Complex networks generated by the Penna bit-string model: emergence of small-world and assortative mixing

The Penna bit-string model successfully encompasses many phenomena of population evolution, including inheritance, mutation, evolution, and aging. If we consider social interactions among individuals in the Penna model, the population will form a complex network. In this paper, we first modify the Verhulst factor to control only the birth rate, and introduce activity-based preferential reproduction of offspring in the Penna model. The social interactions among individuals are generated by both inheritance and activity-based preferential increase. Then we study the properties of the complex network generated by the modified Penna model. We find that the resulting complex network has a small-world effect and the assortative mixing property

Opportunities for quality improvement in cystic fibrosis newborn screening

AbstractBackgroundWith the rapid implementation of cystic fibrosis (CF) newborn screening (NBS), quality improvement (QI) has become essential to identify and prevent errors. Using Process Failure Modes and Effects Analysis (PFMEA), we adapted this method to determine if it could be applied to discover and rank high priority QI opportunities.MethodsSite visits to three programmes were conducted, and PFMEA exercises were accomplished in Colorado, Massachusetts and Wisconsin with 23 experienced professionals. During each of these comprehensive sessions, participants identified and ranked potential failures based on severity, occurrence and detection to calculate risk priority number (RPN) values.ResultsA total of 96 failure modes were generated and ranked in a list of the 20 riskiest problems that show no significant discordances by site, although there were differences by profession of the rater, particularly nurses.ConclusionsOur results illustrate that the PFMEA method applies well to CF NBS and that steps requiring communication and information transfer are perceived to be the highest risks. The number of identified failures makes and their potential impact demonstrate considerable overall risk and a need for ongoing QI

Lesinurad, a novel, oral compound for gout, acts to decrease serum uric acid through inhibition of urate transporters in the kidney.

BackgroundExcess body burden of uric acid promotes gout. Diminished renal clearance of uric acid causes hyperuricemia in most patients with gout, and the renal urate transporter (URAT)1 is important for regulation of serum uric acid (sUA) levels. The URAT1 inhibitors probenecid and benzbromarone are used as gout therapies; however, their use is limited by drug-drug interactions and off-target toxicity, respectively. Here, we define the mechanism of action of lesinurad (Zurampic®; RDEA594), a novel URAT1 inhibitor, recently approved in the USA and Europe for treatment of chronic gout.MethodssUA levels, fractional excretion of uric acid (FEUA), lesinurad plasma levels, and urinary excretion of lesinurad were measured in healthy volunteers treated with lesinurad. In addition, lesinurad, probenecid, and benzbromarone were compared in vitro for effects on urate transporters and the organic anion transporters (OAT)1 and OAT3, changes in mitochondrial membrane potential, and human peroxisome proliferator-activated receptor gamma (PPARγ) activity.ResultsAfter 6 hours, a single 200-mg dose of lesinurad elevated FEUA 3.6-fold (p < 0.001) and reduced sUA levels by 33 % (p < 0.001). At concentrations achieved in the clinic, lesinurad inhibited activity of URAT1 and OAT4 in vitro, did not inhibit GLUT9, and had no effect on ABCG2. Lesinurad also showed a low risk for mitochondrial toxicity and PPARγ induction compared to benzbromarone. Unlike probenecid, lesinurad did not inhibit OAT1 or OAT3 in the clinical setting.ConclusionThe pharmacodynamic effects and in vitro activity of lesinurad are consistent with inhibition of URAT1 and OAT4, major apical transporters for uric acid. Lesinurad also has a favorable selectivity and safety profile, consistent with an important role in sUA-lowering therapy for patients with gout

An evolving network model with community structure

Many social and biological networks consist of communities—groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties

Phospholipase Dζ Enhances Diacylglycerol Flux Into Triacylglycerol

Plant seeds are the primary source of triacylglycerols (TAG) for food, feed, fuel, and industrial applications. As TAG is produced from diacylglycerol (DAG), successful engineering strategies to enhance TAG levels have focused on the conversion of DAG to TAG. However, the production of TAG can be limited by flux through the enzymatic reactions that supply DAG. In this study, two Arabidopsis phospholipase Dζ genes (AtPLDζ1 and AtPLDζ2) were coexpressed in Camelina sativa to test whether the conversion of phosphatidylcholine to DAG impacts TAG levels in seeds. The resulting transgenic plants produced 2% to 3% more TAG as a component of total seed biomass and had increased 18:3 and 20:1 fatty acid levels relative to wild type. Increased DAG and decreased PC levels were examined through the kinetics of lipid assembly by [14C]acetate and [14C]glycerol incorporation into glycerolipids. [14C]acetate was rapidly incorporated into TAG in both wild-type and overexpression lines, indicating a significant flux of nascent and elongated acyl-CoAs into the sn-3 position of TAG. Stereochemical analysis revealed that newly synthesized fatty acids were preferentially incorporated into the sn-2 position of PC, but the sn-1 position of de novo DAG and indicated similar rates of nascent acyl groups into the Kennedy pathway and acyl editing. [14C]glycerol studies demonstrated PC-derived DAG is the major source of DAG for TAG synthesis in both tissues. The results emphasize that the interconversions of DAG and PC pools can impact oil production and composition

Variational data assimilation for the initial-value dynamo problem

The secular variation of the geomagnetic field as observed at the Earth's surface results from the complex magnetohydrodynamics taking place in the fluid core of the Earth. One way to analyze this system is to use the data in concert with an underlying dynamical model of the system through the technique of variational data assimilation, in much the same way as is employed in meteorology and oceanography. The aim is to discover an optimal initial condition that leads to a trajectory of the system in agreement with observations. Taking the Earth's core to be an electrically conducting fluid sphere in which convection takes place, we develop the continuous adjoint forms of the magnetohydrodynamic equations that govern the dynamical system together with the corresponding numerical algorithms appropriate for a fully spectral method. These adjoint equations enable a computationally fast iterative improvement of the initial condition that determines the system evolution. The initial condition depends on the three dimensional form of quantities such as the magnetic field in the entire sphere. For the magnetic field, conservation of the divergence-free condition for the adjoint magnetic field requires the introduction of an adjoint pressure term satisfying a zero boundary condition. We thus find that solving the forward and adjoint dynamo system requires different numerical algorithms. In this paper, an efficient algorithm for numerically solving this problem is developed and tested for two illustrative problems in a whole sphere: one is a kinematic problem with prescribed velocity field, and the second is associated with the Hall-effect dynamo, exhibiting considerable nonlinearity. The algorithm exhibits reliable numerical accuracy and stability. Using both the analytical and the numerical techniques of this paper, the adjoint dynamo system can be solved directly with the same order of computational complexity as that required to solve the forward problem. These numerical techniques form a foundation for ultimate application to observations of the geomagnetic field over the time scale of centuries