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3,476 results for “Parkinsons Disease”
ALAMEDA Data: Bridging the Early Diagnosis and Treatment Gaps of Brain Diseases (Parkinson's Disease, Multiple Slerosis and Stroke)
<p><strong>ALAMEDA</strong> is an Horizon 2020 Research and Innovation project that aims to bridge the early diagnosis and treatment gap of brain diseases via smart, connected, proactive and evidence-based technological interventions. Its vision is to research and prototype new generation Artificial Intelligence (AI) systems to support brain disorders patients' healthcare, focusing on Parkinson's Disease (PD), Multiple Sclerosis (MS) and Stroke.</p> <p>To this end, three (one for each disease) small scale validation pilots were performed in real world settings. Throughout these pilots, various types of data, such as accelerometer, gyroscopic, heart rate, etc., were collected via smart wearable sensors from the patients enrolled. The smart devices that were employed include: a Fitbit smartwatch, a GENEActiv smart bracelet, Novel Loadsol insole sensors and a prototype smart belt with triaxial accelerometers and gyroscopes embedded. Moreover, the patients underwent several clinical assessments and filled in numerous both disease-specific and non-disease-specific questionnaires.</p> <p>In this record, both raw and processed sensory data are combined with both clinical and patient reported outcomes (PROs) to form different disease-specific datasets. More specifically:</p> <ul> <li>For <strong>Parkinson's disease</strong>: Three datasets are provided (one for tremor detection, one for dyskinesia detection, and one for Hoehn & Yahr score estimation) alongside the vertical ground reaction force recordings.</li> <li>For <strong>Multiple Sclerosis</strong>: Two datasets are provided (one for Expanded Disability Status Scale (EDSS) scores classification and one that accumulates clinical data and individual scores from various MS-related questionnaires) alongside the vertical ground reaction force and the smart belt recordings.</li> <li>For <strong>Stroke</strong>: Two datasets are provided (one for rehabilitation exercises' recognition and one for walking classification, both with and without manual annotations) alongside the smart belt recordings.</li> </ul> <p>More information about the datasets provided can be found in the respective READ ME files that are included in the current record.</p>
Parkinson's Disease Tremor Dataset - ALAMEDA
<p><span>The ALAMEDA_PD_tremor_dataset.csv contains 92 features extracted from raw accelerometer data after pre-processing, 4 tremor-related labels and some other metadata. In total, it includes 99 columns:</span></p> <ol> <li> <p><span>The first two columns correspond to the start_timestamp and the end_timestamp of the time window from which the respective features have been extracted.</span></p> </li> <li> <p><span>The third column corresponds to the subject_id, which is used to uniquely identify PD patients enrolled in the current study.</span></p> </li> <li> <p><span>The next 92 columns correspond to features extracted from raw triaxial accelerometer data collected with the GENEActiv smart bracelets throughout 30-min MDS-UPDRS assessment during in-clinic visits, after applying some preprocessing steps. First, the accelerometer signals were band-pass filtered [2.5 Hz, 12.5 Hz] to enable tremor detection. Then, the magnitude and the first principal component of the filtered signals were computed to attenuate the dependency on sensor placement and orientation. Finally, the transformed signals were segmented into time windows of 2048 samples (or 20.48 sec) with 50% overlap. Then, 92 features were extracted in both time and frequency domains. Spectral features were extracted after applying Fast Fourier Transform. The full list of the extracted features is demonstrated in the table below. These features can feed Machine Learning models to predict the presence/absence of PD tremor.</span></p> </li> <li> <p><span>The final 4 columns correspond to tremor-related labels (Constancy_of_rest, Kinetic_tremor, Postural_tremor and Rest_tremor). They derive from the respective MDS-UPDRS III annotations, after transforming them to make them suitable for binary classification. More specifically, zero scores remained 0 to indicate the absence of tremor while positive scores were transformed to 1 to indicate the presence of tremor. Each of these columns can be used as a target to be predicted with the help of Machine Learning models.</span></p> </li> </ol>
Comparative analysis of Parkinson's and inflammatory bowel disease gut microbiomes reveals shared butyrate-producing bacteria depletion
<p><strong>Abstract: </strong>Epidemiological studies reveal that inflammatory bowel disease (IBD) is associated with an increased risk of Parkinson’s disease (PD). Gut dysbiosis has been documented in both PD and IBD, however it is currently unknown whether gut dysbiosis underlies the epidemiological association between both diseases. To identify shared and distinct features of the PD and IBD microbiome, we recruited 54 PD, 26 IBD, and 16 healthy control individuals and performed the first joint analysis of gut metagenomes. Larger, publicly available PD and IBD metagenomic datasets were also analyzed to validate and extend our findings. Depletions in short-chain fatty acid (SCFA)-producing bacteria, including <em>Roseburia intestinalis, Faecalibacterium prausnitzii, Anaerostipes hadrus</em>, and <em>Eubacterium rectale</em>, as well depletion in SCFA-synthesis pathways were detected across PD and IBD datasets, suggesting that depletion of these microbes in IBD may influence the risk for PD development.</p> <p><strong>Zenodo contents:</strong> In this Zenodo archive we provide the post-QC and taxonomic and functional profiling "Source Data" used in all downstream analyses to generate tables and figures seen in our manuscript. We also provide the link to our GitHub repository where we have stored the code used to perform the bioinformatic processing of the shotgun metagenomic sequences and stastical analyses. Individual sample raw shotgun metagenomic sequences and metadata from our UFPF dataset are available on NCBI Sequence Read Archive (SRA) under BioProject <a href="https://www.ncbi.nlm.nih.gov/bioproject/1096686">PRJNA1096686</a>. </p>
The indirect impact of COVID-19 on major clinical outcomes of people with Parkinson's disease or atypical parkinsonism: a cohort study. Raw data
<p>Raw dataset of the study "The indirect impact of COVID-19 epidemic on major clinical outcomes of people with Parkinson’s disease (PD) or atypical parkinsonism: a cohort study"</p>
Raw data for "Effect of MRgFUS treatment on cortical activity in Parkinson's disease: a fNIRS study"
<p>In this paper, a new combined approach, based on Magnetic Resonance-guided Focused Ultrasound Surgery (MRgFUS) technique and functional Near Infrared Spectroscopy (fNIRS), was applied for treatment and monitoring of patients affected by bilateral Parkinson’s disease (PD). On one side, MRgFUS enables non-invasive thalamotomy by combining FUS for tissue ablation and MR for targeting and monitoring. On the other side, fNIRS allows to monitor, non-invasively and without strict motion restriction even in a daily life environment, cortical neural activity related dynamics of both oxygenated and deoxygenated haemoglobin (HbO and HbR, respectively). In particular, the changes of cortical activation pattern in PD patients, with respect to age matched healthy control subjects, were analysed, while performing left and right hand finger tapping (LFT and RFT, respectively), before MRgFUS treatment, and at two different time intervals after the treatment. By comparison with the pre-treatment session, significant activations were predominantly observed one week after the treatment, with patterns recalling those of control group, and partially lost one month later, likely because of the neurodegenerative nature of PD. In addition, activations were more marked for LFT task, being the treatment performed on the right hemisphere. These results appear promising in view of the application of fNIRS for neurorehabilitation, especially in those clinical settings where traditional neuroimaging techniques cannot be applied.</p>
Parkinson's disease-associated, sex-specific changes in DNA methylation at PARK7 (DJ-1), ATXN1, SLC17A6, NR4A2, and PTPRN2 in cortical neurons
<p>Evidence for epigenetic regulation playing a role in Parkinson's disease (PD) is growing, particularly for DNA methylation. Approximately 90% of PD cases are due to a complex interaction between age, genes, and environmental factors, and epigenetic marks are thought to mediate the relationship between aging, genetics, the environment, and disease risk. To date, there are a small number of published genome-wide studies of DNA methylation in PD, but none accounted for cell-type or sex in their analyses. Given the heterogeneity of bulk brain tissue samples and known sex differences in PD risk, progression, and severity, these are critical variables to account for. In this first genome-wide analysis of DNA methylation in an enriched neuronal population from PD post-mortem parietal cortex, we report sex-specific PD-associated methylation changes in <em>PARK7</em> (DJ-1), <em>SLC17A6</em> (VGLUT2), <em>PTPRN2</em> (IA-2β), <em>NR4A2</em> (NURR1), and other genes involved in developmental pathways, neurotransmitter packaging and release, and axon and neuron projection guidance.</p>
Source Data files for: Primary cilia and SHH signaling impairments in human and mouse models of Parkinson's disease
<p>Parkinson’s disease (PD) as a progressive neurodegenerative disorder arises from multiple genetic and environmental factors. However, underlying pathological mechanisms remain poorly understood. Using multiplexed single-cell transcriptomics, we analyze human neural precursor cells (hNPCs) from sporadic PD (sPD) patients. Alterations in gene expression appear in pathways related to primary cilia (PC). Accordingly, in these hiPSC-derived hNPCs and neurons, we observe a shortening of PC. Additionally, we detect a shortening of PC in <em>PINK1</em>-deficient human cellular and mouse models of familial PD. Furthermore, in sPD models, the shortening of PC is accompanied by an increased SHH signal transduction. Inhibition of this pathway rescues the alterations in PC morphology and mitochondrial dysfunction. Thus, increased SHH activity due to ciliary dysfunction is needed for the development of pathoetiological phenotypes observed in sPD, like mitochondrial dysfunction. In sum, altered PC function is part of early PD pathoetiology and inhibiting the overactive SHH signaling is a potential neuroprotective therapy.</p>
The c-Abl inhibitor IkT-148009 therapeutically suppresses neurodegeneration in models of heritable and sporadic Parkinson's Disease
<p>Parkinson's Disease (PD) is the second most prevalent neurodegenerative disease of the central nervous system, with an estimated 5,000,000 cases worldwide. PD pathology is characterized by the accumulation of misfolded a-synuclein, which is thought to play a critical role in the etiopathogenesis of the disease. Animal models of PD suggest that activation of the Abelson Tyrosine Kinase, or c-Abl, plays an essential role in the initiation and progression of a-synuclein pathology and initiates processes leading to the degeneration of dopaminergic and non-dopaminergic neurons. Given the essential role of c-Abl in the disease, a proprietary c-Abl inhibitor library was developed to identify potent, orally bioavailable c-Abl inhibitors capable of crossing the blood-brain barrier based on pre-defined characteristics, leading to the discovery of IkT-148009. IkT-148009 is a selective, potent, brain-penetrant c-Abl inhibitor with a favorable toxicology profile that was analyzed for therapeutic potential in animal models of slowly progressive, a-synuclein-dependent disease. In models of both inherited and sporadic Parkinson's disease in the mouse, IkT-148009 suppressed c-Abl activation to baseline and substantially protected neurons from degeneration when administered therapeutically by once daily oral gavage beginning four weeks after disease initiation. Recovery of normal behavioral function in diseased mice occurred within 8 weeks of initiating treatment and occurred concomitantly with a substantial reduction of a-synuclein pathology in the brain. These disease-modifying outcomes in mice suggest IkT-148009 has the potential to be a disease-modifying therapy in human disease.</p>
Microbiome-based biomarkers to guide personalized microbiome-based therapies for Parkinson's disease
<p><strong>Abstract: </strong>We address an unmet challenge in Parkinson’s disease: the lack of biomarkers to identify the right patients for the right therapy, which is a main reason clinical trials for disease modifying treatments have all failed. The gut microbiome is a new target for treatment of neurodegenerative diseases. Our aim was to develop microbiome-based biomarkers to guide patient selection for microbiome-based clinical trials. We used microbial taxa that are robustly associated with PD across studies and at high significance as dysbiotic features of PD. Using individual-level taxonomic relative abundance data, we classified patients according to their dysbiotic features, effectively defining microbiome-based subtypes of PD. We show that not all persons with PD have a dysbiotic microbiome, and not all dysbiotic PD microbiomes have the same features. Grounded in robust and reproducible data from differential abundance studies, we propose an intuitive and easily modifiable method to identify the optimal candidates for microbiome-based clinical trials, and subsequently, for treatments that are personalized for each individual’s dysbiotic features. We demonstrate the method for PD. The concept, and the method, is generalizable for any disease with a microbiome component.</p> <p><strong>Zenodo</strong> <strong>content: </strong>In this Zenodo archive we provide (a) the method described step by step, which can be implemented in Microsoft Excel (we used v.16.84 (RRID:SCR_016137) <a href="https://www.microsoft.com/en-gb/">https://www.microsoft.com/en-gb/</a>) or in R (we used v4.3.3 (RRID:SCR_001905) <a title="https://www.r-project.org/ Cmd+Click or tap to follow the link" href="https://www.r-project.org/">https://www.r-project.org/</a>); and (b) data used to generate the results, tables and figures (except figure 2). Data for creating figure 2 can be found in source data (doi: 10.5281/zenodo.7246185) and the method is described by Wallen et al 2022 (DOI: <u><a href="https://doi.org/10.1038/s41467-022-34667-x" target="_blank" rel="noopener">10.1038/s41467-022-34667-x</a></u>). All data used here were extracted from the original source data reported by<strong> </strong>Wallen et. al. 2022 (DOI: <u><a href="https://doi.org/10.1038/s41467-022-34667-x" target="_blank" rel="noopener">10.1038/s41467-022-34667-x</a></u>) which can be found on Zenodo (DOI: 10.5281/zenodo.7246185).</p>
Repository of speech features from speakers with and without Parkinson's Disease. Neurovoz - Rasta PLP - V2 - Scientific Reports Publication: Phonetic relevance and phonemic grouping of speech in the automatic detection of Parkinson's Disease
<p>This repository contains the Rasta-PLP features of six different speech recordings (sentences) from Neurovoz corpus (47 parkinsonian and 32 control speakers whose mother tongue is Spanish Castillian.)<br> Number of PLP coefficients: [6, 8, 10, 12, 14, 16, 18, 20].<br> Delta coefficients: Yes<br> Delta Delta coefficients: Yes<br> Sampling rate: 16 kHz<br> Frame size: 15 ms<br> Frame overlapping: 50%</p> <p>This subset of the Neurovoz corpus was recorded between 2015 and 2017 by Universidad Politécncia de Madrid and Hospital General Universitario Gregorio Marañón.</p> <p>This version includes the same files as the previous version and information about UPDRS, H&Y, years since diagnosis and age of each participant.</p> <p>The sentences were:</p> <p>BARBAS: "Cuando las barbas de tu vecino veas pelar, pon las tuyas a remojar"</p> <p>CALLE: "De la calle vendrá quien de tu casa te echará"</p> <p>DIABLO: " Cuando el diablo no sabe qué hacer, con el rabo mata moscas "</p> <p>PETACA BLANCA: " La petaca blanca es mía"</p> <p>PIDIO: "No pidas a quien pidió ni sirvas a quien sirvió"</p> <p>SOMBRA: " El que a buen árbol se arrima, buena sombra le cobija "</p> <p> </p> <p>How to cite:<br> [1] Moro-Velazquez, L., Gomez-Garcia, J. A., Godino-Llorente, J. I., Grandas-Perez, F., Shattuck-Hufnagel, S. Yagüe-Jimenez, V., and Dehak, N. (2019). Phonetic relevance and phonemic grouping of speech in the automatic detection of Parkinson’s disease.Scientific reports 9, 19066.</p> <p><br> [2] Moro-Velazquez, L., Gomez-Garcia, J. A., Godino-Llorente, J. I., Villalba, J., Rusz, J., Shattuck-Hufnagel, S. and Dehak, N. (2019). A forced Gaussians based methodology for the differential evaluation of Parkinson's Disease by means of speech processing. Biomedical Signal Processing and Control, 48, 205-220.</p> <p>BibTeX:</p> <pre><code>@article{moro2019phonetic, title={Phonetic relevance and phonemic grouping of speech in the automatic detection of Parkinson's Disease}, author={Moro-Velazquez, Laureano and Gomez-Garcia, Jorge A. and Godino-Llorente, Juan I. and Grandas-Perez, Francisco and Shattuck-Hufnagel, Stefanie and Yague-Jimenez, Virginia and Dehak, Najim}, journal={Scientific Reports}, volume={9}, pages={19066}, year={2019}, publisher={Nature Research Publishing} } @article{moro2019forced, title={A forced Gaussians based methodology for the differential evaluation of Parkinson's Disease by means of speech processing}, author={Moro-Velazquez, Laureano and Gomez-Garcia, Jorge Andres and Godino-Llorente, Juan Ignacio and Dehak, Najim}, journal={Biomedical Signal Processing and Control}, pages={205--220}, volume={48}, year={2019}, publisher={Elsevier} } </code></pre> <p> </p>
Sway frequencies may predict postural instability in Parkinson's disease: Data
<p>Dataset with raw Center of Pressure (COP) and Center of Mass (COM) time series along with respective wavelet spectrograms.</p> <p>Recorded during 30 seconds of quiet stance. 10 trials per participant. Sampled at 50 Hz.</p> <p>18 individuals with Parkinson's disease, 15 healthy controls.</p> <p>Detailed data description can be found in the word file.</p> <p> </p>
Systemic inflammation accelerates neurodegeneration in a rat model of Parkinson's disease overexpressing human alpha synuclein
<p><span>Parkinson’s disease (PD) involves genetic and<span> </span>environmental risk factors. Increasing research efforts have been made to understand how they interact<span> </span>to<span> </span>impair<span> </span>homeostasis<span> </span>and<span> </span>elevate<span> </span>risk. Inflammation could be one unifying factor. In this study, <em>wild-type</em> (WT) and overexpressing human </span><span>α</span><span>-synuclein (<em>Snca</em><sup>+/+</sup>) rats <span>were intraperitoneally injected with a single dose of </span>lipopolysaccharide<span> </span>(LPS) or with saline (SAL). In these animals we assessed </span><span>the development of PD-like symptoms by immunohistology, high-dimensional flow cytometry, electrophysiology, and behavioral analyses. A single injection of LPS to both WT and <em>Snca<sup>+/+</sup> </em>rats triggered long-lasting increased activation of pro-inflammatory microglial markers, infiltrating monocytes and T-lymphocytes. However, only LPS <em>Snca</em><sup>+/+</sup> rats displayed dopaminergic neuronal loss in the <em>substantia<span> </span>nigra pars compacta<span> </span></em>(SNpc), associated with a reduction of evoked dopamine<span> release </span>in the striatum. No significant<span> </span>changes were observed in the behavioral domain. </span></p> <p><span> </span></p>
Pain coping strategies and their association with quality of life in people with Parkinson's Disease: a Cross-Sectional study
<p><b>Design</b> Cross-sectional, cohort study.</p> <p><b>Setting</b> Monocentric, inpatient, university hospital.</p> <p><b>Participants</b> 52 patients with Parkinson's disease (without dementia) analysed.</p> <p><b>Primary and secondary outcome measures</b> Motor function, nonmotor symptoms, health-related quality of life (QoL), and the Coping Strategies Questionnaire were assessed.</p>
Metagenomics of Parkinson's disease implicates the gut microbiome in multiple disease mechanisms
<p><strong>Abstract:</strong> Parkinson's disease (PD) may start in the gut and spread to the brain. To investigate the role of gut microbiome, we conducted a large-scale study, at high taxonomic resolution, using uniform standardized methods from start to end. We enrolled 490 PD and 234 control individuals, conducted deep shotgun sequencing of fecal DNA, followed by metagenome-wide association studies requiring significance by two methods (ANCOM-BC and MaAsLin2) to declare disease association at species and genus level, followed by network analysis to identify polymicrobial clusters, and functional profiling based on microbial genes and pathways. Here we show that over 30% of species, genes and pathways tested have altered abundances in PD, depicting a widespread dysbiosis. PD-associated species form polymicrobial clusters that grow or shrink together, and some compete. PD microbiome is disease permissive, evidenced by overabundance of pathogens and immunogenic components, dysregulated neuroactive signaling, preponderance of molecules that induce alpha-synuclein pathology, and over-production of toxicants; with the reduction in anti-inflammatory and neuroprotective factors limiting the capacity to recover. We validate, in human PD, findings that were observed in experimental models; reconcile and resolve human PD microbiome literature, and provide a broad foundation with a wealth of concrete testable hypotheses to discern the role of the gut microbiome in PD. </p> <p><strong>Zenodo contents:</strong> In this Zenodo archive we provide (1) post sequence QC and post taxonomic and functional profiling "Source Data" used to generate tables and figures in the manuscript and (2) "Supplementary Code" that contains the workflow and code used to perform bioinformatic processing of shotgun sequences and statistical analyses of microbial profiles and subject metadata. The code provided here is the same "Supplementary Code" that is provided in the supplement of the manuscript. Individual level raw shotgun sequences and metadata are available on NCBI Sequence Read Archive (SRA) under BioProject ID <a href="https://www.ncbi.nlm.nih.gov/bioproject/834801">PRJNA834801</a>.</p>
Microelectrode register (MER) data from Deep Brain Stimulation (DBS) surgery in Parkinson's disease patients
<p>MER data consist of brain signal in different depths when DBS surgery is being done. In each depth, a data file is created, with different duration depending on the depth, and up to three channels.</p> <p>Data come from 14 patients (9 males and 5 females), they are anonymized and labelled from P1 to P14. They correspond to patients in age 65.1 +- 5.6 years.</p> <p>Data are organized in STN-IN and STN-OUT (different depths in each folder), subthalamus-in, and subthalamus-out since the STN area is the target area when implanting a DBS. Classification in STN-IN and STN-OUT was made by the neurophysiologists and surgeons.</p> <p>Data were recorded for left and right lobes, 8 patients in left and right lobe, 1 patient in right lobe, and 5 patients in left lobe.</p> <p>The format is mat file (MATLAB file)</p> <p>Data sampling frequency is 12kHz.</p> <p>No filtering or data processing was made, they are directly obtained from the MER acquisition system.</p> <p> </p>
Clusters of interactions common between the Parkinson's disease map and the Ageing map
<p>This set of files was generated using the script demonstrating the use of MINERVA Net repository.</p> <p>The script is available under:</p> <p><a href="https://gitlab.lcsb.uni.lu/minerva/api-scripts/-/blob/master/R/API-minervanet.R">https://gitlab.lcsb.uni.lu/minerva/api-scripts/-/blob/master/R/API-minervanet.R</a></p> <p>The diagrams should be opened with the CellDesigner software (<a href="https://www.celldesigner.org/">https://www.celldesigner.org/</a>).</p>
Data from: Decreased cerebrospinal fluid orexin levels not associated with clinical sleep disturbance in Parkinson's disease: A retrospective study
<p><span>Patients with Parkinson's disease (PD) often suffer from sleep disturbances, including excessive daytime sleepiness (EDS) and rapid eye movement sleep behavior disorder (RBD). These symptoms are also experienced by patients with narcolepsy, which is characterized by orexin neuronal loss. In PD, a decrease in orexin neurons is observed pathologically, but the association between sleep disturbance in PD and cerebrospinal fluid (CSF) orexin levels is still unclear. This study aimed to clarify the role of orexin as a biomarker in patients with PD.</span></p> <p><span>CSF samples were obtained from a previous cohort study conducted between 2015 and 2020. We cross-sectionally and longitudinally examined the association between CSF orexin levels, sleep, and clinical characteristics.</span></p> <p><span>We analyzed 78 CSF samples from 58 patients with PD and 21 samples from controls. CSF orexin levels in patients with PD (median = 272.0 [interquartile range = 221.7–334.5] pg/mL) were lower than those in controls (352.2 [296.2–399.5] pg/mL, p = 0.007). There were no significant differences in CSF orexin levels according to EDS, RBD, or the use of dopamine agonists. Moreover, no significant correlation was observed between CSF orexin levels and clinical characteristics by multiple linear regression analysis. Furthermore, the longitudinal changes in orexin levels were also not correlated with clinical characteristics.</span></p> <p><span>This study showed decreased CSF orexin levels in patients with PD, but these levels did not show any correlation with any clinical characteristics. Our results suggest the limited efficacy of CSF orexin levels as a biomarker for PD, and that sleep disturbances may also be affected by dysfunction of the nervous system other than orexin, or by dopaminergic treatments in PD.</span><span> Understanding the reciprocal role of orexin among other neurotransmitters may provide a better treatment strategy for sleep disturbance in patients with PD.</span></p>
Barriers to home exercise for patients with Parkinson's disease – a qualitative study
<p><strong>Objective</strong>: This study aimed to explore the barriers to home exercise for patients with Parkinson's disease (PwPDs) and provide guidelines for healthcare providers (HcPs) to build and implement home exercise strategies for PwPDs.</p> <p><strong>Design</strong>: A qualitative descriptive method was used. Semi-structured interviews were conducted and thematic analysis was employed.</p> <p><strong>Setting</strong>: The study was conducted in the Department of Neurology at a Grade 3 Class A general hospital in China.</p> <p><strong>Participants</strong>: A total of 22 participants were interviewed, including 10 PwPDs, seven caregivers, two nurses, one head nurse, and two Parkinson's clinicians.</p> <p><strong>Results</strong>: Five themes were identified in this analysis. (1) Psychosomatic stress and low activity; (2) lack of early rehabilitation authorisation; (3) poor "flow" state of home exercise; (4) inaccessibility of continued service; (5) sociocultural impact on family coping.</p> <p><strong>Conclusion</strong>: PwPDs, caregivers, and specialised medical staff raised the challenges faced by patients' home exercises from different perspectives. Interventions can improve services and integrate resources through the management of multi-disciplinary, early rehabilitation authorisation, exercise experience, continuous service mode, and family coping strategies under different cultures to gradually adjust the home exercise behaviour of PwPDs.</p>
Data for: Deep brain stimulation in early-stage Parkinson disease
<p><strong>Objective</strong>: To report 5-year outcomes from the subthalamic nucleus (STN) deep brain stimulation (DBS) in early-stage Parkinson disease (PD) pilot clinical trial.</p> <p><strong>Methods</strong>: The pilot was a prospective, single-blind clinical trial that randomized patients with early-stage PD (Hoehn & Yahr II off medications) to receive bilateral STN DBS plus optimal drug therapy (ODT) vs ODT alone (IDEG050016, NCT0282152, IRB040797). Participants who completed the 2-year trial participated in this observational follow-up study, which included annual outpatient visits through 5 years. This analysis includes 28 patients who were taking PD medications for 6 months to 4 years at enrollment. Outcomes were analyzed using both proportional odds logistic regression and linear mixed effects models.ResultsEarly STN DBS + ODT participants required lower levodopa equivalent daily doses (p = 0.04, β = −240 mg, 95% confidence interval [CI] −471 to −8) and had 0.06 times the odds of requiring polypharmacy at 5 years compared to early ODT participants (p = 0.01, odds ratio [OR] 0.06, 95% CI 0.00 to 0.65). The odds of having worse rest tremor for early STN DBS + ODT participants were 0.21 times those of early ODT participants (p < 0.001, OR 0.21, 95% CI 0.09 to 0.45). The safety profile was similar between groups.</p> <p><strong>Conclusions</strong>: These results suggest that early DBS reduces the need for and complexity of PD medications while providing long-term motor benefit over standard medical therapy. Further investigation is warranted, and the Food and Drug Administration has approved the conduct of a prospective, multicenter, pivotal clinical trial of DBS in early-stage PD (IDEG050016).</p> <p><strong>Classification of evidence</strong>: This study provides Class II evidence that DBS implanted in early-stage PD decreases the risk of disease progression and polypharmacy compared to optimal medical therapy alone.</p>
Protein network analysis links the NSL complex to Parkinson's disease via mitochondrial & nuclear biology
<p>This online depository corresponds to manuscript : <em>Protein network analysis links the NSL complex to Parkinson’s disease via mitochondrial & nuclear biology.</em></p> <p><strong>Authors: </strong><em>Katie Kelly, Patrick A. Lewis, Helene Plun-Favreau, Claudia Manzoni</em></p> <p>Whilst the majority (~90-95%) of PD cases are sporadic, much of our understanding of the pathophysiological basis of disease can be traced back to the study of rare, monogenic forms of disease. However, in the past decade, the availability of Genome-Wide Association Studies (GWAS) has facilitated a shift in focus, toward identifying common risk variants conferring an increased risk of developing PD across the population. </p> <p>A recently developed mitophagy screening assay of GWAS candidates, has functionally implicated the non-specific lethal (NSL) complex, a chromatin remodeler, in the regulation of PINK1-mitophagy. Here, a bioinformatics approach has been taken to investigate the interactome of the NSL complex, to unpick its relevance to PD progression. The mitochondrial interactome of the NSL complex has been built, mining 3 separate repositories: PINOT, HIPPIE and MIST, for curated, literature-derived protein-protein interaction (PPI) data. A multi-layered approach has been taken to; i) build the ‘mitochondrial’ NSL interactome, applying PD gene-set enrichment analysis to explore the relevance of the NSL mitochondrial interactome to PD and, ii) build the PD-oriented NSL interactome, using functional enrichment, to uncover biological pathways underpinning the NSL /PD association.</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.