Developmental dyslexia: Genetic dissection of a complex cognitive trait

Developmental dyslexia, a specific impairment of reading ability despite adequate intelligence and educational opportunity, is one of the most frequent childhood disorders. Since the first documented cases at the beginning of the last century, it has become increasingly apparent that the reading problems of people with dyslexia form part of a heritable neurobiological syndrome. As for most cognitive and behavioural traits, phenotypic definition is fraught with difficulties and the genetic basis is complex, making the isolation of genetic risk factors a formidable challenge. Against such a background, it is notable that several recent studies have reported the localization of genes that influence dyslexia and other language-related traits. These investigations exploit novel research approaches that are relevant to many areas of human neurogenetics

Artificial Intelligence in the Context of Human Consciousness

Artificial intelligence (AI) can be defined as the ability of a machine to learn and make decisions based on acquired information. AI’s development has incited rampant public speculation regarding the singularity theory: a futuristic phase in which intelligent machines are capable of creating increasingly intelligent systems. Its implications, combined with the close relationship between humanity and their machines, make achieving understanding both natural and artificial intelligence imperative. Researchers are continuing to discover natural processes responsible for essential human skills like decision-making, understanding language, and performing multiple processes simultaneously. Artificial intelligence attempts to simulate these functions through techniques like artificial neural networks, Markov Decision Processes, Human Language Technology, and Multi-Agent Systems, which rely upon a combination of mathematical models and hardware

Fragmentation Increases Impact of Wind Disturbance on Forest Structure and Carbon Stocks in a Western Amazonian Landscape

Tropical second-growth forests could help mitigate climate change, but the degree to which their carbon potential is achieved will depend on exposure to disturbance. Wind disturbance is common in tropical forests, shaping structure, composition, and function, and influencing successional trajectories. However, little is known about the impacts of extreme winds in fragmented landscapes, though second-growth forests are often located in mosaics of forest, pasture, cropland, and other land cover types. Though indirect evidence suggests that fragmentation increases risk of wind damage, few studies have found such impacts following severe storms. In this study, we ask whether fragmentation and forest type (old vs. second growth) were associated with variation in wind damage after a severe convective storm in a fragmented production landscape in western Amazonia. We applied linear spectral unmixing to Landsat 8 imagery from before and after the storm, and combined it with field observations of damage to map wind effects on forest structure and biomass (Figure 4, 5). We also used Landsat 8 imagery to map land cover with the goals of identifying old- and second-growth forest and characterizing fragmentation. We used these data to assess variation in wind disturbance across 95,596 hectares of forest, distributed over 6,110 patches. We find that fragmentation is significantly associated with wind damage, with damage severity higher at forest edges and in edgier, more isolated patches (Figure 7). Damage was more severe in old-growth than in second-growth forests, but this effect was weaker than that of fragmentation (Figure 8). These results illustrate the importance of considering spatial configuration and landscape context in planning tropical forest restoration and predicting carbon sequestration in second-growth forests. Future research should address the mechanisms behind these results, to minimize wind damage risk in second-growth forests so their carbon potential can be maximally achieved

Occurrence of preterm calving in Great Britain and associations with milk production and reproductive performance in dairy cattle

This study describes the occurrence of preterm calving in Great Britain and evaluates its associations with subsequent milk production and reproductive performances and survival on farm of dairy cows. A total of 53 British dairy farms and 5759 animals with detailed breeding and milk recording data available were used to form two study groups: preterm calving (calving occurring between days 266 and 277 of gestation) and full-term calving (calving occurring at 278 days of gestation and over). Mixed effects models were implemented to compare milk production, clinical cases of mastitis and number of services per conception between groups. Kaplan-Meier curves and Cox regression analyses compared time from calving to conception, calving interval and survival on farm between groups. Preterm calving cows showed significantly lower milk yield (P<0.01) and butter fat per cent (P=0.02), increased milk protein per cent (P=0.01), longer survival on farm (P<0.01), and a tendency for shorter calving to conception intervals and fewer services per conception, although other factors were involved in the reproduction outcomes. Experiencing a preterm calving is associated with lower milk production and longer survival times on farm. Potential risk factors for preterm calving, such as infectious diseases, diet and husbandry practices, should be further investigated

A Common Variant Associated with Dyslexia Reduces Expression of the KIAA0319 Gene

Numerous genetic association studies have implicated the KIAA0319 gene on human chromosome 6p22 in dyslexia susceptibility. The causative variant(s) remains unknown but may modulate gene expression, given that (1) a dyslexia-associated haplotype has been implicated in the reduced expression of KIAA0319, and (2) the strongest association has been found for the region spanning exon 1 of KIAA0319. Here, we test the hypothesis that variant(s) responsible for reduced KIAA0319 expression resides on the risk haplotype close to the gene's transcription start site. We identified seven single-nucleotide polymorphisms on the risk haplotype immediately upstream of KIAA0319 and determined that three of these are strongly associated with multiple reading-related traits. Using luciferase-expressing constructs containing the KIAA0319 upstream region, we characterized the minimal promoter and additional putative transcriptional regulator regions. This revealed that the minor allele of rs9461045, which shows the strongest association with dyslexia in our sample (max p-value = 0.0001), confers reduced luciferase expression in both neuronal and non-neuronal cell lines. Additionally, we found that the presence of this rs9461045 dyslexia-associated allele creates a nuclear protein-binding site, likely for the transcriptional silencer OCT-1. Knocking down OCT-1 expression in the neuronal cell line SHSY5Y using an siRNA restores KIAA0319 expression from the risk haplotype to nearly that seen from the non-risk haplotype. Our study thus pinpoints a common variant as altering the function of a dyslexia candidate gene and provides an illustrative example of the strategic approach needed to dissect the molecular basis of complex genetic traits

Characterization of extrasolar terrestrial planets from diurnal photometric variability

The detection of massive planets orbiting nearby stars has become almost routine, but current techniques are as yet unable to detect terrestrial planets with masses comparable to the Earth's. Future space-based observatories to detect Earth-like planets are being planned. Terrestrial planets orbiting in the habitable zones of stars-where planetary surface conditions are compatible with the presence of liquid water-are of enormous interest because they might have global environments similar to Earth's and even harbor life. The light scattered by such a planet will vary in intensity and colour as the planet rotates; the resulting light curve will contain information about the planet's properties. Here we report a model that predicts features that should be discernible in light curves obtained by low-precision photometry. For extrasolar planets similar to Earth we expect daily flux variations up to hundreds of percent, depending sensitively on ice and cloud cover. Qualitative changes in surface or climate generate significant changes in the predicted light curves. This work suggests that the meteorological variability and the rotation period of an Earth-like planet could be derived from photometric observations. Other properties such as the composition of the surface (e.g., ocean versus land fraction), climate indicators (for example ice and cloud cover), and perhaps even signatures of Earth-like plant life could be constrained or possibly, with further study, even uniquely determined.Comment: Published in Nature. 9 pages including 3 figure

Genome-wide screening for DNA variants associated with reading and language traits

This research was funded by: Max Planck Society, the University of St Andrews - Grant Number: 018696, US National Institutes of Health - Grant Number: P50 HD027802, Wellcome Trust - Grant Number: 090532/Z/09/Z, and Medical Research Council Hub Grant Grant Number: G0900747 91070Reading and language abilities are heritable traits that are likely to share some genetic influences with each other. To identify pleiotropic genetic variants affecting these traits, we first performed a genome‐wide association scan (GWAS) meta‐analysis using three richly characterized datasets comprising individuals with histories of reading or language problems, and their siblings. GWAS was performed in a total of 1862 participants using the first principal component computed from several quantitative measures of reading‐ and language‐related abilities, both before and after adjustment for performance IQ. We identified novel suggestive associations at the SNPs rs59197085 and rs5995177 (uncorrected P ≈ 10–7 for each SNP), located respectively at the CCDC136/FLNC and RBFOX2 genes. Each of these SNPs then showed evidence for effects across multiple reading and language traits in univariate association testing against the individual traits. FLNC encodes a structural protein involved in cytoskeleton remodelling, while RBFOX2 is an important regulator of alternative splicing in neurons. The CCDC136/FLNC locus showed association with a comparable reading/language measure in an independent sample of 6434 participants from the general population, although involving distinct alleles of the associated SNP. Our datasets will form an important part of on‐going international efforts to identify genes contributing to reading and language skills.Publisher PDFPeer reviewe

Integrating evidence, politics and society: a methodology for the science–policy interface

There is currently intense debate over expertise, evidence and ‘post-truth’ politics, and how this is influencing policy formulation and implementation. In this article, we put forward a methodology for evidence-based policy making intended as a way of helping navigate this web of complexity. Starting from the premise of why it is so crucial that policies to meet major global challenges use scientific evidence, we discuss the socio-political difficulties and complexities that hinder this process. We discuss the necessity of embracing a broader view of what constitutes evidence—science and the evaluation of scientific evidence cannot be divorced from the political, cultural and social debate that inevitably and justifiably surrounds these major issues. As a pre-requisite for effective policy making, we propose a methodology that fully integrates scientific investigation with political debate and social discourse. We describe a rigorous process of mapping, analysis, visualisation and sharing of evidence, constructed from integrating science and social science data. This would then be followed by transparent evidence evaluation, combining independent assessment to test the validity and completeness of the evidence with deliberation to discover how the evidence is perceived, misunderstood or ignored. We outline the opportunities and the problems derived from the use of digital communications, including social media, in this methodology, and emphasise the power of creative and innovative evidence visualisation and sharing in shaping policy

Mapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imagery

An efficient means to map tree plantations is needed to detect tropical land use change and evaluate reforestation projects. To analyze recent tree plantation expansion in northeastern Costa Rica, we examined the potential of combining moderate-resolution hyperspectral imagery (2005 HyMap mosaic) with multitemporal, multispectral data (Landsat) to accurately classify (1) general forest types and (2) tree plantations by species composition. Following a linear discriminant analysis to reduce data dimensionality, we compared four Random Forest classification models: hyperspectral data (HD) alone; HD plus interannual spectral metrics; HD plus a multitemporal forest regrowth classification; and all three models combined. The fourth, combined model achieved overall accuracy of 88.5%. Adding multitemporal data significantly improved classification accuracy (p less than 0.0001) of all forest types, although the effect on tree plantation accuracy was modest. The hyperspectral data alone classified six species of tree plantations with 75% to 93% producer's accuracy; adding multitemporal spectral data increased accuracy only for two species with dense canopies. Non-native tree species had higher classification accuracy overall and made up the majority of tree plantations in this landscape. Our results indicate that combining occasionally acquired hyperspectral data with widely available multitemporal satellite imagery enhances mapping and monitoring of reforestation in tropical landscapes

Active Amplification of the Terrestrial Albedo to Mitigate Climate Change: An Exploratory Study

This study explores the potential to enhance the reflectance of solar insolation by the human settlement and grassland components of the Earth's terrestrial surface as a climate change mitigation measure. Preliminary estimates derived using a static radiative transfer model indicate that such efforts could amplify the planetary albedo enough to offset the current global annual average level of radiative forcing caused by anthropogenic greenhouse gases by as much as 30 percent or 0.76 W/m2. Terrestrial albedo amplification may thus extend, by about 25 years, the time available to advance the development and use of low-emission energy conversion technologies which ultimately remain essential to mitigate long-term climate change. However, additional study is needed to confirm the estimates reported here and to assess the economic and environmental impacts of active land-surface albedo amplification as a climate change mitigation measure.Comment: 21 pages, 3 figures. In press with Mitigation and Adaptation Strategies for Global Change, Springer, N