Body fatness and sex steroid hormone concentrations in US men: results from NHANES III

Objective: Obesity is associated with a variety of chronic diseases, including cancer, which may partly be explained by its influence on sex steroid hormone concentrations. Whether different measures of obesity, i.e., body mass index (BMI), waist circumference, and percent body fat were differentially associated with circulating levels of sex steroid hormones was examined in 1,265 men, aged 20-90+years old, attending the morning examination session of the Third National Health and Nutrition Examination Survey (NHANES III). Materials and methods: Serum hormones were measured by immunoassay. Weight, height, and waist circumference were measured by trained staff. Percent body fat was estimated from bioelectrical impedance. Multivariate linear regression was used to estimate associations between body fatness measures and hormone levels. Results: Total and free testosterone and sex hormone binding globulin concentrations decreased, whereas total and free estradiol increased with increasing BMI, waist circumference, and percent body fat (all p trend<0.05). The magnitude of change in these hormones was similar for a one-quartile increase in each body fatness measure. Conclusion: Measured BMI, waist circumference, and percent body fat led to similar inferences about their association with hormone levels in me

Nationally Representative Estimates of Serum Testosterone Concentration in Never-Smoking, Lean Men Without Aging-Associated Comorbidities

Context Testosterone deficiency prevalence increases with age, comorbidities, and obesity. Objective To inform clinical guidelines for testosterone deficiency management and development of targets for nonpharmacologic intervention trials for these men, we determined serum testosterone in never-smoking, lean men without select comorbidities in nationally representative surveys. Design Setting Participants We used cross-sectional data for never-smoking, lean men ≥20 years without diabetes, myocardial infarction, congestive heart failure, stroke, or cancer, without use of hormone-influencing medications, and participated in morning sessions of National Health and Nutrition Examination Survey (NHANES) III (phase I 1988-1991) or continuous NHANES (1999-2004). By age, we determined median total testosterone (ng/mL) measured previously by a Food and Drug Administration-approved immunoassay and median estimated free testosterone concentration. Results In NHANES III, in never-smoking, lean men without comorbidities, median (25th, 75th percentile) testosterone was 4% to 9% higher than all men-20 to 39 years: 6.24 (5.16, 7.51), 40 to 59: 5.37 (3.83, 6.49), and ≥60: 4.61 (4.01, 5.18). In continuous NHANES, in never-smoking, lean men without comorbidities, levels were 13% to 24% higher than all men-20 to 39 years: 6.26 (5.32, 7.27), 40 to 59: 5.86 (4.91, 6.55), and ≥60: 4.22 (3.74, 5.73). In never-smoking, lean men without comorbidities, median estimated free testosterone was similar to (NHANES III) or slightly higher than (continuous NHANES) in all men. Conclusions These nationally representative data document testosterone levels (immunoassay) in never-smoking, lean men without select comorbidities 30 and 15 to 20 years ago. This information can be incorporated into guidelines for testosterone deficiency management and used to develop targets for nonpharmacologic intervention trials for testosterone deficiency

Lungs cancer nodules detection from ct scan images with convolutional neural networks

Lungs cancer is a life-taking disease and is causing a problem around the world for a long time. The only plausible solution for this type of disease is the early detection of the disease because at preliminary stages it can be treated or cured. With the recent medical advancements, Computerized Tomography (CT) scan is the best technique out there to get the images of internal body organs. Sometimes, even experienced doctors are not able to identify cancer just by looking at the CT scan. During the past few years, a lot of research work is devoted to achieve the task for lung cancer detection but they failed to achieve accuracy. The main objective of this piece of this research was to find an appropriate method for classification of nodules and non-nodules. For classification, the dataset was taken from Japanese Society of Radiological Technology (JSRT) with 247 three-dimensional images. The images were preprocessed into gray-scale images. The lung cancer detection model was built using Convolutional Neural Networks (CNN). The model was able to achieve an accuracy of 88% with lowest loss rate of 0.21% and was found better than other highly complex methods for classification

Barriers to non-small cell lung cancer trial eligibility

Introduction: Cancer clinical trial (CCT) enrollment is low potentially threatening the generalizability of trial results and expedited regulatory approvals. We assessed whether type of initial patient appointment for non-small cell lung cancer (NSCLC) is associated with CCT eligibility. Methods: Using a patient-to-accrual framework, we conducted a quasi-retrospective cohort pilot study at Sidney Kimmel Comprehensive Cancer Center (SKCCC), Baltimore, Maryland. 153 NSCLC patients new to SKCCC were categorized based on type of initial appointment: patients diagnosed or treated and patients seen for a consultation. CCT eligibility was determined by comparing eligibility criteria for each open trial to the electronic medical record (EMR) of each patient at every office visit occurring within 6-months of initial visit. Results: We found no association between type of initial appointment and CCT eligibility (OR, 1.15; 95% CI, 0.49–2.73). Analyses did suggest current smokers were less likely to be eligible for trials compared to never smokers (OR, 0.15; 95% CI, 0.03–0.64), and stage 4 patients with second line therapy or greater were more likely to be eligible than stage 1 or 2 patients (OR, 5.18; 95% CI, 1.08–24.75). Additional analyses suggested most current smokers and stage 1 or 2 patients had trials available but were still ineligible. Conclusions: SKCCC has a diverse portfolio of trials available for NSCLC patients and should consider research strategies to re-examine eligibility criteria for future trials to ensure increased enrollment of current smokers and stage 1 or 2 patients. We could not confirm whether type of initial visit was related to eligibility

Reuse Choice, Flood Risk and Resilience, and Characteristics of Counties with Brownfield Cleanups

Limited research has examined brownfields clean-up, reuse choice and associations with flood risk or resilience. This cross-sectional analysis examines counties with U.S. Environmental Protection Agency (EPA) funded brownfield cleanups initiated from 2005 through 2009 and assesses the county-level relationship of green reuse with flood risk while accounting for county factors of resources, environmental stressors, race and ethnicity, location, and structural characteristics, as modified from the Gee and Payne-Sturges conceptual model of community environmental health. Flood plain designation predicted a three-fold odds of green reuse alone (OR = 2.96 [95% CI, 1.31&ndash;6.66]) and green with other reuses (OR = 2.88 [95% CI, 1.07&ndash;7.75]). Green reuse alone was influenced negatively when a county had an eastern or western US location or a larger proportion of population aged 5&ndash;24 and positively when population education levels were higher. Among counties with green and other reuse, low education was predictive. Conceptually, decisions for green reuse alone were driven by resources and location while decisions for green and other reuse were driven by resources, location and environmental stressors