76 research outputs found
Clinical identification of feeding and swallowing disorders in 0-6 month old infants with Down syndrome
Feeding and swallowing disorders have been described in children with a variety of neurodevelopmental disabilities, including Down syndrome (DS). Abnormal feeding and swallowing can be associated with serious sequelae such as failure to thrive and respiratory complications, including aspiration pneumonia. Incidence of dysphagia in young infants with DS has not previously been reported. To assess the identification and incidence of feeding and swallowing problems in young infants with DS, a retrospective chart review of 174 infants, ages 0-6 months was conducted at a single specialty clinic. Fifty-seven percent (100/174) of infants had clinical concerns for feeding and swallowing disorders that warranted referral for Videofluroscopic Swallow Study (VFSS); 96/174 (55%) had some degree of oral and/or pharyngeal phase dysphagia and 69/174 (39%) had dysphagia severe enough to warrant recommendation for alteration of breast milk/formula consistency or nonoral feeds. Infants with certain comorbidities had significant risk for significant dysphagia, including those with functional airway/respiratory abnormalities (OR = 7.2). Infants with desaturation with feeds were at dramatically increased risk (OR = 15.8). All young infants with DS should be screened clinically for feeding and swallowing concerns. If concerns are identified, consideration should be given to further evaluation with VFSS for identification of dysphagia and additional feeding modifications
Database resources of the National Center for Biotechnology Information
In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data retrieval systems and computational resources for the analysis of data in GenBank and other biological data made available through NCBI's website. NCBI resources include Entrez, Entrez Programming Utilities, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, RefSeq, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Clusters of Orthologous Groups (COGs), Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheritance in Man (OMIM), the Molecular Modeling Database (MMDB), the Conserved Domain Database (CDD) and the Conserved Domain Architecture Retrieval Tool (CDART). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized datasets. All of the resources can be accessed through the NCBI home page at http://www.ncbi.nlm.nih.gov
Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images
of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL
maps are derived through computational staining using a convolutional neural network trained to
classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and
correlation with overall survival. TIL map structural patterns were grouped using standard
histopathological parameters. These patterns are enriched in particular T cell subpopulations
derived from molecular measures. TIL densities and spatial structure were differentially enriched
among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial
infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic
patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for
the TCGA image archives with insights into the tumor-immune microenvironment
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Virology—the path forward
In the United States (US), biosafety and biosecurity oversight of research on viruses is being reappraised. Safety in virology research is paramount and oversight frameworks should be reviewed periodically. Changes should be made with care, however, to avoid impeding science that is essential for rapidly reducing and responding to pandemic threats as well as addressing more common challenges caused by infectious diseases. Decades of research uniquely positioned the US to be able to respond to the COVID-19 crisis with astounding speed, delivering life-saving vaccines within a year of identifying the virus. We should embolden and empower this strength, which is a vital part of protecting the health, economy, and security of US citizens. Herein, we offer our perspectives on priorities for revised rules governing virology research in the US
A communal catalogue reveals Earth’s multiscale microbial diversity
Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity
A communal catalogue reveals Earth's multiscale microbial diversity
Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.Peer reviewe
A framework for human microbiome research
A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies
Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.
Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels
Structure, function and diversity of the healthy human microbiome
Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in
part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273
to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander;
U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.;
U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.;
R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.;
R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to
D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and
R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.;
R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was
supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves
and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang,
F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J.
V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.);
DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research;
U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and
R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and
D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research
Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF
DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US
Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL
Laboratory-Directed Research and Development grant 20100034DR and the US
Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research
Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career
Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe
J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by
the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial
Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of
Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis
of the HMPdata was performed using National Energy Research Scientific Computing
resources, the BluBioU Computational Resource at Rice University
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