The Function of Sialidase Revealed by Sialidase Activity Imaging Probe

Sialidase cleaves sialic acid residues from glycans such as glycoproteins and glycolipids. In the brain, desorption of the sialic acid by sialidase is essential for synaptic plasticity, learning and memory and synaptic transmission. BTP3-Neu5Ac has been developed for sensitive imaging of sialidase enzyme activity in mammalian tissues. Sialidase activity in the rat hippocampus detected with BTP3-Neu5Ac increases rapidly by neuronal depolarization. It is presumed that an increased sialidase activity in conjunction with neural excitation is involved in the formation of the neural circuit for memory. Since sialidase inhibits the exocytosis of the excitatory neurotransmitter glutamate, the increased sialidase activity by neural excitation might play a role in the negative feedback mechanism against the glutamate release. Mammalian tissues other than the brain have also been stained with BTP3-Neu5Ac. On the basis of information on the sialidase activity imaging in the pancreas, it was found that sialidase inhibitor can be used as an anti-diabetic drug that can avoid hypoglycemia, a serious side effect of insulin secretagogues. In this review, we discuss the role of sialidase in the brain as well as in the pancreas and skin, as revealed by using a sialidase activity imaging probe. We also present the detection of influenza virus with BTP3-Neu5Ac and modification of BTP3-Neu5Ac.     

Chronically Elevated Exogenous Glucose Elicits Antipodal Effects on the Proteome Signature of Differentiating Human iPSC-Derived Pancreatic Progenitors

The past decade revealed that cell identity changes, such as dedifferentiation or transdifferentiation, accompany the insulin-producing β-cell decay in most diabetes conditions. Mapping and controlling the mechanisms governing these processes is, thus, extremely valuable for managing the disease progression. Extracellular glucose is known to influence cell identity by impacting the redox balance. Here, we use global proteomics and pathway analysis to map the response of differentiating human pancreatic progenitors to chronically increased in vitro glucose levels. We show that exogenous high glucose levels impact different protein subsets in a concentration-dependent manner. In contrast, regardless of concentration, glucose elicits an antipodal effect on the proteome landscape, inducing both beneficial and detrimental changes in regard to achieving the desired islet cell fingerprint. Furthermore, we identified that only a subgroup of these effects and pathways are regulated by changes in redox balance. Our study highlights a complex effect of exogenous glucose on differentiating pancreas progenitors characterized by a distinct proteome signature.     

Maternal Exposure to Dibutyl Phthalate (DBP) or Diethylstilbestrol (DES) Leads to Long-Term Changes in Hypothalamic Gene Expression and Sexual Behavior

Xenobiotic exposure during pregnancy and lactation has been linked to perinatal changes in male reproductive outcomes and other endocrine parameters. This pilot study wished to assess whether brief maternal exposure of rats to xenobiotics dibutyl phthalate (DBP) or diethylstilbestrol (DES) might also cause long-term changes in hypothalamic gene expression or in reproductive behavior of the resulting offspring. Time-mated female Sprague Dawley rats were given either DBP (500 mg/kg body weight, every second day from GD14.5 to PND6), DES (125 µg/kg body weight at GD14.5 and GD16.5 only), or vehicle (n = 8–12 per group) and mild endocrine disruption was confirmed by monitoring postnatal anogenital distance. Hypothalamic RNA from male and female offspring at PND10, PND24 and PND90 was analyzed by qRT-PCR for expression of aromatase, oxytocin, vasopressin, ER-alpha, ER-beta, kisspeptin, and GnRH genes. Reproductive behavior was monitored in male and female offspring from PND60 to PND90. Particularly, DES treatment led to significant changes in hypothalamic gene expression, which for the oxytocin gene was still evident at PND90, as well as in sexual behavior. In conclusion, maternal xenobiotic exposure may not only alter endocrine systems in offspring but, by impacting on brain development at a critical time, can have long-term effects on male or female sexual behavior.     

常规水处理工艺对内分泌干扰物的去除

介绍了上海杨树浦水厂、宁波水系、天津水司常规水处理工艺净化去除内分泌干扰物及降低内分泌干扰活性的生产规模的测定情况。常规水处理工艺对13种中的11种内分泌干扰物有一定的去除效果，对内分泌干扰活性为阳性的水能转变为阴性，但也有小部分情况出厂水的干扰物浓度高于水源水，水源水内分泌干扰活性为阴性，而出厂水反而为阳性的情况，作者对这一情况进行了分析和探讨。     

吐温修饰脂肪酶的研究

分别用甲醛和戊二醛作为偶联剂,共价连接吐温80和猪胰脂肪酶,回收共价修饰脂肪酶,并且比较修饰酶与自然酶在性质上的差异。当甲醛和戊二醛浓度相同时,用甲醛连接的修饰酶的活力最高,而用戊二醛连接的修饰酶的氨基连接效率高。当用不同浓度的甲醛修饰时,发现浓度为1．25mg·mL的甲醛连接的修饰酶的活力最高。在碱性条件下,修饰酶比自然酶的活力高,在中性、酸性条件下,自然酶的活力高     

Data-enabled learning and control algorithms for intelligent glucose management: The state of the art

External insulin administration is an effective way for patients with diabetes mellitus to regulate their blood glucose. Multiple daily injections (MDIs), sensor-augmented pump (SAP) and artificial pancreas (AP) are widely adopted approaches in insulin therapy. With the increasing popularity of continuous glucose monitoring (CGM) sensors, a large number of data-enabled learning and control algorithms have been developed for MDI, SAP and AP. In this paper, we perform a systemic review concerning the state-of-the-art methodologies that are developed for MDI, SAP and AP with feedback from CGM data or other available data, from a systems and control perspective. The review characterizes the traditional learning and control methods developed for the MDI, SAP and AP, including run-to-run control, proportional–integral–derivative control, fuzzy logic control and model predictive control, as well as the discussions on the roles of machine learning technologies in MDI, SAP and AP. Finally, potential future directions on the algorithm architecture design, a unified control framework for MDI, SAP and AP algorithm design and practical usage of the MDI, SAP and AP are discussed.     

基于3D路径聚合高分辨率网络的胰腺分割

目的 胰腺的准确分割是胰腺癌识别和分析的重要前提。现有基于深度学习的主流胰腺分割网络大多是编码—解码结构,对特征图采用先降低再增加分辨率的方式,严重丢失了胰腺位置和细节信息,导致分割效果不佳。针对上述问题,提出了基于3D路径聚合高分辨率网络的胰腺分割方法。方法 首先,为了捕获更多3D特征上下文信息,将高分辨率网络中的2D运算拓展为3D运算;其次,提出全分辨特征路径聚合模块,利用连续非线性变换缩小全分辨率输入图像与分割头网络输出特征语义差异的同时,减少茎网络下采样丢失的位置和细节信息对分割结果的影响;最后,提出多尺度特征路径聚合模块,利用渐进自适应特征压缩融合方式,避免低分辨率特征通道过度压缩导致的信息内容损失。结果 在公开胰腺数据集上,提出方法在Dice系数（Dice similarity coefficient,DSC）、Jaccard系数（Jaccard index,JI）、精确率（precision）和召回率（recall）上相比3D高分辨率网络（3D high-resolution net,3DHRNet）分别提升了1.41%、2.09%、2.35%和0.49%,相比具有代表性编码—解码结构的胰腺分割方法,取得了更高的分割精度。结论 本文提出的3D路径聚合高分辨率网络（3D pathaggregation high-resolution network,3DPAHRNet）具有更强的特征位置和细节信息的保留能力,能够显著改善在腹部CT（computed tomography）图像中所占比例较小的胰腺器官的分割结果。开源代码可在https：//github.com/qiuchengjian/PAHRNet3D获得。     

基于晶格的人工内分泌系统模型及在多机器人系统中的应用

为了解决多机器人系统分布式控制问题,借鉴人体内分泌系统研究的理论成果,提出基于晶格的人工内分泌系统模型.该模型以环境晶格化为基础,以细胞智能化为依托,以累加激素为纽带,以靶细胞为导向,能够适应外环境的持续变化,保持内环境的相对稳定,充分体现人体内分泌系统的自组织和自修复特性.实验结果表明,无需复杂的集中控制策略,基于该...     

一种新的型可变r的动态匹配算法r可变动态匹配算法

鉴于动态r匹配算法对为了提高入侵检测系统的性能的重要性,通过研究内分泌系统对生物体内环境的调节机制,提出一个内分泌激素浓度的动态平衡模型及一种基于激素浓度调节的动态r匹配算法。仿真实验结果表明,该匹配算法能根据网络状态的变化,自适应地调整匹配参数,具有较好的匹配效果。     

情感多主体系统的设计与实现

多Agent在复杂多变的环境中行为的自组织是当前人工智能研究的一个热点．本文借鉴生物系统控制的理论，设计了一种多Agent的体系结构，在此结构中包含有遗传、神经和内分泌控制子系统．本文重点论述了内分泌控制子系统的作用，提出了用情感进行行为学习的新方法．在此方法中，神经系统的作用是记忆和行为决策，其行为决策的效果通过内分泌系统进行反馈，从而避免了神经网络的自学习，使得算法具有较好的求解性能．为了验征该算法的有效性，本文做了倒立模控制的仿真实验．仿真结果也表明算法具有很强的自适应求解能力．