<Emphasis Type="SmallCaps">l</Emphasis>-Carnitine/Simvastatin Reduces Lipoprotein (a) Levels Compared with Simvastatin Monotherapy: A Randomized Double-Blind Placebo-Controlled Study

Lipoprotein (a) [Lp(a)] is an independent risk factor for cardiovascular disease. There are currently limited therapeutic options to lower Lp(a) levels. l ‐Carnitine has been reported to reduce Lp(a) levels. The aim of this study was to compare the effect of l ‐carnitine/simvastatin co‐administration with that of simvastatin monotherapy on Lp(a) levels in subjects with mixed hyperlipidemia and elevated Lp(a) concentration. Subjects with levels of low‐density lipoprotein cholesterol (LDL‐C) >160 mg/dL, triacylglycerol (TAG) >150 mg/dL and Lp(a) >20 mg/dL were included in this study. Subjects were randomly allocated to receive l ‐carnitine 2 g/day plus simvastatin 20 mg/day (N = 29) or placebo plus simvastatin 20 mg/day (N = 29) for a total of 12 weeks. Lp(a) was significantly reduced in the l ‐carnitine/simvastatin group [?19.4%, from 52 (20–171) to 42 (15–102) mg/dL; p = 0.01], but not in the placebo/simvastatin group [?6.7%, from 56 (26–108) to 52 (27–93) mg/dL, p = NS versus baseline and p = 0.016 for the comparison between groups]. Similar significant reductions in total cholesterol, LDL‐C, apolipoprotein (apo) B and TAG were observed in both groups. Co‐administration of l ‐carnitine with simvastatin was associated with a significant, albeit modest, reduction in Lp(a) compared with simvastatin monotherapy in subjects with mixed hyperlipidemia and elevated baseline Lp(a) levels.     

Skills prediction based on multi-label resume classification using CNN with model predictions explanation

Neural Computing and Applications - Skills extraction is a critical task when creating job recommender systems. It is also useful for building skills profiles and skills knowledge bases for...     

A Direct Data-Cluster Analysis Method Based on Neutrosophic Set Implication

Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters. A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets. This paper focuses on cluster analysis based on neutrosophic set implication, i.e., a k-means algorithm with a threshold-based clustering technique. This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm. To evaluate the validity of the proposed method, several validity measures and validity indices are applied to the Iris dataset (from the University of California, Irvine, Machine Learning Repository) along with k-means and threshold-based clustering algorithms. The proposed method results in more segregated datasets with compacted clusters, thus achieving higher validity indices. The method also eliminates the limitations of threshold-based clustering algorithm and validates measures and respective indices along with k-means and thresholdbased clustering algorithms.     

Specification and testing using generalized machines: a presentation and a case study

Although testing is a major part of software development, it rarely gets the attention it deserves from researchers, partly because its foundations are weak and ill-understood. The principal purpose of testing is to detect (and then remove) faults in a software system. However, very few of the existing methods allow the tester to make any precise statement about the type or number of faults that remain undetected after testing is completed. In particular, none of the main techniques used by the software industry can give serious guarantees that a system is fault-free after testing has been completed. This paper advocates the use of a formal method both as a specification language and as the basis of a test data selection strategy. It presents a new method for generating test cases from this type of formal specification that provides a more convincing answer to the problem of detecting all faults in a software system. The method is reductionist in the sense that it guarantees that a system is fault-free provided that its components are fault-free; in turn, the same method could be used to test the resulting sub-systems, so the reduction will continue until the components considered are either known to be correct or are fairly simple pieces of code that can be successfully tested using traditional methods. The formal method used, X-machines, is a blend of finite state machines, data structures and processing functions and provides a simple and intuitive way of specifying computer systems. The use of X-machines as a specification tool and the testing method are illustrated with a case study. © 1998 John Wiley & Sons, Ltd.     

Bone Health in Patients with Dyslipidemias: An Underestimated Aspect

Beyond being aging-related diseases, atherosclerosis and osteoporosis share common pathogenetic pathways implicated in bone and vascular mineralization. However, the contributory role of dyslipidemia in this interplay is less documented. The purpose of this narrative review is to provide epidemiological evidence regarding the prevalence of bone disease (osteoporosis, fracture risk) in patients with dyslipidemias and to discuss potential common pathophysiological mechanisms linking osteoporosis and atherosclerosis. The effect of hypolipidemic therapy on bone metabolism is also discussed. Despite the high data heterogeneity and the variable quality of studies, dyslipidemia, mainly elevated total and low-density lipoprotein cholesterol concentrations, is associated with low bone mass and increased fracture risk. This effect may be mediated directly by the increased oxidative stress and systemic inflammation associated with dyslipidemia, leading to increased osteoclastic activity and reduced bone formation. Moreover, factors such as estrogen, vitamin D and K deficiency, and increased concentrations of parathyroid hormone, homocysteine and lipid oxidation products, can also contribute. Regarding the effect of hypolipidemic medications on bone metabolism, statins may slightly increase BMD and reduce fracture risk, although the evidence is not robust, as it is for omega-3 fatty acids. No evidence exists for the effects of ezetimibe, fibrates, and niacin. In any case, more prospective studies are needed further to elucidate the association between lipids and bone strength.     

Assessing the discomfort of the whole-body multi-axis vibration: laboratory and field experiments

Laboratory and field experiments were conducted to determine the best procedure for predicting the discomfort caused by multi-axis vibration. In the laboratory experiment, 11 seated subjects compared single-axis vibration in one axis to single-axis vibration in another axis, and compared dual-axis vibration to single-axis vibration. In the field experiment, 22 lorry drivers rated the discomfort of 16 different rides. The results show that the best procedure for predicting the discomfort is to combine the vibration inputs by taking the square root of the sum of squares of the weighted r.m.s. values of the vibration in each axis.     

How the shape of pre- and postsynaptic signals can influence STDP: a biophysical model

Spike-timing-dependent plasticity (STDP) is described by long-term potentiation (LTP), when a presynaptic event precedes a postsynaptic event, and by long-term depression (LTD), when the temporal order is reversed. In this article, we present a biophysical model of STDP based on a differential Hebbian learning rule (ISO learning). This rule correlates presynaptically the NMDA channel conductance with the derivative of the membrane potential at the synapse as the postsynaptic signal. The model is able to reproduce the generic STDP weight change characteristic. We find that (1) The actual shape of the weight change curve strongly depends on the NMDA channel characteristics and on the shape of the membrane potential at the synapse. (2) The typical antisymmetrical STDP curve (LTD and LTP) can become similar to a standard Hebbian characteristic (LTP only) without having to change the learning rule. This occurs if the membrane depolarization has a shallow onset and is long lasting. (3) It is known that the membrane potential varies along the dendrite as a result of the active or passive backpropagation of somatic spikes or because of local dendritic processes. As a consequence, our model predicts that learning properties will be different at different locations on the dendritic tree. In conclusion, such site-specific synaptic plasticity would provide a neuron with powerful learning capabilities.     

Preparing to live with micros

Ever since the first appearance of microprocessors as system components, there has been a pressing need for integrated study of hardware and software aspects of digital systems. Fundamentally micros were invented by engineers for engineers, although they are now entering the field of traditional computing machinery. Being programmable devices, a thorough knowledge of computer science is needed to make effective use of this new technology. The paper attempts to focus on some of the relevant issues and describe how this department plans to bridge the gap between the two disciplines of hardware and software by introducing a combined degree course in computer science and electronics. This discussion should be of interest to those concerned with education and training aspects related to micros.