Effects of Aging on Genioglossus Motor Units in Humans

The genioglossus is a major upper airway dilator muscle thought to be important in obstructive sleep apnea pathogenesis. Aging is a risk factor for obstructive sleep apnea although the mechanisms are unclear and the effects of aging on motor unit remodeled in the genioglossus remains unknown. To assess possible changes associated with aging we compared quantitative parameters related to motor unit potential morphology derived from EMG signals in a sample of older (n = 11; >55 years) versus younger (n = 29; <55 years) adults. All data were recorded during quiet breathing with the subjects awake. Diagnostic sleep studies (Apnea Hypopnea Index) confirmed the presence or absence of obstructive sleep apnea. Genioglossus EMG signals were analyzed offline by automated software (DQEMG), which estimated a MUP template from each extracted motor unit potential train (MUPT) for both the selective concentric needle and concentric needle macro (CNMACRO) recorded EMG signals. 2074 MUPTs from 40 subjects (mean±95% CI; older AHI 19.6±9.9 events/hr versus younger AHI 30.1±6.1 events/hr) were extracted. MUPs detected in older adults were 32% longer in duration (14.7±0.5 ms versus 11.1±0.2 ms; P = 0.05), with similar amplitudes (395.2±25.1 µV versus 394.6±13.7 µV). Amplitudes of CNMACRO MUPs detected in older adults were larger by 22% (62.7±6.5 µV versus 51.3±3.0 µV; P<0.05), with areas 24% larger (160.6±18.6 µV.ms versus 130.0±7.4 µV.ms; P<0.05) than those detected in younger adults. These results confirm that remodeled motor units are present in the genioglossus muscle of individuals above 55 years, which may have implications for OSA pathogenesis and aging related upper airway collapsibility

Surface and interface study of pulsed-laser-deposited off-stoichiometric NiMnSb thin films on Si(100) substrate

We report a detailed study of surface and interface properties of pulsed-laser deposited NiMnSb films on Si (100) substrate as a function of film thickness. As the thickness of films is reduced below 35 nm formation of a porous layer is observed. Porosity in this layer increases with decrease in NiMnSb film thickness. These morphological changes of the ultra thin films are reflected in the interesting transport and magnetic properties of these films. On the other hand, there are no influences of compositional in-homogeneity and surface/interface roughness on the magnetic and transport properties of the films.Comment: 13 pages, 7 figures, Submitted to Phys. Rev.

Quality Control of Motor Unit Number Index (MUNIX) Measurements in 6 Muscles in a Single-Subject “Round-Robin” Setup

Background Motor Unit Number Index (MUNIX) is a neurophysiological measure that provides an index of the number of lower motor neurons in a muscle. Its performance across centres in healthy subjects and patients with Amyotrophic Lateral Sclerosis (ALS) has been established, but inter-rater variability between multiple raters in one single subject has not been investigated. Objective To assess reliability in a set of 6 muscles in a single subject among 12 examiners (6 experienced with MUNIX, 6 less experienced) and to determine variables associated with variability of measurements. Methods Twelve raters applied MUNIX in six different muscles (abductor pollicis brevis (APB), abductor digiti minimi (ADM), biceps brachii (BB), tibialis anterior (TA), extensor dig. brevis (EDB), abductor hallucis (AH)) twice in one single volunteer on consecutive days. All raters visited at least one training course prior to measurements. Intra- and inter-rater variability as determined by the coefficient of variation (COV) between different raters and their levels of experience with MUNIX were compared. Results Mean intra-rater COV of MUNIX was 14.0% (±6.4) ranging from 5.8 (APB) to 30.3% (EDB). Mean inter-rater COV was 18.1 (±5.4) ranging from 8.0 (BB) to 31.7 (AH). No significant differences of variability between experienced and less experienced raters were detected. Conclusion We provide evidence that quality control for neurophysiological methods can be performed with similar standards as in laboratory medicine. Intra- and inter-rater variability of MUNIX is muscle-dependent and mainly below 20%. Experienced neurophysiologists can easily adopt MUNIX and adequate teaching ensures reliable utilization of this method

Surface step effects on Si (100) under uniaxial tensile stress, by atomistic calculations

This paper reports a study of the influence of the step at a silicon surface under an uniaxial tensile stress, using an empirical potential. Our aim was to find conditions leading to nucleation of dislocations from the step. We obtained that no dislocations could be generated with such conditions. This behaviour, different from the one predicted for metals, could be attributed either to the covalent bonding or to the cubic diamond structure

Energetics and atomic mechanisms of dislocation nucleation in strained epitaxial layers

We study numerically the energetics and atomic mechanisms of misfit dislocation nucleation and stress relaxation in a two-dimensional atomistic model of strained epitaxial layers on a substrate with lattice misfit. Relaxation processes from coherent to incoherent states for different transition paths are studied using interatomic potentials of Lennard-Jones type and a systematic saddle point and transition path search method. The method is based on a combination of repulsive potential minimization and the Nudged Elastic Band method. For a final state with a single misfit dislocation, the minimum energy path and the corresponding activation barrier are obtained for different misfits and interatomic potentials. We find that the energy barrier decreases strongly with misfit. In contrast to continuous elastic theory, a strong tensile-compressive asymmetry is observed. This asymmetry can be understood as manifestation of asymmetry between repulsive and attractive branches of pair potential and it is found to depend sensitively on the form of the potential.Comment: 11 pages, 9 figures, to appear in Phys. Rev.

Fuzzy min-max neural networks for categorical data: application to missing data imputation

The fuzzy min–max neural network classifier is a supervised learning method. This classifier takes the hybrid neural networks and fuzzy systems approach. All input variables in the network are required to correspond to continuously valued variables, and this can be a significant constraint in many real-world situations where there are not only quantitative but also categorical data. The usual way of dealing with this type of variables is to replace the categorical by numerical values and treat them as if they were continuously valued. But this method, implicitly defines a possibly unsuitable metric for the categories. A number of different procedures have been proposed to tackle the problem. In this article, we present a new method. The procedure extends the fuzzy min–max neural network input to categorical variables by introducing new fuzzy sets, a new operation, and a new architecture. This provides for greater flexibility and wider application. The proposed method is then applied to missing data imputation in voting intention polls. The micro data—the set of the respondents’ individual answers to the questions—of this type of poll are especially suited for evaluating the method since they include a large number of numerical and categorical attributes

Behaviour of motor unit action potential rate, estimated from surface EMG, as a measure of muscle activation level

BACKGROUND: Surface electromyography (EMG) parameters such as root-mean-square value (RMS) are commonly used to assess the muscle activation level that is imposed by the central nervous system (CNS). However, RMS is influenced not only by motor control aspects, but also by peripheral properties of the muscle and recording setup. To assess motor control separately, the number of motor unit action potentials (MUAPs) per second, or MUAP Rate (MR) is a potentially useful measure. MR is the sum of the firing rates of the contributing MUs and as such reflects the two parameters that the CNS uses for motor control: number of MUs and firing rate. MR can be estimated from multi-channel surface EMG recordings. The objective of this study was to explore the behaviour of estimated MR (eMR) in relation to number of active MUs and firing rate. Furthermore, the influence of parameters related to peripheral muscle properties and recording setup (number of fibers per MU, fiber diameter, thickness of the subcutaneous layer, signal-to-noise-ratio) on eMR was compared with their influence on RMS. METHODS: Physiological parameters were varied in a simulation model that generated multi-channel EMG signals. The behaviour of eMR in simulated conditions was compared with its behaviour in experimental conditions. Experimental data was obtained from the upper trapezius muscle during a shoulder elevation task (20–100 N). RESULTS: The simulations showed strong, monotonously increasing relations between eMR and number of active MUs and firing rate (r(2 )> 0.95). Because of unrecognized superimpositions of MUAPs, eMR was substantially lower than the actual MUAP Rate (aMR). The percentage of detected MUAPs decreased with aMR, but the relation between eMR and aMR was rather stable in all simulated conditions. In contrast to RMS, eMR was not affected by number of fibers per MU, fiber diameter and thickness of the subcutaneous layer. Experimental data showed a strong relation between eMR and force (individual second order polynomial regression: 0.96 < r(2 )< 0.99). CONCLUSION: Although the actual number of MUAPs in the signal cannot be accurately extracted with the present method, the stability of the relation between eMR and aMR and its independence of muscle properties make eMR a suitable parameter to assess the input from the CNS to the muscle at low contraction levels non-invasively

Techniques of EMG signal analysis: detection, processing, classification and applications

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications

Motor unit potential morphology differences in individuals with non-specific arm pain and lateral epicondylitis

<p>Abstract</p> <p>Background</p> <p>The pathophysiology of non-specific arm pain (NSAP) is unclear and the diagnosis is made by excluding other specific upper limb pathologies, such as lateral epicondylitis or cervical radiculopathy. The purpose of this study was to determine: (i) if the quantitative parameters related to motor unit potential morphology and/or motor unit firing patterns derived from electromyographic (EMG) signals detected from an affected muscle of patients with NSAP are different from those detected in the same muscle of individuals with lateral epicondylitis (LE) and/or control subjects and (ii) if the quantitative EMG parameters suggest that the underlying pathophysiology in NSAP is either myopathic or neuropathic in nature.</p> <p>Methods</p> <p>Sixteen subjects with NSAP, 11 subjects with LE, eight subjects deemed to be at-risk for developing a repetitive strain injury, and 37 control subjects participated. A quantitative electromyography evaluation was completed using decomposition-based quantitative electromyography (DQEMG). Needle- and surface-detected EMG signals were collected during low-level isometric contractions of the extensor carpi radialis brevis (ECRB) muscle. DQEMG was used to extract needle-detected motor unit potential trains (MUPTs), and needle-detected motor unit potential (MUP) and surface detected motor unit potential (SMUP) morphology and motor unit (MU) firing rates were compared among the four groups using one-way analysis of variance (ANOVA). Post hoc analyses were performed using Tukey's pairwise comparisons.</p> <p>Results</p> <p>Significant group differences were found for all MUP variables and for MU firing rate (<it>p</it> < 0.006). The post-hoc analyses revealed that patients with NSAP had smaller MUP amplitude and SMUP amplitude and area compared to the control and LE groups (<it>p </it>< 0.006). MUP duration and AAR values were significantly larger in the NSAP, LE and at-risk groups compared to the control group (<it>p </it>< 0.006); while MUP amplitude, duration and AAR values were smaller in the NSAP compared to the LE group. SMUP duration was significantly shorter in the NSAP group compared to the control group (<it>p </it>< 0.006). NSAP, LE and at-risk subjects had lower mean MU firing rates than the control subjects (<it>p </it>< 0.006).</p> <p>Conclusion</p> <p>The size-related parameters suggest that the NSAP group had significantly smaller MUPs and SMUPs than the control and LE subjects. Smaller MUPs and SMUPs may be indicative of muscle fiber atrophy and/or loss. A prospective study is needed to confirm any causal relationship between smaller MUPs and SMUPs and NSAP as found in this work.</p

Follicular fluid content and oocyte quality: from single biochemical markers to metabolomics

The assessment of oocyte quality in human in vitro fertilization (IVF) is getting increasing attention from embryologists. Oocyte selection and the identification of the best oocytes, in fact, would help to limit embryo overproduction and to improve the results of oocyte cryostorage programs. Follicular fluid (FF) is easily available during oocyte pick-up and theorically represents an optimal source on non-invasive biochemical predictors of oocyte quality. Unfortunately, however, the studies aiming to find a good molecular predictor of oocyte quality in FF were not able to identify substances that could be used as reliable markers of oocyte competence to fertilization, embryo development and pregnancy. In the last years, a well definite trend toward passing from the research of single molecular markers to more complex techniques that study all metabolites of FF has been observed. The metabolomic approach is a powerful tool to study biochemical predictors of oocyte quality in FF, but its application in this area is still at the beginning. This review provides an overview of the current knowledge about the biochemical predictors of oocyte quality in FF, describing both the results coming from studies on single biochemical markers and those deriving from the most recent studies of metabolomic