The Role of Circulating Biomarkers in Peripheral Arterial Disease

Peripheral arterial disease (PAD) of the lower extremities is a chronic illness predominantly of atherosclerotic aetiology, associated to traditional cardiovascular (CV) risk factors. It is one of the most prevalent CV conditions worldwide in subjects >65 years, estimated to increase greatly with the aging of the population, becoming a severe socioeconomic problem in the future. The narrowing and thrombotic occlusion of the lower limb arteries impairs the walking function as the disease progresses, increasing the risk of CV events (myocardial infarction and stroke), amputation and death. Despite its poor prognosis, PAD patients are scarcely identified until the disease is advanced, highlighting the need for reliable biomarkers for PAD patient stratification, that might also contribute to define more personalized medical treatments. In this review, we will discuss the usefulness of inflammatory molecules, matrix metalloproteinases (MMPs), and cardiac damage markers, as well as novel components of the liquid biopsy, extracellular vesicles (EVs), and non-coding RNAs for lower limb PAD identification, stratification, and outcome assessment. We will also explore the potential of machine learning methods to build prediction models to refine PAD assessment. In this line, the usefulness of multimarker approaches to evaluate this complex multifactorial disease will be also discussed.     

Biomarkers in Glycogen Storage Diseases: An Update

Glycogen storage diseases (GSDs) are a group of 19 hereditary diseases caused by a lack of one or more enzymes involved in the synthesis or degradation of glycogen and are characterized by deposits or abnormal types of glycogen in tissues. Their frequency is very low and they are considered rare diseases. Except for X-linked type IX, the different types are inherited in an autosomal recessive pattern. In this study we reviewed the literature from 1977 to 2020 concerning GSDs, biomarkers, and metabolic imbalances in the symptoms of some GSDs. Most of the reported studies were performed with very few patients. Classification of emerging biomarkers between different types of diseases (hepatics GSDs, McArdle and PDs and other possible biomarkers) was done for better understanding. Calprotectin for hepatics GSDs and urinary glucose tetrasaccharide for Pompe disease have been approved for clinical use, and most of the markers mentioned in this review only need clinical validation, as a final step for their routine use. Most of the possible biomarkers are implied in hepatocellular adenomas, cardiomyopathies, in malfunction of skeletal muscle, in growth retardation, neutropenia, osteopenia and bowel inflammation. However, a few markers have lost interest due to a great variability of results, which is the case of biotinidase, actin alpha 2, smooth muscle, aorta and fibroblast growth factor receptor 4. This is the first review published on emerging biomarkers with a potential application to GSDs.     

Application of the classical levels of intelligence to structuring the control system in an automated distribution centre

Traditional management and control models can benefit from added levels of intelligence to increase their capability to adapt to the continuous changes in global markets. After reviewing the classical definition of intelligence and its levels, this paper provides a new approach to help increase the responsiveness of management and control to changes and disturbances in the manufacturing supply chain. The ancient concept of the “Tertium Quid” has inspired a three-level community of agents (MAS-TRIO) that is proposed to improve the coordination of all actors involved. The proposed model combines Multi-Agent Systems (MAS) with Radio-Frequency Identification (RFID) to make possible a certain level of Autonomous Intelligence in the decision-taking process. This paper analyses how these levels of intelligence can be applied to management and control, and the performance of the proposed model has been tested at low and mid-levels on an experimental platform representing the facilities of a distribution centre controlled by a network of programmable logic controllers (PLCs).     

A GPU implementation of a hybrid evolutionary algorithm: GPuEGO

The high computation requirements of global optimization algorithms, when used to solve real optimization problems, have caused the appearance of different parallelization strategies using several parallel computing architectures. In this work, the Universal Evolutionary Global Optimizer is implemented in CUDA to be run on GPU architectures (GPuEGO). This parallelization of the referred evolutionary multimodal optimization algorithm is rather different from other previous parallel implementations designed to be executed into shared or distributed memory processors. In this case, due to the special characteristics of a GPU architecture, the original data structures are not valid and it has been necessary to redefine them and all the functions that operate with them. When this approach is applied the acceleration factors achieved by GPuEGO range from \({\times }\) 6.33 to \({\times }\) 23.20 depending on the test function.     

Comparative evaluation of platforms for parallel Ant Colony Optimization

The rapidly growing field of nature-inspired computing concerns the development and application of algorithms and methods based on biological or physical principles. This approach is particularly compelling for practitioners in high-performance computing, as natural algorithms are often inherently parallel in nature (for example, they may be based on a “swarm”-like model that uses a population of agents to optimize a function). Coupled with rising interest in nature-based algorithms is the growth in heterogenous computing; systems that use more than one kind of processor. We are therefore interested in the performance characteristics of nature-inspired algorithms on a number of different platforms. To this end, we present a new OpenCL-based implementation of the Ant Colony Optimization algorithm, and use it as the basis of extensive experimental tests. We benchmark the algorithm against existing implementations, on a wide variety of hardware platforms, and offer extensive analysis. This work provides rigorous foundations for future investigations of Ant Colony Optimization on high-performance platforms.     

Calmodulin Supports TRPA1 Channel Association with Opioid Receptors and Glutamate NMDA Receptors in the Nervous Tissue

Transient receptor potential ankyrin member 1 (TRPA1) belongs to the family of thermo TRP cation channels that detect harmful temperatures, acids and numerous chemical pollutants. TRPA1 is expressed in nervous tissue, where it participates in the genesis of nociceptive signals in response to noxious stimuli and mediates mechanical hyperalgesia and allodynia associated with different neuropathies. The glutamate N-methyl-d-aspartate receptor (NMDAR), which plays a relevant role in allodynia to mechanical stimuli, is connected via histidine triad nucleotide-binding protein 1 (HINT1) and type 1 sigma receptor (σ1R) to mu-opioid receptors (MORs), which mediate the most potent pain relief. Notably, neuropathic pain causes a reduction in MOR antinociceptive efficacy, which can be reversed by blocking spinal NMDARs and TRPA1 channels. Thus, we studied whether TRPA1 channels form complexes with MORs and NMDARs that may be implicated in the aforementioned nociceptive signals. Our data suggest that TRPA1 channels functionally associate with MORs, delta opioid receptors and NMDARs in the dorsal root ganglia, the spinal cord and brain areas. These associations were altered in response to pharmacological interventions and the induction of inflammatory and also neuropathic pain. The MOR-TRPA1 and NMDAR-TRPA1 associations do not require HINT1 or σ1R but appear to be mediated by calcium-activated calmodulin. Thus, TRPA1 channels may associate with NMDARs to promote ascending acute and chronic pain signals and to control MOR antinociception.     

Cholesterol synthesis and esterification in isolated enterocytes: Regulation by cholesterol and cholestyramine feeding

The purpose of the present study was to investigate the physiological control of the main regulatory enzymes of cholesterol metabolism in isolated enterocytes obtained from chick duodenum, jejunum and ileum. Cholesterol feeding resulted in an inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase and mevalonate 5-pyrophosphate decarboxylase, while cholestyramine feeding increased reductase activity in all the regions studied and decarboxylase activity only in duodenum. Cholesterol feeding markedly increased acyl-CoA:cholesterol acyltransferase, but the effects of cholestyramine were less clear. The effects on transferase activity cannot be due to differences in the availability of acyl-CoA as exogenous substrate as no significant differences were found in acyl-CoA hydrolase activity after any of the dietary treatments. The effects of cholesterol feeding were related to changes in the cholesterol content of epithelial cells, whereas in the case of cholestyramine this relationship was less apparent.     

Effect of refining on the phenolic composition of crude olive oils

By definition, virgin olive oil is consumed unrefined, although a great proportion of the olive oil produced has to be refined to render it edible. Phenolic compounds are among the substances eliminated during the refining process; in the present work these were characterized by HPLC, and their evolution during the different refining steps was studied. The complete refining process removed most polyphenols from oils, but the behavior of individual compounds at each step also was observed. o-Diphenols (hydroxytyrosol, catechol, and hydroxytyrosol acetate) and flavonoids (luteolin and apigenin) were eliminated first during the alkaline treatment. Tyrosol and 4-ethylphenol remained in the oil until the deodorization step. A large amount of phenolic compounds was discovered in the refining by-products such as soapstocks and deodorization distillates. In the latter streams, the concentrations of tyrosol and 4-ethylphenol reached up to 149 and 3720 mg/kg by-product, respectively. This high level of 4-ethylphenol and its well-known strong off-odor can interfere during further processing of the deodorization distillates, and this must be taken into account when deciding what is to become of them. Similarly, the results of this work open the possibility of recovering phenolic compounds from the “second centrifugation olive oils” by adding a new washing step prior to the refining process. By including this new step, the most polar polyphenols, hydroxytyrosol and tyrosol, will diffuse from oil to water and a concentration of up to 1400 mg/L of hydroxytyrosol may be achieved.     

Optimal linear filter design for systems with correlation in the measurement matrices and noises: recursive algorithm and applications

This paper addresses the optimal least-squares linear estimation problem for a class of discrete-time stochastic systems with random parameter matrices and correlated additive noises. The system presents the following main features: (1) one-step correlated and cross-correlated random parameter matrices in the observation equation are assumed; (2) the process and measurement noises are one-step autocorrelated and two-step cross-correlated. Using an innovation approach and these correlation assumptions, a recursive algorithm with a simple computational procedure is derived for the optimal linear filter. As a significant application of the proposed results, the optimal recursive filtering problem in multi-sensor systems with missing measurements and random delays can be addressed. Numerical simulation examples are used to demonstrate the feasibility of the proposed filtering algorithm, which is also compared with other filters that have been proposed.     

Adaptive training interfaces for less-experienced,elderly users of electronic devices

A great number of complex electronic devices are now part of our everyday lives. While many of us learn to handle these products by trial and error; others, especially older users with little experience in using electronic devices, need support. In order to allow the user maximum flexibility in terms of learning time and location, a training programme is presented which is implemented as part of the software embedded in the product itself. Particular focus is placed on the effect of adaptive training on learning. In this study, the training versions differed in their ability to adjust their complexity to the user's experience (adaptive user interface complexity) and their capability to support the learner by prompting them during the learning process (adaptive training advice). The results show that the adjustment of complexity had a positive effect on users’ experience: elderly users who trained with an adaptive interface were more successful in learning to use a mobile phone. Adaptive training advice, however, was found to have no significant effects on learners’ success and reduced their self-efficacy. This work offers guidelines on how to design integrated training applications for electronic devices that successfully help elderly users with little prior experience.