Large phenotype jumps in biomolecular evolution

By defining the phenotype of a biopolymer by its active three-dimensional shape, and its genotype by its primary sequence, we propose a model that predicts and characterizes the statistical distribution of a population of biopolymers with a specific phenotype, that originated from a given genotypic sequence by a single mutational event. Depending on the ratio g0 that characterizes the spread of potential energies of the mutated population with respect to temperature, three different statistical regimes have been identified. We suggest that biopolymers found in nature are in a critical regime with g0 in the range 1-6, corresponding to a broad, but not too broad, phenotypic distribution resembling a truncated Levy flight. Thus the biopolymer phenotype can be considerably modified in just a few mutations. The proposed model is in good agreement with the experimental distribution of activities determined for a population of single mutants of a group I ribozyme.Comment: to appear in Phys. Rev. E; 7 pages, 6 figures; longer discussion in VII, new fig.

The interrelatedness of cognitive abilities in very preterm and full‐term born children at 5.5 years of age : a psychometric network analysis approach

Background Very preterm (VP) birth is associated with a considerable risk for cognitive impairment, putting children at a disadvantage in academic and everyday life. Despite lower cognitive ability on the group level, there are large individual differences among VP born children. Contemporary theories define intelligence as a network of reciprocally connected cognitive abilities. Therefore, intelligence was studied as a network of interrelated abilities to provide insight into interindividual differences. We described and compared the network of cognitive abilities, including strength of interrelations between and the relative importance of abilities, of VP and full-term (FT) born children and VP children with below-average and average-high intelligence at 5.5 years. Methods A total of 2,253 VP children from the EPIPAGE-2 cohort and 578 FT controls who participated in the 5.5-year-follow-up were eligible for inclusion. The WPPSI-IV was used to measure verbal comprehension, visuospatial abilities, fluid reasoning, working memory, and processing speed. Psychometric network analysis was applied to analyse the data. Results Cognitive abilities were densely and positively interconnected in all networks, but the strength of connections differed between networks. The cognitive network of VP children was more strongly interconnected than that of FT children. Furthermore, VP children with below average IQ had a more strongly connected network than VP children with average-high IQ. Contrary to our expectations, working memory had the least central role in all networks. Conclusions In line with the ability differentiation hypothesis, children with higher levels of cognitive ability had a less interconnected and more specialised cognitive structure. Composite intelligence scores may therefore mask domain-specific deficits, particularly in children at risk for cognitive impairments (e.g., VP born children), even when general intelligence is unimpaired. In children with strongly and densely connected networks, domain-specific deficits may have a larger overall impact, resulting in lower intelligence levels

Coordinated Movements Prevent Jamming in an Emperor Penguin Huddle

For Emperor penguins (Aptenodytes forsteri), huddling is the key to survival during the Antarctic winter. Penguins in a huddle are packed so tightly that individual movements become impossible, reminiscent of a jamming transition in compacted colloids. It is crucial, however, that the huddle structure is continuously reorganized to give each penguin a chance to spend sufficient time inside the huddle, compared with time spent on the periphery. Here we show that Emperor penguins move collectively in a highly coordinated manner to ensure mobility while at the same time keeping the huddle packed. Every 30–60 seconds, all penguins make small steps that travel as a wave through the entire huddle. Over time, these small movements lead to large-scale reorganization of the huddle. Our data show that the dynamics of penguin huddling is governed by intermittency and approach to kinetic arrest in striking analogy with inert non-equilibrium systems, including soft glasses and colloids

Evolving Clustered Random Networks

We propose a Markov chain simulation method to generate simple connected random graphs with a specified degree sequence and level of clustering. The networks generated by our algorithm are random in all other respects and can thus serve as generic models for studying the impacts of degree distributions and clustering on dynamical processes as well as null models for detecting other structural properties in empirical networks

Spatial Guilds in the Serengeti Food Web Revealed by a Bayesian Group Model

Food webs, networks of feeding relationships among organisms, provide fundamental insights into mechanisms that determine ecosystem stability and persistence. Despite long-standing interest in the compartmental structure of food webs, past network analyses of food webs have been constrained by a standard definition of compartments, or modules, that requires many links within compartments and few links between them. Empirical analyses have been further limited by low-resolution data for primary producers. In this paper, we present a Bayesian computational method for identifying group structure in food webs using a flexible definition of a group that can describe both functional roles and standard compartments. The Serengeti ecosystem provides an opportunity to examine structure in a newly compiled food web that includes species-level resolution among plants, allowing us to address whether groups in the food web correspond to tightly-connected compartments or functional groups, and whether network structure reflects spatial or trophic organization, or a combination of the two. We have compiled the major mammalian and plant components of the Serengeti food web from published literature, and we infer its group structure using our method. We find that network structure corresponds to spatially distinct plant groups coupled at higher trophic levels by groups of herbivores, which are in turn coupled by carnivore groups. Thus the group structure of the Serengeti web represents a mixture of trophic guild structure and spatial patterns, in contrast to the standard compartments typically identified in ecological networks. From data consisting only of nodes and links, the group structure that emerges supports recent ideas on spatial coupling and energy channels in ecosystems that have been proposed as important for persistence.Comment: 28 pages, 6 figures (+ 3 supporting), 2 tables (+ 4 supporting

Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge

Background: Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Methods: Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results: Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion: Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts. © 2016 The Author(s)

The Fittest versus the Flattest: Experimental Confirmation of the Quasispecies Effect with Subviral Pathogens

The “survival of the fittest” is the paradigm of Darwinian evolution in which the best-adapted replicators are favored by natural selection. However, at high mutation rates, the fittest organisms are not necessarily the fastest replicators but rather are those that show the greatest robustness against deleterious mutational effects, even at the cost of a low replication rate. This scenario, dubbed the “survival of the flattest”, has so far only been shown to operate in digital organisms. We show that “survival of the flattest” can also occur in biological entities by analyzing the outcome of competition between two viroid species coinfecting the same plant. Under optimal growth conditions, a viroid species characterized by fast population growth and genetic homogeneity outcompeted a viroid species with slow population growth and a high degree of variation. In contrast, the slow-growth species was able to outcompete the fast species when the mutation rate was increased. These experimental results were supported by an in silico model of competing viroid quasispecies

Punctate White Matter Lesions Associated With Altered Brain Development And Adverse Motor Outcome In Preterm Infants.

Preterm infants who develop neurodevelopmental impairment do not always have recognized abnormalities on cerebral ultrasound, a modality routinely used to assess prognosis. In a high proportion of infants, MRI detects punctate white matter lesions that are not seen on ultrasonography. To determine the relation of punctate lesions to brain development and early neurodevelopmental outcome we used multimodal brain MRI to study a large cohort of preterm infants. Punctate lesions without other focal cerebral or cerebellar lesions were detected at term equivalent age in 123 (24.3%) (59 male) of the 506 infants, predominantly in the centrum semiovale and corona radiata. Infants with lesions had higher gestational age, birth weight, and less chronic lung disease. Punctate lesions showed a dose dependent relation to abnormalities in white matter microstructure, assessed with tract-based spatial statistics, and reduced thalamic volume (p < 0.0001), and predicted unfavourable motor outcome at a median (range) corrected age of 20.2 (18.4-26.3) months with sensitivity (95% confidence intervals) 71 (43-88) and specificity 72 (69-77). Punctate white matter lesions without associated cerebral lesions are common in preterm infants currently not regarded as at highest risk for cerebral injury, and are associated with widespread neuroanatomical abnormalities and adverse early neurodevelopmental outcome