Surface electromyography using dry polymeric electrodes

Conventional wet Ag/AgCl electrodes are widely used in electrocardiography, electromyography (EMG), and electroencephalography (EEG) and are considered the gold standard for biopotential measurements. However, these electrodes require substantial skin preparation, are single use, and cannot be used for continuous monitoring (>24 h). For these reasons, dry electrodes are preferable during surface electromyography (sEMG) due to their convenience, durability, and longevity. Dry conductive elastomers (CEs) combine conductivity, flexibility, and stretchability. In this study, CEs combining poly(3,4-ehtylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS) in polyurethane are explored as dry, skin contacting EMG electrodes. This study compares these CE electrodes to commercial wet Ag/AgCl electrodes in five subjects, classifying four movements: open hand, fist, wrist extension, and wrist flexion. Classification accuracy is tested using a backpropagation artificial neural network. The control Ag/AgCl electrodes have a 98.7% classification accuracy, while the dry conductive elastomer electrodes have a classification accuracy of 99.5%. As a conclusion, PEDOT based dry CEs were shown to successfully function as on-skin electrodes for EMG recording, matching the performance of Ag/AgCl electrodes, while addressing the need for minimal skin prep, no gel, and wearable technology.

Toward high-throughput oligomer detection and classification for early-stage aggregation of amyloidogenic protein

Aggregation kinetics of proteins and peptides have been studied extensively due to their significance in many human diseases, including neurodegenerative disorders, and the roles they play in some key physiological processes. However, most of these studies have been performed as bulk measurements using Thioflavin T or other fluorescence turn-on reagents as indicators of fibrillization. Such techniques are highly successful in making inferences about the nucleation and growth mechanism of fibrils, yet cannot directly measure assembly reactions at low protein concentrations which is the case for amyloid-β (Aβ) peptide under physiological conditions. In particular, the evolution from monomer to low-order oligomer in early stages of aggregation cannot be detected. Single-molecule methods allow direct access to such fundamental information. We developed a high-throughput protocol for single-molecule photobleaching experiments using an automated fluorescence microscope. Stepwise photobleaching analysis of the time profiles of individual foci allowed us to determine stoichiometry of protein oligomers and probe protein aggregation kinetics. Furthermore, we investigated the potential application of supervised machine learning with support vector machines (SVMs) as well as multilayer perceptron (MLP) artificial neural networks to classify bleaching traces into stoichiometric categories based on an ensemble of measurable quantities derivable from individual traces. Both SVM and MLP models achieved a comparable accuracy of more than 80% against simulated traces up to 19-mer, although MLP offered considerable speed advantages, thus making it suitable for application to high-throughput experimental data. We used our high-throughput method to study the aggregation of Aβ₄₀ in the presence of metal ions and the aggregation of α-synuclein in the presence of gold nanoparticles.

Mind the gap: State-of-the-art technologies and applications for EEG-based brain-computer interfaces

Brain-computer interfaces (BCIs) provide bidirectional communication between the brain and output devices that translate user intent into function. Among the different brain imaging techniques used to operate BCIs, electroencephalography (EEG) constitutes the preferred method of choice, owing to its relative low cost, ease of use, high temporal resolution, and noninvasiveness. In recent years, significant progress in wearable technologies and computational intelligence has greatly enhanced the performance and capabilities of EEG-based BCIs (eBCIs) and propelled their migration out of the laboratory and into real-world environments. This rapid translation constitutes a paradigm shift in human-machine interaction that will deeply transform different industries in the near future, including healthcare and wellbeing, entertainment, security, education, and marketing. In this contribution, the state-of-the-art in wearable biosensing is reviewed, focusing on the development of novel electrode interfaces for long term and noninvasive EEG monitoring. Commercially available EEG platforms are surveyed, and a comparative analysis is presented based on the benefits and limitations they provide for eBCI development. Emerging applications in neuroscientific research and future trends related to the widespread implementation of eBCIs for medical and nonmedical uses are discussed. Finally, a commentary on the ethical, social, and legal concerns associated with this increasingly ubiquitous technology is provided, as well as general recommendations to address key issues related to mainstream consumer adoption.

A Novel Aβ40 Assembly at Physiological Concentration

Aggregates of amyloid-β (Aβ) are characteristic of Alzheimer's disease, but there is no consensus as to either the nature of the toxic molecular complex or the mechanism by which toxic aggregates are produced. We report on a novel feature of amyloid-lipid interactions where discontinuities in the lipid continuum can serve as catalytic centers for a previously unseen microscale aggregation phenomenon. We show that specific lipid membrane conditions rapidly produce long contours of lipid-bound peptide, even at sub-physiological concentrations of Aβ. Using single molecule fluorescence, time-lapse TIRF microscopy and AFM imaging we characterize this phenomenon and identify some exceptional properties of the aggregation pathway which make it a likely contributor to early oligomer and fibril formation, and thus a potential critical mechanism in the etiology of AD. We infer that these amyloidogenic events occur only at areas of high membrane curvature, which suggests a range of possible mechanisms by which accumulated physiological changes may lead to their inception. The speed of the formation is in hours to days, even at 1 nM peptide concentrations. Lipid features of this type may act like an assembly line for monomeric and small oligomeric subunits of Aβ to increase their aggregation states. We conclude that under lipid environmental conditions, where catalytic centers of the observed type are common, key pathological features of AD may arise on a very short timescale under physiological concentration.

A highly stable RNA aptamer probe for the retinoblastoma protein in live cells

Although RNA aptamers can show comparable or better specificity and affinity to antibodies and have the advantage of being able to access different live cell compartments, they are often much less stable in vivo. We report here the first aptamer that binds human retinoblastoma protein (RB) and is stable in live cells. RB is both a key protein in cell cycle control and also a tumour suppressor. The aptamer was selected from an RNA library against a unique 12-residue helical peptide derived from RB rather than the whole protein molecule. It binds RB with high affinity (K _d = 5.1 ± 0.1 nM) and is a putative RNA G-quadruplex structure formed by an 18-nucleotide sequence (18E16 - GGA GGG UGG AGG GAA GGG), which may account for its high stability. Confocal fluorescence microscopy of live cells transfected with the aptamer shows it is stable intracellularly and efficient in entering the nucleus where an analogous antibody was inaccessible. The findings demonstrate this aptamer is an advanced probe for RB in live cell applications.