832 research outputs found
Configuration development study of the X-24C hypersonic research airplane
Bottom line results were made of a three-phase study to determine the feasibility of designing, building, and operating, and maintaining an air-launched high performance aircraft capable of cruising at speeds up to Mach 8 for short durations. The results show that Lockalloy heat-sink structure affords the capability for a 'work-horse' vehicle which can serve as an excellent platform for this research. It was further concluded that the performance of a blended wing body configuration surpassed that of a lifting body design for typical X-24C missions. The cost of a two vehicle program, less engines, B-52 modification and contractor support after delivery, can be kept within $70M (in Jan. 1976 dollars)
Web-based cognitive testing in psychiatric research: validation and usability study
Background:
Cognitive impairments are features of many psychiatric disorders and affect functioning. A barrier to cognitive research on psychiatric disorders is the lack of large cross-disorder data sets. However, the collection of cognitive data can be logistically challenging and expensive. Web-based collection may be an alternative; however, little is known about who does and does not complete web-based cognitive assessments for psychiatric research.
Objective:
The aims of this study are to develop a web-based cognitive battery for use in psychiatric research, validate the battery against the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery, and compare the characteristics of the participants who chose to take part with those of the individuals who did not participate.
Methods:
Tasks were developed by The Many Brains Project and selected to measure the domains specified by the MATRICS initiative. We undertook a cross-validation study of 65 participants with schizophrenia, bipolar disorder, depression, or no history of psychiatric disorders to compare the web-based tasks with the MATRICS Consensus Cognitive Battery. Following validation, we invited participants from 2 large ongoing genetic studies, which recruited participants with psychiatric disorders to complete the battery and evaluated the demographic and clinical characteristics of those who took part.
Results:
Correlations between web-based and MATRICS tasks ranged between 0.26 and 0.73. Of the 961 participants, 887 (92.3%) completed at least one web-based task, and 644 (67%) completed all tasks, indicating adequate completion rates. Predictors of web-based participation included being female (odds ratio [OR] 1.3, 95% CI 1.07-1.58), ethnicity other than White European (OR 0.66, 95% CI 0.46-0.96), higher levels of education (OR 1.19, 95% CI 1.11-1.29), diagnosis of an eating disorder (OR 2.17, 95% CI 1.17-4) or depression and anxiety (OR 5.12, 95% CI 3.38-7.83), and absence of a diagnosis of schizophrenia (OR 0.59, 95% CI 0.35-0.94). Lower performance on the battery was associated with poorer functioning (B=−1.76, SE 0.26; P<.001).
Conclusions:
Our findings offer valuable insights into the advantages and disadvantages of testing cognitive function remotely for mental health research
A meta-analysis comparing cognitive function across the mood/psychosis diagnostic spectrum
Background
The nature and degree of cognitive impairments in schizoaffective disorder is not well established. The aim of this meta-analysis was to characterise cognitive functioning in schizoaffective disorder and compare it with cognition in schizophrenia and bipolar disorder. Schizoaffective disorder was considered both as a single category and as its two diagnostic subtypes, bipolar and depressive disorder.
Methods
Following a thorough literature search (468 records identified), we included 31 studies with a total of 1685 participants with schizoaffective disorder, 3357 with schizophrenia and 1095 with bipolar disorder. Meta-analyses were conducted for seven cognitive variables comparing performance between participants with schizoaffective disorder and schizophrenia, and between schizoaffective disorder and bipolar disorder.
Results
Participants with schizoaffective disorder performed worse than those with bipolar disorder (g = −0.30) and better than those with schizophrenia (g = 0.17). Meta-analyses of the subtypes of schizoaffective disorder showed cognitive impairments in participants with the depressive subtype are closer in severity to those seen in participants with schizophrenia (g = 0.08), whereas those with the bipolar subtype were more impaired than those with bipolar disorder (g = −0.23) and less impaired than those with schizophrenia (g = 0.29). Participants with the depressive subtype had worse performance than those with the bipolar subtype but this was not significant (g = 0.25, p = 0.05).
Conclusion
Cognitive impairments increase in severity from bipolar disorder to schizoaffective disorder to schizophrenia. Differences between the subtypes of schizoaffective disorder suggest combining the subtypes of schizoaffective disorder may obscure a study's results and hamper efforts to understand the relationship between this disorder and schizophrenia or bipolar disorder
Changes In Nitrogen Use Efficiency And Soil Quality After Five Years Of Managing For High Yield Corn And Soybean
Average corn grain yields in the USA have increased linearly at a rate of 1.7 bu/acre over the past 35 years with a national yield average of 140 bu/acre. Corn yield contest winners and simulation models, however, indicate there is ~100 bu/a in exploitable corn yield gap. Four years (1999-2002) of plant development, grain yield and nutrient uptake were compared in intensive irrigated maize systems representing (a) recommended best management practices for a yield goal of 200 bu/acre (M1) and (b) intensive management aiming at a yield goal of 300 bu/acre (M2). For each management level, three levels of plant density (30000-P1, 37000-P2 and 44000-P3 seed/acre) were compared in a continuous corn and corn- soybean rotation. Over five years, the grain yields increased 11% as a function of management and this effect was manifest under higher plant densities. A high yield of 285 bu/acre was achieved at the M2, P2 treatment in 2003. Higher population resulted in greater demand for N and K per unit grain yield. Over the past five years, nitrogen use efficiency has steadily improved in the M2 treatment due to improvements in soil quality. Intensive management and population levels significantly increased residue carbon inputs with disproportionately lower soil respiration. Closing the yield gap requires higher plant population and improved nutrient management to maintain efficient and profitable improvement in maize production. Soil quality improvements and higher residue inputs under intensive management should make this task easier with time
The association between peripheral inflammation, brain glutamate and antipsychotic response in Schizophrenia:Data from the STRATA collaboration
Glutamate and increased inflammation have been separately implicated in the pathophysiology of schizophrenia and the extent of clinical response to antipsychotic treatment. Despite the mechanistic links between pro-inflammatory and glutamatergic pathways, the relationships between peripheral inflammatory markers and brain glutamate in schizophrenia have not yet been investigated. In this study, we tested the hypothesis that peripheral levels of pro-inflammatory cytokines would be positively associated with brain glutamate levels in schizophrenia. Secondary analyses determined whether this relationship differed according to antipsychotic treatment response. The sample consisted of 79 patients with schizophrenia, of whom 40 were rated as antipsychotic responders and 39 as antipsychotic non-responders. Brain glutamate levels were assessed in the anterior cingulate cortex (ACC) and caudate using proton magnetic resonance spectroscopy (1H-MRS) and blood samples were collected for cytokine assay on the same study visit (IL-6, IL-8, IL-10, TNF- α and IFN-γ). Across the whole patient sample, there was a positive relationship between interferon-gamma (IFN-γ) and caudate glutamate levels (r = 0.31, p = 0.02). In the antipsychotic non-responsive group only, there was a positive relationship between interleukin-8 (IL-8) and caudate glutamate (r = 0.46, p = 0.01). These findings provide evidence to link specific peripheral inflammatory markers and caudate glutamate in schizophrenia and may suggest that this relationship is most marked in patients who show a poor response to antipsychotic treatment
A Mendelian randomization study of the causal association between anxiety phenotypes and schizophrenia
Schizophrenia shows a genetic correlation with both anxiety disorder and neuroticism, a trait strongly associated with anxiety. However, genetic correlations do not discern causality from genetic confounding. We therefore aimed to investigate whether anxiety-related phenotypes lie on the causal pathway to schizophrenia using Mendelian randomization (MR). Four MR methods, each with different assumptions regarding instrument validity, were used to investigate casual associations of anxiety and neuroticism related phenotypes on schizophrenia, and vice versa: inverse variance weighted (IVW), weighted median, weighted mode, and, when appropriate, MR Egger regression. MR provided evidence of a causal effect of neuroticism on schizophrenia (IVW odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.12-1.59), but only weak evidence of a causal effect of anxiety on schizophrenia (IVW OR: 1.10, 95% CI: 1.01-1.19). There was also evidence of a causal association from schizophrenia liability to anxiety disorder (IVW OR: 1.28, 95% CI: 1.18-1.39) and worry (IVW beta: 0.05, 95% CI: 0.03-0.07), but effect estimates from schizophrenia to neuroticism were inconsistent in the main analysis. The evidence of neuroticism increasing schizophrenia risk provided by our results supports future efforts to evaluate neuroticism- or anxiety-based therapies to prevent onset of psychotic disorders
Cis-effects on gene expression in the human prenatal brain associated with genetic risk for neuropsychiatric disorders
The majority of common risk alleles identified for neuropsychiatric disorders reside in non-coding regions of the genome and are therefore likely to impact gene regulation. However, the genes that are primarily affected and the nature and developmental timing of these effects remain unclear. Given the hypothesised role for early neurodevelopmental processes in these conditions, we here define genetic predictors of gene expression in the human fetal brain with which we perform transcriptome-wide association studies (TWASs) of attention deficit hyperactivity disorder (ADHD), autism spectrum disorder, bipolar disorder, major depressive disorder and schizophrenia. We identify prenatal cis-regulatory effects on 63 genes and 166 individual transcripts associated with genetic risk for these conditions. We observe pleiotropic effects of expression predictors for a number of genes and transcripts, including those of decreased DDHD2 expression in association with risk for schizophrenia and bipolar disorder, increased expression of a ST3GAL3 transcript with risk for schizophrenia and ADHD, and increased expression of an XPNPEP3 transcript with risk for schizophrenia, bipolar disorder and major depression. For the protocadherin alpha cluster genes PCDHA7 and PCDHA8, we find that predictors of low expression are associated with risk for major depressive disorder while those of higher expression are associated with risk for schizophrenia. Our findings support a role for altered gene regulation in the prenatal brain in susceptibility to various neuropsychiatric disorders and prioritize potential risk genes for further neurobiological investigation
Cognitive performance among carriers of pathogenic copy number variants: analysis of 152,000 UK Biobank subjects
Background The UK Biobank is a unique resource for biomedical research, with extensive phenotypic and genetic data on half a million adults from the general population. We aimed to examine the effect of neurodevelopmental copy number variants (CNVs) on the cognitive performance of participants. Methods We used Affymetrix Power Tools and PennCNV-Affy software to analyze Affymetrix microarrays of the first 152,728 genotyped individuals. We annotated a list of 93 CNVs and compared their frequencies with control datasets. We analyzed the performance on seven cognitive tests of carriers of 12 CNVs associated with schizophrenia (n = 1087) and of carriers of another 41 neurodevelopmental CNVs (n = 484). Results The frequencies of the 93 CNVs in the Biobank subjects were remarkably similar to those among 26,628 control subjects from other datasets. Carriers of schizophrenia-associated CNVs and of the group of 41 other neurodevelopmental CNVs had impaired performance on the cognitive tests, with nine of 14 comparisons remaining statistically significant after correction for multiple testing. They also had lower educational and occupational attainment (p values between 10−7 and 10−18). The deficits in cognitive performance were modest (Z score reductions between 0.01 and 0.51), compared with individuals with schizophrenia in the Biobank (Z score reductions between 0.35 and 0.90). Conclusions This is the largest study on the cognitive phenotypes of CNVs to date. Adult carriers of neurodevelopmental CNVs from the general population have significant cognitive deficits. The UK Biobank will allow unprecedented opportunities for analysis of further phenotypic consequences of CNVs
Pharmacogenomic variants and drug interactions identified through the genetic analysis of clozapine metabolism
Objective: Clozapine is the only effective medication for treatment-resistant schizophrenia, but its worldwide use is still limited because of its complex titration protocols. While the discovery of pharmacogenomic variants of clozapine metabolism may improve clinical management, no robust findings have yet been reported. This study is the first to adopt the framework of genome-wide association studies (GWASs) to discover genetic markers of clozapine plasma concentrations in a large sample of patients with treatment-resistant schizophrenia. Methods: The authors used mixed-model regression to combine data from multiple assays of clozapine metabolite plasma concentrations from a clozapine monitoring service and carried out a genome-wide analysis of clozapine, norclozapine, and their ratio on 10,353 assays from 2,989 individuals. These analyses were adjusted for demographic factors known to influence clozapine metabolism, although it was not possible to adjust for all potential mediators given the available data. GWAS results were used to pinpoint specific enzymes and metabolic pathways and compounds that might interact with clozapine pharmacokinetics. Results: The authors identified four distinct genome-wide significant loci that harbor common variants affecting the metabolism of clozapine or its metabolites. Detailed examination pointed to coding and regulatory variants at several CYP* and UGT* genes as well as corroborative evidence for interactions between the metabolism of clozapine, coffee, and tobacco. Individual effects of single single-nucleotide polymorphisms (SNPs) fine-mapped from these loci were large, such as the minor allele of rs2472297, which was associated with a reduction in clozapine concentrations roughly equivalent to a decrease of 50 mg/day in clozapine dosage. On their own, these single SNPs explained from 1.15% to 9.48% of the variance in the plasma concentration data. Conclusions: Common genetic variants with large effects on clozapine metabolism exist and can be found via genome-wide approaches. Their identification opens the way for clinical studies assessing the use of pharmacogenomics in the clinical management of patients with treatment-resistant schizophrenia
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