In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.

Input: Consider Input: Context: To test whether oral L-81 treatment could improve the condition of mice with diabetes and to investigate how L-81 regulates microsomal triglyceride transfer protein (MTP) activity in the liver.', 'Genetically diabetic (db/db) mice were fed on chow supplemented with or without L-81 for 4 wk. The body weight, plasma glucose level, plasma lipid profile, and adipocyte volume of the db/db mice were assessed after treatment. Toxicity of L-81 was also evaluated. To understand the molecular mechanism, HepG2 cells were treated with L-81 and the effects on apolipoprotein B (apoB) secretion and mRNA level of the MTP gene were assessed.', 'Treatment of db/db mice with L-81 significantly reduced and nearly normalized their body weight, hyperphagia and polydipsia. L-81 also markedly decreased the fasting plasma glucose level, improved glucose tolerance, and attenuated the elevated levels of plasma cholesterol and triglyceride. At the effective dosage, little toxicity was observed. Treatment of HepG2 cells with L-81 not only inhibited apoB secretion, but also significantly decreased the mRNA level of the MTP gene. Similar to the action of insulin, L-81 exerted its effect on the MTP promoter.\Question: Does pluronic L-81 ameliorate diabetic symptoms in db/db mice through transcriptional regulation of microsomal triglyceride transfer protein?

Output: L-81 represents a promising candidate in the development of a selective insulin-mimetic molecule and an anti-diabetic agent.


Input: Consider Input: Context: This study examined the relationship between plasma cholesterol and circulating triiodothyronine and oestradiol in 561 adolescent girls aged 11-17 with eating disorders.', 'Plasma total cholesterol, high-density lipoprotein cholesterol, serum triodothyronine and oestradiol were measured at assessment, and historical weight data were obtained from growth charts provided by the school health services. Cholesterol levels were related to weight change, menstrual status and serum hormones.', 'Plasma total cholesterol levels of >5.0 mmol/L were found in 38% of the 77 girls who were premenarcheal, 32% of the 199 with secondary amenorrhoea and 17% of those who were still menstruating. These cholesterol levels were inversely related to serum oestradiol and triiodothyronine concentrations, but not weight change, in amenorrhoic girls and were positively related to body mass index and inversely related to weight loss and serum triiodothyronine in girls who were still menstruating.\Question: Is plasma cholesterol related to menstrual status in adolescent girls with eating disorders and weight loss?

Output: Increased plasma total cholesterol was related to amenorrhoea in adolescent girls with eating disorders and weight loss. Oestrogens appeared to mediate the effect of starvation on cholesterol, most effectively in premenarcheal girls. Re-establishing menstruation is an important goal in the treatment of eating disorders, to avoid dyslipidaemia and the risk of future cardiovascular disease.


Input: Consider Input: Context: A computerized physician order entry (CPOE) system with embedded clinical decision support can reduce medication errors in hospitals, but might increase the time taken to generate orders.', 'We aimed to quantify the effects of temporal (month, day of week, hour of shift) and other factors (grade of doctor, prior experience with the system, alert characteristics, and shift type) on the time taken to generate a prescription order.', 'A large university teaching hospital using a locally developed CPOE system with an extensive audit database.', 'We retrospectively analyzed prescription orders from the audit database between August 2011 and July 2012.', 'The geometric mean time taken to generate a prescription order within the CPOE system was 11.75\u2005s (95% CI 11.72 to 11.78). Time to prescribe was most affected by the display of high-level (24.59\u2005s (24.43 to 24.76); p<0.001) or previously unseen (18.87\u2005s (18.78 to 18.96); p<0.001) alerts. Prescribers took significantly less time at weekends (11.29\u2005s (11.23 to 11.35)) than on weekdays (11.88\u2005s (11.84 to 11.91); p<0.001), in the first (11.25\u2005s (11.16 to 11.34); p<0.001) and final (11.56\u2005s (11.47 to 11.66); p<0.001) hour of their shifts, and after the first month of using the system.\Question: Do temporal and other factors that influence the time doctors take to prescribe using an electronic prescribing system?


Output: The display of alerts, prescribing experience, system familiarity, and environment all affect the time taken to generate a prescription order. Our study reinforces the need for appropriate alerts to be presented to individuals at an appropriate place in the workflow, in order to improve prescribing efficiency.