Evaluation of Three Machine Learning Algorithms for the Automatic Classification of EMG Patterns in Gait Disorders

Gait disorders are common in neurodegenerative diseases and distinguishing between seemingly similar kinematic patterns associated with different pathological entities is a challenge even for the experienced clinician. Ultimately, muscle activity underlies the generation of kinematic patterns. Therefore, one possible way to address this problem may be to differentiate gait disorders by analyzing intrinsic features of muscle activations patterns. Here, we examined whether it is possible to differentiate electromyography (EMG) gait patterns of healthy subjects and patients with different gait disorders using machine learning techniques. Nineteen healthy volunteers (9 male, 10 female, age 28.2 ± 6.2 years) and 18 patients with gait disorders (10 male, 8 female, age 66.2 ± 14.7 years) resulting from different neurological diseases walked down a hallway 10 times at a convenient pace while their muscle activity was recorded via surface EMG electrodes attached to 5 muscles of each leg (10 channels in total). Gait disorders were classified as predominantly hypokinetic (n = 12) or ataxic (n = 6) gait by two experienced raters based on video recordings. Three different classification methods (Convolutional Neural Network—CNN, Support Vector Machine—SVM, K-Nearest Neighbors—KNN) were used to automatically classify EMG patterns according to the underlying gait disorder and differentiate patients and healthy participants. Using a leave-one-out approach for training and evaluating the classifiers, the automatic classification of normal and abnormal EMG patterns during gait (2 classes: “healthy” and “patient”) was possible with a high degree of accuracy using CNN (accuracy 91.9%), but not SVM (accuracy 67.6%) or KNN (accuracy 48.7%). For classification of hypokinetic vs. ataxic vs. normal gait (3 classes) best results were again obtained for CNN (accuracy 83.8%) while SVM and KNN performed worse (accuracy SVM 51.4%, KNN 32.4%). These results suggest that machine learning methods are useful for distinguishing individuals with gait disorders from healthy controls and may help classification with respect to the underlying disorder even when classifiers are trained on comparably small cohorts. In our study, CNN achieved higher accuracy than SVM and KNN and may constitute a promising method for further investigation

Achiral symmetry breaking and positive Gaussian modulus lead to scalloped colloidal membranes

In the presence of a non-adsorbing polymer, monodisperse rod-like particles assemble into colloidal membranes, which are one rod-length thick liquid-like monolayers of aligned rods. Unlike 3D edgeless bilayer vesicles, colloidal monolayer membranes form open structures with an exposed edge, thus presenting an opportunity to study physics of thin elastic sheets. Membranes assembled from single-component chiral rods form flat disks with uniform edge twist. In comparison, membranes comprised of mixture of rods with opposite chiralities can have the edge twist of either handedness. In this limit disk-shaped membranes become unstable, instead forming structures with scalloped edges, where two adjacent lobes with opposite handedness are separated by a cusp-shaped point defect. Such membranes adopt a 3D configuration, with cusp defects alternatively located above and below the membrane plane. In the achiral regime the cusp defects have repulsive interactions, but away from this limit we measure effective long-ranged attractive binding. A phenomenological model shows that the increase in the edge energy of scalloped membranes is compensated by concomitant decrease in the deformation energy due to Gaussian curvature associated with scalloped edges, demonstrating that colloidal membranes have positive Gaussian modulus. A simple excluded volume argument predicts the sign and magnitude of the Gaussian curvature modulus that is in agreement with experimental measurements. Our results provide insight into how the interplay between membrane elasticity, geometrical frustration and achiral symmetry breaking can be used to fold colloidal membranes into 3D shapes.Comment: Main text: 25 pages, 6 figures. Supplementary information: 6 pages, 6 figure

Clinical Outcome Following Stringent Discontinuation of Dual Antiplatelet Therapy After 12 Months in Real-World Patients Treated With Second-Generation Zotarolimus-Eluting Resolute and Everolimus-Eluting Xience V Stents : 2-Year Follow-Up of the Randomized TWENTE Trial

Objectives The aim of this study was to assess the safety and efficacy of the implantation of Resolute zotarolimus-eluting stents (ZES) (Medtronic Inc., Santa Rosa, California) and Xience V everolimus-eluting stents (EES) (Abbott Vascular, Santa Clara, California) following strict discontinuation of dual antiplatelet therapy (DAPT) after 12 months. Background Only limited long-term follow-up data are available from head-to-head comparisons of second-generation drug-eluting stents. Methods The randomized TWENTE (The Real-World Endeavor Resolute Versus Xience V Drug-Eluting Stent Study in Twente) trial is an investigator-initiated study performed in a population with many complex patients and lesions and only limited exclusion criteria. Patients were randomly assigned 1:1 to ZES (n = 697) or EES (n = 694). Results Two-year follow-up information was available on all patients. The rate of continuation of DAPT beyond 12 months was very low (5.4%). The primary endpoint of target vessel failure, a composite of cardiac death, target vessel–related myocardial infarction, and target vessel revascularization, did not differ between ZES and EES (10.8% vs. 11.6, p = 0.65), despite fewer target lesion revascularizations in patients with EES (2.6% vs. 4.9%, p = 0.03). The patient-oriented composite endpoint was similar (16.4% vs. 17.1%, p = 0.75). Two-year rates of definite or probable stent thrombosis were 1.2% and 1.4%, respectively (p = 0.63). Very late definite or probable stent thrombosis occurred only in 2 patients in each study arm (0.3% vs. 0.3%, p = 1.00). Conclusions After 2 years of follow-up and stringent discontinuation of DAPT beyond 12 months, Resolute ZES and Xience V EES showed similar results in terms of safety and efficacy for treating patients with a majority of complex lesions and off-label indications for drug-eluting stents. (The Real-World Endeavor Resolute Versus Xience V Drug-Eluting Stent Study in Twent

Reconfigurable self-assembly through chiral control of interfacial tension

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature 481 (2012): 348–351, doi:10.1038/nature10769.From determining optical properties of simple molecular crystals to establishing preferred handedness in highly complex vertebrates, molecular chirality profoundly influences the structural, mechanical, and optical properties of both synthetic and biological matter at macroscopic lengthscales1,2. In soft materials such as amphiphilic lipids and liquid crystals, the competition between local chiral interactions and global constraints imposed by the geometry of the self-assembled structures leads to frustration and the assembly of unique materials3-6. An example of particular interest is smectic liquid crystals, where the 2D layered geometry cannot support twist, expelling chirality to the edges in a manner analogous to the expulsion of a magnetic field from superconductors7-10. Here, we demonstrate a previously unexplored consequence of this geometric frustration which leads to a new design principle for the assembly of chiral molecules. Using a model system of colloidal membranes11, we show that molecular chirality can control the interfacial tension, an important property of multi-component mixtures. This finding suggests an analogy between chiral twist which is expelled to the edge of 2D membranes, and amphiphilic surfactants which are expelled to oil-water interfaces12. Similar to surfactants, chiral control of interfacial tension drives the assembly of myriad polymorphic assemblages such as twisted ribbons with linear and circular topologies, starfish membranes, and double and triple helices. Tuning molecular chirality in situ enables dynamical control of line tension that powers polymorphic transitions between various chiral structures. These findings outline a general strategy for the assembly of reconfigurable chiral materials which can easily be moved, stretched, attached to one another, and transformed between multiple conformational states, thus enabling precise assembly and nano-sculpting of highly dynamical and designable materials with complex topologies.This work was supported by the National Science Foundation (NSF-MRSEC-0820492, NSF-DMR-0955776, NSF-MRI 0923057) and Petroleum Research Fund (ACS-PRF 50558-DNI7).2012-07-0

Cyclic AMP signalling pathways in the regulation of uterine relaxation

Studying the mechanism(s) of uterine relaxation is important and will be helpful in the prevention of obstetric difficulties such as preterm labour, which remains a major cause of perinatal mortality and morbidity. Multiple signalling pathways regulate the balance between maintaining relative uterine quiescence during gestation, and the transition to the contractile state at the onset of parturition. Elevation of intracellular cyclic AMP promotes myometrial relaxation, and thus quiescence, via effects on multiple intracellular targets including calcium channels, potassium channels and myosin light chain kinase. A complete understanding of cAMP regulatory pathways (synthesis and hydrolysis) would assist in the development of better tocolytics to delay or inhibit preterm labour. Here we review the enzymes involved in cAMP homoeostasis (adenylyl cyclases and phosphodiesterases) and possible myometrial substrates for the cAMP dependent protein kinase. We must emphasise the need to identify novel pharmacological targets in human pregnant myometrium to achieve safe and selective uterine relaxation when this is indicated in preterm labour or other obstetric complications

A population-specific material model for sagittal craniosynostosis to predict surgical shape outcomes

Sagittal craniosynostosis consists of premature fusion (ossification) of the sagittal suture during infancy, resulting in head deformity and brain growth restriction. Spring-assisted cranioplasty (SAC) entails skull incisions to free the fused suture and insertion of two springs (metallic distractors) to promote cranial reshaping. Although safe and effective, SAC outcomes remain uncertain. We aimed hereby to obtain and validate a skull material model for SAC outcome prediction. Computed tomography data relative to 18 patients were processed to simulate surgical cuts and spring location. A rescaling model for age matching was created using retrospective data and validated. Design of experiments was used to assess the effect of different material property parameters on the model output. Subsequent material optimization—using retrospective clinical spring measurements—was performed for nine patients. A population-derived material model was obtained and applied to the whole population. Results showed that bone Young’s modulus and relaxation modulus had the largest effect on the model predictions: the use of the population-derived material model had a negligible effect on improving the prediction of on-table opening while significantly improved the prediction of spring kinematics at follow-up. The model was validated using on-table 3D scans for nine patients: the predicted head shape approximated within 2 mm the 3D scan model in 80% of the surface points, in 8 out of 9 patients. The accuracy and reliability of the developed computational model of SAC were increased using population data: this tool is now ready for prospective clinical application

Neutron production in (α,n) reactions

Neutrons can induce background events in underground experiments looking for rare processes. Neutrons in a MeV range are produced in radioactive decays via spontaneous fission and () reactions, and by cosmic rays. Neutron fluxes from radioactivity dominate at large depths ( km w. e.). A number of computer codes are available to calculate cross-sections of () reactions, excitation functions and neutron yields. We have used EMPIRE2.19/3.2.3 and TALYS1.9 to calculate neutron production cross-sections and branching ratios for transitions to the ground and excited states, and modified SOURCES4A to evaluate neutron yields and spectra in different materials relevant to high-sensitivity underground experiments. We report here a comparison of different models and codes with experimental data, to estimate the accuracy of these calculations