一种高效挖掘高维数据的频繁闭合模式算法

为了克服传统高维数据挖掘频繁闭合模式算法迭代产生子表,引起算法执行时间长和存储开销大等问题,提出了一种高效挖掘高维数据的频繁闭合模式的算法EMHCP. EMHCP算法采用一种新型结构位图表来压缩存储数据,在仅扫描数据库一次后,建立位图转换表.根据位图转换表来构建混合树结构,采用深度优先的方式和有效的剪枝策略高效挖掘出所有的闭合模式.从而有效地缩小了搜索空间,加快了处理速度.通过在生物数据库应用的实验结果表明, EMHCP算法比已有的CARPENTER和TD-close等算法更为有效.     

Operationalising “Double-Loop” Learning in Service Organisations: A Systems Approach for Creating Knowledge

Learning organisation literature has widely discussed the connections between “double-loop” learning and its significance to organisational performance, but paying little attention to tools and systems that can operationalise “double-loop” learning in organisations. This paper investigates the impact of applying a systems approach for service operations design, expressed as the Vanguard Method (Seddon, Freedom from command and control: a better way to make the work work, 2003), in order to activate “double-loop” learning in service organisations. Two case studies were conducted in the banking mortgage operations and adults’ social care services in the UK, using the dimensions of the learning organisation questionnaire (DLOQ), semi-structured interviews, observations, and documents. The findings of the cross-case analysis support the link of applying the Vanguard Method with operationalising “double-loop” learning through three main factors, namely systematic-operations improvement, organisational capacity development, and outside-in mode of work; that are all embedded into the seven dimensions of the DLOQ. The value of this paper is the introduction of a service operations design tool that can activate “double-loop” learning performance in the fast changing knowledge era. It also provides an impetus for service organisations to creatively influence employees’ competencies to effectively improve internal systems.     

全面二孩政策下对实施教育、医疗、就业配套措施的研究

全面二孩政策的实施与生殖健康、妇幼保健和入托入学等一系列行业与部门息息相关.通过调查居民二孩生育意愿,从教育、医疗和就业3个方面研究在全面二孩政策下人们产生的新需求,使用RPART分析和方差分析等方法深入分析调查数据,研究如何布局好二孩政策的配套措施,消除居民的生育顾虑,促进二孩政策的推行,解决我国面临的人口老龄化问题,优化人口结构.     

Old drugs with new skills: fenoprofen as an allosteric enhancer at melanocortin receptor 3

The efficiency of drug research and development has paradoxically declined over the last decades despite major scientific and technological advances, promoting new cost-effective strategies such as drug repositioning by systematic screening for new actions of known drugs. Here, we performed a screening for positive allosteric modulators (PAMs) at melanocortin (MC) receptors. The non-steroidal anti-inflammatory drug fenoprofen, but not the similar compound ibuprofen, presented PAM activity at MC₃, MC₄, and MC₅ receptors. In a model of inflammatory arthritis, fenoprofen afforded potent inhibition while ibuprofen was nearly inactive. Fenoprofen presented anti-arthritic actions on cartilage integrity and synovitis, effects markedly attenuated in Mc3r?/? mice. Fenoprofen displayed pro-resolving properties promoting macrophage phagocytosis and efferocytosis, independently of cyclooxygenase inhibition. In conclusion, combining repositioning with advances in G-protein coupled receptor biology (allosterism) may lead to potential new therapeutics. In addition, MC₃ PAMs emerged as a viable approach to the development of innovative therapeutics for joint diseases.     

Toxin bioportides: exploring toxin biological activity and multifunctionality

Toxins have been shown to have many biological functions and to constitute a rich source of drugs and biotechnological tools. We focus on toxins that not only have a specific activity, but also contain residues responsible for transmembrane penetration, which can be considered bioportides—a class of cell-penetrating peptides that are also intrinsically bioactive. Bioportides are potential tools in pharmacology and biotechnology as they help deliver substances and nanoparticles to intracellular targets. Bioportides characterized so far are peptides derived from human proteins, such as cytochrome c (CYCS), calcitonin receptor (camptide), and endothelial nitric oxide synthase (nosangiotide). However, toxins are usually disregarded as potential bioportides. In this review, we discuss the inclusion of some toxins and molecules derived thereof as a new class of bioportides based on structure activity relationship, minimization, and biological activity studies. The comparative analysis of the amino acid residue composition of toxin-derived bioportides and their short molecular variants is an innovative analytical strategy which allows us to understand natural toxin multifunctionality in vivo and plan novel pharmacological and biotechnological products. Furthermore, we discuss how many bioportide toxins have a rigid structure with amphiphilic properties important for both cell penetration and bioactivity.     

Skeletal muscle secretome in Duchenne muscular dystrophy: a pivotal anti-inflammatory role of adiponectin

Background

Persistent inflammation exacerbates the progression of Duchenne muscular dystrophy (DMD). The hormone, adiponectin (ApN), which is decreased in the metabolic syndrome, exhibits anti-inflammatory properties on skeletal muscle and alleviates the dystrophic phenotype of mdx mice. Here, we investigate whether ApN retains its anti-inflammatory action in myotubes obtained from DMD patients. We unravel the underlying mechanisms by studying the secretome and the early events of ApN.

Methods

Primary cultures of myotubes from DMD and control patients were treated or not by ApN after an inflammatory challenge. Myokines secreted in medium were identified by cytokine antibody-arrays and ELISAs. The early events of ApN signaling were assessed by abrogating selected genes.

Results

ApN retained its anti-inflammatory properties in both dystrophic and control myotubes. Profiling of secretory products revealed that ApN downregulated the secretion of two pro-inflammatory factors (TNFα and IL-17A), one soluble receptor (sTNFRII), and one chemokine (CCL28) in DMD myotubes, while upregulating IL-6 that exerts some anti-inflammatory effects. These changes were explained by pretranslational mechanisms. Earlier events of the ApN cascade involved AdipoR1, the main receptor for muscle, and the AMPK-SIRT1-PGC-1α axis leading, besides alteration of the myokine profile, to the upregulation of utrophin A (a dystrophin analog).

Conclusion

ApN retains its beneficial properties in dystrophic muscles by activating the AdipoR1-AMPK-SIRT1-PGC-1α pathway, thereby inducing a shift in the secretion of downstream myokines toward a less inflammatory profile while upregulating utrophin. ApN, the early events of the cascade and downstream myokines may be therapeutic targets for the management of DMD.

     

Human heart disease: lessons from human pluripotent stem cell-derived cardiomyocytes

Technical advances in generating and phenotyping cardiomyocytes from human pluripotent stem cells (hPSC-CMs) are now driving their wider acceptance as in vitro models to understand human heart disease and discover therapeutic targets that may lead to new compounds for clinical use. Current literature clearly shows that hPSC-CMs recapitulate many molecular, cellular, and functional aspects of human heart pathophysiology and their responses to cardioactive drugs. Here, we provide a comprehensive overview of hPSC-CMs models that have been described to date and highlight their most recent and remarkable contributions to research on cardiovascular diseases and disorders with cardiac traits. We conclude discussing immediate challenges, limitations, and emerging solutions.     

Epigenetics: a link between addiction and social environment

The detrimental effects of drug abuse are apparently not limited to individuals but may also impact the vulnerability of their progenies to develop addictive behaviours. Epigenetic signatures, early life experience and environmental factors, converge to influence gene expression patterns in addiction phenotypes and consequently may serve as mediators of behavioural trait transmission between generations. The majority of studies investigating the role of epigenetics in addiction do not consider the influence of social interactions. This shortcoming in current experimental approaches necessitates developing social models that reflect the addictive behaviour in a free-living social environment. Furthermore, this review also reports on the advancement of interventions for drug addiction and takes into account the emerging roles of histone deacetylase (HDAC) inhibitors in the etiology of drug addiction and that HDAC may be a potential therapeutic target at nucleosomal level to improve treatment outcomes.     

Immunoregulatory properties of the cytokine IL-34

Interleukin-34 is a cytokine with only partially understood functions, described for the first time in 2008. Although IL-34 shares very little homology with CSF-1 (CSF1, M-CSF), they share a common receptor CSF-1R (CSF-1R) and IL-34 has also two distinct receptors (PTP-ζ) and CD138 (syndecan-1). To make the situation more complex, IL-34 has also been shown as pairing with CSF-1 to form a heterodimer. Until now, studies have demonstrated that this cytokine is released by some tissues that differ to those where CSF-1 is expressed and is involved in the differentiation and survival of macrophages, monocytes, and dendritic cells in response to inflammation. The involvement of IL-34 has been shown in areas as diverse as neuronal protection, autoimmune diseases, infection, cancer, and transplantation. Our recent work has demonstrated a new and possible therapeutic role for IL-34 as a Foxp3⁺ Treg-secreted cytokine mediator of transplant tolerance. In this review, we recapitulate most recent findings on IL-34 and its controversial effects on immune responses and address its immunoregulatory properties and the potential of targeting this cytokine in human.     

基于BEMD-Copula-GARCH模型的股票投资组合VaR风险度量研究

鉴于股票波动具有显著的多尺度特征,本文引入二元经验模态分解(EMD)与二元CopulaGARCH算法,提出一种新的VaR风险度量模型,即BEMD-Copula-GARCH模型.具体地,新BEMD-Copula-GARCH模型可分为三个主要步骤:数据分析,分风险估计和总风险集成.首先,基于二元EMD模型,将复杂且相互作用的股票对分解为若干组较为简单且相互独立的分量,以降低建模难度.其次,引入二元Copula-GARCH模型,刻画各组分量间的相互关系,以度量股票投资组合在不同尺度上的分VaR值.最后,集成各分VaR值以得出最终VaR风险度量结果.实证研究以恒生指数与上证综指为数据样本构造投资组合,结果表明:本文所构建的新模型能有效度量投资组合风险,其估计精度显著优于DCC-GARCH和Copula-GARCH等现有模型.