Background: Myasthenia gravis (MG) and neuromyelitis optica (NMO, also known as Devic disease) are rare autoimmune disorders, with upper-limit prevalence estimates in the general population of 15 per 100 000 and 5 per 100 000, respectively. To our knowledge, an association between these diseases has not been previously reported. Objectives: To describe 4 patients with MG who developed NMO after thymectomy and to analyze possible causes of apparent increased prevalence of NMO among patients with MG. Design: Case series. Patients: Four patients with MG who underwent thymectomy. Interventions: None. Results: The prevalence of MG within the published cohort of patients with NMO is more than 150 times higher than that in the general population. Conclusion: Dysregulation of B-cell autoimmunity in myasthenia, possibly exacerbated by loss of control over autoreactive cells as a result of thymectomy, may predispose patients to the development of NMO.
Abstract. Many robotic systems would, in the future, be required to operate in environments that are highly unstructured (with varying dynamical properties) and active (possessing means of self-actuation). Although a significant volume of results exist in model-based, robust and adaptive control literature, many issues pertinent to the stabilization of contact interactions with unpredictable environments remain unresolved, especially in dealing with large magnitude and high frequency parametric uncertainties. The primary intent of this paper is nonlinear control synthesis for robotic operations in unstructured environments. We introduce the notion of time constrained terminal convergence for controlled systems, and propose an approach to nonlinear control synthesis based upon a new cl;~ss of sliding modes, denoted terminal sliders. Terminal controllers that enforce finite convergence to equilibrium are synthesized for an example nonlinear system (with and without parametric uncertainties). Improved performance is demonstrated through the elimination of high frequency control switching, employed previously for robustness to parametric uncertainties [2]. The dependence of terminal slider stability upon the rate of change of uncertainties over the sliding surface, rather than the magnitude of the uncertainty itself, results in improved control robustness. Improved reliability is demonstrated through the elimination of interpolation regions [2]. Finally, improved (guaranteed) precision is argued for through an analysis of steady state behavior.
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