Dynamic footprints of ?-synucleinopathic mice recorded by CatWalk gait analysis.
Ontology highlight
ABSTRACT:
SUBMITTER: Timotius IK
PROVIDER: S-EPMC5988224 | biostudies-other | 2018 Apr
REPOSITORIES: biostudies-other
Publications
Dynamic footprints of α-synucleinopathic mice recorded by CatWalk gait analysis.
Timotius Ivanna K IK Canneva Fabio F Minakaki Georgia G Pasluosta Cristian C Moceri Sandra S Casadei Nicolas N Riess Olaf O Winkler Jürgen J Klucken Jochen J von Hörsten Stephan S Eskofier Bjoern B
Data in brief 20180103
Characterizing gait is important in the study of movement disorders, also in clinical mouse models. Gait data are therefore necessary for the development of gait analysis methods and the study of diseases. This article presents gait data of two α-synucleinopathic transgenic mouse models and their non-transgenic littermate, backcrossed into the C57BL/6N genetic background. The animal gait was recorded using CatWalk system, which provides the information for each run about the paw positions, paw p ...[more]
Similar Datasets
Project description:Bipedalism is a key adaptation that shaped human evolution, yet the timing and nature of its evolution remain unclear. Here we use new experimentally based approaches to investigate the locomotor mechanics preserved by the famous Pliocene hominin footprints from Laetoli, Tanzania. We conducted footprint formation experiments with habitually barefoot humans and with chimpanzees to quantitatively compare their footprints to those preserved at Laetoli. Our results show that the Laetoli footprints are morphologically distinct from those of both chimpanzees and habitually barefoot modern humans. By analysing biomechanical data that were collected during the human experiments we, for the first time, directly link differences between the Laetoli and modern human footprints to specific biomechanical variables. We find that the Laetoli hominin probably used a more flexed limb posture at foot strike than modern humans when walking bipedally. The Laetoli footprints provide a clear snapshot of an early hominin bipedal gait that probably involved a limb posture that was slightly but significantly different from our own, and these data support the hypothesis that important evolutionary changes to hominin bipedalism occurred within the past 3.66 Myr.
| S-EPMC5013756 | biostudies-literature
Project description:BackgroundOsteoarthritis (OA) is a common problem in the older population. To reduce pain and stress in the affected knee joint compartment, a functional knee brace is often prescribed by physicians to protect it from high loads.ObjectivesAn instrumented gait analysis should evaluate how the 4-point knee orthosis for varus or valgus load relief (M.4s OA) changes the kinematics of the knee, especially in the frontal plane.Methods17 healthy participants took part and were analyzed with an inertial sensor system (MyoMotion) giving continuous, objective information on the anatomical angles. The measurements were made both without wearing a knee brace and with the brace in different settings.ResultsThe results show a significant reduction in the maximum knee abduction and raised knee adduction. The knee brace, with a strong adjustment in varus or valgus orientation, caused a shift of maximum ab-/adduction in the proposed direction in 69% and 75% of the dynamic tests, respectively. The knee motion in the frontal plane shows individual movement patterns.ConclusionThe use of the brace leads to significant changes in the knee's movement. Patient-specific movement patterns may explain different effects of functional knee braces on individual persons. Inertial sensors have been shown to be a low-cost, easy-to-use option for individual movement analysis and further personalized therapy.
| S-EPMC7482934 | biostudies-literature
Project description:In this report we present a mobile brain/body imaging (MoBI) dataset that allows study of source-resolved cortical dynamics supporting coordinated gait movements in a rhythmic auditory cueing paradigm. Use of an auditory pacing stimulus stream has been recommended to identify deficits and treat gait impairments in neurologic populations. Here, the rhythmic cueing paradigm required healthy young participants to walk on a treadmill (constant speed) while attempting to maintain step synchrony with an auditory pacing stream and to adapt their step length and rate to unanticipated shifts in tempo of the pacing stimuli (e.g., sudden shifts to a faster or slower tempo). High-density electroencephalography (EEG, 108 channels), surface electromyography (EMG, bilateral tibialis anterior), pressure sensors on the heel (to register timing of heel strikes), and goniometers (knee, hip, and ankle joint angles) were concurrently recorded in 20 participants. The data is provided in the Brain Imaging Data Structure (BIDS) format to promote data sharing and reuse, and allow the inclusion of the data into fully automated data analysis workflows.
| S-EPMC6797727 | biostudies-literature
Project description:As the challenge of mental health problems such as anxiety and depression increasing today, more convenient, objective, real-time assessing techniques of mental state are in need. The Microsoft Kinect camera is a possible option for contactlessly capturing human gait, which could reflect the walkers' mental state. So we tried to propose a novel method for monitoring individual's anxiety and depression based on the Kinect-recorded gait pattern. In this study, after finishing the 7-item Generalized Anxiety Disorder Scale (GAD-7) and the 9-item Patient Health Questionnaire (PHQ-9), 179 participants were required to walked on the footpath naturally while shot by the Kinect cameras. Fast Fourier Transforms (FFT) were conducted to extract features from the Kinect-captured gait data after preprocessing, and different machine learning algorithms were used to train the regression models recognizing anxiety and depression levels, and the classification models detecting the cases with specific depressive symptoms. The predictive accuracies of the regression models achieved medium to large level: The correlation coefficient between predicted and questionnaire scores reached 0.51 on anxiety (by epsilon-Support Vector Regression, e-SVR) and 0.51 on depression (by Gaussian Processes, GP). The predictive accuracies could be even higher, 0.74 on anxiety (by GP) and 0.64 on depression (by GP), while training and testing the models on the female sample. The classification models also showed effectiveness on detecting the cases with some symptoms. These results demonstrate the possibility to recognize individual's questionnaire measured anxiety/depression levels and some depressive symptoms based on Kinect-recorded gait data through machine learning method. This approach shows the potential to develop non-intrusive, low-cost methods for monitoring individuals' mental health in real time.
| S-EPMC6530855 | biostudies-literature
Project description:Translation is dynamically regulated during cell development and stress response. In order to detect actively translated open reading frames (ORFs) and dynamic cellular translation events, we have developed a computational method, RiboWave, to process ribosome profiling data. RiboWave utilizes wavelet transform to denoise the original signal by extracting 3-nt periodicity of ribosomes and precisely locate their footprint denoted as Periodic Footprint P-site (PF P-site). Such high-resolution footprint is found to capture the full track of actively elongating ribosomes, from which translational landscape can be explicitly characterized. We compare RiboWave with several published methods, like RiboTaper, ORFscore and RibORF, and found that RiboWave outperforms them in both accuracy and usage when defining actively translated ORFs. Moreover, we show that PF P-site derived by RiboWave shows superior performance in characterizing the dynamics and complexity of cellular translatome by accurately estimating the abundance of protein levels, assessing differential translation and identifying dynamic translation frameshift.
| S-EPMC6182183 | biostudies-literature
Project description:The Hereditary Spastic Paraplegias (HSP) are a group of heterogeneous disorders with a wide spectrum of underlying neural pathology, and hence HSP patients express a variety of gait abnormalities. Classification of these phenotypes may help in monitoring disease progression and personalizing therapies. This is currently managed by measuring values of some kinematic and spatio-temporal parameters at certain moments during the gait cycle, either in the doctor´s surgery room or after very precise measurements produced by instrumental gait analysis (IGA). These methods, however, do not provide information about the whole structure of the gait cycle. Classification of the similarities among time series of IGA measured values of sagittal joint positions throughout the whole gait cycle can be achieved by hierarchical clustering analysis based on multivariate dynamic time warping (DTW). Random forests can estimate which are the most important isolated parameters to predict the classification revealed by DTW, since clinicians need to refer to them in their daily practice. We acquired time series of pelvic, hip, knee, ankle and forefoot sagittal angular positions from 26 HSP and 33 healthy children with an optokinetic IGA system. DTW revealed six gait patterns with different degrees of impairment of walking speed, cadence and gait cycle distribution and related with patient's age, sex, GMFCS stage, concurrence of polyneuropathy and abnormal visual evoked potentials or corpus callosum. The most important parameters to differentiate patterns were mean pelvic tilt and hip flexion at initial contact. Longer time of support, decreased values of hip extension and increased knee flexion at initial contact can differentiate the mildest, near to normal HSP gait phenotype and the normal healthy one. Increased values of knee flexion at initial contact and delayed peak of knee flexion are important factors to distinguish GMFCS stages I from II-III and concurrence of polyneuropathy.
| S-EPMC5843164 | biostudies-literature
Project description:Neuropathic pain as a symptom of sensory nerve damage is a frequent side effect of chemotherapy. The most common behavioral observation in animal models of chemotherapy induced polyneuropathy is the development of mechanical allodynia, which is quantified with von Frey filaments. The data from one study, however, cannot be easily compared with other studies owing to influences of environmental factors, inter-rater variability and differences in test paradigms. To overcome these limitations, automated quantitative gait analysis was proposed as an alternative, but its usefulness for assessing animals suffering from polyneuropathy has remained unclear. In the present study, we used a novel mouse model of paclitaxel induced polyneuropathy to compare results from electrophysiology and the von Frey method to gait alterations measured with the Catwalk test. To mimic recently improved clinical treatment strategies of gynecological malignancies, we established a mouse model of dose-dense paclitaxel therapy on the common C57Bl/6 background. In this model paclitaxel treated animals developed mechanical allodynia as well as reduced caudal sensory nerve action potential amplitudes indicative of a sensory polyneuropathy. Gait analysis with the Catwalk method detected distinct alterations of gait parameters in animals suffering from sensory neuropathy, revealing a minimized contact of the hind paws with the floor. Treatment of mechanical allodynia with gabapentin improved altered dynamic gait parameters. This study establishes a novel mouse model for investigating the side effects of dose-dense paclitaxel therapy and underlines the usefulness of automated gait analysis as an additional easy-to-use objective test for evaluating painful sensory polyneuropathy.
| S-EPMC3797113 | biostudies-literature
Project description:ObjectiveGait irregularities are prevalent in neurodevelopmental disorders (NDDs). However, there is a paucity of information on gait phenotypes in NDD experimental models. This is in part due to the lack of understanding of the normal developmental trajectory of gait maturation in the mouse.Materials and methodsUsing the DigiGait system, we have developed a quantitative, standardized, and reproducible assay of developmental gait metrics in commonly used mouse strains that can be added to the battery of mouse model phenotyping. With this assay, we characterized the trajectory of gait in the developing C57BL/6J and FVB/AntJ mouse lines.ResultsIn both lines, a mature stride consisted of 40% swing and 60% stance in the forelimbs, which mirrors the mature human stride. In C57BL/6J mice, developmental trajectories were observed for stance width, paw overlap distance, braking and propulsion time, rate of stance loading, peak paw area, and metrics of intraindividual variability. In FVB/AntJ mice, developmental trajectories were observed for percent shared stance, paw overlap distance, rate of stance loading, and peak paw area, although in different directions than C57 mice. By accounting for the impact of body length on stride measurements, we demonstrate the importance of considering body length when interpreting gait metrics.ConclusionOverall, our results show that aspects of mouse gait development parallel a timeline of normal human gait development, such as the percent of stride that is stance phase and swing phase. This study may be used as a standard reference for developmental gait phenotyping of murine models, such as models of neurodevelopmental disease.
| S-EPMC7303394 | biostudies-literature
Project description:MotivationA global map of transcription factor binding sites (TFBSs) is critical to understanding gene regulation and genome function. DNaseI digestion of chromatin coupled with massively parallel sequencing (digital genomic footprinting) enables the identification of protein-binding footprints with high resolution on a genome-wide scale. However, accurately inferring the locations of these footprints remains a challenging computational problem.ResultsWe present a dynamic Bayesian network-based approach for the identification and assignment of statistical confidence estimates to protein-binding footprints from digital genomic footprinting data. The method, DBFP, allows footprints to be identified in a probabilistic framework and outperforms our previously described algorithm in terms of precision at a fixed recall. Applied to a digital footprinting data set from Saccharomyces cerevisiae, DBFP identifies 4679 statistically significant footprints within intergenic regions. These footprints are mainly located near transcription start sites and are strongly enriched for known TFBSs. Footprints containing no known motif are preferentially located proximal to other footprints, consistent with cooperative binding of these footprints. DBFP also identifies a set of statistically significant footprints in the yeast coding regions. Many of these footprints coincide with the boundaries of antisense transcripts, and the most significant footprints are enriched for binding sites of the chromatin-associated factors Abf1 and Rap1.Supplementary informationSupplementary material is available at Bioinformatics online.
| S-EPMC2881360 | biostudies-literature
Project description:We investigated the feasibility and construct validity of the Dynamic Gait Index (DGI) in children and explored interrater and test-retest reliability.DGI performance of 10 children with fetal alcohol spectrum disorder (FASD), aged 8 to 15 years, was compared with that of 10 age- and sex-matched children with typical development (TD). Interrater reliability was evaluated for 16 children (10 TD, 6 FASD); 11 children returned for a retest (5 TD, 6 FASD).The DGI is simple for raters to learn and easy to administer in children. A Mann-Whitney U test identified a significant difference on the DGI total score between children with FASD and TD (P = .01). Interrater and test-retest reliability were promising but need to be further explored.The DGI was feasible and valid in a population of children aged 8 to 15 years with FASD and TD. Some modifications are suggested for administration of the DGI in children.
| S-EPMC3154737 | biostudies-literature