Current state-of-the-art diagnostic measures of Alzheimer's disease (AD) are invasive (cerebrospinal fluid analysis), expensive (neuroimaging) and time-consuming (neuropsychological assessment) and thus have limited accessibility as frontline screening and diagnostic tools for AD. Thus, there is an increasing need for additional noninvasive and/or cost-effective tools, allowing identification of subjects in the preclinical or early clinical stages of AD who could be suitable for further cognitive evaluation and dementia diagnostics. Implementation of such tests may facilitate early and potentially more effective therapeutic and preventative strategies for AD. Before applying them in clinical practice, these tools should be examined in ongoing large clinical trials. This review will summarize and highlight the most promising screening tools including neuropsychometric, clinical, blood, and neurophysiological tests.

This paper reports an analysis and comparison of the use of 51 different similarity coefficients for computing the similarities between binary fingerprints for both simulated and real chemical data sets. Five pairs and a triplet of coefficients were found to yield identical similarity values, leading to the elimination of seven of the coefficients. The remaining 44 coefficients were then compared in two ways: by their theoretical characteristics using simple descriptive statistics, correlation analysis, multidimensional scaling, Hasse diagrams, and the recently described atemporal target diffusion model; and by their effectiveness for similarity-based virtual screening using MDDR, WOMBAT, and MUV data. The comparisons demonstrate the general utility of the well-known Tanimoto method but also suggest other coefficients that may be worthy of further attention.

The coupling of computer science and theoretical bases such as nonlinear dynamics and chaos theory allows the creation of 'intelligent' agents, such as artificial neural networks (ANNs), able to adapt themselves dynamically to problems of high complexity. ANNs are able to reproduce the dynamic interaction of multiple factors simultaneously, allowing the study of complexity; they can also draw conclusions on individual basis and not as average trends. These tools can offer specific advantages with respect to classical statistical techniques. This article is designed to acquaint gastroenterologists with concepts and paradigms related to ANNs. The family of ANNs, when appropriately selected and used, permits the maximization of what can be derived from available data and from complex, dynamic, and multidimensional phenomena, which are often poorly predictable in the traditional 'cause and effect' philosophy.

The purpose of this study is to understand the impact of health status and cultural participation upon psychological well-being, with special attention to the interaction between patterns of cultural access and other factors known to affect psychological well-being. Data for this report were collected from a sample of 1,500 Italian citizens. A multi-step random sampling method was adopted to draw a large representative sample from the Italian population. Subjects underwent a standard questionnaire for psychological well-being [the Italian short form of the Psychological General Well Being Index (PGWBI)], and a questionnaire related to the frequency of participation to 15 different kinds of cultural activities during the previous year. The results show that, among the various potential factors considered, cultural access unexpectedly rankes as the second most important determinant of psychological well-being, immediately after the absence or presence of diseases, and outperforming factors such as job, age, income, civil status, education, place of living and other important factors. According to a semantic map generated by a powerful data mining algorithm, it turns out that different factors (among which cultural access and health status in particular) may be viewed as concurrent elements of a complex multi-causal scheme that seems to play a primary role in determining psychological distress or well-being. In particular, distress seems to be tightly connected with: living in the Southern part of Italy, average income level, living in semi-urban and urban areas, age group 46-60, presence of more than two concomitant diseases and a low level of cultural access. Well being, on the other hand, is tightly connected with: male gender, high