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Survival for any organism, including people, is a matter of resource management. To ensure survival, people necessarily budget their resources. Spatial perceptions contribute to resource budgeting by scaling the environment to an individual's available resources. Effective budgeting requires setting a balance of income and expenditures around some baseline value. For social resources, this baseline assumes that the individuals are embedded in their social network. A review of the literature supports the proposal that our visual perceptions vary based on the implicit budgeting of physical and social resources, where social resources, as they fluctuate relative to a baseline, can directly alter our visual perceptions.

Enzymes catalyse radical-mediated fluorine atom transfer reactions for enantioselective C(sp3)-F bond formation.

Precision medicine envisions a future of effective diagnosis, treatment, and prevention grounded in precise understandings of the genetic and environmental determinants of disease. Given that the original genome-wide association studies represented a predominately European White population, and that diversity in genomic studies must account for genetic variation both within and across racial categories, new research studies are at a heightened risk for inadequate representation. Currently biological samples are being made available for sequencing in biobanks across the USA, but the diversity of those samples is unknown. The aims of this study were to describe the types of recruitment and enrollment materials used by US biobanks and the diversity of the samples contained within their collection. Biobank websites and brochures were evaluated for reading level, health literacy, and factors known to encourage the recruitment of minorities, such as showing pictures of diverse populations. Biobank managers were surveyed by mail on the methods and materials used for enrollment, recruitment, consent, and the self-reported race/ethnicity of biobank participants. From 51 US biobanks (68% response rate), recruitment and enrollment materials were in English only, and most of the websites and brochures exceeded a fifth-grade reading level. When compared to the 2015 US Census, self-reported race/ethnicity of participants was not significantly different for Whites (61%) and blacks (13%). The percentages were significantly lower for Hispanics and Latinos (18 vs. 7%, p = 0.00) and Hawaiian/Pacific Islanders (0.2 vs. 0.01%; p = 0.01) and higher for Asians (13 vs. 5%, p = 0.01). Materials for recruitment predominantly in English may limit participation by underrepresented populations.

Achieving equitable minority representation in genomic biobanking is one of the most difficult challenges faced by researchers today. Capacity building—a framework for research that includes collaborations and on-going engagement—can be used to help researchers, clinicians and communities better understand the process, utility, and clinical application of genomic science. The purpose of this exploratory descriptive study was to examine factors that influence the decision to participate in genomic research, and identify essential components of capacity building with a community at risk of being under-represented in biobanks. Results of focus groups conducted in Central Harlem with 46 participants were analyzed by a collaborative team of community and academic investigators using content analysis and AtlisTi. Key themes identified were: (1) the potential contribution of biobanking to individual and community health, for example the effect of the environment on health, (2) the societal context of the science, such as DNA criminal databases and paternity testing, that may affect the decision to participate, and (3) the researchers’ commitment to community health as an outcome of capacity building. These key factors can contribute to achieving equity in biobank participation, and guide genetic specialists in biobank planning and implementation.

Community engagement (CE) is critical for advancing health equity and a key approach for promoting inclusive clinical and translational science. However, it requires a workforce trained to effectively design, implement, and evaluate health promotion and improvement strategies through meaningful collaboration with community members. This paper presents an approach for designing CE curricula for research, education, clinical care, and public health learners. A general pedagogical framework is presented to support curriculum development with the inclusion of community members as facilitators or faculty. The overall goal of the curriculum is envisioned as enabling learners to effectively demonstrate the principles of CE in working with community members on issues of concern to communities to promote health and well-being. We highlight transformations needed for the commonly used critical service-learning model and the importance of faculty well-versed in CE. Courses may include didactics and practicums with well-defined objectives and evaluation components. Because of the importance of building and maintaining relationships in CE, a preparatory phase is recommended prior to experiential learning, which should be guided and designed to include debriefing and reflective learning. Depending on the scope of the course, evaluation should include community perspectives on the experience.

The maximum likelihood threshold of a graph is the smallest number of data points that guarantees that maximum likelihood estimates exist almost surely in the Gaussian graphical model associated to the graph. We show that this graph parameter is connected to the theory of combinatorial rigidity. In particular, if the edge set of a graph G is an independent set in the (n – 1)-dimensional generic rigidity matroid, then the maximum likelihood threshold of G is less than or equal to n. This connection allows us to prove many results about the maximum likelihood threshold. We conclude by showing that these methods give exact bounds on the number of observations needed for the score matching estimator to exist with probability one.

Phylogenetic networks represent evolutionary histories of sets of taxa where horizontal evolution or hybridization has occurred. Placing a Markov model of evolution on a phylogenetic network gives a model that is particularly amenable to algebraic study by representing it as an algebraic variety. In this paper, we give a formula for the dimension of the variety corresponding to a triangle-free level-1 phylogenetic network under a group-based evolutionary model. On our way to this, we give a dimension formula for codimension zero toric fiber products. We conclude by illustrating applications to identifiability.

Brownian Dynamics (BD) computer simulations were used to study electrostatic interactions between turnip cytochrome f (cyt f) and spinach plastocyanin (PC). Three different spinach PC structures were studied: The X-ray crystal structure of Xue and coworkers [(1998) Protein Sci 7:2099-2105] and the NMR structure of Musiani et al. [(2005) J Biol Chem 280:18833-18841] and Ubbink and co-workers [(1998) Structure 6:323-335]. Significant differences exist in the backbone conformation between the PC taken from Ubbink and coworkers and the other two PC structures particularly the regions surrounding G10, E59-E60, and D51. Complexes formed in BD simulations using the PC of Ubbink and colleagues had a smaller Cu-Fe distance than the other two. These results suggest that different PC conformations may exist in solution with different capabilities of forming electron-transfer-active docks. All three types of complexes show electrostatic contacts between D42, E43, and D44 on PC and K187 on cyt f as well as between E59 on PC and K58 on cyt f. However, the PC of Ubbink and coworkers reveals additional contacts between D51 and cyt f as a result of the difference in backbone configuration. A second minor complex component was observed for the PC of Ubbink and co-workers and Xue and co-workers which had contacts between K187 on cyt f and E59 and E60 on PC rather than between K187 on cyt f and D42-D44 on PC as observed for the major components. This second type of complex may represent an earlier complex which rearranges to form a final complex capable of electron transfer.

In systems and synthetic biology, much research has focused on the behavior and design of single pathways, while, more recently, experimental efforts have focused on how cross-talk (coupling two or more pathways) or inhibiting molecular function (isolating one part of the pathway) affects systems-level behavior. However, the theory for tackling these larger systems in general has lagged behind. Here, we analyze how joining networks (e.g., cross-talk) or decomposing networks (e.g., inhibition or knock-outs) affects three properties that reaction networks may possess—identifiability (recoverability of parameter values from data), steady-state invariants (relationships among species concentrations at steady state, used in model selection), and multistationarity (capacity for multiple steady states, which correspond to multiple cell decisions). Specifically, we prove results that clarify, for a network obtained by joining two smaller networks, how properties of the smaller networks can be inferred from or can imply similar properties of the original network. Our proofs use techniques from computational algebraic geometry, including elimination theory and differential algebra.

Modeling interindividual variation in internal doses in humans using PBPK models requires data on the variation in physiological parameters across the population of interest. These data should also reflect the correlations between the values of the various parameters in a person. In this project, we develop a source of data for human physiological parameters where (1) the parameter values for an individual are correlated with one another, and (2) values of parameters capture interindividual variation in populations of a specific gender, race, and age range. The parameters investigated in this project include: (1) volumes of selected organs and tissues; (2) blood flows for the organs and tissues; and (3) the total cardiac output under resting conditions and average daily inhalation rate. These parameters are expressed as records of correlated values for the approximately 30,000 individuals evaluated in the NHANES III survey. A computer program, Physiological Parameters for PBPK Modeling (P 3 M), is developed that allows records to be retrieved randomly from the database with specification of constraints on age, sex, and ethnicity. P 3 M is publicly available. The database and accompanying software provide a convenient tool for parameterizating models of interindividual variation in human pharmacokinetics.