Given a passage, 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: The DSM-5 encompasses a wide range of symptoms for Major Depressive Disorder (MDD). Symptoms are commonly added up to sum-scores, and thresholds differentiate between healthy and depressed individuals. The underlying assumption is that all patients diagnosed with MDD have a similar condition, and that sum-scores accurately reflect the severity of this condition. To test this assumption, we examined the number of DSM-5 depression symptom patterns in the "Sequenced Treatment Alternatives to Relieve Depression" (STAR*D) study.', 'We investigated the number of unique symptom profiles reported by 3703 depressed outpatients at the beginning of the first treatment stage of STAR*D.', 'Overall, we identified 1030 unique symptom profiles. Of these profiles, 864 profiles (83.9%) were endorsed by five or fewer subjects, and 501 profiles (48.6%) were endorsed by only one individual. The most common symptom profile exhibited a frequency of only 1.8%. Controlling for overall depression severity did not reduce the amount of observed heterogeneity.
Example Output: Is depression a consistent syndrome : An investigation of unique symptom patterns in the STAR*D study?

Example Input: Doxorubicin is a cytotoxic drug with potential for severe myelosuppression that is highly variable and poorly predictable.', 'We correlated CBR1 and CBR3 genotypes with the pharmacokinetics and pharmacodynamics of doxorubicin in 101 Southeast Asian breast cancer patients receiving first-line doxorubicin.', 'A common CBR3 11G>A variant was associated with lower doxorubicinol area under the concentration-time curve (AUC)/doxorubicin AUC metabolite ratio (P=0.009, GG vs. AA; trend test, P=0.004), lower CBR3 expression in breast tumor tissue (P=0.001, GG vs. AA), greater tumor reduction (P=0.015, GG vs. AA), and greater percentage reduction of leukocyte and platelet counts at nadir (trend test, P < or = 0.03). Chinese and Malays had higher frequency of the CBR3 11G>A variant than Indians (P < or = 0.002). Another variant CBR3 730G>A was associated with higher doxorubicinol AUC (P=0.009, GG vs. AA) and CBR3 expression in breast tumor tissue (P=0.001, GG vs AA).
Example Output: Does genotype of human carbonyl reductase CBR3 correlate with doxorubicin disposition and toxicity?

Example Input: Urothelial carcinoma associated 1 (UCA1) functions as an oncogene, which promotes cancer cell proliferation, invasion, and metastasis, and is responsible for drug resistance. This study aimed to determine the expression level of UCA1 in ovarian cancer and to further investigate its clinical significance.', 'The expression levels of UCA1 in ovarian cancer and normal ovaries were determined by quantitative real-time PCR. The relationship between UCA1 expression and clinical features and the prognostic value of UCA1 for overall survival were examined.', 'UCA1 expression in ovarian cancer tissues was significantly upregulated compared with normal ovarian tissues. High UCA1 expression was related to lymph node metastasis, FIGO stage, and response to chemotherapy. Kaplan-Meier analysis demonstrated that high UCA1 expression was associated with poorer overall survival in patients with ovarian cancer. Cox proportional hazards analysis showed that high UCA1 expression was an independent prognostic marker of poor outcome. This effect remained significant in the further stratification analysis.
Example Output:
Does uCA1 overexpression predict clinical outcome of patients with ovarian cancer receiving adjuvant chemotherapy?