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2,021 results for “non-invasive”
The physiological effects of non-invasive brain stimulation fundamentally differ across the human cortex
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Finite element method (FEM) models for translational research in non-invasive brain stimulation
<p>Finite element method (FEM) models for non-invasive brain stimulation modeling using SimNIBS or other compatible software.<br> The mouse and monkey models are described in detail in Alekseichuk et al., Comparative modeling of transcranial magnetic and electric stimulation in mouse, monkey, and human, NeuroImage 2019.<br> The Petri dish model follows a typical experimental setup for in-vitro TMS, similar to what is described in Lenz et al. Repetitive magnetic stimulation induces plasticity of inhibitory synapses, Nature Communications 2016.<br> <br> The following files are included:<br> 1. Brain tissue slice in a Petri dish.<br> 2. Normal adult male nude mouse "Digimouse" (brain volume of 0.38 cm3).<br> 3. Normal adult male capuchin monkey "S" (brain volume of 68.31 cm3).<br> <br> The models include the following tissues (coded with numbers):<br> 1. White matter volume<br> 2. Grey matter volume<br> 3. CSF volume<br> 4. Skull volume<br> 5. Soft tissues volume<br> 8. Eyeballs volume<br> 1001. White matter outer surfaces<br> 1002. Grey matter outer surfaces<br> 1003. CSF outer surfaces<br> 1004. Skull outer surfaces<br> 1005. Soft tissues outer surfaces<br> 1008. Eyeballs outer surfaces<br> <br> With any questions, please, contact the corresponding authors of the relevant papers or <a href="mailto:aopitz@umn.edu">aopitz@umn.edu</a> (Alexander Opitz).</p>
Is there a non-invasive biomarker for the early detection of ovarian torsion? A systematic review and meta-analysis
<p>We have performed a systematic review and meta-analysis and identified multiple biomarkers that warrant further study as part of a broader diagnostic panel for ovarian torsion. These include SCUBE1, s-DD, IL-6, IMA and TNF-a. </p>
Non-invasive modulation of human corticostriatal activity [Dataset]
<p>This dataset contains resting-state functional MRI data used in the study "Non-invasive modulation of human corticostriatal activity" (Caballero-Insaurriaga et al, PNAS, 2023).</p> <p>In this study two datasets were used: one from a transcranial static-magnetic-field stimulation (tSMS) experiment (tSMS20) and another one from the Human Connectome Project (HCP100). The tSMS20 dataset was originally acquired for a previous study tSMS over the Supplementary Motor Area (Pineda-Pardo et al, Commun Biol, 2019). The regions used in the study are also provided.</p> <p>As for the tSMS20 dataset, the stimulation protocol consisted of 30-minute tSMS using a single magnet placed over the supplementary motor area (SMA). Each subject underwent two stimulation sessions (real and sham) in two separate days, whose order was randomized. In each session, structural MRI was acquired before tSMS, and resting-state fMRI before and after. Structural images were T1-weighted (T1w), with 1 mm isotropic voxel. Functional data was acquired in 10 minutes-long sessions, TR/TE 2400/30 ms (250 volumes per session), with 3mm isotropic voxel. The preprocessed resting-state fMRI data are included in this repository (see dataset_description.txt file and Pineda-Pardo et al, Commun Biol, 2019 for more details)</p> <p>As for the HCP100 dataset, only the subject list is included, as data are already publicly available from the HCP initiative.</p> <p>If you use this data in a publication, please cite:</p> <p>Pineda-Pardo, J. A., Obeso, I., Guida, P., Dileone, M., Strange, B. A., Obeso, J. A., Oliviero, A. & Foffani, G. Static magnetic field stimulation of the supplementary motor area modulates resting-state activity and motor behavior. <em>Communications Biology</em> <strong>2,</strong> (2019)</p> <p>Caballero-Insaurriaga, J., Pineda-Pardo, J. A., Obeso, I., Oliviero, A. & Foffani, G. Non-invasive modulation of human corticostriatal activity. <em>Proceedings of the National Academy of Sciences of the United States of America</em> (2023)</p>
Open data repository, Knab et al., Prediction of stroke outcome in mice based on non-invasive MRI and behavioral testing
<p><strong>Open data repository, Knab et al., Prediction of stroke outcome in mice based on non-invasive MRI and behavioral testing</strong></p> <p><strong>Latest version of files: repository_v2.0.zip, Behavior Data_v2.0.xlsx and MRI IDs Testing&Replication Cohort.xlsx (please ignore repository.zip)</strong></p> <p>Open data repository Knab et al. Prediction of stroke outcome in mice based on non-invasvive MRI and behavioral testing</p> <p>Open code and documentation of prediction models available via <a href="https://github.com/major-s/mouse-mcao-outcome-predictor">https://github.com/major-s/mouse-mcao-outcome-predictor</a></p> <p><strong>Content:</strong></p> <p>README.txt</p> <p>This information</p> <p><strong>dat</strong></p> <p>Contains MRI data in NIFTI format and secondary data from atlas registration. For documentation of atlas registration files see https://pubmed.ncbi.nlm.nih.gov/28829217/<br>Files used for the manuscript:<br>t2.nii: t2 weighted image acquired 24 h post stroke<br>masklesion.nii: manually delineated lesion<br>x_masklesion.nii: lesion in atlas space<br>ix_ANO.nii: Allen brain atlas in native space (i.e. matching t2.nii)<br>Lesion volume was calculated by volume of voxels unequal 0 in x_masklesion.nii<br>Overlap of regions defined by ix_ANO.nii with masklesion.nii were used for calculating percent damage in each atlas region</p> <p><strong>prediction_models</strong></p> <p>Contains separated training and test data as xlsx and csv files with lesion volumes in cubic mm of the Allen brain atlas space, percent damage per atlas region and behavioral data. The training data was used as input for training prediction models in MATLAB, the results were created using the test data.<br>The files have following sturcture:<br>Column 1: animal ID<br>Columns 2-537: MRI regions (column title corresponds to the region number as used in the Allen common coordinate framework)<br>Column 538: lesion volume<br>Column 539: initial performance (subacute deficit) = mean performance/deficit on days 2-6<br>Column 540: mean performance/deficit on days 2-6 = initial performance (subacute deficit) - this column equals column 539 but has different header which was used to train the residual from initial deficit<br>Column 541: residual performance/deficit<br>Column 542: test or training group<br>Consecutive rows contain data for each animal specified by the animal id</p> <p>The repository also contains all trained models, prediction results for the test data and tables with resulting median absolute error (MedAE) and 5th, 25th, 75th and 95 absolute error quantiles for each model.<br>The model files end with '_models.mat' and contain 50 independently trained models each. Each model version is specified by number 1-50.<br>The result files end with '_test_results.mat' or '_test_results.xlsx', files with MedAE and quantiles end with '_test_errors.xlsx' or '_test_errors.csv. The common part of filenames specifies the used paradigm<br>Folder 'subacute deficit prediction' contains:<br> - initial_performance_from_lesion_volume: prediction of subacute deficit using lesion volume<br> - initial_performance_from_segmented_mri: prediction of subacute deficit using segmented mri<br>Folder 'long-term outcome prediction' contains:<br> - lesion_volume: prediction of residual deficit using lesion volume<br> - segmented_mri: prediction of residual deficit using segmented_mri<br> - initial_performance: prediction of residual deficit using subacute deficit<br>Folder 'mri_inc_oob_imp' contains models trained using increasing number of mri segments sorted according to the out-of-bag importance. The number of used segments is given in the file name. The models, results and errors are separated in subfolders.</p> <p>Files with equal file name and different extension always contain the same data</p> <p><strong>templates</strong><br>Allen atlas, template, brain mask, hemisphere masks, tissue probability masks in NIFTI format including annotations of region IDs and parameter.m file for use in MATLAB toolbox ANTx2<br> </p>
The open D1NAMO dataset: A multi-modal dataset for research on non-invasive type 1 diabetes management
<p>The description of the dataset is available at <a href="https://doi.org/10.1016/j.imu.2018.09.003">https://doi.org/10.1016/j.imu.2018.09.003</a></p> <p>The usage of wearable devices has gained popularity in the latest years, especially for health-care and well being. Recently there has been an increasing interest in using these devices to improve the management of chronic diseases such as diabetes. The quality of data acquired through <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/wearable-sensor">wearable sensors</a> is generally lower than what medical-grade devices provide, and existing datasets have mainly been acquired in highly controlled clinical conditions. In the context of the <em>D1NAMO</em> project — aiming to detect <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/glycemic">glycemic</a> events through non-invasive <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/ecg-abnormality">ECG pattern</a> analysis — we elaborated a dataset that can be used to help developing health-care systems based on wearable devices in non-clinical conditions. This paper describes this dataset, which was acquired on 20 healthy subjects and 9 patients with type-1 diabetes. The acquisition has been made in real-life conditions with the <em>Zephyr BioHarness 3</em> wearable device. The dataset consists of <em>ECG</em>, <em>breathing</em>, and <em><a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/accelerometer">accelerometer</a></em> signals, as well as <em>glucose</em> measurements and annotated <em>food pictures</em>. We open this dataset to the scientific community in order to allow the development and evaluation of diabetes management algorithms.</p>
Data from: Non-invasive Assessment of Cartilage Damage of the Human Knee using Acoustic Emission Monitoring: a Pilot Cadaver Study
<p>This dataset accompanies the following article: "Non-invasive Assessment of Cartilage Damage of the Human Knee using Acoustic Emission Monitoring: a Pilot Cadaver Study," in <em>IEEE Transactions on Biomedical Engineering</em>, doi: 10.1109/TBME.2023.3263388.</p> <p>Knee acoustic emissions (AE) recorded in the 100-450 kHz and 15-200kHz frequency ranges from a cadaver specimen knee in flexion/extension. Four stages of artificially inflicted cartilage damage and two sensor positions were investigated. </p> <p><em><strong>Stages of artificially inflicted cartilage damage:</strong></em> the cartilage surface damage on the medial compartment, KL III; the cartilage surface damage on the medial compartment plus patellofemoral surface, KL III; the cartilage surface damage on the medial compartment plus on the patellofemoral surface KL IV; the cartilage surface damage on the medial compartment plus on the patellofemoral surface and lateral compartment.</p> <p><strong><em>Sensor positions</em></strong>: medial and lateral knee</p>
3DNIV/3DNIV: A Novel Dual Non-Invasive Ventilator Continuous Positive Airway Pressure Non-Aerosolization Circuit for Emergency Use in the COVID-19 Pandemic
<p>The COVID19 pandemic is a public health emergency of unprecedented scale. The surge in clinical cases of patients with severe respiratory illness has overwhelmed the traditional capacity of healthcare systems worldwide. Continuous Positive Airway Pressure (CPAP) delivered through Non-Invasive Ventilation (NIV) has been shown to be useful in caring for patients with COVID19. In particular patients with early stage milder acute hypoxemic respiratory failure can benefit from NIV CPAP therapy, though there is an acknowledged risk of COVID19 aerosolization with traditional circuit use. Furthermore, given the surge in clinical care demand, there is an acute global shortage of ventilators, including NIV devices and therefore innovative methods are needed to increase NIV capacity and ameliorate infectious aerosolization. This work outlines an emergency use modified dual NIV CPAP Circuit that uses a 3D printed splitter designed to work with traditional international NIV CPAP tubing standards and a 3D printed respiratory face mask knuckle to allow for distal expiratory breath exhalation through a viral filter rather than through an open to air proximal valve, which is the traditional NIV CPAP configuration. We expect that this work will increase global NIV CPAP capacity and ameliorate aerosolization of COVID19 in patients undergoing therapy in an emergency scenario.</p>
Figure 1 in Non-invasive genetic study and population monitoring of the brown bear (Ursus arctos) (Mammalia: Ursidae) in Kastoria region - Greece
Figure 1. The study area in Kastoria region and capture locations (red dots) for the 75 living bears.
Data and results for manuscript "Multi-frequency electrical impedance tomography as a non-invasive tool to characterize and monitor crop root systems "
<p>Root systems are essential in nutrient uptake and translocation, but are difficult to characterize non-invasively with existing methods. We propose electrical impedance tomography (EIT) as a new tool for the imaging and monitoring of crop root systems. In a laboratory experiment we demonstrate the capability of the method to capture physiological responses of root systems with high spatial and temporal resolution. We conclude that EIT is a promising functional imaging technique for crop roots.</p> <p>This package contains measured raw EIT data, electrical imaging results, spectral results from the Debye decomposition, and the Python scripts used to generate the plots in the manuscript.</p>
Data from: Non-invasive age estimation based on fecal DNA using methylation-sensitive high-resolution melting for Indo-Pacific bottlenose dolphins
<p class="MsoNormal"><span>Age is necessary information for the study of life history of wild animals. A general method to estimate the age of odontocetes is counting dental growth layer groups (GLGs). However, this method is highly invasive as it requires the capture and handling of individuals to collect their teeth.</span><span> Recently, the development of DNA-based age </span><span>estimation methods has been actively studied as an alternative to such invasive methods, of which many have used biopsy samples. However, if DNA-based age estimation can be developed from fecal samples, age estimation can be performed without touching or disrupting individuals, thus establishing an entirely non-invasive method. </span><span>We developed an age estimation model using the methylation rate of two gene regions, <em>GRIA2</em> and <em>CDKN2A,</em> measured through methylation-sensitive high-resolution melting (MS-HRM) from fecal samples of wild Indo-Pacific bottlenose dolphins (<em>Tursiops aduncus</em>). The age of individuals was known through conducting longitudinal individual identification surveys underwater. Methylation rates were quantified from 36 samples. Both gene regions showed a significant correlation between age and methylation rate. The age estimation model was constructed based on the methylation rates of both genes which achieved sufficient accuracy (after LOOCV: MAE = 5.08, <em>R<sup>2</sup></em> = 0.34) for the ecological studies of the Indo-Pacific bottlenose dolphins, with a lifespan of 40-50 years. This is the first study to report the use of non-invasive fecal samples to estimate the age of marine mammals.</span></p>
Data from: Wildlife fecal microbiota exhibit community stability across a semi-controlled longitudinal non-invasive sampling experiment
<p>Wildlife microbiome studies are being used to assess microbial links with animal health and habitat. The gold standard of sampling microbiomes directly from captured animals is ideal for limiting potential abiotic influences on microbiome composition, yet fails to leverage the many benefits of non-invasive sampling. Application of microbiome-based monitoring for rare, endangered, or elusive species creates a need to non-invasively collect scat samples shed into the environment. Since controlling sample age is not always possible, the potential influence of time-associated abiotic factors was assessed. To accomplish this, we analyzed partial 16S rRNA genes of fecal metagenomic DNA sampled non-invasively from Rocky Mountain elk (<em>Cervus canadensis</em>) near Yellowstone National Park. We sampled pellet piles from four different elk, then aged them in a natural forest plot for 1, 3, 7, and 14 days, with triplicate samples at each time point (i.e., a blocked, repeat measures (longitudinal) study design). We compared microbiomes of each elk through time with point estimates of diversity, bootstrapped hierarchical clustering of samples, and a version of ANOVA–simultaneous components analysis (ASCA) with PCA (LiMM-PCA) to assess the variance contributions of time, individual and sample replication. Our results showed community stability through days 0, 1, 3 and 7, with a modest but detectable change in abundance in only 2 genera (<em>Bacteroides</em> and <em>Sporobacter</em>) at day 14. The total variance explained by time in our LiMM-PCA model across the entire 2-week period was not statistically significant (p>0.195) and the overall effect size was small (<10% variance) compared to the variance explained by the individual animal (p<0.0005; 21% var.). We conclude that non-invasive sampling of elk scat collected within one week during winter/early spring provides a reliable approach to characterize microbiome composition in a 16S rDNA survey and that sampled individuals can be directly compared across unknown time points with minimal bias. Further, point estimates of microbiome diversity were not mechanistically affected by sample age. Our assessment of samples using bootstrap hierarchical clustering produced clustering by animal (branches) but not by sample age (nodes). These results support greater use of non-invasive microbiome sampling to assess ecological patterns in animal systems.</p>
Fig. 3 in Non-invasive detection of Orthohalarachne attenuata (Banks, 1910) and Orthohalarachne diminuata (Doetschman, 1944) (Acari: Halarachnidae) in free-ranging synanthropic South American sea lions Otaria flavescens (Shaw, 1800)
Fig. 3. Non-invasive diagnostic techniques for the detection of Orthohalarachne spp. (A) Sampling of sneezed mucus droplets and mucous nasal discharges from substrates of resting places. (B) Metal clothes hanger bent to form a square frame, covered with clingfilm and mounted on a telescopic rod and (C) sterile petri dishes mounted on a telescopic rod to directly collect sputum samples from the animals.
Fig. 1 in Non-invasive detection of Orthohalarachne attenuata (Banks, 1910) and Orthohalarachne diminuata (Doetschman, 1944) (Acari: Halarachnidae) in free-ranging synanthropic South American sea lions Otaria flavescens (Shaw, 1800)
Fig. 1. Sampling area of Orthohalarachne spp. of South American sea lions in Valdivia, Chile. The exact sampling location is shown in the section (upper-left) as a red-framed black star. Map created with QGIS (https://qgis.org/en/site/) and map data used from OpenStreetMap (openstreetmap.org/copyright). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5 in Non-invasive detection of Orthohalarachne attenuata (Banks, 1910) and Orthohalarachne diminuata (Doetschman, 1944) (Acari: Halarachnidae) in free-ranging synanthropic South American sea lions Otaria flavescens (Shaw, 1800)
Fig. 5. Haplotype (TCS) networks of Orthohalarachne diminuata and Orthohalarachne attenuata based on 16S rDNA sequences. (A) Network analysis based on countries of origin, (B) network analysis based on the pinniped host species (CSL=California sea lion, GFS = Guadalupe fur seal, NFS=Northern fur seal, SAS=South American sea lion). For better visualization a combined network analysis of Or. attenuata and Or. diminuata sequences is shown, however, the calculated distance (48 mutations) between species was clipped. Or. attenuata haplotypes are encircled in black boxes with dashed lines, whereas Or. diminuata haplotypes are encircled in light grey boxes with dashed lines based on estimated MOTUs by ABGD.
Fig. 2 in Non-invasive detection of Orthohalarachne attenuata (Banks, 1910) and Orthohalarachne diminuata (Doetschman, 1944) (Acari: Halarachnidae) in free-ranging synanthropic South American sea lions Otaria flavescens (Shaw, 1800)
Fig. 2. Nasal discharge in three individuals (A, B, C) of the "urban" colony of South American sea lions Otaria flavescens in Valdivia, Chile.
Fig. 4 in Non-invasive detection of Orthohalarachne attenuata (Banks, 1910) and Orthohalarachne diminuata (Doetschman, 1944) (Acari: Halarachnidae) in free-ranging synanthropic South American sea lions Otaria flavescens (Shaw, 1800)
Fig. 4. Larval stages of (A) Orthohalarachne attenuata and (B) Orthohalarachne diminuata showing distinct differences in idiosoma length.
Data from: Non-invasive estimation of absorbed ionizing radiation dose in mice using Near-Infrared Spectroscopy (NIRS) and aquaphotomics
<p>Accurate measurement of ionizing radiation exposure, whether therapeutic or accidental, is of utmost importance in various scenarios. This paper presents a study that addresses this critical need by utilizing near-infrared (NIR) spectroscopy and aquaphotomics to estimate radiation dose exposure in mouse models subjected to X-ray irradiation. The analysis of NIR spectra acquired from the mouse abdomen enabled non-invasive estimation of radiation doses ranging from 0.5 to 6.5 Gy, immediately following the irradiation exposure. The findings were consistent with the impact of total body irradiation in mice, as evidenced by measures such as animal survival rate, alterations in body weight observed over a 30-day post-exposure period, and changes in hematocrit levels. The spectroscopic measurements were based on detecting changes in the molecular structure of body water after radiation exposure, utilizing the water spectral pattern as a multidimensional biomarker. While further validation in nonhuman primates is necessary, the findings demonstrate a simple, non-destructive, and rapid method that holds promise for the estimation of radiation exposure across a range of doses, applicable to both clinical applications and catastrophic radiation events. These advancements in radiation dose quantification have significant implications for the timely and precise assessment of radiation exposure in humans.</p>
Novel Peptide-Based PET Probe for Non-invasive Imaging of C-X-C Chemokine Receptor Type 4 (CXCR4) in Tumors
<p>These are RAW data datasets of the following final paper</p> <p>Trotta, A.M., Aurilio, M., D'Alterio, C., Ieranò, C., Di Martino, D., Barbieri, A., Luciano, A., Gaballo, P., Santagata, S., Portella, L., Tomassi, S., Marinelli, L., Sementa, D., Novellino, E., Lastoria, S., Scala, S., Schottelius, M., Di Maro, S.</p> <p>Novel Peptide-Based PET Probe for Non-invasive Imaging of C-X-C Chemokine Receptor Type 4 (CXCR4) in Tumors, (2021) Journal of Medicinal Chemistry, 64 (6), pp. 3449-3461. ISSN 00222623</p> <p>https://doi.org/10.1021/acs.jmedchem.1c00066</p> <p>Abstract</p> <p>The recently reported CXCR4 antagonist 3 (Ac-Arg-Ala-[DCys-Arg-2Nal-His-Pen]-CO2H) was investigated as a molecular scaffold for a CXCR4-targeted positron emission tomography (PET) tracer. Toward this end, 3 was functionalized with 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) and 1,4,7-triazacyclononanetriacetic acid (NOTA). On the basis of convincing affinity data, both tracers, [68Ga]NOTA analogue ([68Ga]-5) and [68Ga]DOTA analogue ([68Ga]-4), were evaluated for PET imaging in “in vivo” models of CHO-hCXCR4 and Daudi lymphoma cells. PET imaging and biodistribution studies revealed higher CXCR4-specific tumor uptake and high tumor/background ratios for the [68Ga]NOTA analogue ([68Ga]-5) than for the [68Ga]DOTA analogue ([68Ga]-4) in both in vivo models. Moreover, [68Ga]-4 and [68Ga]-5 displayed rapid clearance and very low levels of accumulation in all nontarget tissues but the kidney. Although the high tumor/background ratios observed in the mouse xenograft model could partially derive from the hCXCR4 selectivity of [68Ga]-5, our results encourage its translation into a clinical context as a novel peptide-based tracer for imaging of CXCR4-overexpressing tumors.</p> <p> </p> <p> </p>
Urinary biomarkers for the non-invasive diagnosis of endometriosis: a systematic literature review
<p>Raw dataset from a systematic literature review performed until August 2021 in which the research question was 'Are there urine biomarkers sensitive and specific enough for endometriosis detection?' and the Medical Subject Heading (MeSH) terms were (endometrios*) AND (urin*). </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.