Adipose-Derived Stem Cells in the Treatment of Perianal Fistulas in Crohn’s Disease: Rationale,Clinical Results and Perspectives

Between 20 to 25% of Crohn’s disease (CD) patients suffer from perianal fistulas, a marker of disease severity. Seton drainage combined with anti-TNFα can result in closure of the fistula in 70 to 75% of patients. For the remaining 25% of patients there is room for in situ injection of autologous or allogenic mesenchymal stem cells such as adipose-derived stem/stromal cells (ADSCs). ADSCs exert their effects on tissues and effector cells through paracrine phenomena, including the secretome and extracellular vesicles. They display anti-inflammatory, anti-apoptotic, pro-angiogenic, proliferative, and immunomodulatory properties, and a homing within the damaged tissue. They also have immuno-evasive properties allowing a clinical allogeneic approach. Numerous clinical trials have been conducted that demonstrate a complete cure rate of anoperineal fistulas in CD ranging from 46 to 90% of cases after in situ injection of autologous or allogenic ADSCs. A pivotal phase III-controlled trial using allogenic ADSCs (Alofisel^®) demonstrated that prolonged clinical and radiological remission can be obtained in nearly 60% of cases with a good safety profile. Future studies should be conducted for a better knowledge of the local effect of ADSCs as well as for a standardization in terms of the number of injections and associated procedures.     

Chiral Scandium‐Catalysed Enantioselective Ring‐Opening of meso‐Epoxides with N‐Heterocycle,Alcohol and Thiol Derivatives in Water

In the presence of catalytic amounts of Sc(OSO₃C₁₂H₂₅)₃ and a chiral bipyridine ligand, asymmetric ring‐opening of meso‐epoxides with aromatic N‐heterocycles, an alcohol and thiols proceeded smoothly to afford the corresponding products in moderate to good yields (34–85 %) with high to excellent enantioselectivities (74–96 % ee). Water was used as the sole and essential solvent in these important enantioselective transformations.     

BK Polyomavirus bkv-miR-B1-5p: A Stable Micro-RNA to Monitor Active Viral Replication after Kidney Transplantation

Background: Bkv-miR-B1-5p is a viral micro-RNA (miRNA) specifically produced during BK polyomavirus (BKPyV) replication. Recent studies have suggested using bkv-miR-B1-5p as a biomarker to monitor viral infection and predict complications in kidney transplant patients. To identify the technical limitations of this miRNA quantification in biological samples, knowledge of its stability and distribution in the extracellular compartment is necessary. Moreover, a proof of concept for using bkv-miR-B1-5p as a biomarker of active replication in chronic infection is still missing in the published literature. Methods: The stability of bkv-miR-B1-5p was evaluated in samples derived from cell cultures and in urine from BKPyV-infected kidney transplant recipients. The miRNA was quantified in different fractions of the extracellular compartment, including exosomes, and protein binding was evaluated. Finally, we developed an in vitro model for chronic culture of BKPyV clinical isolates to observe changes in the bkv-miR-B1-5p level during persistent infections. Results: Bkv-miR-B1-5p is a stable biomarker in samples from humans and in vitro experiments. Marginally associated with the exosomes, most of the circulating bkv-miR-B1-5p is bound to proteins, especially Ago2, so the miRNA quantification does not require specific exosome isolation. The bkv-miR-B1-5p level is predictable of viral infectivity, which makes it a potential specific biomarker of active BKPyV replication after kidney transplantation.     

Study on the Signal Control System of Urban Traffic with a Genetic Algorithm

In the paper the aim and meaning of traffic microscopic simulation is discussed first, and then three sub-models of the system are established, e. i. the model for random generation of the vehicles, the model for car-following and lane change influenced by an adjacent vehicle, and the model for control and optimization of intersection with signal. Optimization of the traffic signal timing with a genetic algorithm and a microscopic simulation is carried out. It represents a novel approach to solving optimal signal timing.     

Spermine Derivatives of Indole-3-carboxylic Acid,Indole-3-acetic Acid and Indole-3-acrylic Acid as Gram-Negative Antibiotic Adjuvants

The discovery of new antibiotic adjuvants is an attractive option for overcoming antimicrobial resistance. We have previously reported the discovery of a bis-6-bromoindolglyoxylamide derivative of spermine as being able to enhance the action of antibiotics against Gram-negative bacteria but suffers from being cytotoxic and red-blood cell haemolytic. A series of analogues was prepared exploring variation of the indolglyoxylamide unit, to include indole-3-acrylic, indole-3-acetic and indole-3-carboxylate units, and evaluated for antibiotic enhancing properties against a range of Gram-negative bacteria, and for intrinsic antimicrobial, cytotoxic and haemolytic properties. Two spermine derivatives, bearing 5-bromo-indole-3-acetic acid ( 17 ) and 5-methoxy-indole-3-acrylic acid ( 14 ) end groups were found to exhibit good to moderate antibiotic adjuvant activities for doxycycline towards the Gram-negative bacteria Pseudomonas aeruginosa, Escherichia coli and Klebsiella pneumoniae, but with more modest intrinsic antimicrobial activity and greatly reduced cytotoxic and haemolytic properties. The mechanism of action of the latter derivative identified its ability to disrupt the outer membranes of bacteria and to inhibit the AcrAB-TolC efflux pump directly or by inhibiting the proton gradient.     

CORRELATION BETWEEN ASO AND AAO

Using a 34 years database consisting of sea level pressure and sea ice concentration, the relationship between Antarctic Oscillation (AAO) and Antarctic Sea-ice Oscillation (ASO) was investigated. Firstly, Empirical Orthogonal Function (EOF) analysis depicts the spatial variability of AAO and ASO and Antarctic Sea-ice Oscillation Index (ASOI) was defined for the first time. Secondly, power spectrum and headlag correlation analysis show that ASO and AAO have the same periods of quasi-three years, quasi-one year and quasihalf a year. Corresponding to AAO, ASO has an evident antioscillation after one and half a year.     

Estimation of Separation of Electrolytes and Organic Compounds by Nanofiltration Membranes Using an Irreversible Thermodynamic Modei

Nanofiltration separation has become a popular technique for removing large organic molecules and inorganic substances from water. It is achieved by a combination of three mechanisms: electrostatic repulsion, sieving and diffusion. In the present work, a modei based on irreversible thermodynamics is extended and used to estimate rejection of inorganic salts and organic substances. Binary systems are modeled, where the feed contains an ion that is much less permeable to the membrane as compared with the other ion. The two modei parameters are estimated by fitting the modei to the experimental data. Variation of these parameters with the composition of the feed is described by an empirical correlation. This work attempts to describe transport through the nanofiltration membranes by a simple model.     

基于单领航者相对位置测量的多AUV协同导航系统定位性能分析

自主水下航行器 (Autonomous underwater vehicle, AUV) 的协同导航是解决水下导航定位问题的重要方法, 其中导航系统的定位误差增长特性是衡量其定位性能的关键指标. 本文针对单领航者相对位置测量的多 AUV 协同导航系统, 利用扩展卡尔曼滤波方法建立了导航系统的整体定位误差关于相对位置量测误差的传递方程. 在此基础上, 通过求解系统定位误差随时间演化的代数黎卡提方程, 得到了其在稳态情形下的方差上界估计. 理论分析表明, 单领航 AUV 协同导航系统的整体定位误差有界收敛且与初始化滤波方差无关, 具有良好的综合性能. 最后, 仿真实例验证了文中理论分析结果的正确性.     

Adaptive partitioning schemes for bipartite ranking

Recursive partitioning methods are among the most popular techniques in machine learning. The purpose of this paper is to investigate how to adapt this methodology to the bipartite ranking problem. Following in the footsteps of the TreeRank approach developed in Clémençon and Vayatis (Proceedings of the 2008 Conference on Algorithmic Learning Theory, 2008 and IEEE Trans. Inf. Theory 55(9):4316–4336, 2009), we present tree-structured algorithms designed for learning to rank instances based on classification data. The main contributions of the present work are the following: the practical implementation of the TreeRank algorithm, well-founded solutions to the crucial issues related to the splitting rule and the choice of the “right” size for the ranking tree. From the angle embraced in this paper, splitting is viewed as a cost-sensitive classification task with data-dependent cost. Hence, up to straightforward modifications, any classification algorithm may serve as a splitting rule. Also, we propose to implement a cost-complexity pruning method after the growing stage in order to produce a “right-sized” ranking sub-tree with large AUC. In particular, performance bounds are established for pruning schemes inspired by recent work on nonparametric model selection. Eventually, we propose indicators for variable importance and variable dependence, plus various simulation studies illustrating the potential of our method.