realized covering visible-light, infrared radiation and GHz.

Monitoring the quality of marine water is crucial for ensuring the health and sustainability of marine ecosystems. The conventional monitoring approach involves manual sampling using a water sampler, followed by packaging the water samples in plastic bottles and transporting them to a terrestrial laboratory for analysis. However, this method is time consuming, labor intensive, and cannot provide real-time data for addressing unforeseen circumstances. In response to these challenges, an advanced shipborne integrated platform for water quality inspection (ASIPWQI) has been proposed and implemented. This system automates the collection of multi-layer seawater samples in the vertical profile, conducts online measurements of monitoring elements, and provides real-time measurement data. In multiple sea trials, ASIPWQI successfully conducted on-site collection and measurement of a significant number of samples, meeting the water quality monitoring requirements in China’s nearshore waters. Comparative analysis of the laboratory measurement results for nutrients, heavy metals, and total phosphorus and nitrogen in water samples collected using automatic and manual methods revealed no significant differences between the two sampling approaches and demonstrated strong correlation. Further analysis using practical relative error (PRE) statistical methods showed that the data rate of most monitoring elements with relative errors less than 10% was higher than 70%, with nitrite, silicate, and phosphate even exceeding 90%. This indicate that ASIPWQI has excellent stability and applicability, offering a viable alternative to traditional manual sampling and laboratory testing. This innovation makes water quality monitoring significantly more efficient.

Glioblastoma multiforme (GBM) is one of the most prevalent and lethal primary central nervous system malignancies. GBM is notorious for its high rates of recurrence and therapy resistance and the PI3K/Akt pathway plays a pivotal role in its malignant behavior. Crebanine (CB), an alkaloid capable of penetrating the blood–brain barrier (BBB), has been shown to have inhibitory effects on proinflammatory molecules and multiple cancer cell lines via pathways such as PI3K/Akt. This study aims to investigate the efficacy and mechanisms of CB treatment on GBM. It is the first study to elucidate the anti-tumor role of CB in GBM, providing new possibilities for GBM therapy. Through a series of experiments, we demonstrate the significant anti-survival, anti-clonogenicity, and proapoptotic effects of CB treatment on GBM cell lines. Next-generation sequencing (NGS) is also conducted and provides a complete list of significant changes in gene expression after treatment, including genes related to apoptosis, the cell cycle, FoxO, and autophagy. The subsequent protein expressions of the upregulation of apoptosis and downregulation of PI3K/Akt are further proved. The clinical applicability of CB to GBM treatment could be high for its BBB-penetrating feature, significant induction of apoptosis, and blockage of the PI3K/Akt pathway. Future research is needed using in vivo experiments and other therapeutic pathways shown in NGS for further clinical or in vivo studies.

AIM: To observe the effects of N-acetylserotonin (NAS) administration on retinal ischemia-reperfusion (RIR) injury in rats and explore the underlying mechanisms involving the high mobility group box 1 (HMGB1)/receptor for advanced glycation end-products (RAGE)/nuclear factor-kappa B (NF-κB) signaling pathway. METHODS: A rat model of RIR was developed by increasing the pressure of the anterior chamber of the eye. Eighty male Sprague Dawley were randomly divided into five groups: sham group (n=8), RIR group (n=28), RIR+NAS group (n=28), RIR+FPS-ZM1 group (n=8) and RIR+NAS+ FPS-ZM1 group (n=8). The therapeutic effects of NAS were examined by hematoxylin-eosin (H&E) staining, and retinal ganglion cells (RGCs) counting. The expression of interleukin 1 beta (IL-1β), HMGB1, RAGE, and nod-like receptor 3 (NLRP3) proteins and the phosphorylation of nuclear factor-kappa B (p-NF-κB) were analyzed by immunohistochemistry staining and Western blot analysis. The expression of HMGB1 protein was also detected by enzyme-linked immunosorbent assay (ELISA). RESULTS: H&E staining results showed that NAS significantly reduced retinal edema and increased the number of RGCs in RIR rats. With NAS therapy, the HMGB1 and RAGE expression decreased significantly, and the activation of the NF-κB/NLRP3 pathway was antagonized along with the inhibition of p-NF-κB and NLRP3 protein expression. Additionally, NAS exhibited an anti-inflammatory effect by reducing IL-1β expression. The inhibitory of RAGE binding to HMGB1 by RAGE inhibitor FPS-ZM1 led to a significant decrease of p-NF-κB and NLRP3 expression, so as to the IL-1β expression and retinal edema, accompanied by an increase of RGCs in RIR rats. CONCLUSION: NAS may exhibit a neuroprotective effect against RIR via the HMGB1/RAGE/NF-κB signaling pathway, which may be a useful therapeutic target for retinal disease.

Abstract Impedance theory has become a favorite method for metasurface design as it allows perfect control of wave properties. However, its functionality is strongly limited by the condition of strict continuity of normal power flow. In this paper, it is shown that acoustic impedance theory can be generalized under the integral equivalence principle without imposing the continuity of power flow. Equivalent non-local power flow transmission is instead realized through local design of metasurface unit cells that are characterized by a passive, asymmetric impedance matrix. Based on this strategy, a beam splitter loosely respecting local power flow is designed and demonstrated experimentally. It is concluded that arbitrary wave fields can be connected through arbitrarily shaped boundaries, i.e. transformed into one another. Generalized impedance metasurface theory is expected to extend the possible design of metasurfaces and the manipulation of acoustic waves.

In the vehicle to infrastructure communication, the millimeter wave beam width is narrow and user equipment mobility is high. Therefore, effective millimeter wave beam selection is a key and challenging task. Aiming at the problem of high overhead in the beam search process, this paper proposes a millimeter-wave beam selection algorithm based on radar and location information. The proposed algorithm trains a neural network structure on the lidar and beam tracking channel datasets using the Top-k classification metric. It also predicts the best beam pair using the Global Context Net (GCNet) model. The simulation results show that the performance of the proposed algorithm is significantly improved in the classification and recognition accuracy. At the same time, it only needs to search 5 beams to approach the performance of the exhaustive search, which greatly reduces the beam search overhead.

Abstract A set of high-quality pan-genomes would help identify important genes that are still hidden/incomplete in bird reference genomes. In an attempt to address these issues, we have assembled a de novo chromosome-level reference genome of the Silkie (Gallus gallus domesticus), which is an important avian model for unique traits, like fibromelanosis, with unclear genetic foundation. This Silkie genome includes the complete genomic sequences of well-known, but unresolved, evolutionarily, endocrinologically, and immunologically important genes, including leptin, ovocleidin-17, and tumor-necrosis factor-α. The gap-less and manually annotated MHC (major histocompatibility complex) region possesses 38 recently identified genes, with differentially regulated genes recovered in response to pathogen challenges. We also provide whole-genome methylation and genetic variation maps, and resolve a complex genetic region that may contribute to fibromelanosis in these animals. Finally, we experimentally show leptin binding to the identified leptin receptor in chicken, confirming an active leptin ligand-receptor system. The Silkie genome assembly not only provides a rich data resource for avian genome studies, but also lays a foundation for further functional validation of resolved genes.

Tongxie Yaofang (TXYF) has therapeutic effect on the ulcerative colitis (UC) with liver depression and spleen deficiency syndrome. This study investigated the changes in the gut microbiota of UC rats treated with TXYF. Wistar rats were divided into three groups: Control, dinitrobenzene sulfonic acid (DNBS)-colitis, and DNBS + TXYF (n = 8 per group). UC model was constructed via intrarectally injection of DNBS (25 mg DNBS and 0.25 mL 50% ethanol); rats in DNBS + TXYF group were administered with TXYF (20.8 g/kg) for 21 days. Physiological parameters were measured. Five samples from each group were selected for metagenomic analysis. TXYF treatment significantly reduced disease activity index, colon mucosal damage index, and tumor necrosis factor-alpha level. TXYF treatment prevented DNBS-induced dysregulation of gut microbial communities. Compared with DNBS-colitis group, the abundance of Firmicutes increased significantly and that of Bacteroidetes and Proteobacteria decreased in DNBS + TXYF group. Pathways such as protein processing in the endoplasmic reticulum pathway was enriched in the DNBS-colitis group, whereas it was decreased in the DNBS + TXYF group. Thus, TXYF treatment could effectively restore the dysregulation of intestinal flora induced by UC.