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.

Ex Input:
Context: Both obesity and type 2 diabetes are among the risk factors for breast cancer development. Combined effect of these metabolic abnormalities on breast cancer risk however, has not been examined in premenopausal women. We tested this association in type 2 diabetic women, categorized as obese, overweight and normal body weight groups based on BMI.', 'A total of 101 subjects were included in this study. Serum levels of IL-6, TNF-alpha, C reactive protein, leptin, TGF-alpha, adiponectin and insulin were measured by ELISA. Data were logarithmically transformed for variables not normally distributed. Analysis of variance with post-hoc Bonferroni was applied to compare the data between the groups. Simple and partial correlation coefficients between the variables were determined and a stepwise multiple linear regression analysis was performed to determine the relationships between the variables of interest.', 'Significantly increased levels of IL-6, C reactive protein, leptin and significantly decreased levels of adiponectin were found in obese group, while the levels of TNF-alpha and TGF-alpha were unaltered. A positive correlation between waist circumference and IL-6 was found in obese group. Similarly, C reactive protein, waist and hip circumferences were linearly correlated with BMI in obese group. Stepwise multiple linear regression analysis revealed several significant predictors for breast cancer risk.\Question: Do combined effects of obesity and type 2 diabetes contribute to increased breast cancer risk in premenopausal women?

Ex Output:
Obesity and type 2 diabetes, owing to their effects on adipocytokines and inflammatory mediators, contribute to increased breast cancer risk in premenopausal women. This study emphasizes healthy life style and better management of these metabolic disorders to avoid the pathogenesis of breast cancer and of other chronic diseases.


Ex Input:
Context: The measurement of affective symptoms in older persons who decline cognitively is uncertain. The authors investigated whether mood variability predicts dementia in patients with age-related macular degeneration (AMD).', 'Three-year observational study after a clinical trial.', 'Community follow-up of outpatients ascertained from retina clinics.', 'One hundred sixty patients with AMD.', "Geriatric Depression Scale (GDS) administered every 2 weeks for 6 months to subjects; Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) administered to subjects' knowledgeable informants.", 'Twenty-three subjects (14.4%) declined cognitively. Age, education, baseline GDS score > or =5, and variability in GDS scores (i.e., fluctuations between adjacent time points) were associated with cognitive decline. For GDS variability, each 1 unit increase in the residual standard deviation (SD) of the GDS increased the risk for cognitive decline by 93% (IDR = 1.92; 95% CI [1.27-2.91]). Thus, subjects with a residual SD of 1 were nearly twice as likely to become demented as subjects with no variability in GDS scores. The risk for subjects with SDs of 2 increased more than threefold (IDR = 3.68; 95% CI [1.61-8.47]). A multiple regression analysis showed that GDS variability was a significant risk factor for dementia after controlling for significant covariates.\Question: Does variability in depressive symptoms predict cognitive decline in age-related macular degeneration?

Ex Output:
These data suggest a useful approach to conceptualizing and measuring depressive symptoms in older persons. Variability in self-reported mood may be an early sign of dementia and may offer new insights into the neurobiological mechanisms linking depression and cognition


Ex Input:
Context: Cigarette smoking is a major risk factor for atherosclerotic cardiovascular disease, which is responsible for a significant proportion of smoking-related deaths. However, the precise mechanism whereby smoking induces this pathology has not been fully delineated. Based on observation of DNA double-strand breaks (DSBs), the most harmful type of DNA damage, in atherosclerotic lesions, we hypothesized that there is a direct association between smoking and DSBs. The goal of this study was to investigate whether smoking induces DSBs and smoking cessation reverses DSBs in vivo through examination of peripheral mononuclear cells (MNCs).', 'Immunoreactivity of oxidative modification of DNA and DSBs were increased in human atherosclerotic lesions but not in the adjacent normal area. DSBs in human MNCs isolated from the blood of volunteers can be detected as cytologically visible "foci" using an antibody against the phosphorylated form of the histone H2AX (γ-H2AX). Young healthy active smokers (n = 15) showed increased γ-H2AX foci number when compared with non-smokers (n = 12) (foci number/cell: median, 0.37/cell; interquartile range [IQR], 0.31-0.58 vs. 4.36/cell; IQR, 3.09-7.39, p<0.0001). Smoking cessation for 1 month reduced the γ-H2AX foci number (median, 4.44/cell; IQR, 4.36-5.24 to 0.28/cell; IQR, 0.12-0.53, p<0.05). A positive correlation was noted between γ-H2AX foci number and exhaled carbon monoxide levels (r = 0.75, p<0.01).\Question: Does smoking cessation reverse DNA double-strand breaks in human mononuclear cells?

Ex Output:

Smoking induces DSBs in human MNCs in vivo, and importantly, smoking cessation for 1 month resulted in a decrease in DSBs to a level comparable to that seen in non-smokers. These data reinforce the notion that the cigarette smoking induces DSBs and highlight the importance of smoking cessation.