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Elderly patients, aged 65 or older, make up 13.5% of the U.S. population, but represent 45.2% of the top 10% of healthcare utilizers, in terms of expenditures. Middle-aged Americans, aged 45 to 64 make up another 37.0% of that category. Given the high demand for healthcare services by the aforementioned population, it is important to identify high-cost users of healthcare systems and, more importantly, ineffective utilization patterns to highlight where targeted interventions could be placed to improve care delivery. In this work, we present a novel multi-level framework applying machine learning (ML) methods (i.e., random forest regression and hierarchical clustering) to group patients with similar utilization profiles into clusters. We use a vector space model to characterize a patient’s utilization profile as the number of visits to different care providers and prescribed medications. We applied the proposed methods using the 2013 Medical Expenditures Panel Survey (MEPS) dataset. We identified clusters of healthcare utilization patterns of elderly and middle-aged adults in the United States, and assessed the general and clinical characteristics associated with these utilization patterns. Our results demonstrate the effectiveness of the proposed framework to model healthcare utilization patterns. Understanding of these patterns can be used to guide healthcare policy-making and practice.

Fully characterizing structural and functional sites in proteins is a fundamental step in understanding their roles in the cell. This extremely challenging combinatorial problem requires determining the number of sites in the protein and the set of residues involved in each of them. We formulate it as a distance-based supervised clustering task, where training proteins are employed to learn a proper distance function between residues. A partial clustering is then returned by searching for maximum-weight cliques in the resulting weighted graph representation of proteins. A novel stochastic local search algorithm is proposed to efficiently generate approximate solutions. Our method achieves substantial improvements over a previous structured-output approach for metal binding site prediction. Significant improvements over the current state-of-the-art are also achieved in predicting catalytic sites from 3D structure in enzymes.

Objective Prediabetes is a high-risk state for developing diabetes and associated complications. The purpose of this paper was to report trends in prevalence of prediabetes for individuals aged 16 and older in England without previously diagnosed diabetes. Setting Data collected by the Health Survey for England (HSE) in England in the years 2003, 2006, 2009 and 2011. Participants Individuals aged 16 and older who participated in the HSE and provided a blood sample. Primary outcome variable Individuals were classified as having prediabetes if glycated haemoglobin was between 5.7% and 6.4% and were not previously diagnosed with diabetes. Results The prevalence rate of prediabetes increased from 11.6% to 35.3% from 2003 to 2011. By 2011, 50.6% of the population who were overweight (body mass index (BMI)>25) and ≥40 years of age had prediabetes. In bivariate relationships, individuals with greater socioeconomic deprivation were more likely to have prediabetes in 2003 (p=0.0008) and 2006 (p=0.0246), but the relationship was not significant in 2009 (p=0.213) and 2011 (p=0.3153). In logistic regressions controlling for age, sex, race/ethnicity, BMI and high blood pressure, the second most socioeconomically deprived had a significantly elevated risk of having prediabetes (2011, OR=1.45; 95% CI 1.26 to 1.88). Conclusions There has been a marked increase in the proportion of adults in England with prediabetes. The socioeconomically deprived are at substantial risk. In the absence of concerted and effective efforts to reduce risk, the number of people with diabetes is likely to increase steeply in coming years.

We investigated the expression of ERG channels in immature spinal interneurons, using organotypic embryonic cultures of mouse spinal cord after 1 and 2 weeks of development in vitro. We report here that all the genes of the erg family known so far (erg1a,erg1b, erg2, erg3) are expressed in embryonic spinal cultures. We demonstrate for the first time that three ERG proteins (ERG1A, ERG2 and ERG3) are co-expressed in the same neuronal population, and display a spatio-temporal distribution in the spinal slices. ERG immuno-positive cells, representing mainly GABAergic interneurons, were present in large numbers at early stages of development, while declining later, with a ventral to dorsal gradient. Patch clamp recordings confirmed these data, showing that ventral interneurons expressed functional ERG currents only transiently. Similar expression of the erg genes was observed at comparable ages in vivo. The role of ERG currents in regulating neuronal excitability during the earliest phases of spinal circuitry development will be examined in future studies.

info:eu-repo/semantics/published

info:eu-repo/semantics/published

Bone marrow mesenchymal cells (MSCs) can protect leukemic cells from chemotherapy, thus increasing their survival rate. We studied the potential molecular mechanisms underlying this effect in acute lymphoblastic leukemia (ALL) cells. Coculture of ALL cells with MSCs induced on the lymphoblast plasma membrane the expression of a signaling complex formed by hERG1 (human ether-à-go-go-related gene 1) channels, the β1-integrin subunit, and the chemokine receptor CXC chemokine receptor-4. The assembly of such a protein complex activated both the extracellular signal-related kinase 1/2 (ERK1/2) and the phosphoinositide 3-kinase (PI3K)/Akt prosurvival signaling pathways. At the same time, ALL cells became markedly resistant to chemotherapy-induced apoptosis. hERG1 channel function appeared to be important for both the initiation of prosurvival signals and the development of drug resistance, because specific channel blockers decreased the protective effect of MSCs. NOD/SCID mice engrafted with ALL cells and treated with channel blockers showed reduced leukemic infiltration and had higher survival rates. Moreover, hERG1 blockade enhanced the therapeutic effect produced by corticosteroids. Our findings provide a rationale for clinical testing of hERG1 blockers in the context of antileukemic therapy for patients with ALL.

During spinal cord maturation neuronal excitability gradually differentiates to meet different functional demands. Spontaneous activity, appearing early during spinal development, is regulated by the expression pattern of ion channels in individual neurons. While emerging excitability of embryonic motoneurons has been widely investigated, little is known about that of spinal interneurons. Voltage-dependent K+ channels are a heterogeneous class of ion channels that accomplish several functions. Recently voltage-dependent K+ channels encoded by erg subfamily genes (ERG channels) were shown to modulate excitability in immature neurons of mouse and quail. We investigated the expression of ERG channels in immature spinal interneurons, using organotypic embryonic cultures of mouse spinal cord after 1 and 2 weeks of development in vitro. We report here that all the genes of the erg family known so far (erg1a, erg1b, erg2, erg3) are expressed in embryonic spinal cultures. We demonstrate for the first time that three ERG proteins (ERG1A, ERG2 and ERG3) are co-expressed in the same neuronal population, and display a spatio-temporal distribution in the spinal slices. ERG immuno-positive cells, representing mainly GABAergic interneurons, were present in large numbers at early stages of development, while declining later, with a ventral to dorsal gradient. Patch clamp recordings confirmed these data, showing that ventral interneurons expressed functional ERG currents only transiently. Similar expression of the erg genes was observed at comparable ages in vivo. The role of ERG currents in regulating neuronal excitability during the earliest phases of spinal circuitry development will be examined in future studies. © 2005 Published by Elsevier Ltd on behalf of IBRO.

Carbon nanotubes have been applied in several areas of nerve tissue engineering to probe and augment cell behaviour, to label and track subcellular components, and to study the growth and organization of neural networks. Recent reports show that nanotubes can sustain and promote neuronal electrical activity in networks of cultured cells, but the ways in which they affect cellular function are still poorly understood. Here, we show, using single-cell electrophysiology techniques, electron microscopy analysis and theoretical modelling, that nanotubes improve the responsiveness of neurons by forming tight contacts with the cell membranes that might favour electrical shortcuts between the proximal and distal compartments of the neuron. We propose the 'electrotonic hypothesis' to explain the physical interactions between the cell and nanotube, and the mechanisms of how carbon nanotubes might affect the collective electrical activity of cultured neuronal networks. These considerations offer a perspective that would allow us to predict or engineer interactions between neurons and carbon nanotubes.

Voltage-dependent K+ channels are the main determinants in controlling cellular excitability within the central nervous system. Among voltage-dependent K+ channels, the ERG subfamily is deeply involved in the control of cellular excitability, both in mammals and in invertebrates. ERG channels are encoded by different genes: the erg1 gene, which can generate two alternative transcripts (erg1a and erg1b), erg2 and erg3. The aim of the present study was to determine the expression pattern and cellular localization of ERG proteins (ERG1, ERG2, and ERG3) in the mouse CNS, differentiating, for the first time, the ERG1A and ERG1B isoforms. To this purpose, novel specific antibodies were raised against the various channel proteins and their specificity and immunoreactivity tested. It emerged that: 1) all the erg genes were indeed translated in neuronal tissue; 2) ERG proteins distribution in the mouse CNS often overlapped, and only in specific areas each ERG protein showed a distinct pattern of expression; and 3) ERG proteins were generally expressed in neuronal soma, but dendritic and/or white matter labeling could be detected in specific areas. The finding that ERG proteins often have an overlapping expression suggests that neuronal ERG currents could be determined, at least in part, by heterotetrameric ERG channels. This suggestion is demonstrated to occur for ERG1A/ERG1B by showing that the two isoforms coassemble in mouse brain. © 2005 Wiley-Liss, Inc.