Empowering the Participant Voice (EPV): Design and implementation of collaborative infrastructure to collect research participant experience feedback at scale.

Empowering the Participant Voice (EPV) is an NCATS-funded six-CTSA collaboration to develop, demonstrate, and disseminate a low-cost infrastructure for collecting timely feedback from research participants, fostering trust, and providing data for improving clinical translational research. EPV leverages the validated Research Participant Perception Survey (RPPS) and the popular REDCap electronic data-capture platform. This report describes the development of infrastructure designed to overcome identified institutional barriers to routinely collecting participant feedback using RPPS and demonstration use cases.

Implementing DASH-Aligned Meals and Self-Measured Blood Pressure to Reduce Hypertension at Senior Centers: A RE-AIM Analysis.

Low-income, minority seniors face high rates of hypertension that increase cardiovascular risk. Senior centers offer services, including congregate meals, that can be a valuable platform to reach older adults in underserved communities. We implemented two evidence-based interventions not previously tested in this setting: DASH-aligned congregate meals and Self-Measured Blood Pressure (SMBP), to lower blood pressure (BP) at two senior centers serving low-income, racially diverse communities.

Implementing DASH-aligned Congregate Meals and Self-Measured Blood Pressure in two senior centers: An open label study.

Background And Aims: Cardiovascular Disease (CVD) poses significant health risks for seniors, especially among low-income and minority communities. Senior centers offer multiple services. We tested whether implementing two evidence-based interventions- DASH-aligned meals provided through an existing congregate meal program, and support for home Self-Measured Blood Pressure (SMBP) monitoring-lowers blood pressure among participants at two senior centers serving low-income, racially diverse communities.

Molecular Types of Methicillin-Resistant Staphylococcus aureus and Methicillin-Sensitive S. aureus Strains Causing Skin and Soft Tissue Infections and Nasal Colonization, Identified in Community Health Centers in New York City.

In November 2011, The Rockefeller University Center for Clinical and Translational Science (CCTS), the Laboratory of Microbiology and Infectious Diseases, and Clinical Directors Network (CDN) launched a research and learning collaborative project with six community health centers in the New York City metropolitan area to determine the nature (clonal type) of community-acquired Staphylococcus aureus strains causing skin and soft tissue infections (SSTIs). Between November 2011 and March 2013, wound and nasal samples from 129 patients with active SSTIs suspicious for S. aureus were collected and characterized by molecular typing techniques.

On the combination of two visual cognition systems using combinatorial fusion.

When combining decisions made by two separate visual cognition systems, statistical means such as simple average (M ) and weighted average (M and M ), incorporating the confidence level of each of these systems have been used. Although combination using these means can improve each of the individual systems, it is not known when and why this can happen. By extending a visual cognition system to become a scoring system based on each of the statistical means M , M , and M respectively, the problem of combining visual cognition systems is transformed to the problem of combining multiple scoring systems.

TreeParser-aided Klee diagrams display taxonomic clusters in DNA barcode and nuclear gene datasets.

Indicator vector analysis of a nucleotide sequence alignment generates a compact heat map, called a Klee diagram, with potential insight into clustering patterns in evolution. However, so far this approach has examined only mitochondrial cytochrome c oxidase I (COI) DNA barcode sequences. To further explore, we developed TreeParser, a freely-available web-based program that sorts a sequence alignment according to a phylogenetic tree generated from the dataset.

Bioinformatics tools enabling u-statistics for microarrays.

It is rare that a single gene is sufficient to represent all aspects of genomic activity. Similarly, most common diseases cannot be explained by a mutations at a single locus. Since complex systems tend to be neither linear nor hierarchical in nature, but to have correlated components of unknown relative importance, the assumptions of traditional (parametric) multivariate statistical methods can rarely be justified on theoretical grounds.