University of Texas Health Science Center at Houston

About: University of Texas Health Science Center at Houston is a education organization based out in Houston, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 27309 authors who have published 42520 publications receiving 2151596 citations. The organization is also known as: UTHealth & The UT Health Science Center at Houston.

Implementation Mapping: Using Intervention Mapping to Develop Implementation Strategies.

Abstract: Background: The ultimate impact of a health innovation depends not only on its effectiveness but also on its reach in the population and the extent to which it is implemented with high levels of completeness and fidelity. Implementation science has emerged as the potential solution to the failure to translate evidence from research into effective practice and policy evident in many fields. Implementation scientists have developed many frameworks, theories and models, which describe implementation determinants, processes, or outcomes; yet, there is little guidance about how these can inform the development or selection of implementation strategies (methods or techniques used to improve adoption, implementation, sustainment, and scale-up of interventions) (1, 2). To move the implementation science field forward and to provide a practical tool to apply the knowledge in this field, we describe a systematic process for planning or selecting implementation strategies: Implementation Mapping. Methods: Implementation Mapping is based on Intervention Mapping (a six-step protocol that guides the design of multi-level health promotion interventions and implementation strategies) and expands on Intervention Mapping step 5. It includes insights from both the implementation science field and Intervention Mapping. Implementation Mapping involves five tasks: (1) conduct an implementation needs assessment and identify program adopters and implementers; (2) state adoption and implementation outcomes and performance objectives, identify determinants, and create matrices of change objectives; (3) choose theoretical methods (mechanisms of change) and select or design implementation strategies; (4) produce implementation protocols and materials; and (5) evaluate implementation outcomes. The tasks are iterative with the planner circling back to previous steps throughout this process to ensure all adopters and implementers, outcomes, determinants, and objectives are addressed. Discussion: Implementation Mapping provides a systematic process for developing strategies to improve the adoption, implementation, and maintenance of evidence-based interventions in real-world settings.

Exploring population size changes using SNP frequency spectra

Abstract: Inferring demographic history is an important task in population genetics. Many existing inference methods are based on predefined simplified population models, which are more suitable for hypothesis testing than exploratory analysis. We developed a novel model-flexible method called stairway plot, which infers changes in population size over time using SNP frequency spectra. This method is applicable for whole-genome sequences of hundreds of individuals. Using extensive simulation, we demonstrate the usefulness of the method for inferring demographic history, especially recent changes in population size. We apply the method to the whole-genome sequence data of 9 populations from the 1000 Genomes Project and show a pattern of fluctuations in human populations from 10,000 to 200,000 years ago.

Dielectrophoresis-based sample handling in general-purpose programmable diagnostic instruments

Abstract: As the molecular origins of disease are better understood, the need for affordable, rapid, and automated technologies that enable microscale molecular diagnostics has become apparent. Widespread use of microsystems that perform sample preparation and molecular analysis could ensure that the benefits of new biomedical discoveries are realized by a maximum number of people, even those in environments lacking any infrastructure. While progress has been made in developing miniaturized diagnostic systems, samples are generally processed off-device using labor-intensive and time-consuming traditional sample preparation methods. We present the concept of an integrated programmable general-purpose sample analysis processor (GSAP) architecture where raw samples are routed to separation and analysis functional blocks contained within a single device. Several dielectrophoresis-based methods that could serve as the foundation for building GSAP functional blocks are reviewed including methods for cell and particle sorting, cell focusing, cell ac impedance analysis, cell lysis, and the manipulation of molecules and reagent droplets.