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: Endometrial cancers (ECs) are the most common form of gynecologic malignancy. Recent studies have reported that ECs reveal distinct markers for molecular pathogenesis, which in turn is linked to the various histological types of ECs. To understand further the molecular events contributing to ECs and endometrial tumorigenesis in general, a more precise identification of cancer-associated molecules and signaling networks would be useful for the detection and monitoring of malignancy, improving clinical cancer therapy, and personalization of treatments.', 'ECs-specific gene co-expression networks were constructed by differential expression analysis and weighted gene co-expression network analysis (WGCNA). Important pathways and putative cancer hub genes contribution to tumorigenesis of ECs were identified. An elastic-net regularized classification model was built using the cancer hub gene signatures to predict the phenotypic characteristics of ECs. The 19 cancer hub gene signatures had high predictive power to distinguish among three key principal features of ECs: grade, type, and stage. Intriguingly, these hub gene networks seem to contribute to ECs progression and malignancy via cell-cycle regulation, antigen processing and the citric acid (TCA) cycle.
Example Output: Does visual gene-network analysis reveal the cancer gene co-expression in human endometrial cancer?

Example Input: To investigate the influences of bicortical anchorage on values of natural frequencies of dental implants utilizing the 3-dimensional finite element analysis.', 'Using the commercial code of Solidworks, 3-D models of a screw-shaped dental implant and a mandibular bone segment were generated. After the 3-D implant-bone complex was meshed by ABAQUS software, effects of bicortical anchorage on the buccolingual and axial first-order natural frequencies of the implant were computed.', 'Bicortical anchorage increased both the buccolingual and axial natural frequencies remarkably. As the bicortical anchorage got deeper, the frequencies correspondingly got higher.
Example Output: Do [ Influence of bicortical anchorage on the natural frequencies of dental implant ]?

Example Input: In the present study, we evaluated the electroencephalogram (EEG) and auditory N100 potential (N100) before and during propofol-induced sedation. The aim was to test whether using EEG and N100 the level of sedation may be evaluated.', "Twenty-nine cardiac surgery patients were studied. The EEG signal and the N100 potential were recorded at awake one day before the cardiac operation and two times after the operation, when the clinical level of postoperative propofol sedation was considered deep (Ramsay Score 6) and moderate (Ramsay Score 4). Discriminant analysis was used to select those spectral EEG and/or N100 variables which would predict the correct level of sedation best. The final classification was based on canonical discriminant functions and Mahalanobis' distance.", "The spectral EEG variables (slow/fast-ratio, delta, and beta2 powers) predicted the correct level of sedation with 81% (canonical discriminant functions) and 80% (Mahalanobis' distance) accuracy. Similarly, the N100 (amplitude, latency, and the first principal component) predicted the correct level of sedation with 91% and 92% accuracy, and the combination of the EEG and N100 with 96% and 93% accuracy.
Example Output:
Do n100 auditory potential and electroencephalogram discriminate propofol-induced sedation levels?