The Role of ICTs in Supporting Collaborative Networks in the Agro-Food Sector: Two Case Studies from South West England

Over recent years, in a wide range of countries, grassroots initiatives have emerged aimed at overcoming the limits of the mainstream agro-business system. These initiatives aim at improving farmers’ access to local and regional markets and consumers’ access to fresh local produce. Among these initiatives, Food Hubs have emerged as a promising way to improve local food supply systems. They represent collaborative networks of producers and consumers that aggregate, distribute, and market local food products. ICTs enable these collaborative networks by allowing information exchange among their actors and by providing collaborative tools that allow quick co-ordination between members of the network. The paper aims to analyse how the adoption of ICTs have fostered the development of new, initiatives oriented at establishing local food networks and to reconnect producers and consumers. The study will present results from the analysis of two food-hub initiatives based in South West England, which are adopting informative systems to support their activities and to implement novel business models: Stroudco Food Hub and Dean Forest Food Hub

Genome-wide mega-analysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies

The epilepsies affect around 65 million people worldwide and have a substantial missing heritability component. We report a genome-wide mega-analysis involving 15,212 individuals with epilepsy and 29,677 controls, which reveals 16 genome-wide significant loci, of which 11 are novel. Using various prioritization criteria, we pinpoint the 21 most likely epilepsy genes at these loci, with the majority in genetic generalized epilepsies. These genes have diverse biological functions, including coding for ion-channel subunits, transcription factors and a vitamin-B6 metabolism enzyme. Converging evidence shows that the common variants associated with epilepsy play a role in epigenetic regulation of gene expression in the brain. The results show an enrichment for monogenic epilepsy genes as well as known targets of antiepileptic drugs. Using SNP-based heritability analyses we disentangle both the unique and overlapping genetic basis to seven different epilepsy subtypes. Together, these findings provide leads for epilepsy therapies based on underlying pathophysiology

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Analysis of shared heritability in common disorders of the brain

Paroxysmal Cerebral Disorder

Genome-wide mega-analysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies

The epilepsies affect around 65 million people worldwide and have a substantial missing heritability component. We report a genome-wide mega-analysis involving 15,212 individuals with epilepsy and 29,677 controls, which reveals 16 genome-wide significant loci, of which 11 are novel. Using various prioritization criteria, we pinpoint the 21 most likely epilepsy genes at these loci, with the majority in genetic generalized epilepsies. These genes have diverse biological functions, including coding for ion-channel subunits, transcription factors and a vitamin-B6 metabolism enzyme. Converging evidence shows that the common variants associated with epilepsy play a role in epigenetic regulation of gene expression in the brain. The results show an enrichment for monogenic epilepsy genes as well as known targets of antiepileptic drugs. Using SNP-based heritability analyses we disentangle both the unique and overlapping genetic basis to seven different epilepsy subtypes. Together, these findings provide leads for epilepsy therapies based on underlying pathophysiology

GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment

The effect of pain on involuntary and voluntary capture of attention

BACKGROUND: There is converging evidence for the notion that pain affects a broad range of attentional domains. This study investigated the influence of pain on the involuntary capture of attention as indexed by the P3a component in the event-related potential derived from the electroencephalogram. METHODS: Participants performed in an auditory oddball task in a pain-free and a pain condition during which they submerged a hand in cold water. Novel, infrequent and unexpected auditory stimuli were presented randomly in a series of frequent standard and infrequent target tones. P3a and P3b amplitudes were observed to novel, unexpected and target-related stimuli, respectively. RESULTS: Both electrophysiological components were characterized by reduced amplitudes in the pain compared with the pain-free condition. Hit rate and reaction time to target stimuli did not differ between the two conditions presumably because the experimental task was not difficult enough to exceed attentional capacities under pain conditions. CONCLUSIONS: These results indicate that voluntary attention serving the maintenance and control of ongoing information processing (reflected by the P3b amplitude) is impaired by pain. In addition, the involuntary capture of attention and orientation to novel, unexpected information (measured by the P3a) is also impaired by pain. Thus, neurophysiological measures examined in this study support the theoretical positions proposing that pain can reduce attentional processing capacity. These findings have potentially important implications at the theoretical level for our understanding of the interplay of pain and cognition, and at the therapeutic level for the clinical treatment of individuals experiencing ongoing pain

Four-year outcome after early withdrawal of antiepileptic drugs in childhood epilepsy

Four-year follow-up of children with epilepsy included in a randomized trial of early withdrawal of antiepileptic drugs showed that 51% achieved a terminal remission of at least 2 years without medication and 21% with medication; 15% had seizures during the fourth year. Early medication withdrawal is not recommended as standard practice in children with a rapid response to medication. The authors developed a model to predict outcome if withdrawal is considere

Is 4.0 Tesla MRI advantageous for current source localization of weak magnetic fields?

Recently, several methods have been proposed for measuring the magnetic fields produced by weak electric currents using magnetic resonance imaging (MRI), including a theoretically described technique for source localization of current dipoles using signal phase. We have investigated whether these results can be replicated experimentally using 4.0 Tesla (T) MRI with a dipole phantom. While the use of high magnetic fields is advantageous in conventional functional MRI, it is unclear, a priori, whether MR current source localization also benefits. This study presents the technical challenges in MRI current source imaging and quantifies sensitivity using a phantom containing a current dipoleNRC publication: Ye