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: Excessive infant crying, or infantile colic, is a common and often stress-inducing problem for parents that can ultimately result in child abuse. From previous research it is known that maternal depression is related to excessive crying, but so far little is known about the influence of paternal depression.', "In a prospective, population-based study, we obtained information on both maternal and paternal depressive symptoms at 20 weeks of pregnancy by using the Brief Symptom Inventory. Parental depressive symptoms were related to excessive crying in 4426 two-month-old infants. The definition of excessive crying was based on the widely used Wessel's criteria (ie, crying >3 hours for >3 days in the past week).", 'After adjustment for depressive symptoms of the mother and relevant confounders, we found a 1.29 (95% confidence interval: 1.09-1.52) higher risk of excessive infant crying per SD of paternal depressive symptoms.\Question: Are paternal depressive symptoms during pregnancy related to excessive infant crying?
Example Output: Our findings indicate that paternal depressive symptoms during pregnancy might be a risk factor for excessive infant crying. This finding could be related to genetic transmission, interaction of a father with lasting depressive symptoms with the infant, or related indirectly through contextual stressors such as marital, familial, or economic distress.

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: All-oral regimens combining different classes of direct-acting antivirals (DAA) are highly effective for treatment of patients with chronic hepatitis C. NS5A inhibitors will likely form a component of future interferon-sparing treatment regimens. However, despite their potential, the detailed mechanism of action of NS5A inhibitors is unclear. To study their mechanisms, we compared their kinetics of antiviral suppression with those of other classes of DAA, using the hepatitis C virus genotype 1a cell culture-infectious virus H77S.3.', 'We performed detailed kinetic analyses of specific steps in the hepatitis C virus life cycle using cell cultures incubated with protease inhibitors, polymerase inhibitors, or NS5A inhibitors. Assays were designed to measure active viral RNA synthesis and steady-state RNA abundance, polyprotein synthesis, virion assembly, and infectious virus production.', 'Despite their high potency, NS5A inhibitors were slow to inhibit viral RNA synthesis compared with protease or polymerase inhibitors. By 24 hours after addition of an NS5A inhibitor, polyprotein synthesis was reduced <50%, even at micromolar concentrations. In contrast, inhibition of virus release by NS5A inhibitors was potent and rapid, with onset of inhibition as early as 2 hours. Cells incubated with NS5A inhibitors were rapidly depleted of intracellular infectious virus and RNA-containing hepatitis C virus particles, indicating a block in virus assembly.\Question: Do kinetic analyses reveal potent and early blockade of hepatitis C virus assembly by NS5A inhibitors?
Example Output:
DAAs that target NS5A rapidly inhibit intracellular assembly of genotype 1a virions. They also inhibit formation of functional replicase complexes, but have no activity against preformed replicase, thereby resulting in slow shut-off of viral RNA synthesis.