Fluid/solid transition in a hard-core system

We prove that a system of particles in the plane, interacting only with a certain hard-core constraint, undergoes a fluid/solid phase transition

ATM-deficient thymic lymphoma is associated with aberrant tcrd rearrangement and gene amplification

Ataxia telangiectasia mutated (ATM) deficiency predisposes humans and mice to T lineage lymphomas with recurrent chromosome 14 translocations involving the T cell receptor α/δ (Tcra/d) locus. Such translocations have been thought to result from aberrant repair of DNA double-strand breaks (DSBs) during Tcra locus V(D)J recombination, and to require the Tcra enhancer (Eα) for Tcra rearrangement or expression of the translocated oncogene. We now show that, in addition to the known chromosome 14 translocation, ATM-deficient mouse thymic lymphomas routinely contain a centromeric fragment of chromosome 14 that spans up to the 5′ boundary of the Tcra/d locus, at which position a 500-kb or larger region centromeric to Tcra/d is routinely amplified. In addition, they routinely contain a large deletion of the telomeric end of one copy of chromosome 12. In contrast to prior expectations, the recurrent translocations and amplifications involve V(D)J recombination–initiated breaks in the Tcrd locus, as opposed to the Tcra locus, and arise independently of the Eα. Overall, our studies reveal previously unexpected mechanisms that contribute to the oncogenic transformation of ATM-deficient T lineage cells

Representing glycophenotypes: semantic unification of glycobiology resources for disease discovery.

While abnormalities related to carbohydrates (glycans) are frequent for patients with rare and undiagnosed diseases as well as in many common diseases, these glycan-related phenotypes (glycophenotypes) are not well represented in knowledge bases (KBs). If glycan-related diseases were more robustly represented and curated with glycophenotypes, these could be used for molecular phenotyping to help to realize the goals of precision medicine. Diagnosis of rare diseases by computational cross-species comparison of genotype-phenotype data has been facilitated by leveraging ontological representations of clinical phenotypes, using Human Phenotype Ontology (HPO), and model organism ontologies such as Mammalian Phenotype Ontology (MP) in the context of the Monarch Initiative. In this article, we discuss the importance and complexity of glycobiology and review the structure of glycan-related content from existing KBs and biological ontologies. We show how semantically structuring knowledge about the annotation of glycophenotypes could enhance disease diagnosis, and propose a solution to integrate glycophenotypes and related diseases into the Unified Phenotype Ontology (uPheno), HPO, Monarch and other KBs. We encourage the community to practice good identifier hygiene for glycans in support of semantic analysis, and clinicians to add glycomics to their diagnostic analyses of rare diseases

Down by the riverside: urban riparian ecology

Riparian areas are hotspots of interactions between plants, soil, water, microbes, and people. While urban land use change has been shown to have dramatic effects on watershed hydrology, there has been surpris- ingly little analysis of its effects on riparian areas. Here we examine the ecology of urban riparian zones, focusing on work done in the Baltimore Ecosystem Study, a component of the US National Science Foundation's Long Term Ecological Research network. Research in the Baltimore study has addressed how changes in hydrology associated with urbanization create riparian "hydrologic drought" by lowering water tables, which in turn alters soil, vegetation, and microbial processes. We analyze the nature of past and cur- rent human interactions with riparian ecosystems, and review other urban ecosystem studies to show how our observations mirror those in other cities

Optimal spaces for those living with dementia : principles and evidence

This paper represents a synthesis of diverse and disparate evidence in the research literature that provide insights into the impacts of aspects of the built environment on the wellbeing of those living with dementia. The individually focused findings are structured into a set of practical design parameters, driven by three overarching needs-driven design principles, namely: manageable cognitive load, clear sequencing, and appropriate level of stimulation. These needs are contextualized within a general model that suggests that action in any one area (such as the built environment) also has to take into account other key dimensions, namely any support from the caring / social environment and any pharmacological treatment. Addressing these elements holistically should maximize the opportunity to improve the quality of life of the individual. This paper, however, explicitly focuses on the built environment

Developing a vocabulary and ontology for modeling insect natural history data: example data, use cases, and competency questions

Insects are possibly the most taxonomically and ecologically diverse class of multicellular organisms on Earth. Consequently, they provide nearly unlimited opportunities to develop and test ecological and evolutionary hypotheses. Currently, however, large-scale studies of insect ecology, behavior, and trait evolution are impeded by the difficulty in obtaining and analyzing data derived from natural history observations of insects. These data are typically highly heterogeneous and widely scattered among many sources, which makes developing robust information systems to aggregate and disseminate them a significant challenge. As a step towards this goal, we report initial results of a new effort to develop a standardized vocabulary and ontology for insect natural history data. In particular, we describe a new database of representative insect natural history data derived from multiple sources (but focused on data from specimens in biological collections), an analysis of the abstract conceptual areas required for a comprehensive ontology of insect natural history data, and a database of use cases and competency questions to guide the development of data systems for insect natural history data. We also discuss data modeling and technology-related challenges that must be overcome to implement robust integration of insect natural history data

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven\u27t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits