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.

[EX Q]: Clinical predictors associated with acute paraquat (PQ) poisoning have not been systematically studied.', 'To identify independent predictors of death in patients with acute PQ poisoning.', 'This is a retrospective study executed in the emergency department of a university hospital. One hundred three consecutive patients poisoned with PQ between January 1999 and December 2004 were enrolled. Urine PQ concentration, electrolyte and renal function, detailed history, and Acute Physiology and Chronic Health Evaluation II were extracted from medical records. The outcome measure was 30-day mortality. Multivariate analysis was done by Cox-proportional hazard regression model. Receiver operating characteristics area under the curve was calculated for selected predictors.', 'The crude 30-day mortality was 67.9% (70 of 103). Independent predictors of death were acute renal failure (hazard ratio, 3.53; 95% confidence interval, 1.97-6.32), hypokalemia (2.07, 1.21-3.51), hypothermia (2.91, 1.67-5.07), suicide (2.11, 1.04-4.29), and self-reported ingested dose (2.06, 1.38-3.06). The receiver operating characteristics area under the curve of serum potassium concentrations, maximal urine PQ concentrations, and Acute Physiology and Chronic Health Evaluation II scores were 0.75 (95% confidence interval, 0.60-0.81), 0.71 (0.66-0.84), and 0.80 (0.71-0.88), respectively. Under the cutoff value of 3.6 mEq/L, hypokalemia had a sensitivity of 75% and specificity of 54% in predicting mortality.
[EX A]: Are hypokalemia and hypothermia associated with 30-day mortality in patients with acute paraquat poisoning?

[EX Q]: Body weight correlates with risk of breast cancer death.', 'A retrospective cohort study using patient medical records, electronic cancer registry data, and archived tissue specimens.', 'A 395-bed, comprehensive community hospital.', 'One thousand three hundred seventy-six women, aged 24 to 81 years, who were diagnosed with breast cancer between January 1, 1988, and December 31, 1995, and for whom complete medical records and adequate tissue specimens existed.', "Body weight at the time of diagnosis and patient status (ie, alive and free of breast cancer, living with breast cancer, dead of breast cancer, or dead of other cause) at the time of longest follow-up. Additional data collected, including age at diagnosis, menopausal status, tumor size, tumor grade, lymph node status, stage at diagnosis, race, estrogen-receptor (ER) status, and treatment information, were used to create multivariate Cox proportional hazards models to estimate hazard rate (HR) ratios and 95% confidence intervals (CIs) for breast cancer death. We collected ER status from the patients' medical records, when available, and supplemented the information by using immunohistochemical techniques to determine ER status from archived paraffin-embedded tumor blocks.", 'Patients were followed up for a median of 6.8 years after diagnosis. Two hundred forty-six patients died from breast cancer. Among patients with early-stage disease (I and IIA), we observed a dose-response relationship of increasing weight with increasing likelihood of dying of breast cancer. Compared with women in the lowest category of weight (< 133 lb [60 kg] at diagnosis), women in the highest category (> or = 175 lb [79 kg]) experienced a 2.5-fold increased risk of dying from breast cancer (HR ratio, 2.54 [95% CI, 1.08-6.00]; trend P = .02). Women with ER-negative cancer experienced an approximately 2-fold higher risk of dying from breast cancer compared with women with ER-positive cancer, regardless of stage at diagnosis. Women in the upper 50th percentile of weight with early-stage disease and with ER-negative tumors had a nearly 5-fold increased risk of dying (HR ratio, 4.99 [95% CI, 2.17-11.48]; P for interaction = .10) compared with women in the lower 50th percentile of weight and ER-positive tumors. The results were similar for body mass index, a measure of obesity in which weight is adjusted for height.
[EX A]: Does body weight correlate with mortality in early-stage breast cancer?

[EX Q]: Large mega base-pair genomic regions show robust alterations in DNA methylation levels in multiple cancers. A vast majority of these regions are hypomethylated in cancers. These regions are generally enriched for CpG islands, Lamin Associated Domains and Large organized chromatin lysine modification domains, and are associated with stochastic variability in gene expression. Given the size and consistency of hypomethylated blocks (HMB) across cancer types, we hypothesized that the immediate causes of methylation instability are likely to be encoded in the genomic region near HMB boundaries, in terms of specific genomic or epigenomic signatures. However, a detailed characterization of the HMB boundaries has not been reported.', 'Here, we focused on ~13 k HMBs, encompassing approximately half of the genome, identified in colon cancer. We modeled the genomic features of HMB boundaries by Random Forest to identify their salient features, in terms of transcription factor (TF) binding motifs. Additionally we analyzed various epigenomic marks, and chromatin structural features of HMB boundaries relative to the non-HMB genomic regions.', 'We found that the classical promoter epigenomic mark--H3K4me3, is highly enriched at HMB boundaries, as are CTCF bound sites. HMB boundaries harbor distinct combinations of TF motifs. Our Random Forest model based on TF motifs can accurately distinguish boundaries not only from regions inside and outside HMBs, but surprisingly, from active promoters as well. Interestingly, the distinguishing TFs and their interacting proteins are involved in chromatin modification. Finally, HMB boundaries significantly coincide with the boundaries of Topologically Associating Domains of the chromatin.
[EX A]:
Do distinct genomic and epigenomic features demarcate hypomethylated blocks in colon cancer?