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The language network reemerges during recovery from severe traumatic brain injury
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Patellar Tendon Load Progression during Rehabilitation Exercises: Implications for the Treatment of Patellar Tendon Injuries
<h3><strong>Purpose </strong></h3><p>To evaluate patellar tendon loading profiles (loading index, based on loading peak, loading impulse, and loading rate) of rehabilitation exercises to develop clinical guidelines to incrementally increase the rate and magnitude of patellar tendon loading during rehabilitation.</p><h3><strong>Methods </strong></h3><p>Twenty healthy adults (10 females/10 males, 25.9 ± 5.7 years) performed 35 rehabilitation exercises, including different variations of squats, lunge, jumps, hops, landings, running, and sports specific tasks. Kinematic and kinetic data were collected and a patellar tendon loading index was determined for each exercise using a weighted sum of loading peak, loading rate, and cumulative loading impulse. Then, the exercises were ranked, according to the loading index, into tier 1 (loading index≤0.33), tier 2 (0.33 < loading index<0.66), and tier 3 (loading index≥0.66).</p><h3><strong>Results </strong></h3><p>The single-leg decline squat showed the highest loading index (0.747). Other tier 3 exercises included single-leg forward hop (0.666), single-leg countermovement jump (0.711), and running cut (0.725). The Spanish squat was categorized as a tier 2 exercise (0.563), as was running (0.612), double-leg countermovement jump (0.610), single-leg drop vertical jump (0.599), single-leg full squat (0.580), double-leg drop vertical jump (0.563), lunge (0.471), double-leg full squat (0.428), single-leg 60° squat (0.411), and the Bulgarian squat (0.406). Tier 1 exercises included 20 cm step up (0.187), 20 cm step down (0.288), 30 cm step up (0.321), and double-leg 60° squat (0.224).</p><h3><strong>Conclusions </strong></h3><p>Three patellar tendon loading tiers were established based on a combination of loading peak, loading impulse, and loading rate. Clinicians may use these loading tiers as a guide to progressively increase patellar tendon loading during the rehabilitation of patients with patellar tendon disorders and after anterior cruciate ligament reconstruction using the bone patellar tendon bone graft.</p>
Genome- and transcriptome-wide association summary statistics for outcome from traumatic brain injury
<p>The dataset contains summary statistics for the genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in traumatic brain injury (TBI). The study participants attended hospital within 24 hours of TBI, and underwent head computed tomography imaging.</p> <p><strong>Study participants</strong></p> <p>European ancestry data set contains 4710 individuals; multi-ethnic cohort 5268 individuals, including Europeans (n = 4710), Africans (n = 245) and Admixed Americans (n = 313).</p> <p>The largest European population contribution was from CENTER-TBI (Collaborative European NeuroTrauma Effectiveness Research, https://www.center-tbi.eu), where each participating center (60 centers from 20 countries in Europe) recruited patients between December 2013 and December 2017. The patients recruited in CENTER-TBI were supplemented by subjects from cohorts recruited at two European centres (Cambridge, UK, and Turku, Finland).</p> <p>The majority of patients in the US cohort were recruited between 2014 and 2018 to TRACK-TBI (Transforming Research and Clinical Knowledge in TBI, https://tracktbi.ucsf.edu) by the 18 US participant sites. The subjects recruited to the US cohort from TRACK-TBI were supplemented by patients recruited to an institutional research initiative at Mass General Brigham (MGB).</p> <p><strong>Outcome definition</strong></p> <p>Outcomes were measured using the extended Glasgow Outcome Scale (GOSE), ranging from 1 (dead) to 8 (upper good recovery), measured 6 months post-TBI. TBI severity was specified using the Glasgow Coma Score (GCS), with TBI classified as mild (GCS 13-15), moderate (GCS 9-12), or severe (GCS 3-8).</p> <p>To account for the effect of injury severity on outcome, sliding dichotomization was used to categorize outcome as favourable or unfavourable. A GOSE ≤ 4 was used to define an unfavourable outcome for patients with either moderate (GCS 9-12) or severe (GCS 3-8) TBI, while the unfavourable group was extended to patients with GOSE ≤ 7 if they had mild (GCS 13-15) TBI.</p> <p><strong>Genotype data and imputation</strong></p> <p>Genotyping was completed at FIMM Technology Center for CENTER-TBI, Cambridge, Turku patients and the Broad Institute for TRACK-TBI, using the Illumina Global Screening Array (GSA-24v2-0 + Multi-Disease). The MGB cohort were genotyped using Illumina’s Multi-Ethnic Global array (MEGA) and the pre-releases forms, including MEGA and MEGA-Ex arrays at Illumina at the MGB Translational Genomics Core.</p> <p>A unified quality control procedure was applied for each study cohort and the array-based genotypes were imputed using the Haplotype Reference Consortium panel. Autosomal chromosomes were considered, post-imputation data was filtered by imputation quality (INFO > 0.4 for CENTER-TBI, Cambridge and Turku; R2 > 0.4 for TRACK-TBI and MGB) and MAF > 1%.</p> <p><strong>Genome-wide association analysis and meta-analysis</strong></p> <p>Genome-wide single-marker scans were performed using a penalized likelihood-based Firth logistic regression, and implemented in PLINK v2.0. Using favourable outcome as reference, models were fitted on the basis of imputed allelic dosages. Age, sex, major extracranial injury, pupillary reactivity, and the first 10 principal components were included as covariates. Study cohort (CENTER-TBI, Cambridge, Turku) was an additional covariate in the CENTER-TBI GWAS.</p> <p>Fixed-effects meta-analysis of the three European ancestry GWAS was performed using METAL. For trans-ethnic meta-analysis, summary statistics of five GWASs in patients of European, African and Admixed Americans were aggregated via MR-MEGA.</p> <p><strong>Transcriptome-wide association study</strong></p> <p>Genetically regulated gene expression (GREx) was imputed using a regression model fitted on a separate gene expression database. Elastic net models provided by PrediXcan for all available GTEx brain tissues and whole blood were used. For TWAS, the same sliding dichotomy model for outcome with the same set of covariates as in the GWAS, but PCA components were replaced with the top five principal components of the respective gene expression data. </p> <p><strong>Column headers - GWAS</strong></p> <p>rsID: variant rsID<br> Chrom: chromosome<br> Pos: position (build GRCh38)<br> A1: effect allele<br> A2: reference allele<br> EAF: allele frequency of effect allele<br> Effect: effect size of effect allele<br> StdErr: standard error of effect size<br> P: p value of association (with genomic correction)<br> N: sample size</p> <p>Note. 'Effect' and 'StdErr' are only available for the European ancestry meta-analysis.</p> <p><br> <strong>Column headers - TWAS</strong></p> <p>tissue: GTEx tissue type<br> id: ensembl gene id<br> coef: model coefficient<br> se: model standard error for coefficient<br> p: model-based p value<br> symbol: gene symbol<br> name: gene name written out<br> chr: chromosome<br> start: gene start position (build GRCh38)</p>
Epidemiological and clinical characteristics predictive of ICU mortality of traumatic brain injury patients treated at a trauma reference hospital – A cohort study - Dataset
<p><strong>Dataset of a cohort whose summary is described below.</strong></p> <p><strong>ABSTRACT</strong></p> <p><strong>Background</strong>: Traumatic brain injury (TBI) has substantial physical, psychological, social and economic impacts, with high rates of morbidity and mortality. Considering its high incidence, the aim of this study was to identify epidemiological and clinical characteristics that predict mortality in patients hospitalized for TBI in intensive care units (ICUs). <strong>Methods</strong>: A retrospective cohort study was carried out with patients over 18 years old with TBI admitted to an ICU of a Brazilian trauma referral hospital between January 2012 and August 2019. TBI was compared with other traumas in terms of clinical characteristics of ICU admission and outcome. Univariate and multivariate analyses were used to estimate the odds ratio for mortality. <strong>Results</strong>: Of the 4816 patients included, 1114 had TBI, with a predominance of males (85.1%). Compared with patients with other traumas, patients with TBI had a lower mean age (45.3 ± 19.1 versus 57.1 ± 24.1 years, p < 0.001), higher median APACHE II (19 versus 15, p <0.001) and SOFA (6 versus 3, p < 0.001) scores, lower median Glasgow Coma Scale (GCS) score (10 versus 15, p < 0.001), higher median length of stay (7 days versus 4 days, p < 0.001) and higher mortality (27.6% versus 13.3%, p < 0.001). In the multivariate analysis, the predictors of mortality were older age (OR: 1.008 [1.002-1.015], p = 0.016), higher APACHE II score (OR: 1.180 [1.155-1.204], p < 0.001), lower GCS score for the first 24 hours (OR: 0.730 [0.700-0.760], p < 0.001), and greater number of brain injuries and presence of associated chest trauma (OR: 1.727 [1.192-2.501], p < 0.001). <strong>Conclusion</strong>: Patients admitted to the ICU for TBI were younger and had worse prognostic scores, longer hospital stays and higher mortality than those admitted to the ICU for other traumas. The independent predictors of mortality were advanced age, APACHE II score, first 24-hour GCS score, number of brain injuries and chest trauma.</p>
Prediction of repurposed drugs for treating lung injury in COVID-19
<p>These are output files of shared R scripts used in prediction of repurposed drugs for treating lung injury in COVID-19.</p> <p> </p> <p>R scripts are available here: https://doi.org/10.5281/zenodo.3822923</p> <p> </p> <p>Description of files:</p> <p>HCC515_6_data_for_drug.csv #Differential expression of genes in HCC515 cell at 6 h after treatment of ACE2 inhibitor</p> <p>HCC515_24_data_for_drug.csv #Differential expression of genes in HCC515 cell at 24 h after treatment of ACE2 inhibitor</p> <p>COVID19-Lung_data_for_drug.csv #Differential expression of genes in lung tissues with COVID-19</p> <p>HCC515_6_drug.csv #Drugs for HCC515 cell at 6 h after transfection of ACE2 inhibitor</p> <p>HCC515_24_drug.csv #Drugs for HCC515 cell at 24 h after transfection of ACE2 inhibitor</p> <p>COVID19-Lung_drug.csv #Drugs for lung tissuse from COVID-19 patients</p> <p>COL-3_single_treatment_response_data.csv #Differential expression of genes in HCC515 cell at 24h after treatment of COL-3</p> <p>CGP-60474_single_treatment_response_data.csv #Differential expression of genes in HCC515 cell at 24h after treatment of CGP-60474</p>
Data for Mellado et al. The impacts of marking on bats: mark-recapture models for assessing injury rates and tag loss. Journal of Mammalogy. 103:100-110. DOI:10.1093/jmammal/gyab153
<p>Data sets used in Mellado et al. The impacts of marking on bats: mark-recapture models for assessing injury rates and tag loss. Journal of Mammalogy. 103:100-110. (https://doi.org/10.1093/jmammal/gyab153)</p> <p>File Descriptions:</p> <p>CapHistTagLoss.txt - Capture histories for <em>Carollia perspicillata</em> identifying if individual was captured with both tags (B), arm bands (A), collar (C), not captured (0) or not monitored (dot). Covariates included are Sex, Forearm Length and Scaled Mass Index.<br> CaptHistTagInj.txt - Capture histories for <em>Carollia perspicillata</em> identifying if individual was captured with no lesions from arm band (A), minor injury (I), major injury (M), not captured (0) or not monitored (dot). Covariates included are Sex, Forearm Length and Scaled Mass Index.<br> LesionOccurrence.txt - Censored time-to-event data for survival analysis. Recorded events were the occurrence of lesions of any type due to arm bands.<br> RingCondition.txt - Censored time-to-event data for survival analysis. Recorded events were the occurrence of damage to arm bands.<br> SMI.txt - Longitudinal data for individual <em>Carollia perspicillata</em> Scaled Mass Index, identifying individual records, the occurrence of lesions, sex, month, year</p> <p> </p>
Continuous monitoring of patient mobility for 18 months using inertial sensors following traumatic knee injury: a case study
<p><strong>This repository contains raw data relating to: </strong>Continuous monitoring of patient mobility for 18 months using inertial sensors following traumatic knee injury: a case study Mueller A., Hoefling H., Nuritdinow T., et al. DOI: 10.1159/000490919</p> <p><strong>Metadata and processed data derived from the raw data deposited here is available here:</strong> https://github.com/Novartis/mueller_et_al_2018</p> <p><strong>Article Abstract</strong></p> <p>Continuous patient activity monitoring during rehabilitation, enabled by digital technologies, will allow the objective capture of real-world mobility and aligning treatment to each individual’s recovery trajectory in real time. To explore the feasibility and added value of such approaches, we present a case study of a 36-year-old male participant monitored continuously for activity levels and gait parameters using a waist-worn inertial sensor following a tibial plateau fracture on the right side, sustained as a result of a high-energy trauma during a sporting accident. During rehabilitation, data were collected for a period of 553 days, with > 80% daytime compliance, until the participant returned to near full mobility. The participant completed a daily diary with the annotation of major events (falls, near falls, cycling periods, or physiotherapy sessions) and key dates in the patient’s recovery, including medical interventions, transitioning off crutches, and returning to work. We demonstrate the feasibility of collecting, storing, and mining of continuous digital mobility data and show that such data can detect changes in mobility and provide insights into long-term rehabilitation. We make both raw data and annotations available as a resource with the aspiration that further methods and insights will be built on this initial exploration of added value and continue to demonstrate that continuous monitoring can be deployed to aid rehabilitation.</p>
Data from: Kir2.1 modulation in macrophages sensitises dorsal root ganglion neurons through TNF secretion after nerve injury
<p>This data pertain to the manuscript titled "Kir2.1 modulation in macrophages sensitises dorsal root ganglion neurons through TNF secretion after nerve injury", currently in preprint on BioRxiv (https://doi.org/10.1101/2023.06.21.545843). The name of the data files correspond to the for each figure in the study. The data file in .csv format are organized so that they can easily be opened in R or other analysis language. To understand them and how they are labelled, it is advised to open the figure next to them and find the appropriate panel.</p> <p>Here are included:</p> <ul> <li>Example images of section of mouse dorsal root ganglion (DRG) after spared nerve injury (SNI), labelled for CX3CR1+ cells, Ki67 and MHC class II by immunohistochemistry.</li> <li>LC-MS-MS proteomic data set of CX3CR1+ cells from DRG of mice after SNI.</li> <li>Voltage clamp data of CX3CR1+ cells from DRG of mice after SNI</li> <li>Electrophysiological data sets (multi-electrode array, current clamp and voltage clamp) of dissociated DRG neurons treated with medium conditioned by CX3CR1+ or GFAP+ cells sorted from ipsilateral or contralateral DRG from mice after SNI. In addition, pharmacological treatments were added to the conditioned medium (CM).</li> </ul>
Balancing risks of injury and disturbance to marine mammals when pile driving at offshore windfarms
<p>1. Offshore windfarms require construction procedures that minimise impacts on protected marine mammals. Uncertainty over the efficacy of existing guidelines for mitigating near-field injury when pile-driving recently resulted in the development of alternative measures, which integrated the routine deployment of acoustic deterrent devices (ADD) into engineering installation procedures without prior monitoring by Marine Mammal Observers.</p> <p>2. We conducted research around the installation of jacket foundations at the UK's first deep-water offshore windfarm to address data gaps identified by regulators when consenting this new approach. Specifically, we aimed to a) measure the relationship between noise levels and hammer energy to inform assessments of near-field injury zones, b) assess the efficacy of ADDs to disperse harbour porpoises from these zones.</p> <p>3. Distance from source had the biggest influence on received noise levels but, unexpectedly, received levels at any given distance were highest at low hammer energies. Modelling highlighted that this was because noise from pin pile installations was dominated by the strong negative relationship with pile penetration depth with only a weak positive relationship with hammer energy.</p> <p>4. Acoustic detections of porpoises along a gradient of ADD exposure decreased in the 3-hours following a 15-minute ADD playback, with a 50% probability of response within 21.7 km. The minimum time to the first porpoise detection after playbacks was > 2 hours for sites within 1 km of the playback.</p> <p>5. Our data suggest that the current regulatory focus on maximum hammer energies needs review, and future assessments of noise exposure should also consider foundation type. Despite higher piling noise levels than predicted, responses to ADD playback suggest mitigation was sufficiently conservative. Conversely, strong responses of porpoises to ADDs resulted in far-field disturbance beyond that required to mitigate injury. We recommend that risks to marine mammals can be further minimised by: 1) optimising ADD source signals and/or deployment schedules to minimise broad-scale disturbance; 2) minimising initial hammer energies when received noise levels were highest; 3) extending the initial phase of soft start with minimum hammer energies and low blow rates.Minhyuk Seo</p>
Fluorescent Microglia Images for Analyzing Morphological Changes due to Injury Duration in the Ischemic Rat Brain
<p>The image data included in this dataset are the confocal microscope images (converted from original .nd2 file to .tiff form) used for the publication: Joseph, A., Liao, R., Zhang, M., Helmbrecht, H., McKenna, M., Filteau, J. R., & Nance, E. (2020). Nanoparticle-microglial interaction in the ischemic brain is modulated by injury duration and treatment. <em>Bioengineering & translational medicine</em>, <em>5</em>(3), e10175. https://doi.org/10.1002/btm2.10175</p> <p>The data is organized by brain slice number, region, and image number. There is also an included excel file 'datadescriptions.xlsx' that provides more information about the metadata of the dataset. </p> <p> </p> <p>The data was procured and processed by the Disease Directed Engineering Lab, PI: Elizabeth Nance, at the University of Washington.</p>
Post-injury immunosuppression and secondary infections are caused by an AIM2 inflammasome-driven signaling cascade
<p>RAW FCS files for the manuscript:</p> <p>"Post-injury immunosuppression and secondary infections are caused by an AIM2 inflammasome-driven signaling cascade"</p> <p> </p>
Raw data of Injury-feigning of Savanna Nightjar
<p>The raw data of the manuscript "Injury-feigning of Savanna Nightjar: a test of the vulnerability and brood value hypotheses<strong>"</strong></p>
Dataset related to: Sirt3 deficiency promotes endothelial dysfunction and aggravates renal injury
<p>The .xlsx file contains raw data related to the article "<i><strong>Sirt3</strong></i><strong> deficiency promotes endothelial dysfunction and aggravates renal injury</strong>. <i>PLOS One</i>. 2023 Oct 10;18(10):e0291909<i>", </i>available at the following <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0291909">link</a>.</p><p> </p><p><strong>Abstract</strong></p><p>Sirtuin 3 (SIRT3), the main deacetylase of mitochondria, modulates the acetylation levels of substrates governing metabolism and oxidative stress. In the kidney, we showed that SIRT3 affects the proper functioning of high energy-demanding cells, such as tubular cells and podocytes. Less is known about the role of SIRT3 in regulating endothelial cell function and its impact on the progression of kidney disease. Here, we found that whole body <i>Sirt3</i>-deficient mice exhibited reduced renal capillary density, reflecting endothelial dysfunction, and VEGFA expression compared to wild-type mice. This was paralleled by activation of hypoxia signaling, upregulation of HIF-1α and Angiopietin-2, and oxidative stress increase. These alterations did not result in kidney disease. However, when <i>Sirt3</i>-deficient mice were exposed to the nephrotoxic stimulus Adriamycin (ADR) they developed aggravated endothelial rarefaction, altered VEGFA signaling, and higher oxidative stress compared to wild-type mice receiving ADR. As a result, ADR-treated <i>Sirt3</i>-deficient mice experienced a more severe injury with exacerbated albuminuria, podocyte loss and fibrotic lesions. These data suggest that SIRT3 is a crucial regulator of renal vascular homeostasis and its dysregulation is a predisposing factor for kidney disease. By extension, our findings indicate SIRT3 as a pharmacologic target in progressive renal disease whose treatments are still imperfect.</p>
Effect of older age and/or ACL injury on the dose–response relationship between ambulatory load magnitude and immediate load-induced change in serum cartilage oligomeric matrix protein
<p>The data presented here was used in the models in the pulication doi <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jshs.2024.100993" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.jshs.2024.100993</span></span></a>.</p> <p>The purpose of this study was to assess the influence of age, anterior cruciate ligament (ACL) injury, and sex on resting sCOMP concentration, on the immediate load-induced sCOMP kinetics after a 30-minute treadmill walking stress, and on the dose-response relationship between ambulatory load magnitude and the load-induced sCOMP change.</p> <p>Overall, data of 85 participants in four groups (20–30 years healthy, HEA<sub>20–30</sub>, n=24; 20–30 years ACL-injured, ACL<sub>20–30</sub>, n=23; 40–60 years healthy, HEA<sub>40–60</sub>, n=23; 40–60 years ACL-injured, ACL<sub>40–60</sub>, n=15) were included in this dataset. ACL injured participants suffered from an ACL injury 2-10 years prior to inclusion. The dateaset includes, patient data and serum cartilage oligomeric matrix protein (sCOMP) concentration measured on three testdays (m1, m2, m3) immediately before (t0) and immediately after 30 minutes of treadmill walking (t1) where the ambulatory loads were 80% bodyweight (BW), 100% BW or 120% BW (block randomized order). This dateset represents a subset of data collected in the parent study.</p> <p>The detailed experimental protocol of the parent study has been described in Herger, S., Vach, W., Nüesch, C., Liphardt, A. M., Egloff, C., & Mündermann, A. (2022). Dose-response relationship of in vivo ambulatory load and mechanosensitive cartilage biomarkers—The role of age, tissue health and inflammation: A study protocol. <em>PLoS One, 17</em>(8), e0272694. <a href="https://doi.org/10.1371/journal.pone.0272694">https://doi.org/10.1371/journal.pone.0272694</a></p>
RNA sequencing of macrophages co-cultured with MSCs and RNA sequencing of alveolar macrophages from mice with lung injury treated with MSCs
<p>RNA sequencing of macrophages co-cultured with MSCS Table 5</p> <p>RNA sequencing of alveolar macrophages from mice with lung injury treated with MSCS Table 8</p>
SPT results - Simulation of zonation-function relationships in the liver using coupled multiscale models: Application to drug-induced liver injury
<p>Results of the study "Simulation of zonation-function relationships in the liver using coupled multiscale models: Application to drug-induced liver injury"</p>
High resolution 3D reconstruction of regenerating nerve within a chitosan conduit 7 days after injury and repair
<p><strong>Video S1:</strong> high resolution 3D reconstruction of 7 consecutive 50 µm thick sections labelled with Reca1 (red, endothelial cell marker) and S100β (green, Schwann cell marker).</p>
Figure 2-Immunofluorescence staining of regenerating nerves 7, 14, 21, and 28 days after the injury and repair.
<p>Figure 2- Immunofluorescence staining of regenerating nerves 7, 14, 21, and 28 days after the injury and repair. One section every millimeter labeled with Reca1 (red, endothelial cell marker), S100β (green, Schwann cell marker), and Neurofilament/NF (white, axon marker) to follow the nerve regeneration progression. The single labeling is shown in Figures S1 (NF), S2 (S100β), and S3 (Reca1) in the published manuscript. The dotted line delimits the region containing cell nuclei identified with DAPI (as in Figure 1B). Scale bar: 400 µm. It is possible to zoom in on this high-resolution version of this figure to appreciate the interactions between the different structures.</p> <p> </p>
Raw Data for the article: Donor Preconditioning with Inhaled Sevoflurane Mitigates the Effects of Ischemia-Reperfusion Injury in a Swine Model of Lung Transplantation
<p>Primary graft dysfunction (PGD) and ischemia-reperfusion injury (IRI) occur in up to 30% of patients undergoing lung transplantation and may impact on the clinical outcome. Several strategies for the prevention and treatment of PGD have been proposed, but with limited use in clinical practice. In this study, we investigate the potential application of sevoflurane (SEV) preconditioning to mitigate IRI after lung transplantation. The study included two groups of swines (preconditioned and not preconditioned with SEV) undergoing left lung transplantation after 24-hour of cold ischemia. Recipients' data was collected for 6 hours after reperfusion. Outcome analysis included assessment of ventilatory, hemodynamic, and hemogasanalytic parameters, evaluation of cellularity and cytokines in BAL samples, and histological analysis of tissue samples. Hemogasanalytic, hemodynamic, and respiratory parameters were significantly favorable, and the histological score showed less inflammatory and fibrotic injury in animals receiving SEV treatment. BAL cellular and cytokine profiling showed an anti-inflammatory pattern in animals receiving SEV compared to controls. In a swine model of lung transplantation after prolonged cold ischemia, SEV showed to mitigate the adverse effects of ischemia/reperfusion and to improve animal survival. Given the low cost and easy applicability, the administration of SEV in lung donors may be more extensively explored in clinical practice.</p>
Computational analysis of cortical neuronal excitotoxicity in a large animal model of neonatal brain injury
<p>This is the dataset accompanying the manuscript:</p> <p><strong>"Computational Analysis of Cortical Neuronal Excitotoxicity in a Large Animal Model of Neonatal Brain Injury"</strong></p> <p>Panagiotis Kratimenos<sup>1,2,5 </sup>*, Abhya Vij<sup>5</sup>, Robinson Vidva<sup>6</sup>, Ioannis Koutroulis<sup>3,4,5</sup>, Maria Delivoria-Papadopoulos<sup>7</sup>**, Vittorio Gallo<sup>1,5</sup>, and Aaron Sathyanesan<sup>1,5</sup>*</p> <p><em><sup>1</sup></em><em>Center for Neuroscience Research, Children’s National Research Institute, Children’s National Hospital, Washington DC, USA</em></p> <p><em><sup>2</sup></em><em>Department of Pediatrics, Division of Neonatology, Children’s National Hospital, Washington DC, USA</em></p> <p><em><sup>3</sup></em><em>Department of Pediatrics, Division of Emergency Medicine, Children’s National Hospital, Washington, DC, USA</em></p> <p><em><sup>4</sup></em><em>Center for Genetic Medicine Research, Children’s National Research Institute and Department of Genomics and Precision Medicine, George Washington University School of Medicine and Health Sciences, Washington, DC, USA</em></p> <p><em><sup>5</sup></em><em>George Washington University School of Medicine and Health Sciences, Washington DC, USA</em></p> <p><em><sup>6</sup></em><em>Digirobi Solutions, Bengaluru, Karnataka, India</em></p> <p><em><sup>7</sup></em><em>Department of Pediatrics, Drexel University College of Medicine, Philadelphia, PA, USA</em></p> <p>*Corresponding Authors:</p> <p>Panagiotis Kratimenos, MD, PhD: <a href="mailto:panagiotis.kratimenos@childrensnational.org">panagiotis.kratimenos@childrensnational.org</a></p> <p>Aaron Sathyanesan, PhD: <a href="mailto:asathyanesan@childrensnational.org">asathyanesan@childrensnational.org</a></p> <p>111 Michigan Avenue, Washington, DC, 20010, USA</p>
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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.