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11,745 results for “Disorder”
Data for Project 'Feasibility, Usability and Acceptance of a Newly Developed Exergame-Based Training Concept for Older Adults with Mild Neurocognitive Disorder - A Pilot Randomized Controlled Trial'
<p>Data for Project 'Feasibility, Usability and Acceptance of a Newly Developed Exergame-Based Training Concept for Older Adults with Mild Neurocognitive Disorder - A Pilot Randomized Controlled Trial' (trial registered at clinicaltrials.gov (<a href="https://clinicaltrials.gov/ct2/show/NCT04996654">NCT04996654</a>; date of registration: 11 July 2021), consisting of:</p> <p>(1) the original and complete data set for all primary outcomes ('Data_Primary-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(2) the original and complete data set for all secondary outcomes ('Data_Secondary-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(3) the original and complete data set for all other outcomes (i.e. baseline factors (demographic data, type of usual care interventions) and training heart rate; 'Data_Other-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(4) folder including the raw and processed heart rate variability (HRV) and electroencephalography (EEG) data for all participants and measurements (HRV-and-EEG_raw-and-processed-data.zip);</p> <p>(5) a corresponding README file including (a) general information, (b) data and file overview, (c) sharing and access information, (d) methodological information, and (e) data-specific information.</p>
Spectral response of disorder-free localized lattice gauge theories
<p>Raw data for all figures in the manuscript "Spectral response of disorder-free localized lattice gauge theories"</p>
Extreme dynamics of a small molecule in its bound state with an intrinsically disordered protein
<p>These data support the manuscript entitled "Extreme dynamics of a small molecule in its bound state with an intrinsically disordered protein" by Heller, Shukla, Figueiredo, and Hansen.</p><p>This data should be used with the code provided on GitHub at https://github.com/hansenlab-ucl/R2_IDP_small_mol. Once downloaded, this directory should be extracted using the following command:</p><p> tar -xzvf Data.tar.gz</p><p>The directory should be saved with the name 'Data' placed in the same directory as the GitHub README.md file.</p><p><strong>This dataset contains: </strong><br><i>Nuclear Magnetic Resonance (NMR) spectroscopy data files (.ft2 format) including: </i></p><p>* 1H 1D ligand-detected chemical shift titration of 5-fluoroindole (50 uM) with increasing concentrations of the protein, non-structural protein 5A, domains 2 and 3 (NS5A-D2D3), in 1H_1D_ft2_data/</p><p>* 1H pseudo-2D Diffusion Ordered SpectroscopY (DOSY) data of 5-fluoroindole (50 uM) with and without NS5A-D2D3 (75 uM) in 1H_DOSY_data/</p><p>* 1H-15N Heteronuclear Single Quantum Coherence (HSQC) measurements of NS5A-D2D3 (40 uM) in the absence and presence of 5-fluoroindole (160 and 320 uM) in 1H_15N_HSQC_ft2_and_metadata/</p><p>* 19F 1D ligand-detected chemical shift titration of 5-fluoroindole (50 uM) with increasing concentrations of NS5A-D2D3 in 19F_1D_ft2_data/</p><p>* 19F pseudo-2D ligand-detected longitudinal (spin-lattice, R1,eff) relaxation titration data of 5-fluoroindole (50 uM) with increasing concentrations of NS5A-D2D3 in 19F_R1eff_ft2_data/</p><p>* 19F pseudo-2D ligand-detected longitudinal (spin-spin, R2,eff) relaxation titration data of 5-fluoroindole (50 uM) with increasing concentrations of NS5A-D2D3 in 19F_R2eff_ft2_data/</p><p><i>Circular Dichroism (CD) data files (.txt format) including: </i></p><p>* CD measurements of NS5A-D2D3 at increasing concentrations in CD_data/no_molecule/</p><p>* CD measurements of NS5A-D2D3 with and without the small molecule, 5-fluoroindole CD_data/with_molecule/</p><p><i>Metadata </i></p><p>* Metadata from the Biological Magnetic Resonance Data Bank (https://bmrb.io/) used to determine scaling factors for the calculation of chemical shift perturbations in 1H_15N_HSQC_ft2_and_metadata/</p>
DATASET: Protein Binding Leads to Reduced Stability and Solvated Disorder in the Polystyrene Nanoparticle Corona
<p>This dataset contains the DLS, CD, fluorescence, ITC, TEM, and ANS raw data used for the manuscript.</p>
Dataset for "Structural diversity with varying disorder enables the multicolored display in the longhorn beetle Sulawesiella rafaelae"
<p><strong>Dataset for</strong> "Structural diversity with varying disorder enables the multicolored display in the longhorn beetle <em>Sulawesiella rafaelae</em>"</p> <p>The data is arranged into a .zip folder, containing the following files (.txt, .tif, jpg files). This data and the descriptions below should be read in conjunction with the manuscript and “Supporting Info”, both of which may be found on the <em>iScience</em> homepage.</p> <p>Doi: https://doi.org/10.1016/j.isci.2020.101339</p>
data for "A disordered encounter complex is central to the yeast Abp1p SH3 domain binding pathway"
<p>Protein-protein interactions are involved in a wide range of cellular processes. These interactions often involve intrinsically disordered proteins (IDPs) and protein binding domains. However, the details of IDP binding pathways are hard to characterize using experimental approaches, which can rarely capture intermediate states present at low populations. SH3 domains are common protein interaction domains that typically bind proline-rich disordered segments and are involved in cell signaling, regulation, and assembly. We hypothesized, given the flexibility of SH3 binding peptides, that their binding pathways include multiple steps important for function. Molecular dynamics simulations were used to characterize the steps of binding between the yeast Abp1p SH3 domain (AbpSH3) and a proline-rich IDP, ArkA. Before binding, the N-terminal segment 1 of ArkA is pre-structured and adopts a polyproline II helix, while segment 2 of ArkA (C-terminal) adopts a 310 helix, but is far less structured than segment 1. As segment 2 interacts with AbpSH3, it becomes more structured, but retains flexibility even in the fully engaged state. Binding simulations reveal that ArkA enters a flexible encounter complex before forming the fully engaged bound complex. In the encounter complex, transient nonspecific hydrophobic and long- range electrostatic contacts form between ArkA and the binding surface of SH3. The encounter complex ensemble includes conformations with segment 1 in both the forward and reverse orientation, suggesting that segment 2 may play a role in stabilizing the correct binding orientation. While the encounter complex forms quickly, the slow step of binding is the transition from the disordered encounter ensemble to the fully engaged state. In this transition, ArkA makes specific contacts with AbpSH3 and buries more hydrophobic surface. Simulating the binding between ApbSH3 and ArkA provides insight into the role of encounter complex intermediates and nonnative hydrophobic interactions for other SH3 domains and IDPs in general.</p>
European Study on Risk Factors for Violence in Mental Disorder and Forensic Care: a multicentre project. The EU-Viormed Dataset
<p>The aims of this project, through a series of interlinked work packages, designed by researchers and practicing clinicians, and lead by an experienced management team, is to explore and map these differences, test new risk assessment tools and identify and share best practice where it exists. It aims are fourfold. Firstly to describe forensic psychiatry services as they exist today in 2017 across the European Union. Secondly to identify risk factors for violence in a unique international forensic sample and thirdly to test for the very first time in a related EU sample two contrasting methods of violence risk assessment. Finally it explored what works for these often marginalised patients, their families and their carers, at an operational, clinical and ethical level.<br> These aims were achieved through two studies designs:<br> Study 1: case-control retrospective design in which forensic patients with Schizophrenia<br> Spectrum Disorders (SSDs) who have a history of interpersonal violence and live in forensic<br> units will be compared to non-violent patients with SSDs living in the community.<br> Study 2: prospective cohort study, with 6 and 12 month follow-up, to test the predictive validity<br> of the leading structured professional clinical judgement guide for violence prediction, the<br> HCR-20v3, the Forensic Psychiatry and Violence Tool (FoVOx) and the Mental Illness and<br> Suicide Tool (OXMIS, https://oxrisk.com/)</p>
Reproduction package for "Recombination of localized quasiparticles in disordered superconductors"
<p>This is a reproduction package to the paper "Recombination of localized quasiparticles in disordered superconductors". It contains all data and code to reproduce the figures in this paper.</p>
III PhasAGE International Conference - PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins - Lecture
<p>The III PhasAGE International Conference "Multiscale understanding of protein aggregation and biomolecular condensates in aging and disease" brought together members of the PhasAGE consortium as well as outstanding international speakers from multidisciplinary fields dedicated to unraveling the intricacies of protein aggregation and biomolecular condensates in the context of aging and disease. For details on the conference program please see https://phasage.eu/iii-phasage-international-conference/. </p>
The Mexican dataset of an rTMS clinical trial on cocaine use disorder patients: SUDMEX TMS
<p>The SUDMEX_TMS dataset is the result of a longitudinal clinical trial of cocaine use disorder patients that were treated with rTMS at 5-Hz on the left dorsolateral prefrontal cortex (lDLPFC) for a 2 week double-blind acute phase and an open-label maintenance phase that included clinical, cognitive and MRI data acquisition. The design was a double-blind placebo-controlled randomized controlled trial with parallel groups (acute phase). The study was done at the National Institute of Psychiatry .</p> <p>Each patient had more than one clinical and MRI session or time point from baseline (T0), 2 weeks (T1), 3 months (T2), 6 months (T3) and some patients had 12 months (T4). The T14 time point was only for patients in the Sham group who decided to continue the clinical trial with open-label rTMS. The T14 refers to 2 weeks after T1 (4 weeks after T0).</p> <p>The MRI sequences were: 1) T1-weighted, 2) rsfMRI 10 min, 3) HARDI-DWI multishell (next release).</p> <p>The data set is curated and organized by test and item for each experimental phase and also has a dictionary to define the variables measured.</p> <p> </p> <p>If you require more information about data or scales, please contact us. </p> <p><em>LANIREM (</em><em>National MRI Laboratory)</em><em>, Institute of Neurobiology, </em></p> <p><em>Universidad Nacional Autónoma de México (UNAM), </em><em>Querétaro, México.</em></p> <p><strong>Diego Angeles Valdez, M. Sc. </strong></p> <ul> <li>diego.ang.val@gmail.com</li> <li>diego.ang.val@inb.unam.mx</li> </ul> <p><br> <strong>Eduardo A. Garza-Villarreal, M.D., Ph.D.</strong></p> <ul> <li>egarza@gmail.com</li> <li>egarza@comunidad.unam.mx</li> </ul>
16S rRNA Sequencing Data of Fecal Microbiota in an Italian Cohort of Patients with CDKL5 Deficiency Disorder
<h3>Summary of the study </h3> <p>CDKL5 deficiency disorder (CDD) is a neurodevelopmental condition characterized by global developmental delay, early-onset seizures, intellectual disability, visual and motor impairments, distinct from Rett Syndrome (RTT) due to the absence of a clear regression period. Gastrointestinal (GI) disturbances and signs of subclinical immune dysregulation are common in CDD patients, yet the underlying causes are unknown. Recent studies hint at a possible link between neurological disorders and gut microbiota, an unexplored area in CDD. In this groundbreaking study, we examined fecal microbiota in CDD patients and their healthy relatives, revealing differences in bacterial diversity and composition. We further investigated microbiota changes based on various factors, including the severity of GI issues, seizure frequency, sleep disorders, food intake type, neuro-behavioral features (assessed through the RTT Behaviour Questionnaire – RSBQ), and ambulation capacity. </p> <p>Our findings suggest a potential connection between CDD, microbiota, and symptom severity. This study represents the first exploration of the gut-microbiota-brain axis in CDD patients, contributing to the growing body of research on the role of gut microbiota in neurodevelopmental disorders. It opens doors to potential interventions targeting intestinal microbes to enhance the well-being of individuals with CDD.</p> <h3>Mehods</h3> <p>The Dataset represent the raw data (.fastq) obtained from the sequencing of the fecal samples from 17 Italian Patients with CDD, and 17 Healthy Relatives (i.e. siblings or mother), collected at a single time-point.</p> <p>Samples from Patients affected by CDD are called CDD, samples from Healthy Relatives are called HC-CDD (i.e. healthy controls of patients affected by CDD). For details about the sample names see the “Explanation Table”.</p> <p>Bacterial DNA was extracted from fecal samples using the QIAmp Powerfexal DNA Kit (Qiagen, Germany) following the manufacturer's protocol. The 16S rRNA sequencing and analysis was performed by a service offered by Zymo Research (Germany).</p> <p><em>Targeted Library Preparation</em>: The DNA samples were prepared for targeted sequencing with the Quick-16S™ NGS Library Prep Kit (Zymo Research). The primer sets used were Quick-16S™ Primer Set V3-V4 (Zymo Research). The sequencing library was prepared using an innovative library preparation process in which PCR reactions were performed in real-time PCR machines to control cycles and therefore limit PCR chimera formation. The final PCR products were quantified with qPCR fluorescence readings and pooled together based on equal molarity. The final pooled library was cleaned up with the Select-a-Size DNA Clean & Concentrator™, then quantified with TapeStation® (Agilent Technologies, Santa Clara, CA) and Qubit® (Thermo Fisher Scientific, Waltham, WA). </p> <p><em>Sequencing:</em> The final library was sequenced on Illumina® MiSeq™ with a v3 reagent kit (600 cycles). </p>
A Dataset for Engagement Prediction in Neuromotor Disorder Patients during Rehabilitation
<p>This dataset is related to the work titled "Artificial Intelligence Tools for Engagement Prediction in Neuromotor Disorder Patients undergoing Robot-Assisted Rehabilitation," whose aim is to methodologically explore the performance of artificial intelligence algorithms applied to structured datasets made of heart rate variability (HRV) and electrodermal activity (EDA) features to predict the level of patient engagement during robot-assisted gait rehabilitation (RAGR).</p> <p>It is composed of three Excel files related to the 3-minute windows data augmentation scenario applied to the bimodal dataset made of 14 HRV and 19 EDA features. Specifically:</p> <ul> <li>ds_bimodal_win_3min.xlsx contains the features extracted from 3-minute windows of HRV and EDA signals, recorded during the RAGR activity, and normalized with respect to the reference (baseline) signals. Features are not z-scored.</li> <li>labels_self_win_3min contains one single column with, for each row, the label related to the self-perceived engagement classification target. </li> <li>labels_therapist_win_3min contains one single column with, for each row, the label related to the therapist-perceived engagement classification target.</li> </ul> <p>The coding of classes for both classification targets is:</p> <ul> <li>0: Underchallenged</li> <li>1: Minimally Challenged</li> <li>2: Challenged</li> </ul>
Small molecules targeting the structural dynamics of AR-V7 partially disordered protein using deep learning and physics based models.
<p>Partially disordered proteins can contain both stable and unstable secondary structure segments and are involved in various (mis)functions in the cell. The extensive conformational dynamics of partially disordered proteins scaling with extent of disorder and length of the protein hampers the efficiency of traditional experimental and in-silico structure-based drug discovery approaches. Therefore new efficient paradigms in drug discovery taking into account conformational ensembles of proteins need to emerge. In this study, using as a test case the AR-V7 transcription factor splicing variant related to prostate cancer, we present an automated methodology that can accelerate the screening of small molecule binders targeting partially disordered proteins. By swiftly identifying the conformational ensemble of AR-V7, and reducing the dimension of binding-sites by a factor of 90 by applying appropriate physicochemical filters, we combine physics based molecular docking and multi-objective classification machine learning models that speed up the screening of thousands of compounds targeting AR-V7 multiple binding sites. Our method not only identifies previously known binding sites of AR-V7, but also discovers new ones, as well as increases the multi-binding site hit-rate of small molecules by a factor of 17 compared to naive physics-based molecular docking. </p>
Work-related burden of diseases and disorders
<p><span>The burden of the work-related diseases is a major global health challenge. This data provides the global, regional and country level estimates on the work-related burden of occupational diseases and accidents for the year 2019 in terms of deaths, disability adjusted life years (DALYs) and economic loss as a percentage of total gross domestic product (GDP). </span></p> <p><span>The data contains calculated estimates based on the employment figures, mortality rates, occupational injuries, accidents, self-reported occupational illnesses and injuries from electronic data sources of international organizations, institutions, and public websites. Risk ratios (RR) and population attributable fractions (PAF) for the risk factors outcome pairs were derived from literature. Estimated mortality and DALYs for a group of seven major diseases covering 120 risk-outcome pairs attributable to work are calculated at global, WHO regions and at country level. The details of the methodology of the data have been published already (<a href="https://www.sjweh.fi/article/4132"><span>https://www.sjweh.fi/article/4132</span></a>).</span></p> <p><span>In general, the method is based on the number of problems identified at work: injuries, illnesses, and disorders including fatal or no-fatal cases. This was implemented by calculating the deaths, Years of Life Lost (YLL), Years Lived with Disability (YLD) and their combination Disability Adjusted Life Years (DALY) based on primarily ILO numbers as adjusted by the Institute of Health Metrics and Evaluation (IHME) Global Burden of Disease and Injury (GBD) process outcomes. While there are existing estimates updated annually by the GBD process, latest for the year 2019, these do cover only a selected group of occupational risks. Therefore, the GBD 2019 outcomes would not be comparable to ILO Estimates and – if directly used – would end up in clear underestimates of the size of the problem. The differences between ILO and GBD2015 outcomes are reported elsewhere. </span></p> <div> <div> <p><span> </span></p> </div> </div>
Experimental X-ray Diffraction Data for "Cooling-Induced Order-Disorder Phase Transition in CsPbBr3 Nanocrystal Superlattices"
<p>Experimental X-ray diffraction data: </p> <p>-- temperature-dependent diffraction patterns (theta:2theta, rocking curves) for C18 and C8 CsPbBr3 nanocrystal superlattice samples;</p> <p>-- room temperature diffraction patterns (theta:2theta, rocking curves) for C6, C8, C10, C12, and C18 CsPbBr3 nanocrystal superlattices;</p> <p>in all files, first column is angle in degrees and the second column is intensity.</p>
Basic visual functions of children and adolescents with Autism, Attention Deficit Hyperactivity Disorder, and Dyslexia
<p>Data for the manuscript Basic visual functions of children and adolescents with Autism, Attention Deficit Hyperactivity Disorder, and Dyslexia</p> <div> </div>
Supplemental image data for "Mechanical annealing and memories in a disordered solid"
<p>This archive contains raw and subtracted experimental images of a 2D colloidal disordered solid, sufficient to verify the major qualitative results of the paper "Mechanical annealing and memories in a disordered solid" by Nathan C. Keim and Dani Medina. Descriptions of the images may be found in the main text and Supplementary Information for that paper, a preprint of which is available at arXiv.org.</p>
Dataset Related to article "NEURODEVELOPMENTAL DISORDER AND LATE-ONSET DEGENERATIVE PARKINSONISM IN A PATIENT WITH A WDR45 DEFECT"
<p>NGS data (.vcf; .bam; .bam.bai; .csv; .fastq) of patient analysed and sanger sequencing (.abi) for confirm the mutation.</p>
Indicator values for the many-body localization of the Heisenberg spin chain at various energies, system sizes and disorder magnitude
<p>This data set accompanies the preprint <em>Scalable approach to many-body localization via quantum data </em>(arXiv: <a href="https://arxiv.org/abs/2202.08853">2202.08853</a>) and its code, available at <a href="https://github.com/GreschAl/MBLlearning">GitHub</a>.</p> <p>It consists of the numerically obtained indicator values for the many-body localization for the Heisenberg model (see preprint for details and background) for various values of the energy density <span class="math-tex">\(\epsilon = 0.05, 0.1, \dots, 0.9, 0.95\)</span> and for chain lengths <span class="math-tex">\(L = 10, 12, 14\)</span>. For each tuple <span class="math-tex">\((\epsilon,L)\)</span>, there exist two files, representing the training and the test set, respectively. Each such file contains various values of the disorder parameter <span class="math-tex">\(h = 0.5, 1, \dots, 14.5, 15\)</span> with <span class="math-tex">\(N = 1000\ (100)\)</span> sampled realizations of the disorder vector for each <span class="math-tex">\(h\)</span> for the training (test) set, followed by the three calculated values of the three indicators.</p> <p>The data is automatically processable by the code provided in the GitHub repository.</p>
Borg tandem repeats undergo rapid evolution and are under strong selection to create new intrinsically disordered regions in proteins
<p>This repository contains files that accompany the Schoelmerich <em>et al. </em>(2022) bioRxiv preprint.</p> <p>These files include</p> <p>- all Borg proteins used for protein family clustering (<a href="https://zenodo.org/api/files/f75689a0-d40c-44a6-b154-b74e3594fc04/all_Borg_proteins.fasta">all_Borg_proteins.fasta</a>)</p> <p>- 37 additional aaTR-proteins from manually curated Borg contigs (<a href="https://zenodo.org/api/files/f75689a0-d40c-44a6-b154-b74e3594fc04/37_Borg_aaTR-proteins.fasta?versionId=bfdfe7b6-e3b5-48b8-b7e6-a20304097e7d">37_Borg_aaTR-proteins.fasta</a>)</p> <p>- IQ-TREE of Borg DNA polymerases and reference sequences from doi: 10.1093/nar/gkaa760 (<a href="https://zenodo.org/api/files/f75689a0-d40c-44a6-b154-b74e3594fc04/DNAPolB_iqtree.treefile?versionId=c588a98c-822d-4a2f-a92d-7dcb3b1675f0">DNAPolB_iqtree.treefile</a>)</p> <p>- Borg Sm ribonucleoprotein sequences (<a href="https://zenodo.org/api/files/f75689a0-d40c-44a6-b154-b74e3594fc04/21_Borg_Sm_ribonucleoproteins.fasta">21_Borg_Sm_ribonucleoproteins.fasta</a>)</p> <p>- Borg MHC sequences (<a href="https://zenodo.org/api/files/f75689a0-d40c-44a6-b154-b74e3594fc04/14_Borg_MHC_proteins.fasta">14_Borg_MHC_proteins.fasta</a>)</p> <p>- AlphaFold2 predicted structural models of Borg Sm ribonucleoproteins and MHCs with aaTRs</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.