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.     

Research on Crop Irrigation Schedules Under Deficit Irrigation—A Meta-analysis

Water Resources Management - Increasing water consumption in agriculture due to global climate change has posed considerable challenges to food security, thus improving the efficiency of water...     

Photoregulation of Gene Expression with Ligand-Modified Caged siRNAs through Host/Guest Interaction

Small interfering RNA (siRNA) can effectively silence target genes through Argonate 2 (Ago2)-induced RNA interference (RNAi). It is very important to control siRNA activity in both spatial and temporal modes. Among different masking strategies, photocaging can be used to regulate gene expression through light irradiation with spatiotemporal and dose-dependent resolution. Many different caging strategies and caging groups have been reported for light-activated siRNA gene silencing. Herein, we describe a novel caging strategy that increases the blocking effect of RISC complex formation/process through host/guest (including ligand/receptor) interactions, thereby enhancing the inhibition of caged siRNA activity until light activation. This strategy can be used as a general approach to design caged siRNAs for the photomodulation of gene silencing of exogenous and endogenous genes.     

梁结构振动支承约束反力控制

支承或连接构件对梁结构的动力学性能有至关重要影响,必须保证其在振动过程中不发生破坏或者失效。通过合理设计和布局附加弹性支承可以实现对这些重要连接构件所承受约束反力的控制。应用微分变换法推导含附加支承的梁结构支承约束反力及其对于附加支承位置和刚度的灵敏度表达式,并通过优化设计附加支承位置和刚度实现具有弹性约束端的简支梁结构各支承约束反力的平衡,可提高结构的动力学性能。     

Simultaneous fractionation of multiple classes of polyphenols from honeybush tea using solid-phase extraction

The structural diversity of polyphenols and the inherent limitations of current extraction techniques pose a challenge to extract polyphenols using a simple and green method. Hence, in this study, a method was developed to simultaneously fractionate multiple classes of polyphenols by only varying ethanol-water solutions. Honeybush tea, which is rich in polyphenols, was selected as a model for this study. Solvent extraction followed by solid-phase extraction (SPE) was developed to obtain a polyphenol-rich fraction from six honeybush samples. Based on a gradient elution programme (10%, 30%, 50%, 70% and 90% (v/v) ethanol-water solution) of SPE, the Strata X cartridge showed a better recovery of most targeted polyphenols under 0.9 mL of the drying volume and 1 mL min⁻¹ of the dispensing speed. The elution programme for fractionating most polyphenols was as follows: single elution with 50% ethanol, followed by twice elution with 70% ethanol. The antioxidant capacity was used to analyse the differences among the polyphenol-rich fractions from six honeybush samples. Principal component analysis (PCA) revealed that unfermented C. genistoides (GG) has the greatest antioxidant capacity among the honeybush species studied. Additionally, mangiferin, isomangiferin and vicenin-2 were the main contributors to the antioxidant capacity in six honeybush fractions according to the correlation study.     

Dual effect synergistically triggered Ce:(Y,Tb)3(Al,Mn)5O12 transparent ceramics enabling a high color-rendering index and excellent thermal stability for white LEDs

Ce:Y₃Al₅O₁₂ transparent ceramics (TCs) with appropriate emission light proportion and high thermal stability are significant to construct white light emitting diode devices with excellent chromaticity parameters. In this work, strategies of controlling crystal-field splitting around Ce³⁺ ion and doping orange-red emitting ion, were adopted to fabricate Ce:(Y,Tb)₃(Al,Mn)₅O₁₂ TCs via vacuum sintering technique. Notably, 85.4 % of the room-temperature luminescence intensity of the TC was retained at 150 °C, and the color rendering index was as high as 79.8. Furthermore, a 12 nm red shift and a 16.2 % increase of full width at half maximum were achieved owing to the synergistic effects of Tb³⁺ and Mn²⁺ ions. By combining TCs with a 460 nm blue chip, a warm white light with a low correlated color temperature of 4155 K was acquired. Meanwhile, the action mechanism of Tb³⁺ ion and the energy transfer between Ce³⁺ and Mn²⁺ ions were verified in prepared TCs.     

Performance analysis of bit error rate of data link system under pulse LFM interference in time-varying rayleigh channel

Wireless Networks - In such mobile platforms as ships and aircraft, the detection and reconnaissance devices are near to the communication facilities. When working at the same time, they will...     

Nacre-Inspired,Liquid Metal-Based Ultrasensitive Electronic Skin by Spatially Regulated Cracking Strategy

The realization of liquid metal-based wearable systems will be a milestone toward high-performance, integrated electronic skin. However, despite the revolutionary progress achieved in many other components of electronic skin, liquid metal-based flexible sensors still suffer from poor sensitivity due to the insufficient resistance change of liquid metal to deformation. Herein, a nacre-inspired architecture composed of a biphasic pattern (liquid metal with Cr/Cu underlayer) as “bricks” and strain-sensitive Ag film as “mortar” is developed, which breaks the long-standing sensitivity bottleneck of liquid metal-based electronic skin. With 2 orders of magnitude of sensitivity amplification while maintaining wide (>85%) working range, for the first time, liquid metal-based strain sensors rival the state-of-art counterparts. This liquid metal composite features spatially regulated cracking behavior. On the one hand, hard Cr cells locally modulate the strain distribution, which avoids premature cut-through cracks and prolongs the defect propagation in the adjacent Ag film. On the other hand, the separated liquid metal cells prevent unfavorable continuous liquid-metal paths and create crack-free regions during strain. Demonstrated in diverse scenarios, the proposed design concept may spark more applications of ultrasensitive liquid metal-based electronic skins, and reveals a pathway for sensor development via crack engineering.     

Generating Questions Based on Semi-Automated and End-to-End Neural Network

With the emergence of large-scale knowledge base, how to use triple information to generate natural questions is a key technology in question answering systems. The traditional way of generating questions require a lot of manual intervention and produce lots of noise. To solve these problems, we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions. The semi-automated model can generate question templates and real questions combining the knowledge base and center graph. The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network. Meanwhile, the attention mechanism is utilized in the decoding layer, which makes the triples and generated questions more relevant. Finally, the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.