457 research outputs found
Sembrando Esperanza
La portada del presente número está constituida por un fragmento del Mural realizado por el trabajo colectivo de varios grupos de artistas riojanos y que fuera compuesto para recordar la figura y el mensaje del obispo Enrique Angelelli
SNP discovery in proso millet (\u3ci\u3ePanicum miliaceum\u3c/i\u3e L.) using lowpass genome sequencing
Domesticated ~10,000 years ago in northern China, Proso millet (Panicum miliaceum L.) is a climate-resilient and human health-promoting cereal crop. The genome size of this self-pollinated allotetraploid is 923 Mb. Proso millet seeds are an important part of the human diet in many countries. In the USA, its use is restricted to the birdseed and pet food market. Proso millet is witnessing gradual demand in the global human health and wellness food market owing to its health-promoting properties such as low glycemic index and gluten-free. The breeding efforts for developing improved proso millet cultivars are hindered by the dearth of genomic resources available to researchers. The publication of the reference genome and availability of costeffective NGS methodologies could lead to the identification of high-quality genetic variants, which can be incorporated into breeding pipelines. Here, we report the identification of single-nucleotide polymorphisms (SNPs) by low-pass (1x) genome sequencing of 85 diverse proso millet accessions from 23 different countries. The 2 x 150 bp Illumina paired-end reads generated after sequencing were aligned to the proso millet reference genome. The resulting sequence alignment information was used to call SNPs. We obtained 972,863 bi-allelic SNPs after quality filtering of the raw SNPs. These SNPs were used to assess the population structure and phylogenetic relationships among the accessions. Most of the accessions were found to be highly inbred with heterozygosity ranging between .05 and .20. Principal component analysis (PCA) showed that PC1 (principal component) and PC2 explained 19% of the variability in the population. PCA also clustered all the genotypes into three groups. A neighbor-joining tree clustered the genotypes into four distinct groups exhibiting diverse representation within the population. The SNPs identified in our study could be used for molecular breeding and genetics research (e.g., genetic and association mapping, and population genetics) in proso millet after proper validation
СИНДРОМ ХРОНІЧНОЇ ВТОМИ ТА СУЧАСНЕ СУСПІЛЬСТВО
The article contains data of epidemiology, diagnostic criteria and social mean of chronic fatique syndrom.У статті наведено дані щодо епідеміології, клініки, діагностики та соціального значення синдрому хронічної втоми
Mouse Phenome Database
The Mouse Phenome Database (MPD; http://www.jax.org/phenome) is an open source, web-based repository of phenotypic and genotypic data on commonly used and genetically diverse inbred strains of mice and their derivatives. MPD is also a facility for query, analysis and in silico hypothesis testing. Currently MPD contains about 1400 phenotypic measurements contributed by research teams worldwide, including phenotypes relevant to human health such as cancer susceptibility, aging, obesity, susceptibility to infectious diseases, atherosclerosis, blood disorders and neurosensory disorders. Electronic access to centralized strain data enables investigators to select optimal strains for many systems-based research applications, including physiological studies, drug and toxicology testing, modeling disease processes and complex trait analysis. The ability to select strains for specific research applications by accessing existing phenotype data can bypass the need to (re)characterize strains, precluding major investments of time and resources. This functionality, in turn, accelerates research and leverages existing community resources. Since our last NAR reporting in 2007, MPD has added more community-contributed data covering more phenotypic domains and implemented several new tools and features, including a new interactive Tool Demo available through the MPD homepage (quick link: http://phenome.jax.org/phenome/trytools)
СИНДРОМ ХРОНІЧНОЇ ВТОМИ У ХВОРИХ РЕВМАТОЛОГІЧНОГО ПРОФІЛЮ
An article deals with results of the research about epidemiology of chronic fatique syndrom in patients with rheumatic diseases.У статті наведені результати дослідження щодо поширеності синдрому хронічної втоми у хворих ревматологічного профілю
SPARC-LoRa: A Scalable, Power-efficient, Affordable, Reliable, and Cloud Service-enabled LoRa Networking System for Agriculture Applications
With the rapid development of cloud and edge computing, Internet of Things
(IoT) applications have been deployed in various aspects of human life. In this
paper, we design and implement a holistic LoRa-based IoT system with LoRa
communication capabilities, named SPARC-LoRa, which consists of field sensor
nodes and a gateway connected to the Internet. SPARC-LoRa has the following
important features. First, the proposed wireless network of SPARC-LoRa is
even-driven and using off-the-shelf microcontroller and LoRa communication
modules with a customized PCB design to integrate all the hardware. This
enables SPARC-LoRa to achieve low power consumption, long range communication,
and low cost. With a new connection-based upper layer protocol design, the
scalability and communication reliability of SPARC-loRa can be achieved.
Second, an open source software including sensor nodes and servers is designed
based on Docker container with cloud storage, computing, and LTE
functionalities. In order to achieve reliable wireless communication under
extreme conditions, a relay module is designed and applied to SPARC-LoRa to
forward the data from sensor nodes to the gateway node. The system design and
implementation is completely open source and hosted on the DigitalOcean Droplet
Cloud. Hence, the proposed system enables further research and applications in
both academia and industry. The proposed system has been tested in real fields
under different and extreme environmental conditions in Salt Lake City, Utah
and the University of Nebraska-Lincoln. The experimental results validate the
features of SPARC-LoRa including low power, reliability, and cloud services
provided by SPARC-LoRa.Comment: 6 pages, 8 figures, submitted for publicatio
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