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Metasurfaces enable a new degree of controlling electromagnetic (EM) wave by modulating subwavelength artificial structures. In this article, a reflection-type metasurface based on the modified Pancharatnam–Berry (P-B) phase elements is proposed to manipulate the reflected EM wave under oblique incidence. Based on the modified P-B phase, the desired linear phase gradient along the x-axis can be achieved at the interface of the metasurface by adjusting the rotation angle of the unit cells. When a circularly polarized EM wave illuminates on the metasurface obliquely, the anomalous reflected wave can be observed in a broad bandwidth with high efficiency, and the reflection angle can be predicted by the generalized snell’s law. Two metasurfaces with different phase gradients are designed in this article. The simulated results agree well with the theoretical designs, showing outstanding ability to manipulate the propagation of the EM wave. With specific phase gradient of the proposed metasurface, the anomalous reflected wave can be bent to the same side of the normal with the incident wave, which means that negative reflection effect can be achieved. Our design provides a solution to manipulate reflected beam under oblique incidence with high conversion efficiency, which has great practical applications in medical imaging, communication technology, and energy harvesting. [ABSTRACT FROM AUTHOR]

Huygens metasurface, composed of electric and magnetic dipoles, can fully control the transmission and reflection coefficient in theory. In this paper, a multi-phase hologram utilizing Huygens metasurface is presented in microwave regime. Here, we focus on the achievement of holographic rotation around the origin of Cartesian coordinates and the center of images individually. The spatial rotation operations are realized with calculated phase distribution based on time-shifting operations and rotational invariance of Fourier transform. Our designs expand the route to realize more powerful manipulations of electromagnetic (EM) wave propagation for flexible and continuous control of holographic images. [ABSTRACT FROM AUTHOR]

Two new Anderson-type polyoxometalate (POM)-based metal-organic complexes {Cu2(H2pytty)2[CrMo6(OH)5O19](H2O)8}·10H2O(1), {Cu5(pytty)2[TeMo6O24](H2O)16}·6H2O (2) (H2pytty = 3-(pyrazin-2-yl)-5-(1H-1,2,4-triazol-3-yl)-1,2,4-triazolyl) have been synthesized under hydrothermal conditions and structurally determined by single-crystal X-ray diffraction. In addition, in vitro anticancer activity of compounds 1 and 2 on three human endometrial carcinoma cells (RL-952, Ishikawa and ECC-1) was further determined via the MTT assay. [ABSTRACT FROM AUTHOR]

• Identified ten high-confidence candidate genes related to ischemic stroke through bioinformatics analyses: ARG1, LY96, ABCA1, SLC22A4, CD163, TPM2, SLC25A42, ID3, FAM102A and CD79B. • The potential regulatory relationships of ten high-confidence candidate genes based on TF-gene interaction network and TF-miRNA network. • SP1 (P = 0.0246) as the key transcription factor for the six high-confidence candidate genes ABCA1, ARG1, CD163, ID3, LY96, and SLC22A4. • The diagnostic value of ten high-confidence candidate genes was relatively high, and the area under curve ranged from 0.841 to 0.974. Stroke is the third leading cause of disability-adjusted life years worldwide, and drugs available for its treatment are limited. This study aimed to explore high-confidence candidate genes associated with ischemic stroke (IS) through bioinformatics analysis and identify potential diagnostic biomarkers and gene-drug interactions. Weighted gene coexpression network analysis (WGCNA) and differentially expressed genes (DEGs) were integrated to identify overlapping genes. Then, high-confidence candidate genes were screened by least absolute shrinkage and selection operator (LASSO) regression. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic value of high-confidence candidate genes as biomarkers for IS. The NetworkAnalyst database was used to construct the TF-gene network and miRNA-TF regulatory network of the high-confidence candidate genes. The DGIdb database was used to identified gene-drug interactions. Through the comprehensive analysis of GSE58294 and GSE16561, 10 high-confidence candidate genes were identified by LASSO regression: ARG1, LY96, ABCA1, SLC22A4, CD163, TPM2, SLC25A42, ID3, FAM102A and CD79B. FAM102A had the highest diagnostic value, and the area under curve (AUC), sensitivity and specificity values were 0.974, 0.919 and 0.936, respectively. The HPA database demonstrated that 10 high-confidence candidate genes were expressed in the brain and blood in normal humans. Finally, DGIdb database analysis identified 8 gene-drug interactions. We identified IS-related diagnostic biomarkers and gene-drug interactions that potentially provide new insights into the diagnosis and treatment of IS. [ABSTRACT FROM AUTHOR]