Role of the HSP70 Co-Chaperone SIL1 in Health and Disease

Cell surface and secreted proteins provide essential functions for multicellular life. They enter the endoplasmic reticulum (ER) lumen co-translationally, where they mature and fold into their complex three-dimensional structures. The ER is populated with a host of molecular chaperones, associated co-factors, and enzymes that assist and stabilize folded states. Together, they ensure that nascent proteins mature properly or, if this process fails, target them for degradation. BiP, the ER HSP70 chaperone, interacts with unfolded client proteins in a nucleotide-dependent manner, which is tightly regulated by eight DnaJ-type proteins and two nucleotide exchange factors (NEFs), SIL1 and GRP170. Loss of SIL1′s function is the leading cause of Marinesco-Sjögren syndrome (MSS), an autosomal recessive, multisystem disorder. The development of animal models has provided insights into SIL1′s functions and MSS-associated pathologies. This review provides an in-depth update on the current understanding of the molecular mechanisms underlying SIL1′s NEF activity and its role in maintaining ER homeostasis and normal physiology. A precise understanding of the underlying molecular mechanisms associated with the loss of SIL1 may allow for the development of new pharmacological approaches to treat MSS.     

基于WebGL的3D立库可视化系统设计与实现

针对当前扩大化和普及化的仓储物流,提出了一种3D自动化立体仓库可视化系统的实现方案,用以解决仓储系统中遇到的数据不直观的问题。该系统采用JavaScript编程语言,以Three.js引擎为基础,构建了基于WebGL的三维自动化立体仓库的可视化系统,该系统能有效直观的进行仓储管理,适合现代化仓储企业的管理需求。     

Efficient Flexible M-Tree Bulk Loading Using FastMap and Space-Filling Curves

Many database applications currently deal with objects in a metric space. Examples of such objects include unstructured multimedia objects and points of interest (POIs) in a road network. The M-tree is a dynamic index structure that facilitates an efficient search for objects in a metric space. Studies have been conducted on the bulk loading of large datasets in an M-tree. However, because previous algorithms involve excessive distance computations and disk accesses, they perform poorly in terms of their index construction and search capability. This study proposes two efficient M-tree bulk loading algorithms. Our algorithms minimize the number of distance computations and disk accesses using FastMap and a space-filling curve, thereby significantly improving the index construction and search performance. Our second algorithm is an extension of the first, and it incorporates a partitioning clustering technique and flexible node architecture to further improve the search performance. Through the use of various synthetic and real-world datasets, the experimental results demonstrated that our algorithms improved the index construction performance by up to three orders of magnitude and the search performance by up to 20.3 times over the previous algorithm.     

宰前倒挂应激对鸭血凝胶特性的影响

宰前倒挂因能有效提高屠宰效率成为肉鸭宰杀前必经的一个工艺过程，但倒挂往往会加剧肉鸭的应激程度，影响其血液品质，已成为工厂生产中亟待解决的问题。因此，本实验旨在借助血液学与凝血相关指标探究宰前倒挂应激对鸭血凝胶特性的影响。在屠宰前，将40 只樱桃谷鸭随机分为2 个处理组：对照组和宰前倒挂组（宰前倒挂2.5 min），屠宰后采集血样并制备血凝块，随后分析血液指标（应激指标、血液学指标、凝血指标）以及鸭血凝胶特性。结果表明，宰前倒挂组鸭血中皮质酮激素及促肾上腺皮质激素的水平均高于对照组，说明实验所建立宰前倒挂模型成立。倒挂应激后，红细胞计数、血小板计数、血红蛋白质量浓度增加，红细胞比容、平均红细胞体积及平均血小板体积增大；凝血酶原的水平极显著上升（P＜0.01），组织因子的水平显著上升（P＜0.05）。宰前倒挂最终导致鸭血凝胶化加快，鸭血凝胶体系中水分迁移速率增大，结合水与自由水比例减少，不易流动水比例增大，质构特性和保水性变差。研究揭示了宰前倒挂应激通过影响鸭血的血液学指标和凝血系统从而改变其凝胶行为及凝胶特性，可为工厂改善应激对鸭血凝胶品质的影响提供理论依据。