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.

Input: Consider Input: Extranodal natural killer/T-cell lymphoma, nasal type (ENKTL), is an aggressive type of lymphoma whose standard treatment and validated prognostic model have not yet been defined.', 'CD30 expression was detected using immunohistochemistry in 96 ENKTL patients, and the data were used to evaluate its relationship with clinical features, treatment response and prognosis.', 'Expression of CD30 was detected in 31.2% of ENKTL patients, which was significantly correlated with B symptoms and elevated serum lactate dehydrogenase. The complete remission rate was not significantly different between CD30-positive and negative groups. After a median follow-up time of 31 months, 5-year overall survival (OS) and 5-year progression-free survival (PFS) rates in the CD30-positive group were both significantly lower than those in the CD30-negative group (34.1% vs. 64.4%, P=0.002, for 5 year-OS; 26.0% vs. 66.7%, P<0.001, for 5 year-PFS). In patients with an International Prognostic Index (IPI) or Korean Prognostic Index (KPI) score of 0-1, CD30 positivity was associated with shorter 5-year OS and PFS (IPI: P=0.001 and 0.002, respectively; KPI: P=0.018 and 0.023, respectively). In a multivariate Cox regression model, CD30 expression and stage were independent prognostic factors for OS (p=0.004 and p=0.012, respectively) and PFS (p=0.001 and p=0.022, respectively).

Output: Is cD30 expression a novel prognostic indicator in extranodal natural killer/T-cell lymphoma , nasal type?


Input: Consider Input: To analyze the functional connectivity patterns of the different EEG bands during wakefulness and sleep (different sleep stages and cyclic alternating pattern (CAP) conditions), using concepts derived from Graph Theory.', 'We evaluated spatial patterns of EEG band synchronization between all possible pairs of electrodes (19) placed over the scalp of 10 sleeping healthy young normal subjects using two graph theoretical measures: the clustering coefficient (Cp) and the characteristic path length (Lp). The measures were obtained during wakefulness and the different sleep stages/CAP conditions from the real EEG connectivity networks and randomized control (surrogate) networks (Cp-s and Lp-s).', 'We found values of Cp and Lp compatible with a small-world network organization in all sleep stages and for all EEG bands. All bands below 15Hz showed an increase of these features during sleep (and during CAP-A phases in particular), compared to wakefulness.

Output: Does the functional connectivity of different EEG bands move towards small-world network organization during sleep?


Input: Consider Input: To test whether weight loss may improve endothelial dysfunction in human obesity, we recruited 28 healthy obese subjects, aged 30-46 years, with BMI 30-43 kg/m(2).', 'Endothelium-dependent and -independent vasodilation were investigated by intra-arterial infusion of increasing doses of acetylcholine (ACh; 7.5, 15, and 30 microg x ml(-1) x min(-1)) and sodium nitroprusside (0.8, 1.6, and 3.2 microg x ml(-1) x min(-1)). Insulin resistance was estimated by homeostasis model assessment (HOMA). Weight loss was obtained by caloric restriction and physical activity.', 'We observed a significant reduction in BMI (from 33.1 +/- 4.2 to 27.5 +/- 4.5 kg/m(2), -16.9%, P < 0.0001) and in waist circumference (from 108.2 +/- 12.1 to 96.8 +/- 12.9 cm, -10.5%, P < 0.0001). Weight loss was also associated with a significant increase in ACh-stimulated forearm blood flow (FBF), from 7.4 +/- 2.8 to 12.9 +/- 3.4 ml. 100 ml(-1) of tissue x min(-1) kg/m(2) (P < 0.0001). Multivariate regression analysis demonstrated that the only independent predictor of FBF was HOMA, accounting for 44.5% of the variation, whereas the addition of BMI explained another 2.3% of the variation.


Output: Does weight loss in combination with physical activity improve endothelial dysfunction in human obesity?