Estimating the total genetic diversity of a spatial field population from a sample and implications of its dependence on habitat area

The total genetic diversity of a species is a key factor in its persistence and conservation. Because realistic sample sizes are far smaller than the total population, it is impractical to exhaustively characterize diversity of most populations. Here, we demonstrate the possibility of calculating the genetic diversity of a spatial population from a sample using genealogical models. We trace the history of a population by simulating the locations of the ancestors of a particular sample of the population backwards in time. We use this method to estimate the genetic diversity of the global population of Pseudomonas bacteria. The same results are obtained whether using a global sample or a subsample restricted to a particular geographic region (California). The results are also validated by comparing additional predictions of the model to the data. Furthermore, we use these results to show that the level of genetic diversity in a population depends strongly on the size of its habitat, much more strongly than does biodiversity as measured by the number of species. The strong dependence of diversity on habitat area has significant implications for conservation strategies.     

Workplace lactation support, Part I: A return-to-work breastfeeding assessment tool.

As health professionals with expertise in the physiological and social aspects of breastfeeding, lactation consultants are in a unique position to help new mothers succeed at combining breastfeeding and employment. This involves helping women address logistical and interpersonal issues in the workplace as well as the mechanics of safe pumping and storage of breast milk. This article describes a return-to-work breastfeeding assessment tool designed to help lactation consultants evaluate clients' workplace lactation support. It also offers suggestions for use of this tool and other exercises to help new mothers negotiate the time, space and workplace support necessary to continue nursing upon return to work. The second part of this series addresses how lactation consultants can work with employers to support workplace lactation.     

Developing a Mobile Produce Distribution System for Low-Income Urban Residents in Food Deserts

Low-income households in the contemporary city often lack adequate access to healthy foods, like fresh produce, due to a variety of social and spatial barriers that result in neighborhoods being underserved by full-service supermarkets. Because of this, residents commonly resort to purchasing food at fast food restaurants or convenience stores with poor selections of produce. Research has shown that maintaining a healthy diet contributes to disease prevention and overall quality of life. This research seeks to increase low-income residents’ access to healthy foods by addressing spatial constraints through the characterization of a mobile market distribution system model that serves in-need neighborhoods. The model optimally locates mobile markets based on the geographic distribution of these residents. Using data from the medium-sized city of Buffalo, New York, results show that, with relatively few resources, the model increases these residents’ access to healthy foods, helping to create a healthier city.     

Response of complex networks to stimuli

We consider the response of complex systems to stimuli and argue for the importance of both sensitivity, the possibility of large response to small stimuli, and robustness, the possibility of small response to large stimuli. Using a dynamic attractor network model for switching of patterns of behavior, we show that the scale-free topologies often found in nature enable more sensitive response to specific changes than do random networks. This property may be essential in networks where appropriate response to environmental change is critical and may, in such systems, be more important than features, such as connectivity, often used to characterize network topologies. Phenomenologically observed exponents for functional scale-free networks fall in a range corresponding to the onset of particularly high sensitivities, while still retaining robustness.     

Applications of Complex Systems Science in Obesity and Noncommunicable Chronic Disease Research

Interest in the application of systems science (SS) to obesity and noncommunicable chronic disease (NCD) research has been growing rapidly over the past decade as the epidemic of obesity and NCDs continues to grow globally. This article summarizes the key messages of the presentations made in the special symposium “Applications of Complex Systems Science in Obesity and Noncommunicable Chronic Disease Research,” held during the ASN Scientific Sessions and Annual Meeting at Experimental Biology 2014. Invited leaders from various fields presented cutting-edge aspects of the applications of SS in public health research, with a focus on obesity and NCDs. In addition, the symposium was capped with a discussion on funding opportunities from the NIH. The speakers described the nature of SS, how it could be applied to biomedical and public health research, lessons from SS to inform obesity and NCD interventions, and the promises, challenges, and recommendations going forward.     

Improving the effectiveness of health care and public health: a multiscale complex systems analysis

The US health care system is struggling with a mismatch between the large, simple (low-information) financial flow and the complex (high-information) treatment of individual patients. Efforts to implement cost controls and industrial efficiency that are appropriate for repetitive tasks but not high-complexity tasks lead to poor quality of care. Multiscale complex systems analysis suggests that an important step toward relieving this structural problem is a separation of responsibility for 2 distinct types of tasks: medical care of individual patients and prevention/population health. These distinct tasks require qualitatively different organizational structures. The current use of care providers and organizations for both purposes leads to compromises in organizational process that adversely affect the ability of health care organizations to provide either individual or prevention/population services. Thus, the overall system can be dramatically improved by establishing 2 separate but linked systems with distinct organizational forms: (a) a high-efficiency system performing large-scale repetitive tasks such as screening tests, inoculations, and generic health care, and (b) a high-complexity system treating complex medical problems of individual patients.     

Fanconi anaemia group A (FANCA) mutations in Israeli non-Ashkenazi Jewish patients

Fanconi anaemia (FA) is a genetically heterogeneous disease with at least eight complementation groups (A-H). In the present study, we investigated the molecular basis of the disease in 13 unrelated Israeli Jewish (non-Ashkenazi) patients with FA. All 43 exons of the Fanconi anaemia A (FANCA) gene were amplified from genomic DNA and screened for mutations by single-strand conformation polymorphism and DNA sequencing. We identified four ethnic-specific mutations: (1) 2172-2173insG (exon 24), the first 'Moroccan mutation': (2) 4275delT (exon 43), the second 'Moroccan mutation'; (3) 890-893del (exon 10), the 'Tunisian mutation'; and (4) 2574C > G (S858R), the 'Indian mutation'. The tetranucleotide CCTG motif, previously identified as a mutation hotspot in FANCA and other human genes, was found in the vicinity of 2172-2173insG and 890-893del. According to our study, the four mutations account for the majority (88%) of the FANCA alleles in the Israeli Jewish (non-Ashkenazi) FA population. A screening of 300 Moroccan Jews identified three carriers of the first 'Moroccan mutation', but we did not find any carrier of the second 'Moroccan mutation' among 140 Moroccan Jews, nor any carrier of the 'Tunisian mutation' among 50 Tunisian Jews. Two 'Indian mutation' carriers were identified among 53 Indian Jews. All carriers within each ethnic group had the same haplotype, suggesting a common founder for each mutation.