StrongNet: An International Network to Improve Diagnostics and Access to Treatment for Strongyloidiasis Control

Strongyloidiasis is a disease caused by an infection with a soil-transmitted helminth that affects, according to largely varying estimates, between 30 million and 370 million people worldwide [1,2]. Not officially listed as a neglected tropical disease (NTD), strongyloidiasis stands out as particularly overlooked [3]. Indeed, there is a paucity of research and public health efforts pertaining to strongyloidiasis. Hence, clinical, diagnostic, epidemiologic, treatment, and control aspects are not adequately addressed to allow for an effective management of the disease, both in clinical medicine and in public health programs [4]. The manifold signs and symptoms caused by Strongyloides stercoralis infection, coupled with the helminth’s unique potential to cause lifelong, persistent infection, make strongyloidiasis relevant beyond tropical and subtropical geographic regions, where, however, most of the disease burden is concentrated. Indeed, strongyloidiasis is acquired through contact with contaminated soil, and the infection is, thus, primarily transmitted in areas with poor sanitation, inadequate access to clean water, and lack of hygiene

Efficient raytracing of deforming point-sampled surfaces

We present efficient data structures and caching schemes to accelerate ray-surface intersections for deforming point-sampled surfaces. By exploiting spatial and temporal coherence of the deformation during the animation, we are able to improve rendering performance by a factor of two to three compared to existing techniques. Starting from a tight bounding sphere hierarchy for the undeformed object, we use a lazy updating scheme to adapt the hierarchy to the deformed surface in each animation step. In addition, we achieve a significant speedup for ray-surface intersections by caching per-ray intersection points. We also present a technique for rendering sharp edges and corners in point-sampled models by introducing a novel surface clipping algorithm. © The Eurographics Association and Blackwell Publishing 2005

Meshless animation of fracturing solids

We present a new meshless animation framework for elastic and plastic materials that fracture. Central to our method is a highly dynamic surface and volume sampling method that supports arbitrary crack initiation, propagation, and termination, while avoiding many of the stability problems of traditional mesh-based techniques. We explicitly model advancing crack fronts and associated fracture surfaces embedded in the simulation volume. When cutting through the material, crack fronts directly affect the coupling between simulation nodes, requiring a dynamic adaptation of the nodal shape functions. We show how local visibility tests and dynamic caching lead to an efficient implementation of these effects based on point collocation. Complex fracture patterns of interacting and branching cracks are handled using a small set of topological operations for splitting, merging, and terminating crack fronts. This allows continuous propagation of cracks with highly detailed fracture surfaces, independent of the spatial resolution of the simulation nodes, and provides effective mechanisms for controlling fracture paths. We demonstrate our method for a wide range of materials, from stiff elastic to highly plastic objects that exhibit brittle and/or ductile fracture. Copyright © 2005 by the Association for Computing Machinery, Inc

The Clinical Impact of Continuing to Prescribe Antiretroviral Therapy in Patients with Advanced AIDS Who Manifest No Virologic or Immunologic Benefit

Introduction: Despite the efficacy and tolerability of modern antiretroviral therapy (ART), many patients with advanced AIDS prescribed these regimens do not achieve viral suppression or immune reconstitution as a result of poor adherence, drug resistance, or both. The clinical outcomes of continued ART prescription for such patients have not been well characterized. Methods: We examined the causes and predictors of all-cause mortality, AIDS-defining conditions, and serious non-AIDS-defining events among a cohort of participants in a clinical trial of pre-emptive therapy for CMV disease. We focused on participants who, despite ART had failed to achieve virologic suppression and substantive immune reconstitution. Results: 233 ART-receiving participants entered with a median baseline CD4+ T cell count of 30/mm3 and plasma HIV RNA of 5 log10 copies/mL. During a median 96 weeks of follow-up, 24.0% died (a mortality rate of 10.7/100 patient-years); 27.5% reported a new AIDS-defining condition, and 22.3% a new serious non-AIDS event. Of the deaths, 42.8% were due to an AIDS-defining condition, 44.6% were due to a non-AIDS-defining condition, and 12.5% were of unknown etiology. Decreased risk of mortality was associated with baseline CD4+ T cell count ≥25/mm3 and lower baseline HIV RNA. Conclusions: Among patients with advanced AIDS prescribed modern ART who achieve neither virologic suppression nor immune reconstitution, crude mortality percentages appear to be lower than reported in cohorts of patients studied a decade earlier. Also, in contrast to the era before modern ART became available, nearly half of the deaths in our modern-era study were caused by serious non-AIDS-defining events. Even among the most advanced AIDS patients who were not obtaining apparent immunologic and virologic benefit from ART, continued prescription of these medications appears to alter the natural history of AIDS—improving survival and shifting the causes of death from AIDS- to non-AIDS-defining conditions

Retention in care of HIV-infected pregnant and lactating women starting art under Option B+ in rural Mozambique.

OBJECTIVE In 2013, Mozambique adopted Option B+, universal lifelong antiretroviral therapy (ART) for all pregnant and lactating women, as national strategy for prevention of mother-to-child transmission of HIV. We analyzed retention in care of pregnant and lactating women starting Option B+ in rural northern Mozambique. METHODS We compared ART outcomes in pregnant ("B+pregnant"), lactating ("B+lactating") and non-pregnant-non-lactating women of childbearing age starting ART after clinical and/or immunological criteria ("own health") between July 2013 and June 2014. Lost to follow-up was defined as no contact >180 days after the last visit. Multivariable competing risk models were adjusted for type of facility (type 1 vs. peripheral type 2 health center), age, WHO stage and time from HIV diagnosis to ART. RESULTS Over 333 person-years of follow-up (of 243 "B+pregnant", 65″B+lactating" and 317 "own health" women), 3.7% of women died and 48.5% were lost to follow-up. "B+pregnant" and "B+lactating" women were more likely to be lost in the first year (57% vs. 56.9% vs. 31.6%; p<0.001) and to have no follow-up after the first visit (42.4% vs. 29.2% vs. 16.4%; p<0.001) than "own health" women. In adjusted analyses, risk of being lost to follow-up was higher in "B+pregnant" (adjusted subhazard ratio [asHR]: 2.77; 95% CI: 2.18-3.50; p<0.001) and "B+lactating" (asHR: 1.94; 95% CI: 1.37-2.74; p<0.001). Type 2 health center was the only additional significant risk factor for loss to follow-up. CONCLUSIONS Retaining pregnant and lactating women in option B+ ART was poor; losses to follow-up were mainly early. The success of Option B+ for prevention of mother-to-child transmission of HIV in rural settings with weak health systems will depend on specific improvements in counseling and retention measures, especially at the beginning of treatment. This article is protected by copyright. All rights reserved

Research Needs and Challenges in the FEW System: Coupling Economic Models with Agronomic, Hydrologic, and Bioenergy Models for Sustainable Food, Energy, and Water Systems

On October 12–13, a workshop funded by the National Science Foundation was held at Iowa State University in Ames, Iowa with a goal of identifying research needs related to coupled economic and biophysical models within the FEW system. Approximately 80 people attended the workshop with about half representing the social sciences (primarily economics) and the rest from the physical and natural sciences. The focus and attendees were chosen so that findings would be particularly relevant to SBE research needs while taking into account the critical connectivity needed between social sciences and other disciplines. We have identified several major gaps in existing scientific knowledge that present substantial impediments to understanding the FEW system. We especially recommend research in these areas as a priority for future funding: 1. Economic models of decision-making in coupled systems Deliberate human activity has been the dominant factor driving environmental and land-use changes for hundreds of years. While economists have made great strides in modeling and understanding these choices, the coupled systems modeling literature, with some important exceptions, has not reflected these contributions. Several paths forward seem fruitful. First, baseline economic models that assume rationality can be used much more widely than they are currently. Moreover, the current generation of IAMs that include rational agents have emphasized partial equilibrium studies appropriate for smaller systems. To allow this approach to be used to study larger systems, the potential for (and consequences of) general equilibrium effects should be studied as well. Second, it is important to address shortcomings in these models of economic decision-making. Valuable improvements could be gained from developing coupled models that draw insights from behavioral economics. Many decision-makers deviate systematically from actions that would be predicted by strict rationality, but very few IAMs incorporate this behavior, potentially leading to inaccurate predictions about the effects of policies and regulations. Improved models of human adaptation and induced technological change can also be incorporated into coupled models. Particularly for medium to long-run models, decisions about adaptation and technological change will have substantial effects on the conclusions and policy implications, but more compelling methods for incorporating these changes into modeling are sorely needed. In addition, some economic decisions are intrinsically dynamic yet few coupled models explicitly incorporate dynamic models. Economic models that address uncertainty in decision making are also underutilized in coupled models of the FEW system. 2. Coupling models across disciplines Despite much recent progress, established models for one component of the FEW system often cannot currently produce outcomes that can be used as inputs for models of other components. This misalignment makes integrated modeling difficult and is especially apparent in linking models of natural phenomena with models of economic decision-making. Economic agents typically act to maximize a form of utility or welfare that is not directly linked to physical processes, and they typically require probabilistic forecasts as an input to their decision-making that many models in the natural sciences cannot directly produce. We believe that an especially promising approach is the development of “bridge” models that convert outputs from one model into inputs for another. Such models can be viewed as application-specific, reduced-form distillations of a richer and more realistic underlying model. Ideally, these bridge models would be developed in collaborative research projects involving economists, statisticians, and disciplinary specialists, and would contribute to improved understanding in the scientific discipline as well. 3. Model validation and comparison There is little clarity on how models should be evaluated and compared to each other, both within individual disciplines and as components of larger IAMs. This challenge makes larger integrated modeling exercises extremely difficult. Some potential ways to advance are by developing statistical criteria that measure model performance along the dimensions suitable for inclusion in an IAM as well as infrastructure and procedures to facilitate model comparisons. Focusing on the models’ out-of-sample distributional forecasting performance, as well as that of the IAM overall, is especially promising and of particular importance. Moreover, applications of IAMs tend to estimate the effect of hypothetical future policy actions, but there have been very few studies that have used these models to estimate the effect of past policy actions. These exercises should be encouraged. They offer a well-understood test bed for the IAMs, and also contribute to fundamental scientific knowledge through better understanding of the episode in question. The retrospective nature of this form of analysis also presents the opportunity to combine reduced-form estimation strategies with the IAMs as an additional method of validation

Throwing more light on the dark side of psychopathy: An extension of previous findings for the revised Reinforcement Sensitivity Theory

Despite previous studies of psychopathy and the motivational systems of the Reinforcement Sensitivity Theory (RST) of personality, few have examined psychopathy in light of the revised RST model. In a large sample (N= 779) of young adults, we expand on Hughes, Moore, Morris, and Corr's (2012) preliminary findings relating primary/secondary psychopathy to revised RST's three systems: Flight-Flight-Freeze System (FFFS), Behavioral Inhibition System (BIS), and Behavioral Approach System (BAS). Converging results between Hughes et al. and the current study emphasize three major findings: (1) primary psychopathy is negatively related to the BIS as well as the FFFS; (2) primary psychopathy is positively related to goal-driven behavior of the BAS; and, (3) secondary psychopathy is positively related to impulsivity reflected in the BAS. The FFFS was incrementally predictive of primary but not secondary psychopathy. No evidence for a BAS × BIS interaction in psychopathy was found. Results are discussed in terms of future research directions

Enabling structural resilience of street-involved children and youth in Kenya: reintegration outcomes and the Flourishing Community model

IntroductionMillions of children and youth live on city streets across the globe, vulnerable to substance use, abuse, material and structural neglect. Structural resilience, the re-establishment of access to structural goods within a society such as housing, education, and healthcare following some interruption, provides an orientation for research and interventional efforts with street-involved children and youth (SICY). Further, a structural resilience framework supports organizing interactions between levels and sectors of a socio-ecology.MethodsFollowing the expressed interests of Kenyan SICY, and consistent with emerging policy interests at national and global levels, we assess reintegration trajectories of Kenyan SICY (n = 227) participating in a new program intervention and model. The intervention combines two coordinated, parallel programs – one focused on the rescue, rehabilitation, reintegration and resocialization of SICY, and the other focused on empowering families and communities to provide better care for children and youth who are reintegrating from life on the streets to the broader community. Data were collected and analyzed from multiple stages across SICY involvement with the intervention.ResultsWe found 79% of SICY participants reintegrated with the broader community, and 50% reintegrated with families of origin and returned to school. Twenty-five percent of participants reintegrated to a boarding school, polytechnical school, or began a business. Probability of reintegrating successfully was significantly improved among participants whose families participated in the family- and community-oriented program, who were younger, with less street-exposure, expressed more personal interests, and desired to reintegrate with family.DiscussionTo our knowledge, these are the first quantitative data published of successful reintegration of SICY to the broader, non-institutionalized community in any low- or middle-income country. Future research should (1) identify factors across socio-ecological levels and sectors contributing to health and developmental outcomes of reintegrated children and youth, (2) mechanisms to support SICY for whom the interventional strategy did not work, (3) methods to prevent street-migration by children and youth, and (4) system development to coordinate follow-up and relevant investment by institutions, organizations and community leaders to continue reintegration work

An Observational Cohort Comparison of Facilitators of Retention in Care and Adherence to Anti-Eetroviral Therapy at an HIV Treatment Center in Kenya

BACKGROUND: Most HIV treatment programs in resource-limited settings utilize multiple facilitators of adherence and retention in care but there is little data on the efficacy of these methods. We performed an observational cohort analysis of a treatment program in Kenya to assess which program components promote adherence and retention in HIV care in East Africa. METHODS: Patients initiating ART at A.I.C. Kijabe Hospital were prospectively enrolled in an observational study. Kijabe has an intensive program to promote adherence and retention in care during the first 6 months of ART that incorporates the following facilitators: home visits by community health workers, community based support groups, pharmacy counseling, and unannounced pill counts by clinicians. The primary endpoint was time to treatment failure, defined as a detectable HIV-1 viral load; discontinuation of ART; death; or loss to follow-up. Time to treatment failure for each facilitator was calculated using Kaplan-Meier analysis. The relative effects of the facilitators were determined by the Cox Proportional Hazards Model. RESULTS: 301 patients were enrolled. Time to treatment failure was longer in patients participating in support groups (448 days vs. 337 days, P<0.001), pharmacy counseling (480 days vs. 386 days, P = 0.002), pill counts (482 days vs. 189 days, P<0.001) and home visits (485 days vs. 426 days, P = 0.024). Better adherence was seen with support groups (89% vs. 82%, P = 0.05) and pill counts (89% vs. 75%, P = 0.02). Multivariate analysis using the Cox Model found significant reductions in risk of treatment failure associated with pill counts (HR = 0.19, P<0.001) and support groups (HR = 0.43, P = 0.003). CONCLUSION: Unannounced pill counts by the clinician and community based support groups were associated with better long term treatment success and with better adherence

A Mapping of Drug Space from the Viewpoint of Small Molecule Metabolism

Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the “effect space” comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism