Probucol mitigates high-fat diet-induced cognitive and social impairments by regulating brain redox and insulin resistance.

Probucol has been utilized as a cholesterol-lowering drug with antioxidative properties. However, the impact and fundamental mechanisms of probucol in obesity-related cognitive decline are unclear. In this study, male C57BL/6J mice were allocated to a normal chow diet (NCD) group or a high-fat diet (HFD) group, followed by administration of probucol to half of the mice on the HFD regimen. Subsequently, the mice were subjected to a series of behavioral assessments, alongside the measurement of metabolic and redox parameters. Notably, probucol treatment effectively alleviates cognitive and social impairments induced by HFD in mice, while exhibiting no discernible influence on mood-related behaviors. Notably, the beneficial effects of probucol arise independently of rectifying obesity or restoring systemic glucose and lipid homeostasis, as evidenced by the lack of changes in body weight, serum cholesterol levels, blood glucose, hyperinsulinemia, systemic insulin resistance, and oxidative stress. Instead, probucol could regulate the levels of nitric oxide and superoxide-generating proteins, and it could specifically alleviate HFD-induced hippocampal insulin resistance. These findings shed light on the potential role of probucol in modulating obesity-related cognitive decline and urge reevaluation of the underlying mechanisms by which probucol exerts its beneficial effects.

GLPanoDepth: Global-to-Local Panoramic Depth Estimation.

Depth estimation is a fundamental task in many vision applications. With the popularity of omnidirectional cameras, it becomes a new trend to tackle this problem in the spherical space. In this paper, we propose a learning-based method for predicting dense depth values of a scene from a monocular omnidirectional image. An omnidirectional image has a full field-of-view, providing much more complete descriptions of the scene than perspective images. However, fully-convolutional networks that most current solutions rely on fail to capture rich global contexts from the panorama. To address this issue and also the distortion of equirectangular projection in the panorama, we propose Cubemap Vision Transformers (CViT), a new transformer-based architecture that can model long-range dependencies and extract distortion-free global features from the panorama. We show that cubemap vision transformers have a global receptive field at every stage and can provide globally coherent predictions for spherical signals. As a general architecture, it removes any restriction that has been imposed on the panorama in many other monocular panoramic depth estimation methods. To preserve important local features, we further design a convolution-based branch in our pipeline (dubbed GLPanoDepth) and fuse global features from cubemap vision transformers at multiple scales. This global-to-local strategy allows us to fully exploit useful global and local features in the panorama, achieving state-of-the-art performance in panoramic depth estimation.

The Emerging Roles of circSMARCA5 in Cancer.

Circular RNAs have a unique covalent closed-loop structure, which is mainly formed by the reverse splicing of exons from a precursor mRNA. With the development of key technologies such as high-throughput sequencing and the advancement of bioinformatics in recent years, our understanding of circular RNAs has become increasingly more detailed, and their abnormal expression in a variety of cancers has attracted increasing attention. Studies have shown that circSNARCA5 not only plays a crucial role in the occurrence and development of cancer but may also serve as a reliable indicator for tumor screening or a good marker for evaluating cancer prognosis. Nevertheless, there are no reviews focusing on the relationship between circSMARCA5 and cancer. Therefore, we will first explain the main biological characteristics of circSMARCA5, such as biogenesis and biological effects. Then, the focus will be on its role and significance in cancer. Finally, we will summarize the known information on circSMARCA5 in cancer and discuss future research prospects.

Composite organic-inorganic nanoparticles as Raman labels for tissue analysis.

Composite organic-inorganic nanoparticles (COINs) are novel optical labels for detection of biomolecules. We have previously developed methods to encapsulate COINs and to functionalize them with antibodies. Here we report the first steps toward application of COINs to the detection of proteins in human tissues. Two analytes, PSA and CK18, are detected simultaneously using two different COINs in a direct binding assay, and two different COINs are shown to simultaneously label PSA in tissue samples.