5,733 research outputs found

    Thalamic inflammation after brain trauma is associated with thalamo-cortical white matter damage

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    Background Traumatic brain injury can trigger chronic neuroinflammation, which may predispose to neurodegeneration. Animal models and human pathological studies demonstrate persistent inflammation in the thalamus associated with axonal injury, but this relationship has never been shown in vivo. Findings Using [11C]-PK11195 positron emission tomography, a marker of microglial activation, we previously demonstrated thalamic inflammation up to 17 years after traumatic brain injury. Here, we use diffusion MRI to estimate axonal injury and show that thalamic inflammation is correlated with thalamo-cortical tract damage. Conclusions These findings support a link between axonal damage and persistent inflammation after brain injury

    An early and late peak in microglial activation in Alzheimer's disease trajectory

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    search input Search An early and late peak in microglial activation in Alzheimer’s disease trajectory Zhen Fan, David J. Brooks, Aren Okello, Paul Edison Brain, Volume 140, Issue 3, March 2017, Pages 792–803, https://doi.org/10.1093/brain/aww349 Published: 24 January 2017 Article history Received: 20 June 2016 Revision received: 31 October 2016 Accepted: 18 November 2016 Published: 24 January 2017 pdfPDF Split View Cite Permissions Icon Permissions Share Abstract Amyloid-β deposition, neuroinflammation and tau tangle formation all play a significant role in Alzheimer’s disease. We hypothesized that there is microglial activation early on in Alzheimer’s disease trajectory, where in the initial phase, microglia may be trying to repair the damage, while later on in the disease these microglia could be ineffective and produce proinflammatory cytokines leading to progressive neuronal damage. In this longitudinal study, we have evaluated the temporal profile of microglial activation and its relationship between fibrillar amyloid load at baseline and follow-up in subjects with mild cognitive impairment, and this was compared with subjects with Alzheimer’s disease. Thirty subjects (eight mild cognitive impairment, eight Alzheimer’s disease and 14 controls) aged between 54 and 77 years underwent 11C-(R)PK11195, 11C-PIB positron emission tomography and magnetic resonance imaging scans. Patients were followed-up after 14 ± 4 months. Region of interest and Statistical Parametric Mapping analysis were used to determine longitudinal alterations. Single subject analysis was performed to evaluate the individualized pathological changes over time. Correlations between levels of microglial activation and amyloid deposition at a voxel level were assessed using Biological Parametric Mapping. We demonstrated that both baseline and follow-up microglial activation in the mild cognitive impairment cohort compared to controls were increased by 41% and 21%, respectively. There was a longitudinal reduction of 18% in microglial activation in mild cognitive impairment cohort over 14 months, which was associated with a mild elevation in fibrillar amyloid load. Cortical clusters of microglial activation and amyloid deposition spatially overlapped in the subjects with mild cognitive impairment. Baseline microglial activation was increased by 36% in Alzheimer’s disease subjects compared with controls. Longitudinally, Alzheimer’s disease subjects showed an increase in microglial activation. In conclusion, this is one of the first longitudinal positron emission tomography studies evaluating longitudinal changes in microglial activation in mild cognitive impairment and Alzheimer’s disease subjects. We found there is an initial longitudinal reduction in microglial activation in subjects with mild cognitive impairment, while subjects with Alzheimer’s disease showed an increase in microglial activation. This could reflect that activated microglia in mild cognitive impairment initially may adopt a protective activation phenotype, which later change to a cidal pro-inflammatory phenotype as disease progresses and amyloid clearance fails. Thus, we speculate that there might be two peaks of microglial activation in the Alzheimer’s disease trajectory; an early protective peak and a later pro-inflammatory peak. If so, anti-microglial agents targeting the pro-inflammatory phenotype would be most beneficial in the later stages of the disease

    A proposal for a comprehensive grading of Parkinson's disease severity combining motor and non-motor assessments: meeting an unmet need.

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    Non-motor symptoms are present in Parkinson's disease (PD) and a key determinant of quality of life. The Non-motor Symptoms Scale (NMSS) is a validated scale that allows quantifying frequency and severity (burden) of NMS. We report a proposal for using NMSS scores to determine levels of NMS burden (NMSB) and to complete PD patient classification

    Motion-correlated flow distortion and wave-induced biases in air-sea flux measurements from ships

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    Direct measurements of the turbulent air–sea fluxes of momentum, heat, moisture and gases are often made using sensors mounted on ships. Ship-based turbulent wind measurements are corrected for platform motion using well established techniques, but biases at scales associated with wave and platform motion are often still apparent in the flux measurements. It has been uncertain whether this signal is due to time-varying distortion of the air flow over the platform or to wind–wave interactions impacting the turbulence. Methods for removing such motion-scale biases from scalar measurements have previously been published but their application to momentum flux measurements remains controversial. Here we show that the measured motion-scale bias has a dependence on the horizontal ship velocity and that a correction for it reduces the dependence of the measured momentum flux on the orientation of the ship to the wind. We conclude that the bias is due to experimental error and that time-varying motion-dependent flow distortion is the likely source

    Genetic variation within GRIN2B in adolescents with alcohol use disorder may be associated with larger left posterior cingulate cortex volume.

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    OBJECTIVE: Brain structure differences and adolescent alcohol dependence both show substantial heritability. However, exactly which genes are responsible for brain volume variation in adolescents with substance abuse disorders are currently unknown. The aim of this investigation was to determine whether genetic variants previously implicated in psychiatric disorders are associated with variation in brain volume in adolescents with alcohol use disorder (AUD). METHODS: The cohort consisted of 58 adolescents with DSM-IV AUD and 58 age and gender-matched controls of mixed ancestry ethnicity. An Illumina Infinium iSelect custom 6000 bead chip was used to genotype 5348 single nucleotide polymorphisms (SNPs) in 378 candidate genes. Magnetic resonance images were acquired and volumes of global and regional structures were estimated using voxel-based morphometry. To determine whether any of the genetic variants were associated with brain volume, association analysis was conducted using linear regression in Plink. RESULTS: From the exploratory analysis, the GRIN2B SNP rs219927 was associated with brain volume in the left posterior cingulate cortex (p<0.05), whereby having a G-allele was associated with a bigger volume. CONCLUSION: The GRIN2B gene is involved in glutamatergic signalling and may be associated with developmental differences in AUD in brain regions such as the posterior cingulate cortex. Such differences may play a role in risk for AUD, and deserve more detailed investigation

    A Microsoft-Excel-based tool for running and critically appraising network meta-analyses--an overview and application of NetMetaXL.

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    This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.BACKGROUND: The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves. METHODS: We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL's interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation. RESULTS: We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software. CONCLUSIONS: Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows for more efficient and transparent critical appraisal of network meta-analyses, enhanced standardization of reporting, and integration with health economic evaluations which are frequently Excel-based.CC is a recipient of a Vanier Canada Graduate Scholarship from the Canadian Institutes of Health Research (funding reference number—CGV 121171) and is a trainee on the Canadian Institutes of Health Research Drug Safety and Effectiveness Network team grant (funding reference number—116573). BH is funded by a New Investigator award from the Canadian Institutes of Health Research and the Drug Safety and Effectiveness Network. This research was partly supported by funding from CADTH as part of a project to develop Excel-based tools to support the conduct of health technology assessments. This research was also supported by Cornerstone Research Group
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