The purpose of this study was to determine the effects of dietary protein intake and eating frequency on perceived appetite, satiety, and hormonal responses in overweight/obese men. Thirteen men (age 51 ± 4 years; BMI 31.3 ± 0.8 kg/m2) consumed eucaloric diets containing normal protein (79 ± 2 g protein/day; 14% of energy intake as protein) or higher protein (138 ± 3 g protein/day; 25% of energy intake as protein) equally divided among three eating occasions (3-EO; every 4 h) or six eating occasions (6-EO; every 2 h) on four separate days in randomized order. Hunger, fullness, plasma glucose, and hormonal responses were assessed throughout 11 h. No protein × eating frequency interactions were observed for any of the outcomes. Independent of eating frequency, higher protein led to greater daily fullness (P < 0.05) and peptide YY (PYY) concentrations (P < 0.05). In contrast, higher protein led to greater daily ghrelin concentrations (P < 0.05) vs. normal protein. Protein quantity did not influence daily hunger, glucose, or insulin concentrations. Independent of dietary protein, 6-EO led to lower daily fullness (P < 0.05) and PYY concentrations (P < 0.05). The 6-EO also led to lower glucose (P < 0.05) and insulin concentrations (P < 0.05) vs. 3-EO. Although the hunger-related perceived sensations and hormonal responses were conflicting, the fullness-related responses were consistently greater with higher protein intake but lower with increased eating frequency. Collectively, these data suggest that higher protein intake promotes satiety and challenge the concept that increasing the number of eating occasions enhances satiety in overweight and obese men.

Objective: This study assessed the effectiveness of a prescribed weight-loss diet with 0.8 versus 1.4 g proteinÁkg À1 day À1 on changes in weight, body composition, indices of metabolic syndrome, and resting energy expenditure (REE) in overweight and obese men. Design and Methods: Men were randomized to groups that consumed diets containing 750 kcal day À1 less than daily energy needs for weight maintenance with either normal protein (NP, n ¼ 21) or higher protein (HP, n ¼ 22) content for 12 weeks. The macronutrient distributions of the NP and HP diets were 25:60:15, and 25:50:25 percent energy from fat, carbohydrate, and protein, respectively. Assessments were made pre and post intervention. The subjects were retrospectively subgrouped into overweight and obese groups. Results and Conclusion: Both diet groups lost comparable body weight and fat. The HP group lost less lean body mass than the NP group (À1.9 6 0.3 vs. À3.0 6 0.4 kg). The effects of protein and BMI status on lean body mass loss were additive. The reductions in total cholesterol, HDL-C, triacylglycerol, glucose, and insulin, along with LDL-C, total cholesterol-to-HDL-C ratio, and HOMA-IR, were not statistically different between NP and HP. Likewise, macronutrient distributions of the diet did not affect the reductions in REE, and blood pressure. In conclusion, energy restriction effectively improves multiple clinical indicators of cardiovascular health and glucose control, and consumption of a higher-protein diet and accomplishing weight loss when overweight versus obese help men preserve lean body mass over a short period of time.

BackgroundThe cultivated peanut (Arachis hypogaea L.) is an important oil and food crop in the world. Pod- and kernel-related traits are direct factors involved in determining the yield of the peanut. However, the genetic basis underlying pod- and kernel-related traits in the peanut remained largely unknown, which hampered the improvement of peanut through marker-assisted selection. To understand the genetic basis underlying pod- and kernel-related traits in the peanut and provide more useful information for marker-assisted breeding, we conducted quantitative trait locus (QTL) analysis for pod length and width and seed length and width by use of two F2:3 populations derived from cultivar Fuchuan Dahuasheng × ICG 6375 (FI population) and cultivar Xuhua 13 × cultivar Zhonghua 6 (XZ population) in this study.ResultsTwo genetic maps containing 347 and 228 polymorphic markers were constructed for FI and XZ populations respectively. In total, 39 QTLs explaining 1.25–26.11 % of the phenotypic variations were detected in two populations. For the FI population, 26 QTLs were detected between the two environments, among which twelve were not mapped before. For the XZ population, thirteen QTLs were detected, among which eight were not reported before. One QTL for pod width was repeatedly mapped between the two populations.ConclusionThe QTL analyses for pod length and width and seed length and width were conducted in this study using two mapping populations. Novel QTLs were identified, which included two for pod length, four for pod width, five for seed length and one for seed width in the FI population, and three for pod length, three for pod width and two for seed width in the XZ population. Our results will be helpful for improving pod- and seed-related traits in peanuts through marker-assisted selection.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0337-x) contains supplementary material, which is available to authorized users.

BackgroundProtein intake from cow milk–based infant formula has been associated with rapid weight gain and increased adiposity, but the effect of protein from complementary foods has not been prospectively evaluated, and the effect of protein from sources other than formula during complementary feeding is not clear.ObjectiveThe aim of this study was to directly compare the effect of protein from 2 common complementary food sources, meat and dairy, on infant growth and weight trajectory.DesignHealthy term, formula-fed infants were recruited from the metro Denver area, matched by sex and race/ethnicity and randomly assigned to a meat or a dairy complementary food group from 5 to 12 mo of age. Total protein intake during this 7-mo intervention was ∼3 g ⋅ kg−1 ⋅ d−1 for both groups. Intakes of infant formula, cereal, fruit, and vegetables were ad libitum. Caregivers also completed 3-d diet records at 5, 10, and 12 mo of age. Anthropometric measures were obtained during monthly home visits, and blood samples were collected at 5 and 12 mo of age.ResultsSixty-four infants completed the intervention (meat: n = 32; dairy: n = 32). The average total protein intake (mean ± SD) increased from 2.01 ± 0.06 g ⋅ kg−1 ⋅ d−1 at 5 mo to 3.35 ±0.12 g ⋅ kg−1 ⋅ d−1 at 12 mo and did not differ between groups. Over time, weight and weight-for-age z score increased by 0.48 ± 0.07. However, there was a significant group-by-time interaction for both length-for-age z score (LAZ) and weight-for-length z score (WLZ). Post hoc analysis showed that LAZ increased in the meat group (+0.33 ± 0.09; P = 0.001 over time) and decreased in the dairy group (−0.30 ± 0.10; P = 0.0002 over time); WLZ significantly increased in the dairy group (0.76 ± 0.21; P = 0.000002 over time) compared with the meat group (0.30 ± 0.17; P = 0.55 over time). Insulin-like growth factor I and insulin-like growth factor-binding protein 3 both increased over time without group differences.ConclusionsProtein source may have an important role in regulating growth. In these formula-fed older infants, meat- and dairy-based complementary foods led to distinct growth patterns, especially for length. This trial was registered at www.clinicaltrials.gov as NCT02142647.

Notwithstanding uncertainty about the validity of the use of the IAAO technique to assess protein requirements, the results of this study with octogenarian women suggest that the current EAR and RDA for elderly women may be underestimated. The limitations of this short-term, noninvasive method underscore the need for new research that uses alternative experimental designs and measuring physiologic, morphologic, and health-related outcomes.