Measurements from the RV Ronald H. Brown and related platforms as part of the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC)

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Quinn, P. K., Thompson, E. J., Coffman, D. J., Baidar, S., Bariteau, L., Bates, T. S., Bigorre, S., Brewer, A., de Boer, G., de Szoeke, S. P., Drushka, K., Foltz, G. R., Intrieri, J., Iyer, S., Fairall, C. W., Gaston, C. J., Jansen, F., Johnson, J. E., Krueger, O. O., Marchbanks, R. D., Moran, K. P., Noone, D., Pezoa, S., Pincus, R., Plueddemann, A. J., Poehlker, M. L., Poeschl, U., Melendez, E. Q., Royer, H. M., Szczodrak, M., Thomson, J., Upchurch, L. M., Zhang, C., Zhang, D., & Zuidema, P. Measurements from the RV Ronald H. Brown and related platforms as part of the Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC). Earth System Science Data, 13(4), (2021): 1759-1790, https://doi.org/10.5194/essd-13-1759-2021.The Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) took place from 7 January to 11 July 2020 in the tropical North Atlantic between the eastern edge of Barbados and 51∘ W, the longitude of the Northwest Tropical Atlantic Station (NTAS) mooring. Measurements were made to gather information on shallow atmospheric convection, the effects of aerosols and clouds on the ocean surface energy budget, and mesoscale oceanic processes. Multiple platforms were deployed during ATOMIC including the NOAA RV Ronald H. Brown (RHB) (7 January to 13 February) and WP-3D Orion (P-3) aircraft (17 January to 10 February), the University of Colorado's Robust Autonomous Aerial Vehicle-Endurant Nimble (RAAVEN) uncrewed aerial system (UAS) (24 January to 15 February), NOAA- and NASA-sponsored Saildrones (12 January to 11 July), and Surface Velocity Program Salinity (SVPS) surface ocean drifters (23 January to 29 April). The RV Ronald H. Brown conducted in situ and remote sensing measurements of oceanic and atmospheric properties with an emphasis on mesoscale oceanic–atmospheric coupling and aerosol–cloud interactions. In addition, the ship served as a launching pad for Wave Gliders, Surface Wave Instrument Floats with Tracking (SWIFTs), and radiosondes. Details of measurements made from the RV Ronald H. Brown, ship-deployed assets, and other platforms closely coordinated with the ship during ATOMIC are provided here. These platforms include Saildrone 1064 and the RAAVEN UAS as well as the Barbados Cloud Observatory (BCO) and Barbados Atmospheric Chemistry Observatory (BACO). Inter-platform comparisons are presented to assess consistency in the data sets. Data sets from the RV Ronald H. Brown and deployed assets have been quality controlled and are publicly available at NOAA's National Centers for Environmental Information (NCEI) data archive (https://www.ncei.noaa.gov/archive/accession/ATOMIC-2020, last access: 2 April 2021). Point-of-contact information and links to individual data sets with digital object identifiers (DOIs) are provided herein.NOAA's Climate Variability and Predictability Program provided funding under NOAA CVP NA19OAR4310379, GC19-301, and GC19-305. The Joint Institute for the Study of the Atmosphere and Ocean (JISAO) supported this study under NOAA cooperative agreement NA15OAR4320063. Additional support was provided by the NOAA's Uncrewed Aircraft Systems (UAS) Program Office, NOAA's Physical Sciences Laboratory, and NOAA AOML's Physical Oceanography Division. The NTAS project is funded by the NOAA's Global Ocean Monitoring and Observing Program (CPO FundRef number 100007298), through the Cooperative Institute for the North Atlantic Region (CINAR) under cooperative agreement NA14OAR4320158

Reproductive factors and subtypes of breast cancer defined by hormone receptor and histology

Reproductive factors are associated with reduced risk of breast cancer, but less is known about whether there is differential protection against subtypes of breast cancer. Assuming reproductive factors act through hormonal mechanisms they should protect predominantly against cancers expressing oestrogen (ER) and progesterone (PR) receptors. We examined the effect of reproductive factors on subgroups of tumours defined by hormone receptor status as well as histology using data from the NIHCD Women's Contraceptive and Reproductive Experiences (CARE) Study, a multicenter case–control study of breast cancer. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) as measures of relative risk using multivariate unconditional logistic regression methods. Multiparity and early age at first birth were associated with reduced relative risk of ER + PR + tumours (P for trend=0.0001 and 0.01, respectively), but not of ER − PR − tumours (P for trend=0.27 and 0.85), whereas duration of breastfeeding was associated with lower relative risk of both receptor-positive (P for trend=0.0002) and receptor-negative tumours (P=0.0004). Our results were consistent across subgroups of women based on age and ethnicity. We found few significant differences by histologic subtype, although the strongest protective effect of multiparity was seen for mixed ductolobular tumours. Our results indicate that parity and age at first birth are associated with reduced risk of receptor-positive tumours only, while lactation is associated with reduced risk of both receptor-positive and -negative tumours. This suggests that parity and lactation act through different mechanisms. This study also suggests that reproductive factors have similar protective effects on breast tumours of lobular and ductal origin

Probing the competition among different coordination motifs in metal-ciprofloxacin complexes through IRMPD spectroscopy and DFT calculations

The vibrational spectra of ciprofloxacin complexes with monovalent (Li+, Na+, K+, Ag+) and polyvalent (Mg2+, Al3+) metal ions are recorded in the range 1000-1900 cm(-1) by means of infrared multiple-photon dissociation (IRMPD) spectroscopy. The IRMPD spectra are analyzed and interpreted in the light of density functional theory (DFT)-based quantum chemical calculations in order to identify the possible structures present under our experimental conditions. For each metal-ciprofloxacin complex, four isomers are predicted, considering different chelation patterns. A good agreement is found between the measured IRMPD spectrum and the calculated absorption spectrum of the most stable isomer for each complex. Metal ion size and charge are found to drive the competition among the different coordination motifs: small size and high charge density metal ions prefer to coordinate the quinolone between the two carbonyl oxygen atoms, whereas large-size metal ions prefer the carboxylate group as a coordination site. In the latter case, an intramolecular hydrogen bond compensates the weaker interaction established by these cations. The role of the metal cation on the stabilization of ionic and nonionic structures of ciprofloxacin is also investigated. It is found that large-size metal ions preferentially stabilize charge separated motifs and that the increase of metal ion charge has a stabilizing effect on the zwitterionic form of ciprofloxacin

Overview of the 2010 Carbonaceous Aerosols and Radiative Effects Study (CARES)

Substantial uncertainties still exist in the scientific understanding of the possible interactions between urban and natural (biogenic) emissions in the production and transformation of atmospheric aerosol and the resulting impact on climate change. The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Carbonaceous Aerosol and Radiative Effects Study (CARES) carried out in June 2010 in Central Valley, California, was a comprehensive effort designed to improve this understanding. The primary objective of the field study was to investigate the evolution of secondary organic and black carbon aerosols and their climate-related properties in the Sacramento urban plume as it was routinely transported into the forested Sierra Nevada foothills area. Urban aerosols and trace gases experienced significant physical and chemical transformations as they mixed with the reactive biogenic hydrocarbons emitted from the forest. Two heavily-instrumented ground sites – one within the Sacramento urban area and another about 40 km to the northeast in the foothills area – were set up to characterize the evolution of meteorological variables, trace gases, aerosol precursors, aerosol size, composition, and climate-related properties in freshly polluted and "aged" urban air. On selected days, the DOE G-1 aircraft was deployed to make similar measurements upwind and across the evolving Sacramento plume in the morning and again in the afternoon. The NASA B-200 aircraft, carrying remote sensing instruments, was also deployed to characterize the vertical and horizontal distribution of aerosols and aerosol optical properties within and around the plume. This overview provides: (a) the scientific background and motivation for the study, (b) the operational and logistical information pertinent to the execution of the study, (c) an overview of key observations and initial findings from the aircraft and ground-based sampling platforms, and (d) a roadmap of planned data analyses and focused modeling efforts that will facilitate the integration of new knowledge into improved representations of key aerosol processes and properties in climate models.United States. Dept. of Energy. Atmospheric System Research Program (Contract DE-AC06-76RLO 1830)United States. National Oceanic and Atmospheric AdministrationUnited States. National Aeronautics and Space Administration. HQ Science Mission Directorate Radiation Sciences ProgramUnited States. National Aeronautics and Space Administration. CALIPSO ProgramUnited States. Dept. of Energy. Atmospheric Radiation Measurement Program (Interagency Agreement No. DE-AI02-05ER63985

Evaluation of unclassified variants in the breast cancer susceptibility genes BRCA1 and BRCA2 using five methods: results from a population-based study of young breast cancer patients

Introduction Efforts are ongoing to determine the significance of unclassified variants (UVs) in the breast cancer susceptibility genes BRCA1/BRCA2, but no study has systematically assessed whether women carrying the suspected deleterious UVs have characteristics commonly seen among women carrying known deleterious or disease-causing mutations in BRCA1/BRCA2. Methods We sequenced BRCA1/BRCA2 in 1,469 population-based female breast cancer patients diagnosed between the ages of 20 and 49 years. We used existing literature to classify variants into known deleterious mutations, polymorphic variants, and UVs. The UVs were further classified as high risk or low risk based on five methods: allele frequency, Polyphen algorithm, sequence conservation, Grantham matrix scores, and a combination of the Grantham matrix score and sequence conservation. Furthermore, we examined whether patients who carry the variants classified as high risk using these methods have risk characteristics similar to patients with known deleterious BRCA1/BRCA2 mutations (early age at diagnosis, family history of breast cancer or ovarian cancer, and negative estrogen receptor/progesterone receptor). Results We identified 262 distinct BRCA1/BRCA2 variants, including 147 UVs, in our study population. The BRCA1 UV carriers, but not the BRCA2 UV carriers, who were classified as high risk using each classification method were more similar to the deleterious mutation carriers with respect to family history than those carriers classified as low risk. For example, the odds ratio of having a first-degree family history for the high-risk women classified using Polyphen was 3.39 (95% confidence interval = 1.16 to 9.94) compared with normal/polymorphic BRCA1 carriers. The corresponding odds ratio of low-risk women was 1.53 (95% confidence interval = 1.07 to 2.18). The odds ratio for high-risk women defined by allele frequency was 2.00 (95% confidence interval = 1.14 to 3.51), and that of low-risk women was 1.30 (95% confidence interval = 0.87 to 1.93). Conclusion The results suggest that the five classification methods yielded similar results. Polyphen was particularly better at isolating BRCA1 UV carriers likely to have a family history of breast cancer or ovarian cancer, and may therefore help to classify BRCA1 UVs. Our study suggests that these methods may not be as successful in classifying BRCA2 UVs

Teacher led school-based surveillance can allow accurate tracking of emerging infectious diseases - evidence from serial cross-sectional surveys of febrile respiratory illness during the H1N1 2009 influenza pandemic in Singapore

10.1186/1471-2334-12-336BMC Infectious Diseases12-BIDM

SNP-SNP interactions in breast cancer susceptibility

BACKGROUND: Breast cancer predisposition genes identified to date (e.g., BRCA1 and BRCA2) are responsible for less than 5% of all breast cancer cases. Many studies have shown that the cancer risks associated with individual commonly occurring single nucleotide polymorphisms (SNPs) are incremental. However, polygenic models suggest that multiple commonly occurring low to modestly penetrant SNPs of cancer related genes might have a greater effect on a disease when considered in combination. METHODS: In an attempt to identify the breast cancer risk conferred by SNP interactions, we have studied 19 SNPs from genes involved in major cancer related pathways. All SNPs were genotyped by TaqMan 5'nuclease assay. The association between the case-control status and each individual SNP, measured by the odds ratio and its corresponding 95% confidence interval, was estimated using unconditional logistic regression models. At the second stage, two-way interactions were investigated using multivariate logistic models. The robustness of the interactions, which were observed among SNPs with stronger functional evidence, was assessed using a bootstrap approach, and correction for multiple testing based on the false discovery rate (FDR) principle. RESULTS: None of these SNPs contributed to breast cancer risk individually. However, we have demonstrated evidence for gene-gene (SNP-SNP) interaction among these SNPs, which were associated with increased breast cancer risk. Our study suggests cross talk between the SNPs of the DNA repair and immune system (XPD-[Lys751Gln] and IL10-[G(-1082)A]), cell cycle and estrogen metabolism (CCND1-[Pro241Pro] and COMT-[Met108/158Val]), cell cycle and DNA repair (BARD1-[Pro24Ser] and XPD-[Lys751Gln]), and within carcinogen metabolism (GSTP1-[Ile105Val] and COMT-[Met108/158Val]) pathways. CONCLUSION: The importance of these pathways and their communication in breast cancer predisposition has been emphasized previously, but their biological interactions through SNPs have not been described. The strategy used here has the potential to identify complex biological links among breast cancer genes and processes. This will provide novel biological information, which will ultimately improve breast cancer risk management

Enhanced Statistical Tests for GWAS in Admixed Populations: Assessment using African Americans from CARe and a Breast Cancer Consortium

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations