Diabetes and Ischemic Stroke: An Old and New Relationship an Overview of the Close Interaction between These Diseases

Diabetes mellitus is a comprehensive expression to identify a condition of chronic hyperglycemia whose causes derive from different metabolic disorders characterized by altered insulin secretion or faulty insulin effect on its targets or often both mechanisms. Diabetes and atherosclerosis are, from the point of view of cardio- and cerebrovascular risk, two complementary diseases. Beyond shared aspects such as inflammation and oxidative stress, there are multiple molecular mechanisms by which they feed off each other: chronic hyperglycemia and advanced glycosylation end-products (AGE) promote ‘accelerated atherosclerosis’ through the induction of endothelial damage and cellular dysfunction. These diseases impact the vascular system and, therefore, the risk of developing cardio- and cerebrovascular events is now evident, but the observation of this significant correlation has its roots in past decades. Cerebrovascular complications make diabetic patients 2–6 times more susceptible to a stroke event and this risk is magnified in younger individuals and in patients with hypertension and complications in other vascular beds. In addition, when patients with diabetes and hyperglycemia experience an acute ischemic stroke, they are more likely to die or be severely disabled and less likely to benefit from the one FDA-approved therapy, intravenous tissue plasminogen activator. Experimental stroke models have revealed that chronic hyperglycemia leads to deficits in cerebrovascular structure and function that may explain some of the clinical observations. Increased edema, neovascularization, and protease expression as well as altered vascular reactivity and tone may be involved and point to potential therapeutic targets. Further study is needed to fully understand this complex disease state and the breadth of its manifestation in the cerebrovasculature.     

Fast and Selective Determination of Ochratoxin A in Wines Using an Optimized and Validated Liquid Chromatographic Method

Determination of ochratoxin A (OTA) in wines requires a cleanup step using solid phase extraction (SPE). Immunoaffinity columns are commonly the columns of choice but due to its high cost, other SPE columns have been assayed without optimal results. The present work reports an optimized and validated liquid chromatographic method for a fast and selective quantification of OTA in wines using C₁₈ columns for cleanup. Chromatographic conditions were optimized using a central composite design, establishing the following optimal conditions: acetonitrile/water/acetic acid (59.5:39.5:1.0 v/v/v) as mobile phase, flow rate of 1.2 mL min^?1, and column temperature of 30 °C. With these conditions, OTA had a retention time (~4 min) up to five times lower than those reported earlier. Regarding validation, calibration data (n?=?8) fitted a linear regression model with a determination coefficient (R ²) of 0.9992. Repeatability (relative standard deviation (RSD)) and intermediate precision (RSD) in matrix showed values of 1.3 % (n?=?6) and 0.8 % (n?=?3), respectively. Recoveries at five levels ranged from 87.2 to 118.9 % (mean RSD of 7.4 %). Fifty-three samples from different origins were analyzed, finding only seven samples (13 %) with quantifiable OTA content (0.15–0.26 μg L^?1). According to the levels found, the contribution of wine consumption to OTA daily intake was at least 58 times lower than the current tolerable daily intake. In view of optimization and validation results as well as its applicability to real samples, this method could be considered a good alternative for routine analysis of OTA in wines.     

Surface Analysis of Cr2O3‐, CoO‐, and Al2O3‐Doped Iron–Phosphate Glasses at High Temperature

Surface structures of iron–phosphate glasses were examined using X‐ray photoelectron spectroscopy (XPS). Cr₂O₃, CoO, and Al₂O₃ were introduced to the glass by the replacement of a part of Fe₂O₃, and the simulated fission products are also added. The obtained glasses showed high chemical durabilities by MCC‐1 test. In situ high‐temperature and room‐temperature XPS measurements were conducted on the polished sample surfaces and also those after 1‐week chemical durability test. Unique trends were observed in XPS spectra on heating and after the chemical durability test, respectively. Nature of the glass surface of iron–phosphate glasses was explained from the point of view of surface energy, and the origin of high chemical durability and the effect of chromium ions were discussed based on the changes on surface composition and valence states of transition‐metal ions.     

Fault tolerant network design inspired by Physarum polycephalum

Physarum polycephalum, a true slime mould, is a primitive, unicellular organism that creates networks to transport nutrients while foraging. The design of these natural networks proved to be advanced, e.g. the slime mould was able to find the shortest path through a maze. The underlying principles of this design have been mathematically modelled in literature. As in real life the slime mould can design fault tolerant networks, its principles can be applied to the design of man-made networks. In this paper, an existing model and algorithm are adapted and extended with stimulation and migration mechanisms which encourage formation of alternative paths, optimize edge positioning and allow for automated design. The extended model can then be used to better design fault tolerant networks. The extended algorithm is applied to several national and international network configurations. Results show that the extensions allow the model to capture the fault tolerance requirements more accurately. The resulting extended algorithm overcomes weaknesses in geometric graph design and can be used to design fault tolerant networks such as telecommunication networks with varying fault tolerance requirements.     

Age‐Related Physiological Responses to Working in Deep Cold

Professional order‐picking in deep cold‐storage depots (i.e., storing, picking, and dispatching of frozen groceries) requires employees to remain working at temperatures of approximately ?24°C for a whole workday. Actually, a well‐regulated organization of working times and breaks has not been established, and no competent knowledge exists as to whether an additional age‐differentiated organization is necessary. To assess the physiological effects while working in deep cold, 30 male subjects (Ss) were classified into two age groups (20‐ to 35‐year‐olds and 40‐ to 65‐year‐olds). In whole workday tests, possible age‐dependent effects on the strain were measured to guarantee the preservation of the subjects' ability to work in the long run. For the objectification of the physiological strain, heart rate and skin surface temperature were registered continuously, and blood pressure and body core temperature were measured and recorded discretely during cold exposures of 80, 100, and 120 min, separated by 20‐min warming‐up breaks. Systematic differences of blood pressure could not be found. The heart rate values indicated a high physiological strain for both younger and older Ss, with work‐related increases above the resting level of 30 bpm and more. Due to increases over time, endurance level sometimes was exceeded. Age‐related differences in skin temperature could not be recorded, but the ability to generate heat deteriorated with advancing age, which is shown by more substantial decreases of body core temperature in the group of 40‐ to 65‐year‐olds taken at the tympanum. Regarding physiological strain brought about by maximum heart rate decreasing with age and declined heat generation, correspondingly adapted workday break regimes have to be provided for older employees to ensure their ability to work in the long run. © 2011 Wiley Periodicals, Inc.     

A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments

The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %.     

A methodology for screening of microalgae as a decision making tool for energy and green chemical process applications

The increasing interest for biotechnological use of microalgae demands a methodology for selection of species suitable to support the development of technologies based on the use of such non-conventional renewable raw material, i.e., green industrial applications. The vast and expanding collection of experimental data on both cell growth and biomass composition available in the literature can be used to reduce the cost of the experimental investigations required to support process engineering and optimization. Selecting the appropriate organism requires extracting useful information from such data, a cumbersome task since various multidisciplinary factors must be considered. This paper presents a computer-aided methodology for selecting appropriate algal species given an energy or green chemical process application employing microalgae as a renewable raw material. The approach is “system oriented”, based on biomass composition and chemical processing of the biomass downstream of the CO₂ biofixation and harvesting operations. Quantitative performance results are supported by professional process simulation. Besides comparison of a set of species performances, the proposed methodology also allows the discrimination among distinct algal compositions resulting from different growth conditions for a given species. Furthermore, three categories of screening metrics are proposed to be maximized by the decision making procedure in order to elicit the relevant information. To demonstrate the potential of the proposed methodology, a databank of both biochemical and elemental compositions of microalgal biomass was used in three green applications: Assessment of biomass heating value; production of syngas by gasification of the biomass; and production of Bio-H₂. Within the accuracy of the databank employed to illustrate the procedure, the methodology selected Botryococcus braunii and Isochrysis galbana as potential promising candidates, for the three examined applications.     

Direct characterisation of phenolic antioxidants in infusions from four Mapuche medicinal plants by liquid chromatography with diode array detection (HPLC-DAD) and electrospray ionisation tandem mass spectrometry (HPLC-ESI-MS)

A simple, fast and direct method was developed for the qualitative analysis of phenolic constituents from infusions of Mapuche medicinal plants. Teas made of Linum chamissonis Schiede, Quinchamalium chilensis Mol., Adesmia emarginata Clos. and Escallonia illinita K. Presl. were analysed by high-performance liquid chromatography with diode array detector (HPLC-DAD) and electrospray mass spectrometry (ESI-MS). This technique allowed for the first time the tentative identification of 16 phenolic compounds in E. illinita, 27 in Q. chilensis, 10 in L. chamissonis and 19 in A. emarginata. The compounds were mainly phenolic acids, flavonoid glycosides, anthocyanins and tannins. The total phenolic and flavonoid content of the infusions was assessed as well as the free radical scavenging capacity measured by the bleaching of a solution of the 2,2-diphenyl-1-picrylhydrazyl (DPPH⁻) radical. From the four species, Q. chilensis exhibited the strongest antioxidant activity with highest total phenolic and flavonoid content.     

Detecting component changes at run time with behavior models

Modern software systems are composed of several services which may be developed and maintained by third parties and thus they can change independently and without notice during the system’s runtime execution. In such systems, changes may possibly be a threat to system functional correctness, and thus to its reliability. Hence, it is important to detect them as soon as they happen to enable proper reaction. Change detection can be done by monitoring system execution and comparing the observed execution traces against models of the services composing the application. Unfortunately, formal specifications for services are not usually provided and developers have to infer them. In this paper we propose a methodology which exactly addresses these issues by using software behavior models to monitor component execution and detect changes. In particular, we describe a technique to infer behavior model specifications with a dynamic black box approach, keep them up-to-date with run time observations and detect behavior changes. Finally, we present a case study to validate the effectiveness of the approach in component change detection for a component that implements a complex, real communication protocol.     

Complex and dynamic population structures: synthesis, open questions, and future directions

The population structure of an evolutionary algorithm influences the dissemination and mixing of advantageous alleles, and therefore affects search performance. Much recent attention has focused on the analysis of complex population structures, characterized by heterogeneous connectivity distributions, non-trivial clustering properties, and degree–degree correlations. Here, we synthesize the results of these recent studies, discuss their limitations, and highlight several open questions regarding (1) unsolved theoretical issues and (2) the practical utility of complex population structures for evolutionary search. In addition, we will discuss an alternative complex population structure that is known to significantly influence dynamical processes, but has yet to be explored for evolutionary optimization. We then shift our attention toward dynamic population structures, which have received markedly less attention than their static counterparts. We will discuss the strengths and limitations of extant techniques and present open theoretical and experimental questions and directions for future research. In particular, we will focus on the prospects of “active linking,” wherein edges are dynamically rewired according to the genotypic or phenotypic properties of individuals, or according to the success of prior inter-individual interactions.