Absence of an embryonic stem cell DNA methylation signature in human cancer.

BackgroundDifferentiated cells that arise from stem cells in early development contain DNA methylation features that provide a memory trace of their fetal cell origin (FCO). The FCO signature was developed to estimate the proportion of cells in a mixture of cell types that are of fetal origin and are reminiscent of embryonic stem cell lineage. Here we implemented the FCO signature estimation method to compare the fraction of cells with the FCO signature in tumor tissues and their corresponding nontumor normal tissues.MethodsWe applied our FCO algorithm to discovery data sets obtained from The Cancer Genome Atlas (TCGA) and replication data sets obtained from the Gene Expression Omnibus (GEO) data repository. Wilcoxon rank sum tests, linear regression models with adjustments for potential confounders and non-parametric randomization-based tests were used to test the association of FCO proportion between tumor tissues and nontumor normal tissues. P-values of < 0.05 were considered statistically significant.ResultsAcross 20 different tumor types we observed a consistently lower FCO signature in tumor tissues compared with nontumor normal tissues, with 18 observed to have significantly lower FCO fractions in tumor tissue (total n = 6,795 tumor, n = 922 nontumor, P < 0.05). We replicated our findings in 15 tumor types using data from independent subjects in 15 publicly available data sets (total n = 740 tumor, n = 424 nontumor, P < 0.05).ConclusionsThe results suggest that cancer development itself is substantially devoid of recapitulation of normal embryologic processes. Our results emphasize the distinction between DNA methylation in normal tightly regulated stem cell driven differentiation and cancer stem cell reprogramming that involves altered methylation in the service of great cell heterogeneity and plasticity

Technical note: Creating a four‐dimensional model of the liver using finite element analysis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134997/1/mp5055.pd

Genetic Analysis of Population Dynamics of the Southeastern Coyote (Canis latrans)

Coyotes (Canis latrans) have been extremely successful in dispersing and expanding their range that now includes all fifty states of the United States in addition to Canada and parts of Central America. These animals have generally been considered a pest species due to their adaptive ability, high reproductivity, and impact as a top predator on commercial agricultural business. Population dynamics of coyotes is still poorly understood, yet such knowledge would be beneficial to management of coyotes in all areas. The goal of this study is to determine population structure in Alabama by using microsatellite DNA markers. In addition we plan to examine patterns of gene flow across an urban to rural gradient. This research is extremely applicable in urban coyote management as we will be able to describe gene flow between and among population of coyotes. Information gained about population structure among coyotes in east-central Alabama could be informative about populations across the southeastern region. It is our expectation that such biological data will be consolidated with the vast knowledge of the ecology of the southeastern coyote gathered to date to inform and aid management plans and decisions across the region. Approaching both conservation and management issues with a more unbiased view of the ecology of coyote populations will allow greater effectiveness in management practices for this species

RDMA vs. RPC for implementing distributed data structures

Distributed data structures are key to implementing scalable applications for scientific simulations and data analysis. In this paper we look at two implementation styles for distributed data structures: remote direct memory access (RDMA) and remote procedure call (RPC). We focus on operations that require individual accesses to remote portions of a distributed data structure, e.g., accessing a hash table bucket or distributed queue, rather than global operations in which all processors collectively exchange information. We look at the trade-offs between the two styles through microbenchmarks and a performance model that approximates the cost of each. The RDMA operations have direct hardware support in the network and therefore lower latency and overhead, while the RPC operations are more expressive but higher cost and can suffer from lack of attentiveness from the remote side. We also run experiments to compare the real-world performance of RDMA- and RPC-based data structure operations with the predicted performance to evaluate the accuracy of our model, and show that while the model does not always precisely predict running time, it allows us to choose the best implementation in the examples shown. We believe this analysis will assist developers in designing data structures that will perform well on current network architectures, as well as network architects in providing better support for this class of distributed data structures

Entrustable Professional Activities (EPAs) for Global Health

Purpose As global health education and training shift toward competency-based approaches, academic institutions and organizations must define appropriate assessment strategies for use across health professions. The authors aim to develop entrustable professional activities (EPAs) for global health to apply across academic and workplace settings. Method In 2019, the authors invited 55 global health experts from medicine, nursing, pharmacy, and public health to participate in a multiround, online Delphi process; 30 (55%) agreed. Experts averaged 17 years of global health experience, and 12 (40%) were from low-to middle-income countries. In round one, participants listed essential global health activities. The authors used in vivo coding for round one responses to develop initial EPA statements. In subsequent rounds, participants used 5-point Likert-Type scales to evaluate EPA statements for importance and relevance to global health across health professions. The authors elevated statements that were rated 4 (important/relevant to most) or 5 (very important/relevant to all) by a minimum of 70% of participants (decided a priori) to the final round, during which participants evaluated whether each statement represented an observable unit of work that could be assigned to a trainee. Descriptive statistics were used for quantitative data analysis. The authors used participant comments to categorize EPA statements into role domains. Results Twenty-Two EPA statements reached at least 70% consensus. The authors categorized these into 5 role domains: partnership developer, capacity builder, data analyzer, equity advocate, and health promoter. Statements in the equity advocate and partnership developer domains had the highest agreement for importance and relevance. Several statements achieved 100% agreement as a unit of work but achieved lower levels of agreement regarding their observability. Conclusions EPAs for global health may be useful to academic institutions and other organizations to guide the assessment of trainees within education and training programs across health professions

European wildcat populations are subdivided into five main biogeographic groups: consequences of Pleistocene climate changes or recent anthropogenic fragmentation?

Extant populations of the European wildcat are fragmented across the continent, the likely consequence of recent extirpations due to habitat loss and over-hunting. However, their underlying phylogeographic history has never been reconstructed. For testing the hypothesis that the European wildcat survived the Ice Age fragmented in Mediterranean refuges, we assayed the genetic variation at 31 microsatellites in 668 presumptive European wildcats sampled in 15 European countries. Moreover, to evaluate the extent of subspecies/population divergence and identify eventual wild × domestic cat hybrids, we genotyped 26 African wildcats from Sardinia and North Africa and 294 random-bred domestic cats. Results of multivariate analyses and Bayesian clustering confirmed that the European wild and the domestic cats (plus the African wildcats) belong to two well-differentiated clusters (average Ф ST = 0.159, r st = 0.392, P > 0.001; Analysis of molecular variance [AMOVA]). We identified from c. 5% to 10% cryptic hybrids in southern and central European populations. In contrast, wild-living cats in Hungary and Scotland showed deep signatures of genetic admixture and introgression with domestic cats. The European wildcats are subdivided into five main genetic clusters (average Ф ST = 0.103, r st = 0.143, P > 0.001; AMOVA) corresponding to five biogeographic groups, respectively, distributed in the Iberian Peninsula, central Europe, central Germany, Italian Peninsula and the island of Sicily, and in north-eastern Italy and northern Balkan regions (Dinaric Alps). Approximate Bayesian Computation simulations supported late Pleistocene-early Holocene population splittings (from c. 60 k to 10 k years ago), contemporary to the last Ice Age climatic changes. These results provide evidences for wildcat Mediterranean refuges in southwestern Europe, but the evolution history of eastern wildcat populations remains to be clarified. Historical genetic subdivisions suggest conservation strategies aimed at enhancing gene flow through the restoration of ecological corridors within each biogeographic units. Concomitantly, the risk of hybridization with free-ranging domestic cats along corridor edges should be carefully monitored

Automated generation of a four‐dimensional model of the liver using warping and mutual information

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134809/1/mp6781.pd

Catastrophic Phase Transitions and Early Warnings in a Spatial Ecological Model

Gradual changes in exploitation, nutrient loading, etc. produce shifts between alternative stable states (ASS) in ecosystems which, quite often, are not smooth but abrupt or catastrophic. Early warnings of such catastrophic regime shifts are fundamental for designing management protocols for ecosystems. Here we study the spatial version of a popular ecological model, involving a logistically growing single species subject to exploitation, which is known to exhibit ASS. Spatial heterogeneity is introduced by a carrying capacity parameter varying from cell to cell in a regular lattice. Transport of biomass among cells is included in the form of diffusion. We investigate whether different quantities from statistical mechanics -like the variance, the two-point correlation function and the patchiness- may serve as early warnings of catastrophic phase transitions between the ASS. In particular, we find that the patch-size distribution follows a power law when the system is close to the catastrophic transition. We also provide links between spatial and temporal indicators and analyze how the interplay between diffusion and spatial heterogeneity may affect the earliness of each of the observables. We find that possible remedial procedures, which can be followed after these early signals, are more effective as the diffusion becomes lower. Finally, we comment on similarities and differences between these catastrophic shifts and paradigmatic thermodynamic phase transitions like the liquid-vapour change of state for a fluid like water