Genotype moderates the impact of food additives on hyperactive behavior in children

Introduction: The claim of a relationship between artificial food color and additive (AFCs) intake and behavior is highly contentious. We have shown in a previous population-based trial with 3yo children adverse effects of food additives on parentally-rated hyperactive behaviour (Bateman et al, 2004). The possible role of genetic polymorphisms in moderating this adverse effect has not been previously examined. Methods A randomised, double blind, placebo-controlled, within subject crossover food challenge was used for 144, 8 to 9 year old children and 153, 3 year old children. Following baseline assessment children were placed on a diet eliminating food additives and a benzoate preservative for 6 weeks during which time they were challenged for weekly periods with either a placebo mix or a drink containing sodium benzoate (45mg daily) and one of two mixes of AFCs.: Results: The T939C and Thr105Ile polymorphisms of the histamine N-methyltransferase gene (HNMT) moderated the adverse effect s of AFCs but the polymorphisms in catecholamine genes COMT Val108Met and ADRA2A C1291G did not. These findings point to a possible role for histamine in mediating the effects of food additives and help to explain why there has been inconsistency between previous studies. Conclusions: Genes influencing a range of neurotransmitter systems and their interplay with environmental factors, such as diet, need to be examined to understand genetic influences on hyperactivity.<br/

An Immersive Motion Sketch Pad

GROCS: GRant Opportunities [collaborative spaces], a Digital Media Commons program to fund student research on the use of rich media in collaborative learning.http://deepblue.lib.umich.edu/bitstream/2027.42/57302/1/Cave_Capture proposal.pd

Granton Coastal Park: a high-level climate adaptation and environmental cost benefit assessment

Final report for City of Edinburgh Council (CEC), July 2022. This document has been prepared with the CEC with funding from UKRI/NERC (NE/R009236/1, led by Naylor), with data inputs (and/or modelling outputs) and support from staff in the City of Edinburgh, Atkins, SEPA (Kirsten Thorburn, Paul Lewis), the Dynamic Coast 2 project and the Edinburgh Shoreline project team who helped co-design the aims of this report. This report was reviewed by several staff in different levels of Scottish Government and/or organisations (e.g., Adaptation Scotland) tasked with the delivery of key aspects of climate change delivery for Scotland. These included: Dr Alistair Rennie, Elise Schneider, Linda Hamilton, Sat Patel, Anna Beswick and Fiona Macleod

MAGIQ at the W. M. Keck Observatory: initial deployment of a new acquisition, guiding, and image quality monitoring system

The W. M. Keck Observatory has completed the development and initial deployment of MAGIQ, the Multi-function Acquisition, Guiding and Image Quality monitoring system. MAGIQ is an integrated system for acquisition, guiding and image quality measurement for the Keck telescopes. This system replaces the acquisition and guiding hardware and software for existing instruments at the Observatory and is now the standard for visible wavelength band acquisition cameras for future instrumentation. In this paper we report on the final design and implementation of this new system, which includes three major components: a visible wavelength band acquisition camera, image quality measurement capability, and software for acquisition, guiding and image quality monitoring. The overall performance is described, as well as the details of our approach to integrating low order wavefront sensing capability in order to provide closed loop control of telescope focus

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation:A Multi-center, Multi-vendor, and Multi-disease Study

Background: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton (1H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acquisition parameters.Purpose: Develop a generalizable CNN for lung segmentation in 1H-MRI, robust to pathology, acquisition protocol, vendor, and center.Study type: Retrospective.Population: A total of 809 1H-MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6–85); 42% females) and 31 healthy participants (median age (range): 34 (23–76); 34% females) that were split into training (593 scans (74%); 157 participants (55%)), testing (50 scans (6%); 50 participants (17%)) and external validation (164 scans (20%); 82 participants (28%)) sets.Field Strength/Sequence: 1.5-T and 3-T/3D spoiled-gradient recalled and ultrashort echo-time 1H-MRI.Assessment: 2D and 3D CNNs, trained on single-center, multi-sequence data, and the conventional spatial fuzzy c-means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance.Statistical Tests: Kruskal–Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland–Altman analyses assessed agreement with manually derived lung volumes. A P value of &lt;0.05 was considered statistically significant.Results: The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880–0.987), Average HD of 1.63 mm (0.65–5.45) and XOR of 0.079 (0.025–0.240) on the testing set and a DSC of 0.973 (0.866–0.987), Average HD of 1.11 mm (0.47–8.13) and XOR of 0.054 (0.026–0.255) on external validation data.Data Conclusion: The 3D CNN generated accurate 1H-MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center.Evidence Level: 4.Technical Efficacy: Stage 1.</p

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

MAGIQ at the W. M. Keck Observatory: initial deployment of a new acquisition, guiding, and image quality monitoring system

The W. M. Keck Observatory has completed the development and initial deployment of MAGIQ, the Multi-function Acquisition, Guiding and Image Quality monitoring system. MAGIQ is an integrated system for acquisition, guiding and image quality measurement for the Keck telescopes. This system replaces the acquisition and guiding hardware and software for existing instruments at the Observatory and is now the standard for visible wavelength band acquisition cameras for future instrumentation. In this paper we report on the final design and implementation of this new system, which includes three major components: a visible wavelength band acquisition camera, image quality measurement capability, and software for acquisition, guiding and image quality monitoring. The overall performance is described, as well as the details of our approach to integrating low order wavefront sensing capability in order to provide closed loop control of telescope focus

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy