Anonymised results from the 2020 UoE Research Culture Survey

Quantitative results of 2020 University of Edinburgh Research Culture Survey, based on Wellcome Trust 2019 Research Culture Survey. Line listing of 1491 responses from research academic, postgraduate research students and research professional staff.Macleod, Malcolm. (2021). Anonymised results from the 2020 UoE Research Culture Survey, 2020 [dataset]. Edinburgh Research Improvement Project. https://doi.org/10.7488/ds/2990

Proteomic analysis to identify the pathways and processes affected by altered levels of Sideroflexin3 (SFXN3) in the synapse.

Proteomic data from TMT based analysis of synapses biochemically isolated from Sfxn3-KO mice (http://www.mousephenotype.org/data/genes/MGI:2137679). See attached word/.txt description for further information. Briefly - Synapses are a primary pathological target in neurodegenerative diseases. Identifying therapeutic targets at the synapse could delay progression of numerous conditions. The mitochondrial protein SFXN3 is a neuronally-enriched protein expressed in synaptic terminals and regulated by key synaptic proteins, including alpha-synuclein (previously reported in Amorim et al., 2017 [PMID:28049726] and Graham et al., 2017 [PMID: 29078798]). Applying high-resolution proteomics to synapses biochemically isolated from Sfxn3-KO mice (http://www.mousephenotype.org/data/genes/MGI:2137679), we sought to identify what the molecular consequences of altered SFXN3 expression are in vivo. Analysis of the data contained within this submission suggest that Sfxn3 regulates proteins and pathways associated with neurodegeneration and cell death (including CSP alpha and caspase-3), as well as cascades altered in other neurological conditions (including Parkinson’s disease and Alzheimer’s disease).Wishart, Thomas. (2021). Proteomic analysis to identify the pathways and processes affected by altered levels of Sideroflexin3 (SFXN3) in the synapse., [dataset]. University of Edinburgh. Roslin Institute. https://doi.org/10.7488/ds/3068

Proteomic profiling of primate synapses during normal healthy ageing

Normal mammalian brain ageing is characterised by the selective loss of discrete populations of dendritic spines and synapses, particularly affecting neuroanatomical regions such as the hippocampus. Although previous investigations have quantified this morphologically, the molecular pathways orchestrating preferential synaptic vulnerability remain to be elucidated. Using quantitative proteomics and healthy rhesus macaque and human patient brain regional tissues, we have profiled the temporal expression of the synaptic proteome throughout the adult lifespan in differentially vulnerable brain regions. Comparative profiling of hippocampal (age-vulnerable) and occipital cortex (age-resistant) synapses revealed discrete and dynamic alterations in the synaptic proteome, which appear unequivocally conserved between species. The generation of these unique and important datasets will aid in delineating the molecular mechanisms underpinning primate brain ageing, in addition to deciphering the regulatory biochemical cascades governing neurodegenerative disease pathogenesis.Wishart, Thomas. (2018). Proteomic profiling of primate synapses during normal healthy ageing, [dataset]. University of Edinburgh. College of Medicine & Veterinary Medicine. https://doi.org/10.7488/ds/243

Real-world Independent Testing of e-ASPECTS Software (RITeS): Checklist for Statistical Analysis Plan

Statistical Analysis Plan reporting checklist as per: https://www.equator-network.org/reporting-guidelines/guidelines-for-the-content-of-statistical-analysis-plans-in-clinical-trials/ . ## Background - RITeS project ## The Real-world Independent Testing of e-ASPECTS Software (RITeS) project will test commercially available AI software that claims to provide automated assessment of CT brain imaging for patients with acute stroke. RITeS will independently compare the results of e-ASPECTS and e-CTA software against the current gold-standard, expert human interpretation using a large representative sample of CT imaging collected in several clinical trials of acute stroke.Mair, Grant. (2020). Real-world Independent Testing of e-ASPECTS Software (RITeS): Checklist for Statistical Analysis Plan, [text]. University of Edinburgh. College of Medicine & Veterinary Medicine. https://doi.org/10.7488/ds/2803

Structural MRI: from Slices to Faces and the effect of defacing

Image (3 formats, png original, psd and jpg size and resolution interpolated and colour edited) of a reconstructed face from a series of MRI slices, along with various 'defacing' for pseudonymization. MRI data were obtained at the Brain Research Imaging Centre, showing the authors' face. Face renders were made with MRICroGL (http://www.cabiatl.com/mricrogl/), and defaced version computed using mask_face (https://nrg.wustl.edu/software/face-masking/usage/), mri_deface from the freesurfer suite (https://surfer.nmr.mgh.harvard.edu/fswiki/mri_deface) and SPM12 (https://www.fil.ion.ucl.ac.uk/spm/software/spm12/).Pernet, Cyril. (2020). Structural MRI: from Slices to Faces and the effect of defacing, [image]. University of Edinburgh, Center for Clinical Brain Sciences & Edinburgh Imaging. https://doi.org/10.7488/ds/2877

Dyslexia GWAS Summary Statistics for top 10K SNPs

Reading and writing are crucial life skills but roughly 1 in 10 children are affected by dyslexia, which can persist into adulthood. Family studies of dyslexia suggest heritability up to 70%, yet few convincing genetic markers have been found. Our genome-wide association study of 51,800 adults self-reporting a dyslexia diagnosis and 1,087,070 controls identified 42 independent significant loci: 15 in genes linked to cognitive ability/educational attainment; 27 novel and potentially more specific to dyslexia. Twenty-three loci (13 novel) were validated in independent cohorts of Chinese and European ancestry. Genetic aetiology of dyslexia was similar between sexes, and genetic covariance with many traits was found, including ambidexterity, but not neuroanatomical measures of language-related circuitry. Dyslexia polygenic scores explained up to 6% of variance in reading traits, and might in future contribute to earlier identification and remediation of dyslexia.Fontanillas, Pierre; Luciano, Michelle. (2022). Dyslexia GWAS Summary Statistics for top 10K SNPs, [dataset]. 23andMe, Inc. https://doi.org/10.7488/ds/3465

Best practice for fMRI displays, plots and colour maps

Sets of illustrations for best practices in displaying tomographic imaging data - applied here to functional MRI. Images either shows different ways to present the data or show various colour maps with luminance correction.Pernet, Cyril; Madan, Christopher. (2019). Best practice for fMRI displays, plots and colour maps, [image]. University of Edinburgh, Centre for Clinical Brain Sciences & Edinburgh Imaging. https://doi.org/10.7488/ds/2516

Matlab codes for "Amplitude- and Fluctuation-based Dispersion Entropy"

Dispersion entropy (DispEn) is a recently introduced entropy metric to quantify the uncertainty of time series. It is fast and, so far, it has demonstrated very good performance in the characterisation of time series. It includes a mapping step, but the effect of different mappings has not been studied yet. Here, we investigate the effect of linear and nonlinear mapping approaches in DispEn. We also inspect the sensitivity of different parameters of DispEn to noise. Moreover, we develop fluctuation-based DispEn (FDispEn) as a measure to deal with only the fluctuations of time series. Furthermore, the original and fluctuation-based forbidden dispersion patterns are introduced to discriminate deterministic from stochastic time series. Finally, we compare the performance of DispEn, FDispEn, permutation entropy, sample entropy, and Lempel–Ziv complexity on two physiological datasets. The results show that DispEn is the most consistent technique to distinguish various dynamics of the biomedical signals. Due to their advantages over existing entropy methods, DispEn and FDispEn are expected to be broadly used for the characterization of a wide variety of real-world time series. The Matlab codes used in this paper are freely available here.Azami, Hamed; Escudero, Javier. (2018). Matlab codes for "Amplitude- and Fluctuation-based Dispersion Entropy", [dataset]. University of Edinburgh. School of Engineering. Institute for Digital Communications. http://dx.doi.org/10.7488/ds/2326

International Stroke Trial-1 (version 2)

The International Stroke Trial (IST) was one the biggest randomised trials in acute stroke. Methods: Available data on variables assessed at randomisation, at the early outcome point (14-days after randomisation or prior discharge) and at 6-months were extracted and made publicly available. Results and Conclusions: The IST provides an excellent source of primary data easy-to-use for sample size calculations and preliminary analysis necessary for planning a good quality trial.Sandercock, Peter; Niewada, Maciej; Czlonkowska, Anna. (2011). International Stroke Trial database (version 2), [dataset]. University of Edinburgh. Department of Clinical Neurosciences. http://dx.doi.org/10.7488/ds/104

Project Soothe: Images nos. 1 to 656

Use of these images for purposes *other* than research or therapy is *not* permitted.This dataset includes 621 images donated to Project Soothe by volunteers through the Project Soothe website, numbered #1 to #656 except for a small number which were excluded for the reasons listed in the file "Note_images_removed_and_privacy.txt". For a more detailed overview of the research please see "Wilson, A; Schwannauer, M; McLaughlin, A; Ashworth, F; Chan, S. 2017, 'Vividness of positive mental imagery predicts positive emotional response to visually-presented Project Soothe pictures' British Journal of Psychology, pp. 1-18. DOI: 10.1111/bjop.12267".Chan, Stella. (2018). Project Soothe: Images nos. 1 to 656, [image]. University of Edinburgh. School of Health in Social Science. http://dx.doi.org/10.7488/ds/235