Mosquito (Diptera: Culicidae) diversity along a rainy season and edge effects in a riparian forest in Southeastern Brazil

Knowledge on the distribution of mosquito communities over time and across human-modified landscapes is important in determining the risk for vector-borne disease. The diversity of mosquitoes along a rainy season and edge effects were evaluated in a riparian forest in the Cerrado biome, Southeastern Brazil. Mosquito communities were sampled with Shannon traps in three distinct habitats (forest interior, forest edge and pasture) throughout an entire rainy season, comprising five sampling months (December 2015 to April 2016). A total of 13 549 mosquitoes belonging to 54 species were sampled. Mosquito species richness and abundance were greater in February, which coincided with the middle of the rainy season and just after the months with greater rainfall. Mosquito species richness did not differ among habitats for any particular month. In February, month when 74% of individuals were recorded, mosquito abundance was lower in the pasture compared with the forest edge and interior, which did not differ statistically from each other. Four of the six most abundant mosquito species (which account for 93.5% of the sampled individuals) had more individuals collected in the forest edge, and 28 species were more abundant at the edge compared with 15 species in the forest interior. Months with high rainfall probably allowed the availability and maintenance of high-water level in breeding sites leading to a further increase in mosquito populations. While the pasture did not seem to have the ideal abiotic conditions and/or resources (e.g. food and breeding sites) for mosquito species, edge effects appear to favour mosquito populations. Therefore, the risk of mosquito-borne diseases is expected to be greater in the middle of the rain season at the riparian forest-pasture edge, when and where a greater number of disease-vectoring species are present.     

Physical training prevents oxidative stress in L‐NAME‐induced hypertension rats

The present study investigated the effects of a 6‐week swimming training on blood pressure, nitric oxide (NO) levels and oxidative stress parameters such as protein and lipid oxidation, antioxidant enzyme activity and endogenous non‐enzymatic antioxidant content in kidney and circulating fluids, as well as on serum biochemical parameters (cholesterol, triglycerides, urea and creatinine) from Nω‐nitro‐L‐arginine methyl ester hydrochloride (L‐NAME)‐induced hypertension treated rats. Animals were divided into four groups (n = 10): Control, Exercise, L‐NAME and Exercise L‐NAME. Results showed that exercise prevented a decrease in NO levels in hypertensive rats (P < 0·05). An increase in protein and lipid oxidation observed in the L‐NAME‐treated group was reverted by physical training in serum from the Exercise L‐NAME group (P < 0·05). A decrease in the catalase (CAT) and superoxide dismutase (SOD) activities in the L‐NAME group was observed when compared with normotensive groups (P < 0·05). In kidney, exercise significantly augmented the CAT and SOD activities in the Exercise L‐NAME group when compared with the L‐NAME group (P < 0·05). There was a decrease in the non‐protein thiols (NPSH) levels in the L‐NAME‐treated group when compared with the normotensive groups (P < 0·05). In the Exercise L‐NAME group, there was an increase in NPSH levels when compared with the L‐NAME group (P < 0·05). The elevation in serum cholesterol, triglycerides, urea and creatinine levels observed in the L‐NAME group were reverted to levels close to normal by exercise in the Exercise L‐NAME group (P < 0·05). Exercise training had hypotensive effect, reducing blood pressure in the Exercise L‐NAME group (P < 0·05). These findings suggest that physical training could have a protector effect against oxidative damage and renal injury caused by hypertension. Copyright © 2012 John Wiley & Sons, Ltd.     

Comparison of methods to detect copy number alterations in cancer using simulated and real genotyping data

ABSTRACT: BACKGROUND: The detection of genomic copy number alterations (CNA) in cancer based on SNP arrays requires methods that take into account tumour specific factors such as normal cell contamination and tumour heterogeneity. A number of tools have been recently developed but their performance needs yet to be thoroughly assessed. To this aim, a comprehensive model that integrates the factors of normal cell contamination and intra-tumour heterogeneity and that can be translated to synthetic data on which to perform benchmarks is indispensable. METHODS: We propose such model and implement it in an R package called CnaGen to synthetically generate a wide range of alterations under different normal cell contamination levels. Six recently published methods for CNA and loss of heterozygosity (LOH) detection on tumour samples were assessed on this synthetic data and on a dilution series of a breast cancer cell-line: ASCAT, GAP, GenoCNA, GPHMM, MixHMM and OncoSNP. We report the recall rates in terms of normal cell contamination levels and alteration characteristics: length, copy number and LOH state, as well as the false discovery rate distribution for each copy number under different normal cell contamination levels. RESULTS: Assessed methods are in general better at detecting alterations with low copy number and under a little normal cell contamination levels. All methods except GPHMM, which failed to recognize the alteration pattern in the cell-line samples, provided similar results for the synthetic and cell-line sample sets. MixHMM and GenoCNA are the poorliest performing methods, while GAP and ASCAT, the two segmentation-based methods, generally performed better . This supports the viability of approaches other than the common hidden Markov model (HMM)-based. CONCLUSIONS: We devised and implemented a comprehensive model to generate data that simulate tumoural samples genotyped using SNP arrays. The validity of the model is supported by the similarity of the results obtained with synthetic and real data. Based on these results and on the software implementation of the methods, we recommend GAP for advanced users, ASCAT for users of basic R and GPHMM for a fully driven analysis.     

Effects of gamma irradiation on instream leaf litter decomposition

Hydrobiologia - Leaf litter decomposition is a key process in stream ecosystems, the rates of which can vary with changes in litter quality or its colonization by microorganisms. Decomposition in...     

Assessing the potential of environmental DNA metabarcoding for monitoring Neotropical mammals: a case study in the Amazon and Atlantic Forest,Brazil

The application of environmental DNA (eDNA) metabarcoding as a biomonitoring tool has greatly increased, but studies have focused on temperate aquatic macro-organisms. We apply eDNA metabarcoding to detecting the mammalian community in two high-biodiversity regions of Brazil: the Amazon and Atlantic Forests. We identified Critically Endangered and Endangered mammalian species and found overlap with species identified via camera trapping. We highlight the potential for using eDNA monitoring for mammals in biodiverse regions and identify challenges: we need a better understanding of the ecology of eDNA within variable environments and more appropriate reference sequences for species identification in these anthropogenically impacted biomes.