Infinity: An In-Silico Tool for Genome-Wide Prediction of Specific DNA Matrices in miRNA Genomic Loci.

MOTIVATION: miRNAs are potent regulators of gene expression and modulate multiple cellular processes in physiology and pathology. Deregulation of miRNAs expression has been found in various cancer types, thus, miRNAs may be potential targets for cancer therapy. However, the mechanisms through which miRNAs are regulated in cancer remain unclear. Therefore, the identification of transcriptional factor-miRNA crosstalk is one of the most update aspects of the study of miRNAs regulation. RESULTS: In the present study we describe the development of a fast and user-friendly software, named infinity, able to find the presence of DNA matrices, such as binding sequences for transcriptional factors, on ~65kb (kilobase) of 939 human miRNA genomic sequences, simultaneously. Of note, the power of this software has been validated in vivo by performing chromatin immunoprecipitation assays on a subset of new in silico identified target sequences (CCAAT) for the transcription factor NF-Y on colon cancer deregulated miRNA loci. Moreover, for the first time, we have demonstrated that NF-Y, through its CCAAT binding activity, regulates the expression of miRNA-181a, -181b, -21, -17, -130b, -301b in colon cancer cells. CONCLUSIONS: The infinity software that we have developed is a powerful tool to underscore new TF/miRNA regulatory networks. AVAILABILITY AND IMPLEMENTATION: Infinity was implemented in pure Java using Eclipse framework, and runs on Linux and MS Windows machine, with MySQL database. The software is freely available on the web at https://github.com/bio-devel/infinity. The website is implemented in JavaScript, PHP and HTML with all major browsers supported.

Physiological aging impacts the hemispheric balances of resting state primary somatosensory activities.

To hone knowledge of sensorimotor cerebral organization changes with physiological aging, we focused on the primary somatosensory cortical area (S1). S1 neuronal pools (FS_S1) were identified by the functional source separation (FSS) algorithm applied to magnetoencephalographic recordings during median nerve stimulation. Age-dependence of FS_S1 was then studied at rest separately in the left and right hemispheres of 26 healthy, right-handed subjects between the ages of 24 and 95 years. The resting state FS_S1 spectral features changed with increasing age: (1) alpha activity slowed down; (2) total power increased only in the right hemisphere; (3) right>left interhemispheric asymmetry increased in the whole spectrum; (4) spectral entropy increased with age selectively in the left hemisphere. The present FSS-enriched electrophysiological procedure provided measures of resting state hand representation area sensitive to changes with age. Alterations were stronger in the right hemisphere. Relationships between resting state S1 activity and its responsiveness to external stimuli, revealed that the interhemispheric unbalances which emerged with age were conceivably due to an increased excitability within the right thalamocortical circuit impacting left versus right unbalances of spontaneous firing rates and of local inhibitory-excitatory networks.

Nonlinear surface EMG analysis to detect changes of motor unit conduction velocity and synchronization.

Amplitude and frequency content of the surface electromyographic (EMG) signal reflect central and peripheral modifications of the neuromuscular system. Classic surface EMG spectral variables applied to assess muscle functions are the centroid and median power spectral frequencies. More recently, nonlinear tools have been introduced to analyze the surface EMG; among them, the recurrence quantification analysis (RQA) was shown to be particularly promising for the detection of muscle status changes. The purpose of this work was to analyze the effect of motor unit short-term synchronization and conduction velocity (CV) on EMG spectral variables and two variables extracted by RQA, the percentage of recurrence (%Rec) and determinism (%Det). The study was performed on the basis of a simulation model, which allowed changing the degree of synchronization and mean CV of a number of motor units, and of an experimental investigation of the surface EMG signal properties detected during high-force-level isometric fatiguing contractions of the biceps brachii muscle. Simulations and experimental results were largely in agreement and show that 1) spectral variables, %Rec, and %Det are influenced by CV and degree of synchronization; 2) spectral variables are highly correlated with %Det (R = -0.95 in the simulations and -0.78 and -0.75 for the initial values and normalized slopes, respectively, in the experimental signals), and thus the information they provide on muscle properties is basically the same; and 3) variations of %Det and %Rec in response to changes in muscle properties are significantly larger than the variations of spectral variables. This study validates RQA as a means for fatigue assessment with potential advantages (such as the higher sensitivity to changes of muscle status) with respect to the classic spectral analysis.