Discriminative ability of functional loading tests for adolescent jumper

Objective: To investigate the reliability and validity of five squat-based loading tests that are clinically appropriate for jumper's knee. The loading tests were step up, double leg squat, double leg squat on a 25-degree decline (decline squat), single leg decline squat, and decline hop. Design: Cross-sectional controlled cohort. Subjects without knee pain comprised controls, those with extensor tendon pain comprised the jumper's knee group. Setting: Institutional athlete study group in Australia. Participants: Fifty-six elite adolescent basketball players participated in this study, thirteen comprised the jumper's knee group, fifteen athletes formed a control group. Intervention: Each subject performed each loading test for baseline and reliability data on the first testing day. Subjects then performed three days of intensive (6 h daily) basketball training, after which each loading test was reexamined. Main outcome measures: Eleven point interval scale for pain. Results: The tests that best detected a change in pain due to intensive workload were the single leg decline squat and single leg decline hop. This study found that decline tests have better discriminative ability than the standard squat to detect change in jumper's knee pain due to intensive training. The typical error for these tests ranged from 0.3 to 0.5, however, caution should be exercised in the interpretation of these reliability figures due to relatively low scores. Conclusions: The single leg decline squat is recommended in the physical assessment of adolescent jumper's knee. The decline squat was selected as the best clinical test over the decline hop because it was easier to standardise performance.

Discovery of structural and functional features in RNA pseudoknots

An RNA pseudoknot consists of nonnested double-stranded stems connected by single-stranded loops. There is increasing recognition that RNA pseudoknots are one of the most prevalent RNA structures and fulfill a diverse set of biological roles within cells, and there is an expanding rate of studies into RNA pseudoknotted structures as well as increasing allocation of function. These not only produce valuable structural data but also facilitate an understanding of structural and functional characteristics in RNA molecules. PseudoBase is a database providing structural, functional, and sequence data related to RNA pseudoknots. To capture the features of RNA pseudoknots, we present a novel framework using quantitative association rule mining to analyze the pseudoknot data. The derived rules are classified into specified association groups regarding structure, function, and category of RNA pseudoknots. The discovered association rules assist biologists in filtering out significant knowledge of structure-function and structure-category relationships. A brief biological interpretation to the relationships is presented, and their potential correlations with each other are highlighted.