Revealing the Fate of Transplanted Stem Cells In Vivo with a Novel Optical Imaging Strategy

Stem‐cell‐based regenerative medicine holds great promise in clinical practices. However, the fate of stem cells after transplantation, including the distribution, viability, and the cell clearance, is not fully understood, which is critical to understand the process and the underlying mechanism of regeneration for better therapeutic effects. Herein, we develop a dual‐labeling strategy to in situ visualize the fate of transplanted stem cells in vivo by combining the exogenous near‐infrared fluorescence imaging in the second window (NIR‐II) and endogenous red bioluminescence imaging (BLI). The NIR‐II fluorescence of Ag₂S quantum dots is employed to dynamically monitor the trafficking and distribution of all transplanted stem cells in vivo due to its deep tissue penetration and high spatiotemporal resolution, while BLI of red‐emitting firefly luciferase (RfLuc) identifies the living stem cells after transplantation in vivo because only the living stem cells express RfLuc. This facile strategy allows for in situ visualization of the dynamic trafficking of stem cells in vivo and the quantitative evaluation of cell translocation and viability with high temporal and spatial resolution, and thus reports the fate of transplanted stem cells and how the living stem cells help, regeneration, for an instance, of a mouse with acute liver failure.     

3D Bioprinting: from Benches to Translational Applications

Over the last decades, the fabrication of 3D tissues has become commonplace in tissue engineering and regenerative medicine. However, conventional 3D biofabrication techniques such as scaffolding, microengineering, and fiber and cell sheet engineering are limited in their capacity to fabricate complex tissue constructs with the required precision and controllability that is needed to replicate biologically relevant tissues. To this end, 3D bioprinting offers great versatility to fabricate biomimetic, volumetric tissues that are structurally and functionally relevant. It enables precise control of the composition, spatial distribution, and architecture of resulting constructs facilitating the recapitulation of the delicate shapes and structures of targeted organs and tissues. This Review systematically covers the history of bioprinting and the most recent advances in instrumentation and methods. It then focuses on the requirements for bioinks and cells to achieve optimal fabrication of biomimetic constructs. Next, emerging evolutions and future directions of bioprinting are discussed, such as freeform, high‐resolution, multimaterial, and 4D bioprinting. Finally, the translational potential of bioprinting and bioprinted tissues of various categories are presented and the Review is concluded by exemplifying commercially available bioprinting platforms.     

基于双向LSTM和GBDT的中医文本关系抽取模型

为解决采用softmax作为长短期记忆网络分类器导致实体关系识别模型泛化能力不足,不能较好适用中医实体关系抽取等问题,提出一种融合梯度提升树的双向长短期记忆网络的关系识别算法（BILSTM-GBDT）。先采用word2vec对中医文本进行向量化表示,再利用基于注意力机制的双向长短期记忆网络提取高阶特征,最后采用集成分类模型梯度提升树作为特征分类器,提高关系识别效果。在中医等多个关系语料库上的实验结果表明,该模型与传统SVM方法、GBDT方法及其深度学习方法相比,均有更高的精确率、召回率和◢F◣值。     

新型养老环境下的药品投送机器人系统

针对室内医疗系统信息化程度低、远程监控不足、药品投递研究偏少和当前系统设备无法满足实际需求等不足,提出了基于云技术与物联网药品投递智能系统框架;采用多核嵌入式系统、RFID、IEEE 802.11通信协议、开放云平台等构建了新型室内医疗系统与药品投送机器人系统;设计了远程移动端和PC端管理系统;构建相关试验环境,对系统与设备的相关性能进行测试,验证系统的合理性与可行性.实验结果表明：网络节点最快的控制周期为48 s/次,平均周期48.3 s/次,系统配送一颗药物平均花费时间4.19 s.系统上传云端数据最快上传储存时间为2.1 s,平均花费5.21 s,通信成功率大于90%.     

基于移动Agent的野战远程诊疗系统的应用研究

随着现代野战医疗的需要及其网络技术的发展,野战医疗诊断系统已经成为当前的一个研究热点.本文介绍了移动Agent的相关技术,并利用它的技术优势,针对野战远程医疗诊断系统的特点和现状,提出了一个基于移动Agent技术的远程医疗诊断系统的设计,并且给出了具体的思路和方法,进一步完善了野战远程医疗诊断中智能性、灵活性不足等问题.     

基于自适应模糊PID的中药提取温度控制

以某制药厂中药提取系统为研究对象,分析中药提取工段的工艺设备和传热过程,建立简化模型.针对提取工段温度控制非线性、时变性、纯滞后的特点,设计自适应模糊PID控制器,并进行了仿真研究.仿真结果表明采用参数自整定模糊PID控制,系统调节时间短,响应速度快,具有较好的鲁棒稳定性.利用仿真得出的模糊控制参数表于某中药厂提取温控系统中进行在线PID整定,应用表明,使用此控制方法可有效减少温浸动态提取中的温度波动,达到良好的提取效果.     

物流业务辅助支持系统的设计与实现

把基于案例推理技术用于中医诊疗专家系统的知识表示和推理.提出一个系统模型,介绍案例推理的基本结构,案例提取网以及案例提取算法,对系统中案例的学习和修正机制进行了说明,给出用基于案例的解释来生成诊断结果的解释性说明,以及辅助构建基于案例的中医诊疗辅助教学系统.对系统的特点进行总结,指出进一步研究发展方向.