Nanovaccine-Mediated Cell Selective Delivery of Neoantigens Potentiating Adoptive Dendritic Cell Transfer for Personalized Immunization

Neoantigen vaccines and adoptive dendritic cell (DC) transfer are major clinical approaches to initiate personalized immunity in cancer patients. However, the immunization efficacy is largely limited by the in vivo trajectory including neoantigens’ access to resident DCs and DCs’ access to lymph nodes (LNs). Herein, an innovative strategy is proposed to improve personalized immunization through neoantigen-loaded nanovaccines synergized with adoptive DC transfer. It is found that it enables selective delivery of neoantigens to resident DCs and macrophages by coating cancer cell membranes onto neoantigen-loaded nanoparticles. In addition, the nanovaccines promote the secretion of chemokine C-C motif ligand 2 (CCL2), CCL3, and C-X-C motif ligand 10 from macrophages, thus potentiating the access of transferred DCs to LNs. This immunization strategy enables coordinated delivery of identified neoantigens and autologous tumor lysate-derived undefined antigens, leading to initiation of antitumor T cell immunity in a personalized manner. It significantly inhibits tumor growth in prophylactic and established mouse tumor models. The findings provide a new vision for potentiating adoptive cell transfer by nanovaccines, which may open the door to a transformative possibility for improving personalized immunization.     

高等级生物安全实验室通风空调系统冗余设计原则探讨

对比分析了国内外标准有关高等级生物安全实验室通风空调系统冗余设计的要求。结合我国已有高等级生物安全实验室,重点分析了送风机、排风机、排风高效过滤器冗余设计的具体实施形式和存在的问题,给出了冗余设计原则建议。     

Mesoporous g-C3N4 decorated by Ni2P nanoparticles and CdS nanorods together for enhancing photocatalytic hydrogen evolution

Ni₂P nanoparticles and CdS nanorods were grew together on a mesoporous g-C₃N₄ through a facile in-situ solvothermal approach. Under visible light (λ > 400 nm), the as-prepared ternary PCN–CdS-5% Ni₂P composite displays a high H₂ evolution rate with 2905.86 μmol g^?1 h^?1, which is about 14, 18 and 279 times that of PCN–CdS, PCN–Ni₂P and PCN, respectively. The enhanced photocatalytic activity is mainly attributed to the improved separation efficiency of the photocarriers by the type II PCN–CdS heterojunction and the effective extraction of photogenerated electrons by Ni₂P. Meanwhile, Ni₂P acts as co-catalyst to provide the photocatalytic active site for hydrogen reduction. In addition, PCN–CdS-5% Ni₂P composite exerts good stability in 12-h cycles.     

Nanomaterials for radiotherapeutics-based multimodal synergistic cancer therapy

Over the past decade, numerous studies have attempted to enhance the effectiveness of radiotherapy (external beam radiotherapy and internal radioisotope therapy) for cancer treatment. However, the low radiation absorption coefficient and radiation resistance of tumors remain major critical challenges for radiotherapy in the clinic. With the development of nanomedicine, nanomaterials in combination with radiotherapy offer the possibility to improve the efficiency of radiotherapy in tumors. Nanomaterials act not only as radiosensitizers to enhance radiation energy, but also as nanocarriers to deliver therapeutic units in combating radiation resistance. In this review, we discuss opportunities for a synergistic cancer therapy by combining radiotherapy based on nanomaterials designed for chemotherapy, photodynamic therapy, photothermal therapy, gas therapy, genetic therapy, and immunotherapy. We highlight how nanomaterials can be utilized to amplify antitumor radiation responses and describe cooperative enhancement interactions among these synergistic therapies. Moreover, the potential challenges and future prospects of radio-based nanomedicine to maximize their synergistic efficiency for cancer treatment are identified.

     

基于DSP的智能电源控制单元设计与实现

本文利用TI公司TMS320F28335芯片高效的浮点运算能力,结合片上丰富的外设,设计并实现了一种具有高可靠性的智能电源控制单元。该控制单元周期性地对各片上外设进行自检维护,完成多路负载通道控制、电压、电流的实时监控,并对故障进行指示、处理和上报,同时提供人机交互界面更新状态信息。经过验证,该控制单元工作稳定,具备良好的工程应用价值。     

Viscoplastic behavior of AA7075 aluminum alloy at high strain rate

Journal of Mechanical Science and Technology - The flow stress increases with the increase in strain rate. This phenomenon is the strain rate effect of plastic deformation. Hopkinson experiment...     

A practical reliability assessment approach and its application for pile-stabilized slopes using FORM and support vector machine

Bulletin of Engineering Geology and the Environment - Many uncertainties exist in pile-stabilized slopes which make their design substantially complicated. In this paper, a first-order reliability...     

A Student's t-based density peaks clustering with superpixel segmentation (tDPCSS) method for image color clustering

Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results.