33 research outputs found
Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro Imaging genetics through meta analysis (ENIGMA) Consortium
BACKGROUND: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group.
METHODS: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide.
RESULTS: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset.
CONCLUSIONS: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia
On mutual impact of numerical linear algebra and large-scale optimization with focus on interior point methods
Temporal Association between Home Nursing and Hospital Costs at End of Life in Three Provinces
Background: Research has demonstrated that increases in palliative homecare nursing are associated with a reduction in the rate of subsequent hospitalizations. However, little evidence is available about the cost-savings potential of palliative nursing when accounting for both increased nursing costs and potentially reduced hospital costs. Methods: Our retrospective cohort study included cancer decedents from British Columbia, Ontario, and Nova Scotia who received any palliative nursing in the last 6 months of life. A Poisson regression analysis was used to determine the association of increased nursing costs (in 2-week blocks) on the relative average hospital costs in the subsequent 2-week block and on the overall total cost (hospital costs plus nursing costs in the preceding 2-week block). Results: The cohort included 58,022 cancer decedents. Results of the analysis for the last month of life showed an association between increased nursing costs and decreased relative hospital costs in comparisons with a reference group (>0 to 1 hour nursing in the block): the maximum decrease was 55% for Ontario, 31% for British Columbia, and 38% for Nova Scotia. Also, increased nursing costs in the last month were almost always associated with lower total costs in comparison with the reference. For example, cost savings per person-block ranged from 376 (>10 nursing hours) to 1,124 (>4 to 6 nursing hours) in British Columbia. Conclusions: In the last month of life, increased palliative nursing costs (compared with costs for >0 to 1 hour of nursing in the block) were associated with lower relative hospital costs and a lower total cost in a subsequent block. Our research suggests a cost-savings potential associated with increased community-based palliative nursing
Compensation of decreased ion energy by increased hydrogen dilution in plasma deposition of thin film silicon solar cells at low substrate temperatures
Architectonics of GABAergic inhibitory network in the sensorimotor area of the rat neocortex in the early postnatal period under normal conditions and after acute perinatal hypoxia
Understanding children’s emotional processes and behavioral strategies in the context of marital conflict
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Leveraging the NEON Airborne Observation Platform for socio-environmental systems research
During the 21st century, human–environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Human–environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi-resolution information for analysis. Climate change, land-use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high-density, and high-resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) for Socio-Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross-site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio-environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data. © 2021 The Authors.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]