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.

Ex Input:
Context: Current views on the control of cell development are anchored on the notion that phenotypes are defined by networks of transcriptional activity. The large amounts of information brought about by transcriptomics should allow the definition of these networks through the analysis of cell-specific transcriptional signatures. Here we test this principle by applying an analogue to comparative anatomy at the cellular level, searching for conserved transcriptional signatures, or conserved small gene-regulatory networks (GRNs) on root hairs (RH) and pollen tubes (PT), two filamentous apical growing cells that are a striking example of conservation of structure and function in plants.', 'We developed a new method for isolation of growing and mature root hair cells, analysed their transcriptome by microarray analysis, and further compared it with pollen and other single cell transcriptomics data. Principal component analysis shows a statistical relation between the datasets of RHs and PTs which is suggestive of a common transcriptional profile pattern for the apical growing cells in a plant, with overlapping profiles and clear similarities at the level of small GTPases, vesicle-mediated transport and various specific metabolic responses. Furthermore, cis-regulatory element analysis of co-regulated genes between RHs and PTs revealed conserved binding sequences that are likely required for the expression of genes comprising the apical signature. This included a significant occurrence of motifs associated to a defined transcriptional response upon anaerobiosis.
Answer: Our results suggest that maintaining apical growth mechanisms synchronized with energy yielding might require a combinatorial network of transcriptional regulation. We propose that this study should constitute the foundation for further genetic and physiological dissection of the mechanisms underlying apical growth of plant cells.

Ex Output:
Does transcriptional profiling of Arabidopsis root hairs and pollen define an apical cell growth signature?


Ex Input:
Context: Altered cerebrospinal fluid (CSF) levels of lactate have been described in neurodegenerative diseases and related to mitochondrial dysfunction and neuronal degeneration. We investigated the relationship between CSF lactate levels, disease severity, and biomarkers associated with neuroaxonal damage in patients with multiple sclerosis (MS).', 'One-hundred eighteen subjects with relapsing-remitting multiple sclerosis (RRMS) were included, along with one-hundred fifty seven matched controls. CSF levels of lactate, tau protein, and neurofilament light were detected at the time of diagnosis. Patients were followed-up for a mean of 5 years. Progression index (PI), multiple sclerosis severity scale (MSSS), and Bayesian risk estimate for multiple sclerosis (BREMS) were assessed as clinical measures of disease severity and progression. Differences between groups and correlation between CSF lactate, disease severity and CSF biomarkers of neuronal damage were explored.', 'CSF lactate was higher in RRMS patients compared to controls. A negative correlation was found between lactate levels and disease duration. Patients with higher CSF lactate concentration had significantly higher PI, MSSS, and BREMS scores at long-term follow-up. Furthermore, CSF lactate correlated positively and significantly with CSF levels of both tau protein and neurofilament light protein.
Answer: Measurement of CSF lactate may be helpful, in conjunction with other biomarkers of tissue damage, as an early predictor of disease severity in RRMS patients. A better understanding of the alterations of mitochondrial metabolic pathways associated to RRMS severity may pave the way to new therapeutic targets to contrast axonal damage and disease severity.

Ex Output:
Is cerebrospinal fluid lactate associated with multiple sclerosis disease progression?


Ex Input:
Context: To determine the utility of a prehospital sepsis screening protocol utilizing systemic inflammatory response syndrome (SIRS) criteria and end-tidal carbon dioxide (ETCO2).', 'We conducted a prospective cohort study among sepsis alerts activated by emergency medical services during a 12 month period after the initiation of a new sepsis screening protocol utilizing ≥2 SIRS criteria and ETCO2 levels of ≤25 mmHg in patients with suspected infection. The outcomes of those that met all criteria of the protocol were compared to those that did not. The main outcome was the diagnosis of sepsis and severe sepsis. Secondary outcomes included mortality and in-hospital lactate levels.', 'Of 330 sepsis alerts activated, 183 met all protocol criteria and 147 did not. Sepsis alerts that followed the protocol were more frequently diagnosed with sepsis (78% vs 43%, P < .001) and severe sepsis (47% vs 7%, P < .001), and had a higher mortality (11% vs 5%, P = .036). Low ETCO2 levels were the strongest predictor of sepsis (area under the ROC curve (AUC) of 0.99, 95% CI 0.99-1.00; P < .001), severe sepsis (AUC 0.80, 95% CI 0.73-0.86; P < .001), and mortality (AUC 0.70, 95% CI 0.57-0.83; P = .005) among all prehospital variables. Sepsis alerts that followed the protocol had a sensitivity of 90% (95% CI 81-95%), a specificity of 58% (95% CI 52-65%), and a negative predictive value of 93% (95% CI 87-97%) for severe sepsis. There were significant associations between prehospital ETCO2 and serum bicarbonate levels (r = 0.415, P < .001), anion gap (r = -0.322, P < .001), and lactate (r = -0.394, P < .001).
Answer: A prehospital screening protocol utilizing SIRS criteria and ETCO2 predicts sepsis and severe sepsis, which could potentially decrease time to therapeutic intervention.

Ex Output:

Does a prehospital screening tool utilizing end-tidal carbon dioxide predict sepsis and severe sepsis?