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.

[Q]: Context: To describe technical challenges encountered using the Ovation endograft for abdominal aortic aneurysms and suggest tips and maneuvers for successful management.', "Deployment of the Ovation's unsupported main body is often associated with the anteroposterior arrangement of the limb gates instead of the usual side-by-side configuration, rendering contralateral catheterization challenging. Successful catheterization of the contralateral limb can be confirmed by lateral deviation of the ipsilateral stiff guidewire caused by balloon inflation within the contralateral limb. Moreover, failure to cannulate the contralateral limb gate due to persistent impingement of the guidewire or compromise of the inflated rings can be overcome using the transbrachial antegrade approach.\Question: Does technical challenge encountered during deployment of the ovation abdominal aortic stent-graft system?
[A]: Awareness of certain aspects associated with the use of the Ovation device and adoption of the adjunctive techniques herein described helps the interventionist avoid unexpected challenges or manage technical difficulties to maximize the device's safety and effectiveness.


[Q]: Context: Lung cancer is the most important cause of cancer mortality worldwide, but the underlying mechanisms of this disease are not fully understood. Copy number variations (CNVs) are promising genetic variations to study because of their potential effects on cancer.', 'Here we conducted a pilot study in which we systematically analyzed the association of CNVs in two lung cancer datasets: the Environment And Genetics in Lung cancer Etiology (EAGLE) and the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial datasets. We used a preestablished association method to test the datasets separately and conducted a combined analysis to test the association accordance between the two datasets. Finally, we identified 167 risk SNP loci and 22 CNVs associated with lung cancer and linked them with recombination hotspots. Functional annotation and biological relevance analyses implied that some of our predicted risk loci were supported by other studies and might be potential candidate loci for lung cancer studies.\Question: Does combined analysis with copy number variation identify risk loci in lung cancer?
[A]: Our results further emphasized the importance of copy number variations in cancer and might be a valuable complement to current genome-wide association studies on cancer.


[Q]: Context: Factors that influence energy metabolism and substrate oxidation, such as thyroid hormones (THs), may be important regulators of body weight.', 'We investigated associations of THs cross-sectionally with obesity, energy expenditure, and substrate oxidation and prospectively with weight change.', 'Euthyroid, nondiabetic, healthy, adult Pima Indians (n = 89; 47 M, 42 F) were studied. Percentage body fat (%BF) was measured by using dual-energy X-ray absorptiometry; sleeping metabolic rate (SMR), respiratory quotient, and substrate oxidation rates were measured in a respiratory chamber. Thyroid-stimulating hormone (TSH), free thyroxine (T(4)), free triiodothyronine (T(3)), and leptin concentrations were measured in fasting plasma samples.', 'TSH, but neither free T(3) nor free T(4), was associated with %BF and leptin concentrations (r = 0.27 and 0.29, respectively; both: P <or= 0.01). In multiple regression analyses adjusted for age, sex, fat mass, and fat-free mass, free T(3) was a positive predictor of SMR (P = 0.02). After adjustment for age, sex, %BF, and energy balance, free T(3) was a negative predictor of 24-h respiratory quotient (P < 0.05) and a positive predictor of 24-h lipid oxidation rate (P = 0.006). Prospectively, after an average follow-up of 4 +/- 2 y, the mean increase in weight was 3 +/- 9 kg. Baseline T(3) concentrations were associated with absolute and annual percentage of changes in weight (r = -0.27, P = 0.02, and r = -0.28, P = 0.009, for the age- and sex-adjusted associations, respectively).\Question: Do plasma concentrations of free triiodothyronine predict weight change in euthyroid persons?
[A]:
In euthyroid Pima Indians, lower free T(3) but not free T(4) concentrations were an independent predictor of SMR and lipid oxidation and a predictor of weight gain. This finding indicates that control of T(4)-to-T(3) conversion may play a role in body weight regulation.