Background-Diffusion tensor imaging (DTI) studies have shown significant cross-sectional differences among normal controls (Bozzali et al., 2002), mild cognitive impairment (Robbins et al.) and Alzheimer's disease (AD) patients in several fiber tracts in the brain, but longitudinal assessment is needed.

The literature of acute exacerbation of chronic obstructive pulmonary disease (COPD) is fast expanding. This review focuses on several aspects of acute exacerbation of COPD (AECOPD) including epidemiology, diagnosis and management. COPD poses a major health and economic burden in the Asia-Pacific region, as it does worldwide. Triggering factors of AECOPD include infectious (bacteria and viruses) and environmental (air pollution and meteorological effect) factors. Disruption in the dynamic balance between the 'pathogens' (viral and bacterial) and the normal bacterial communities that constitute the lung microbiome likely contributes to the risk of exacerbations. The diagnostic approach to AECOPD varies based on the clinical setting and severity of the exacerbation. After history and examination, a number of investigations may be useful, including oximetry, sputum culture, chest X-ray and blood tests for inflammatory markers. Arterial blood gases should be considered in severe exacerbations, to characterize respiratory failure. Depending on the severity, the acute management of AECOPD involves use of bronchodilators, steroids, antibiotics, oxygen and noninvasive ventilation. Hospitalization may be required, for severe exacerbations. Nonpharmacological interventions including disease-specific self-management, pulmonary rehabilitation, early medical follow-up, home visits by respiratory health workers, integrated programmes and telehealth-assisted hospital at home have been studied during hospitalization and shortly after discharge in patients who have had a recent AECOPD. Pharmacological approaches to reducing risk of future exacerbations include long-acting bronchodilators, inhaled steroids, mucolytics, vaccinations and long-term macrolides. Further studies are needed to assess the cost-effectiveness of these interventions in preventing COPD exacerbations.

Restricted Random Testing (RRT) is a new method of testing software that improves upon traditional Random Testing (RT) techniques. Research has indicated that failure patterns (portions of an input domain which, when executed, cause the program to fail or reveal an error) can influence the effectiveness of testing strategies. For certain types of failure patterns, it has been found that a widespread and even distribution of test cases in the input domain can be significantly more effective at detecting failure compared with ordinary RT. Testing methods based on RT, but which aim to achieve even and widespread distributions, have been called Adaptive Random Testing (ART) strategies. One implementation of ART is RRT. RRT uses exclusion zones around executed, but non-failure-causing, test cases to restrict the regions of the input domain from which subsequent test cases may be drawn. In this paper, we introduce the motivation behind RRT, explain the algorithm and detail some empirical analyses carried out to examine the effectiveness of the method. Two versions of RRT are presented: Ordinary RRT (ORRT) and Normalized RRT (NRRT). The two versions share the same fundamental algorithm, but differ in their treatment of non-homogeneous input domains. Investigations into the use of alternative exclusion shapes are outlined, and a simple technique for reducing the computational overheads of RRT, prompted by the alternative exclusion shape investigations, is also explained. The performance of RRT is compared with RT and another ART method based on maximized minimum test case separation (DART), showing excellent improvement over RT and a very favorable comparison with DART.

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TA was cytotoxic to both SVG and ARPE19 cells, with higher efficacy on SVG. TA caused the activation of the caspase-3 pathway more readily than the cell-protective c-fos and c-jun pathways in SVG cells, making those cells more vulnerable than the ARPE19 cells. The results suggest that TA toxicity in one cell type may not reliably indicate its toxicity in other cells. Different cells within the retina may react to TA differently, or TA may cause changes in the gene expressions differentially with different concentrations of the same stimulus.