***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Context In 2003 , the authors reported that severely obese adults lost more weight and had better serum lipid patterns after 6 months of a low-carbohydrate diet rather than a conventional low-fat diet . Contribution After 1 year , these same patients still had more favorable triglyceride and high-density lipoprotein cholesterol levels on the low-carbohydrate diet than on the conventional diet . However , weight loss and the other metabolic parameters were similar in the 2 diet groups . Caution s The effect of the modest improvements in high-density lipoprotein cholesterol and triglyceride levels on the development of diabetes and cardiovascular disease is unknown . The Editors The prevalence of obesity and its associated metabolic abnormalities has increased markedly over the past 2 decades ( 1 , 2 ) . Although guidelines to follow a highcomplex carbohydrate , low-fat , energy-deficient diet to achieve weight loss are generally accepted ( 3 ) , considerable public interest has focused on low-carbohydrate diets ( 4 ) . We recently reported that persons with severe obesity lost more weight and had greater improvements in triglyceride levels , insulin sensitivity , and glycemic control after 6 months of a low-carbohydrate diet as compared with a conventional weight loss diet based on calorie and fat restriction ( 5 ) . However , these findings were preliminary because of the short duration of that study ( 6 ) . A simultaneously published study by Foster and colleagues suggested that persons on a low-carbohydrate diet  tended to regain weight by 1 year ( 7 ) . These findings were limited , however , because few participants completed the study and because the study used a self-help approach , which is less effective than direct counseling for maintaining weight loss ( 8) . Foster and colleagues also excluded persons with diabetes , which is highly prevalent in the obese population . During the development of this study , we decided to analyze and report preliminary results at 6 months and final results at 1 year . We thought that the short-term results would be important , given the high-risk nature of our study sample , but that long-term outcomes would provide more information about the sustainability of any diet-related outcomes . We now report our findings 1 year after r and omization to a low-carbohydrate diet versus a low-fat weight loss diet ( conventional diet ) in severely obese adults with a high prevalence of diabetes or the metabolic syndrome . Methods Study Participants The study design has been previously described ( 5 ) . Participants were recruited from the outpatient practice s of the Philadelphia Veterans Affairs Medical Center and included persons 18 years of age and older with a body mass index ( BMI ) of 35 kg/m2 or greater . The exclusion criteria were a serum creatinine level greater than 133 mol/L ( > 1.5 mg/dL ) , hepatic disease , severe life-limiting medical illness , inability to self-monitor glucose levels , or active use of a weight loss program or weight loss medication . Between May 2001 and November 2001 , 132 persons were r and omly assigned to either a low-carbohydrate diet ( n = 64 ) or a conventional diet ( n = 68 ) . The Institutional Review Committee at the Philadelphia Veterans Affairs Medical Center approved the study , and all participants provided written informed consent . Interventions Diet groups met in weekly counseling sessions for 4 weeks , followed by 11 monthly sessions . Participants on the low-carbohydrate diet were instructed only to reduce carbohydrate intake to less than 30 g per day . Participants on the conventional diet were instructed to reduce caloric intake by 500 calories per day , with less than 30 % of calories derived from fat , in accordance with the National Heart , Lung , and Blood Institute guidelines ( 3 ) . Outcome Measures We collected data , including weight ( single calibrated scale , SR Instruments , Inc. , Tonaw and a , New York ) , medical history ( self-reported ) , and blood pressure , at baseline , 6 months , and 1 year . Fasting blood specimens were obtained for glucose , hemoglobin A1c , and serum lipid levels ( Synchron LX20 , Beckman Coulter , Inc. , Fullerton , California ) . Low-density lipoprotein ( LDL ) cholesterol level was calculated by using the Friedewald formula ( 9 ) . We defined the presence of diabetes by a historical fasting blood glucose level greater than 6.94 mmol/L ( > 125 mg/dL ) or use of antidiabetic medications . The metabolic syndrome was considered present if a participant had 3 or more of the following ( 10 ) : central obesity , fasting blood glucose level of 6.11 mmol/L ( 110 mg/dL ) or greater , fasting triglyceride level of 1.70 mmol/L ( 150 mg/dL ) or greater , high-density lipoprotein ( HDL ) cholesterol level less than 1.04 mmol/L ( < 40 mg/dL ) for men or less than 1.30 mmol/L ( < 50 mg/dL ) for women , blood pressure of 130/85 mm Hg or greater , or antihypertensive therapy . We assumed that all participants had central obesity because of the uniform severity of their obesity ( BMI range , 35.0 to 79.4 kg/m2 ) . Serum insulin was measured by radioimmunoassay ( Laboratory Corporation of America Holdings [ LabCorp ] , Burlington , North Carolina ] ) . Insulin resistance in nondiabetic persons was estimated by the quantitative insulin sensitivity check ( QUICK ) index : 1/[(log ( fasting insulin ( U/mL ) ) + ( log fasting glucose(mg/dL ) ) ] . Statistical Analysis Our primary end point was total weight loss at 1 year . Secondary analyses included the change from baseline in serum lipid levels , insulin sensitivity , and glycemic control . We estimated that we would need 100 persons ( 50 per group ) , assuming a 2-sided type I error of 5 % , for the study to have 80 % power to detect a 5-kg greater mean weight loss in the low-carbohydrate group than in the conventional diet group . These calculations were based on an anticipated maximum weight loss by 6 months , with weight stabilization in both diet groups between 6 months and 1 year . To compensate for an anticipated dropout rate of 25 % , we set our enrollment target at 135 persons . R and omization was performed by using a pre-established algorithm generated from a r and om set of numbers that was constructed and held in a separate center and concealed from those enrolling persons during r and omization . We used stratified r and omization , with blocking within strata , to ensure assignment of approximately equal numbers of women , diabetic persons , and severely obese persons ( BMI 40 kg/m2 ) to each study group . Changes in weight , dietary intake , and metabolic data were compared between the 2 diets by r and om-coefficient analysis ( 11 ) . This type of analysis was selected to allow for a variable number of observations for participants and to take into account that the repeated observations of the outcome variables over time for individuals were correlated . The r and om-coefficient analysis model takes these correlations into account by allowing the intercept to vary r and omly among persons . We used a restricted maximum likelihood analysis , which assumed that changes were distributed according to a bivariate normal distribution and that data were missing at r and om . The outcome variables were changes from baseline in weight , dietary macronutrient consumption , and metabolic measurements . For all of these analyses , the covariates included an indicator variable for time ( 6 months and 1 year ) , diet group , and a diet group by time interaction term . This diet group by time interaction term was kept in the model , regardless of its statistical significance ( P = 0.063 for the weight loss analysis ) . Separate analyses to adjust for baseline differences between diet groups were also made by entering the following covariates to each of these models : age ; race ( white or African American ) ; sex ; baseline BMI ; baseline caloric intake ; and the presence or absence of hypertension , use of lipid-lowering therapy , diabetes , active smoking , and sleep apnea ( 12 ) . All variables were assessed for normality before entry into the analyses . Triglyceride , insulin , and glucose levels were skewed and thus were log-transformed before the analyses . Baseline differences between diet groups were compared by chi-square analysis for dichotomous variables and by the unpaired t-test for continuous variables . All P values are 2-sided , and a P value of 0.05 was considered statistically significant . Analyses were performed with SPSS statistical software , version 11.1 ( SPSS , Inc. , Chicago , Illinois ) . Missing Data Of the 132 enrolled persons , follow-up was done at 6 months for 79 persons and at 1 year for 87 persons . For measurements at 6 months , we retrieved weights on an additional 16 persons on the low-carbohydrate diet and 23 persons on the conventional diet ( total , 39 persons at a mean [ SD ] of 6.6 1.2 months ) . For measurements at 1 year , we retrieved weights on 18 persons on the low-carbohydrate diet and 21 persons on the conventional diet ( total , 39 persons at a mean [ SD ] of 13.5 3.2 months ) . Thus , we had 6-month weights on 118 of 132 persons ( 89 % ) and 1-year weights on 126 of 132 persons ( 96 % ) . Of the 18 persons who missed the 6-month visit but returned for the 1-year visit ( 6 in the low-carbohydrate group and 12 in the conventional diet group ) , all but 2 had 6-month weights retrieved from medical records . Of the 6 persons for whom no 1-year weights were available , 2 were in the low-carbohydrate group and 4 in the conventional diet group . The weights retrieved from medical records were obtained on scales that were different from those used for the study and were probably obtained in a nonuniform manner with regard to clothing . We used several approaches to h and le the 45 participants with missing data for diet recall and metabolic measurements . For the primary analysis by r and om-coefficient analysis , we assumed data were missing at r and om . To verify this assumption , we performed sensitivity analyses based on comparisons of baseline characteristics and weight loss differences between those who dropped out and those who completed the study . We also performed 2 additional sensitivity Two studies were conducted to investigate the effects of red pepper ( capsaicin ) on feeding behaviour and energy intake . In the first study , the effects of dietary red pepper added to high-fat ( HF ) and high-carbohydrate ( HC ) meals on subsequent energy and macronutrient intakes were examined in thirteen Japanese female subjects . After the ingestion of a st and ardized dinner on the previous evening , the subjects ate an experimental breakfast ( 1883 kJ ) of one of the following four types : ( 1 ) HF ; ( 2 ) HF and red pepper ( 10 g ) ; ( 3 ) HC ; ( 4 ) HC and red pepper .  Ad libitum energy and macronutrient intakes were measured at lunch-time . The HC breakfast significantly reduced the desire to eat and hunger after breakfast . The addition of red pepper to the HC breakfast also significantly decreased the desire to eat and hunger before lunch . Differences in diet composition at breakfast time did not affect energy and macronutrient intakes at lunch-time . However , the addition of red pepper to the breakfast significantly decreased protein and fat intakes at lunch-time . In Study 2 , the effects of a red-pepper appetizer on subsequent energy and macronutrient intakes were examined in ten Caucasian male subjects . After ingesting a st and ardized breakfast , the subjects took an experimental appetizer ( 644 kJ ) at lunch-time of one of the following two types : ( 1 ) mixed diet and appetizer ; ( 2 ) mixed diet and red-pepper ( 6 g ) appetizer . The addition of red pepper to the appetizer significantly reduced the cumulative ad libitum energy and carbohydrate intakes during the rest of the lunch and in the snack served several hours later . Moreover , the power spectral analysis of heart rate revealed that this effect of red pepper was associated with an increase in the ratio sympathetic : parasympathetic nervous system activity . These results indicate that the ingestion of red pepper decreases appetite and subsequent protein and fat intakes in Japanese females and energy intake in Caucasian males . Moreover , this effect might be related to an increase in sympathetic nervous system activity in Caucasian males BACKGROUND Capsinoids-nonpungent capsaicin analogs-are known to activate brown adipose tissue ( BAT ) thermogenesis and whole-body energy expenditure ( EE ) in small rodents . BAT activity can be assessed by [¹⁸F]fluorodeoxyglucose-positron emission tomography ( FDG-PET ) in humans . OBJECTIVES The aims of the current study were to examine the acute effects of capsinoid ingestion on EE and to analyze its relation to BAT activity in humans . DESIGN Eighteen healthy men aged 20 - 32 y underwent FDG-PET after 2 h of cold exposure ( 19 ° C ) while wearing light clothing .  Whole-body EE and skin temperature , after oral ingestion of capsinoids ( 9 mg ) , were measured for 2 h under warm conditions ( 27 ° C ) in a single-blind , r and omized , placebo-controlled , crossover design . RESULTS When exposed to cold , 1 
    Output:
    
Study findings suggest a minimum dose of 2 mg of capsaicinoids is needed to contribute to reductions in ad libitum energy intake , which appears to be attributed to an altered preference for carbohydrate-rich foods over foods with a higher fat content .
Meta-anlysis findings suggest that daily consumption of capsaicinoids may contribute to weight management through reductions in energy intake .
Subsequently , there may be potential for capsaicinoids to be used as long-term , natural weight-loss aids .