Exosomal CD44 Cooperates with Integrin α6β4 to Support Organotropic Metastasis via Regulating Tumor Cell Motility and Target Host Cell Activation

Rapid metastasis to vital organs such as the lung, liver, and brain is responsible for the vast majority of pancreatic cancer deaths. Liver metastasis of pancreatic cancer accounts for the high mortality rate in patients. Exosomes derived from pancreatic cancer cells tend to be enriched in proteins that are anchored to the cell membrane, supporting the reprogramming of the tumor microenvironment and the progression of distant metastatic lesions. For the first time, our study has demonstrated that cluster of differentiation 44 (CD44), a transmembrane glycoprotein delivered by exosomes, is involved in the metastatic process of pancreatic cancer. Moreover, CD44 was found to interact with integrin α6β4 to form a complex, thereby remodeling intracellular skeleton proteins, and to promote tumor cell motility through the activation of the Src and Ras signaling cascades. Notably, we also demonstrated that the CD44–α6β4 complex can be delivered to the target region via the paracrine effects of exosomes. The selective uptake of CD44-competent tumor exosomes by liver cells activated fibrotic pathways and generated a pre-metastatic niche by stimulating the cytokines, proinflammatory factors, and growth factors that ultimately support tumor metastasis. Our results suggest the potential application of exosomal CD44 as a biomarker for the clinical diagnosis of and therapy for pancreatic cancer.     

当代产品设计中的侘寂文化审美观照与流变研究

目的 小众文化往往通过工业设计以产品载体的形式赋予大众式的体验。而产品体验所蕴含的文化审美观不可避免会发生变化,设计师需要对创意过程中的审美流变具有更清晰的认知。方法 针对侘寂文化,立足于物化审美的设计视角,分析工业设计如何将侘寂文化演变为适合于大众审美取向的视觉特征,以及侘寂的精神内涵在迈向大众体验过程中的误读和异化。结论 提出了当代产品物象呈现的禅意风格,是工业设计寻求文化体验的普适性的缩影,而小众文化的流变则是消费主义影响设计难以避免的结果。     

基于小生境遗传算法的雷达组网误差配准

多传感器信息融合须进行误差配准。传统的误差配准技术采用RTQC、最小二乘法或极大似然估计法,将非线性方程进行线性化,而线性化过程会引入误差。给出了一种基于小生境遗传算法的误差配准算法,该方法在采用基于ECEF坐标系的误差配准技术的基础上,克服了将非线性方程线性化带来的误差,并在传统遗传算法的基础上引入小生境技术,提高了遗传算法全局寻优能力、收敛速度以及系统误差估计结果的精度。最后,将该方法与基于ECEF坐标系的最小二乘法及传统遗传算法进行了比较,仿真实验结果验证了算法的有效性。     

促进清洁能源消纳的多网联合优化与决策模型

针对我国西南地区,弃电量大、清洁能源消纳受阻的问题,考虑清洁能源外送消纳的方式,本文以互联电网各自运行成本最小为目标,建立了多网联合多目标优化模型。基于小生境多目标粒子群算法对模型进行求解,应用基于熵权法的逼近理想解排序法进行最佳均衡解决策。以云南送广东、广西的“一个送端+两个受端”系统为例进行实例分析,结果表明：小生境多目标粒子群算法求解得到了均匀分布的近似Pareto前沿;基于熵权法的逼近理想解排序法决策得到的最佳均衡解显示,送端电网清洁能源消纳率达到100%,外送通道日利用小时数最大,表明多网联合优化计算能够大大提高清洁能源的消纳能力和外送通道的利用程度。     

对南京储烟昆虫群落的初步研究

１９９２年４月到１９９３年４月对南京仓储烟叶及露天垛储存烟叶上的昆虫群落进行了研究。从分类类群及生态功能上对这两类昆虫群落的结构进行了分析和研究，估计出了它们各自包含的物种数及最大可能漏查的物种数，确定了常见种和优势种；计算和分析了这两类群落物种的时间生态位宽度和时间生态位重叠指数；对储烟昆虫群落的多样性指数和均匀性指数也进行了计算和分析，最后研究了储烟昆虫群落的季节格局，并组建了群落及优势种的消长模型。     

免疫记忆遗传算法及其完全收敛性研究

指出多模态优化中现有小生境遗传算法(NGA)和简单子群遗传算法(SSGA)无法实现完全收敛。受精英个体保留策略的启示,基于免疫系统的记忆细胞机制设计了免疫记忆遗传算法(IMGA),利用马尔柯夫链为数学工具,从理论上证明了NGA不能完全收敛而IMGA能够完全收敛。选择小生境遗传算法与该文算法进行了对比仿真实验,不仅验证了理论上的完全收敛性结论,同时验证了所提算法求解多模态问题的有效性、快速收敛能力及其收敛的稳定性。     

Exosomes and Brain Metastases: A Review on Their Role and Potential Applications

Brain metastases (BM) are a frequent complication in patients with advanced stages of cancer, associated with impairment of the neurological function, quality of life, prognosis, and survival. BM treatment consists of a combination of the available cancer therapies, such as surgery, radiotherapy, chemotherapy, immunotherapy and targeted therapies. Even so, cancer patients with BM are still linked to poor prognosis, with overall survival being reported as 12 months or less. Intercellular communication has a pivotal role in the development of metastases, therefore, it has been extensively studied not only to better understand the metastization process, but also to further develop new therapeutic strategies. Exosomes have emerged as key players in intercellular communication being potential therapeutic targets, drug delivery systems (DDS) or biomarkers. In this Review, we focus on the role of these extracellular vesicles (EVs) in BM formation and their promising application in the development of new BM therapeutic strategies.     

蟒河硅藻生态位研究

对山西省蟒河风景区的着生硅藻进行采样并在实验室内观察,共设10个采样点,共有17个属的硅藻种类。首先,用Levins生态位宽度公式和Pinaka生态位重叠指数公式计算了样本中17个属的生态位宽度和生态位重叠度,并对各属的生态位宽度和生态位重叠度进行了探讨。结果表明,在17个属中,菱形藻属、舟形藻属和曲壳藻属等的生态位宽度值最大,而且生态位大的属与其他属的生态位重叠度也相对较大。其次,对17个属进行相关系数的计算,并进行属间相关性分析。结果表明,所有属对中,呈正相关的属对占89.5%,负相关的属对占3.3%,其余7.2%是不相关属对。这些属的生态位和相关性指示了不同样点的水体状况。     

基于种群小生境微粒群算法的前向神经网络设计

根据自然界中鱼鸟等所具有的种群运动特征,借鉴递阶编码的思想,构造出一种种群小生境微粒群算法,具有小生境内个体微粒自由运动特征分量和小生境种群运动特征分量分层递阶进化的特征,克服了标准微粒群算法或其改进算法在多蜂函数寻优时出现的微粒“早熟”现象,应用该算法进行三层前向神经网络连接权值和网络结构联合并行自适应设计,在混沌时间序列预测中显示了良好的性能。     

基于隔离小生境粒子群算法的APF优化配置

随着非线性负载的广泛应用,传统负荷端分散的谐波治理方式弊端渐显。以中小型电网中有源电力滤波器的集中补偿配置为目标,设计一种基于隔离小生境粒子群算法的APF优化配置方法。建立了有源电力滤波器的优化配置数学模型,以节点电压畸变率均方根为目标函数,并使用罚函数处理约束条件。改进后的粒子群算法兼顾全局与局部寻优能力,避免陷入局部最优点。在阐述所提优化配置方法流程的基础上,IEEE算例分析表明该配置方法可以同时进行APF位置和容量的寻优,治理后系统各节点总谐波电压畸变率小于4%,谐波附加损耗降低90%以上,实现对单、多谐波源系统电能质量的有效治理。