TASK DEFINITION: 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.
PROBLEM: To investigate the association between adenoidectomy and/or tonsillectomy in childhood and asthma, allergic rhinitis (AR), and eczema in adolescence.', 'Longitudinal birth cohort study of 1328 members born in the city of Nijmegen. Information on ear-nose-throat surgery was documented at 2, 4, and 8 years of age. In 1055 cohort members the incidence of asthma, AR, and eczema at 21 years of age was determined using the International Study of Asthma and Allergic disease in Childhood Core Questionnaire. To analyse the association between adenoidectomy and/or tonsillectomy in childhood and asthma, AR, and eczema at age 21 years, relative risks (RR) were calculated.', 'Six hundred and ninety-three (66%) members completed the questionnaire at age 21 years, of whom 104 (15%) had undergone adenoidectomy and/or tonsillectomy and 262 (38%) reported atopic disease. Children who underwent adenoidectomy and/or tonsillectomy before the age of 8 years were not more likely to develop asthma, AR, or eczema at the age of 21 years than children who did not; RR 0.93 (95% confidence limits (CL) 0.52-1.64), RR 0.94 (CL 0.68-1.30), and RR 1.00 (CL 0.59-1.68), respectively.

SOLUTION: Is adenoidectomy and/or tonsillectomy in childhood associated with atopic disease later in life?

PROBLEM: High mobility group box 1 (HMGB1) protein has been identified as a novel pro-inflammatory cytokine in coronary artery disease (CAD). We investigated the relationship between serum HMGB1 level and the severity of coronary artery stenosis.', 'Serum HMGB1 concentration in patients was measured by ELISA. All patients underwent coronary angiography and were assigned into groups according to the quartile of HMGB1 level.', 'HMGB1 level in USAP group was higher than that in control and SAP group. HMGB1 level in SAP group was higher than that in control group (p<0.05). Gensini scores in the highest quartile group (group IV), group III and group II were all significantly higher than that in the lowest quartile group (group I). There was significant correlation between angiographic Gensini score and serum level of HMGB1 (r=0.710, p<0.05). However, in subgroup analysis, we found that serum HMGB1 level was only correlated with angiographic Gensini score in SAP patients (r=0.786, p<0.05), but not USAP patients.

SOLUTION: Is increased serum HMGB1 related to the severity of coronary artery stenosis?

PROBLEM: Manual scoring of sleep relies on identifying certain characteristics in polysomnograph (PSG) signals. However, these characteristics are disrupted in patients with neurodegenerative diseases.', "This study evaluates sleep using a topic modeling and unsupervised learning approach to identify sleep topics directly from electroencephalography (EEG) and electrooculography (EOG). PSG data from control subjects were used to develop an EOG and an EEG topic model. The models were applied to PSG data from 23 control subjects, 25 patients with periodic leg movements (PLMs), 31 patients with idiopathic REM sleep behavior disorder (iRBD) and 36 patients with Parkinson's disease (PD). The data were divided into training and validation datasets and features reflecting EEG and EOG characteristics based on topics were computed. The most discriminative feature subset for separating iRBD/PD and PLM/controls was estimated using a Lasso-regularized regression model.", 'The features with highest discriminability were the number and stability of EEG topics linked to REM and N3, respectively. Validation of the model indicated a sensitivity of 91.4% and a specificity of 68.8% when classifying iRBD/PD patients.

SOLUTION:
Does data-driven modeling of sleep EEG and EOG reveal characteristics indicative of pre-Parkinson 's and Parkinson 's disease?