The Taxpayer Relief Act of 1997 and Homeownership: Is Smaller Now Better?

Prior to 1997, homeowners under 55 were allowed to defer capital gains taxes from a home sale if they bought another house at least as expensive, while those over 55 received a capital gains exclusion regardless of the cost of their new home. The Taxpayer Relief Act of 1997 (TRA97) eliminated this differential tax treatment. We exploit the differential treatment before 1997 to uncover TRA97’s effects. Comparing homeowners under 55 before and after 1997, we find that those who moved after 1997 are twice as likely as to list “seeking less expensive housing” as a reason for moving, 8 percent less likely to own their residences and 9 percent less likely to live in a single family home.

The Taxpayer Relief Act Of 1997 And Homeownership: Is Smaller Now Better?

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106064/1/ecin.12056.pd

Cultivation of common bacterial species and strains from human skin, oral, and gut microbiota.

BACKGROUND: Genomics-driven discoveries of microbial species have provided extraordinary insights into the biodiversity of human microbiota. In addition, a significant portion of genetic variation between microbiota exists at the subspecies, or strain, level. High-resolution genomics to investigate species- and strain-level diversity and mechanistic studies, however, rely on the availability of individual microbes from a complex microbial consortia. High-throughput approaches are needed to acquire and identify the significant species- and strain-level diversity present in the oral, skin, and gut microbiome. Here, we describe and validate a streamlined workflow for cultivating dominant bacterial species and strains from the skin, oral, and gut microbiota, informed by metagenomic sequencing, mass spectrometry, and strain profiling. RESULTS: Of total genera discovered by either metagenomic sequencing or culturomics, our cultivation pipeline recovered between 18.1-44.4% of total genera identified. These represented a high proportion of the community composition reconstructed with metagenomic sequencing, ranging from 66.2-95.8% of the relative abundance of the overall community. Fourier-Transform Infrared spectroscopy (FT-IR) was effective in differentiating genetically distinct strains compared with whole-genome sequencing, but was less effective as a proxy for genetic distance. CONCLUSIONS: Use of a streamlined set of conditions selected for cultivation of skin, oral, and gut microbiota facilitates recovery of dominant microbes and their strain variants from a relatively large sample set. FT-IR spectroscopy allows rapid differentiation of strain variants, but these differences are limited in recapitulating genetic distance. Our data highlights the strength of our cultivation and characterization pipeline, which is in throughput, comparisons with high-resolution genomic data, and rapid identification of strain variation

A Simple Standard for Sharing Ontological Mappings (SSSOM).

Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR). The SSSOM specification can be found at http://w3id.org/sssom/spec. Database URL: http://w3id.org/sssom/spec

Understanding the barriers to successful adoption and use of a mobile health information system in a community health center in São Paulo, Brazil: a cohort study

BACKGROUND: Mobile technology to support community health has surged in popularity, yet few studies have systematically examined usability of mobile platforms for this setting. METHODS: We conducted a mixed-methods study of 14 community healthcare workers at a public healthcare clinic in São Paulo, Brazil. We held focus groups with community healthcare workers to elicit their ideas about a mobile health application and used this input to build a prototype app. A pre-use test survey was administered to all participants, who subsequently use-tested the app on three different devices (iPhone, iPad mini, iPad Air). Usability was assessed by objectively scored data entry errors and through a post-use focus group held to gather open-ended feedback on end-user satisfaction. RESULTS: All of the participants were women, ranging from 18–64 years old. A large percentage (85.7%) of participants had at least a high school education. Internet (92.8%), computer (85.7%) and cell phone (71.4%) use rates were high. Data entry error rates were also high, particularly in free text fields, ranging from 92.3 to 100%. Error rates were comparable across device type. In a post-use focus group, participants reported that they found the app easy to use and felt that its design was consistent with their vision. The participants raised several concerns, including that they did not find filling out the forms in the app to be a useful task. They also were concerned about an app potentially creating more work for them and personal security issues related to carrying a mobile device in low-income areas. CONCLUSION: In a cohort of formally educated community healthcare workers with high levels of personal computer and cell phone use, we identified no technological barriers to adapting their existing work to a mobile device based system. Transferring current data entry work into a mobile platform, however, uncovered underlying dissatisfaction with some data entry tasks. This dissatisfaction may be a more significant barrier than the data entry errors our testing revealed. Our results highlight the fact that without a deep understanding of local process to optimize usability, technology-based solutions in health may fail. Developing such an understanding must be a central component in the design of any mHealth solution in global health

biopragmatics/biomappings:

<ul> <li>Improve curation interface</li> <li>Add new tools for generating predictions from PyOBO/Gilda</li> <li>Add additional curations for CCLE (thanks @ALHoyt)</li> <li>Import ComPath</li> <li>Add APICURON upload</li> </ul&gt

biomappings/biomappings:

<ul> <li>Refactor gilda predictions pipeline</li> <li>Add major curation of DOID-MeSH by @ALHoyt </li> </ul&gt

biopragmatics/biomappings: v0.3.0 - Publication revision

<p>This release corresponds to the changes that go with the re-submission of the biomappings paper.</p> What's Changed <ul> <li>Assess curation precision by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/113">https://github.com/biopragmatics/biomappings/pull/113</a></li> <li>Add sort by confidence to web app by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/75">https://github.com/biopragmatics/biomappings/pull/75</a></li> <li>Add epidemiology curation by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/115">https://github.com/biopragmatics/biomappings/pull/115</a></li> <li>Cleanup and update by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/116">https://github.com/biopragmatics/biomappings/pull/116</a></li> <li>Improve prediction linting by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/118">https://github.com/biopragmatics/biomappings/pull/118</a></li> <li>Propagate metadata from predictions into curated files by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/117">https://github.com/biopragmatics/biomappings/pull/117</a></li> </ul> <p><strong>Full Changelog</strong>: <a href="https://github.com/biopragmatics/biomappings/compare/v0.2.0...v0.3.0">https://github.com/biopragmatics/biomappings/compare/v0.2.0...v0.3.0</a></p&gt

biopragmatics/biomappings: v0.2.0

<p>This release prepares for the Biomappings paper submission (probably that no more curations are necessary before next release).</p> What's Changed <ul> <li>Add predictions and curations for MeSH-ChEBI equivalences by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/70">https://github.com/biopragmatics/biomappings/pull/70</a></li> <li>Predict DOID mappings to UMLS, MeSH, and EFO by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/68">https://github.com/biopragmatics/biomappings/pull/68</a></li> <li>Add more specific script URL for predictions by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/76">https://github.com/biopragmatics/biomappings/pull/76</a></li> <li>Assorted DOID and ChEBI curations by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/74">https://github.com/biopragmatics/biomappings/pull/74</a></li> <li>Add manually curated PubChem-MeSH mappings by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/77">https://github.com/biopragmatics/biomappings/pull/77</a></li> <li>Remove DOID mappings where primary mappings exist by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/79">https://github.com/biopragmatics/biomappings/pull/79</a></li> <li>Remove more redundant predictions and curate some DOID mappings by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/80">https://github.com/biopragmatics/biomappings/pull/80</a></li> <li>More manual DOID-MeSH curation by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/81">https://github.com/biopragmatics/biomappings/pull/81</a></li> <li>Add UBERON-MeSH mappings by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/86">https://github.com/biopragmatics/biomappings/pull/86</a></li> <li>Generate and curate a new set of MESH-CHEBI mappings by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/89">https://github.com/biopragmatics/biomappings/pull/89</a></li> <li>Predict and curate CL-MESH mappings by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/91">https://github.com/biopragmatics/biomappings/pull/91</a></li> <li>Miscellaneous curation by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/92">https://github.com/biopragmatics/biomappings/pull/92</a></li> <li>More curations by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/93">https://github.com/biopragmatics/biomappings/pull/93</a></li> <li>Curate MONDO-MeSH mappings by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/95">https://github.com/biopragmatics/biomappings/pull/95</a></li> <li>Add AGRO-AGROVOC mappings by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/83">https://github.com/biopragmatics/biomappings/pull/83</a></li> <li>Curate AGRO-AGROVOC-Mappings by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/97">https://github.com/biopragmatics/biomappings/pull/97</a></li> <li>Add predicted WikiPathways orthologs by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/59">https://github.com/biopragmatics/biomappings/pull/59</a></li> <li>Additional curation and updates for bioregistry by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/98">https://github.com/biopragmatics/biomappings/pull/98</a></li> <li>Improve interface by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/99">https://github.com/biopragmatics/biomappings/pull/99</a></li> <li>Update MONDO local unique identifiers by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/105">https://github.com/biopragmatics/biomappings/pull/105</a></li> <li>Curate additional DOID-MESH mappings and contribute to DOID by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/104">https://github.com/biopragmatics/biomappings/pull/104</a></li> <li>Some MeSH curations by @bgyori in <a href="https://github.com/biopragmatics/biomappings/pull/107">https://github.com/biopragmatics/biomappings/pull/107</a></li> <li>Add hetionet duplication and value added notebooks by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/102">https://github.com/biopragmatics/biomappings/pull/102</a></li> <li>Add project governance documentation by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/106">https://github.com/biopragmatics/biomappings/pull/106</a></li> <li>Fill out project skeleton by @cthoyt in <a href="https://github.com/biopragmatics/biomappings/pull/108">https://github.com/biopragmatics/biomappings/pull/108</a></li> </ul> <p><strong>Full Changelog</strong>: <a href="https://github.com/biopragmatics/biomappings/compare/v0.1.2...v0.2.0">https://github.com/biopragmatics/biomappings/compare/v0.1.2...v0.2.0</a></p&gt