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: To investigate the influence of metabolic syndrome on prostate-specific antigen levels by considering prostate volume and plasma volume.', 'We retrospectively analyzed 4111 men who underwent routine check-ups including prostate-specific antigen and transrectal ultrasonography. The definition of metabolic syndrome was based on the modified Adult Treatment Panel III criteria. Prostate-specific antigen mass density (prostate-specific antigen plasma volume / prostate volume) was calculated for adjusting plasma volume and prostate volume. We compared prostate-specific antigen and prostate-specific antigen mass density levels of participants with metabolic syndrome (metabolic syndrome group, n = 1242) and without metabolic syndrome (non-prostate-specific antigen metabolic syndrome group, n = 2869). To evaluate the impact of metabolic syndrome on prostate-specific antigen, linear regression analysis for the natural logarithm of prostate-specific antigen was used.', 'Patients in the metabolic syndrome group had significantly older age (P < 0.001), larger prostate volume (P < 0.001), higher plasma volume (P < 0.001) and lower mean serum prostate-specific antigen (non-metabolic syndrome group vs metabolic syndrome group; 1.22 0.91 vs 1.15 0.76 ng/mL, P = 0.006). Prostate-specific antigen mass density in the metabolic syndrome group was still significantly lower than that in the metabolic syndrome group (0.124 0.084 vs 0.115 0.071 g/mL, P = 0.001). After adjusting for age, prostate volume and plasma volume using linear regression model, the presence of metabolic syndrome was a significant independent factor for lower prostate-specific antigen (prostate-specific antigen decrease by 4.1%, P = 0.046).

Output: Is prostate-specific antigen lowering effect of metabolic syndrome influenced by prostate volume?

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: In obese French Caucasian subjects we previously described a silent UCP3 Tyr99Tyr mutation, associated with body mass index. We hypothesised that an unknown polymorphism in the vicinity of the gene could contribute to obesity.', 'Morbidly obese subjects were screened for mutations in 1 kb upstream from the UCP3 gene. Association studies were done between a variant and obesity in 401 morbidly obese and 231 control subjects.', 'We detected three rare genetic variants and one polymorphism: a +5 G-->A in exon 1, a -155 C-->T, a -439 A insertion and a -55 C-->T located 6 bp from the putative TATA box. This variant was in linkage disequilibrium with the Tyr99Tyr polymorphism. Frequencies of the variant allele at the -55 locus were similar in the obese and control groups (0.23 vs 0.21). The -55 polymorphism was associated with BMI in the obese group (p = 0.0031): BMI was higher in TT than in CC or CT patients. Likewise control subjects with a TT genotype had a higher BMI (p = 0.03). In the obese group, homozygosity for this variant is a risk factor for high BMI (odds ratio: 1:75, p = 0.02). Obese patients were divided into tertiles according to physical activity. In the group with a wild C/C genotype, BMI was negatively associated with physical activity (p = 0.015).
Output: Is a genetic variation in the 5 ' flanking region of the UCP3 gene associated with body mass index in humans in interaction with physical activity?