Treatment of Parkinson’s Disease:Early, Late, and Combined

Medical therapy in de novo Parkinson’s disease typically starts with a dopamine agonist or levodopa in combination with a decarboxylase inhibitor or if symptoms are still very mild with a MAO-B inhibitor. When patients do not (or no longer) respond satisfactorily to these initial therapies, different drugs can be initiated or combined (i.e., “add-on” treatments). These add-on therapies not only comprise oral agents but also intra-jejunal and intra-cutaneous treatments and functional neurosurgical procedures. This chapter starts with the treatment of de novo Parkinson’s disease whereafter indications and expected effects of the different “add-on” therapies will be described. The “add-on” therapies will be described in a hierarchical way and treatment algorithms will be provided based on prevailing symptoms including non-motor symptoms. The symptoms that will be discussed are: (1) bradykinesia and “wearing-OFF, " (2) tremor at rest, (3) dyskinesia, (4) gait and postural symptoms including freezing of gait, and (5) important non-motor symptoms. Finally, a comprehensive add-on treatment algorithm will be provided that takes into account non-motor symptoms that may limit the efficacy and tolerability of the different add-on therapies.</p

Superspace realizations of the Bannai-Ito algebra

A model of the Bannai-Ito algebra in a superspace is introduced. It is obtained from the three-fold tensor product of the basic realization of the Lie superalgebra $osp(1|2)$ in terms of operators in one continuous and one Grassmanian variable. The basis vectors of the resulting Bannai-Ito algebra module involve Jacobi polynomials

Orthosymplectically invariant functions in superspace

The notion of spherically symmetric superfunctions as functions invariant under the orthosymplectic group is introduced. This leads to dimensional reduction theorems for differentiation and integration in superspace. These spherically symmetric functions can be used to solve orthosymplectically invariant Schroedinger equations in superspace, such as the (an)harmonic oscillator or the Kepler problem. Finally the obtained machinery is used to prove the Funk-Hecke theorem and Bochner's relations in superspace.Comment: J. Math. Phy

Superparamagnetic iron oxide polyacrylic acid coated {\gamma}-Fe2O3 nanoparticles does not affect kidney function but causes acute effect on the cardiovascular function in healthy mice

This study describes the distribution of intravenously injected polyacrylic acid (PAA) coated {\gamma}-Fe2O3 NPs (10 mg kg-1) at the organ, cellular and subcellular levels in healthy BALB/cJ mice and in parallel addresses the effects of NP injection on kidney function, blood pressure and vascular contractility. Magnetic resonance imaging (MRI) and transmission electron microscopy (TEM) showed accumulation of NPs in the liver within 1h after intravenous infusion, accommodated by intracellular uptake in endothelial and Kupffer cells with subsequent intracellular uptake in renal cells, particularly the cytoplasm of the proximal tubule, in podocytes and mesangial cells. The renofunctional effects of NPs were evaluated by arterial acid-base status and measurements of glomerular filtration rate (GFR) after instrumentation with chronically indwelling catheters. Arterial pH was 7.46 and 7.41 in mice 0.5 h after injections of saline or NP, and did not change over the next 12h. In addition, the injections of NP did not affect arterial PCO2 or [HCO3-] either. Twenty-four and 96h after NP injections, the GFR averaged 11.0 and 13.0 ml min-1 g-1, respectively, values which were statistically comparable with controls (14.0 and 14.0 ml min-1 g-1). Mean arterial blood pressure (MAP) decreased 12-24h after NP injections (111 vs 123 min-1) associated with a decreased contractility of small mesenteric arteries revealed by myography to characterise endothelial function. In conclusion, our study demonstrates that accumulation of superparamagnetic iron oxide nanoparticles does not affect kidney function in healthy mice but temporarily decreases blood pressure.Comment: 21 pages, 12 figures, published in Toxicology and Applied Pharmacology 201

Private Distribution Learning with Public Data: The View from Sample Compression

We study the problem of private distribution learning with access to public data. In this setup, which we refer to as public-private learning, the learner is given public and private samples drawn from an unknown distribution $p$ belonging to a class $\mathcal Q$, with the goal of outputting an estimate of $p$ while adhering to privacy constraints (here, pure differential privacy) only with respect to the private samples. We show that the public-private learnability of a class $\mathcal Q$ is connected to the existence of a sample compression scheme for $\mathcal Q$, as well as to an intermediate notion we refer to as list learning. Leveraging this connection: (1) approximately recovers previous results on Gaussians over $\mathbb R^d$; and (2) leads to new ones, including sample complexity upper bounds for arbitrary $k$-mixtures of Gaussians over $\mathbb R^d$, results for agnostic and distribution-shift resistant learners, as well as closure properties for public-private learnability under taking mixtures and products of distributions. Finally, via the connection to list learning, we show that for Gaussians in $\mathbb R^d$, at least $d$ public samples are necessary for private learnability, which is close to the known upper bound of $d+1$ public samples.Comment: 31 page