Different miRNA Profiles in Plasma Derived Small and Large Extracellular Vesicles from Patients with Neurodegenerative Diseases

Identifying biomarkers is essential for early diagnosis of neurodegenerative diseases (NDs). Large (LEVs) and small extracellular vesicles (SEVs) are extracellular vesicles (EVs) of different sizes and biological functions transported in blood and they may be valid biomarkers for NDs. The aim of our study was to investigate common and different miRNA signatures in plasma derived LEVs and SEVs of Alzheimer’s disease (AD), Parkinson’s disease (PD), Amyotrophic Lateral Sclerosis (ALS) and Fronto-Temporal Dementia (FTD) patients. LEVs and SEVs were isolated from plasma of patients and healthy volunteers (CTR) by filtration and differential centrifugation and RNA was extracted. Small RNAs libraries were carried out by Next Generation Sequencing (NGS). MiRNAs discriminate all NDs diseases from CTRs and they can provide a signature for each NDs. Common enriched pathways for SEVs were instead linked to ubiquitin mediated proteolysis and Toll-like receptor signaling pathways and for LEVs to neurotrophin signaling and Glycosphingolipid biosynthesis pathway. LEVs and SEVs are involved in different pathways and this might give a specificity to their role in the spreading of the disease. The study of common and different miRNAs transported by LEVs and SEVs can be of great interest for biomarker discovery and for pathogenesis studies in neurodegeneration.     

A comparison of self-reported drug use with a urine drug screen in a working population.

This study summarized information on 162 workers who completed urine screen and self-report concerning drug use. It is the first to compare self-report of drug use in the workplace with a urine screen in which individual participant (nonaggregate) data were used. The findings indicate that agreement between the 2 methods of drug detection, although statistically significant, is at best only moderate. The level of agreement was consistent for segments of the sample when divided by sociodemographic characteristics. Although urine screen may be the more reliable and accurate method of detecting prevalence of drug use, self-report must be considered to assess drug use histories and the role of other variables. These 2 methods should be considered as complementary assessment techniques; the appropriate method depends on the conditions and purposes of the drug use study. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ordered Line Integral Methods for Computing the Quasi-Potential

The quasi-potential is a key function in the Large Deviation Theory. It characterizes the difficulty of the escape from the neighborhood of an attractor of a stochastic non-gradient dynamical system due to the influence of small white noise. It also gives an estimate of the invariant probability distribution in the neighborhood of the attractor up to the exponential order. We present a new family of methods for computing the quasi-potential on a regular mesh named the ordered line integral methods (OLIMs). In comparison with the first proposed quasi-potential finder based on the ordered upwind method (OUM) (Cameron in Phys D Nonlinear Phenom 241:1532–1550, 2012), the new methods are 1.5–4 times faster, can produce error two to three orders of magnitude smaller, and may exhibit faster convergence. Similar to the OUM, OLIMs employ the dynamical programming principle. Contrary to it, they (1) have an optimized strategy for the use of computationally expensive triangle updates leading to a notable speed-up, and (2) directly solve local minimization problems using quadrature rules instead of solving the corresponding Hamilton–Jacobi-type equation by the first order finite difference upwind scheme. The OLIM with the right-hand quadrature rule is equivalent to OUM. The use of higher order quadrature rules in local minimization problems dramatically boosts up the accuracy of OLIMs. We offer a detailed discussion on the origin of numerical errors in OLIMs and propose rules-of-thumb for the choice of the important parameter, the update factor, in the OUM and OLIMs. Our results are supported by extensive numerical tests on two challenging 2D examples.     

South African research in selected scientific areas: Status 1981–2000

The paper is a bibliometric study of the publication and citation patterns and impact of South African research 1981–2000 in five selected research fields: Animal & Plant sciences; Chemistry; Biochemistry; Microbiology & molecular biology, including genetics; and Physics, excluding Space science. Data are collected from Science Citation Index via the ISI product National Science Indicators. With the exception of Microbiology & molecular biology and Physics the results demonstrate a decrease of SA publications from 1986–1990. The SA world share declines for all five fields. First from the period 1994–1998 the Animal & plant sciences and Microbiology & molecular biology turn the decline into an increase. Absolute citation impact is increasing for all the fields from 1989–1993, except for Chemistry. One reason for the decline is a lower publication output. General & internal medicine, as an supplementary volume-heavy field observed, declines in citations until that same period from which it becomes stable, also in impact, but with a marked decrease in cited paper proportion. In citation world shares the five fields combined show positive signs also since 1989–1993, after which period the international eco-political embargo of SA was lifted. However, Biochemistry and Chemistry continue to decline during the 1990s. Citation impact relative to the world shows a similar pattern, but stagnation appears towards the end of the 1990s in all the observed fields combined. The trends are quite similar to those of Mexico and New Zealand. It is thus highly uncertain if a general citation embargo of SA occurred; yet, in some fields like the Animal & plant sciences, Veterinary science, Chemistry, and General & internal medicine there are signs that a mild citation embargo might have occurred. However, the economic embargo, combined with a significant brain drain, may have had an effect on the publication productivity, after it was lifted. For all indicators Chemistry is undergoing a marked decline during the last decade. This is in line with the negative trends for General & internal medicine, whereas some other medical specialities, biology, economics and other social sciences, the engineering fields and materials sciences keep stable or increase their production. SA is in line with the Mexican development but below that of New Zealand, seemingly losing ground to the developed countries. This revised version was published online in June 2006 with corrections to the Cover Date.     

Controlling swimming and crawling in a fish robot using a central pattern generator

Online trajectory generation for robots with multiple degrees of freedom is still a difficult and unsolved problem, in particular for non-steady state locomotion, that is, when the robot has to move in a complex environment with continuous variations of the speed, direction, and type of locomotor behavior. In this article we address the problem of controlling the non-steady state swimming and crawling of a novel fish robot. For this, we have designed a control architecture based on a central pattern generator (CPG) implemented as a system of coupled nonlinear oscillators. The CPG, like its biological counterpart, can produce coordinated patterns of rhythmic activity while being modulated by simple control parameters. To test our controller, we designed BoxyBot, a simple fish robot with three actuated fins capable of swimming in water and crawling on firm ground. Using the CPG model, the robot is capable of performing and switching between a variety of different locomotor behaviors such as swimming forwards, swimming backwards, turning, rolling, moving upwards/downwards, and crawling. These behaviors are triggered and modulated by sensory input provided by light, water, and touch sensors. Results are presented demonstrating the agility of the robot and interesting properties of a CPG-based control approach such as stability of the rhythmic patterns due to limit cycle behavior, and the production of smooth trajectories despite abrupt changes of control parameters. The robot is currently used in a temporary 20-month long exhibition at the EPFL. We present the hardware setup that was designed for the exhibition, and the type of interactions with the control system that allow visitors to influence the behavior of the robot. The exhibition is useful to test the robustness of the robot for long term use, and to demonstrate the suitability of the CPG-based approach for interactive control with a human in the loop. This article is an extended version of an article presented at BioRob2006 the first IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics.     

Applying Pareto Ranking and Niche Formation to Genetic Algorithm-Based Multiobjective Time–Cost Optimization

Time–cost optimization (TCO) is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Although the TCO problem has been extensively examined, many research studies only focused on minimizing the total cost for an early completion. This does not necessarily convey any reward to the contractor. However, with the increasing popularity of alternative project delivery systems, clients and contractors are more concerned about the combined benefits and opportunities of early completion as well as cost savings. In this paper, a genetic algorithms (GAs)-driven multiobjective model for TCO is proposed. The model integrates the adaptive weight to balance the priority of each objective according to the performance of the previous “generation.” In addition, the model incorporates Pareto ranking as a selection criterion and the niche formation techniques to improve popularity diversity. Based on the proposed framework, a prototype system has been developed in Microsoft Project for testing with a medium-sized project. The results indicate that greater robustness can be attained by the introduction of adaptive weight approach, Pareto ranking, and niche formation to the GA-based multiobjective TCO model.