A Pilot Study of an mHealth Application for Healthcare Workers: Poor Uptake Despite High Reported Acceptability at a Rural South African Community-Based MDR-TB Treatment Program

Introduction: As the South African province of KwaZulu-Natal addresses a growing multidrug-resistant tuberculosis (MDR-TB) epidemic by shifting care and treatment from trained specialty centers to community hospitals, delivering and monitoring MDR-TB therapy has presented new challenges. In particular, tracking and reporting adverse clinical events have been difficult for mobile healthcare workers (HCWs), trained health professionals who travel daily to patient homes to administer and monitor therapy. We designed and piloted a mobile phone application (Mobilize) for mobile HCWs that electronically standardized the recording and tracking of MDR-TB patients on low-cost, functional phones. Objective: We assess the acceptability and feasibility of using Mobilize to record and submit adverse events forms weekly during the intensive phase of MDR-TB therapy and evaluate mobile HCW perceptions throughout the pilot period. Methods: All five mobile HCWs at one site were trained and provided with phones. Utilizing a mixed-methods evaluation, mobile HCWs’ usage patterns were tracked electronically for seven months and analyzed. Qualitative focus groups and questionnaires were designed to understand the impact of mobile phone technology on the work environment. Results: Mobile HCWs submitted nine of 33 (27%) expected adverse events forms, conflicting with qualitative results in which mobile HCWs stated that Mobilize improved adverse events communication, helped their daily workflow, and could be successfully expanded to other health interventions. When presented with the conflict between their expressed views and actual practice, mobile HCWs cited forgetfulness and believed patients should take more responsibility for their own care. Discussion This pilot experience demonstrated poor uptake by HCWs despite positive responses to using mHealth. Though our results should be interpreted cautiously because of the small number of mobile HCWs and MDR-TB patients in this study, we recommend carefully exploring the motivations of HCWs and technologic enhancements prior to scaling new mHealth initiatives in resource poor settings

Clustering of resting state networks

BACKGROUND: The goal of the study was to demonstrate a hierarchical structure of resting state activity in the healthy brain using a data-driven clustering algorithm. METHODOLOGY/PRINCIPAL FINDINGS: The fuzzy-c-means clustering algorithm was applied to resting state fMRI data in cortical and subcortical gray matter from two groups acquired separately, one of 17 healthy individuals and the second of 21 healthy individuals. Different numbers of clusters and different starting conditions were used. A cluster dispersion measure determined the optimal numbers of clusters. An inner product metric provided a measure of similarity between different clusters. The two cluster result found the task-negative and task-positive systems. The cluster dispersion measure was minimized with seven and eleven clusters. Each of the clusters in the seven and eleven cluster result was associated with either the task-negative or task-positive system. Applying the algorithm to find seven clusters recovered previously described resting state networks, including the default mode network, frontoparietal control network, ventral and dorsal attention networks, somatomotor, visual, and language networks. The language and ventral attention networks had significant subcortical involvement. This parcellation was consistently found in a large majority of algorithm runs under different conditions and was robust to different methods of initialization. CONCLUSIONS/SIGNIFICANCE: The clustering of resting state activity using different optimal numbers of clusters identified resting state networks comparable to previously obtained results. This work reinforces the observation that resting state networks are hierarchically organized

Towards Universal Health Coverage: An Evaluation of Rwanda Mutuelles in Its First Eight Years

Background: Mutuelles is a community-based health insurance program, established since 1999 by the Government of Rwanda as a key component of the national health strategy on providing universal health care. The objective of the study was to evaluate the impact of Mutuelles on achieving universal coverage of medical services and financial risk protection in its first eight years of implementation. Methods and Findings: We conducted a quantitative impact evaluation of Mutuelles between 2000 and 2008 using nationally-representative surveys. At the national and provincial levels, we traced the evolution of Mutuelles coverage and its impact on child and maternal care coverage from 2000 to 2008, as well as household catastrophic health payments from 2000 to 2006. At the individual level, we investigated the impact of Mutuelles' coverage on enrollees' medical care utilization using logistic regression. We focused on three target populations: the general population, under-five children, and women with delivery. At the household level, we used logistic regression to study the relationship between Mutuelles coverage and the probability of incurring catastrophic health spending. The main limitation was that due to insufficient data, we are not able to study the impact of Mutuelles on health outcomes, such as child and maternal mortalities, directly. The findings show that Mutuelles improved medical care utilization and protected households from catastrophic health spending. Among Mutuelles enrollees, those in the poorest expenditure quintile had a significantly lower rate of utilization and higher rate of catastrophic health spending. The findings are robust to various estimation methods and datasets. Conclusions: Rwanda's experience suggests that community-based health insurance schemes can be effective tools for achieving universal health coverage even in the poorest settings. We suggest a future study on how eliminating Mutuelles copayments for the poorest will improve their healthcare utilization, lower their catastrophic health spending, and affect the finances of health care providers

Electrophysiological Guidance of Epidural Electrode Array Implantation over the Human Lumbosacral Spinal Cord to Enable Motor Function after Chronic Paralysis.

Epidural electrical stimulation (EES) of the spinal cord has been shown to restore function after spinal cord injury (SCI). Characterization of EES-evoked motor responses has provided a basic understanding of spinal sensorimotor network activity related to EES-enabled motor activity of the lower extremities. However, the use of EES-evoked motor responses to guide EES system implantation over the spinal cord and their relation to post-operative EES-enabled function in humans with chronic paralysis attributed to SCI has yet to be described. Herein, we describe the surgical and intraoperative electrophysiological approach used, followed by initial EES-enabled results observed in 2 human subjects with motor complete paralysis who were enrolled in a clinical trial investigating the use of EES to enable motor functions after SCI. The 16-contact electrode array was initially positioned under fluoroscopic guidance. Then, EES-evoked motor responses were recorded from select leg muscles and displayed in real time to determine electrode array proximity to spinal cord regions associated with motor activity of the lower extremities. Acceptable array positioning was determined based on achievement of selective proximal or distal leg muscle activity, as well as bilateral muscle activation. Motor response latencies were not significantly different between intraoperative recordings and post-operative recordings, indicating that array positioning remained stable. Additionally, EES enabled intentional control of step-like activity in both subjects within the first 5 days of testing. These results suggest that the use of EES-evoked motor responses may guide intraoperative positioning of epidural electrodes to target spinal cord circuitry to enable motor functions after SCI

Three-dimensional structure of the weakly associated protein homodimer SeR13 using RDCs and paramagnetic surface mapping

The traditional NMR-based method for determining oligomeric protein structure usually involves distinguishing and assigning intra- and intersubunit NOEs. This task becomes challenging when determining symmetric homo-dimer structures because NOE cross-peaks from a given pair of protons occur at the same position whether intra- or intersubunit in origin. While there are isotope-filtering strategies for distinguishing intra from intermolecular NOE interactions in these cases, they are laborious and often prove ineffectual in cases of weak dimers, where observation of intermolecular NOEs is rare. Here, we present an efficient procedure for weak dimer structure determination based on residual dipolar couplings (RDCs), chemical shift changes upon dilution, and paramagnetic surface perturbations. This procedure is applied to the Northeast Structural Genomics Consortium protein target, SeR13, a negatively charged Staphylococcus epidermidis dimeric protein (Kd 3.4 ± 1.4 mM) composed of 86 amino acids. A structure determination for the monomeric form using traditional NMR methods is presented, followed by a dimer structure determination using docking under orientation constraints from RDCs data, and scoring under residue pair potentials and shape-based predictions of RDCs. Validation using paramagnetic surface perturbation and chemical shift perturbation data acquired on sample dilution is also presented. The general utility of the dimer structure determination procedure and the possible relevance of SeR13 dimer formation are discussed. Published by Wiley-Blackwell. © 2010 The Protein Society

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives

Star formation rates in Lyman break galaxies: radio stacking of LBGs in the COSMOS field and the sub-μ\muJy radio source population

We present an analysis of the radio properties of large samples of Lyman Break Galaxies (LBGs) at $z \sim 3$, 4, and 5 from the COSMOS field. The median stacking analysis yields a statistical detection of the $z \sim 3$ LBGs (U-band drop-outs), with a 1.4 GHz flux density of $0.90 \pm 0.21 \mu$Jy. The stacked emission is unresolved, with a size $< 1"$, or a physical size $< 8$kpc. The total star formation rate implied by this radio luminosity is $31\pm 7$ $M_\odot$ year$^{-1}$, based on the radio-FIR correlation in low redshift star forming galaxies. The star formation rate derived from a similar analysis of the UV luminosities is 17 $M_\odot$ year$^{-1}$, without any correction for UV dust attenuation. The simplest conclusion is that the dust attenuation factor is 1.8 at UV wavelengths. However, this factor is considerably smaller than the standard attenuation factor $\sim 5$, normally assumed for LBGs. We discuss potential reasons for this discrepancy, including the possibility that the dust attenuation factor at $z \ge 3$ is smaller than at lower redshifts. Conversely, the radio luminosity for a given star formation rate may be systematically lower at very high redshift. Two possible causes for a suppressed radio luminosity are: (i) increased inverse Compton cooling of the relativistic electron population due to scattering off the increasing CMB at high redshift, or (ii) cosmic ray diffusion from systematically smaller galaxies. The radio detections of individual sources are consistent with a radio-loud AGN fraction of 0.3%. One source is identified as a very dusty, extreme starburst galaxy (a 'submm galaxy').Comment: 15 pages, 2 figures AASTEX, to appear in Ap

Engineering Thermostability in Artificial Metalloenzymes to Increase Catalytic Activity

Protein engineering has shown widespread use in improving the industrial application of enzymes and broadening the conditions they are able to operate under by increasing their thermostability and solvent tolerance. Here, we show that protein engineering can be used to increase the thermostability of an artificial metalloenzyme. Thermostable variants of the human steroid carrier protein 2L, modified to bind a metal catalyst, were created by rational design using structural data and a 3DM database. These variants were tested to identify mutations that enhanced the stability of the protein scaffold, and a significant increase in melting temperature was observed with a number of modified metalloenzymes. The ability to withstand higher reaction temperatures resulted in an increased activity in the hydroformylation of 1-octene, with more than fivefold improvement in turnover number, whereas the selectivity for linear aldehyde remained high up to 80%