Search results for "Biomedical"
showing 10 items of 2328 documents
Assessment of nonnegative matrix factorization algorithms for electroencephalography spectral analysis.
2020
AbstractBackgroundNonnegative matrix factorization (NMF) has been successfully used for electroencephalography (EEG) spectral analysis. Since NMF was proposed in the 1990s, many adaptive algorithms have been developed. However, the performance of their use in EEG data analysis has not been fully compared. Here, we provide a comparison of four NMF algorithms in terms of accuracy of estimation, stability (repeatability of the results) and time complexity of algorithms with simulated data. In the practical application of NMF algorithms, stability plays an important role, which was an emphasis in the comparison. A Hierarchical clustering algorithm was implemented to evaluate the stability of NM…
Loss Aversion and Risk Aversion in Non-Clinical Negative Symptoms and Hypomania
2020
In the field of behavioral decision-making, “loss aversion” is a behavioral phenomenon in which individuals show a higher sensitivity to potential losses than to gains. Conversely, “risk averse” individuals have an enhanced sensitivity/aversion to options with uncertain consequences. Here we examine whether hypomania or negative symptoms predict the degree of these choice biases. We chose to study these two symptom dimensions because they present a common theme across many syndromes with compromised decision-making. In our exploratory study, we employed a non-clinical sample to dissociate the hypomanic from negative symptom dimension regarding choice behavior. We randomly selected a sample …
Tracking Healing Process of Experimental Liver Injuries Treated with Different Sealants and Adhesives Biomaterials. Matrix Metalloproteinase Evaluati…
2018
Sealants and adhesives are used in the repair and preservation of damaged solid organs. This study examines the matrix metalloproteinases (MMP) activity in the healing of liver injuries treated with two biological adhesives (Tachosil® and GelitaSpon®) as well as that of a new elastic cyanoacrylate (Adhflex®). Methods. We induced in 90 male rats hepatic lesions using a Stiefel biopsy punch in the liver. Wound healing was assessed 2, 6, and 18 days after injury by quantifying MMP1, 2, 8, 9, and 13 tissue levels. The histopathological repair was evaluated by hematoxylin-eosin, Masson’s trichrome, and Periodic Acid Schiff (PAS) staining and CD31, CD68 immunohis…
Pairwise and higher-order measures of brain-heart interactions in children with temporal lobe epilepsy
2022
Abstract Objective. While it is well-known that epilepsy has a clear impact on the activity of both the central nervous system (CNS) and the autonomic nervous system (ANS), its role on the complex interplay between CNS and ANS has not been fully elucidated yet. In this work, pairwise and higher-order predictability measures based on the concepts of Granger Causality (GC) and partial information decomposition (PID) were applied on time series of electroencephalographic (EEG) brain wave amplitude and heart rate variability (HRV) in order to investigate directed brain-heart interactions associated with the occurrence of focal epilepsy. Approach. HRV and the envelopes of δ and α EEG activity re…
Mastering the Tools: Natural versus Artificial Vesicles in Nanomedicine
2020
Naturally occurring extracellular vesicles and artificially made vesicles represent important tools in nanomedicine for the efficient delivery of biomolecules and drugs. Since its first appearance in the literature 50 years ago, the research on vesicles is progressing at a fast pace, with the main goal of developing carriers able to protect cargoes from degradation, as well as to deliver them in a time- and space-controlled fashion. While natural occurring vesicles have the advantage of being fully compatible with their host, artificial vesicles can be easily synthetized and functionalized according to the target to reach. Research is striving to merge the advantages of natural and artifici…
Efficient contour-based annotation by iterative deep learning for organ segmentation from volumetric medical images
2022
Abstract Purpose Training deep neural networks usually require a large number of human-annotated data. For organ segmentation from volumetric medical images, human annotation is tedious and inefficient. To save human labour and to accelerate the training process, the strategy of annotation by iterative deep learning recently becomes popular in the research community. However, due to the lack of domain knowledge or efficient human-interaction tools, the current AID methods still suffer from long training time and high annotation burden. Methods We develop a contour-based annotation by iterative deep learning (AID) algorithm which uses boundary representation instead of voxel labels to incorp…
Performance Evaluation of EEG Based Mental Stress Assessment Approaches for Wearable Devices
2021
Mental stress has been identified as the root cause of various physical and psychological disorders. Therefore, it is crucial to conduct timely diagnosis and assessment considering the severe effects of mental stress. In contrast to other health-related wearable devices, wearable or portable devices for stress assessment have not been developed yet. A major requirement for the development of such a device is a time-efficient algorithm. This study investigates the performance of computer-aided approaches for mental stress assessment. Machine learning (ML) approaches are compared in terms of the time required for feature extraction and classification. After conducting tests on data for real-t…
Artificial cartilage bio-matrix formed of hyaluronic acid and Mg2+-polyphosphate.
2016
Here we show that inorganic polyphosphate (polyP), a polyanionic metabolic regulator consisting of multiple phosphate residues linked by energy-rich phosphoanhydride bonds, is present in the synovial fluid. In a biomimetic approach, to enhance cartilage synthesis and regeneration, we prepared amorphous polyP microparticles with Mg2+ as counterions. The particles were characterised by X-ray diffraction (XRD), energy-dispersive X-ray (EDX) and Fourier transformed infrared spectroscopic (FTIR) analyses. Similar particles were obtained after addition of Mg2+ ions to a solution containing hyaluronic acid, as a major component of the synovial fluid, and soluble Na-polyP. The viscous paste-like ma…
Automatic Processing of Changes in Facial Emotions in Dysphoria: A Magnetoencephalography Study
2018
It is not known to what extent the automatic encoding and change detection of peripherally presented facial emotion is altered in dysphoria. The negative bias in automatic face processing in particular has rarely been studied. We used magnetoencephalography (MEG) to record automatic brain responses to happy and sad faces in dysphoric (Beck’s Depression Inventory ≥ 13) and control participants. Stimuli were presented in a passive oddball condition, which allowed potential negative bias in dysphoria at different stages of face processing (M100, M170, and M300) and alterations of change detection (visual mismatch negativity, vMMN) to be investigated. The magnetic counterpart of the vMMN was el…
Exploring Oscillatory Dysconnectivity Networks in Major Depression During Resting State Using Coupled Tensor Decomposition
2022
Dysconnectivity of large-scale brain networks has been linked to major depression disorder (MDD) during resting state. Recent researches show that the temporal evolution of brain networks regulated by oscillations reveals novel mechanisms and neural characteristics of MDD. Our study applied a novel coupled tensor decomposition model to investigate the dysconnectivity networks characterized by spatio-temporal-spectral modes of covariation in MDD using resting electroencephalography. The phase lag index is used to calculate the functional connectivity within each time window at each frequency bin. Then, two adjacency tensors with the dimension of time frequency connectivity subject are constr…