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.
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Question: Context: We evaluated the impact of impermeable bed covers on asthma in asthmatics with clinically relevant house dust mite (HDM) sensitization.', 'The study included 32 HDM-sensitized asthmatics in whom HDM allergy was considered as a significant factor in their asthma. They were randomized into either an intervention group whose bedding was encased with impermeable covers, or a control group who received cotton covers. Before and 3 and 6 months after encasement, dust samples were collected from the bedding and assayed for Der p 1. Clinical outcomes included quality of life, lung function, bronchial reactivity to methacholine, symptoms, medications and peak flow rates.', 'Baseline Der p 1 levels in both the active and the placebo groups were comparable and high (19.2 vs 18.9 microg/g of dust). There was a significant reduction in Der p 1 levels in the active group after 6 months, but not in the placebo group (7.3 vs 21.9 microg/g of dust). Quality of life improved significantly in both the intervention and control groups, but there was no significant difference in the improvements between the groups. There was no significant change in lung function, symptoms, and requirements for medications.
Answer: Encasement of bedding significantly reduced the Der p 1 levels. However, this was not sufficient to produce worthwhile clinical improvement in those in whom dust mite avoidance might well have been recommended as part of their clinical management.

Answer: Does encasement of bedding improve asthma in atopic adult asthmatics?

Question: Context: Anosognosia is a common manifestation of Alzheimer's disease. There is an association between impaired awareness and frontal-executive cognitive deficits. Anosognosia is also correlated with decreased metabolism in the right hemisphere, particularly in frontal lobe regions.", "To investigate pathological correlates of anosognosia in Alzheimer's disease.", "41 subjects followed longitudinally in the University of Pittsburgh memory disorders clinic and with necropsy verified Alzheimer's disease were divided into two groups, based on previous clinical assessment: +Aware (n = 23) and -Aware (n = 18). A subset analysis matching subjects for dementia severity using mini-mental state examination scores was also carried out (13 +Aware; 13 -Aware). Histopathological data from necropsy brain tissue consisted of senile plaque (SP) and neurofibrillary tangle (NFT) counts (regional density) from four different brain regions in the right and left hemispheres: superior and middle frontal gyri (SMF), superior temporal isocortex (ST), the prosubiculum of the hippocampus (PRO), and the entorhinal cortex (EC).", 'SP density was greater in the right PRO region of -Aware subjects (F = 6.54, p = 0.015) than +Aware subjects. Significant differences between SP or NFT density were not observed in any other regions. In the subset analysis matching for dementia severity, SP density was again greater in the right PRO region of -Aware subjects than in the other regions (F = 12.72, p = 0.002).
Answer: Increased SP density in the right PRO region suggests that selective pathological involvement of this area contributes to awareness deficits in Alzheimer's disease. The putative role of the PRO in self appraisal may reflect its interconnections with other medial temporal and prefrontal regions.

Answer: Does right prosubiculum amyloid plaque density correlate with anosognosia in Alzheimer 's disease?

Question: Context: A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles.', 'We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes.
Answer: Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient for finding complexes involving most of the proteins and interactions in a typical PPIN.

Answer:
Do triangle network motifs predict complexes by complementing high-error interactomes with structural information?