Measuring vascular reactivity with breath-holds after stroke: a method to aid interpretation of group-level BOLD signal changes in longitudinal fMRI studies

Blood oxygenation level dependent (BOLD) contrast fMRI is a widely used technique to map brain function, and to monitor its recovery after stroke. Since stroke has a vascular etiology, the neurovascular coupling between cerebral blood flow and neural activity may be altered, resulting in uncertainties when interpreting longitudinal BOLD signal changes. The purpose of this study was to demonstrate the feasibility of using a recently validated breath-hold task in patients with stroke, both to assess group level changes in cerebrovascular reactivity (CVR) and to determine if alterations in regional CVR over time will adversely affect interpretation of task-related BOLD signal changes. Three methods of analyzing the breathhold data were evaluated. The CVR measures were compared over healthy tissue, infarcted tissue, and the peri-infarct tissue, both sub-acutely (~two weeks) and chronically (~four months). In this cohort, a lack of CVR differences in healthy tissue between the patients and controls indicates that any group level BOLD signal change observed in these regions over time is unlikely to be related to vascular alterations. CVR was reduced in the peri-infarct tissue but remained unchanged over time. Therefore, although a lack of activation in this region compared to the controls may be confounded by a reduced CVR, longitudinal grouplevel BOLD changes may be more confidently attributed to neural activity changes in this cohort. By including this breath-hold based CVR assessment protocol in future studies of stroke recovery, researchers can be more assured that longitudinal changes in BOLD signal reflect true alterations in neural activity

Open Science and Open Innovation in Socio-Political Context: Knowledge Production and Societal Impact in an Age of Populism

This conceptual paper traces the origins and progress of Open Science and proposes its generative coupling to Open Innovation in the contemporary socio-political context; where universities are re-imaging their civic missions in the face of anti-establishment populist politics. This setting is one of changing knowledge production regimes and institutional pressures that create contradictions identifiable through the prism of the series of scientific norms conceptualised by Robert K. Merton. This paper privileges a sociological perspective to proffer scientific knowledge production as a societally embedded process, which is well illustrated by scholarship in the Science and Technology Studies (STS) and Science in Society fields. In doing so, it identifies the co-evolution, co-existence and co-production of Open Science with Open Innovation; and notes how it shares the attributes of other recent diagnoses of changing knowledge production regimes; in particular Mode 2, post-normal science and the Quadruple Helix. It also argues that Open Science can be coupled with Open Innovation to catalyse positive societal change, but that the rise of a populist post-truth era opposed to objectivity, expertise and technocratic political solutions gives the demand for openness and participation a different complexion. Merton’s norms provide a useful lens to observe recent shifts in the delivery of science, knowledge and innovation in society towards more inclusive, ethical and sustainable outcomes; and expose the limited reflection on how the appropriation and exploitation of open scientific knowledge encounters industrial R&D and Open Innovation

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

Topological Analysis of Metabolic Networks Integrating Co-Segregating Transcriptomes and Metabolomes in Type 2 Diabetic Rat Congenic Series

Background: The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus is caused by complex organ-specific cellular mechanisms contributing to impaired insulin secretion and insulin resistance. Methods: We used systematic metabotyping by 1H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualise shortest paths between metabolites and genes significantly associated with each genomic block. Results: Despite strong genomic similarities (95-99%) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific metabotypes (mQTL) and genome-wide expression traits (eQTL). Variation in key metabolites like glucose, succinate, lactate or 3-hydroxybutyrate, and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing shortest path length drove prioritization of biological validations by gene silencing. Conclusions: These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulations and to characterize novel functional roles for genes determining tissue-specific metabolism

Spin injection between epitaxial Co2.4Mn1.6Ga and an InGaAs quantum well

Electrical spin injection in a narrow [100] In0.2Ga0.8As quantum well in a GaAs p-i-n optical device is reported. The quantum well is located 300 nm from an AlGaAs Schottky barrier and this system is used to compare the efficiencies and temperature dependences of spin injection from Fe and the Heusler alloy Co2.4Mn1.6Ga grown by molecular-beam epitaxy. At 5 K, the injected electron spin polarizations for Fe and Co2.4Mn1.6Ga injectors are 31% and 13%, respectively. Optical detection is carried out in the oblique Hanle geometry. A dynamic nuclear polarization effect below 10 K enhances the magnetic field seen by the injected spins in both devices. The Co2.4Mn1.6Ga thin films are found to have a transport spin polarization of similar to 50% by point contact Andreev reflection conductivity measurements. (c) 2005 American Institute of Physics

Dynamical system analysis and forecasting of deformation produced by an earthquake fault

We present a method of constructing low-dimensional nonlinear models describing the main dynamical features of a discrete 2D cellular fault zone, with many degrees of freedom, embedded in a 3D elastic solid. A given fault system is characterized by a set of parameters that describe the dynamics, rheology, property disorder, and fault geometry. Depending on the location in the system parameter space we show that the coarse dynamics of the fault can be confined to an attractor whose dimension is significantly smaller than the space in which the dynamics takes place. Our strategy of system reduction is to search for a few coherent structures that dominate the dynamics and to capture the interaction between these coherent structures. The identification of the basic interacting structures is obtained by applying the Proper Orthogonal Decomposition (POD) to the surface deformations fields that accompany strike-slip faulting accumulated over equal time intervals. We use a feed-forward artificial neural network (ANN) architecture for the identification of the system dynamics projected onto the subspace (model space) spanned by the most energetic coherent structures. The ANN is trained using a standard back-propagation algorithm to predict (map) the values of the observed model state at a future time given the observed model state at the present time. This ANN provides an approximate, large scale, dynamical model for the fault.Comment: 30 pages, 12 figure

Stroke genetics: prospects for personalized medicine.

Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice

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

Prevalence and Factors Associated with Interpersonal Violence among In-School Adolescents in Ghana: Analysis of the Global School-Based Health Survey Data

Interpersonal violence is a critical public health concern that is linked with many negative consequences, including mortality. It is the second most predominant cause of death among male adolescents aged 15–19. This study used a nationally representative data from the recent Ghana Global School-based Health Survey to examine the prevalence and factors associated with interpersonal violence among Ghanaian in-school adolescents. A total of 2214 in-school adolescents were included in the final analysis. Multivariable binomial logistic regression analysis was performed to determine the factors assciated with interpersonal violence. The results of the regression analysis were presented as adjusted odds ratios (aOR) with 95% confidence level (CI) in all the analyses. Statistical significance was set at p &lt; 0.05. The overall prevalence of interpersonal violence was 55.7%, of which the prevalences of physical fighting and attack were 38.2% and 41.5%, respectively. In-school adolescents who had an injury were more likely to experience interpersonal violence (aOR = 2.29, 95% CI = 1.71–3.06) compared with those who did not have an injury. The odds of interpersonal violence were higher among in-school adolescents who were bullied (aOR = 2.48, 95% CI = 1.84–3.34) compared with those who were not bullied. In addition, in-school adolescents who attempted suicide (aOR = 1.56, 95% CI = 1.22–2.47), consumed alcohol at the time of the survey (aOR = 1.88, 95% CI = 1.15–3.06), and were truant (aOR = 1.58, 95% CI = 1.29–1.99) had higher odds of experiencing interpersonal violence. These factors provide education directors and school heads/teachers with the relevant information to guide them in designing specific interventions to prevent interpersonal violence, particularly physical fights and attacks in the school settings. School authorities should organize parent–teacher meetings or programs to help parents improve their relationships with in-school adolescents to prevent or minimize their risky behaviors, including physical fights.</jats:p