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: Extracellular histones exert part of their prothrombotic activity through the stimulation of blood cells. Besides platelets, histones can bind to red blood cells (RBCs), which are important contributors to thrombogenesis, but little is known about the functional consequences of this interaction.', 'To evaluate the effect of histones on the procoagulant potential of human RBCs with particular regard to the expression of surface phosphatidylserine (PS).', 'PS exposure on human RBCs treated with a natural mixture of histones or recombinant individual histones was evaluated with fluorescein isothiocyanate-annexin-V binding and measured with flow cytometry. Calcium influx in RBCs loaded with the calcium-sensitive fluorophore Fluo-4\xa0AM was assessed with flow cytometry. The procoagulant potential of histone-treated RBCs was evaluated with a purified prothrombinase assay and a one-stage plasma recalcification clotting test.', 'Natural histones induced PS exposure on RBCs in a dose-dependent manner, and neutralization or cleavage of histones by heparin or activated protein\xa0C, respectively, abolished PS externalization. H4 was mainly responsible for the stimulating activity of histones, whereas the other subtypes were almost ineffective. Similarly, natural histones and H4 induced influx of calcium into RBCs, whereas the other individual histones did not. Histone-induced exposure of PS on RBCs translated into increased prothrombinase complex-mediated prothrombin activation and accelerated fibrin formation in plasma.\Question: Do histones induce phosphatidylserine exposure and a procoagulant phenotype in human red blood cells?
Example Output: Histones induce RBCs to express a procoagulant phenotype through the externalization of PS. This finding provides new insights into the prothrombotic activity of extracellular histones.

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: Left ventricular hypertrophy (LVH) is common in dialysis patients, and an independent predictor of mortality. While recent studies have shown no differences in mortality between the two most common dialysis modalities, hemodialysis (HD) and peritoneal dialysis (PD), their impact on LVH is controversial. We thus performed cardiac ultrasound studies in prevalent dialysis patients receiving either HD or PD and compared LVH.', 'We included 48 HD and 62 PD patients receiving treatment for at least three months in our dialysis center. All patients underwent echocardiographic examination and blood pressure measurements immediately following therapy. Volume status was assessed by bioelectrical impedance analysis.', 'There was no baseline difference in demographics or comorbidities between HD and PD patients. As expected, extracellular water (ECW) in post-HD patients was significantly lower than that in pre-HD and PD patients, while cardiac output (CO) and systolic blood pressure (SBP) were higher in pre-HD than that in post-HD or PD patients. There was no significant difference in CO or SBP between post-HD and PD patients. Left ventricular mass index (LVMI) was markedly higher in HD patients as compared to PD patients. Thus, the prevalence of LVH according to the Framingham criteria was 68.8% in HD patients and 45.2% in PD patients. Subgroup analysis showed similar results in the patients who had been on single-modality dialysis for at least two years and in the anuric patients. Finally, in a linear regression model (r(2) = 0.364, p < 0.001), SBP, treatment modality (to be in HD), and ECW were all independent predictors of LVMI.\Question: Is the prevalence of left ventricular hypertrophy in Chinese hemodialysis patients higher than that in peritoneal dialysis patients?
Example Output:
In a cross-sectional analysis of prevalent Chinese patients, we found a higher LVMI and a higher prevalence of LVH in HD than in PD patients. As LVMI was associated with high blood pressure and volume overload, we suggest that in these patients, PD may preserve more physiological hemodynamics even during long-term therapy.