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.

Input: Consider Input: Context: This study was designed to investigate the effects of simvastatin in a rat model of acute myocardial infarction.', 'Male Wistar rats were anesthetized (thiopentone sodium 120 mg/kg). After a thoracotomy, the left-anterior-descending coronary artery (LAD) was occluded (for 25 min) and reperfused (for 120 min). Area at risk (AR) was determined with Evans Blue dye and infarct size after staining of the area at risk with nitroblue tetrazolium.', 'In rats, which received the vehicle for simvastatin (10% DMSO, 1 ml/kg i.v. at 1 h prior to the occlusion of the LAD), occlusion of the LAD for 25 min followed by reperfusion for 2 hours resulted in an infarct size of 54 +/- 4% (n=7) of the AR. When compared with vehicle, administration of simvastatin (1 mg/kg i.v. bolus administration at 1 h prior to the onset of myocardial ischemia) caused a significant reduction in myocardial infarct size of 39%. LAD-occlusion and reperfusion caused a progressive fall in mean arterial blood pressure (when compared with sham-operated animals). Simvastatin had no significant effect on blood pressure.
Answer: The result indicates that simvastatin, an inhibitor of HMG-CoA reductase and a ligand of PPAR-a and PPAR-g, reduces the tissue necrosis associated with acute myocardial infarction. We propose that statins may be useful in conditions associated with ischemia-reperfusion of the heart and other organs.

Output: Does simvastatin reduce infarct size in a model of acute myocardial ischemia and reperfusion in the rat?


Input: Consider Input: Context: A number of risk factors for chronic renal allograft rejection have been identified; in particular the number and severity of acute rejections, hypertension, hyperlipidemia, and insufficient immunosuppression.', 'In a retrospective case control study, all histologically confirmed cases of chronic rejection (n=45) that occurred between 1985 and 1993 among patients transplanted at Huddinge Hospital were compared with twice as many controls. Determinants such as donor age and sex, HLA-mismatch, cold ischemia time, recipient age and sex, body mass index, cause of renal disease, time undergoing dialysis, condition of blood vessels at surgery, time of onset, number of acute rejection episodes during the first 3 months, area under the serum creatinine versus time curve (AUC(Creatinine)), blood pressure, blood lipids, and cyclosporine concentrations at various times after the transplantation were also compared. Additional data were obtained from a questionnaire, concerning 79% of the cases and controls.', 'Cases and controls were similar with regard to most determinants, that is, blood pressure, blood lipids, and average cyclosporine concentrations. The main outstanding risk factor for chronic rejection was the time-averaged creatinine (AUC(Creatinine)) value between day 22 and 3 months after transplantation. The adjusted odds ratio for chronic rejection increased stepwise from 1.1 to 9.2, when AUC(Creatinine) increased from < 150 to >300 micromol/l. The number of acute rejection episodes and number of HLA-mismatches also had a significant effect on the risk of chronic rejection.
Answer: To reduce the risk of developing chronic rejection after renal transplantation acute rejection episodes during the first 3 months should be avoided as much as possible.

Output: Is area under the serum creatinine time-curve a strong predictor of chronic renal allograft rejection?


Input: Consider Input: Context: Central nervous system (CNS) trauma and neurodegenerative disorders trigger a cascade of cellular and molecular events resulting in neuronal apoptosis and regenerative failure. The pathogenic mechanisms and gene expression changes associated with these detrimental events can be effectively studied using a rodent optic nerve crush (ONC) model. The purpose of this study was to use a mouse ONC model to: (a) evaluate changes in retina and optic nerve (ON) gene expression, (b) identify neurodegenerative pathogenic pathways and (c) discover potential new therapeutic targets.', 'Only 54% of total neurons survived in the ganglion cell layer (GCL) 28 days post crush. Using Bayesian Estimation of Temporal Regulation (BETR) gene expression analysis, we identified significantly altered expression of 1,723 and 2,110 genes in the retina and ON, respectively. Meta-analysis of altered gene expression (≥1.5, ≤-1.5, p\u2009<\u20090.05) using Partek and DAVID demonstrated 28 up and 20 down-regulated retinal gene clusters and 57 up and 41 down-regulated optic nerve clusters. Regulated gene clusters included regenerative change, synaptic plasticity, axonogenesis, neuron projection, and neuron differentiation. Expression of selected genes (Vsnl1, Syt1, Synpr and Nrn1) from retinal and ON neuronal clusters were quantitatively and qualitatively examined for their relation to axonal neurodegeneration by immunohistochemistry and qRT-PCR.
Answer: A number of detrimental gene expression changes occur that contribute to trauma-induced neurodegeneration after injury to ON axons. Nrn1 (synaptic plasticity gene), Synpr and Syt1 (synaptic vesicle fusion genes), and Vsnl1 (neuron differentiation associated gene) were a few of the potentially unique genes identified that were down-regulated spatially and temporally in our rodent ONC model. Bioinformatic meta-analysis identified significant tissue-specific and time-dependent gene clusters associated with regenerative changes, synaptic plasticity, axonogenesis, neuron projection, and neuron differentiation. These ONC induced neuronal loss and regenerative failure associated clusters can be extrapolated to changes occurring in other forms of CNS trauma or in clinical neurodegenerative pathological settings. In conclusion, this study identified potential therapeutic targets to address two key mechanisms of CNS trauma and neurodegeneration: neuronal loss and regenerative failure.


Output: Does optic nerve crush induce spatial and temporal gene expression patterns in retina and optic nerve of BALB/cJ mice?