Dataset Information

Applying fuzzy logic to assess the biogeographical risk of dengue in South America.

ABSTRACT: BACKGROUND:Over the last decade, reports about dengue cases have increase worldwide, which is particularly worrisome in South America due to the historic record of dengue outbreaks from the seventeenth century until the first half of the twentieth century. Dengue is a viral disease that involves insect vectors, namely Aedes aegypti and Ae. albopictus, which implies that, to prevent and combat outbreaks, it is necessary to understand the set of ecological and biogeographical factors affecting both the vector species and the virus. METHODS:We contribute with a methodology based on fuzzy logic that is helpful to disentangle the main factors that determine favorable environmental conditions for vectors and diseases. Using favorability functions as fuzzy logic modelling technique and the fuzzy intersection, union and inclusion as fuzzy operators, we were able to specify the territories at biogeographical risk of dengue outbreaks in South America. RESULTS:Our results indicate that the distribution of Ae. aegypti mostly encompasses the biogeographical framework of dengue in South America, which suggests that this species is the principal vector responsible for the geographical extent of dengue cases in the continent. Nevertheless, the intersection between the favorability for dengue cases and the union of the favorability for any of the vector species provided a comprehensive map of the biogeographical risk for dengue. CONCLUSIONS:Fuzzy logic is an appropriate conceptual and operational tool to tackle the nuances of the vector-illness biogeographical interaction. The application of fuzzy logic may be useful in decision-making by the public health authorities to prevent, control and mitigate vector-borne diseases.

SUBMITTER: Romero D

PROVIDER: S-EPMC6727500 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Applying fuzzy logic to assess the biogeographical risk of dengue in South America.

Romero David D Olivero Jesús J Real Raimundo R Guerrero José Carlos JC

Parasites & vectors 20190905 1

<h4>Background</h4>Over the last decade, reports about dengue cases have increase worldwide, which is particularly worrisome in South America due to the historic record of dengue outbreaks from the seventeenth century until the first half of the twentieth century. Dengue is a viral disease that involves insect vectors, namely Aedes aegypti and Ae. albopictus, which implies that, to prevent and combat outbreaks, it is necessary to understand the set of ecological and biogeographical factors affec ...[more]

PMID: 31488198

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Project description:We examine, for the first time, biogeographic patterns in a series of tropical montane coastal systems in northern South America. We use amphibians and reptiles, which constitute the most critical communities based upon the prevalence of endemic taxa, to assess the region's biodiversity. The montane coastal system spans an east-west distance of 925 km. It includes peaks ranging from 549 m to 2765 m above sea level and encompasses the montane complexes of northern Venezuela (including Isla de Margarita), an outlier at Santa Marta (Colombia), and ranges on the islands Trinidad and Tobago. The area supports 14 family level amphibian clades and 23 family level reptile clades. Fieldwork, museum specimen surveys, and a literature review suggest that biodiversity decreases at higher elevations. Here we examine the biogeographic patterns in the region to assess the role of the montane systems as possible refugia. We also look at the possible island and sky island effects using data from altitudes >200 m. At lower elevations, we tabulated 294 species, comprising 112 amphibians and 182 reptiles. About 45% of these taxa are endemic or exclusive to different sub-regions. At mid-elevation montane cloud forests, we find a much-reduced biodiversity with a total of 125 species (66 amphibians and 59 reptiles) exclusive or restricted to the region, and few species shared between systems. We find that biogeographical patterns follow a natural topographic disposition above 200 m in elevations. At the lower elevation cut off, there are 118 species (26 amphibians and 92 reptiles) shared among two or more of the studied mountain systems, suggesting a common origin and dispersal events, despite what seem to be topographic barriers. Biogeographical relationships support a topographic disposition of the region with close associations between the islands of Trinidad and Tobago, the Paria Range and the Turimiquire Massif, and close associations between the Sierra Nevada de Santa Marta and the Sierra de San Luis. Overall, the biogeographic relationships between amphibians and reptiles are similar. Species diversity in the eastern Caribbean region is less rich than in the west. This study includes the first herpetological surveys at the two easternmost mountains (Cerro La Cerbatana and Campeare) belonging to the Paria Range biogeographic unit, and aims to contribute to a better understanding of the rich biodiversity of the region.

Project description:BackgroundTo date, only a limited number of transcriptional regulatory interactions have been uncovered. In a pilot study integrating sequence data with microarray data, a position weight matrix (PWM) performed poorly in inferring transcriptional interactions (TIs), which represent physical interactions between transcription factors (TF) and upstream sequences of target genes. Inferring a TI means that the promoter sequence of a target is inferred to match the consensus sequence motifs of a potential TF, and their interaction type such as AT or RT is also predicted. Thus, a robust PWM (rPWM) was developed to search for consensus sequence motifs. In addition to rPWM, one feature extracted from ChIP-chip data was incorporated to identify potential TIs under specific conditions. An interaction type classifier was assembled to predict activation/repression of potential TIs using microarray data. This approach, combining an adaptive (learning) fuzzy inference system and an interaction type classifier to predict transcriptional regulatory networks, was named AdaFuzzy.ResultsAdaFuzzy was applied to predict TIs using real genomics data from Saccharomyces cerevisiae. Following one of the latest advances in predicting TIs, constrained probabilistic sparse matrix factorization (cPSMF), and using 19 transcription factors (TFs), we compared AdaFuzzy to four well-known approaches using over-representation analysis and gene set enrichment analysis. AdaFuzzy outperformed these four algorithms. Furthermore, AdaFuzzy was shown to perform comparably to 'ChIP-experimental method' in inferring TIs identified by two sets of large scale ChIP-chip data, respectively. AdaFuzzy was also able to classify all predicted TIs into one or more of the four promoter architectures. The results coincided with known promoter architectures in yeast and provided insights into transcriptional regulatory mechanisms.ConclusionAdaFuzzy successfully integrates multiple types of data (sequence, ChIP, and microarray) to predict transcriptional regulatory networks. The validated success in the prediction results implies that AdaFuzzy can be applied to uncover TIs in yeast.

Dataset Information

Applying fuzzy logic to assess the biogeographical risk of dengue in South America.

Publications

Applying fuzzy logic to assess the biogeographical risk of dengue in South America.

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