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.

Q: Context: Heat shock protein-27 (HSP-27) belongs to the group of small heat shock proteins that become induced in response to various pathologic conditions. HSP-27 has been shown to protect cells and subcellular structures, particularly mitochondria, and serves as a carrier for estradiol. It is a reliable marker for tissues affected by oxidative stress. Oxidative stress and related cellular defence mechanisms are currently thought to play a major role during experimentally induced epileptic neuropathology. We addressed the question whether HSP-27 becomes induced in the neocortex resected from patients with pharmacoresistant epilepsy.', "Human epileptic temporal neocortex was obtained during neurosurgery, and control tissue was obtained at autopsy from subjects without known neurologic diseases. The tissues were either frozen for Western blot analysis or fixed in Zamboni's fixative for the topographic detection of HSP-27 at the cellular level by means of immunohistochemistry.", 'HSP-27 was highly expressed in all epilepsy specimens and in the cortex of a patient who died in the final stage of multiple sclerosis (positive control), whereas only low amounts of HSP-27 were detectable in control brains. In epilepsy patients, HSP-27 was present in astrocytes and in the walls of blood vessels. The intracortical distribution patterns varied strongly among the epilepsy specimens.
Answer: These results demonstrate that HSP-27 becomes induced in response to epileptic pathology. Although the functional aspects of HSP-27 induction during human epilepsy have yet to be elucidated, it can be concluded that HSP-27 is a marker for cortical regions in which a stress response has been caused by seizures.

A: Is heat shock protein-27 upregulated in the temporal cortex of patients with epilepsy?
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Q: Context: Before desflurane is advocated for patients undergoing neurosurgical procedures, it is necessary to determine the effect of desflurane on cerebral blood flow (CBF). In this study, CBF values are compared between desflurane and isoflurane at two doses. In addition, CBF reactivity to CO2 and the effect of prolonged exposure were compared between the two agents.', 'Cerebral blood flow measurements with intravenous 133Xe were performed in 24 patients undergoing craniotomy for mass lesions, randomized to receive either isoflurane or desflurane in oxygen and air. Cerebral blood flow was determined at 1 and 1.5 MAC concentrations at PaCO2 of 25 mmHg in the absence of surgical stimulation. Intraoperatively, with 1.25 MAC anesthesia, CBF was determined at target PaCO2 of 25 and 35 mmHg. In 15 patients, an additional measurement at 1.25 MAC was made before closure.', 'At 1.0 MAC, mean +/- SD CBF values for the desflurane and isoflurane groups were 18 +/- 2 and 20 +/- 3 ml x 100 g-1 x min-1, respectively. At 1.5 MAC, CBF values were the same for the two anesthetics; 17 +/- 3 ml x 100 g-1 x min-1 for isoflurane and 19 +/- 4 ml.100 g-1 x min-1 for desflurane. During 1.25 MAC anesthesia, there were no differences between groups, with CO2 reactivity 1.3 +/- 1.2 ml x 100 g-1 x min-1 x mmHg-1 for desflurane and 1.6 +/- 0.6 ml.100 g-1 x min-1 x mmHg-1 for isoflurane. There was no demonstrable decrease in CBF with prolonged exposure to either agent.
Answer: Desflurane and isoflurane are similar in terms of absolute CBF, the response to increasing doses, and the preservation of CO2 reactivity.

A: Do desflurane and isoflurane have similar effects on cerebral blood flow in patients with intracranial mass lesions?
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Q: Context: Mass spectrometry-based proteomics experiments generate spectra that are rich in information. Often only a fraction of this information is used for peptide/protein identification, whereas a significant proportion of the peaks in a spectrum remain unexplained. In this paper we explore how a specific class of data mining techniques termed "frequent itemset mining" can be employed to discover patterns in the unassigned data, and how such patterns can help us interpret the origin of the unexpected/unexplained peaks.', 'First a model is proposed that describes the origin of the observed peaks in a mass spectrum. For this purpose we use the classical correlative database search algorithm. Peaks that support a positive identification of the spectrum are termed explained peaks. Next, frequent itemset mining techniques are introduced to infer which unexplained peaks are associated in a spectrum. The method is validated on two types of experimental proteomic data. First, peptide mass fingerprint data is analyzed to explain the unassigned peaks in a full scan mass spectrum. Interestingly, a large numbers of experimental spectra reveals several highly frequent unexplained masses, and pattern mining on these frequent masses demonstrates that subsets of these peaks frequently co-occur. Further evaluation shows that several of these co-occurring peaks indeed have a known common origin, and other patterns are promising hypothesis generators for further analysis. Second, the proposed methodology is validated on tandem mass spectrometral data using a public spectral library, where associations within the mass differences of unassigned peaks and peptide modifications are explored. The investigation of the found patterns illustrates that meaningful patterns can be discovered that can be explained by features of the employed technology and found modifications.
Answer: This simple approach offers opportunities to monitor accumulating unexplained mass spectrometry data for emerging new patterns, with possible applications for the development of mass exclusion lists, for the refinement of quality control strategies and for a further interpretation of unexplained spectral peaks in mass spectrometry and tandem mass spectrometry.

A:
Does unravelling associations between unassigned mass spectrometry peak with frequent itemset mining techniques?
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