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.

Example Input: Context: RNA editing is the process whereby an RNA sequence is modified from the sequence of the corresponding DNA template. In the mitochondria of land plants, some cytidines are converted to uridines before translation. Despite substantial study, the molecular biological mechanism by which C-to-U RNA editing proceeds remains relatively obscure, although several experimental studies have implicated a role for cis-recognition. A highly non-random distribution of nucleotides is observed in the immediate vicinity of edited sites (within 20 nucleotides 5' and 3'), but no precise consensus motif has been identified.", "Data for analysis were derived from the the complete mitochondrial genomes of Arabidopsis thaliana, Brassica napus, and Oryza sativa; additionally, a combined data set of observations across all three genomes was generated. We selected datasets based on the 20 nucleotides 5' and the 20 nucleotides 3' of edited sites and an equivalently sized and appropriately constructed null-set of non-edited sites. We used tree-based statistical methods and random forests to generate models of C-to-U RNA editing based on the nucleotides surrounding the edited/non-edited sites and on the estimated folding energies of those regions. Tree-based statistical methods based on primary sequence data surrounding edited/non-edited sites and estimates of free energy of folding yield models with optimistic re-substitution-based estimates of approximately 0.71 accuracy, approximately 0.64 sensitivity, and approximately 0.88 specificity. Random forest analysis yielded better models and more exact performance estimates with approximately 0.74 accuracy, approximately 0.72 sensitivity, and approximately 0.81 specificity for the combined observations.\Question: Do simple statistical models predict C-to-U edited sites in plant mitochondrial RNA?
Example Output: Simple models do moderately well in predicting which cytidines will be edited to uridines, and provide the first quantitative predictive models for RNA edited sites in plant mitochondria. Our analysis shows that the identity of the nucleotide -1 to the edited C and the estimated free energy of folding for a 41 nt region surrounding the edited C are the most important variables that distinguish most edited from non-edited sites. However, the results suggest that primary sequence data and simple free energy of folding calculations alone are insufficient to make highly accurate predictions.

Example Input: Context: The present study aimed to identify the relationship between glycemic variability (GV) and the 10-y risk of cardiovascular disease (CVD) in type 2 diabetes mellitus (T2DM) patients with good glycemic control.', 'Two-hundred forty consecutive T2DM patients (HbA1c7.0%) without CVD were included to calculate the 10-y CVD risk by Framingham risk score (FRS), and divided into 3 groups: low-risk group (FRS10%), intermediate-risk group (>10%, 20%) and high-risk group (>20%). Inter-group differences of GV were determined by comparing the SD of blood glucose (SDBG), mean amplitudes of glycemic excursion (MAGE), and mean of daily differences (MODD) gathered from 72-h continuous glucose monitoring system.', 'The levels of SDBG and MAGE significantly increased along with the raises of 10-y CVD risk of T2DM patients (p<0.01). FRS was positively correlated with age, systolic blood pressure, SDBG and MAGE (r=0.717, 0.525, 0.509 and 0.485 respectively, p<0.01), while negatively correlated with the level of HDL-C (r=-0.348, p<0.01). Furthermore, multivariate logistic regression analysis confirmed that increased MAGE [OR: 1.623(1.198-2.316), p<0.001] and patients with high urine albumin excretion rates [OR: 1.743(1.247-2.793), p<0.001] were independent predictors for high 10-y CVD risk.\Question: Is glycemic variability evaluated by continuous glucose monitoring system associated with the 10-y cardiovascular risk of diabetic patients with well-controlled HbA1c?
Example Output: GV predicts independently the 10-y CVD risk of T2DM patients with well-controlled HbA1c.

Example Input: Context: Prep1 and Pbx2 are the main homeodomain DNA-binding proteins of the TALE (three amino acid loop extension) family expressed in the thymus. We previously reported reduced Pbx2 expression and defective thymocyte maturation in Prep1 hypomorphic mice. To further investigate the role of this homeodomain DNA-binding protein in T cell development, we generated transgenic mice expressing the N-terminal fragment of Pbx1 (Pbx1NT) under the control of the Lck proximal promoter.', 'Pbx1NT causes Prep1 cytosolic sequestration, abolishes Prep1-dependent DNA-binding activity and results in reduced Pbx2 expression in developing thymocytes. Transgenic thymi reveal increased numbers of CD4(-) CD8(-) CD44(-) (DN3 and DN4) thymocytes, due to a higher frequency of DN2 and DN4 Pbx1NT thymocytes in the S phase. Transgenic thymocytes however do not accumulate at later stages, as revealed by a normal representation of CD4/CD8 double positive and single positive thymocytes, due to a higher rate of apoptotic cell death of DN4 Pbx1NT thymocytes.\Question: Does cytosolic sequestration of Prep1 influence early stages of T cell development?
Example Output:
The results obtained by genetic (Prep1 hypomorphic) and functional (Pbx1NT transgenic) inactivation of Prep1 support nonredundant roles for this homeodomain protein during different stages of T cell development.