Building a Machine-learning Framework to Remotely Assess Parkinson's Disease Using Smartphones.

Parkinson's disease (PD) is a neurodegenerative disorder that affects multiple neurological systems. Traditional PD assessment is conducted by a physician during infrequent clinic visits. Using smartphones, remote patient monitoring has the potential to obtain objective behavioral data semi-continuously, track disease fluctuations, and avoid rater dependency. Smartphones collect sensor data during various active tests and passive monitoring, including balance (postural instability), dexterity (skill in performing tasks using hands), gait (the pattern of walking), tremor (involuntary muscle contraction and relaxation), and voice. Some of the features extracted from smartphone data are potentially associated with specific PD symptoms identified by physicians. To leverage large-scale cross-modality smartphone features, we propose a machine-learning framework for performing automated disease assessment. The framework consists of a two-step feature selection procedure and a generic model based on the elastic-net regularization. Using this framework, we map the PD-specific architecture of behaviors using data obtained from both PD participants and healthy controls (HCs). Utilizing these atlases of features, the framework shows promises to (a) discriminate PD participants from HCs, and (b) estimate the disease severity of individuals with PD. Data analysis results from 437 behavioral features obtained from 72 subjects (37 PD and 35 HC) sampled from 17 separate days during a period of up to six months suggest that this framework is potentially useful for the analysis of remotely collected smartphone sensor data in individuals with PD

Interaction and flocculation of spherical colloids wetted by a surface-induced corona of paranematic order

Particles dispersed in a liquid crystal above the nematic-isotropic phase transition are wetted by a surface-induced corona of paranematic order. Such coronas give rise to pronounced two-particle interactions. In this article, we report details on the analytical and numerical study of these interactions published recently [Phys. Rev. Lett. 86, 3915 (2001)]. We especially demonstrate how for large particle separations the asymptotic form of a Yukawa potential arises. We show that the Yukawa potential is a surprisingly good description for the two-particle interactions down to distances of the order of the nematic coherence length. Based on this fact, we extend earlier studies on a temperature induced flocculation transition in electrostatically stabilized colloidal dispersions [Phys. Rev. E 61, 2831 (2000)]. We employ the Yukawa potential to establish a flocculation diagram for a much larger range of the electrostatic parameters, namely the surface charge density and the Debye screening length. As a new feature, a kinetically stabilized dispersion close to the nematic-isotropic phase transition is found.Comment: Revtex v4.0, 16 pages, 12 Postscript figures. Accepted for publication in Phys. Rev.

Mutation of Directed Graphs -- Corresponding Regular Expressions and Complexity of Their Generation

Directed graphs (DG), interpreted as state transition diagrams, are traditionally used to represent finite-state automata (FSA). In the context of formal languages, both FSA and regular expressions (RE) are equivalent in that they accept and generate, respectively, type-3 (regular) languages. Based on our previous work, this paper analyzes effects of graph manipulations on corresponding RE. In this present, starting stage we assume that the DG under consideration contains no cycles. Graph manipulation is performed by deleting or inserting of nodes or arcs. Combined and/or multiple application of these basic operators enable a great variety of transformations of DG (and corresponding RE) that can be seen as mutants of the original DG (and corresponding RE). DG are popular for modeling complex systems; however they easily become intractable if the system under consideration is complex and/or large. In such situations, we propose to switch to corresponding RE in order to benefit from their compact format for modeling and algebraic operations for analysis. The results of the study are of great potential interest to mutation testing

Somatostatin subtype-2 receptor-targeted metal-based anticancer complexes

Conjugates of a dicarba analogue of octreotide, a potent somatostatin agonist whose receptors are overexpressed on tumor cells, with [PtCl 2(dap)] (dap = 1-(carboxylic acid)-1,2-diaminoethane) (3), [(η 6-bip)Os(4-CO 2-pico)Cl] (bip = biphenyl, pico = picolinate) (4), [(η 6-p-cym)RuCl(dap)] + (p-cym = p-cymene) (5), and [(η 6-p-cym)RuCl(imidazole-CO 2H)(PPh 3)] + (6), were synthesized by using a solid-phase approach. Conjugates 3-5 readily underwent hydrolysis and DNA binding, whereas conjugate 6 was inert to ligand substitution. NMR spectroscopy and molecular dynamics calculations showed that conjugate formation does not perturb the overall peptide structure. Only 6 exhibited antiproliferative activity in human tumor cells (IC 50 = 63 ± 2 μ in MCF-7 cells and IC 50 = 26 ± 3 μ in DU-145 cells) with active participation of somatostatin receptors in cellular uptake. Similar cytotoxic activity was found in a normal cell line (IC 50 = 45 ± 2.6 μ in CHO cells), which can be attributed to a similar level of expression of somatostatin subtype-2 receptor. These studies provide new insights into the effect of receptor-binding peptide conjugation on the activity of metal-based anticancer drugs, and demonstrate the potential of such hybrid compounds to target tumor cells specifically. © 2012 American Chemical Society

Deficiency of the Metalloproteinase-Disintegrin ADAM8 Is Associated with Thymic Hyper-Cellularity

Thymopoiesis requires thymocyte-stroma interactions and proteases that promote cell migration by degrading extracellular matrix and releasing essential cytokines and chemokines. A role for several members of the A Disintegrin and Metalloprotease (ADAM) family in T cell development has been reported in the past

Sequence History Analysis (SHA) : Estimating the Effect of Past Trajectories on an Upcoming Event

In this article, we propose an innovative method which is a combination of Sequences Analysis and Event History Analysis. We called this method Sequence History Analysis (SHA). We start by identifying typical past trajectories of individuals over time by using Sequence Analysis. We then estimate the effect of these typical past trajectories on the event under study using discrete-time models. The aim of this approach is to estimate the effect of past trajectories on the chances of experiencing an event. We apply the proposed methodological approach to an original study of the effect of past childhood co-residence structures on the chances of leaving the parental home in Switzerland. The empirical research was based on the LIVES Cohort study, a panel survey that started in autumn 2013 in Switzerland. Analyses show that it is not only the occurrence of an event that increases the risk of experiencing another event, but also the order in which various states occurred. What is more, it seems that two features have a significant influence on departure from the parental home: the co-residence structures and the arrival or departure of siblings from the parental home

Prospective open randomized study comparing efficacies and safeties of a 3-day course of azithromycin and a 10-day course of erythromycin in children with community-acquired acute lower respiratory tract infections.

The efficacies and safeties of a 3-day, 3-dose course of azithromycin (10 mg/kg of body weight per day) and a 10-day, 30-dose course of erythromycin (40 mg/kg/day) for the treatment of acute lower respiratory tract infections in children were compared in an open randomized multicenter study. Sixty-eight of 85 evaluable patients (80%) had radiologically proven pneumonia, and 20% had bronchitis. Treatment success defined as cure or major improvement was achieved in 42 of 45 (93%) azithromycin recipients versus 36 of 40 (90%) erythromycin recipients. Adverse events were reported in 12 of 45 and 6 of 40 of the patients treated with azithromycin and erythromycin, respectively, a difference which was not statistically significant. In conclusion, a 3-day course of azithromycin is as effective as a 10-day course of erythromycin in the treatment of community-acquired lower respiratory tract infections in children, with comparable safety and acceptability profiles. This shorter treatment course might have a beneficial effect on compliance, especially in the pediatric age group