Double pulsed field gradient diffusion MRI to assess skeletal muscle microstructure.

PURPOSE: Preliminary study to determine whether double pulsed field gradient (PFG) diffusion MRI is sensitive to key features of muscle microstructure related to function. METHODS: The restricted diffusion profile of molecules in models of muscle microstructure derived from histology were systematically simulated using a numerical simulation approach. Diffusion tensor subspace imaging analysis of the diffusion signal was performed, and spherical anisotropy (SA) was calculated for each model. Linear regression was used to determine the predictive capacity of SA on the fiber area, fiber diameter, and surface area to volume ratio of the models. Additionally, a rat model of muscle hypertrophy was scanned using a single PFG and a double PFG pulse sequence, and the restricted diffusion measurements were compared with histological measurements of microstructure. RESULTS: Excellent agreement between SA and muscle fiber area (r2 = 0.71; p < 0.0001), fiber diameter (r2 = 0.83; p < 0.0001), and surface area to volume ratio (r2 = 0.97; p < 0.0001) in simulated models was found. In a scanned rat leg, the distribution of these microstructural features measured from histology was broad and demonstrated that there is a wide variance in the microstructural features observed, similar to the SA distributions. However, the distribution of fractional anisotropy measurements in the same tissue was narrow. CONCLUSIONS: This study demonstrates that SA-a scalar value from diffusion tensor subspace imaging analysis-is highly sensitive to muscle microstructural features predictive of function. Furthermore, these techniques and analysis tools can be translated to real experiments in skeletal muscle. The increased dynamic range of SA compared with fractional anisotropy in the same tissue suggests increased sensitivity to detecting changes in tissue microstructure.

Induced emission of Alfvén waves in inhomogeneous streaming plasma: implications for solar corona heating and solar wind acceleration.

The results of a self-consistent kinetic model of heating the solar corona and accelerating the fast solar wind are presented for plasma flowing in a nonuniform magnetic field configuration of near-Sun conditions. The model is based on a scale separation between the large transit or inhomogeneity scales and the small dissipation scales. The macroscale instability of the marginally stable particle distribution function compliments the resonant frequency sweeping dissipation of transient Alfvén waves by their induced emission in inhomogeneous streaming plasma that provides enough energy for keeping the plasma temperature decaying not faster than r(-1) in close agreement with in situ heliospheric observations.

YOABS: yet other aligner of biological sequences--an efficient linearly scaling nucleotide aligner.

MOTIVATION: Explosive growth of short-read sequencing technologies in the recent years resulted in rapid development of many new alignment algorithms and programs. But most of them are not efficient or not applicable for reads > or approximately equal to 200 bp because these algorithms specifically designed to process short queries with relatively low sequencing error rates. However, the current trend to increase reliability of detection of structural variations in assembled genomes as well as to facilitate de novo sequencing demand complimenting high-throughput short-read platforms with long-read mapping. Thus, algorithms and programs for efficient mapping of longer reads are becoming crucial. However, the choice of long-read aligners effective in terms of both performance and memory are limited and includes only handful of hash table (BLAT, SSAHA2) or trie (Burrows-Wheeler Transform - Smith-Waterman (BWT-SW), Burrows-Wheeler Alignerr - Smith-Waterman (BWA-SW)) based algorithms. RESULTS: New O(n) algorithm that combines the advantages of both hash and trie-based methods has been designed to effectively align long biological sequences (> or approximately equal to 200 bp) against a large sequence database with small memory footprint (e.g. ~2 GB for the human genome). The algorithm is accurate and significantly more fast than BLAT or BWT-SW, but similar to BWT-SW it can find all local alignments. It is as accurate as SSAHA2 or BWA-SW, but uses 3+ times less memory and 10+ times faster than SSAHA2, several times faster than BWA-SW with low error rates and almost two times less memory. AVAILABILITY AND IMPLEMENTATION: The prototype implementation of the algorithm will be available upon request for non-commercial use in academia (local hit table binary and indices are at ftp://styx.ucsd.edu).