Avalanche Predictions Based on ML

Our Avalanche Prediction Model utilizes machine learning to analyze weather and climate data in order to provide users in the Northern California back-country with accurate probabilities of avalanche occurrences. Snow forecasts only provide information relating to how much snow will fall. Current avalanche danger ratings only provide the potential level for injury there is if an avalanche will occur. Our system, Avy Safe ML, let’s users survey geographic terrain and see direct probability indicators for precise geo-locations of mountain faces and ranges. These indicators are represented as variably-shaded geo-polygons that indicate avalanche risk classifications. Our data visualization allows access to the results of calculations accomplished by our support vector machine model all in a user-friendly experience. Avy Safe ML hopes to provide back-country folks with the ability ”know before they go” into potentially dangerous terrain

Using Landsat satellite data to support pesticide exposure assessment in California

<p>Abstract</p> <p>Background</p> <p>The recent U.S. Geological Survey policy offering Landsat satellite data at no cost provides researchers new opportunities to explore relationships between environment and health. The purpose of this study was to examine the potential for using Landsat satellite data to support pesticide exposure assessment in California.</p> <p>Methods and Results</p> <p>We collected a dense time series of 24 Landsat 5 and 7 images spanning the year 2000 for an agricultural region in Fresno County. We intersected the Landsat time series with the California Department of Water Resources (CDWR) land use map and selected field samples to define the phenological characteristics of 17 major crop types or crop groups. We found the frequent overpass of Landsat enabled detection of crop field conditions (e.g., bare soil, vegetated) over most of the year. However, images were limited during the winter months due to cloud cover. Many samples designated as single-cropped in the CDWR map had phenological patterns that represented multi-cropped or non-cropped fields, indicating they may have been misclassified.</p> <p>Conclusions</p> <p>We found the combination of Landsat 5 and 7 image data would clearly benefit pesticide exposure assessment in this region by 1) providing information on crop field conditions at or near the time when pesticides are applied, and 2) providing information for validating the CDWR map. The Landsat image time-series was useful for identifying idle, single-, and multi-cropped fields. Landsat data will be limited during the winter months due to cloud cover, and for years prior to the Landsat 7 launch (1999) when only one satellite was operational at any given time. We suggest additional research to determine the feasibility of integrating CDWR land use maps and Landsat data to derive crop maps in locations and time periods where maps are not available, which will allow for substantial improvements to chemical exposure estimation.</p

Estimating Water Supply Arsenic Levels in the New England Bladder Cancer Study

Background: Ingestion of inorganic arsenic in drinking water is recognized as a cause of bladder cancer when levels are relatively high (≥ 150 µg/L). The epidemiologic evidence is less clear at the low-to-moderate concentrations typically observed in the United States. Accurate retrospective exposure assessment over a long time period is a major challenge in conducting epidemiologic studies of environmental factors and diseases with long latency, such as cancer. Objective: We estimated arsenic concentrations in the water supplies of 2,611 participants in a population-based case–control study in northern New England. Methods: Estimates covered the lifetimes of most study participants and were based on a combination of arsenic measurements at the homes of the participants and statistical modeling of arsenic concentrations in the water supply of both past and current homes. We assigned a residential water supply arsenic concentration for 165,138 (95%) of the total 173,361 lifetime exposure years (EYs) and a workplace water supply arsenic level for 85,195 EYs (86% of reported occupational years). Results: Three methods accounted for 93% of the residential estimates of arsenic concentration: direct measurement of water samples (27%; median, 0.3 µg/L; range, 0.1–11.5), statistical models of water utility measurement data (49%; median, 0.4 µg/L; range, 0.3–3.3), and statistical models of arsenic concentrations in wells using aquifers in New England (17%; median, 1.6 µg/L; range, 0.6–22.4). Conclusions: We used a different validation procedure for each of the three methods, and found our estimated levels to be comparable with available measured concentrations. This methodology allowed us to calculate potential drinking water exposure over long periods

Determinants of Agricultural Pesticide Concentrations in Carpet Dust

Background: Residential proximity to agricultural pesticide applications has been used as a surrogate for exposure in epidemiologic studies, although little is known about the relationship with levels of pesticides in homes

Biallelic loss-of-function variants in PLD1 cause congenital right-sided cardiac valve defects and neonatal cardiomyopathy

Congenital heart disease is the most common type of birth defect, accounting for one-third of all congenital anomalies. Using whole-exome sequencing of 2718 patients with congenital heart disease and a search in GeneMatcher, we identified 30 patients from 21 unrelated families of different ancestries with biallelic phospholipase D1 (PLD1) variants who presented predominantly with congenital cardiac valve defects. We also associated recessive PLD1 variants with isolated neonatal cardiomyopathy. Furthermore, we established that p.I668F is a founder variant among Ashkenazi Jews (allele frequency of ~2%) and describe the phenotypic spectrum of PLD1-associated congenital heart defects. PLD1 missense variants were overrepresented in regions of the protein critical for catalytic activity, and, correspondingly, we observed a strong reduction in enzymatic activity for most of the mutant proteins in an enzymatic assay. Finally, we demonstrate that PLD1 inhibition decreased endothelial-mesenchymal transition, an established pivotal early step in valvulogenesis. In conclusion, our study provides a more detailed understanding of disease mechanisms and phenotypic expression associated with PLD1 loss of function

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

Residential proximity to industrial combustion facilities and risk of non-Hodgkin lymphoma: a case–control study

Abstract Background Residence near municipal solid waste incinerators, a major historical source of dioxin emissions, has been associated with increased risk of non-Hodgkin lymphoma (NHL) in European studies. The aim of our study was to evaluate residence near industrial combustion facilities and estimates of dioxin emissions in relation to NHL risk in the United States. Methods We conducted a population-based case–control study of NHL (1998–2000) in four National Cancer Institute-Surveillance Epidemiology and End Results centers (Detroit, Iowa, Los Angeles, Seattle). Residential histories 15 years before diagnosis (similar date for controls) were linked to an Environmental Protection Agency database of dioxin-emitting facilities for 969 cases and 749 controls. We evaluated proximity (3 and 5 km) to 10 facility types that accounted for \u3e85% of U.S. emissions and a distance-weighted average emission index (AEI [ng toxic equivalency quotient (TEQ)/year]). Results Proximity to any dioxin-emitting facility was not associated with NHL risk (3 km OR = 1.0, 95% CI 0.8-1.3). Risk was elevated for residence near cement kilns (5 km OR = 1.7, 95% CI 0.8-3.3; 3 km OR = 3.8, 95% CI 1.1-14.0) and reduced for residence near municipal solid waste incinerators (5 km OR = 0.5, 95% CI 0.3-0.9; 3 km OR = 0.3, 95% CI 0.1-1.4). The AEI was not associated with risk of NHL overall. Risk for marginal zone lymphoma was increased for the highest versus lowest quartile (5 km OR = 2.6, 95% CI 1.0-6.8; 3 km OR = 3.0, 95% CI 1.1-8.3). Conclusions Overall, we found no association with residential exposure to dioxins and NHL risk. However, findings for high emissions and marginal zone lymphoma and for specific facility types and all NHL provide some evidence of an association and deserve future study

Farm residence and lymphohematopoietic cancers in the Iowa Womens Health Study

BACKGROUND: Cancer incidence in male farmers has been studied extensively; however, less is known about risk among women residing on farms or in agricultural areas, who may be exposed to pesticides by their proximity to crop fields. We extended a previous follow-up of the Iowa Women’s Health Study cohort to examine farm residence and the incidence of lymphohematopoietic cancers. Further, we investigated crop acreage within 750 m of residences, which has been associated with higher herbicide levels in Iowa homes. METHODS: We analyzed data for a cohort of 37,099 Iowa women aged 55–69 years who reported their residence location (farm, rural (not a farm), town size based on population) at enrollment in 1986. We identified incident lymphohematopoietic cancers (1986–2009) by linkage with the Iowa Cancer Registry. Using a geographic information system, we geocoded addresses and calculated acreage of pasture and row crops within 750 m of homes using the 1992 National Land Cover Database. Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) in multivariate analyses of cancer risk in relation to both residence location and crop acreage. RESULTS: As found in an earlier analysis of residence location, risk of acute myeloid leukemia (AML) was higher among women living on farms (HR= 2.23, 95%CI: 1.25–3.99) or rural areas (but not on a farm) (HR= 1.95, 95%CI: 0.89–4.29) compared with women living in towns of > 10,000 population. We observed no association between farm or rural residence and non-Hodgkin lymphoma (NHL; overall or for major subtypes) or multiple myeloma. In analyses of crop acreage, we observed no association between pasture or row crop acreage within 750 m of homes and risk of leukemia overall or for the AML subtype. Chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL) risk was nonsignificantly elevated among women with pasture acreage within 750 m of their home (HRs for increasing tertiles= 1.8, 1.8 and 1.5) and with row crop acreage within 750 m (HRs for increasing tertiles of acreage= 1.4, 1.5 and 1.6) compared to women with no pasture or row crop acreage, respectively. CONCLUSIONS: Iowa women living on a farm or in a rural area were at increased risk of developing AML, which was not related to crop acreage near the home. Living near pasture or row crops may confer an increased risk of CLL/SLL regardless of residence location. Further investigation of specific farm-related exposures and these cancers among women living on farms and in agricultural areas is warranted

Residential proximity to industrial combustion facilities and risk of non-Hodgkin lymphoma: a case–control study

Abstract Background Residence near municipal solid waste incinerators, a major historical source of dioxin emissions, has been associated with increased risk of non-Hodgkin lymphoma (NHL) in European studies. The aim of our study was to evaluate residence near industrial combustion facilities and estimates of dioxin emissions in relation to NHL risk in the United States. Methods We conducted a population-based case–control study of NHL (1998–2000) in four National Cancer Institute-Surveillance Epidemiology and End Results centers (Detroit, Iowa, Los Angeles, Seattle). Residential histories 15 years before diagnosis (similar date for controls) were linked to an Environmental Protection Agency database of dioxin-emitting facilities for 969 cases and 749 controls. We evaluated proximity (3 and 5 km) to 10 facility types that accounted for \u3e85% of U.S. emissions and a distance-weighted average emission index (AEI [ng toxic equivalency quotient (TEQ)/year]). Results Proximity to any dioxin-emitting facility was not associated with NHL risk (3 km OR = 1.0, 95% CI 0.8-1.3). Risk was elevated for residence near cement kilns (5 km OR = 1.7, 95% CI 0.8-3.3; 3 km OR = 3.8, 95% CI 1.1-14.0) and reduced for residence near municipal solid waste incinerators (5 km OR = 0.5, 95% CI 0.3-0.9; 3 km OR = 0.3, 95% CI 0.1-1.4). The AEI was not associated with risk of NHL overall. Risk for marginal zone lymphoma was increased for the highest versus lowest quartile (5 km OR = 2.6, 95% CI 1.0-6.8; 3 km OR = 3.0, 95% CI 1.1-8.3). Conclusions Overall, we found no association with residential exposure to dioxins and NHL risk. However, findings for high emissions and marginal zone lymphoma and for specific facility types and all NHL provide some evidence of an association and deserve future study