Emergent scale-free networks

Many complex systems--from social and communication networks to biological networks and the Internet--are thought to exhibit scale-free structure. However, prevailing explanations rely on the constant addition of new nodes, an assumption that fails dramatically in some real-world settings. Here, we propose a model in which nodes are allowed to die, and their connections rearrange under a mixture of preferential and random attachment. With these simple dynamics, we show that networks self-organize towards scale-free structure, with a power-law exponent $\gamma = 1 + \frac{1}{p}$ that depends only on the proportion $p$ of preferential (rather than random) attachment. Applying our model to several real networks, we infer $p$ directly from data, and predict the relationship between network size and degree heterogeneity. Together, these results establish that realistic scale-free structure can emerge naturally in networks of constant size and density, with broad implications for the structure and function of complex systems.Comment: 24 pages, 5 figure

A Multi-Core Numerical Framework for Characterizing Flow in Oil Reservoirs

Presented at the SCS Spring Simulation Multi-Conference – SpringSim 2011, April 4-7, 2011 – Boston, USA Awarded Best Paper in the 19th High Performance Computing Symposium and Best Overall Paper at SpringSim 2011.This paper presents a numerical framework that enables scalable, parallel execution of engineering simulations on multi-core, shared memory architectures. Distribution of the simulations is done by selective hash-tabling of the model domain which spatially decomposes it into a number of orthogonal computational tasks. These tasks, the size of which is critical to optimal cache blocking and consequently performance, are then distributed for execution to multiple threads using the previously presented task management algorithm, H-Dispatch. Two numerical methods, smoothed particle hydrodynamics (SPH) and the lattice Boltzmann method (LBM), are discussed in the present work, although the framework is general enough to be used with any explicit time integration scheme. The implementation of both SPH and the LBM within the parallel framework is outlined, and the performance of each is presented in terms of speed-up and efficiency. On the 24-core server used in this research, near linear scalability was achieved for both numerical methods with utilization efficiencies up to 95%. To close, the framework is employed to simulate fluid flow in a porous rock specimen, which is of broad geophysical significance, particularly in enhanced oil recovery

Stroke penumbra defined by an MRI-based oxygen challenge technique: 2. Validation based on the consequences of reperfusion

Magnetic resonance imaging (MRI) with oxygen challenge (T2* OC) uses oxygen as a metabolic biotracer to define penumbral tissue based on CMRO2 and oxygen extraction fraction. Penumbra displays a greater T2* signal change during OC than surrounding tissue. Since timely restoration of cerebral blood flow (CBF) should salvage penumbra, T2* OC was tested by examining the consequences of reperfusion on T2* OC-defined penumbra. Transient ischemia (109±20 minutes) was induced in male Sprague-Dawley rats (n=8). Penumbra was identified on T2*-weighted MRI during OC. Ischemia and ischemic injury were identified on CBF and apparent diffusion coefficient maps, respectively. Reperfusion was induced and scans repeated. T2 for final infarct and T2* OC were run on day 7. T2* signal increase to OC was 3.4% in contralateral cortex and caudate nucleus and was unaffected by reperfusion. In OC-defined penumbra, T2* signal increased by 8.4%±4.1% during ischemia and returned to 3.25%±0.8% following reperfusion. Ischemic core T2* signal increase was 0.39%±0.47% during ischemia and 0.84%±1.8% on reperfusion. Penumbral CBF increased from 41.94±13 to 116.5±25 mL per 100 g per minute on reperfusion. On day 7, OC-defined penumbra gave a normal OC response and was located outside the infarct. T2* OC-defined penumbra recovered when CBF was restored, providing further validation of the utility of T2* OC for acute stroke management

Stroke penumbra defined by an MRI-based oxygen challenge technique: 1. validation using [14C]2-deoxyglucose autoradiography

Accurate identification of ischemic penumbra will improve stroke patient selection for reperfusion therapies and clinical trials. Current magnetic resonance imaging (MRI) techniques have limitations and lack validation. Oxygen challenge T2* MRI (T2* OC) uses oxygen as a biotracer to detect tissue metabolism, with penumbra displaying the greatest T2* signal change during OC. [14C]2-deoxyglucose (2-DG) autoradiography was combined with T2* OC to determine metabolic status of T2*-defined penumbra. Permanent middle cerebral artery occlusion was induced in anesthetized male Sprague-Dawley rats (n=6). Ischemic injury and perfusion deficit were determined by diffusion- and perfusion-weighted imaging, respectively. At 147±32 minutes after stroke, T2* signal change was measured during a 5-minute 100% OC, immediately followed by 125 μCi/kg 2-DG, intravenously. Magnetic resonance images were coregistered with the corresponding autoradiograms. Regions of interest were located within ischemic core, T2*-defined penumbra, equivalent contralateral structures, and a region of hyperglycolysis. A T2* signal increase of 9.22%±3.9% (mean±s.d.) was recorded in presumed penumbra, which displayed local cerebral glucose utilization values equivalent to contralateral cortex. T2* signal change was negligible in ischemic core, 3.2%±0.78% in contralateral regions, and 1.41%±0.62% in hyperglycolytic tissue, located outside OC-defined penumbra and within the diffusion abnormality. The results support the utility of OC-MRI to detect viable penumbral tissue follow

Potential use of oxygen as a metabolic biosensor in combination with T2*-weighted MRI to define the ischemic penumbra

We describe a novel magnetic resonance imaging technique for detecting metabolism indirectly through changes in oxyhemoglobin:deoxyhemoglobin ratios and T2* signal change during ‘oxygen challenge’ (OC, 5 mins 100% O2). During OC, T2* increase reflects O2 binding to deoxyhemoglobin, which is formed when metabolizing tissues take up oxygen. Here OC has been applied to identify tissue metabolism within the ischemic brain. Permanent middle cerebral artery occlusion was induced in rats. In series 1 scanning (n=5), diffusion-weighted imaging (DWI) was performed, followed by echo-planar T2* acquired during OC and perfusion-weighted imaging (PWI, arterial spin labeling). Oxygen challenge induced a T2* signal increase of 1.8%, 3.7%, and 0.24% in the contralateral cortex, ipsilateral cortex within the PWI/DWI mismatch zone, and ischemic core, respectively. T2* and apparent diffusion coefficient (ADC) map coregistration revealed that the T2* signal increase extended into the ADC lesion (3.4%). In series 2 (n=5), FLASH T2* and ADC maps coregistered with histology revealed a T2* signal increase of 4.9% in the histologically defined border zone (55% normal neuronal morphology, located within the ADC lesion boundary) compared with a 0.7% increase in the cortical ischemic core (92% neuronal ischemic cell change, core ADC lesion). Oxygen challenge has potential clinical utility and, by distinguishing metabolically active and inactive tissues within hypoperfused regions, could provide a more precise assessment of penumbra

Evaluation of optical flow algorithms for tracking endocardial surfaces on three-dimensional ultrasound data

With relatively high frame rates and the ability to acquire volume data sets with a stationary transducer, 3D ultrasound systems, based on matrix phased array transducers, provide valuable three-dimensional information, from which quantitative measures of cardiac function can be extracted. Such analyses require segmentation and visual tracking of the left ventricular endocardial border. Due to the large size of the volumetric data sets, manual tracing of the endocardial border is tedious and impractical for clinical applications. Therefore the development of automatic methods for tracking three-dimensional endocardial motion is essential. In this study, we evaluate a four-dimensional optical flow motion tracking algorithm to determine its capability to follow the endocardial border in three dimensional ultrasound data through time. The four-dimensional optical flow method was implemented using three-dimensional correlation. We tested the algorithm on an experimental open-chest dog data set and a clinical data set acquired with a Philips' iE33 three-dimensional ultrasound machine. Initialized with left ventricular endocardial data points obtained from manual tracing at end-diastole, the algorithm automatically tracked these points frame by frame through the whole cardiac cycle.A finite element surface was fitted through the data points obtained by both optical flow tracking and manual tracing by an experienced observer for quantitative comparison of the results. Parameterization of the finite element surfaces was performed and maps displaying relative differences between the manual and semi-automatic methods were compared.The results showed good consistency between manual tracing and optical flow estimation on 73% of the entire surface with fewer than 10% difference. In addition, the optical flow motion tracking algorithm greatly reduced processing time (about 94% reduction compared to human involvement per cardiac cycle) for analyzing cardiac function in three-dimensional ultrasound data sets

HIV-1 Protease, Reverse Transcriptase, and Integrase Variation

ABSTRACT HIV-1 protease (PR), reverse transcriptase (RT), and integrase (IN) variability presents a challenge to laboratories performing genotypic resistance testing. This challenge will grow with increased sequencing of samples enriched for proviral DNA such as dried blood spots and increased use of next-generation sequencing (NGS) to detect low-abundance HIV-1 variants. We analyzed PR and RT sequences from >100,000 individuals and IN sequences from >10,000 individuals to characterize variation at each amino acid position, identify mutations indicating APOBEC-mediated G-to-A editing, and identify mutations resulting from selective drug pressure. Forty-seven percent of PR, 37% of RT, and 34% of IN positions had one or more amino acid variants with a prevalence of ≥1%. Seventy percent of PR, 60% of RT, and 60% of IN positions had one or more variants with a prevalence of ≥0.1%. Overall 201 PR, 636 RT, and 346 IN variants had a prevalence of ≥0.1%. The median intersubtype prevalence ratios were 2.9-, 2.1-, and 1.9-fold for these PR, RT, and IN variants, respectively. Only 5.0% of PR, 3.7% of RT, and 2.0% of IN variants had a median intersubtype prevalence ratio of ≥10-fold. Variants at lower prevalences were more likely to differ biochemically and to be part of an electrophoretic mixture compared to high-prevalence variants. There were 209 mutations indicative of APOBEC-mediated G-to-A editing and 326 mutations nonpolymorphic treatment selected. Identification of viruses with a high number of APOBEC-associated mutations will facilitate the quality control of dried blood spot sequencing. Identifying sequences with a high proportion of rare mutations will facilitate the quality control of NGS. IMPORTANCE Most antiretroviral drugs target three HIV-1 proteins: PR, RT, and IN. These proteins are highly variable: many different amino acids can be present at the same position in viruses from different individuals. Some of the amino acid variants cause drug resistance and occur mainly in individuals receiving antiretroviral drugs. Some variants result from a human cellular defense mechanism called APOBEC-mediated hypermutation. Many variants result from naturally occurring mutation. Some variants may represent technical artifacts. We studied PR and RT sequences from >100,000 individuals and IN sequences from >10,000 individuals to quantify variation at each amino acid position in these three HIV-1 proteins. We performed analyses to determine which amino acid variants resulted from antiretroviral drug selection pressure, APOBEC-mediated editing, and naturally occurring variation. Our results provide information essential to clinical, research, and public health laboratories performing genotypic resistance testing by sequencing HIV-1 PR, RT, and IN

Predominance of enterovirus B and echovirus 30 as cause of viral meningitis in a UK population.

BACKGROUND/OBJECTIVES: Enteroviruses are the most common cause of aseptic or lymphocytic meningitis, particularly in children. With reports of unusually severe neurological disease in some patients infected with enterovirus D68 in North America, and a recent increase in the number of paediatric enterovirus meningitis cases presenting in this UK Midlands population, a retrospective regional surveillance study was performed. STUDY DESIGN: Cerebrospinal fluid (CSF) samples received were tested using the polymerase chain reaction (PCR) for HSV-1/2, VZV, enteroviruses and parechoviruses. Enterovirus PCR positive CSF samples were sent for further serotyping. A phylogenetic tree was constructed of the echovirus 30 VP1 sequences, where sufficient sample remained for sequencing. RESULTS: The number of enterovirus positive CSFs from each year were: 21 (2008), 7 (2011), 53 (2012), 58 (2013) and 31 (2014). Overall, 163 of the 170 serotyped enteroviruses belonged to the species B (echovirus 5, 6, 7, 9, 11, 13, 16, 17, 18, 21, 25, 30; coxsackie B1, B2, B3, B4, B5, A9), with only 7 belonging to species A (coxsackie A2, A6, A16 and enterovirus 71). Echovirus 30 was the predominant serotype overall, identified in 43 (25.3%) of samples, with a significantly higher proportion in the adult age group (37.3%) compared to the infant age group (12.3%). Phylogenetic analysis showed that these UK Midlands echovirus 30 VP1 sequences clustered most closely with those from Europe and China. CONCLUSION: This study showed a continued predominance of echovirus 30 as a cause of viral meningitis, particularly in adults, though more surveillance is needed

Sex differences in the risk of coronary heart disease associated with type 2 diabetes:a Mendelian Randomization analysis

OBJECTIVE Observational studies have demonstrated that type 2 diabetes is a stronger risk factor for coronary heart disease (CHD) in women compared with men. However, it is not clear whether this reflects a sex differential in the causal effect of diabetes on CHD risk or results from sex-specific residual confounding. RESEARCH DESIGN AND METHODS Using 270 single nucleotide polymorphisms (SNPs) for type 2 diabetes identified in a type 2 diabetes genome-wide association study, we performed a sex-stratified Mendelian randomization (MR) study of type 2 diabetes and CHD using individual participant data in UK Biobank (251,420 women and 212,049 men). Weighted median, MR-Egger, MR-pleiotropy residual sum and outlier, and radial MR from summary-level analyses were used for pleiotropy assessment. RESULTS MR analyses showed that genetic risk of type 2 diabetes increased the odds of CHD for women (odds ratio 1.13 [95% CI 1.08–1.18] per 1-log unit increase in odds of type 2 diabetes) and men (1.21 [1.17–1.26] per 1-log unit increase in odds of type 2 diabetes). Sensitivity analyses showed some evidence of directional pleiotropy; however, results were similar after correction for outlier SNPs. CONCLUSIONS This MR analysis supports a causal effect of genetic liability to type 2 diabetes on risk of CHD that is not stronger for women than men. Assuming a lack of bias, these findings suggest that the prevention and management of type 2 diabetes for CHD risk reduction is of equal priority in both sexes