A spatial case-control study on symptomatic and inapparent primary dengue infections in an endemic city in Brazil.

We conducted a spatial case-control study nested in a dengue incidence cohort to explore the role of the spatial and socioeconomic factors in the proportion of symptomatic (cases) and inapparent primary dengue virus infections (controls). Cohort participants were children and adolescents (2 to 16 years of age) at the beginning of the follow-up. Case definitions were, for symptomatic cases, fever plus a positive lab result for acute dengue (NS1, RT-PCR, ELISA IgM/IgG), and for inapparent infection a positive result for dengue IgG (ELISA) in subjects without symptoms and with a previously negative result at baseline. The covariates included sociodemographic factors, residential location, and socioeconomic context variables of the census tracts of residence of cases and controls. We used principal component analysis to reduce the contextual covariates, with the component values assigned to each one based on their residences. The data were modeled in a Bayesian context, considering the spatial dependence. The final sample consisted of 692 children, 274 cases and 418 controls, from the first year of follow-up (2014-2015). Being male, older age, higher educational level of the head of the family and having a larger number of rooms in the household were associated with a greater chance of presenting dengue symptomatic infection at the individual level. The contextual covariates were not associated with the outcome. Inapparent dengue infection has extensive epidemiological consequences. Relying solely on notifications of symptomatic dengue infections underestimates the number of cases, preserves a silent source of the disease, potentially spreading the virus to unaffected areas.

A spatial case-control study on symptomatic and inapparent primary dengue infections in an endemic city in Brazil

ABSTRACT We conducted a spatial case-control study nested in a dengue incidence cohort to explore the role of the spatial and socioeconomic factors in the proportion of symptomatic (cases) and inapparent primary dengue virus infections (controls). Cohort participants were children and adolescents (2 to 16 years of age) at the beginning of the follow-up. Case definitions were, for symptomatic cases, fever plus a positive lab result for acute dengue (NS1, RT-PCR, ELISA IgM/IgG), and for inapparent infection a positive result for dengue IgG (ELISA) in subjects without symptoms and with a previously negative result at baseline. The covariates included sociodemographic factors, residential location, and socioeconomic context variables of the census tracts of residence of cases and controls. We used principal component analysis to reduce the contextual covariates, with the component values assigned to each one based on their residences. The data were modeled in a Bayesian context, considering the spatial dependence. The final sample consisted of 692 children, 274 cases and 418 controls, from the first year of follow-up (2014-2015). Being male, older age, higher educational level of the head of the family and having a larger number of rooms in the household were associated with a greater chance of presenting dengue symptomatic infection at the individual level. The contextual covariates were not associated with the outcome. Inapparent dengue infection has extensive epidemiological consequences. Relying solely on notifications of symptomatic dengue infections underestimates the number of cases, preserves a silent source of the disease, potentially spreading the virus to unaffected areas.

Chick heterophils release DNA extracellular traps (DETs) in vitro and in vivo upon Aspergillus fumigatus conidia exposure.

Aspergillosis is a common fungal disease in avian species, causing high mortality in young chicks in agricultural farms and yards. It is caused by fungi belonging to the genus Aspergillus. Aspergillosis occurs by inhalation of fungal conidia, and in chickens, effective infection control relies on a rapid and large influx of heterophils to the lungs. Heterophils, upon different stimuli, release to the extracellular milieu their chromatin associated with several proteins that ensnare and kill different pathogens similarly to neutrophil extracellular traps. Here, we showed that Aspergillus fumigatus conidia and the peptidogalactomannan (PGM), isolated from the fungus cell wall, induce the release of DNA extracellular traps (DETs) in chicks' blood and lung heterophils. We demonstrated that reactive oxygen species, elastase and peptidyl arginine deiminase (PAD) were involved in DETs extrusion, the occurrence of DETs in the lungs of A. fumigatus-exposed chicks in vivo, and its role in chick survival. These results may contribute to developing more efficient tools for the therapeutic and diagnosis of aspergillosis.

Systematic profiling of subtelomeric silencing factors in budding yeast.

Subtelomeric gene silencing is the negative transcriptional regulation of genes located close to telomeres. This phenomenon occurs in a variety of eukaryotes with salient physiological implications, such as cell adherence, virulence, immune-system escape, and ageing. The process has been widely studied in the budding yeast Saccharomyces cerevisiae, where genes involved in this process have been identified mostly on a gene-by-gene basis. Here, we introduce a quantitative approach to study gene silencing, that couples the classical URA3 reporter with GFP monitoring, amenable to high-throughput flow cytometry analysis. This dual silencing reporter was integrated into several subtelomeric loci in the genome, where it showed a gradual range of silencing effects. By crossing strains with this dual reporter at the COS12 and YFR057W subtelomeric query loci with gene-deletion mutants, we carried out a large-scale forward screen for potential silencing factors. The approach was replicable and allowed accurate detection of expression changes. Results of our comprehensive screen suggest that the main players influencing subtelomeric silencing were previously known, but additional potential factors underlying chromatin conformation are involved. We validate and report the novel silencing factor LGE1, a protein with unknown molecular function required for histone H2B ubiquitination. Our strategy can be readily combined with other reporters and gene perturbation collections, making it a versatile tool to study gene silencing at a genome-wide scale.

Seroprevalence of SARS-CoV-2 in Brazil: A systematic review and meta-analysis.

OBJECTIVES: To summarize the data on SARS-CoV-2 seroprevalence surveys conducted in Brazil before the introduction of vaccines METHODS: The authors conducted a systematic review and meta-analysis on the seroprevalence of SARS-CoV-2 infection in Brazil. The present review followed the PRISMA guidelines. The authors searched Medline, Embase, and LILACS databases for serologic surveys conducted in the Brazilian population, in the period from 01/10/2019 to 07/11/2021, without language restrictions. The authors included studies that presented data concerning SARS-CoV-2 antibodies seroprevalence in Brazil and had a sample size ≥50 individuals. Considering the expected heterogeneity between studies, all analyses were performed using the random effects model, and heterogeneity was assessed using the I2 statistic RESULTS: Of 586 publications identified in the initial searches, 54 were included in the review and meta-analysis, which contained the results of 135 surveys, with 336,620 participants. The estimated seroprevalence was 11.0%, ranging from 1.0% to 83.0%, with a substantial heterogeneity (I2 = 99.55%). In subgroup analyses, the authors observed that the prevalence of SARS-CoV-2 antibodies was 13.0% in blood donors, 9.0% in the population-based surveys, 13% in schoolchildren, and 11.0% in healthcare workers. CONCLUSIONS: Seroprevalence increases over time. Large differences were observed among the regions of the country. It was higher in the Northern region, decreasing towards the South. The present results may contribute to the analysis of the spread of SARS-CoV-2 infection in the Brazilian population before vaccination, one of the factors that may be influencing the clinical presentation of COVID-19 cases related to the new variants, as well as the effectiveness of the vaccination program.

Development of the dairy products incorporated with co-product bioactive compounds-rich as an alternative ingredient in the food industry.

The objective was to optimize the phenolic compounds extraction from cocoa shells using the simplex-centroid design with a mixture of solvents (water, methanol, and acetone) as its components, to prove the presence of these compounds and antioxidant activity. Also, the development of dairy products, such as milk beverages and dairy desserts, with bioactive compounds, through the replacement of cocoa powder by cocoa shell was studied and evaluated sensorially. The extraction optimization indicated that a solvent with 56.44% water, 23.77% methanol, and 19.80% acetone are ideal for maximizing the phenolic compounds. In addition, the cocoa shell showed a high antioxidant activity by the methods ß-carotene/linoleic acid, FRAP, and phosphomolybdenum complex. The Check-All-That-Apply, Cochran's Q test, contingency analysis, and hierarchical cluster analysis allowed description characteristics of the dairy products and showed sensory differences between formulations with 100% cocoa shell and others. Both dairy products had good sensory acceptance in all attributes evaluated (appearance, flavor, texture, and overall impression), and their scores did not differ statistically by Tukey's test (p > 0.05). Thus, the cocoa shell is shown as an alternative substitute ingredient to be used in the dairy industry.

Determination of the lactose content in low-lactose milk using Fourier-transform infrared spectroscopy (FTIR) and convolutional neural network.

Demand for low lactose milk and milk products has been increasing worldwide due to the high number of people with lactose intolerance. These low lactose dairy foods require fast, low-cost and efficient methods for sugar quantification. However, available methods do not meet all these requirements. In this work, we propose the association of FTIR (Fourier Transform Infrared) spectroscopy with artificial intelligence to identify and quantify residual lactose and other sugars in milk. Convolutional neural networks (CNN) were built from the infrared spectra without preprocessing the data using hyperparameter adjustment and saliency map. For the quantitative prediction of the sugars in milk, a regression model was proposed, while for the qualitative assessment, a classification model was used. Raw, pasteurized and ultra-high temperature (UHT) milk was added with lactose, glucose, and galactose in six concentrations (0.1-7.0 mg mL-1) and, in total, 432 samples were submitted to convolutional neural network. Accuracy, precision, sensitivity, specificity, root mean square error, mean square error, mean absolute error, and coefficient of determination (R2) were used as evaluation parameters. The algorithms indicated a predictive capacity (accuracy) above 95% for classification, and R2 of 81%, 86%, and 92% for respectively, lactose, glucose, and galactose quantification. Our results showed that the association of FTIR spectra with artificial intelligence tools, such as CNN, is an efficient, quick, and low-cost methodology for quantifying lactose and other sugars in milk.

The protein-protein interaction landscape of transcription factors during gynoecium development in Arabidopsis.

Flowers are composed of organs whose identity is defined by the combinatorial activity of transcription factors (TFs). The interactions between MADS-box TFs and protein complex formation have been schematized in the floral quartet model of flower development. The gynoecium is the flower's female reproductive part, crucial for fruit and seed production and, hence, for reproductive success. After the establishment of carpel identity, many tissues arise to form a mature gynoecium. TFs have been described as regulators of gynoecium development, and some interactions and complexes have been identified. However, broad knowledge about the interactions among these TFs and their participation during development remains scarce. In this study, we used a systems biology approach to understand the formation of a complex reproductive unit-as the gynoecium-by mapping binary interactions between well-characterized TFs. We analyzed almost 4500 combinations and detected more than 250 protein-protein interactions (PPIs), resulting in a process-specific interaction map. Topological analyses suggest hidden functions and novel roles for many TFs. In addition, we observed a close relationship between TFs involved in auxin and cytokinin-signaling pathways and other TFs. Furthermore, we analyzed the network by combining PPI data, expression, and genetic data, which helped us to dissect it into several dynamic spatio-temporal subnetworks related to gynoecium development processes. Finally, we generated an extended PPI network that predicts new players in gynoecium development. Taken together, all these results serve as a valuable resource for the plant community.

Time-course biofilm formation and presence of antibiotic resistance genes on everyday plastic items deployed in river waters.

The plastisphere has been widely studied in the oceans; however, there is little information on how living organisms interact with the plastisphere in freshwater ecosystems, and particularly on how this interaction changes over time. We have characterized, over one year, the evolution of the eukaryotic and bacterial communities colonizing four everyday plastic items deployed in two sites of the same river with different anthropogenic impact. α-diversity analyses showed that site had a significant role in bacterial and eukaryotic diversity, with the most impacted site having higher values of the Shannon diversity index. ß-diversity analyses showed that site explained most of the sample variation followed by substrate type (i.e., plastic item) and time since first colonization. In this regard, core microbiomes/biomes in each plastic at 1, 3, 6 and 12 months could be identified at genus level, giving a global overview of the evolution of the plastisphere over time. The measured concentration of antibiotics in the river water positively correlated with the abundance of antibiotic resistance genes (ARGs) on the plastics. These results provide relevant information on the temporal dynamics of the plastisphere in freshwater ecosystems and emphasize the potential contribution of plastic items to the global spread of antibiotic resistance.

Seroprevalence of SARS-CoV-2 in Brazil: A systematic review and meta-analysis

Abstract Objectives To summarize the data on SARS-CoV-2 seroprevalence surveys conducted in Brazil before the introduction of vaccines Methods The authors conducted a systematic review and meta-analysis on the seroprevalence of SARS-CoV-2 infection in Brazil. The present review followed the PRISMA guidelines. The authors searched Medline, Embase, and LILACS databases for serologic surveys conducted in the Brazilian population, in the period from 01/10/2019 to 07/11/2021, without language restrictions. The authors included studies that presented data concerning SARS-CoV-2 antibodies seroprevalence in Brazil and had a sample size ≥50 individuals. Considering the expected heterogeneity between studies, all analyses were performed using the random effects model, and heterogeneity was assessed using the I2 statistic Results Of 586 publications identified in the initial searches, 54 were included in the review and meta-analysis, which contained the results of 135 surveys, with 336,620 participants. The estimated seroprevalence was 11.0%, ranging from 1.0% to 83.0%, with a substantial heterogeneity (I2= 99.55%). In subgroup analyses, the authors observed that the prevalence of SARS-CoV-2 antibodies was 13.0% in blood donors, 9.0% in the population-based surveys, 13% in schoolchildren, and 11.0% in healthcare workers. Conclusions Seroprevalence increases over time. Large differences were observed among the regions of the country. It was higher in the Northern region, decreasing towards the South. The present results may contribute to the analysis of the spread of SARS-CoV-2 infection in the Brazilian population before vaccination, one of the factors that may be influencing the clinical presentation of COVID-19 cases related to the new variants, as well as the effectiveness of the vaccination program.

A machine learning proposal method to detect milk tainted with cheese whey.

Cheese whey addition to milk is a type of fraud with high prevalence and severe economic effects, resulting in low yield for dairy products, nutritional reduction of milk and milk-derived products, and even some safety concerns. Nevertheless, methods to detect fraudulent addition of cheese whey to milk are expensive and time consuming, and are thus ineffective as screening methods. The Fourier-transform infrared (FTIR) spectroscopy technique is a promising alternative to identify this type of fraud because a large number of data are generated, and useful information might be extracted to be used by machine learning models. The objective of this work was to evaluate the use of FTIR with machine learning methods, such as classification tree and multilayer perceptron neural networks to detect the addition of cheese whey to milk. A total of 520 samples of raw milk were added with cheese whey in concentrations of 1, 2, 5, 10, 15, 20, 25, and 30%; and 65 samples were used as control. The samples were stored at 7, 20, and 30°C for 0, 24, 48, 72, and 168 h, and analyzed using FTIR equipment. Complementary results of 520 samples of authentic raw milk were used. Selected components (fat, protein, casein, lactose, total solids, and solids nonfat) and freezing point (°C) were predicted using FTIR and then used as input features for the machine learning algorithms. Performance metrics included accuracy as high as 96.2% for CART (classification and regression trees) and 97.8% for multilayer perceptron neural networks, with precision, sensitivity, and specificity above 95% for both methods. The use of milk composition and freezing point predicted using FTIR, associated with machine learning techniques, was highly efficient to differentiate authentic milk from samples added with cheese whey. The results indicate that this is a potential method to be used as a high-performance screening process to detected milk adulterated with cheese whey in milk quality laboratories.

A System for Structuring, Storage and Georeferenciation of Dengue Vector Surveillance Data.

Dengue is a main public health issue around the world and is an epidemic in Brazil. As part of the Brazilian national program to fight the disease, every municipality has a Zoonosis Control Center responsible for health and case surveillance, among other actions. The fieldwork includes routine visiting of houses and strategic sites (e.g. industries and vacant lands), water sampling, container elimination, and larvicide administration. However, the field data are gathered and summarized by hand. In this work, our goal is to ease the collection and visualization of field data to support decision-making. We have developed a mobile system to collect and georeference field data which could then be used to build geospatial and geo-temporal visualizations of indices such as House, Container, and Breteau1 indices. This solution could enhance entomological surveillance and leverage action planning and evaluation.

Evolution of prokaryotic colonisation of greenhouse plastics discarded into the environment.

Current knowledge on the capacity of plastics as vectors of microorganisms and their ability to transfer microorganisms between different habitats (i.e. air, soil and river) is limited. The objective of this study was to characterise the evolution of the bacterial community adhered to environmental plastics [low-density polyethylene (LDPE)] across different environments from their point of use to their receiving environment destination in the sea. The study took place in a typical Mediterranean intermittent river basin in Larnaka, Cyprus, characterised by a large greenhouse area whose plastic debris may end up in the sea due to mismanagement. Five locations were selected to represent the environmental fate of greenhouse plastics from their use, through their abandonment in soil and subsequent transport to the river and the sea, taking samples of plastics and the surrounding environments (soil and water). The bacterial community associated with each sample was studied by 16S rRNA metabarcoding; also, the main physicochemical parameters in each environmental compartment were analysed to understand these changes. The identification and chemical changes in greenhouse plastics were tracked using Attenuated Total Reflection Fourier Transform Infra-red spectroscopy (ATR-FTIR). Scanning Electron Microscope (SEM) analysis demonstrated an evolution of the biofilm at each sampling location. ß-diversity studies showed that the bacterial community adhered to plastics was significantly different from that of the surrounding environment only in samples taken from aqueous environments (freshwater and sea) (p-value p-value > 0.05). The environmental parameters (pH, salinity, total nitrogen and total phosphorus) explained the differences observed at each location to a limited extent. Furthermore, bacterial community differences among samples were lower in plastics collected from the soil than in plastics taken from rivers and seawater. Six genera (Flavobacterium, Altererythrobacter, Acinetobacter, Pleurocapsa, Georgfuchsia and Rhodococcus) were detected in the plastic, irrespective of the sampling location, confirming that greenhouse plastics can act as possible vectors of microorganisms between different environments: from their point of use, through a river system to the final coastal receiving environment. In conclusion, this study confirms the ability of greenhouse plastics to transport bacteria, including pathogens, between different environments. Future studies should evaluate these risks by performing complete sequencing metagenomics to decipher the functions of the plastisphere.

Development of Nutraceutical Ice Creams Using Flour Yellow Worm Larvae (Tenebrio molitor), Chia (Salvia hispanica), and Quinoa (Chenopodium quinoa).

Functional ice creams were developed by adding larvae of the insect Tenebrio molitor mixed with a seed (Salvia hispanica) and a pseudocereal (Chenopodium quinoa) to strawberry-cranberry ice cream. The objective was to increase micronutrients, macronutrients, and antioxidants, thus rendering the product a food complement. Four ice cream formulations were manufactured: the control strawberry-cranberry ice cream and three experimental mixtures, one of them with an addition of Tenebrio larvae (HT) and two others with a combination of Tenebrio larvae, chia (HTC), and quinoa (HTQ). The ice creams were submitted to proximate chemical analysis: mineral, fatty acid, vitamin, and one antioxidant (cyanidin 3 glucoside) determination. The strawberry-cranberry ice cream was used as a control formulation to evaluate if there were significant differences among nutrients, to which a Dunnett test with a critical value of α = 0.05% was applied. The three formulations that were studied showed a significant increase in the analyzed micronutrients and macronutrients compared to the control formulation. We observed increases of up to 62% in lipid content in the HTC formulation, while an increase of 41% in the protein content of the HT formulation was observed. We quantified an increase and enrichment of vitamins and minerals in the manufactured products, so that their nutritional value was significantly enhanced. In the determination of cyanidin 3 glucoside, we found that the formulation to which chia had been added showed an increase of 74% as compared to the control ice cream; this is important because anthocyanins are a group of flavonoids that stand out for their antioxidant and antimutagenic capabilities.

In Silico Laboratory Experiments Using Statistical Model Checking: A New Model of the Palytoxin-Induced Pump Channel as Case Study.

Studying biological systems is a difficult but important task. Traditional methods include laboratory experimentation and computer simulations. However, often researchers need to explore important but potentially rare events that are not easily observed or simulated. We use UPPAAL-SMC, a formal verification tool to support a methodology that allows us to model biological systems, specify events and conditions that we want to analyze, and to explore system executions using controlled simulations. We also describe an efficient way to reproduce laboratory experiments in silico. Unlike traditional simulations, we are able to guide the experiment to explore special events and conditions by expressing these conditions in temporal logic formulas. We have applied this methodology to create a more detailed model of Palytoxin-induced Na +/K + pump channels than was previously possible. Moreover, we have reproduced experimental protocols and their associated electrophysiological recordings, which has not been done in previous works. As a consequence, we have been able to propose a new diprotomeric model for the PTX-pump complex and study its behaviour. The use of our methodology has enabled us to reduce the effort and time to perform this research. It can be used to model and analyze other complex biological systems, potentially increasing the productivity of such studies.

Early and differential bacterial colonization on microplastics deployed into the effluents of wastewater treatment plants.

Microbial colonization of microplastics (MPs) in aquatic ecosystems is a well-known phenomenon; however, there is insufficient knowledge of the early colonization phase. Wastewater treatment plant (WWTP) effluents have been proposed as important pathways for MPs entry and transport in aquatic environments and are hotspots of bacterial pathogens and antibiotic resistance genes (ARGs). This study aimed at characterizing bacterial communities in the early stage of biofilm formation on seven different types of MPs deployed in two different WWTPs effluents as well as measuring the relative abundance of two ARGs (sulI and tetM) on the tested MPs. Illumina Miseq sequencing of the 16S rRNA showed significant higher diversity of bacteria on MPs in comparison with free-living bacteria in the WWTP effluents. ß-diversity analysis showed that the in situ environment (sampling site) and hydrophobicity, to a lesser extent, had a role in the early bacterial colonization phase. An early colonization phase MPs-core microbiome could be identified. Furthermore, specific core microbiomes for each type of polymer suggested that each type might select early attachment of bacteria. Although the tested WWTP effluent waters contained antibiotic resistant bacteria (ARBs) harboring the sulI and tetM ARGs, MPs concentrated ARBs harboring the sulI gene but not tetM. These results highlight the relevance of the early attachment phase in the development of bacterial biofilms on different types of MP polymers and the role that different types of polymers might have facilitating the attachment of specific bacteria, some of which might carry ARGs.

Vaccine development against neglected tropical diseases. / O desenvolvimento de vacinas contra as doenças tropicais negligenciadas.

Neglected tropical diseases constitute a heterogeneous group of diseases that have as a common characteristic to affect poor and unassisted populations with little vocalization capacity and political power. As a result, they receive little attention from the pharmaceutical industry and academia. The present study aimed to summarize the state of the art regarding vaccine development for three relevant neglected tropical diseases in Brazil: Chagas disease, schistosomiasis (Schistosoma mansoni), and leishmaniasis. To this end, we conducted a narrative review of the scientific literature, including publications that allowed us to outline a current overview on the vaccine development for the three diseases. Vaccines against the three diseases are in different stages of development. Vaccine development projects against American trypanosomiasis have yet to reach the clinical evaluation phase. For schistosomiasis, we have candidates for the vaccine in the advanced phase of clinical evaluation. For leishmaniasis, there are already licensed veterinary vaccines, and product candidates for human vaccine in the intermediate stage of clinical evaluation. The reduced funding for these projects has contributed to slow product development.

As doenças tropicais negligenciadas constituem um grupo heterogêneo de enfermidades que apresentam como característica comum afetarem populações pobres e desassistidas, com pouca capacidade de vocalização e de poder político. Em consequência, recebem pouca atenção da indústria farmacêutica e da academia. O presente estudo teve como propósito resumir o estado da arte quanto ao desenvolvimento de vacinas para três doenças tropicais negligenciadas de relevância no Brasil, a doença de Chagas, a esquistossomose mansoni e as leishmanioses. Para tanto, realizou-se uma revisão narrativa da literatura científica, na qual foram incluídas publicações que permitiram traçar um panorama atual do desenvolvimento de vacinas para as três doenças. Essas vacinas estão em estágios distintos de desenvolvimento. Os projetos de desenvolvimento de vacinas contra a tripanossomíase americana ainda não chegaram à fase clínica de avaliação. Já para a esquistossomose há candidatos à vacina em fase avançada de avaliação clínica. Para as leishmanioses já existem vacinas veterinárias licenciadas e produtos candidatos à vacina humana em etapa intermediária de avaliação clínica. O reduzido financiamento para esses projetos tem contribuído para retardar o desenvolvimento dos produtos.

Las enfermedades tropicales desatendidas constituyen un grupo heterogéneo de enfermedades, que presentan como característica común el hecho de que afectan a poblaciones pobres y desasistidas, con poca capacidad de interlocución y poder político. En consecuencia, reciben poca atención de la industria farmacéutica, así como de la academia. Este estudio tuvo como propósito resumir el estado de la cuestión, respecto al desarrollo de vacunas para tres enfermedades tropicales desatendidas relevantes en Brasil como son: la enfermedad de Chagas, la esquistosomiasis y leishmaniosis. Para ello, se realizó una revisión narrativa de la literatura científica, en la que se incluyeron publicaciones que permitieron trazar un panorama actual del desarrollo de vacunas para las tres enfermedades. Estas vacunas están en estadios distintos de desarrollo. Los proyectos de desarrollo de vacunas contra la tripanosomiasis americana todavía no llegaron a la fase clínica de evaluación. Ya en el caso de la esquistosomiasis hay candidatos a la vacuna en fase avanzada de evaluación clínica. Para las leishmaniosis ya existen vacunas veterinarias licenciadas y productos candidatos a la vacuna humana en etapa intermedia de evaluación clínica. La reducida financiación para esos proyectos ha contribuido al retraso en el desarrollo de los productos.

Different neighborhood walkability indexes for active commuting to school are necessary for urban and rural children and adolescents.

BACKGROUND: Literature focusing on youth has reported limited evidence and non-conclusive associations between neighborhood walkability measures and active commuting to and from school (ACS). Moreover, there is a lack of studies evaluating both macro- and micro-scale environmental factors of the neighborhood when ACS is analyzed. Likewise, most studies on built environment attributes and ACS focus on urban areas, whereas there is a lack of studies analyzing rural residential locations. Moreover, the relationship between built environment attributes and ACS may differ in children and adolescents. Hence, this study aimed to develop walkability indexes in relation to ACS for urban and rural children and adolescents, including both macro- and micro-scale school-neighborhood factors. METHODS: A cross-sectional study of 4593 participants from Spain with a mean age of 12.2 (SD 3.6) years was carried out. Macro-scale environmental factors were evaluated using geographic information system data, and micro-scale factors were measured using observational procedures. Socio-demographic characteristics and ACS were assessed with a questionnaire. Several linear regression models were conducted, including all the possible combinations of six or less built environment factors in order to find the best walkability index. RESULTS: Analyses showed that intersection density, number of four-way intersections, and residential density were positively related to ACS in urban participants, but negatively in rural participants. In rural children, positive streetscape characteristics, number of regulated crossings, traffic calming features, traffic lanes, and parking street buffers were also negatively related to ACS. In urban participants, other different factors were positively related to ACS: number of regulated crossings, positive streetscape characteristics, or crossing quality. Land use mix acted as a positive predictor only in urban adolescents. Distance to the school was a negative predictor on all the walkability indexes. However, aesthetic and social characteristics were not included in any of the indexes. CONCLUSIONS: Interventions focusing on improving built environments to increase ACS behavior need to have a better understanding of the walkability components that are specifically relevant to urban or rural samples.

An Optimized Competitive-Aging Method Reveals Gene-Drug Interactions Underlying the Chronological Lifespan of Saccharomyces cerevisiae.

The chronological lifespan of budding yeast is a model of aging and age-related diseases. This paradigm has recently allowed genome-wide screening of genetic factors underlying post-mitotic viability in a simple unicellular system, which underscores its potential to provide a comprehensive view of the aging process. However, results from different large-scale studies show little overlap and typically lack quantitative resolution to derive interactions among different aging factors. We previously introduced a sensitive, parallelizable approach to measure the chronological-lifespan effects of gene deletions based on the competitive aging of fluorescence-labeled strains. Here, we present a thorough description of the method, including an improved multiple-regression model to estimate the association between death rates and fluorescent signals, which accounts for possible differences in growth rate and experimental batch effects. We illustrate the experimental procedure-from data acquisition to calculation of relative survivorship-for ten deletion strains with known lifespan phenotypes, which is achieved with high technical replicability. We apply our method to screen for gene-drug interactions in an array of yeast deletion strains, which reveals a functional link between protein glycosylation and lifespan extension by metformin. Competitive-aging screening coupled to multiple-regression modeling provides a powerful, straight-forward way to identify aging factors in yeast and their interactions with pharmacological interventions.

Data on dengue incidence in South-eastern Brazil, 2014-2018.

Data from the routine surveillance systems have been extensively used to estimate the incidence of dengue. However, routine surveillance data frequently underestimate the diseases' incidence. Underreporting of dengue cases is related to the varying spectrum of its clinical presentation, with a large proportion of mild and asymptomatic infections, to its unspecific signs and symptoms, to the limitations of access to health care, and to the performance of the surveillance system itself [1-3]. In order to obtain accurate figures on dengue incidence, a cohort of children and adolescents was set up and followed during four years. The incidence of reported cases was used as a reference for the sample size calculation, which was stratified by age groups. A two-stage procedure was used to select the participants: census tracts were randomly selected, and within each one, a pre-determined number of children of each age group was randomly selected. The parents or legal guardians of the participating children and adolescents provided a written informed consent. In the first home visit, they responded to a questionnaire containing data on socio-demographic characteristics, housing, access to water, sewage, and garbage collection. Also, during the first visit a blood sample of the participating child/adolescent was collected for dengue baseline serology. Beginning in the week after the enrolment, the parent or legal guardian that was designated in the first visit received weekly phone calls for fever surveillance. If the child/adolescent had fever during the week, a nurse was dispatched to the family's home to collect more detailed data on the fever episode and collect a blood sample for dengue diagnosis (IgG, IgM, NS1 and PCR). If the dengue diagnosis was confirmed, a medical appointment was scheduled, and another blood sample for confirmatory tests was collected. It was also agreed that in every anniversary of their participation, they would receive another visit for a blood collection for dengue serology, regardless if they had a fever episode or a confirmed dengue diagnosis during the previous year. This article contains the description of the cohort's dataset. It is associated with the article published in Acta Tropica, under the title "A cohort study to assess the incidence of dengue, Brazil, 2014-2018" [4]. The associated article focused on the seroprevalence and incidence of dengue, and explored some associations between both outcomes and some explanatory variables.