These collagen hydrogels enabled investigation of the responses of cell lines (fibroblasts, epithelial cells, and myoblasts) and primary cells (rat cardiomyocytes) to soft topographic cues such as thosein vivounder the positive correlation betweenCandE. These cells adhered directly to the collagen hydrogels and chose to stay atop or spontaneously migrate into them depending onE, that is, the density of the collagen network,C. We revealed that the cell morphology and actin cytoskeleton organization conformed to the topographic cues, even when they are as soft asin vivoECM. The stiffer microgrooves on collagen hydrogels aligned cells more effectively, except HeLa cells that underwent drastic changes in cell morphology. These collagen hydrogels may not only reducein vivoandin vitrocell behavioral disparity but also facilitate artificial ECM design to control cell function and fate for applications in tissue engineering and regenerative medicine.The cancer microenvironment influences tumor progression and metastasis and is pivotal to consider when designingin vivo-like cancer models. Current preclinical testing platforms for cancer drug development are mainly limited to 2D cell culture systems that poorly mimic physiological environments and traditional, low throughput animal models. The aim of this work was to produce a tunable testing platform based on 3D printed scaffolds (3DPS) with a simple geometry that, by extracellular components and response of breast cancer reporter cells, mimics patient-derived scaffolds (PDS) of breast cancer. Here, the biocompatible polysaccharide alginate was used as base material to generate scaffolds consisting of a 3D grid containing periostin and hydroxyapatite. Breast cancer cell lines (MCF7 and MDA-MB-231) produced similar phenotypes and gene expression levels of cancer stem cell, epithelial-mesenchymal transition, differentiation and proliferation markers when cultured on 3DPS and PDS, contrasting conventional 2D cultures. Importantly, cells cultured on 3DPS and PDS showed scaffold-specific responses to cytotoxic drugs (doxorubicin and 5-fluorouracil) that were different from 2D cultured cells. In conclusion, the data presented support the use of a tunable alginate-based 3DPS as a tumor model in breast cancer drug discovery.Objective.Achieving high precision rapid serial visual presentation (RSVP) task often requires many electrode channels to obtain more information. However, the more channels may contain more redundant information and also lead to its limited practical applications. Therefore, it is necessary to reduce the number of channels to enhance the classification performance and users experience. Furthermore, cross-subject generalization has always been one of major challenges in electroencephalography channel reduction, especially in the RSVP paradigm. Most search-based channel selection method presented in the literature are single-objective methods, the classification accuracy (ACC) is usually chosen as the only criterion.Approach.In this article, the idea of multi-objective optimization was introduced into the RSVP channel selection to minimize two objectives classification error and the number of channels. selleck inhibitor By combining a multi-objective evolutionary algorithm for solving large-scale sparse problems and hierarchical discriminant component analysis (HDCA), a novel channel selection method for RSVP was proposed. After that, the cross-subject generalization validation through the proposed channel selection method.Main results.The proposed method achieved an average ACC of 95.41% in a public dataset, which is 3.49% higher than HDCA. The ACC was increased by 2.73% and 2.52%, respectively. Besides, the cross-subject generalization models in channel selection, namely special-16 and special-32, on untrained subjects show that the classification performance is better than the Hoffmann empirical channels.Significance.The proposed channel selection method could reduce the calibration time in the experimental preparation phase and obtain a better accuracy, which is promising application in the RSVP scenario that requires low-density electrodes.Thermosets possess diverse physical and chemical properties and thus they are widely used in various applications such as electronic packaging, construction, and automotive industries. However, their poor thermal conductivity and weak mechanical performance jeopardize their continual spread in modern industry. In this study, boron nitride nanosheets (BNNSs) were employed to promote both mechanical and thermal properties of epoxy nanocomposites. BNNSs and their epoxy nanocomposites were fabricated usingin situsolvent ultrasonication andin situpolymerization, respectively. Thermal conductivity was enhanced by 153% increment in epoxy/BNNS nanocomposite at 7 wt% in comparison with neat epoxy. In parallel, Young's modulus, lap shear strength, fracture toughness (K1C) and energy release rate (G1C) increased by 69%, 31%, 122% and 118%, respectively at 1 wt% BNNSs. Moreover, fatigue life and strength of lap shear joints were significantly improved upon adding BNNSs. A numerical model of the single lap shear joint was developed to validate the accuracy of the material constants obtained. Epoxy/BNNS nanocomposites exhibited an outstanding mechanical performance as well as high thermal conductivity giving them merits to widen their applications in electronic and automotive industry.Thethree-dimensional (3D) imaging and quantitative analysis of bone microvasculature are important to describe angiogenesis involvement in bone metastatic processes. Here, we propose an algorithm based on marker-controlled watershed for the 3D segmentation of vessels and bone in mouse bone imaged with a contrast agent using synchrotron radiation micro-computed tomography (SR-μCT). Markers were generated using hysteresis thresholding and morphological filters, and the control surface was constructed using the monogenic signal phase asymmetry. The accuracy and robustness of the proposed method were evaluated on a series of synthetic volumes generated to mimic the vessel, bone and background structures. Different contrast between different structures, as well as different noise levels were considered. A series of multi-class synthetic volumes were segmented using the proposed method, and the overall segmentation quality was evaluated using the Matthews correlation coefficient (MCC) by comparing to the ground truth.