A Data-Driven Approach to Predict the Success of Bank Telemarketing

We propose a data mining (DM) approach to predict the success of telemarketing calls for selling bank long-term deposits. A Portuguese retail bank was addressed, with data collected from 2008 to 2013, thus including the effects of the recent finan- cial crisis. We analyzed a large set of 150 features related with bank client, product and social-economic attributes. A semi-automatic feature selection was explored in the modeling phase, performed with the data prior to July 2012 and that allowed to select a reduced set of 22 features. We also compared four DM models: logistic regression, decision trees (DT), neural network (NN) and support vector machine. Using two metrics, area of the receiver operating characteristic curve (AUC) and area of the LIFT cumulative curve (ALIFT), the four models were tested on an eval- uation phase, using the most recent data (after July 2012) and a rolling windows scheme. The NN presented the best results (AUC=0.8 and ALIFT=0.7), allowing to reach 79% of the subscribers by selecting the half better classified clients. Also, two knowledge extraction methods, a sensitivity analysis and a DT, were applied to the NN model and revealed several key attributes (e.g., Euribor rate, direction of the call and bank agent experience). Such knowledge extraction confirmed the obtained model as credible and valuable for telemarketing campaign managers

Integrating climate mitigation and environmental peacebuilding objectives through sustainable land use systems: Theory of change and indicators

Land is an essential natural resource for climate mitigation and peace. It is commonly connected with sources of GHG emissions and with drivers of (violent) conflict. Therefore, climate mitigation and peacebuilding strategies are co-designing sustainable land-use systems (SLUS) with affected communities to integrate land-based climate mitigation and peacebuilding objectives. SLUS is practiced within agricultural production systems that meet sustainability principles (environmental, social, and economic). Nevertheless, there needs to be more program evaluation frameworks, especially measurable indicators, that integrate these two objectives (achieving peace and climate mitigation). This study aims to develop a methodology and criteria to evaluate the precise mechanisms of SLUS influencing greenhouse gas (GHG) emissions and drivers of conflict. A mix-method approach was used in two case study regions, Cesar and Caquetá, Colombia, where SLUS strategies where implemented. First, we conducted three workshops, two in-person and one virtual (n = 103). Secondly, we held semi-structured interviews (n = 115) to make an analysis of the conflict. Our research focused on the drivers of land-based emissions and conflict drivers targeted by the SLUS implementation. Lastly, through a household survey (n = 929), we illustrated the impacts of SLUS in peacebuilding at the farm level. Results show that SLUS, such as cocoa agroforestry, can contribute to climate change mitigation and deliver co-benefits in four core factors: (i) socio-economic inclusion by creating jobs and diversifying livelihoods, (ii) dialogue and conflict transformation by allowing negotiations around the participatory design of farms, including conservation agreements, (iii) natural resource governance, and (iv) cooperation by creating knowledge exchange and a community of practice

Sex differences in responses to antiretroviral treatment in South African HIV-infected children on ritonavir-boosted lopinavir- and nevirapine-based treatment

Background: While studies of HIV-infected adults on antiretroviral treatment (ART) report no sex differences in immune recovery and virologic response but more ART-associated complications in women, sex differences in disease progression and response to ART among children have not been well assessed. The objective of this study was to evaluate for sex differences in response to ART in South African HIV-infected children who were randomized to continue ritonavir-boosted lopinavir (LPV/r)-based ART or switch to nevirapine-based ART. Methods: ART outcomes in HIV-infected boys and girls in Johannesburg, South Africa from 2005–2010 were compared. Children initiated ritonavir-boosted lopinavir (LPV/r)-based ART before 24 months of age and were randomized to remain on LPV/r or switch to nevirapine-based ART after achieving viral suppression. Children were followed for 76 weeks post-randomization and then long-term follow up continued for a minimum of 99 weeks and maximum of 245 weeks after randomization. Viral load, CD4 count, lipids, anthropometrics, drug concentrations, and adherence were measured at regular intervals. Outcomes were compared between sexes within treatment strata. Results: A total of 323 children (median age 8.8 months, IQR 5.1-13.5), including 168 boys and 155 girls, initiated LPV/r-based ART and 195 children were randomized. No sex differences in risk of virological failure (confirmed viral load >1000 copies/mL) by 156 weeks post-randomization were observed within either treatment group. Girls switched to nevirapine had more robust CD4 count improvement relative to boys in this group through 112 weeks post-randomization. In addition, girls remaining on LPV/r had higher plasma concentrations of ritonavir than boys during post-randomization visits. After a mean of 3.4 years post-randomization, girls remaining on LPV/r also had a higher total cholesterol:HDL ratio and lower mean HDL than boys on LPV/r. Conclusions: Sex differences are noted in treated HIV-infected children even at a young age, and appear to depend on treatment regimen. Future studies are warranted to determine biological mechanisms and clinical significance of these differences. Trial registration: ClinicalTrials.gov Identifier: NCT0011772

Long-Term Effects of Self-Control on Alcohol Use and Sexual Behavior among Urban Minority Young Women

High risk alcohol use and sexual behaviors peak in young adulthood and often occur in the same individuals. Alcohol use has been found to impair decision-making and contribute to high risk sexual activity. However, the association between alcohol use and risky sexual behavior may also reflect enduring individual differences in risk taking, sociability, self-control, and related variables. Both behaviors can serve similar functions related to recreation, interpersonal connection, and the pursuit of excitement or pleasure. The present study examined the extent to which high risk drinking and sexual behavior clustered together in a sample of urban minority young adult women, a demographic group at elevated risk for negative outcomes related to sexual health. We tested whether psychosocial functioning measured at the beginning of high school predicted classes of risk behaviors when girls were tracked longitudinally into young adulthood. Latent class analysis indicated three distinct profiles based on high risk drinking and sexual behavior (i.e., multiple sex partners) in young adulthood. The largest class (73% of the sample) reported low levels of risky drinking and sexual behavior. The next largest class (19%) reported high risk drinking and low risk sexual behavior, and the smallest class (8%) reported high levels of both behaviors. Compared to women from other racial/ethnic groups, black women were more likely to be categorized in the high risk drinking/low risk sex class. Multinomial logistic regression indicated that self-control in adolescence had a broad and enduring protective effect on risk behaviors eight years later and was associated with a greater probability of being in the low risk drinking/low risk sex class. Findings are discussed in terms of understanding the phenotypic expressions of risk behavior as they relate to early psychosocial development and the long-term protective function of self-control in reducing high risk drinking and sexual behaviors

Microbial metatranscriptomics in a permanent marine oxygen minimum zone

Simultaneous characterization of taxonomic composition, metabolic gene content and gene expression in marine oxygen minimum zones (OMZs) has potential to broaden perspectives on the microbial and biogeochemical dynamics in these environments. Here, we present a metatranscriptomic survey of microbial community metabolism in the Eastern Tropical South Pacific OMZ off northern Chile. Community RNA was sampled in late austral autumn from four depths (50, 85, 110, 200 m) extending across the oxycline and into the upper OMZ. Shotgun pyrosequencing of cDNA yielded 180 000 to 550 000 transcript sequences per depth. Based on functional gene representation, transcriptome samples clustered apart from corresponding metagenome samples from the same depth, highlighting the discrepancies between metabolic potential and actual transcription. BLAST-based characterizations of non-ribosomal RNA sequences revealed a dominance of genes involved with both oxidative (nitrification) and reductive (anammox, denitrification) components of the marine nitrogen cycle. Using annotations of protein-coding genes as proxies for taxonomic affiliation, we observed depth-specific changes in gene expression by key functional taxonomic groups. Notably, transcripts most closely matching the genome of the ammonia-oxidizing archaeon Nitrosopumilus maritimus dominated the transcriptome in the upper three depths, representing one in five protein-coding transcripts at 85 m. In contrast, transcripts matching the anammox bacterium Kuenenia stuttgartiensis dominated at the core of the OMZ (200 m; 1 in 12 protein-coding transcripts). The distribution of N. maritimus-like transcripts paralleled that of transcripts matching ammonia monooxygenase genes, which, despite being represented by both bacterial and archaeal sequences in the community DNA, were dominated (> 99%) by archaeal sequences in the RNA, suggesting a substantial role for archaeal nitrification in the upper OMZ. These data, as well as those describing other key OMZ metabolic processes (e.g. sulfur oxidation), highlight gene-specific expression patterns in the context of the entire community transcriptome, as well as identify key functional groups for taxon-specific genomic profiling.Agouron InstituteGordon and Betty Moore FoundationUnited States. Dept. of Energy (Office of Science)Comisión Nacional de Investigación Ciencia y Tecnología (Chile) (Program Fondap

High-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium.

Automated methods are needed to facilitate high-throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large-scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37-0.87) and study (kappa range = 0.39-0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p-value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000-4,500 cells: kappa = 0.78) than those with lower counts (50-500 cells: kappa = 0.41; p-value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre- and post-analytical quality control procedures are necessary in order to ensure satisfactory performance.ABCS was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009-4363]; BBMRI-NL, which is a Research Infrastructure financed by the Dutch government (NWO 184.021.007); and the Dutch National Genomics Initiative. CNIO-BCS was supported by the Genome Spain Foundation, the Red Tematica de Investigacion Cooperativa en Cancer and grants from the Asociacion Espaola Contra el Cancer and the Fondo de Investigacion Sanitario (PI11/00923 and PI081120). The Human Genotyping-CEGEN Unit (CNIO) is supported by the Instituto de Salud Carlos III. The ESTHER study was supported by a grant from the Baden Wurttemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). The KBCP was financially supported by the special Government Funding (EVO) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, the Academy of Finland and by the strategic funding of the University of Eastern Finland. We wish to thank Heather Thorne, Eveline Niedermayr, all the kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the Clinical Follow Up Study (which has received funding from the NHMRC, the National Breast Cancer Foundation, Cancer Australia, and the National Institute of Health (USA)) for their contributions to this resource, and the many families who contribute to kConFab. kConFab is supported by a grant from the National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. The MARIE study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. The MCBCS was supported by an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], the Breast Cancer Research Foundation, the Mayo Clinic Breast Cancer Registry and a generous gift from the David F. and Margaret T. Grohne Family Foundation and the Ting Tsung and Wei Fong Chao Foundation. ORIGO authors thank E. Krol-Warmerdam, and J. Blom; The contributing studies were funded by grants from the Dutch Cancer Society (UL1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). SEARCH is funded by programme grant from Cancer Research UK [C490/A10124. C490/A16561] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. Part of this work was supported by the European Community’s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009223175) (COGS). The UKBGS is funded by Breakthrough Breast Cancer and the Institute of Cancer Research (ICR), London. ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. We acknowledge funds from Breakthrough Breast Cancer, UK, in support of MGC at the time this work was carried out and funds from the Cancer Research, UK, in support of MA.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/cjp2.4

Geographic and Racial Variation in Premature Mortality in the U.S.: Analyzing the Disparities

Life expectancy at birth, estimated from United States period life tables, has been shown to vary systematically and widely by region and race. We use the same tables to estimate the probability of survival from birth to age 70 (S70), a measure of mortality more sensitive to disparities and more reliably calculated for small populations, to describe the variation and identify its sources in greater detail to assess the patterns of this variation. Examination of the unadjusted probability of S70 for each US county with a sufficient population of whites and blacks reveals large geographic differences for each race-sex group. For example, white males born in the ten percent healthiest counties have a 77 percent probability of survival to age 70, but only a 61 percent chance if born in the ten percent least healthy counties. Similar geographical disparities face white women and blacks of each sex. Moreover, within each county, large differences in S70 prevail between blacks and whites, on average 17 percentage points for men and 12 percentage points for women. In linear regressions for each race-sex group, nearly all of the geographic variation is accounted for by a common set of 22 socio-economic and environmental variables, selected for previously suspected impact on mortality; R2 ranges from 0.86 for white males to 0.72 for black females. Analysis of black-white survival chances within each county reveals that the same variables account for most of the race gap in S70 as well. When actual white male values for each explanatory variable are substituted for black in the black male prediction equation to assess the role explanatory variables play in the black-white survival difference, residual black-white differences at the county level shrink markedly to a mean of −2.4% (+/−2.4); for women the mean difference is −3.7% (+/−2.3)

High-throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium (BCAC)

Automated methods are needed to facilitate high-throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large-scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performanc