No evidence that protein truncating variants in BRIP1 are associated with breast cancer risk: implications for gene panel testing.

BACKGROUND: BRCA1 interacting protein C-terminal helicase 1 (BRIP1) is one of the Fanconi Anaemia Complementation (FANC) group family of DNA repair proteins. Biallelic mutations in BRIP1 are responsible for FANC group J, and previous studies have also suggested that rare protein truncating variants in BRIP1 are associated with an increased risk of breast cancer. These studies have led to inclusion of BRIP1 on targeted sequencing panels for breast cancer risk prediction. METHODS: We evaluated a truncating variant, p.Arg798Ter (rs137852986), and 10 missense variants of BRIP1, in 48 144 cases and 43 607 controls of European origin, drawn from 41 studies participating in the Breast Cancer Association Consortium (BCAC). Additionally, we sequenced the coding regions of BRIP1 in 13 213 cases and 5242 controls from the UK, 1313 cases and 1123 controls from three population-based studies as part of the Breast Cancer Family Registry, and 1853 familial cases and 2001 controls from Australia. RESULTS: The rare truncating allele of rs137852986 was observed in 23 cases and 18 controls in Europeans in BCAC (OR 1.09, 95% CI 0.58 to 2.03, p=0.79). Truncating variants were found in the sequencing studies in 34 cases (0.21%) and 19 controls (0.23%) (combined OR 0.90, 95% CI 0.48 to 1.70, p=0.75). CONCLUSIONS: These results suggest that truncating variants in BRIP1, and in particular p.Arg798Ter, are not associated with a substantial increase in breast cancer risk. Such observations have important implications for the reporting of results from breast cancer screening panels.The COGS project is funded through a European Commission's Seventh Framework Programme grant (agreement number 223175 - HEALTH-F2-2009-223175). BCAC is funded by Cancer Research UK [C1287/A10118, C1287/A12014] and by the European Community´s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 16 CA148065 and 1U19 CA148112 - the GAME-ON initiative), the Department of Defense (W81XWH-10-1- 0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. This study made use of data generated by the Wellcome Trust Case Control consortium. Funding for the project was provided by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Project established by the National Cancer Institute and National Human Genome Research Institute.This is the author accepted manuscript. The final version is available from BMJ Group at http://dx.doi.org/10.1136/jmedgenet-2015-103529

The global monsoon system representation in BAM-v1.2 and HadGEM3 climate simulations

The features of monsoon systems in the Northern and Southern Hemispheres are analysed in climate simulations of two atmospheric models: the Brazilian Global Atmospheric Model version 1.2 (BAM-v1.2) and the UK Met Office Hadley Centre Global Environment Model version 3 (HadGEM3). The results are compared to GPCP precipitation and ERA5 datasets. Although they have different configurations and parameterizations, the purpose is to evaluate their ability in representing key features of the global monsoon system. The spatial extent of the monsoon domains is well simulated by the models, as well as the main characteristics of the monsoons, although precipitation biases are noticed in the regions affected by the systems, consistent with vertical motion and moisture flux biases. The largest precipitation biases are found in the West Pacific Monsoon Region, extended to the east, and in the Australia Monsoon Region extended to the Maritime continent. Deficiencies in precipitation can be related to inaccuracy of vertical motion and humidity flux, as well as to the lack of air–sea interaction. However, the atmospheric circulation features at low and high levels are well represented in all monsoon regions, as well as the annual cycle of precipitation in those regions by both models. The divergence at high levels and convergence at low levels associated with ascending air movement and precipitation in monsoon regions are well represented by the models. An analysis of two monsoon indices at eight monsoon regions showed the models are generally able to simulate the relationship between precipitation and circulation features. In the majority of years, the signs of indices from the models agree with observations. Correlations of precipitation and circulation indices between models and observations show statistically significant values for some monsoon regions. The results obtained contribute to improving knowledge about global monsoon features and their representation in the two models

Fusarium species (section liseola) occurrence and natural incidence of beauvericin, fusaproliferinand fumonisins in maize hybrids harvested in mexico

Fusarium species can produce fumonisins (FBs), fusaric acid, beauvericin (BEA), fusaproliferin (FUS) and moniliformin. Data on the natural occurrence of FBs have been widely reported, but information on BEA and FUS in maize is limited. The aims of this study were to establish the occurrence of Fusarium species in different maize hybrids in Mexico, to determine the ability of Fusarium spp. isolates to produce BEA, FUS and FBs and their natural occurrence in maize. Twenty-eight samples corresponding to seven different maize hybrids were analyzed for mycobiota and natural mycotoxin contamination by LC. Fusarium verticillioides was the dominant species (44-80%) followed by F. subglutinans (13-37%) and F. proliferatum (2-16%). Beauvericin was detected in three different hybrids with levels ranging from 300 to 400 ng g-1, while only one hybrid was contaminated with FUS (200 ng g-1). All samples were positive for FB1 and FB2 contamination showing levels up to 606 and 277 ng g-1, respectively. All F. verticillioides isolates were able to produce FB1 (13.8-4,860 μg g-1) and some also produced FB2 and FUS. Beauvericin, FUS, FB1 and FB2 were produced by several isolates including F. proliferatum and F. subglutinans and co-production was observed. This is the first report on the co-occurrence of these toxins in maize samples from Mexico. The analysis of the presence of multiple mycotoxins in this substrate is necessary to understand the significance of these compounds in the human and animal food chains. © Society for Mycotoxin Research and Springer 2011

Assessing precipitation concentration in the Amazon basin from different satellite‐based data sets

Daily precipitation concentration in the Amazon basin (AB) is characterized using concentration index (CI), which is computed from HYBAM Observed Precipitation (HOP) data set, for 1980–2009 period. The ability of four satellite precipitation data sets (TMPA V7, TMPA RT, CMORPH and PERSIANN) to estimate CI is evaluated for 2001–2009 period. Our findings provide new information about the spatial irregularity of daily rainfall distribution over the AB. In addition, the spatial distribution of CI values is not completely explained by rainfall seasonality, which highlights the influence of different weather systems over the AB. The results of rainfall concentration indicate that the distribution of daily rainfall is more regular over northwest (northern Peru) and central Andes. Conversely, Roraima region and a large area of Bolivian Amazon register the highest irregularity in the daily rainfall. Bolivian Amazon also represents regions where the large percentage of total rainfall arises from extreme events (>90th percentile). Heavy rainfall episodes over Roraima region are induced by humidity influx come from Caribbean region, while heavy rainfall events over Bolivian Amazon and Andes region are induced by the northwards propagation of cold and dry air along both sides of Andes Mountains, but only propagate in all tropospheric levels for the Andes. The results also show that PERSIANN and TMPA7 data sets better estimates the daily precipitation concentration for whole AB, but with a relative error 8%. CI estimated from satellites does not agree well with HOP over the Andes and northern Peruvian Amazon. On the other hand, the temporal variability of CI can partly be detected using CMORPH and TMPAV7 data sets over the Peruvian Andes, and central and southern Brazil. Errors in CI estimating might be related to inaccurate estimation of daily rainfall. Finally, we conclude that satellite‐based precipitation data sets are useful for analysing rainfall concentration in some regions of AB

Influência da precipitação na qualidade da água do Rio Purus Impacts of precipitation on the water quality of the Purus River

Os impactos da precipitação na qualidade da água ao longo do rio Purus, localizado no estado do Amazonas, foi investigado por meio de dados de precipitação, estimada por satélites, e informações sobre a temperatura da água, condutividade, pH, turbidez, oxigênio dissolvido e sólidos suspensos totais, adquiridas em quatro diferentes áreas ao longo do rio. Os resultados mostraram correlação negativa entre precipitação e turbidez e positiva entre precipitação e temperatura, condutividade, oxigênio dissolvido, sólidos suspensos totais e pH. O uso do solo, juntamente com o regime de precipitação, parecem ser os fatores principais que determinam a qualidade da água nos pontos de amostragem.<br>The impacts of precipitation on the water quality along the Purus River, located in the Brazilian State of the Amazonas, was investigated using data of precipitation estimated by satellite and information about water temperature, conductivity, pH, turbidity, dissolved oxygen and total suspended solids. The data were acquired in four different areas along the river. The results showed negative correlation between precipitation and turbidity. They also showed positive correlation between precipitation and temperature, conductivity, dissolved oxygen, total suspended solids and pH. The land use together with the rainfall regime seems to be the main sources of impact on the water quality around the sampling places