Statistical prediction of single-stranded regions in RNA secondary structure and application to predicting effective antisense target sites and beyond

Single-stranded regions in RNA secondary structure are important for RNA–RNA and RNA–protein interactions. We present a probability profile approach for the prediction of these regions based on a statistical algorithm for sampling RNA secondary structures. For the prediction of phylogenetically-determined single-stranded regions in secondary structures of representative RNA sequences, the probability profile offers substantial improvement over the minimum free energy structure. In designing antisense oligonucleotides, a practical problem is how to select a secondary structure for the target mRNA from the optimal structure(s) and many suboptimal structures with similar free energies. By summarizing the information from a statistical sample of probable secondary structures in a single plot, the probability profile not only presents a solution to this dilemma, but also reveals ‘well-determined’ single-stranded regions through the assignment of probabilities as measures of confidence in predictions. In antisense application to the rabbit β-globin mRNA, a significant correlation between hybridization potential predicted by the probability profile and the degree of inhibition of in vitro translation suggests that the probability profile approach is valuable for the identification of effective antisense target sites. Coupling computational design with DNA–RNA array technique provides a rational, efficient framework for antisense oligonucleotide screening. This framework has the potential for high-throughput applications to functional genomics and drug target validation.

The Patient Informatics Consult Service (PICS): an approach for a patient-centered service

The Patient Informatics Consult Service (PICS) at the Eskind Biomedical Library at Vanderbilt University Medical Center (VUMC) provides patients with consumer-friendly information by using an information prescription mechanism. Clinicians refer patients to the PICS by completing the prescription and noting the patient's condition and any relevant factors. In response, PICS librarians critically appraise and summarize consumer-friendly materials into a targeted information report. Copies of the report are given to both patient and clinician, thus facilitating doctor-patient communication and closing the clinician-librarian feedback loop. Moreover, the prescription form also circumvents many of the usual barriers for patients in locating information, namely, patients' unfamiliarity with medical terminology and lack of knowledge of authoritative sources. PICS librarians capture the time and expertise put into these reports by creating Web-based pathfinders on prescription topics. Pathfinders contain librarian-created disease overviews and links to authoritative resources and seek to minimize the consumer's exposure to unreliable information. Pathfinders also adhere to strict guidelines that act as a model for locating, appraising, and summarizing information for consumers. These mechanisms—the information prescription, research reports, and pathfinders—serve as steps toward the long-term goal of full integration of consumer health information into patient care at VUMC.

A Computer-Assisted Personalized Approach in an Undergraduate Plant Physiology Class1

We used Computer-Assisted Personalized Approach (CAPA), a networked teaching and learning tool that generates computer individualized homework problem sets, in our large-enrollment introductory plant physiology course. We saw significant improvement in student examination performance with regular homework assignments, with CAPA being an effective and efficient substitute for hand-graded homework. Using CAPA, each student received a printed set of similar but individualized problems of a conceptual (qualitative) and/or quantitative nature with quality graphics. Because each set of problems is unique, students were encouraged to work together to clarify concepts but were required to do their own work for credit. Students could enter answers multiple times without penalty, and they were able to obtain immediate feedback and hints until the due date. These features increased student time on task, allowing higher course standards and student achievement in a diverse student population. CAPA handles routine tasks such as grading, recording, summarizing, and posting grades. In anonymous surveys, students indicated an overwhelming preference for homework in CAPA format, citing several features such as immediate feedback, multiple tries, and on-line accessibility as reasons for their preference. We wrote and used more than 170 problems on 17 topics in introductory plant physiology, cataloging them in a computer library for general access. Representative problems are compared and discussed.

Geographical structuring in the mtDNA of Italians.

Geographical patterns of mtDNA variation were studied in 12 Italian samples (1072 individuals) by two different spatial autocorrelation methods. Separate analyses of the frequencies of 12 restriction morphs show North-South clines, differences between Sardinia and the mainland populations, and the effects of isolation by distance. A recently developed autocorrelation statistic summarizing molecular similarity at all sites (AIDA; autocorrelation index for DNA analysis) confirms the presence of a clinical pattern; differences between random pairs of haplotypes tend to increase with their geographical distance. The partition of gene diversity, however, reveals that most variability occurs within populations, whereas differences between populations are minor (GST = 0.057). When the data from the 12 samples are pooled, two descriptors of genetic variability (number of polymorphic sites and average sequence difference between pairs of individuals) do not behave as expected under neutrality. The presence of clinal patterns, Tajima's tests, and a simulation experiment agree in suggesting that population sizes increased rapidly in Italy and Sicily but not necessarily so in Sardinia. The distribution of pairwise sequence differences in the Italian peninsula (excluding Sardinia) permits a tentative location of the demographic increase between 8000 and 20,500 years ago. These dates are consistent with archaeological estimates of two distinct expansion processes, occurring, respectively, in the Neolithic and after the last glacial maximum in the Paleolithic. Conversely, there is no genetic evidence that such processes have had a major impact on the Sardinian population.