Adaptive Precoded MIMO for LTE Wireless Communication

Long-Term Evolution (LTE) and Long Term Evolution-Advanced (ATE-A) have provided a major step forward in mobile communication capability. The objectives to be achieved are high peak data rates in high spectrum bandwidth and high spectral efficiencies. Technically, pre-coding means that multiple data streams are emitted from the transmit antenna with independent and appropriate weightings such that the link throughput is maximized at the receiver output thus increasing or equalizing the received signal to interference and noise (SINR) across the multiple receiver terminals. However, it is not reliable enough to fully utilize the information transfer rate to fit the condition of channel according to the bandwidth size. Thus, adaptive pre-coding is proposed. It applies pre-coding matrix indicator (PMI) channel state making it possible to change the pre-coding codebook accordingly thus improving the data rate higher than fixed pre-coding

Exome sequencing followed by genotyping suggests SYPL2 as a susceptibility gene for morbid obesity

Recently developed high-throughput sequencing technology shows power to detect low-frequency disease-causing variants by deep sequencing of all known exons. We used exome sequencing to identify variants associated with morbid obesity. DNA from 100 morbidly obese adult subjects and 100 controls were pooled (n=10/pool), subjected to exome capture, and subsequent sequencing. At least 100 million sequencing reads were obtained from each pool. After several filtering steps and comparisons of observed frequencies of variants between obese and non-obese control pools, we systematically selected 144 obesity-enriched non-synonymous, splicing site or 5′ upstream single-nucleotide variants for validation. We first genotyped 494 adult subjects with morbid obesity and 496 controls. Five obesity-associated variants (nominal P-value<0.05) were subsequently genotyped in 1425 morbidly obese and 782 controls. Out of the five variants, only rs62623713:A>G (NM_001040709:c.A296G:p.E99G) was confirmed. rs62623713 showed strong association with body mass index (beta=2.13 (1.09, 3.18), P=6.28 × 10−5) in a joint analysis of all 3197 genotyped subjects and had an odds ratio of 1.32 for obesity association. rs62623713 is a low-frequency (2.9% minor allele frequency) non-synonymous variant (E99G) in exon 4 of the synaptophysin-like 2 (SYPL2) gene. rs62623713 was not covered by Illumina or Affymetrix genotyping arrays used in previous genome-wide association studies. Mice lacking Sypl2 has been reported to display reduced body weight. In conclusion, using exome sequencing we identified a low-frequency coding variant in the SYPL2 gene that was associated with morbid obesity. This gene may be involved in the development of excess body fat

The NIH Somatic Cell Genome Editing program.

The move from reading to writing the human genome offers new opportunities to improve human health. The United States National Institutes of Health (NIH) Somatic Cell Genome Editing (SCGE) Consortium aims to accelerate the development of safer and more-effective methods to edit the genomes of disease-relevant somatic cells in patients, even in tissues that are difficult to reach. Here we discuss the consortium\u27s plans to develop and benchmark approaches to induce and measure genome modifications, and to define downstream functional consequences of genome editing within human cells. Central to this effort is a rigorous and innovative approach that requires validation of the technology through third-party testing in small and large animals. New genome editors, delivery technologies and methods for tracking edited cells in vivo, as well as newly developed animal models and human biological systems, will be assembled-along with validated datasets-into an SCGE Toolkit, which will be disseminated widely to the biomedical research community. We visualize this toolkit-and the knowledge generated by its applications-as a means to accelerate the clinical development of new therapies for a wide range of conditions

The NIH Somatic Cell Genome Editing program.

The move from reading to writing the human genome offers new opportunities to improve human health. The United States National Institutes of Health (NIH) Somatic Cell Genome Editing (SCGE) Consortium aims to accelerate the development of safer and more-effective methods to edit the genomes of disease-relevant somatic cells in patients, even in tissues that are difficult to reach. Here we discuss the consortium's plans to develop and benchmark approaches to induce and measure genome modifications, and to define downstream functional consequences of genome editing within human cells. Central to this effort is a rigorous and innovative approach that requires validation of the technology through third-party testing in small and large animals. New genome editors, delivery technologies and methods for tracking edited cells in vivo, as well as newly developed animal models and human biological systems, will be assembled-along with validated datasets-into an SCGE Toolkit, which will be disseminated widely to the biomedical research community. We visualize this toolkit-and the knowledge generated by its applications-as a means to accelerate the clinical development of new therapies for a wide range of conditions