In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

Input: Consider Input: Context: Physical inactivity has been associated with obesity and related chronic diseases. Understanding built environment (BE) influences on specific domains of physical activity (PA) around homes and workplaces is important for public health interventions to increase population PA.', 'To examine the association of home and workplace BE features with PA occurring across specific life domains (work, leisure, and travel).', 'Between 2012 and 2013, telephone interviews were conducted with participants in four Missouri metropolitan areas. Questions included sociodemographic characteristics, home and workplace supports for PA, and dietary behaviors. Data analysis was conducted in 2013; logistic regression was used to examine associations between BE features and domain-specific PA.', "In home neighborhoods, seven of 12 BE features (availability of fruits and vegetables, presence of shops and stores, bike facilities, recreation facilities, crime rate, seeing others active, and interesting things) were associated with leisure PA. The global average score of home neighborhood BE features was associated with greater odds of travel PA (AOR=1.99, 95% CI=1.46, 2.72); leisure PA (AOR=1.84, 95% CI=1.44, 2.34); and total PA (AOR=1.41, 95% CI=1.04, 1.92). Associations between workplace neighborhoods' BE features and workplace PA were small but in the expected direction.\Question: Does home and workplace built environment support for physical activity?

Output: This study offers empirical evidence on BE supports for domain-specific PA. Findings suggest that diverse, attractive, and walkable neighborhoods around workplaces support walking, bicycling, and use of public transit. Public health practitioners, researchers, and worksite leaders could benefit by utilizing worksite domains and measures from this study for future BE assessments.


Input: Consider Input: Context: The purpose of this study was to investigate the ability of neutrophil gelatinase-associated lipocalin (NGAL), cystatin C, and their combination in predicting the duration and severity of acute kidney injury (AKI) after cardiac surgery in adults.', 'Using data from a prospective observational study of 100 adult cardiac surgical patients, we correlated early postoperative concentrations of plasma NGAL and serum cystatin C with the duration (time during which AKI persisted according to the Acute Kidney Injury Network criteria) and severity of AKI (change in serum creatinine) and with length of stay in intensive care.', 'We found a mean AKI duration of 67.2 +/- 41.0 hours which was associated with prolonged hospitalization (p < 0.001). NGAL, cystatin C, and their combination on arrival in intensive care correlated with subsequent AKI duration (all p < 0.01) and severity (all p < 0.001). The area under the receiver operating characteristic curve for AKI prediction was 0.77 (95% confidence interval: 0.63 to 0.91) for NGAL and 0.76 (95% confidence interval: 0.61 to 0.91) for cystatin C on arrival in intensive care. Both markers also correlated with length of stay in intensive care (p = 0.037; p = 0.001). Neutrophil gelatinase-associated lipocalin and cystatin C were independent predictors of AKI duration and severity and of length of stay in intensive care (all p < 0.05). The value of cystatin C on arrival in intensive care appeared to be due to a carry-over effect from preoperative values.\Question: Do novel biomarkers early predict the severity of acute kidney injury after cardiac surgery in adults?

Output: Immediately postoperatively, NGAL and cystatin C correlated with and were independent predictors of duration and severity of AKI and duration of intensive care stay after adult cardiac surgery. The combination of both renal biomarkers did not add predictive value.


Input: Consider Input: Context: Endometrial cancer is a common gynecologic cancer whose incidence is increasing annually worldwide. Current methods to detect endometrial cancer are unreliable and biomarkers are unsatisfactory for screening. Cervical scrapings were reported as a potential source of material for molecular testing. DNA methylation is a promising cancer biomarker, but limited use for detecting endometrial cancer.', 'We analyzed two methylomics databases of endometrioid-type endometrial cancer. Using nonnegative matrix factorization algorithm clustered the methylation pattern and reduced the candidate genes. We verified in pools DNA from endometrial cancer tissues and cervical scrapings, and validated in 146 cervical scrapings from patients with endometrioid-type endometrial cancer (n = 50), uterine myoma (n = 40), and healthy controls (n = 56) using quantitative methylation-specific PCR (QMSP). The logistic regression was used to evaluate the performance of methylation signal and gene combination.', 'We filtered out 180 methylated genes, which constituted four consensus clusters. Serial testing of tissues and cervical scrapings detected 14 genes that are hypermethylated in endometrial cancer. Three genes, BHLHE22, CDO1, and CELF4, had the best performance. Individual genes were sensitivity of 83.7%-96.0% and specificity of 78.7%-96.0%. A panel comprising any two of the three hypermethylated genes reached a sensitivity of 91.8%, specificity of 95.5%, and odds ratio of 236.3 (95% confidence interval, 56.4-989.6). These markers were also applied to cervical scrapings of type II endometrial cancer patients, and detected in 13 of 14 patients.\Question: Does integrated Epigenomics Analysis reveal a DNA Methylation Panel for Endometrial Cancer Detection Using Cervical Scrapings?


Output: This study demonstrates the potential use of methylated BHLHE22/CDO1/CELF4 panel for endometrial cancer screening of cervical scrapings. Clin Cancer Res; 1-10. ©2016 AACR.


