Collaboration in the Semantic Grid: a Basis for e-Learning

The CoAKTinG project aims to advance the state of the art in collaborative mediated spaces for the Semantic Grid. This paper presents an overview of the hypertext and knowledge based tools which have been deployed to augment existing collaborative environments, and the ontology which is used to exchange structure, promote enhanced process tracking, and aid navigation of resources before, after, and while a collaboration occurs. While the primary focus of the project has been supporting e-Science, this paper also explores the similarities and application of CoAKTinG technologies as part of a human-centred design approach to e-Learning

Building a case for accessing service provision in child and adolescent mental health assessments

In everyday conversations, people put forward versions of events and provide supporting evidence to build a credible case. In environments where there are potentially competing versions, case-building may take a more systematic format. Specifically, we conducted a rhetorical analysis to consider how in child mental health settings, families work to present a credible ‘doctorable’ reason for attendance. Data consisted of video-recordings of 28 families undergoing mental health assessments. Our findings point to eight rhetorical devices utilised in this environment to build a case. The devices functioned rhetorically to add credibility and authenticate the case being built, which was relevant as the only resource available to families claiming the presence of a mental health difficulty in the child were their spoken words. In other words, the ‘problem’ was something constructed through talk and therefore the kinds of resources used were seminal in decision-making

Unlocking the bottleneck in forward genetics using whole-genome sequencing and identity by descent to isolate causative mutations

Forward genetics screens with N-ethyl-N-nitrosourea (ENU) provide a powerful way to illuminate gene function and generate mouse models of human disease; however, the identification of causative mutations remains a limiting step. Current strategies depend on conventional mapping, so the propagation of affected mice requires non-lethal screens; accurate tracking of phenotypes through pedigrees is complex and uncertain; out-crossing can introduce unexpected modifiers; and Sanger sequencing of candidate genes is inefficient. Here we show how these problems can be efficiently overcome using whole-genome sequencing (WGS) to detect the ENU mutations and then identify regions that are identical by descent (IBD) in multiple affected mice. In this strategy, we use a modification of the Lander-Green algorithm to isolate causative recessive and dominant mutations, even at low coverage, on a pure strain background. Analysis of the IBD regions also allows us to calculate the ENU mutation rate (1.54 mutations per Mb) and to model future strategies for genetic screens in mice. The introduction of this approach will accelerate the discovery of causal variants, permit broader and more informative lethal screens to be used, reduce animal costs, and herald a new era for ENU mutagenesis.The High-Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics is funded by Wellcome Trust grant reference 090532/Z/09/Z and MRC Hub grant G0900747 91070. This study was supported by Wellcome Trust Strategic Award 082030 (CCG), Wellcome Trust Studentship 094446/Z/10/Z (KRB), the Oxford NIHR Biomedical Research Centre, and the MRC Human Immunology Unit (RJC). AJR and GL were supported by Wellcome Trust grant 090532/Z/ 09/Z, CCG and AE by a Major initiative Award from the Clive and Vera Ramaciotti Foundation, and AE by an NHMRC Career Development Award. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Burned area and carbon emissions across northwestern boreal North America from 2001-2019

Fire is the dominant disturbance agent in Alaskan and Canadian boreal ecosystems and releases large amounts of carbon into the atmosphere. Burned area and carbon emissions have been increasing with climate change, which have the potential to alter the carbon balance and shift the region from a historic sink to a source. It is therefore critically important to track the spatiotemporal changes in burned area and fire carbon emissions over time. Here we developed a new burned-area detection algorithm between 2001-2019 across Alaska and Canada at 500 m (meters) resolution that utilizes finer-scale 30 m Landsat imagery to account for land cover unsuitable for burning. This method strictly balances omission and commission errors at 500 m to derive accurate landscape- and regional-scale burned-area estimates. Using this new burned-area product, we developed statistical models to predict burn depth and carbon combustion for the same period within the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) core and extended domain. Statistical models were constrained using a database of field observations across the domain and were related to a variety of response variables including remotely sensed indicators of fire severity, fire weather indices, local climate, soils, and topographic indicators. The burn depth and aboveground combustion models performed best, with poorer performance for belowground combustion. We estimate 2.37×106 ha (2.37 Mha) burned annually between 2001-2019 over the ABoVE domain (2.87 Mha across all of Alaska and Canada), emitting 79.3 ± 27.96 Tg (±1 standard deviation) of carbon (C) per year, with a mean combustion rate of 3.13 ± 1.17 kg C m-2. Mean combustion and burn depth displayed a general gradient of higher severity in the northwestern portion of the domain to lower severity in the south and east. We also found larger-fire years and later-season burning were generally associated with greater mean combustion. Our estimates are generally consistent with previous efforts to quantify burned area, fire carbon emissions, and their drivers in regions within boreal North America; however, we generally estimate higher burned area and carbon emissions due to our use of Landsat imagery, greater availability of field observations, and improvements in modeling. The burned area and combustion datasets described here (the ABoVE Fire Emissions Database, or ABoVE-FED) can be used for local- to continental-scale applications of boreal fire science

A Randomized Placebo-Controlled Trial of \u3cem\u3eN\u3c/em\u3e-Acetylcysteine for Cannabis Use Disorder in Adults

Background—Cannabis use disorder (CUD) is a prevalent and impairing condition, and established psychosocial treatments convey limited efficacy. In light of recent findings supporting the efficacy of N-acetylcysteine (NAC) for CUD in adolescents, the objective of this trial was to evaluate its efficacy in adults. Methods—In a 12-week double-blind randomized placebo-controlled trial, treatment-seeking adults ages 18–50 with CUD (N=302), enrolled across six National Drug Abuse Treatment Clinical Trials Network-affiliated clinical sites, were randomized in a 1:1 ratio to a 12-week course of NAC 1200 mg (n=153) or placebo (n=149) twice daily. All participants received contingency management (CM) and medical management. The primary efficacy measure was the odds of negative urine cannabinoid tests during treatment, compared between NAC and placebo participants. Results—There was not statistically significant evidence that the NAC and placebo groups differed in cannabis abstinence (odds ratio = 1.00, 95% confidence interval 0.63 – 1.59; p=0.984). Overall, 22.3% of urine cannabinoid tests in the NAC group were negative, compared with 22.4% in the placebo group. Many participants were medication non-adherent; exploratory analysis within medication-adherent subgroups revealed no significant differential abstinence outcomes by treatment group. Conclusions—In contrast with prior findings in adolescents, there is no evidence that NAC 1200 mg twice daily plus CM is differentially efficacious for CUD in adults when compared to placebo plus CM. This discrepant finding between adolescents and adults with CUD may have been influenced by differences in development, cannabis use profiles, responses to embedded behavioral treatment, medication adherence, and other factors

A mouse model with a frameshift mutation in the nuclear factor I/X (NFIX) gene has phenotypic features of Marshall-Smith syndrome

The nuclear factor I/X (NFIX) gene encodes a ubiquitously expressed transcription factor whose mutations lead to two allelic disorders characterized by developmental, skeletal, and neural abnormalities, namely, Malan syndrome (MAL) and Marshall–Smith syndrome (MSS). NFIX mutations associated with MAL mainly cluster in exon 2 and are cleared by nonsense-mediated decay (NMD) leading to NFIX haploinsufficiency, whereas NFIX mutations associated with MSS are clustered in exons 6–10 and escape NMD and result in the production of dominant-negative mutant NFIX proteins. Thus, different NFIX mutations have distinct consequences on NFIX expression. To elucidate the in vivo effects of MSS-associated NFIX exon 7 mutations, we used CRISPR-Cas9 to generate mouse models with exon 7 deletions that comprised: a frameshift deletion of two nucleotides (Nfix Del2); in-frame deletion of 24 nucleotides (Nfix Del24); and deletion of 140 nucleotides (Nfix Del140). Nfix+/Del2, Nfix+/Del24, Nfix+/Del140, NfixDel24/Del24, and NfixDel140/Del140 mice were viable, normal, and fertile, with no skeletal abnormalities, but NfixDel2/Del2 mice had significantly reduced viability (p Nfix Del2 was not cleared by NMD, and NfixDel2/Del2 mice, when compared to Nfix+/+ and Nfix+/Del2 mice, had: growth retardation; short stature with kyphosis; reduced skull length; marked porosity of the vertebrae with decreased vertebral and femoral bone mineral content; and reduced caudal vertebrae height and femur length. Plasma biochemistry analysis revealed NfixDel2/Del2 mice to have increased total alkaline phosphatase activity but decreased C-terminal telopeptide and procollagen-type-1-N-terminal propeptide concentrations compared to Nfix+/+ and Nfix+/Del2 mice. NfixDel2/Del2 mice were also found to have enlarged cerebral cortices and ventricular areas but smaller dentate gyrus compared to Nfix+/+ mice. Thus, NfixDel2/Del2 mice provide a model for studying the in vivo effects of NFIX mutants that escape NMD and result in developmental abnormalities of the skeletal and neural tissues that are associated with MSS

Deep Sequencing of Pyrethroid-Resistant Bed Bugs Reveals Multiple Mechanisms of Resistance within a Single Population

A frightening resurgence of bed bug infestations has occurred over the last 10 years in the U.S. and current chemical methods have been inadequate for controlling this pest due to widespread insecticide resistance. Little is known about the mechanisms of resistance present in U.S. bed bug populations, making it extremely difficult to develop intelligent strategies for their control. We have identified bed bugs collected in Richmond, VA which exhibit both kdr-type (L925I) and metabolic resistance to pyrethroid insecticides. Using LD50 bioassays, we determined that resistance ratios for Richmond strain bed bugs were ∼5200-fold to the insecticide deltamethrin. To identify metabolic genes potentially involved in the detoxification of pyrethroids, we performed deep-sequencing of the adult bed bug transcriptome, obtaining more than 2.5 million reads on the 454 titanium platform. Following assembly, analysis of newly identified gene transcripts in both Harlan (susceptible) and Richmond (resistant) bed bugs revealed several candidate cytochrome P450 and carboxylesterase genes which were significantly over-expressed in the resistant strain, consistent with the idea of increased metabolic resistance. These data will accelerate efforts to understand the biochemical basis for insecticide resistance in bed bugs, and provide molecular markers to assist in the surveillance of metabolic resistance

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

MiR-137-derived polygenic risk: effects on cognitive performance in patients with schizophrenia and controls

Variants at microRNA-137 (MIR137), one of the most strongly associated schizophrenia risk loci identified to date, have been associated with poorer cognitive performance. As microRNA-137 is known to regulate the expression of ~1900 other genes, including several that are independently associated with schizophrenia, we tested whether this gene set was also associated with variation in cognitive performance. Our analysis was based on an empirically derived list of genes whose expression was altered by manipulation of MIR137 expression. This list was cross-referenced with genome-wide schizophrenia association data to construct individual polygenic scores. We then tested, in a sample of 808 patients and 192 controls, whether these risk scores were associated with altered performance on cognitive functions known to be affected in schizophrenia. A subgroup of healthy participants also underwent functional imaging during memory (n=108) and face processing tasks (n=83). Increased polygenic risk within the empirically derived miR-137 regulated gene score was associated with significantly lower performance on intelligence quotient, working memory and episodic memory. These effects were observed most clearly at a polygenic threshold of P=0.05, although significant results were observed at all three thresholds analyzed. This association was found independently for the gene set as a whole, excluding the schizophrenia-associated MIR137 SNP itself. Analysis of the spatial working memory fMRI task further suggested that increased risk score (thresholded at P=10−5) was significantly associated with increased activation of the right inferior occipital gyrus. In conclusion, these data are consistent with emerging evidence that MIR137 associated risk for schizophrenia may relate to its broader downstream genetic effects