Speciational view of macroevolution: are micro and macroevolution decoupled?

We introduce a simple computational model that, with a microscopic dynamics driven by natural selection and mutation alone, allows the description of true speciation events. A statistical analysis of the so generated evolutionary tree captures realistic features showing power laws for frequency distributions in time and size. Albeit these successful predictions, the difficulty in obtaining punctuated dynamics with mass extinctions suggests the necessity of decoupling micro and macro-evolutionary mechanisms in agreement with some ideas of Gould's and Eldredge's theory of punctuated equilibrium.Comment: Europhys. Lett. 75:342--34

The phase diagram of random threshold networks

Threshold networks are used as models for neural or gene regulatory networks. They show a rich dynamical behaviour with a transition between a frozen and a chaotic phase. We investigate the phase diagram of randomly connected threshold networks with real-valued thresholds h and a fixed number of inputs per node. The nodes are updated according to the same rules as in a model of the cell-cycle network of Saccharomyces cereviseae [PNAS 101, 4781 (2004)]. Using the annealed approximation, we derive expressions for the time evolution of the proportion of nodes in the "on" and "off" state, and for the sensitivity $\lambda$. The results are compared with simulations of quenched networks. We find that for integer values of h the simulations show marked deviations from the annealed approximation even for large networks. This can be attributed to the particular choice of the updating rule.Comment: 8 pages, 6 figure

Tangled Nature: A model of emergent structure and temporal mode among co-evolving agents

Understanding systems level behaviour of many interacting agents is challenging in various ways, here we'll focus on the how the interaction between components can lead to hierarchical structures with different types of dynamics, or causations, at different levels. We use the Tangled Nature model to discuss the co-evolutionary aspects connecting the microscopic level of the individual to the macroscopic systems level. At the microscopic level the individual agent may undergo evolutionary changes due to mutations of strategies. The micro-dynamics always run at a constant rate. Nevertheless, the system's level dynamics exhibit a completely different type of intermittent abrupt dynamics where major upheavals keep throwing the system between meta-stable configurations. These dramatic transitions are described by a log-Poisson time statistics. The long time effect is a collectively adapted of the ecological network. We discuss the ecological and macroevolutionary consequences of the adaptive dynamics and briefly describe work using the Tangled Nature framework to analyse problems in economics, sociology, innovation and sustainabilityComment: Invited contribution to Focus on Complexity in European Journal of Physics. 25 page, 1 figur

Genome-wide association study of problematic opioid prescription use in 132,113 23andMe research participants of European ancestry

The growing prevalence of opioid use disorder (OUD) constitutes an urgent health crisis. Ample evidence indicates that risk for OUD is heritable. As a surrogate (or proxy) for OUD, we explored the genetic basis of using prescription opioids \u27not as prescribed\u27. We hypothesized that misuse of opiates might be a heritable risk factor for OUD. To test this hypothesis, we performed a genome-wide association study (GWAS) of problematic opioid use (POU) in 23andMe research participants of European ancestry (N = 132,113; 21% cases). We identified two genome-wide significant loci (rs3791033, an intronic variant of KDM4A; rs640561, an intergenic variant near LRRIQ3). POU showed positive genetic correlations with the two largest available GWAS of OUD and opioid dependence (

Self-optimization, community stability, and fluctuations in two individual-based models of biological coevolution

We compare and contrast the long-time dynamical properties of two individual-based models of biological coevolution. Selection occurs via multispecies, stochastic population dynamics with reproduction probabilities that depend nonlinearly on the population densities of all species resident in the community. New species are introduced through mutation. Both models are amenable to exact linear stability analysis, and we compare the analytic results with large-scale kinetic Monte Carlo simulations, obtaining the population size as a function of an average interspecies interaction strength. Over time, the models self-optimize through mutation and selection to approximately maximize a community fitness function, subject only to constraints internal to the particular model. If the interspecies interactions are randomly distributed on an interval including positive values, the system evolves toward self-sustaining, mutualistic communities. In contrast, for the predator-prey case the matrix of interactions is antisymmetric, and a nonzero population size must be sustained by an external resource. Time series of the diversity and population size for both models show approximate 1/f noise and power-law distributions for the lifetimes of communities and species. For the mutualistic model, these two lifetime distributions have the same exponent, while their exponents are different for the predator-prey model. The difference is probably due to greater resilience toward mass extinctions in the food-web like communities produced by the predator-prey model.Comment: 26 pages, 12 figures. Discussion of early-time dynamics added. J. Math. Biol., in pres

Characteristics of Antiphospholipid Antibody Positive Patients in AntiPhospholipid Syndrome Alliance for Clinical Trials and InternatiOnal Networking

OBJECTIVE: To describe baseline characteristics of antiphospholipid antibody (aPL)-positive patients, overall and by clinical and laboratory subtypes, enrolled in an international registry. METHODS: AntiPhospholipid Syndrome Alliance for Clinical Trials and InternatiOnal Networking Registry includes persistently aPL-positive adults. We evaluated baseline sociodemographic and aPL-related (APS classification criteria and "non-criteria") characteristics of patients overall and in subgroups (aPL-positive without APS, APS overall, thrombotic APS [TAPS] only, obstetric APS [OAPS] only, and both TAPS/OAPS). We assessed baseline characteristics of patients tested for three aPL (lupus anticoagulant test [LA], anticardiolipin antibody [aCL], and anti-β2 -Glycoprotein-I [aβ2 GPI]) by aPL profiles (LA only, single, double, and triple aPL positivity). RESULTS: Of 804 aPL-positive patients (mean age: 45 ± 13y; female: 74%; white 68%; other systemic autoimmune diseases: 36%), 80% were classified as APS (55% TAPS, 9% OAPS, and 15% TAPS/OAPS). In the overall cohort, 71% had vascular thrombosis, 50% with pregnancy history had obstetric morbidity, and 56% had at least one non-criteria manifestation. Among those with three aPL tested (n: 660), 42% were triple aPL positive. While single, double and triple aPL positive subgroups had similar frequencies of vascular, obstetric, and non-criteria events, these events were lowest in the single aPL subgroup consisting of aCL or aβ2 GPI only. CONCLUSION: Our study demonstrates the heterogeneity of aPL-related clinical manifestations and laboratory profiles in a multicenter, international cohort. Within single aPL-positivity, LA may be a major contributor to clinical events. Future prospective analyses, using standardized core laboratory aPL tests, will help clarify aPL risk profiles and improve risk stratification

Human vascular adhesion proteın-1 (VAP-1): Serum levels for hepatocellular carcinoma in non-alcoholic and alcoholic fatty liver disease

<p>Abstract</p> <p>Background</p> <p>The incidence of hepatocellular cancer in complicated alcoholic and non-alcoholic fatty liver diseases is on the rise in western countries as well in our country. Vascular adhesion protein-1 (VAP-1) levels have been presented as new marker. In our study protocol, we assessed the value of this serum protein, as a newly postulant biomarker for hepatocellular cancer in patients with a history of alcoholic and non-alcoholic fatty liver diseases.</p> <p>Methods</p> <p>Pre-operative serum samples from 55 patients with hepatocellular cancer with a history of alcoholic and non-alcoholic fatty liver diseases and patients with cirrhosis were assessed by a quantitative sandwich ELISA using anti-VAP-1 mAbs. This technique is used to determine the levels of soluble VAP-1 (sVAP-1) in the serum.</p> <p>Results</p> <p>sVAP-1 levels were evaluated in patients with hepatocellular cancer and liver cirrhosis. There was a significant difference in mean VAP-1 levels between groups. Serum VAP-1 levels were found higher in patients with hepatocellular cancer.</p> <p>Conclusion</p> <p>These findings indicate that the serum level of sVAP-1 might be a beneficial marker of disease activity in chronic liver diseases.</p

Reliability of Transcriptional Cycles and the Yeast Cell-Cycle Oscillator

A recently published transcriptional oscillator associated with the yeast cell cycle provides clues and raises questions about the mechanisms underlying autonomous cyclic processes in cells. Unlike other biological and synthetic oscillatory networks in the literature, this one does not seem to rely on a constitutive signal or positive auto-regulation, but rather to operate through stable transmission of a pulse on a slow positive feedback loop that determines its period. We construct a continuous-time Boolean model of this network, which permits the modeling of noise through small fluctuations in the timing of events, and show that it can sustain stable oscillations. Analysis of simpler network models shows how a few building blocks can be arranged to provide stability against fluctuations. Our findings suggest that the transcriptional oscillator in yeast belongs to a new class of biological oscillators

Stochastic Delay Accelerates Signaling in Gene Networks

The creation of protein from DNA is a dynamic process consisting of numerous reactions, such as transcription, translation and protein folding. Each of these reactions is further comprised of hundreds or thousands of sub-steps that must be completed before a protein is fully mature. Consequently, the time it takes to create a single protein depends on the number of steps in the reaction chain and the nature of each step. One way to account for these reactions in models of gene regulatory networks is to incorporate dynamical delay. However, the stochastic nature of the reactions necessary to produce protein leads to a waiting time that is randomly distributed. Here, we use queueing theory to examine the effects of such distributed delay on the propagation of information through transcriptionally regulated genetic networks. In an analytically tractable model we find that increasing the randomness in protein production delay can increase signaling speed in transcriptional networks. The effect is confirmed in stochastic simulations, and we demonstrate its impact in several common transcriptional motifs. In particular, we show that in feedforward loops signaling time and magnitude are significantly affected by distributed delay. In addition, delay has previously been shown to cause stable oscillations in circuits with negative feedback. We show that the period and the amplitude of the oscillations monotonically decrease as the variability of the delay time increases