Modeling long-range cross-correlations in two-component ARFIMA and FIARCH processes

We investigate how simultaneously recorded long-range power-law correlated multi-variate signals cross-correlate. To this end we introduce a two-component ARFIMA stochastic process and a two-component FIARCH process to generate coupled fractal signals with long-range power-law correlations which are at the same time long-range cross-correlated. We study how the degree of cross-correlations between these signals depends on the scaling exponents characterizing the fractal correlations in each signal and on the coupling between the signals. Our findings have relevance when studying parallel outputs of multiple-component of physical, physiological and social systems.Comment: 8 pages, 5 figures, elsart.cl

Effects of High-Speed Versus Traditional Resistance Training in Older Adults

BACKGROUND: The losses of strength, agility, balance, and functionality caused by aging are harmful to the elderly population. Resistance training (RT) may be an efficient tool to mitigate such neuromuscular decline and different RT methods can be used. Therefore, it is important to investigate the different responses to different training methods. HYPOTHESIS: Eight weeks of traditional resistance training (TRT) are expected to promote similar results to high-speed training (HST) in physical functional performance (PFP) and quality of life in the elderly. STUDY DESIGN: A clinical trial. LEVEL OF EVIDENCE: Level 3. METHODS: Participants (n = 24) with a mean age of 67.8 ± 6.3 years completed 8 weeks of RT. They were allocated into HST (n = 12) and TRT (n = 12). TRT involved training with 10 to 12 repetitions at controlled velocity until momentary muscle failure, while HST involved performing 6 to 8 repetitions at 40% to 60% of 1 repetition maximum (1RM) at maximum velocity. Pre- and posttraining, the participants were tested for (1) maximum strength in the 45° leg press and chest press; (2) PFP in the 30-second chair stand, timed-up-and-go (TUG), and medicine ball throw test; and (3) quality of life. RESULTS: Both groups improved muscle strength in the 45° leg press, with greater increases for TRT (HST: +21% vs TRT: +49%, P = 0.019). There was no change in chest press strength for HST (−0.6%) (P = 0.61), but there was a significant increase for the TRT group (+21%, P = 0.001). There was a similar improvement (P < 0.05) for both groups in TUG (HST: 7%; TRT: 10%), chair stand (HST: 18%; TRT: 21%), and medicine ball throwing performance (HST: 9%; TRT: 9%), with no difference between groups (P = 0.08-0.94). Emotional aspect significantly increased by 20% (P = 0.04) in HST and 50% (P = 0.04) in TRT. CONCLUSION: Both TRT and HST are able to promote improvements in functional performance in the elderly with greater in strength gains for TRT. Therefore, exercise professionals could choose based on individual characteristics and preferences. CLINICAL RELEVANCE: The findings provide important insights into how health care professionals can prescribe HST and TRT, considering efficiency, safety, and individual aspects

Integration of biological networks and gene expression data using Cytoscape

Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape