Given a passage with a context and an answer, construct a question on the basis of the information present in the passage. Construct the question in such a way that (i) it is unambiguous, (ii) it is answerable from the passage, (iii) its answer is unique (iv) it answer uses text phrases from the passage. Avoid creating questions that (i) can't be answered correctly without actually understanding the passage and (ii) uses the same words or phrases given in the passage.

Example Input: Context: Cirrhosis, or liver fibrosis, which is mainly triggered by cirrhosis fat-storing cells (CFSCs) activation, has traditionally been considered an irreversible disease. However, recent observations indicate that even advanced fibrosis is still reversible by removing the causative agents. Anti-fibrotic effects of bone marrow-derived stromal cells (BMSCs) have been demonstrated by inhibiting CFSCs via cytokines secretion; however, the mechanisms are still unclear.', 'The purpose of this study was to explore the underlying mechanisms by which BMSCs modulate the function of activated CFSCs.', 'After the co-culture of CFSCs with BMSCs supernatants with or without the addition of recombinant rat adrenomedullin (AM)/AM-specific siRNA, western blot analysis was mainly used to detect the differences of relative protein expression on CFSCs.', 'BMSC-secreted adrenomedullin (AM) effectively inhibited the proliferation and activation of CFSCs by suppressing the expression of Ang II and its binding receptor, AT1, which resulted in a reduction of p47-phox formation.
Answer: Our data suggested that BMSCs inhibited CFSC activation in vitro via the AM-Ang II-p47-phox signaling pathway, and since CFSC activation is an essential part of hepatic fibrosis process, this inhibition by BMSCs implies us new insights into the potential treatment of hepatic fibrosis via BMSCs.
Example Output: Do bone Marrow Stromal Cells Inhibit the Activation of Liver Cirrhotic Fat-Storing Cells via Adrenomedullin Secretion?

Example Input: Context: A computerized physician order entry (CPOE) system with embedded clinical decision support can reduce medication errors in hospitals, but might increase the time taken to generate orders.', 'We aimed to quantify the effects of temporal (month, day of week, hour of shift) and other factors (grade of doctor, prior experience with the system, alert characteristics, and shift type) on the time taken to generate a prescription order.', 'A large university teaching hospital using a locally developed CPOE system with an extensive audit database.', 'We retrospectively analyzed prescription orders from the audit database between August 2011 and July 2012.', 'The geometric mean time taken to generate a prescription order within the CPOE system was 11.75\u2005s (95% CI 11.72 to 11.78). Time to prescribe was most affected by the display of high-level (24.59\u2005s (24.43 to 24.76); p<0.001) or previously unseen (18.87\u2005s (18.78 to 18.96); p<0.001) alerts. Prescribers took significantly less time at weekends (11.29\u2005s (11.23 to 11.35)) than on weekdays (11.88\u2005s (11.84 to 11.91); p<0.001), in the first (11.25\u2005s (11.16 to 11.34); p<0.001) and final (11.56\u2005s (11.47 to 11.66); p<0.001) hour of their shifts, and after the first month of using the system.
Answer: The display of alerts, prescribing experience, system familiarity, and environment all affect the time taken to generate a prescription order. Our study reinforces the need for appropriate alerts to be presented to individuals at an appropriate place in the workflow, in order to improve prescribing efficiency.
Example Output: Do temporal and other factors that influence the time doctors take to prescribe using an electronic prescribing system?

Example Input: Context: The genus Fusarium comprises a heterogeneous group of fungi important for agriculture. Fusarium solani f. sp. eumartii (F. eumartii), historically considered to be a fungal pathogen of potato, has also been associated with tomato disease. Currently, chitosan and its derivatives have been receiving more attention as environmentally friendly antimicrobial compounds in sustainable practices. The aim of the present work was to characterize downstream events associated with the mode of action of chitosan, including nitrosative reactive species, in order to identify new biomarkers of its cytotoxic action.', 'Data indicated that chitosan-mediated nitric oxide (NO) production might lead to conidial death, concomitant with the strong reduction in fungal pathogenicity in tomato plants. Following chitosan applications, a notably dose-dependent reduction in conidial viability was demonstrated in F. eumartii. Thereafter, the infectivity of chitosan-treated spores was tested by a bioassay using tomato seedlings.
Answer: All these data highlight NO valuable properties as a quantitative and qualitative biomarker of cytotoxic action of chitosan in conidial cells. In addition, these findings place the chitosan assayed here as a fungicide with a high potential of application in sustainable horticultural practices.
Example Output:
Is nitric-oxide-mediated cell death triggered by chitosan in Fusarium eumartii spores?