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2,021 results for “non-invasive”
Data from: Oral samples as non-invasive proxies for assessing the composition of the rumen microbial community
Microbial community analysis was carried out on ruminal digesta obtained directly via rumen fistula and buccal fluid, regurgitated digesta (bolus) and faeces of dairy cattle to assess if non-invasive samples could be used as proxies for ruminal digesta. Samples were collected from five cows receiving grass silage based diets containing no additional lipid or four different lipid supplements in a 5 x 5 Latin square design. Extracted DNA was analysed by qPCR and by sequencing 16S and 18S rRNA genes or the fungal ITS1 amplicons. Faeces contained few protozoa, and bacterial, fungal and archaeal communities were substantially different to ruminal digesta. Buccal and bolus samples gave much more similar profiles to ruminal digesta, although fewer archaea were detected in buccal and bolus samples. Bolus samples overall were most similar to ruminal samples. The differences between both buccal and bolus samples and ruminal digesta were consistent across all treatments. It can be concluded that either proxy sample type could be used as a predictor of the rumen microbial community, thereby enabling more convenient large-scale animal sampling for phenotyping and possible use in future animal breeding programs aimed at selecting cattle with a lower environmental footprint.
Data from: Variation in non-invasive ventilation use in amyotrophic lateral sclerosis
Objective: We sought to examine prevalence and predictors of non-invasive ventilation (NIV) in a composite cohort of amyotrophic lateral sclerosis (ALS) patients followed in a clinical trials setting (PRO-ACT database). Methods: NIV initiation and status were ascertained from response to question 12 of the revised ALS functional rating scale (ALSFRS-R). Factors affecting NIV use in patients with forced vital capacity (FVC) ≤ 50% of predicted were examined. Predictors of NIV were evaluated by Cox proportional hazard models and generalized linear mixed models. Results: Among 1,784 patients with 8,417 simultaneous ALSFRS-R and FVC% measures, NIV was used by 604 (33.9%). Of 918 encounters when FVC% ≤ 50%, NIV was reported in 482 (52.5%). Independent predictors of NIV initiation were lower FVC% (hazard ratio HR 1.27, 95% CI: 1.17-1.37 for 10% drop), dyspnea (HR 2.62, 95% CI: 1.87-3.69), orthopnea (HR 4.09, 95% CI: 3.02-5.55), lower bulbar and gross motor subscores of ALSFRS-R (HRs 1.09 (95% CI: 1.03-1.14) and 1.13 (95% CI: 1.07-1.20) respectively, per point), and male sex (HR 1.73, 95% CI: 1.31-2.28). Adjusted for other variables, bulbar onset did not significantly influence time to NIV (HR 0.72 (95% CI: 0.47-1.08)). Considerable unexplained variability in NIV use was found. Conclusion: NIV use was lower than expected in this ALS cohort that was likely to be optimally managed. Absence of respiratory symptoms and female sex may be barriers to NIV use. Prospective exploration of factors affecting adoption of NIV may help bridge this gap and improve care in ALS.
Non-invasive recording of EEG from the cervical spinal cord via surface electrodes placed around the neck
<p>Data and scripts used for Chander et al. 2022. EEG data recorded via 10 electrodes placed around the neck of 17 healthy young human individuals, in addition to EEG data recorded from scalp electrodes (numbers of electrodes vary across individuals), an ECG channel, and EOG channels. The reference electrode was placed above the right acromion, the ground electrode above the left acromion. Sampling rate 5000 Hz, online lowpass filter 1000 Hz, online highpass filter .1 Hz (BrainAmp DC amplifier). During recordings, the left median nerve of participants was stimulated using a DS7 Digitimer at ~110% of motor threshold (constant current stimulation, 50-500 µsec pulse width (depending on the participant), square wave) at 3 Hz. 15% of stimuli were pseudo-randomly omitted. Participants counted the number of omissions in each of 3 minute blocks. The montage for neck electrodes is explained in Chander et al. 2022. There are three trigger values: 1 = experimenter pressed a key to start the experiment, or to initiate a new block. 130 = median nerve stimulation. 99 = omission. Further details in Chander et al. 2022. The scripts are mostly aiming at characterizing high-frequency signals (400-1200 Hz) in response to median nerve stimulation (8 to 16 ms), and their dissociation from the evoked response.</p>
FIGURE 4 in A new blind snake of the genus Letheobia (Serpentes: Typhlopidae) from Rwanda with redescriptions of L. gracilis (Sternfeld, 1910) and L. graueri (Sternfeld, 1912) and the introduction of a non-invasive preparation procedure for scanning electron microscopy in zoology
FIGURE 4. Holotype of Letheobia akagerae sp. nov. (ZFMK 100862) in life.
Non-invasive monitoring of a reactive soil transition zone during water table fluctuations using spectral induced polarization (SIP) and electrodic potential (EP)
<p>Transition zones separating the unsaturated and saturated domains in soils are a hotspot for biogeochemical activity. They are challenging to study because they are dynamic, requiring high resolution temporal and spatial data acquisition methods to capture the biogeochemical processes across the water table. Non-invasive geophysical techniques, such as spectral induced polarization (SIP) and electrodic potential (EP), offer comparatively inexpensive monitoring approaches that yield data on changes in soil electrical properties, driven by reactive processes at high spatial and temporal resolutions. We investigated SIP and EP signal variations in artificial soil-filled columns, experiencing periodic water table fluctuations in order to: (1) assess the effectiveness of SIP and EP in monitoring a complex soil transition zone, and (2) couple the measured geophysical signals to changes in physical, chemical and microbial properties. SIP responses showed a clear dependence on the depth-distribution of microbial biomass. Dynamic imaginary conductivity (<em>σ''</em>) responses were only detected in the water table fluctuation zone and, in contrast to real conductivity (<em>σ'</em>) data, did not exhibit a direct soil moisture driven dependence. We attribute the observed dynamics in <em>σ'' </em>to microbially driven reactions. An EP anomaly arose concurrent to the production of SO<sub>4</sub><sup>2- </sup>as a result of oxygenation at depth during drainage of the columns. Our findings show that continuous SIP and EP signals, in conjunction with periodic measurements of geochemical indicators, can help determine the location and temporal variability of biogeochemical activity and be used to monitor targeted reaction zones and pathways in complex soil environments.</p>
Supplementary material 1 from: Zemanova MA (2019) Poor implementation of non-invasive sampling in wildlife genetics studies. Rethinking Ecology 4: 119-132. https://doi.org/10.3897/rethinkingecology.4.32751
: Data type: reference data
Data from: Electromyography data for non-invasive naturally controlled robotic hand prostheses
Recent advances in rehabilitation robotics suggest that it may be possible for hand-amputated subjects to recover at least a significant part of the lost hand functionality. The control of robotic prosthetic hands using non-invasive techniques is still a challenge in real life: myoelectric prostheses give limited control capabilities, the control is often unnatural and must be learned through long training times. Meanwhile, scientific literature results are promising but they are still far from fulfilling real-life needs. This work aims to close this gap by allowing worldwide research groups to develop and test movement recognition and force control algorithms on a benchmark scientific database. The database is targeted at studying the relationship between surface electromyography, hand kinematics and hand forces, with the final goal of developing non-invasive, naturally controlled, robotic hand prostheses. The validation section verifies that the data are similar to data acquired in real-life conditions, and that recognition of different hand tasks by applying state-of-the-art signal features and machine-learning algorithms is possible.
Figure 3 from: Nader M, El Indary S, Abi Salloum B, Abou Dagher M (2011) Combining non-invasive methods for the rapid assessment of mammalian richness in a transectquadrat survey scheme – Case Study of the Horsh Ehden Nature Reserve, North Lebanon. ZooKeys 119: 63-71. https://doi.org/10.3897/zookeys.119.1040
Figure 3 - Mammalian distribution map showing the location of mammalian activity and the location of the Motion Sensor Cameras.
Non-invasive monitoring of multiple wildlife health factors by fecal microbiome analysis
<p>Fecal microbial biomarkers represent a less invasive alternative for acquiring information on wildlife populations than many traditional sampling methodologies. Our goal was to evaluate linkages between fecal microbiome communities in Rocky Mountain elk (<i>Cervus canadensis</i>) and four host factors including sex, age, population, and physical condition (body-fat). We paired a feature-selection algorithm with an LDA-classifier trained on elk differential bacterial abundance (16S-rRNA amplicon survey) to predict host health factors from 104 elk microbiomes across four elk populations. We validated the accuracy of the various classifier predictions with leave-one-out cross-validation using known measurements. We demonstrate that the elk fecal microbiome can predict the four host factors tested. Our results show that elk microbiomes respond to both the strong extrinsic factor of biogeography and simultaneously occurring, but more subtle, intrinsic forces of individual body-fat, sex, and age class. Thus, we have developed and described herein a generalizable approach to disentangle microbiome responses attributed to multiple host factors of varying strength from the same bacterial sequence data set. Wildlife conservation and management presents many challenges, but we demonstrate that non-invasive microbiome surveys from scat samples can provide alternative options for wildlife population monitoring. We believe that, with further validation, this method could be broadly applicable in other species and potentially predict other measurements. Our study can help guide the future development of microbiome-based monitoring of wildlife populations and supports hypothetical expectations found in host-microbiome theory.</p>
Is there a non-invasive biomarker for the early-stage detection of ovarian torsion: a systematic literature review
<p>Articles for meta-analysis </p>
Gamification of Joint Rehabilitation Utilizing Non-Invasive Sensors and Vision-Based Software: Framework Development and Validation
<p>This file contains the video supplementary materials for an MDPI Sensor paper publication.</p>
Supplementary material 1 from: Giangregorio P, Mucci N, Norman AJ, Pedrotti L, Filacorda S, Molinari P, Spong G, Davoli F (2023) Performance of SNP markers for parentage analysis in the Italian Alpine brown bear using non-invasive samples. Nature Conservation 53: 105-123. https://doi.org/10.3897/natureconservation.53.86739
Genetic and field data
Cutting-edge IMAGING Technologies to Improve the SAFEty and the Sustainability of LUNG Cancer Screening and the Accuracy of Non-invasive Lung Nodules Characterization
ClinicalTrials.gov study NCT06963515. IPD Sharing: NO. Countries: 0. Publications: 9.
Non-invasive Brain Stimulation and Strategic Memory Training
ClinicalTrials.gov study NCT05929872. IPD Sharing: NO. Countries: 0. Publications: 11.
Non-Invasive Non-Ionizing Polarized Imaging System to Assess Structure of Cervix
ClinicalTrials.gov study NCT00955864. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Non-Invasive Reduction of Abdominal Fat
ClinicalTrials.gov study NCT01101997. IPD Sharing: NO. Countries: 1. Publications: 0.
Utility of Non-invasive Carboxyhemoglobin and Total Hemoglobin Measurement in the Emergency Department
ClinicalTrials.gov study NCT03017742. IPD Sharing: NO. Countries: 1. Publications: 0.
MRI for Non-Invasive Imaging in Neonates and Children
ClinicalTrials.gov study NCT02163681. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Non-Invasive Cooling of Fat Cells
ClinicalTrials.gov study NCT00762437. IPD Sharing: NO. Countries: 1. Publications: 0.
Non-invasive Brain Stimulation in Adults Who Stutter
ClinicalTrials.gov study NCT03437512. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
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.