New algorithms for automated phylogenetic reconstruction using artificial intelligence and data mining techniques

Academic and industrial research in the late 90s have brought about an exponential explosion of DNA sequence data. Automated expert systems are being created to help biologists to extract patterns, trends and links from this ever-deepening ocean of information. Two such systems aimed on retrieving and subsequently utilizing phylogenetically relevant information have been developed in this dissertation, the major objective of which was to automate the often difficult and confusing phylogenetic reconstruction process. ^ Popular phylogenetic reconstruction methods, such as distance-based methods, attempt to find an optimal tree topology (that reflects the relationships among related sequences and their evolutionary history) by searching through the topology space. Various compromises between the fast (but incomplete) and exhaustive (but computationally prohibitive) search heuristics have been suggested. An intelligent compromise algorithm that relies on a flexible “beam” search principle from the Artificial Intelligence domain and uses the pre-computed local topology reliability information to adjust the beam search space continuously is described in the second chapter of this dissertation. ^ However, sometimes even a (virtually) complete distance-based method is inferior to the significantly more elaborate (and computationally expensive) maximum likelihood (ML) method. In fact, depending on the nature of the sequence data in question either method might prove to be superior. Therefore, it is difficult (even for an expert) to tell a priori which phylogenetic reconstruction method—distance-based, ML or maybe maximum parsimony (MP)—should be chosen for any particular data set. ^ A number of factors, often hidden, influence the performance of a method. For example, it is generally understood that for a phylogenetically “difficult” data set more sophisticated methods (e.g., ML) tend to be more effective and thus should be chosen. However, it is the interplay of many factors that one needs to consider in order to avoid choosing an inferior method (potentially a costly mistake, both in terms of computational expenses and in terms of reconstruction accuracy.) ^ Chapter III of this dissertation details a phylogenetic reconstruction expert system that selects a superior proper method automatically. It uses a classifier (a Decision Tree-inducing algorithm) to map a new data set to the proper phylogenetic reconstruction method. ^

Is sexual intimacy among older adults positively associated with mental well-being?

Background. The elderly population aged 60 and above is increasing rapidly throughout the world. The aging process affects physical health of individuals, which in turn affects sexuality and sexual activity. However, many elderly adults continue to engage in one or more forms of sexual activities well into their 70s, 80s, and even in 90s. Despite the widespread stereotypes, misconceptions, and negative attitudes surrounding sexuality in elderly adults, it has been found to be an important aspect of the health of the elderly. However, association between the frequency of sexual activity and mental well being among older adults has not been documented in the literature. ^ Methods. To test the hypotheses that mental well being indicators such as depression, anxiety, and stress were inversely associated with greater frequency of sexual intimacy, a secondary data analysis was conducted using the National Social Life Health and Aging Project (NSHAP) using multivariate logistic regression. The NSHAP was a population-based study that was conducted on a national scale including 1455 men and 1550 women aged 57-85.^ Results. Approximately 1430 (54.1%) of the total population reported being sexually intimate in the past 12 months whereas 1481 (45.9%) participants reported that they did not perform any sexual activity in the past 12 months. In addition, approximately 895(31.1%) participants reported engaging in sexual activity ≥ 2-3 times per month with 665 (78.9%) of these participants reported performing vaginal intercourse only, 14(2.0%) oral sex only, and 89(10.5%) reported performing both vaginal intercourse and oral sex. Controlling for socio-demographic characteristics, frequently (≥2-3 times per month) sexually active participants showed lower odds ratio of depression (OR= 0.60; 95%CI = 0.46, 0.78), anxiety (OR= 0.67; 95% CI= 0.53, 0.86), and stress (OR=0.73; 95% CI = 0.6, 0.88) compared to those who had less frequent sexual activity or who had no sexual activity in the past 12 months.^ Conclusion. Lower levels of depression, anxiety, and stress appear to be associated with greater frequency of sexual activity. Public health interventions should focus on educating elderly adults about their sexual health and how to seek medical help for their sexual problems. Public health professionals should also be educated on how to best assess sexual needs of the elderly adults.^