The Prevalence of Fatigue Following Deep Brain Stimulation Surgery in Parkinson's Disease and Association with Quality of Life

Fatigue is a common and disabling nonmotor symptom seen in Parkinson's disease (PD). While deep brain stimulation surgery (DBS) improves motor symptoms, it has also been associated with non-motor side effects. To date no study has utilized standardized instruments to evaluate fatigue following DBS surgery. Our objective was to determine the prevalence of fatigue following DBS surgery in PD its impact on quality of life and explore predictive factors. We recruited 44 PD subjects. At least one year following DBS placement, we administered the Fatigue Severity Scale (FSS), the Parkinson's Disease Questionnaire (PDQ-39), the Beck Depression Inventory, the Beck Anxiety Inventory, the UPDRS, and a neuropsychological battery. Fifty-eight percent of subjects had moderate to severe fatigue. Fatigue was significantly associated with quality of life, depression, and anxiety. Depression preoperatively was the only predictive factor of fatigue. Fatigue is common following DBS surgery and significantly impacts quality of life

Who speaks for the future of Earth? How critical social science can extend the conversation on the Anthropocene

This paper asks how the social sciences can engage with the idea of the Anthropocene in productive ways. In response to this question we outline an interpretative research agenda that allows critical engagement with the Anthropocene as a socially and culturally bounded object with many possible meanings and political trajectories. In order to facilitate the kind of political mobilization required to meet the complex environmental challenges of our times, we argue that the social sciences should refrain from adjusting to standardized research agendas and templates. A more urgent analytical challenge lies in exposing, challenging and extending the ontological assumptions that inform how we make sense of and respond to a rapidly changing environment. By cultivating environmental research that opens up multiple interpretations of the Anthropocene, the social sciences can help to extend the realm of the possible for environmental politics

Determination of HIV status and identification of incident HIV infections in a large, community-randomized trial: HPTN 071 (PopART).

INTRODUCTION: The HPTN 071 (PopART) trial evaluated the impact of an HIV combination prevention package that included "universal testing and treatment" on HIV incidence in 21 communities in Zambia and South Africa during 2013-2018. The primary study endpoint was based on the results of laboratory-based HIV testing for> 48,000 participants who were followed for up to three years. This report evaluated the performance of HIV assays and algorithms used to determine HIV status and identify incident HIV infections in HPTN 071, and assessed the impact of errors on HIV incidence estimates. METHODS: HIV status was determined using a streamlined, algorithmic approach. A single HIV screening test was performed at centralized laboratories in Zambia and South Africa (all participants, all visits). Additional testing was performed at the HPTN Laboratory Center using antigen/antibody screening tests, a discriminatory test and an HIV RNA test. This testing was performed to investigate cases with discordant test results and confirm incident HIV infections. RESULTS: HIV testing identified 978 seroconverter cases. This included 28 cases where the participant had acute HIV infection at the first HIV-positive visit. Investigations of cases with discordant test results identified cases where there was a participant or sample error (mixups). Seroreverter cases (errors where status changed from HIV infected to HIV uninfected, 0.4% of all cases) were excluded from the primary endpoint analysis. Statistical analysis demonstrated that exclusion of those cases improved the accuracy of HIV incidence estimates. CONCLUSIONS: This report demonstrates that the streamlined, algorithmic approach effectively identified HIV infections in this large cluster-randomized trial. Longitudinal HIV testing (all participants, all visits) and quality control testing provided useful data on the frequency of errors and provided more accurate data for HIV incidence estimates

Chapter 4. In search of relevant predictors for marine species distribution modelling using the MarineSPEED benchmark dataset

Aim: Ideally, datasets for species distribution modelling (SDM) contain evenly sampled records covering the entire distribution of the species, confirmed absences and auxiliary ecophysiological data allowing informed decisions on relevant predictors. Unfortunately, these criteria are rarely met for marine organisms for which distributions are too often only scantly characterized and absences generally not recorded. Here, we investigate predictor relevance as a function of modelling algorithms and settings for a global dataset of marine species.Location: Global marine.Methods: We selected well-studied and identifiable species from all major marine taxonomic groups. Distribution records were compiled from public sources (e.g., OBIS, GBIF, Reef Life Survey) and linked to environmental data from Bio-ORACLE and MARSPEC. Using this dataset, predictor relevance was analysed under different variations of modelling algorithms, numbers of predictor variables, cross-validation strategies, sampling bias mitigation methods, evaluation methods and ranking methods. SDMs for all combinations of predictors from eight correlation groups were fitted and ranked, from which the top five predictors were selected as the most relevant. Results: We collected two million distribution records from 514 species across 18 phyla. Mean sea surface temperature and calcite are, respectively, the most relevant and irrelevant predictors. A less clear pattern was derived from the other predictors. The biggest differences in predictor relevance were induced by varying the number of predictors, the modelling algorithm and the sample selection bias correction. The distribution data and associated environmental data are made available through the R package marinespeed and at http://marinespeed.org.Main conclusions: While temperature is a relevant predictor of global marine species distributions, considerable variation in predictor relevance is linked to the SDM set-up. We promote the usage of a standardized benchmark dataset (MarineSPEED) for methodological SDM studies

Antiretroviral Drug Detection in a Community-Randomized Trial of Universal HIV Testing and Treatment: HPTN 071 (PopART).

BACKGROUND: Antiretroviral therapy (ART) reduces human immunodeficiency virus (HIV) transmission risk. The primary aim of this study was to evaluate ART uptake in a trial in Zambia and South Africa that implemented a community-wide universal testing and treatment package to reduce HIV incidence. METHODS: Study communities were randomized to 3 arms: A, combination-prevention intervention with universal ART; B, combination-prevention intervention with ART according to local guidelines; and C, standard of care. Samples were collected from people with HIV (PWH) during a survey visit conducted 2 years after study implementation: these samples were tested for 22 antiretroviral (ARV) drugs. Antiretroviral therapy uptake was defined as detection of ≥1 ARV drug. Resistance was evaluated in 612 randomly selected viremic participants. A 2-stage, cluster-based approach was used to assess the impact of the study intervention on ART uptake. RESULTS: Antiretroviral drugs were detected in 4419 of 6207 (71%) samples (Arm A, 73%; Arm B, 70%; Arm C, 60%); 4140 (94%) of samples with ARV drugs had viral loads <400 copies/mL. Drug resistance was observed in 237 of 612 (39%) viremic participants (95 of 102 [93%] with ARV drugs; 142 of 510 [28%] without drugs). Antiretroviral therapy uptake was associated with older age, female sex, enrollment year, seroconverter status, and self-reported ART (all P < .001). The adjusted risk ratio for ART uptake was similar for Arm A versus C (1.21; 95% confidence interval [CI], .94-1.54; P = .12) and Arm B versus C (1.14; 95% CI, .89-1.46; P = .26). CONCLUSIONS: At the 2-year survey, 71% of PWH were on ART and 94% of those participants were virally suppressed. Universal testing and treatment was not significantly associated with increased ART uptake in this cohort

A novel method for mapping reefs and subtidal rocky habitats using artificial neural networks

Reefs and subtidal rocky habitats are sites of high biodiversity and productivity which harbour commercially important species of fish and invertebrates. Although the conservation management of reef associated species has been informed using species distribution models (SDM) and community based approaches, to date their use has been constrained to specific regions where the locality and spatial extent of reefs is well known. Much of the world's subtidal habitats remain either undiscovered or unmapped, including coasts of intense human use. Consequently, to facilitate a stronger understanding of species-environmental relationships there is an urgent need for a cost and time effective standard method to map reefs at fine spatial resolutions across broad geographical extents. We used bathymetric data (∼250. m resolution) to calculate the local slope and curvature of the seabed. We then constructed artificial neural networks (ANNs) to forecast the probability of reef occurrence within grid cells as a function of bathymetric and slope variables. Testing over an independent data set not used in training showed that ANNs were able to accurately predict the location of reefs for 86% of all grid cells (Kappa = 0.63) without over fitting. The ANN with greatest support, combining bathymetric values of the target grid cell with the slope of adjacent grid cells, was used to map inshore reef locations around the Southern Australian coastline (∼250. m resolution). Broadly, our results show that reefs are identifiable from coarse-scale bathymetry data of the seabed. We anticipate that our research technique will strengthen systematic conservation planning tools in many regions of the world, by enabling the identification of rocky substratum and mapping in localities that remain poorly surveyed due to logistics or monetary constraints. © 2011 Elsevier B.V.Michael J. Watts, Yuxiao Li, Bayden D. Russell, Camille Mellin, Sean D. Connell, Damien A. Fordha

Sex-biased weaning and early childhood diet among middle holocene hunter-gatherers in Central California

This article evaluates age of weaning and early childhood diets of eight males and nine females from a Middle Holocene (4300-3000 BP) site in Central California, CA-CCO-548. All individuals died as adults. δ(15) N values from serial sections of dentin collagen in first molars suggest females were fully weaned, on average, by 3.6 years of age, about 0.4 years later than males in the sample, suggesting possible greater parental investment in female offspring. However, throughout childhood females consumed lower trophic-level foods than males. This could indicate greater investment in males through provisioning of higher quality foods, or alternatively, some degree of independent foraging by males starting as early as 2 to 3 years of age. Even as adults, these same males and females consumed a different range of foods as indicated by their bone collagen δ(13) C and δ(15) N values. Overall, the data suggest children were enculturated early into their respective gendered diets, with girls consuming greater amounts of plant foods and boys consuming greater amounts of higher-trophic level fish and meat protein