Do HIV treatment eligibility expansions crowd out the sickest? Evidence from rural South Africa

OBJECTIVE: The 2015 WHO recommendation to initiate all HIV patients on antiretroviral therapy (ART) at diagnosis could potentially overextend health systems and crowd out sicker patients, mitigating the policy's impact. We evaluate whether South Africa's prior eligibility expansion from CD4 ≤200 to CD4 ≤350 cells/μL reduced ART uptake in the sickest patients. METHODS: Using data on all patients presenting to the Hlabisa HIV Treatment and Care Program in KwaZulu-Natal from April 2010 - June 2012 (n=13,809), we assessed the impact of the August 2011 eligibility expansion on the number of patients seeking care, number initiating ART, and time from HIV diagnosis to ART initiation among patients always eligible (CD4 0-200), newly eligible (CD4 201-350), and not yet eligible by CD4 count (>350). We used interrupted time series methods to control for long-run trends and isolate the effect of the policy. RESULTS: Expanding ART eligibility led to an increased number of patients initiating ART per month [+95.5; 95% CI (-1.3; 192.3)]. Newly eligible patients (CD4 201-350) initiated treatment 47% faster than before (95% CI 19%; 82%), while the sickest patients (CD4 ≤200) saw no decline in the monthly number of patients initiating treatment or the rate of treatment uptake. CONCLUSION: The Hlabisa program successfully extended ART to patients with CD4 ≤350 cells/μL, while ensuring that the sickest patients did not experience delays in ART initiation. Treatment programs must be vigilant to maintain quality of care for the sickest as countries move to treat all patients irrespective of CD4 count. This article is protected by copyright. All rights reserved

Making optical atomic clocks more stable with 10−1610^{-16} level laser stabilization

The superb precision of an atomic clock is derived from its stability. Atomic clocks based on optical (rather than microwave) frequencies are attractive because of their potential for high stability, which scales with operational frequency. Nevertheless, optical clocks have not yet realized this vast potential, due in large part to limitations of the laser used to excite the atomic resonance. To address this problem, we demonstrate a cavity-stabilized laser system with a reduced thermal noise floor, exhibiting a fractional frequency instability of $2 \times 10^{-16}$. We use this laser as a stable optical source in a Yb optical lattice clock to resolve an ultranarrow 1 Hz transition linewidth. With the stable laser source and the signal to noise ratio (S/N) afforded by the Yb optical clock, we dramatically reduce key stability limitations of the clock, and make measurements consistent with a clock instability of $5 \times 10^{-16} / \sqrt{\tau}$

Resurrection of an ancestral 5S rRNA

<p>Abstract</p> <p>Background</p> <p>In addition to providing phylogenetic relationships, tree making procedures such as parsimony and maximum likelihood can make specific predictions of actual historical sequences. Resurrection of such sequences can be used to understand early events in evolution. In the case of RNA, the nature of parsimony is such that when applied to multiple RNA sequences it typically predicts ancestral sequences that satisfy the base pairing constraints associated with secondary structure. The case for such sequences being actual ancestors is greatly improved, if they can be shown to be biologically functional.</p> <p>Results</p> <p>A unique common ancestral sequence of 28 <it>Vibrio </it>5S ribosomal RNA sequences predicted by parsimony was resurrected and found to be functional in the context of the <it>E. coli </it>cellular environment. The functionality of various point variants and intermediates that were constructed as part of the resurrection were examined in detail. When separately introduced the changes at single stranded positions and individual double variants at base-paired positions were also viable. An additional double variant was examined at a different base-paired position and it was also valid.</p> <p>Conclusions</p> <p>The results show that at least in the case of the 5S rRNAs considered here, ancestors predicted by parsimony are likely to be realistic when the prediction is not overly influenced by single outliers. It is especially noteworthy that the phenotype of the predicted ancestors could be anticipated as a cumulative consequence of the phenotypes of the individual variants that comprised them. Thus, point mutation data is potentially useful in evaluating the reasonableness of ancestral sequences predicted by parsimony or other methods. The results also suggest that in the absence of significant tertiary structure constraints double variants that preserve pairing in stem regions will typically be accepted. Overall, the results suggest that it will be feasible to resurrect additional meaningful 5S rRNA ancestors as well as ancestral sequences of many different types of RNA.</p

Dynamical approach to spectator fragmentation in Au+Au reactions at 35 MeV/A

The characteristics of fragment emission in peripheral $^{197}$Au+$^{197}$Au collisions 35 MeV/A are studied using the two clusterization approaches within framework of \emph{quantum molecular dynamics} model. Our model calculations using \emph{minimum spanning tree} (MST) algorithm and advanced clusterization method namely \emph{simulated annealing clusterization algorithm} (SACA) showed that fragment structure can be realized at an earlier time when spectators contribute significantly toward the fragment production even at such a low incident energy. Comparison of model predictions with experimental data reveals that SACA method can nicely reproduce the fragment charge yields and mean charge of the heaviest fragment. This reflects suitability of SACA method over conventional clusterization techniques to investigate spectator matter fragmentation in low energy domain.Comment: 6 pages, 5 figures, accepte

A phase 2 multicenter study of ublituximab, a novel glycoengineered anti-CD20 monoclonal antibody, in patients with relapsing forms of multiple sclerosis.

Background: Ublituximab, a novel monoclonal antibody (mAb) targeting a unique epitope on the CD20 antigen, is glycoengineered for enhanced B-cell targeting through antibody-dependent cellular cytotoxicity (ADCC). Greater ADCC may allow lower doses and shorter infusion times versus other anti-CD20 mAbs. Objective: The objective was to determine optimal dose, infusion time, and activity of ublituximab in relapsing multiple sclerosis. Methods: This is a phase 2, placebo-controlled study. Patients received three ublituximab infusions (150 mg over 1-4 hours on day 1 and 450-600 mg over 1-3 hours on day 15 and week 24) in six dosing cohorts. The primary endpoint was B-cell depletion. Results: In all cohorts (N = 48), median B-cell depletion was &gt;99% by week 4, maintained at weeks 24 and 48. Most common adverse events (AEs) were infusion-related reactions (all grade 1-2), with no apparent increased incidence at shorter infusion times. There were no AE-related discontinuations. At weeks 24 and 48, no T1 gadolinium-enhancing lesions (p = 0.003) and a 10.6% decrease in T2 lesion volume (p = 0.002) were detected. The annualized relapse rate was 0.07; 93% remained relapse free on study. Overall, 74% of patients had no evidence of disease activity (NEDA). Conclusion: Ublituximab was safely infused as rapid as 1 hour, producing robust B-cell depletion and profound reductions in magnetic resonance imaging (MRI) activity and relapses

Social impacts and life cycle assessment: proposals for methodological development for SMEs in the European food and drink sector

Purpose: Small and medium enterprises (SMEs) account for 99 % of companies operating in the European food and drink industry and, often, are part of highly fragmented and complex food chains. The article focuses on the development of a social impact assessment methodology for SMEs in selected food and drink products as part of the EU-FP7 SENSE research project. The proposed methodology employs a top-down and bottom-up approach and focuses on labour rights/working conditions along the product supply chain as the key social impact indicator, limiting key stakeholder classification to workers/employees and local communities impacted by the production process. Problems related to this emerging field are discussed, and questions for further research are expounded. Methods: The article reviews both academic and 'grey' literature on life cycle assessment (LCA) and its relationship to social LCA (S-LCA) and SMEs at the beginning of 2013 and includes case study evidence from the food sector. A pilot questionnaire survey sent to European food and drink sector SMEs and trade associations (as partners in the research project) about their knowledge, experience and engagement with social impacts is presented. Proposals are elaborated for a social impact assessment methodology that identifies the key data for SMEs to collect. Results and discussion: The literature reveals the complexity of the S-LCA approach as it aims to unite disparate and often conflicting interests. Findings from the pilot questionnaire are discussed. Using a top-down and bottom-up approach, the proposed methodology assesses data from SMEs along the supply chain in order to gauge social improvements in the management of labour-related issues for different product sectors. Issues relating to the 'attributional' choice of a social impact indicator and key stakeholder categories are discussed. How 'scoring' is interpreted and reported and what the intended effect of its use will be are also elaborated upon. Conclusions: Whilst recognising the difficulty of devising a robust social impact assessment for SMEs in the food and drink sector, it is argued that the proposed methodology makes a useful contribution in this fast-emerging field

Legal framework for small autonomous agricultural robots

Legal structures may form barriers to, or enablers of, adoption of precision agriculture management with small autonomous agricultural robots. This article develops a conceptual regulatory framework for small autonomous agricultural robots, from a practical, self-contained engineering guide perspective, sufficient to get working research and commercial agricultural roboticists quickly and easily up and running within the law. The article examines the liability framework, or rather lack of it, for agricultural robotics in EU, and their transpositions to UK law, as a case study illustrating general international legal concepts and issues. It examines how the law may provide mitigating effects on the liability regime, and how contracts can be developed between agents within it to enable smooth operation. It covers other legal aspects of operation such as the use of shared communications resources and privacy in the reuse of robot-collected data. Where there are some grey areas in current law, it argues that new proposals could be developed to reform these to promote further innovation and investment in agricultural robots

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective

Evaluation of the zucker diabetic fatty (ZDF) rat as a model for human disease based on urinary peptidomic profiles

Representative animal models for diabetes-associated vascular complications are extremely relevant in assessing potential therapeutic drugs. While several rodent models for type 2 diabetes (T2D) are available, their relevance in recapitulating renal and cardiovascular features of diabetes in man is not entirely clear. Here we evaluate at the molecular level the similarity between Zucker diabetic fatty (ZDF) rats, as a model of T2D-associated vascular complications, and human disease by urinary proteome analysis. Urine analysis of ZDF rats at early and late stages of disease compared to age- matched LEAN rats identified 180 peptides as potentially associated with diabetes complications. Overlaps with human chronic kidney disease (CKD) and cardiovascular disease (CVD) biomarkers were observed, corresponding to proteins marking kidney damage (eg albumin, alpha-1 antitrypsin) or related to disease development (collagen). Concordance in regulation of these peptides in rats versus humans was more pronounced in the CVD compared to the CKD panels. In addition, disease-associated predicted protease activities in ZDF rats showed higher similarities to the predicted activities in human CVD. Based on urinary peptidomic analysis, the ZDF rat model displays similarity to human CVD but might not be the most appropriate model to display human CKD on a molecular level

Investigation of attentional bias in obsessive compulsive disorder with and without depression in visual search

Copyright: © 2013 Morein-Zamir et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedWhether Obsessive Compulsive Disorder (OCD) is associated with an increased attentional bias to emotive stimuli remains controversial. Additionally, it is unclear whether comorbid depression modulates abnormal emotional processing in OCD. This study examined attentional bias to OC-relevant scenes using a visual search task. Controls, non-depressed and depressed OCD patients searched for their personally selected positive images amongst their negative distractors, and vice versa. Whilst the OCD groups were slower than healthy individuals in rating the images, there were no group differences in the magnitude of negative bias to concern-related scenes. A second experiment employing a common set of images replicated the results on an additional sample of OCD patients. Although there was a larger bias to negative OC-related images without pre-exposure overall, no group differences in attentional bias were observed. However, OCD patients subsequently rated the images more slowly and more negatively, again suggesting post-attentional processing abnormalities. The results argue against a robust attentional bias in OCD patients, regardless of their depression status and speak to generalized difficulties disengaging from negative valence stimuli. Rather, post-attentional processing abnormalities may account for differences in emotional processing in OCD.Peer reviewedFinal Published versio