Stereo image pairs can be used to improve the performance of super-resolution (SR) since additional information is provided from a second viewpoint. However, it is challenging to incorporate this information for SR since disparities between stereo images vary significantly. In this paper, we propose a parallax-attention stereo superresolution network (PASSRnet) to integrate the information from a stereo image pair for SR. Specifically, we introduce a parallax-attention mechanism with a global receptive field along the epipolar line to handle different stereo images with large disparity variations. We also propose a new and the largest dataset for stereo image SR (namely, Flickr1024). Extensive experiments demonstrate that the parallax-attention mechanism can capture correspondence between stereo images to improve SR performance with a small computational and memory cost. Comparative results show that our PASSRnet achieves the state-of-the-art performance on the Middlebury, KITTI 2012 and KITTI 2015 datasets.

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Single-frame infrared small target (SIRST) detection aims at separating small targets from clutter backgrounds. With the advances of deep learning, CNN-based methods have yielded promising results in generic object detection due to their powerful modeling capability. However, existing CNN-based methods cannot be directly applied to infrared small targets since pooling layers in their networks could lead to the loss of targets in deep layers. To handle this problem, we propose a dense nested attention network (DNA-Net) in this paper. Specifically, we design a dense nested interactive module (DNIM) to achieve progressive interaction among high-level and low-level features. With the repetitive interaction in DNIM, the information of infrared small targets in deep layers can be maintained. Based on DNIM, we further propose a cascaded channel and spatial attention module (CSAM) to adaptively enhance multilevel features. With our DNA-Net, contextual information of small targets can be well incorporated and fully exploited by repetitive fusion and enhancement. Moreover, we develop an infrared small target dataset (namely, NUDT-SIRST) and propose a set of evaluation metrics to conduct comprehensive performance evaluation. Experiments on both public and our self-developed datasets demonstrate the effectiveness of our method. Compared to other state-of-the-art methods, our method achieves better performance in terms of probability of detection (P d ), false-alarm rate (Fa), and intersection of union (IoU ).

To solve the challenge of poor knee repair, an aptamer-bilayer scaffold is designed for autologous mesenchymal stem cell (MSC) recruitment and osteochondral regeneration. The scaffold can efficiently recruit MSCs to the defect and induce the directional differentiation of MSCs, thus successfully achieving simultaneous regeneration of cartilage and bone in the knee joint.

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Persistent luminescence nanoparticles (PLNPs) are an emerging group of promising luminescent materials that can remain luminescent after the excitation ceases. In the past decade, PLNPs with intriguing optical properties have been developed and their applications in biomedicine have been widely studied. Due to the ultra-long decay time of persistent luminescence, autofluorescence interference in biosensing and bioimaging can be efficiently eliminated. Moreover, PLNPs can remain luminescent for hours, making them valuable in bio-tracing. Also, persistent luminescence imaging can guide cancer therapy with a high signal-to-noise ratio (SNR) and superior sensitivity. Briefly, PLNPs are demonstrated to be a newly-emerging class of functional materials with unprecedented advantages in biomedicine. In this review, we summarized recent advances in the preparation of PLNPs and the applications of PLNPs in biosensing, bioimaging and cancer therapy.

Extracellular vesicles (EVs) are involved in the regulation of cell physiological activity and the reconstruction of extracellular environment. Matrix vesicles (MVs) are a type of EVs released by bone-related functional cells, and they participate in the regulation of cell mineralization. Here, we report bioinspired MVs embedded with black phosphorus (BP) and functionalized with cell-specific aptamer (denoted as Apt-bioinspired MVs) for stimulating biomineralization. The aptamer can direct bioinspired MVs to targeted cells, and the increasing concentration of inorganic phosphate originating from BP can facilitate cell biomineralization. The photothermal effect of the Apt-bioinspired MVs can also promote the biomineralization process by stimulating the upregulated expression of heat shock proteins and alkaline phosphatase. In addition, the Apt-bioinspired MVs display outstanding bone regeneration performance. Our strategy provides a method for designing bionic tools to study the mechanisms of biological processes and advance the development of medical engineering.