22 Matching Annotations
  1. Jun 2019
  2. Oct 2018
  3. Jul 2017
    1. BMI

      Test if this shows up in another list.

    2. Finally found its BMI distribution... turns out to be in demographic category. So most samples from this study have BMI > 24. Good for us.

    1. Partial loss-of-func- tion alleles cause the preferential loss of ventral structures and the expansion of remaining lateral and dorsal struc- tures (Figure 1 c) (Anderson and Niisslein-Volhard, 1988). These loss-of-function mutations in spz produce the same phenotypes as maternal effect mutations in the 10 other genes of the dorsal group.

      This paper has been curated by Flybase.

    1. Obesity rs8043757 intron FTO 16 : 53,779,538 5.000 x 10-110 NHGRI 23563607

      The top match SNP with key words: Obesity, T2D and CVD is on gene FTO.

    1. Obesity was highly prevalent among the study sample; 64.6% of females and 41.2% of males were obese according to Polynesian cutoffs (BMI ≥ 32 kg/m2). Females were less likely than males to have hypertension (31.7% vs. 36.7%) but equally likely to have diabetes (17.8% vs. 16.4%).

      Those with obesity but not hypertension or diabetes can be our candidates.

      The data set can be found here: dbGaP Study Accession: phs000972.v2.p1 https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000972.v2.p1

    1. This T2D study measured BMI, DBP, SBP and cardiovascular disease medications as well. May have samples we need.

    1. Samoans have been studied for >40 years with a focus on the increase in, and levels of, BMI, obesity, and associated cardiometabolic conditions due to economic modernization

      This one may contain the sample we need. need to check their publications.

    1. ((obesity[Disease]) NOT type 2 diabetes mellitus[Disease]) NOT cardiovascular diseases[Disease] AND 1[s_discriminator]

      NCBI can save this query for me... I can annotate this as well.

  4. Jul 2016
    1. Page 115

      Borgman makes the point here that while there is a Commons in the infrastructure of scholarly publishing there is less of a Commons in the infrastructure 4 data across disciplines.

      The infrastructure of scholarly publishing Bridges disciplines: every field produces Journal articles, conference papers, and books albeit in differing ratios. Libraries select, collect organize and make accessible publications of all types, from all fields. No comparable infrastructure exists for data. A few Fields have major mechanisms for publishing data in repositories. Some fields are in the stage of developing standards and practices to activate their data resorces and Nathan were widely accessible. In most Fields, especially Outside The Sciences, data practices remain local idiosyncratic, and oriented to current usage rather than preservation operation, and access. Most data collections Dash where they exist Dash are managed by individual agencies within disciplines, rather than by libraries are archives. Data managers usually are trained within the disciplines they serve. Only a few degree programs and information studies include courses on data management. The lack of infrastructure for data amplifies the discontinuities in scholarly publishing despite common concerns, independent debates continue about access to Publications and data.