Predicting the onset and persistence of episodes of depression in primary health care. The predictD-Spain study: Methodology

Background: The effects of putative risk factors on the onset and/or persistence of depression remain unclear. We aim to develop comprehensive models to predict the onset and persistence of episodes of depression in primary care. Here we explain the general methodology of the predictD-Spain study and evaluate the reliability of the questionnaires used. Methods: This is a prospective cohort study. A systematic random sample of general practice attendees aged 18 to 75 has been recruited in seven Spanish provinces. Depression is being measured with the CIDI at baseline, and at 6, 12, 24 and 36 months. A set of individual, environmental, genetic, professional and organizational risk factors are to be assessed at each follow-up point. In a separate reliability study, a proportional random sample of 401 participants completed the test-retest (251 researcher-administered and 150 self-administered) between October 2005 and February 2006. We have also checked 118,398 items for data entry from a random sample of 480 patients stratified by province. Results: All items and questionnaires had good test-retest reliability for both methods of administration, except for the use of recreational drugs over the previous six months. Cronbach's alphas were good and their factorial analyses coherent for the three scales evaluated (social support from family and friends, dissatisfaction with paid work, and dissatisfaction with unpaid work). There were 191 (0.16%) data entry errors. Conclusion: The items and questionnaires were reliable and data quality control was excellent. When we eventually obtain our risk index for the onset and persistence of depression, we will be able to determine the individual risk of each patient evaluated in primary health car

Global and decomposition evolutionary support vector machine approaches for time series forecasting

Multi-step ahead Time Series Forecasting (TSF) is a key tool for support- ing tactical decisions (e.g., planning resources). Recently, the support vector machine emerged as a natural solution for TSF due to its nonlinear learning capabilities. This paper presents two novel Evolutionary Support Vector Machine (ESVM) methods for multi-step TSF. Both methods are based on an Estimation Distribution Algorithm (EDA) search engine that automatically performs a simultaneous variable (number of inputs) and model (hyperparameters) selection. The Global ESVM (GESVM) uses all past patterns to fit the support vector machine, while the Decomposition ESVM (DESVM) separates the series into trended and stationary effects, using a distinct ESVM to forecast each effect and then summing both predictions into a sin- gle response. Several experiments were held, using six time series. The proposed approaches were analyzed under two criteria and compared against a recent Evolu- tionary Artificial Neural Network (EANN) and two classical forecasting methods, Holt-Winters and ARIMA. Overall, the DESVM and GESVM obtained competitive and high quality results. Furthermore, both ESVM approaches consume much less computational effort when compared with EANN.The authors wish to thank Ramon Sagarna for introducing the subject of EDA. The work of P. Cortez was supported by FEDER (program COMPETE and FCT) under project FCOMP-01-0124-FEDER-022674

The Genomic Signature of Crop-Wild Introgression in Maize

The evolutionary significance of hybridization and subsequent introgression has long been appreciated, but evaluation of the genome-wide effects of these phenomena has only recently become possible. Crop-wild study systems represent ideal opportunities to examine evolution through hybridization. For example, maize and the conspecific wild teosinte Zea mays ssp. mexicana, (hereafter, mexicana) are known to hybridize in the fields of highland Mexico. Despite widespread evidence of gene flow, maize and mexicana maintain distinct morphologies and have done so in sympatry for thousands of years. Neither the genomic extent nor the evolutionary importance of introgression between these taxa is understood. In this study we assessed patterns of genome-wide introgression based on 39,029 single nucleotide polymorphisms genotyped in 189 individuals from nine sympatric maize-mexicana populations and reference allopatric populations. While portions of the maize and mexicana genomes were particularly resistant to introgression (notably near known cross-incompatibility and domestication loci), we detected widespread evidence for introgression in both directions of gene flow. Through further characterization of these regions and preliminary growth chamber experiments, we found evidence suggestive of the incorporation of adaptive mexicana alleles into maize during its expansion to the highlands of central Mexico. In contrast, very little evidence was found for adaptive introgression from maize to mexicana. The methods we have applied here can be replicated widely, and such analyses have the potential to greatly informing our understanding of evolution through introgressive hybridization. Crop species, due to their exceptional genomic resources and frequent histories of spread into sympatry with relatives, should be particularly influential in these studies

In-Depth Molecular Characterization of Mycobacterium tuberculosis from New Delhi – Predominance of Drug Resistant Isolates of the ‘Modern’ (TbD1−) Type

BACKGROUND: India has the highest estimated burden of tuberculosis in the world, accounting for 21% of all tuberculosis cases world-wide. However, due to lack of systematic analysis using multiple markers the available information on the genomic diversity of Mycobacterium tuberculosis in India is limited. METHODOLOGY/PRINCIPAL FINDINGS: Thus, 65 M. tuberculosis isolates from New Delhi, India were analyzed by spoligotyping, MIRU-VNTR, large deletion PCR typing and single nucleotide polymorphism analysis (SNP). The Central Asian (CAS) 1 _DELHI sub-lineage was the most prevalent sub-lineage comprising 46.2% (n = 30) of all isolates, with shared-type (ST) 26 being the most dominant genotype comprising 24.6% (n = 16) of all isolates. Other sub-lineages observed were: East-African Indian (EAI)-5 (9.2%, n = 6), EAI6_BGD1 (6.2%, n = 4), EAI3_IND, CAS and T1 with 6.2% each (n = 4 each), Beijing (4.6%, n = 3), CAS2 (3.1%, n = 2), and X1 and X2 with 1 isolate each. Genotyping results from five isolates (7.7%) did not match any existing spoligopatterns, and one isolate, ST124, belonged to an undefined lineage. Twenty-six percent of the isolates belonged to the TbD1+ PGG1 genogroup. SNP analysis of the pncA gene revealed a CAS-lineage specific silent mutation, S65S, which was observed for all CAS-lineage isolates (except two ST26 isolates) and in 1 orphan. Mutations in the pncA gene, conferring resistance to pyrazinamide, were observed in 15.4% of all isolates. Collectively, mutations in the rpoB gene, the katG gene and in both rpoB and katG genes, conferring resistance to rifampicin and isoniazid, respectively, were more frequent in CAS1_DELHI isolates compared to non-CAS_DELHI isolates (OR: 3.1, CI95% [1.11, 8.70], P = 0.045). The increased frequency of drug-resistance could not be linked to the patients' history of previous anti-tuberculosis treatment (OR: 1.156, CI95% [0.40, 3.36], P = 0.79). Fifty-six percent of all new tuberculosis patients had mutations in either the katG gene or the rpoB gene, or in both katG and rpoB genes. CONCLUSION: CAS1_DELHI isolates circulating in New Delhi, India have a high frequency of mutations in the rpoB and katG genes. A silent mutation (S65S) in the pncA gene can be used as a putative genetic marker for CAS-lineage isolates

New approaches to high-resolution mapping of marine vertical structures

Vertical walls in marine environments can harbour high biodiversity and provide natural protection from bottom-trawling activities. However, traditional mapping techniques are usually restricted to down-looking approaches which cannot adequately replicate their 3D structure. We combined sideways-looking multibeam echosounder (MBES) data from an AUV, forward-looking MBES data from ROVs and ROV-acquired videos to examine walls from Rockall Bank and Whittard Canyon, Northeast Atlantic. High-resolution 3D point clouds were extracted from each sonar dataset and structure from motion photogrammetry (SfM) was applied to recreate 3D representations of video transects along the walls. With these reconstructions, it was possible to interact with extensive sections of video footage and precisely position individuals. Terrain variables were derived on scales comparable to those experienced by megabenthic individuals. These were used to show differences in environmental conditions between observed and background locations as well as explain spatial patterns in ecological characteristics. In addition, since the SfM 3D reconstructions retained colours, they were employed to separate and quantify live coral colonies versus dead framework. The combination of these new technologies allows us, for the first time, to map the physical 3D structure of previously inaccessible habitats and demonstrates the complexity and importance of vertical structures

Evaluating susceptibility of karst dolines (sinkholes) for collapse in Sango, Tennessee, USA

Dolines or sinkholes are earth depressions that develop in soluble rocks complexes such as limestone, dolomite, gypsum, anhydrite, and halite; dolines appear in a variety of shapes from nearly circular to complex structures with highly curved perimeters. The occurrence of dolines in the studied karst area is not random; they are the results of geomorphic, hydrologic and chemical processes that have caused partial subsidence, even total collapse of the land surface, when voids and caves are present in the bedrock and the regolith arch overbridging these voids is unstable. In the study area, the majority of collapses occur in the regolith (bedrock cover) that bridges voids in the bedrock. Because these collapsing dolines can damage property and cause even the loss of lives, there is a need to develop methods for evaluating karst hazards; such methods can be used by planners and practitioners for urban and economic development, especially in regions with a growing population. The purpose of this project is threefold: 1) to develop a karst feature database, 2) to investigate critical indicators associated with doline collapse, and 3) to design a doline susceptibility model for potential doline collapse based on external morphometric data. The study revealed the presence of short range spatial dependence in the distribution of the dolines’ morphometric parameters such as circularity, geographic orientation of the main doline axes and the length-to-width doline ratios; therefore, geostatistics can be used to spatially evaluate the susceptibility of the karst area for doline collapse using the probability of occurrence of these critical parameters. The partial susceptibility estimates were combined into final spatial probabilities enabling the identification of areas where undetected dolines may cause significant hazards

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Evidence-Based African First Aid Guidelines and Training Materials

Stijn Van de Velde and colleagues describe the African First Aid Materials project, which developed evidence-based guidelines on administering first aid in the African context as well as training materials to support the implementation of the guidelines

Impact of long-term viral suppression in CD4+ recovery of HIV-children on Highly Active Antiretroviral Therapy

BACKGROUND: The effects of HAART may differ between children and adults because children have a developing immune system, and the long-term immunological outcome in HIV-infected children on HAART is not well-known. A major aim of our study was to determine CD4+ evolution associated with long-term VL control during 4 years of observation on HAART. METHODS: We carried out a retrospective study on a cohort of 160 vertically HIV-infected children. It was carried out from 1996 to 2004 in six large Spanish pediatric referral hospitals. We compared 33 children who had long-term VL suppression (VL ≤400 copies/ml) in the first 12 months of follow-up and maintained that level throughout follow-up (Responders-group), and 127 children with persistently detectable VL in spite of ART switches (Non-Responders-group). RESULTS: We observed a quick initial and significant increase in CD4(+ )counts from the baseline to 12 months on HAART in both groups (p < 0.01). The Non-Responders group sustained CD4+ increases and most of these children maintained high CD4(+ )level counts (≥25%). The Non-Responders group reached a plateau between 26% and 27% CD4(+ )at the first 12 months of follow-up that remained stable during the following 3 years. However, the Responders group reached a plateau between 30% and 32% CD4(+ )at 24, 36 and 48 months of follow-up. We found that the Responders group had higher CD4(+ )count values and higher percentages of children with CD4(+ )≥25% than the Non-Responders group (p < 0.05) after month 12. CONCLUSION: Long-term VL suppression in turn induces large beneficial effects in immunological responses. However, it is not indispensable to recover CD4(+ )levels

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration