Sporulation, bacterial cell envelopes, and the origin of life

Electron cryotomography (ECT) enables the 3D reconstruction of intact cells in a near-native state. Images produced by ECT have led to the proposal that an ancient sporulation-like event gave rise to the second membrane in diderm bacteria. Tomograms of sporulating monoderm and diderm bacterial cells show how sporulation can lead to the generation of diderm cells. Tomograms of Gram-negative and Gram-positive cell walls and purified sacculi suggest that they are more closely related than previously thought and support the hypothesis that they share a common origin. Mapping the distribution of cell envelope architectures onto a recent phylogenetic tree of life indicates that the diderm cell plan, and therefore the sporulation-like event that gave rise to it, must be very ancient. One explanation for this model is that during the cataclysmic transitions of the early Earth, cellular evolution may have gone through a bottleneck in which only spores survived, which implies that the last bacterial common ancestor was a spore

Low rates of mutation in clinical grade human pluripotent stem cells under different culture conditions

Abstract: The occurrence of repetitive genomic changes that provide a selective growth advantage in pluripotent stem cells is of concern for their clinical application. However, the effect of different culture conditions on the underlying mutation rate is unknown. Here we show that the mutation rate in two human embryonic stem cell lines derived and banked for clinical application is low and not substantially affected by culture with Rho Kinase inhibitor, commonly used in their routine maintenance. However, the mutation rate is reduced by >50% in cells cultured under 5% oxygen, when we also found alterations in imprint methylation and reversible DNA hypomethylation. Mutations are evenly distributed across the chromosomes, except for a slight increase on the X-chromosome, and an elevation in intergenic regions suggesting that chromatin structure may affect mutation rate. Overall the results suggest that pluripotent stem cells are not subject to unusually high rates of genetic or epigenetic alterations

Complex networks for terrorist target prediction

Developments in statistics and computer science have influenced research on many social problems. This process also applies to the study of terrorism. In this context, network analysis is one of the most popular mathematical methods for analyzing terrorist organizations and dynamics. Nonetheless, few studies have applied network science to the analysis of terrorist events. Therefore, in this work we first introduce a novel method to analyze the heterogeneous dynamics of terrorist attacks through the creation of a dynamic meta-network of terror for the period 1997\u20132016. Second, we use our terrorist meta-network to test the power of Network-based Inference algorithm in predicting terrorist targets. Results are promising and show how this algorithm reaches high levels of precision, accuracy, and recall and indicate that network outcomes can be used in broader machine learning models

Maternal Peripartum Serum DDT/E and Urinary Pyrethroid Metabolite Concentrations and Child Infections at 2 Years in the VHEMBE Birth Cohort

BACKGROUND : Indoor residual spraying (IRS) of insecticides, conducted in low- and middle-income countries to control malaria, may result in high exposure to dichlorodiphenyltrichloroethane (DDT), its breakdown product dichlorodiphenyldichloroethylene (DDE), or pyrethroids. Animal studies suggest in utero exposure to these chemicals may increase childhood infection frequency. OBJECTIVES : We investigated associations between maternal DDT/E and pyrethroid metabolite concentration and child infection associations in an IRS setting in which susceptibility factors are common and infections are leading causes of child morbidity and mortality. METHODS : Using gas chromatography–mass spectrometry, we measured serum DDT/E and urinary pyrethroid metabolite concentrations in peripartum samples from 674 women participating in the Venda Health Examination of Mother, Babies and their Environment (VHEMBE) study. Counts of persistent child fevers, otitis media, and severe sore throat between 1 and 2 y of age were ascertained from maternal interviews. Associations between DDT/E and pyrethroid metabolite concentrations and infections were estimated using zero-inflated Poisson regression. We estimated relative excess risks due to interaction (RERI) with poverty, maternal energy intake, and maternal HIV status. RESULTS : Concentrations of DDT/E, particularly p,p′-DDE, were associated with higher rates of persistent fevers [IRR=1.21 (95% CI: 1.01, 1.46)], for a 10-fold increase in p,p′-DDE). This association was stronger among children from households below versus above the South African food poverty line [IRR=1.31 (95% CI: 1.08, 1.59) vs. IRR=0.93 (95% CI: 0.69, 1.25), respectively] and for children whose mothers had insufficient versus sufficient caloric intake during pregnancy [IRR=1.30 (95% CI: 1.07, 1.58) vs. IRR=0.96 (95% CI: 0.72, 1.28), respectively]. CONCLUSIONS : In utero IRS insecticide exposure may increase childhood infection rates. This was particularly apparent among children from poorer households or whose mothers had low energy intake during pregnancy.The National Institutes of Environmental Health Sciences (1R01ES020360-01)http://ehp.niehs.nih.govam2019School of Health Systems and Public Health (SHSPH

Detecting latent terrorist communities testing a gower\u2019s similarity-based clustering algorithm for multi-partite networks

Finding hidden patterns represents a key task in terrorism research. In light of this, the present work seeks to test an innovative clustering algorithm designed for multi-partite networks to find communities of terrorist groups active worldwide from 1997 to 2016. This algorithm uses Gower\u2019s coefficient of similarity as the similarity measure to cluster perpetrators. Data include information on weapons, tactics, targets, and active regions. We show how different dimensional weighting schemes lead to different types of grouping, and we therefore concentrate on the outcomes of the unweighted algorithm to highlight interesting patterns naturally emerging from the data. We highlight that groups belonging to different ideologies actually share very common behaviors. Finally, future work directions are discussed

A Network-Based Analysis of International Refugee Migration Patterns Using GERGMs

Understanding determinants of migration is central to anticipating and mitigating the adverse effects of large-scale human displacement. Traditional migration models quantify the influence of different factors on migration but fail to consider the interdependent nature of human displacement. In contrast, network models inherently take into account interdependencies in data, making them ideal for modeling relational phenomena such as migration. In this study, we apply one such model, a Generalized Exponential Random Graph Model (GERGM), to two different weighted-edge networks of international refugee migration from 2015, centered around Syria and the Democratic Republic of Congo (DRC), respectively. The GERGM quantifies the influence of various factors on out-migration and in-migration within the networks, allowing us to determine which push and pull factors are largely at play. Our results indicate that both push factors and pull factors drive migration within the DRC network, while migration within the Syria network is predominately driven by push factors. We suspect the reason for this difference may lie in that the conflict in Syria is relatively recent, in contrast to the conflict in the DRC, which has been ongoing for almost two decades, allowing for the establishment of systematic migration channels, migration networks, and resettlement, all which are related to pull factors, throughout the years