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.

Context: To determine the prevalence of five physical frailty phenotype components and to assess the relationship between them and other clinical factors.', "A population-based cross-sectional study was performed. Subjects 75 years and older were randomly selected from primary care databases (with sampling stratified by gender). Physical frailty phenotypes were assessed using Fried's criteria. Sociodemographic data, comorbidities, nutritional status, and functional capacity were assessed.", '126 subjects were recruited (47% women). Prevalence rates were poor muscle strength: 50%; low physical activity: 29%; slow gait: 28%; exhaustion: 27%; and weight loss: 5%. Prefrailty and frailty prevalence rates were 35.7% and 29.4%, respectively. Poor muscle strength and low physical activity showed a close relationship and concordance (kappa = 0.92). Most frailty components were associated with outdoor activity, hours walked daily, and certain comorbidities.
Answer: Poor muscle strength was the most prevalent frailty component and was closely associated with physical activity, suggesting that training programs may revert or prevent the frailty process.
Do poor Muscle Strength and Low Physical Activity Are the Most Prevalent Frailty Components in Community-Dwelling Older Adults?

Context: Respiratory failure is a major complication after cardiac surgery. The purpose was to evaluate the impact of minimally invasive aortic valve replacement (mini AVR) on the occurrence of left lower lobe atelectasis (LLLA) in the cardiac intensive care unit (ICU).', '98 patients were scheduled to undergo mini AVR. 14 of these patients were converted to a full sternotomy due to technical problems. These patients were compared to a group of 50 patients having planned AVR through a full sternotomy. The incidence of LLLA was evaluated on the first postoperative chest X-ray in the cardiac ICU.', 'In the group having completed mini AVR 20/84 (24%) had a partial LLLA while in the group having extension to a full sternotomy 9/14 (64%) had LLLA lobe (P<0.005). In the group of 50 patients who had AVR through a full sternotomy, 27 patients (54%) had LLLA in the ICU which is also significantly higher (P<0.008) than the percentage of atelectasis in the mini AVR group.
Answer: Patients who had mini AVR had a significantly lower incidence of LLLA in the cardiac ICU than patients who had AVR through a full sternotomy.
Does minimally invasive aortic valve replacement reduce atelectasis in cardiac intensive care?

Context: Mutation rates are consistently varied in cancer genome and play an important role in tumorigenesis, however, little has been known about their function potential and impact on the distribution of functional mutations. In this study, we investigated genomic features which affect mutation pattern and the function importance of mutation pattern in cancer.', 'Somatic mutations of clear-cell renal cell carcinoma, liver cancer, lung cancer and melanoma and single nucleotide polymorphisms (SNPs) were intersected with 54 distinct genomic features. Somatic mutation and SNP densities were then computed for each feature type. We constructed 2856 1-Mb windows, in which each row (1-Mb window) contains somatic mutation, SNP densities and 54 feature vectors. Correlation analyses were conducted between somatic mutation, SNP densities and each feature vector. We also built two random forest models, namely somatic mutation model (CSM) and SNP model to predict somatic mutation and SNP densities on a 1-Kb scale. The relation of CSM and SNP scores was further analyzed with the distributions of deleterious coding variants predicted by SIFT and Mutation Assessor, non-coding functional variants evaluated with FunSeq 2 and GWAVA and disease-causing variants from HGMD and ClinVar databases.', 'We observed a wide range of genomic features which affect local mutation rates, such as replication time, transcription levels, histone marks and regulatory elements. Repressive histone marks, replication time and promoter contributed most to the CSM models, while, recombination rate and chromatin organizations were most important for the SNP model. We showed low mutated regions preferentially have higher densities of deleterious coding mutations, higher average scores of non-coding variants, higher fraction of functional regions and higher enrichment of disease-causing variants as compared to high mutated regions.
Answer: Somatic mutation densities vary largely across cancer genome, mutation frequency is a major indication of function and influence on the distribution of functional mutations in cancer.
Is mutation pattern an influential factor on functional mutation rates in cancer?