The MoCA is a suitably accurate, brief test when screening all levels of cognition in PD.

Receiver operating characteristic (ROC) curves have been useful in two-group classification problems. In three- and multiple-class diagnostic problems, an ROC surface or hyper-surface can be constructed. The volume under these surfaces can be used for inference using bootstrap techniques or U-statistics theory. In this article, ROC surfaces and hyper-surfaces are defined and their behaviour and utility in multi-group classification problems is investigated. The formulation of the problem is equivalent to what has previously been proposed in the general multi-category classification problem but the definition of ROC surfaces here is less complex and addresses directly the narrower problem of ordered categories in the three-class and, by extension, the multi-class problem applied to continuous and ordinal data. Non-parametric manipulation of both continuous and discrete test data and comparison between two diagnostic tests applied to the same subjects are considered. A three-group classification example in the context of HIV neurological disease is presented and the results are discussed.

Wireless Sensor Networks are considered to be among the most rapidly evolving technological domains thanks to the numerous benefits that their usage provides. As a result, from their first appearance until the present day, Wireless Sensor Networks have had a continuously growing range of applications. The purpose of this article is to provide an up-to-date presentation of both traditional and most recent applications of Wireless Sensor Networks and hopefully not only enable the comprehension of this scientific area but also facilitate the perception of novel applications. In order to achieve this goal, the main categories of applications of Wireless Sensor Networks are identified, and characteristic examples of them are studied. Their particular characteristics are explained, while their pros and cons are denoted. Next, a discussion on certain considerations that are related with each one of these specific categories takes place. Finally, concluding remarks are drawn.

After establishing the utility of a continuous diagnostic marker investigators will typically address the question of determining a cut-off point which will be used for diagnostic purposes in clinical decision making. The most commonly used optimality criterion for cut-off point selection in the context of ROC curve analysis is the maximum of the Youden index. The pair of sensitivity and specificity proportions that correspond to the Youden index-based cut-off point characterize the performance of the diagnostic marker. Confidence intervals for sensitivity and specificity are routinely estimated based on the assumption that sensitivity and specificity are independent binomial proportions as they arise from the independent populations of diseased and healthy subjects, respectively. The Youden index-based cut-off point is estimated from the data and as such the resulting sensitivity and specificity proportions are in fact correlated. This correlation needs to be taken into account in order to calculate confidence intervals that result in the anticipated coverage. In this article we study parametric and non-parametric approaches for the construction of confidence intervals for the pair of sensitivity and specificity proportions that correspond to the Youden index-based optimal cut-off point. These approaches result in the anticipated coverage under different scenarios for the distributions of the healthy and diseased subjects. We find that a parametric approach based on a Box-Cox transformation to normality often works well. For biomarkers following more complex distributions a non-parametric procedure using logspline density estimation can be used.

SummaryWe study properties of the index J 3 , defined as the accuracy, or the maximum correct classification, for a given three-class classification problem. Specifically, using J 3 one can assess the discrimination between the three distributions and obtain an optimal pair of cut-off points c 1 < c 2 in the sense that the sum of the correct classification proportions will be maximized. It also serves as the generalization of the Youden index in three-class problems. Parametric and nonparametric approaches for estimation and testing are considered and methods are applied to data from an MRS study on HIV patients.

Persistence and thriving of univoltine, herbivore insect species of the temperate zone rely on obligate diapause response that ensures winter survival and synchronization with host phenology. We used a stenophagous fruit fly (Rhagoletis cerasi) with obligate pupae diapause to determine genetic and environmental effects on diapause intensity of geographically isolated populations with habitat heterogeneity. Pupae from two Greek and one German populations with various gene flow rates were exposed at five constant chilling temperatures (0-12°C) for different durations and then incubated at a high temperature until all adults have emerged. Pupae diapause intensity differs among Greek and German populations, suggesting an adaptive response to habitat heterogeneity (mostly differences in phenology patterns of local host cultivars). Moderately warm winter temperatures, such as 8°C, promote diapause termination in all three populations. Insufficient chilling (short duration or warmer temperatures) regulates the expression of prolonged dormancy. Interestingly, extended chilling (longer than required for terminating diapause) 'return' pupae to another (facultative) cycle of dormancy enabling adults to emerge during the next appropriate 'window of time'; a strategy first time reported for univoltine insects. Consequently, diapause duration of R. cerasi is determined both by i) the adaptive response to local climatic conditions (annual dormancy) and ii) the plastic responses to interannual climatic variability resulting in two types of long life cycles within populations, prolonged and facultative dormancy as response to insufficient chilling and extended exposure to chilling, respectively. Long life cycles are expressed as a part of dormancy bet-hedging strategies of R. cerasi populations.

Comparisons among populations from different localities represent an important tool in the study of evolution. Medflies have colonized many temperate and tropical areas all over the world during the last few centuries. In a common garden environment, we examined whether medfly populations obtained from six global regions [Africa (Kenya), Pacific (Hawaii), Central America (Guatemala), South America (Brazil), Extra-Mediterranean (Portugal) and Mediterranean (Greece)] have evolved different survival and reproductive schedules. Whereas females were either short-lived [life expectancy at eclosion (e0) 48-58 days; Kenya, Hawaii and Guatemala] or long-lived (e0 72-76 days; Greece, Portugal and Brazil], males with one exception (Guatemala) were generally long-lived (e0 106-122 days). Although males universally outlived females in all populations, the longevity gender gap was highly variable (20-58 days). Lifetime fecundity rates were similar among populations. However, large differences were observed in their age-specific reproductive patterns. Short-lived populations mature at earlier ages and allocate more of their resources to reproduction early in life compared with long-lived ones. In all populations, females experienced a post-reproductive lifespan, with this segment being significantly longer in Kenyan flies. Therefore, it seems plausible that medfly populations, inhabiting ecologically diverse habitats, have evolved different life history strategies to cope with local environmental conditions.

No abstract