Complementary Effects of Carbamylated and Citrullinated LL37 in Autoimmunity and Inflammation in Systemic Lupus Erythematosus

LL37 acts as T-cell/B-cell autoantigen in Systemic lupus erythematosus (SLE) and psoriatic disease. Moreover, when bound to “self” nucleic acids, LL37 acts as “danger signal,” leading to type I interferon (IFN-I)/pro-inflammatory factors production. T-cell epitopes derived from citrullinated-LL37 act as better antigens than unmodified LL37 epitopes in SLE, at least in selected HLA-backgrounds, included the SLE-associated HLA-DRB1*1501/HLA-DRB5*0101 backgrounds. Remarkably, while “fully-citrullinated” LL37 acts as better T-cell-stimulator, it loses DNA-binding ability and the associated “adjuvant-like” properties. Since LL37 undergoes a further irreversible post-translational modification, carbamylation and antibodies to carbamylated self-proteins other than LL37 are present in SLE, here we addressed the involvement of carbamylated-LL37 in autoimmunity and inflammation in SLE. We detected carbamylated-LL37 in SLE-affected tissues. Most importantly, carbamylated-LL37-specific antibodies and CD4 T-cells circulate in SLE and both correlate with disease activity. In contrast to “fully citrullinated-LL37,” “fully carbamylated-LL37” maintains both innate and adaptive immune-cells’ stimulatory abilities: in complex with DNA, carbamylated-LL37 stimulates plasmacytoid dendritic cell IFN-α production and B-cell maturation into plasma cells. Thus, we report a further example of how different post-translational modifications of a self-antigen exert complementary effects that sustain autoimmunity and inflammation, respectively. These data also show that T/B-cell responses to carbamylated-LL37 represent novel SLE disease biomarkers.     

基于概率交易模型的线下百货推荐

该文提出了一种新颖的概率交易模型PTM,针对线下百货进行个性化的推荐。传统的推荐模型,如K-近邻算法、矩阵分解等,或者仅利用局部的数据,使得模型面临线下数据极大的稀疏性挑战,或者忽略百货数据中的交易维度,使得模型损失了同一交易中多商品共现的强相关信息,最终导致它们在面对线下百货推荐问题时性能低下。针对以上的问题,本模型从交易的维度出发,建模交易记录中的共现模式,并利用全局的交易数据来学习商品的相关分量,在此基础上推断出用户的兴趣分布,实现个性化的推荐。在真实的线下百货交易数据上的实验结果表明,该模型能够极大地提高线下百货领域个性化推荐的准确性。
     

Mechanisms of histone lysine-modifying enzymes: A computational perspective on the role of the protein environment

Epigenetic pathways are involved in a wide range of diseases, including cancer and neurological disorders. Specifically, histone modifying and reading processes are the most broadly studied and are targeted by several licensed drugs. Although there have been significant advances in understanding the mechanistic aspects underlying epigenetic regulation, the development of selective small-molecule inhibitors remains a challenge.Experimentally, it is generally difficult to elucidate the atomistic basis for substrate recognition, as well as the sequence of events involved in binding and the subsequent chemical processes. In this regard, computational modelling is particularly valuable, since it can provide structural features (including transition state structures along with kinetic and thermodynamic parameters) that enable both qualitative and quantitative evaluation of the mechanistic details involved. Here, we summarize knowledge gained from computational modelling studies elucidating the role of the protein environment in histone-lysine modifying and reading mechanisms. We give a perspective on the importance of calculations to aid and advance the understanding of these processes and for the future development of selective inhibitors for epigenetic regulators.     

Cysteine tagging for MS-based proteomics

Amino acid-tagging strategies are widespread in proteomics. Because of the central role of mass spectrometry (MS) as a detection technique in protein sciences, the term "mass tagging" was coined to describe the attachment of a label, which serves MS analysis and/or adds analytical value to the measurements. These so-called mass tags can be used for separation, enrichment, detection, and quantitation of peptides and proteins. In this context, cysteine is a frequent target for modifications because the thiol function can react specifically by nucleophilic substitution or addition. Furthermore, cysteines present natural modifications of biological importance and a low occurrence in the proteome that justify the development of strategies to specifically target them in peptides or proteins. In the present review, the mass-tagging methods directed to cysteine residues are comprehensively discussed, and the advantages and drawbacks of these strategies are addressed. Some concrete applications are given to underline the relevance of cysteine-tagging techniques for MS-based proteomics.     

Analysis of the Site-Specific Myoglobin Modifications in the Melibiose-Derived Novel Advanced Glycation End-Product

MAGE (melibiose-derived advanced glycation end-product) is the glycation product generated in the reaction of a model protein with melibiose. The in vivo analog accumulates in several tissues; however, its origin still needs explanation. In vitro MAGE is efficiently generated under dry conditions in contrast to the reaction carried in an aqueous solvent. Using liquid chromatography coupled with mass spectrometry, we analyzed the physicochemical properties and structures of myoglobin glycated with melibiose under different conditions. The targeted peptide analysis identified structurally different AGEs, including crosslinking and non-crosslinking modifications associated with lysine, arginine, and histidine residues. Glycation in a dry state was more efficient in the formation of structures containing an intact melibiose moiety (21.9%) compared to glycation under aqueous conditions (15.6%). The difference was reflected in characteristic fluorescence that results from protein structural changes and impact on a heme group of the model myoglobin protein. Finally, our results suggest that the formation of in vitro MAGE adduct is initiated by coupling melibiose to a model myoglobin protein. It is confirmed by the identification of intact melibiose moieties. The intermediate glycation product can further rearrange towards more advanced structures, including cross-links. This process can contribute to a pool of AGEs accumulating locally in vivo and affecting tissue biology.     

基于肽序列标签的蛋白质翻译后修饰中的过滤算法

大量的质谱数据无法被鉴定或是鉴定的精度不够高,特别是在肽段数据库较大时,普通的算法精度下降很快。提出一种新的盲搜索算法,此算法基于一种全新的基于相似关系度量的打分模型。为了处理大规模问题,同时还应用了基于母离子质量和肽序列标签的前过滤方法,使得此算法在较大规模的数据库上精度得到很好的保证。实验结果表明,对于规模为10000, 20000, 50000的肽段数据库,其鉴定准确率分别为78.3%,74.2%,65.5%。随着数据库规模的增大,算法的鉴定准确率保持得较好。     

一种铝电解多功能机组主梁刚性修复方法及效果分析

简述了铝电解多功能机组结构、用途及使用环境,并对有限元方法及其与传统方法的区别进行了描述。叙述了机组主要承载部件主梁的重要性和影响寿命的关键指标,并通过介绍一种主梁刚性修复的方法,采用有限元计算分析,验证和探讨了该修复方法的效果,为主梁改造、优化设计、修复等展示了现代虚拟试验方法的优越性和工程实际问题处理的重要性。     

热敏纸的新进展

本文扼要综述了热敏纸的发展和分类,并介绍了几种新型热敏纸。     

PRM、PTM组合调Q钕玻璃激光系统输出特性研究

介绍了脉冲反射式（PRM）、脉冲透射式（PTM）组合电光调Q激光系统的主要工作原理，并对影响其输出特性的主要参数进行了较系统的理论分析，给出了光束中两偏振分量间的相位差与晶体两端听加的电压之间的关系，系统输出能量透过率与所加电压间的关系。通过实验对组合调Q钕玻璃激光系统输出特性进行了测试，得到了较为理想的结果。