Feasibility, drug safety, and effectiveness of etiological treatment programs for Chagas disease in Honduras, Guatemala, and Bolivia: 10-year experience of Médecins Sans Frontières

BACKGROUND: Chagas disease (American trypanosomiasis) is a zoonotic or anthropozoonotic disease caused by the parasite Trypanosoma cruzi. Predominantly affecting populations in poor areas of Latin America, medical care for this neglected disease is often lacking. Médecins Sans Frontières/Doctors Without Borders (MSF) has provided diagnostic and treatment services for Chagas disease since 1999. This report describes 10 years of field experience in four MSF programs in Honduras, Guatemala, and Bolivia, focusing on feasibility protocols, safety of drug therapy, and treatment effectiveness. METHODOLOGY: From 1999 to 2008, MSF provided free diagnosis, etiological treatment, and follow-up care for patients <18 years of age seropositive for T. cruzi in Yoro, Honduras (1999-2002); Olopa, Guatemala (2003-2006); Entre Ríos, Bolivia (2002-2006); and Sucre, Bolivia (2005-2008). Essential program components guaranteeing feasibility of implementation were information, education, and communication (IEC) at the community and family level; vector control; health staff training; screening and diagnosis; treatment and compliance, including family-based strategies for early detection of adverse events; and logistics. Chagas disease diagnosis was confirmed by testing blood samples using two different diagnostic tests. T. cruzi-positive patients were treated with benznidazole as first-line treatment, with appropriate counseling, consent, and active participation from parents or guardians for daily administration of the drug, early detection of adverse events, and treatment withdrawal, when necessary. Weekly follow-up was conducted, with adverse events recorded to assess drug safety. Evaluations of serological conversion were carried out to measure treatment effectiveness. Vector control, entomological surveillance, and health education activities were carried out in all projects with close interaction with national and regional programs. RESULTS: Total numbers of children and adolescents tested for T. cruzi in Yoro, Olopa, Entre Ríos, and Sucre were 24,471, 8,927, 7,613, and 19,400, respectively. Of these, 232 (0.9%), 124 (1.4%), 1,475 (19.4%), and 1,145 (5.9%) patients, respectively, were diagnosed as seropositive. Patients were treated with benznidazole, and early findings of seroconversion varied widely between the Central and South American programs: 87.1% and 58.1% at 18 months post-treatment in Yoro and Olopa, respectively; 5.4% by up to 60 months in Entre Ríos; and 0% at an average of 18 months in Sucre. Benznidazole-related adverse events were observed in 50.2% and 50.8% of all patients treated in Yoro and Olopa, respectively, and 25.6% and 37.9% of patients in Entre Ríos and Sucre, respectively. Most adverse events were mild and manageable. No deaths occurred in the treatment population. CONCLUSIONS: These results demonstrate the feasibility of implementing Chagas disease diagnosis and treatment programs in resource-limited settings, including remote rural areas, while addressing the limitations associated with drug-related adverse events. The variability in apparent treatment effectiveness may reflect differences in patient and parasite populations, and illustrates the limitations of current treatments and measures of efficacy. New treatments with improved safety profiles, pediatric formulations of existing and new drugs, and a faster, reliable test of cure are all urgently needed

A novel multivariate STeady-state index during general ANesthesia (STAN)

The assessment of the adequacy of general anesthesia for surgery, namely the nociception/anti-nociception balance, has received wide attention from the scientific community. Monitoring systems based on the frontal EEG/EMG, or autonomic state reactions (e.g. heart rate and blood pressure) have been developed aiming to objectively assess this balance. In this study a new multivariate indicator of patients' steady-state during anesthesia (STAN) is proposed, based on wavelet analysis of signals linked to noxious activation. A clinical protocol was designed to analyze precise noxious stimuli (laryngoscopy/intubation, tetanic, and incision), under three different analgesic doses; patients were randomized to receive either remifentanil 2.0, 3.0 or 4.0 ng/ml. ECG, PPG, BP, BIS, EMG and [Formula: see text] were continuously recorded. ECG, PPG and BP were processed to extract beat-to-beat information, and [Formula: see text] curve used to estimate the respiration rate. A combined steady-state index based on wavelet analysis of these variables, was applied and compared between the three study groups and stimuli (Wilcoxon signed ranks, Kruskal-Wallis and Mann-Whitney tests). Following institutional approval and signing the informed consent thirty four patients were enrolled in this study (3 excluded due to signal loss during data collection). The BIS index of the EEG, frontal EMG, heart rate, BP, and PPG wave amplitude changed in response to different noxious stimuli. Laryngoscopy/intubation was the stimulus with the more pronounced response [Formula: see text]. These variables were used in the construction of the combined index STAN; STAN responded adequately to noxious stimuli, with a more pronounced response to laryngoscopy/intubation (18.5-43.1 %, [Formula: see text]), and the attenuation provided by the analgesic, detecting steady-state periods in the different physiological signals analyzed (approximately 50 % of the total study time). A new multivariate approach for the assessment of the patient steady-state during general anesthesia was developed. The proposed wavelet based multivariate index responds adequately to different noxious stimuli, and attenuation provided by the analgesic in a dose-dependent manner for each stimulus analyzed in this study.The first author was supported by a scholarship from the Portuguese Foundation for Science and Technology (FCT SFRH/BD/35879/2007). The authors would also like to acknowledge the support of UISPA—System Integration and Process Automation Unit—Part of the LAETA (Associated Laboratory of Energy, Transports and Aeronautics) a I&D Unit of the Foundation for Science and Technology (FCT), Portugal. FCT support under project PEst-OE/EME/LA0022/2013.info:eu-repo/semantics/publishedVersio

New insights into the classification and nomenclature of cortical GABAergic interneurons.

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts' assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus

Clinical Manifestations and Case Management of Ebola Haemorrhagic Fever caused by a newly identified virus strain, Bundibugyo, Uganda, 2007-2008

A confirmed Ebola haemorrhagic fever (EHF) outbreak in Bundibugyo, Uganda, November 2007-February 2008, was caused by a putative new species (Bundibugyo ebolavirus). It included 93 putative cases, 56 laboratory-confirmed cases, and 37 deaths (CFR = 25%). Study objectives are to describe clinical manifestations and case management for 26 hospitalised laboratory-confirmed EHF patients. Clinical findings are congruous with previously reported EHF infections. The most frequently experienced symptoms were non-bloody diarrhoea (81%), severe headache (81%), and asthenia (77%). Seven patients reported or were observed with haemorrhagic symptoms, six of whom died. Ebola care remains difficult due to the resource-poor setting of outbreaks and the infection-control procedures required. However, quality data collection is essential to evaluate case definitions and therapeutic interventions, and needs improvement in future epidemics. Organizations usually involved in EHF case management have a particular responsibility in this respect

AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment

<p>Abstract</p> <p>Background</p> <p>Machine learning has a vast range of applications. In particular, advanced machine learning methods are routinely and increasingly used in quantitative structure activity relationship (QSAR) modeling. QSAR data sets often encompass tens of thousands of compounds and the size of proprietary, as well as public data sets, is rapidly growing. Hence, there is a demand for computationally efficient machine learning algorithms, easily available to researchers without extensive machine learning knowledge. In granting the scientific principles of transparency and reproducibility, Open Source solutions are increasingly acknowledged by regulatory authorities. Thus, an Open Source state-of-the-art high performance machine learning platform, interfacing multiple, customized machine learning algorithms for both graphical programming and scripting, to be used for large scale development of QSAR models of regulatory quality, is of great value to the QSAR community.</p> <p>Results</p> <p>This paper describes the implementation of the Open Source machine learning package AZOrange. AZOrange is specially developed to support batch generation of QSAR models in providing the full work flow of QSAR modeling, from descriptor calculation to automated model building, validation and selection. The automated work flow relies upon the customization of the machine learning algorithms and a generalized, automated model hyper-parameter selection process. Several high performance machine learning algorithms are interfaced for efficient data set specific selection of the statistical method, promoting model accuracy. Using the high performance machine learning algorithms of AZOrange does not require programming knowledge as flexible applications can be created, not only at a scripting level, but also in a graphical programming environment.</p> <p>Conclusions</p> <p>AZOrange is a step towards meeting the needs for an Open Source high performance machine learning platform, supporting the efficient development of highly accurate QSAR models fulfilling regulatory requirements.</p

A systematic review of the evidence for single stage and two stage revision of infected knee replacement

BACKGROUND: Periprosthetic infection about the knee is a devastating complication that may affect between 1% and 5% of knee replacement. With over 79 000 knee replacements being implanted each year in the UK, periprosthetic infection (PJI) is set to become an important burden of disease and cost to the healthcare economy. One of the important controversies in treatment of PJI is whether a single stage revision operation is superior to a two-stage procedure. This study sought to systematically evaluate the published evidence to determine which technique had lowest reinfection rates. METHODS: A systematic review of the literature was undertaken using the MEDLINE and EMBASE databases with the aim to identify existing studies that present the outcomes of each surgical technique. Reinfection rate was the primary outcome measure. Studies of specific subsets of patients such as resistant organisms were excluded. RESULTS: 63 studies were identified that met the inclusion criteria. The majority of which (58) were reports of two-stage revision. Reinfection rated varied between 0% and 41% in two-stage studies, and 0% and 11% in single stage studies. No clinical trials were identified and the majority of studies were observational studies. CONCLUSIONS: Evidence for both one-stage and two-stage revision is largely of low quality. The evidence basis for two-stage revision is significantly larger, and further work into direct comparison between the two techniques should be undertaken as a priority

Prevalence, Clinical Staging and Risk for Blood-Borne Transmission of Chagas Disease among Latin American Migrants in Geneva, Switzerland

Chagas disease, a parasitic disease caused by Trypanosoma cruzi, is a leading cause of cardiac and digestive tract disorders in Mexico, Central and South America. An increasing number of cases have recently been reported in North America and Europe due to international human migration, but data outside Latin America remains scarce. This study showed that Chagas disease is an emerging health problem in Switzerland, affecting a substantial proportion of Latin American migrants (13%). Persons at increased risk of infection were Bolivian, older than 35 years or had a mother infected with T. cruzi. Early signs of cardiac or digestive tract disease were found in one out of six infected patients. The risk of local transmission by blood transfusion or organ transplant was illustrated by the frequent willingness expressed by patients to donate blood or organs in Switzerland. The authors recommend the screening of persons at risk of infection and the diffusion of appropriate information to the medical community to increase awareness of this emerging health problem. Considering that affected persons frequently lack health insurance in Switzerland, a facilitated access to medical care is an important step towards better recognition and management of Chagas disease

Genetic variability in five populations of Partamona helleri (Hymenoptera, Apidae) from Minas Gerais State, Brazil

Partamona is a Neotropical genus of stingless bees that comprises 33 species distributed from Mexico to southern Brazil. These bees are well-adapted to anthropic environments and build their nests in several substrates. In this study, 66 colonies of Partamona helleri from five localities in the Brazilian state of Minas Gerais (São Miguel do Anta, Teixeiras, Porto Firme, Viçosa and Rio Vermelho) were analyzed using nine microsatellite loci in order to assess their genetic variability. Low levels of observed (Ho = 0.099-0.137) and expected (H e = 0.128-0.145) heterozygosity were encountered and revealed discrete genetic differentiation among the populations (F ST = 0.025). AMOVA further showed that most of the total genetic variation (94.24%) in P. helleri was explained by the variability within local populations

Phosphorus Is Associated with Coronary Artery Disease in Patients with Preserved Renal Function

High serum phosphorus levels have been associated with mortality and cardiovascular events in patients with chronic kidney disease and in the general population. In addition, high phosphorus levels have been shown to induce vascular calcification and endothelial dysfunction in vitro. The aim of this study was to evaluate the relation of phosphorus and coronary calcification and atherosclerosis in the setting of normal renal function. This was a cross-sectional study involving 290 patients with suspected coronary artery disease and undergoing elective coronary angiography, with a creatinine clearance >60 ml/min/1.73 m2. Coronary artery obstruction was assessed by the Friesinger score and coronary artery calcification by multislice computed tomography. Serum phosphorus was higher in patients with an Agatston score >10 than in those with an Agatston score ≤10 (3.63±0.55 versus 3.49±0.52 mg/dl; p = 0.02). In the patients with Friesinger scores >4, serum phosphorus was higher (3.6±0.5 versus 3.5±0.6 mg/dl, p = 0.04) and median intact fibroblast growth factor 23 was lower (40.3 pg/ml versus 45.7 pg/ml, p = 0.01). Each 0.1-mg/dl higher serum phosphate was associated with a 7.4% higher odds of having a Friesinger score >4 (p = 0.03) and a 6.1% greater risk of having an Agatston score >10 (p = 0.01). Fibroblast growth factor 23 was a negative predictor of Friesinger score (p = 0.002). In conclusion, phosphorus is positively associated with coronary artery calcification and obstruction in patients with suspected coronary artery disease and preserved renal function

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio