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In remote sensing image fusion, the conventional Convolutional Neural Networks (CNNs) extract local features of the image through layered convolution, which is limited by the receptive field and struggles to capture global features. Transformer utilizes self-attention to capture long-distance dependencies in images, which has a global receptive field, but the computational cost for high-resolution images is excessively high. In response to the above issues, this paper draws inspiration from the FusionNet network, harnessing the local detail acquisition capability of CNNs and the global data procuring capacity of Transformer. It presents a novel method for remote sensing image sharpening named Guided Filtering-Cross Stage Partial Network-Transformer, abbreviated as GF-CSTNet. This solution unifies the strengths of Guided Filtering (GF), Cross Stage Partial Network (CSPNet), and Transformer. Firstly, this method utilizes GF to enhance the acquired remote sensing image data. The CSPNet and Transformer structures are then combined to further enhance fusion performance by leveraging their respective advantages. Subsequently, a Rep-Conv2Former method is designed to streamline attention and extract diverse receptive field features through a multi-scale convolution modulator block. Simultaneously, a reparameterization module is constructed to integrate the multiple branches generated during training into a unified branch during inference, thereby optimizing the model’s inference speed. Finally, a residual learning module incorporating attention has been devised to augment the modeling and feature extraction capabilities of images. Experimental results obtained from the GaoFen-2 and WorldView-3 datasets demonstrate the effectiveness of the proposed GF-CSTNet approach. It effectively extracts detailed information from images while avoiding the problem of spectral distortion.

What are the main findings? A physics-aware, modular and vectorized architecture (PLMT-Net) achieves competitive accuracy on the Argoverse 1 dataset while reducing model parameters and inference time. Embedding physics priors at two levels—interaction-target filtering and physics-guided graph attention—improves the physical plausibility and stability of multi-agent trajectory prediction. What are the implications of the main findings? The method offers a practical path to real-time, resource-constrained deployment without sacrificing prediction quality. Lightweight physics priors integrated into learned attention provide a generalizable design pattern that can enhance robustness and physical feasibility in future trajectory-forecasting systems. Accurate and efficient multi-agent trajectory prediction remains a core challenge for autonomous driving, particularly in modeling complex interactions while maintaining physical plausibility and computational efficiency. Many existing methods- especially those based on large transformer architectures- tend to overlook physical constraints, leading to unrealistic predictions and high deployment costs. In this work, we propose a lightweight trajectory prediction framework that integrates physical information to enhance interaction modeling and runtime performance. Our method introduces two physically inspired strategies: (1) a constraint-guided mechanism is used to filter irrelevant or distracting neighbors, and (2) a physics-aware attention module is applied to steer attention weights toward physically plausible interactions. The overall architecture adopts a modular and vectorized design, effectively reducing model complexity and inference latency. Experiments on the Argoverse V1 dataset, comparing against multiple existing methods, demonstrate that our approach achieves a favorable balance among accuracy, physical feasibility, and efficiency, running in real time on a commodity desktop GPU. Future work will focus on validating its performance on embedded hardware.

A dual‐polarized 256‐element integrated phased‐array antenna is presented, with an operating frequency range covering the 5G NR N257 band (i.e., 26.5–29.5 GHz). By adopting an integrated phased array technology with cost‐effective fabrication, multifunctional circuits can be implemented in high‐density configurations, thereby reducing system footprint without sacrificing performance. A design methodology for the dual‐polarized antennas with high isolation is employed to enhance the cross‐polarization suppression. The proposed phased array supports scanning angles of ± $\\pm$ 40∘ $40^\\circ$and ± $\\pm$ 60∘ $60^\\circ$in the azimuth and elevation planes, respectively. The typical effective isotropic radiated power (EIRP) of the dual‐polarized antenna is greater than 61 dBm with the 5G NR 400‐MHz 64‐QAM modulation (EVM < $<$5.6% $\\%$ ). A 256‐element dual‐polarized phased‐array antenna is presented. Integrated phased‐array implementation methodology and high‐isolation dual‐polarized antenna technology are employed, achieving effective isotropic radiated powers (EIRPs) of greater than 70 dBm at P‐1dB and 61 dBm with 400‐MHz 64‐QAM modulation, respectively, along with a large scanning angle of ±60∘ $\\pm 60^{\\circ }$in the elevation plane.

NLRP3 inflammasome is a multiple protein complex sensing exogenous or endogenous stimuli, and aberrant activation of the NLRP3 inflammasome is implicated in various inflammatory disorders. While numerous small‐molecule compounds targeting NLRP3 inflammasome activity have been developed, most have encountered limited success in clinical translation. Through screening of a kinase compound library, GSK461364 is identified as a potent and selective NLRP3 inflammasome inhibitor. Notably, GSK461364 confers significant protective effects in murine models of LPS‐induced endotoxemia and DSS‐induced colitis. Mechanistic study reveals that GSK461364 exerts its inhibitory effects via targeting Polo‐like Kinase 1(PLK1). Specifically, that PLK1‐mediated phosphorylation of NEK7, likely occurring at evolutionarily conserved serine residues (Ser221 and Ser260), is shown to enhance NEK7‐NLRP3 binding, a critical step for NLRP3 inflammasome assembly. These findings not only establish GSK461364 as a novel therapeutic candidate for NLRP3‐driven inflammatory diseases but also provide new insights into the regulatory mechanisms governing inflammasome activation through post‐translational modification. Schematic diagram of the mechanism by which GSK461364 inhibits NLRP3 inflammasome activation. GSK461364 inhibits the phosphorylation of NEK7 likely at serine 221 and serine 260 by suppressing the activity of PLK1, thereby restraining the formation of the NLRP3 inflammasome.

Osteosarcoma (OS) is a primary malignant tumor of bone occurring in young adults. OS stem cells (OSCs) play an important role in the occurrence, growth, metastasis, drug resistance and recurrence of OS. CD133 is an integral membrane glycoprotein, which has been identified as an OSC marker. However, the mechanisms of metastasis, chemoresistance, and progression in CD133(+) OSCs need to be further explored. In this study, we aim to explore differences in miRNA levels between CD133(+) and CD133(−) cells from the MG-63 cell line. We found 20 differentially expressed miRNAs (DEmiRNAs) (16 upregulated and 4 downregulated) in CD133(+) cells compared with CD133(−) cells. Hsa-miR-4485-3p, hsa-miR-4284 and hsa-miR-3656 were the top three upregulated DEmiRNAs, while hsa-miR-487b-3p, hsa-miR-493-5p and hsa-miR-431-5p were the top three downregulated DEmiRNAs. In addition, RT-PCR analysis confirmed that the expression levels of hsa-miR-4284, hsa-miR-4485-3p and hsa-miR-3656 were significantly increased, while the expression levels of hsa-miR-487b-3p, hsa-miR-493-5p, and hsa-miR-431-5p were significantly decreased in CD133(+) cells compared with CD133(−) cells. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that predicted or validated target genes for all 20 DEmiRNAs or the selected 6 DEmiRNAs participated in the “PI3K-Akt signaling pathway,” “Wnt signaling pathway,” “Rap1 signaling pathway,” “Cell cycle” and “MAPK signaling pathway”. Among the selected six DEmiRNAs, miR-4284 was especially interesting. MiR-4284 knockdown significantly reduced the sphere forming capacity of CD133(+) OS cells. The number of invasive CD133(+) OS cells was markedly decreased after miR-4284 knockdown. In addition, miR-4284 knockdown increased the p-β-catenin levels in CD133(+) OS cells. In conclusion, RNA-seq analysis revealed DEmiRNAs between CD133(+) and CD133(−) cells. MiRNAs might play significant roles in the function of OSCs and could serve as targets for OS treatment. MiR-4284 prompted the self-renewal and invasion of OSCs. The function of miR-4284 might be associated with the Wnt signaling pathway.

Recent study implicates that gastric cancer stem cells (CSCs) are capable of generating multiple types of cells to promote tumor growth and heterogeneity important for the development of gastric cancer. However, knowledge is limited regarding the expression and characteristics of marker-positive gastric CSCs. Therefore, gastric CSCs from a series of human gastric cancer cell lines (SNU-5, SNU-16, BGC-823, PAMC-82, MKN-45, and NCI-N87) using four putative CSC surface markers (CD44, CD90, CD133, and epithelial-cell adhesion molecule) were investigated the underlying mechanisms regulating such subpopulations. Only SNU-5 and SNU-16 exhibited independent co-expression of CD44+ and CD90+, which exhibited spheroid-colony formation in vitro and tumor formation in immunodeficient mice. Functional studies revealed that CD44+ cells were more invasive compared with CD90+ cells, whereas CD90+ cells exhibited higher levels of proliferation than CD44+ cells. Furthermore, serial xenotransplantation in mice of CD44+/CD90+ cells derived from SNU-5 and SNU-16 revealed rapid growth of CD90+ cells in subcutaneous lesions and a high metastatic capacity of CD44+ cells in the lung. Mechanistic analyses revealed that CD44+ cells underwent epithelial-to-mesenchymal transition (EMT) following acquisition of mesenchymal features, whereas CD90+ cells enhanced the activation of retinoblastoma phosphorylation at Ser780 and oncogenic cell cycle regulators. The expression of CD44 and CD90 in gastric cancer tissues was associated with distant metastasis and the differentiation state of tumors. These results demonstrated that CD44 and CD90 are specific biomarkers capable of identifying and isolating metastatic and tumorigenic CSCs through their ability to regulate EMT and the cell cycle in gastric cancer cell lines.

Gastric cancer (GC) is a common malignant tumor in the digestive system and a significant health burden worldwide. In this study, we found that hsa-let-7d-5p was upregulated in GC cells, promoted GC cell proliferation, migration, and invasion, and reduced apoptosis. Moreover, we found that the expression of PRDM5 (PR domain protein 5) was downregulated in GC cells and upregulated in GC cells treated with hsa-let-7d-5p inhibitor. Further investigation showed that hsa-let-7d-5p was the target of PRDM5, and the functions of hsa-let-7d-5p on GC progression were rescued by PRDM5 overexpression in GC cells. Collectively, our findings suggested that hsa-let-7d-5p promoted the development of GC by targeting PRDM5, indicating that hsa-let-7d-5p could be a promising therapeutic molecule for the treatment of gastric cancer.

Following the publication of the article, a concerned reader drew to the authors' attention that, in Fig. 1B and C on p. 316, two pairs of the data panels showing the results from invasion and migration assay experiments appeared to be overlapping, such that they would have been derived from the same original sources where they were intended to show the results from different experiments; moreover, on p. 1698, the '17‑AAG / MG‑63' data panels in Fig. 3B and C were also overlapping, albeit the images were presented at a different scale and in a slightly different orientation. After having examined their original data, the authors have realized that these figures were inadvertently assembled incorrectly. The corrected versions of Figs. 1 and 3, now showing the correct data in Fig. 1C (where the errors made in compiling the figure had occurred) and the correct data for the '17‑AAG / MG‑63' data panel in Fig. 3C, are shown on the next two pages. These corrections do not grossly affect either the results or the conclusions reported in this work. The authors all agree to the publication of this Corrigendum, and are grateful to the Editor of for granting them the opportunity to correct the errors that were made during the assembly of these figures. Lastly, the authors apologize to the readership for any inconvenience these errors may have caused. [Oncology Reports 44: 313‑324, 2020; DOI: 10.3892/or.2020.7597].

Multiple drug resistance is a major obstacle to the successful treatment of osteosarcoma (OS). Recent studies have demonstrated that a subset of cells, referred to as OS stem cells (OSCs), play a crucial role in the acquisition of multiple drug resistance. Therefore, an improved understanding of OS biology and pathogenesis is required to advance the development of targeted therapies aimed at eradicating this particular subset of cells in order to reverse acquired chemoresistance in OS. The aim of the present study was to assess the anti-OSC effects of 17-AAG and determine the underlying molecular mechanism. Heat shock protein 90 expression was found to be increased in sarcosphere cells and was positively associated with cancer stem cell characteristics. In addition, 17-AAG was able to suppress the stem cell-like phenotype of OS cells. Mechanistically, 17-AAG inhibited OSC-like properties and chemoresistance through glycogen synthase kinase (GSK) 3β inactivation-mediated repression of the Hedgehog signaling pathway. The findings of the present study provided comprehensive evidence for the inhibition of OSC properties and chemoresistance by 17-AAG through repression of the GSK3β/Hedgehog signaling pathway, suggesting that 17-AAG may be a promising therapeutic agent for targeting OSCs.