A cost-effectiveness analysis of provider and community interventions to improve the treatment of uncomplicated malaria in Nigeria: study protocol for a randomized controlled trial.

BACKGROUND: There is mounting evidence of poor adherence by health service personnel to clinical guidelines for malaria following a symptomatic diagnosis. In response to this, the World Health Organization (WHO) recommends that in all settings clinical suspicion of malaria should be confirmed by parasitological diagnosis using microscopy or Rapid Diagnostic Test (RDT). The Government of Nigeria plans to introduce RDTs in public health facilities over the coming year. In this context, we will evaluate the effectiveness and cost-effectiveness of two interventions designed to support the roll-out of RDTs and improve the rational use of ACTs. It is feared that without supporting interventions, non-adherence will remain a serious impediment to implementing malaria treatment guidelines. METHODS/DESIGN: A three-arm stratified cluster randomized trial is used to compare the effectiveness and cost-effectiveness of: (1) provider malaria training intervention versus expected standard practice in malaria diagnosis and treatment; (2) provider malaria training intervention plus school-based intervention versus expected standard practice; and (3) the combined provider plus school-based intervention versus provider intervention alone. RDTs will be introduced in all arms of the trial. The primary outcome is the proportion of patients attending facilities that report a fever or suspected malaria and receive treatment according to malaria guidelines. This will be measured by surveying patients (or caregivers) as they exit primary health centers, pharmacies, and patent medicine dealers. Cost-effectiveness will be presented in terms of the primary outcome and a range of secondary outcomes, including changes in provider and community knowledge. Costs will be estimated from both a societal and provider perspective using standard economic evaluation methodologies. TRIAL REGISTRATION: Clinicaltrials.gov NCT01350752

Does maternal exposure to an environmental stressor affect offspring response to predators?

There is growing recognition of the ways in which maternal effects can influence offspring size, physiological performance, and survival. Additionally, environmental contaminants increasingly act as stressors in maternal environments, possibly leading to maternal effects on subsequent offspring. Thus, it is important to determine whether contaminants and other stressors can contribute to maternal effects, particularly under varied ecological conditions that encompass the range under which offspring develop. We used aquatic mesocosms to determine whether maternal effects of mercury (Hg) exposure shape offspring phenotype in the American toad (Bufo americanus) in the presence or absence of larval predators (dragonfly naiads). We found significant maternal effects of Hg exposure and significant effects of predators on several offspring traits, but there was little evidence that maternal effects altered offspring interactions with predators. Offspring from Hg-exposed mothers were 18% smaller than those of reference mothers. Offspring reared with predators were 23% smaller at metamorphosis than those reared without predators. There was also evidence of reduced larval survival when larvae were reared with predators, but this was independent of maternal effects. Additionally, 5 times more larvae had spinal malformations when reared without predators, suggesting selective predation of malformed larvae by predators. Lastly, we found a significant negative correlation between offspring survival and algal density in mesocosms, indicating a role for top-down effects of predators on periphyton communities. Our results demonstrate that maternal exposure to an environmental stressor can induce phenotypic responses in offspring in a direction similar to that produced by direct exposure of offspring to predators

DNA resection in eukaryotes: deciding how to fix the break

DNA double-strand breaks are repaired by different mechanisms, including homologous recombination and nonhomologous end-joining. DNA-end resection, the first step in recombination, is a key step that contributes to the choice of DSB repair. Resection, an evolutionarily conserved process that generates single-stranded DNA, is linked to checkpoint activation and is critical for survival. Failure to regulate and execute this process results in defective recombination and can contribute to human disease. Here, I review recent findings on the mechanisms of resection in eukaryotes, from yeast to vertebrates, provide insights into the regulatory strategies that control it, and highlight the consequences of both its impairment and its deregulation

The Surgical Infection Society revised guidelines on the management of intra-abdominal infection

Background: Previous evidence-based guidelines on the management of intra-abdominal infection (IAI) were published by the Surgical Infection Society (SIS) in 1992, 2002, and 2010. At the time the most recent guideline was released, the plan was to update the guideline every five years to ensure the timeliness and appropriateness of the recommendations. Methods: Based on the previous guidelines, the task force outlined a number of topics related to the treatment of patients with IAI and then developed key questions on these various topics. All questions were approached using general and specific literature searches, focusing on articles and other information published since 2008. These publications and additional materials published before 2008 were reviewed by the task force as a whole or by individual subgroups as to relevance to individual questions. Recommendations were developed by a process of iterative consensus, with all task force members voting to accept or reject each recommendation. Grading was based on the GRADE (Grades of Recommendation Assessment, Development, and Evaluation) system; the quality of the evidence was graded as high, moderate, or weak, and the strength of the recommendation was graded as strong or weak. Review of the document was performed by members of the SIS who were not on the task force. After responses were made to all critiques, the document was approved as an official guideline of the SIS by the Executive Council. Results: This guideline summarizes the current recommendations developed by the task force on the treatment of patients who have IAI. Evidence-based recommendations have been made regarding risk assessment in individual patients; source control; the timing, selection, and duration of antimicrobial therapy; and suggested approaches to patients who fail initial therapy. Additional recommendations related to the treatment of pediatric patients with IAI have been included. Summary: The current recommendations of the SIS regarding the treatment of patients with IAI are provided in this guideline

Tool-use learning by common marmosets (Callithrix jacchus)

One of the most critical and common features of tool use is that the tool essentially functions as a part of the body. This feature is likely rooted in biological features that are shared by tool users. To establish an ideal primate model to explore the neurobiological mechanisms supporting tool-use behaviours, we trained common marmosets, a small New World monkey species that is not usually associated with tool use, to use a rake-shaped tool to retrieve food. Five naive common marmosets were systematically trained to manipulate the tool using a 4-stage, step-by-step protocol. The relative positions of the tool and the food were manipulated, so that the marmosets were required to (1) pull the tool vertically, (2) move the tool horizontally, (3) make an arc to retrieve a food item located behind the tool and (4) retrieve the food item. We found considerable individual differences in tool-use technique; for example, one animal consistently used a unilateral hand movement for all of the steps, whereas the others (n = 4) used both hands to move the tool depending on the location of the food item. After extensive training, all of the marmosets could manipulate the rake-shaped tool, which is reported in this species for the first time. The common marmoset is thus a model primate for such studies. This study sets the stage for future research to examine the biological mechanisms underlying the cognitive ability of tool use at the molecular and genetic levels

Species identification by experts and non-experts: comparing images from field guides

Accurate species identification is fundamental when recording ecological data. However, the ability to correctly identify organisms visually is rarely questioned. We investigated how experts and non-experts compared in the identification of bumblebees, a group of insects of considerable conservation concern. Experts and non-experts were asked whether two concurrent bumblebee images depicted the same or two different species. Overall accuracy was below 60% and comparable for experts and non-experts. However, experts were more consistent in their answers when the same images were repeated, and more cautious in committing to a definitive answer. Our findings demonstrate the difficulty of correctly identifying bumblebees using images from field guides. Such error rates need to be accounted for when interpreting species data, whether or not they have been collected by experts. We suggest that investigation of how experts and non-experts make observations should be incorporated into study design, and could be used to improve training in species identification

Automatic mapping of atoms across both simple and complex chemical reactions

Mapping atoms across chemical reactions is important for substructure searches, automatic extraction of reaction rules, identification of metabolic pathways, and more. Unfortunately, the existing mapping algorithms can deal adequately only with relatively simple reactions but not those in which expert chemists would benefit from computer's help. Here we report how a combination of algorithmics and expert chemical knowledge significantly improves the performance of atom mapping, allowing the machine to deal with even the most mechanistically complex chemical and biochemical transformations. The key feature of our approach is the use of few but judiciously chosen reaction templates that are used to generate plausible "intermediate" atom assignments which then guide a graph-theoretical algorithm towards the chemically correct isomorphic mappings. The algorithm performs significantly better than the available state-of-the-art reaction mappers, suggesting its uses in database curation, mechanism assignments, and - above all - machine extraction of reaction rules underlying modern synthesis-planning programs

Induction of IgG3 to LPS via Toll-Like Receptor 4 Co-Stimulation

B-cells integrate antigen-specific signals transduced via the B-cell receptor (BCR) and antigen non-specific co-stimulatory signals provided by cytokines and CD40 ligation in order to produce IgG antibodies. Toll-like receptors (TLRs) also provide co-stimulation, but the requirement for TLRs to generate T-cell independent and T-cell dependent antigen specific antibody responses is debated. Little is known about the role of B-cell expressed TLRs in inducing antigen-specific antibodies to antigens that also activate TLR signaling. We found that mice lacking functional TLR4 or its adaptor molecule MyD88 harbored significantly less IgG3 natural antibodies to LPS, and required higher amounts of LPS to induce anti-LPS IgG3. In vitro, BCR and TLR4 signaling synergized, lowering the threshold for production of T-cell independent IgG3 and IL-10. Moreover, BCR and TLR4 directly associate through the transmembrane domain of TLR4. Thus, in vivo, BCR/TLR synergism could facilitate the induction of IgG3 antibodies against microbial antigens that engage both innate and adaptive B-cell receptors. Vaccines might exploit BCR/TLR synergism to rapidly induce antigen-specific antibodies before significant T-cell responses arise

Drug Off-Target Effects Predicted Using Structural Analysis in the Context of a Metabolic Network Model

Recent advances in structural bioinformatics have enabled the prediction of protein-drug off-targets based on their ligand binding sites. Concurrent developments in systems biology allow for prediction of the functional effects of system perturbations using large-scale network models. Integration of these two capabilities provides a framework for evaluating metabolic drug response phenotypes in silico. This combined approach was applied to investigate the hypertensive side effect of the cholesteryl ester transfer protein inhibitor torcetrapib in the context of human renal function. A metabolic kidney model was generated in which to simulate drug treatment. Causal drug off-targets were predicted that have previously been observed to impact renal function in gene-deficient patients and may play a role in the adverse side effects observed in clinical trials. Genetic risk factors for drug treatment were also predicted that correspond to both characterized and unknown renal metabolic disorders as well as cryptic genetic deficiencies that are not expected to exhibit a renal disorder phenotype except under drug treatment. This study represents a novel integration of structural and systems biology and a first step towards computational systems medicine. The methodology introduced herein has important implications for drug development and personalized medicine

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente