Dietary protein - its role in satiety, energetics, weight loss and health

Obesity is a serious health problem because of its co-morbidities. The solution, implying weight loss and long-term weight maintenance, is conditional on: (i) sustained satiety despite negative energy balance, (ii) sustained basal energy expenditure despite BW loss due to (iii) a sparing of fat-free mass (FFM), being the main determinant of basal energy expenditure. Dietary protein has been shown to assist with meeting these conditions, since amino acids act on the relevant metabolic targets. This review deals with the effects of different protein diets during BW loss and BW maintenance thereafter. Potential risks of a high protein diet are dealt with. The required daily intake is 0.8-1.2 g/kg BW, implying sustaining the original absolute protein intake and carbohydrate and fat restriction during an energy-restricted diet. The intake of 1.2 g/kg BW is beneficial to body composition and improves blood pressure. A too low absolute protein content of the diet contributes to the risk of BW regain. The success of the so-called 'low carb' diet that is usually high in protein can be attributed to the relatively high-protein content per se and not to the relatively lower carbohydrate content. Metabolic syndrome parameters restore, mainly due to BW loss. With the indicated dosage, no kidney problems have been shown in healthy individuals. In conclusion, dietary protein contributes to the treatment of obesity and the metabolic syndrome, by acting on the relevant metabolic targets of satiety and energy expenditure in negative energy balance, thereby preventing a weight cycling effect

Generalized pricing formulas for stochastic volatility jump diffusion models applied to the exponential Vasicek model

Path integral techniques for the pricing of financial options are mostly based on models that can be recast in terms of a Fokker-Planck differential equation and that, consequently, neglect jumps and only describe drift and diffusion. We present a method to adapt formulas for both the path-integral propagators and the option prices themselves, so that jump processes are taken into account in conjunction with the usual drift and diffusion terms. In particular, we focus on stochastic volatility models, such as the exponential Vasicek model, and extend the pricing formulas and propagator of this model to incorporate jump diffusion with a given jump size distribution. This model is of importance to include non-Gaussian fluctuations beyond the Black-Scholes model, and moreover yields a lognormal distribution of the volatilities, in agreement with results from superstatistical analysis. The results obtained in the present formalism are checked with Monte Carlo simulations.Comment: 9 pages, 2 figures, 1 tabl

Low energy excitations and dynamic Dzyaloshinskii-Moriya interaction in α′\alpha'-NaV2_2O5_5 studied by far infrared spectroscopy

We have studied far infrared transmission spectra of alpha'-NaV2O5 between 3 and 200cm-1 in polarizations of incident light parallel to a, b, and c crystallographic axes in magnetic fields up to 33T. The triplet origin of an excitation at 65.4cm-1 is revealed by splitting in the magnetic field. The magnitude of the spin gap at low temperatures is found to be magnetic field independent at least up to 33T. All other infrared-active transitions appearing below Tc are ascribed to zone-folded phonons. Two different dynamic Dzyaloshinskii-Moriya (DM) mechanisms have been discovered that contribute to the oscillator strength of the otherwise forbidden singlet to triplet transition. 1. The strongest singlet to triplet transition is an electric dipole transition where the polarization of the incident light's electric field is parallel to the ladder rungs, and is allowed by the dynamic DM interaction created by a high frequency optical a-axis phonon. 2. In the incident light polarization perpendicular to the ladder planes an enhancement of the singlet to triplet transition is observed when the applied magnetic field shifts the singlet to triplet resonance frequency to match the 68cm-1 c-axis phonon energy. The origin of this mechanism is the dynamic DM interaction created by the 68cm-1 c-axis optical phonon. The strength of the dynamic DM is calculated for both mechanisms using the presented theory.Comment: 21 pages, 22 figures. Version 2 with replaced fig. 18 were labels had been los

Changes in gut hormone and glucose concentrations in relation to hunger and fullness

Background: The search for biomarkers of appetite is very active. Objectives: The aims were to compare dynamics of hunger and fullness ratings on a visual analog scale (VAS) with dynamics of glucagon-like peptide 1, peptide tyrosine-tyrosine, ghrelin, glucose, and insulin concentrations throughout different meal patterns-and thus different timings of nutrient delivery to the gut-by using a statistical approach that focuses on within-subject relations of these observations and to investigate whether appetite ratings are synchronized with or lag behind or in front of changes in hormone and glucose concentrations. Design: Subjects (n = 38) with a mean (+/- SD) age of 24 +/- 6 y and BMI (in kg/m(2)) of 25.1 +/- 3.1 came to the university twice for consumption of a 4-course lunch in 0.5 or 2 h (randomized crossover design). Per subject regression slopes and R(2) values of VAS scores on hormone and glucose concentrations were calculated. We tested whether the means of the slopes were different from zero. Regarding possible lags in the relations, the analyses were repeated with VAS scores related to hormone and glucose concentrations of the relevant previous and following measurement periods. Results: VAS scores and hormone and glucose concentrations changed synchronously (P <0.005, R(2) = 0.4-0.7). Changes in ghrelin concentrations lagged behind (10-30 min) changes in hunger scores (P <0.005, R(2) = 0.7) and insulin concentrations (P <0.005, R(2) = 0.6), which suggests a role for insulin as a possible negative regulator of ghrelin. No major differences in slopes and R 2 values were found between the meal patterns. Conclusions: This method may be useful for understanding possible differences in relations between VAS scores and hormone and glucose concentrations between subjects or conditions. Yet, the reported explained variation of 40% to 70% seems to be too small to use hormone and glucose concentrations as appropriate biomarkers for appetite, at least at the individual level and probably at the group level. This study started in 2007, which means that it was not registered as a clinical trial. Am J Clin Nutr 2011;94:717-25

Sex differences in HPA axis activity in response to a meal

BACKGROUND: Sex may influence the relationship between HPA axis functioning and obesity. This has been suggested to be due to sex-specific differences in body composition, body fat distribution and psychological variables. Age and the use of oral contraceptives may also influence the relationship between HPA axis functioning and obesity. OBJECTIVE: To systematically investigate whether body composition, body fat distribution, psychological variables, age, or possibly oral contraceptive use contribute to sex differences in HPA axis activity in response to a meal. METHODS: Subjects were men (n=19) and women (n=19) between 18 and 51years old with BMI between 20.3 and 33.2kg/m(2). HPA axis activity was measured by salivary free cortisol levels before consuming a meal, and at 45, 75 and 125min postprandial on four repeated test days. Anthropometric and body composition measurements were performed. Questionnaires were used to assess cognitive eating behavior and trait anxiety level. RESULTS: No differences between the test days in postprandial cortisol responses appeared. Responses were significantly higher in men compared with women (p<.05). No significant correlations were found between cortisol concentrations and sex-specific body composition or body fat distribution. Psychological variables did not contribute to differences in cortisol responses after a meal between men and women. In women, baseline cortisol concentrations correlated inversely with age (p=.024). CONCLUSION: Higher HPA axis activity following a meal in men vs. women remained irrespective of sex-specific differences in body composition, body fat distribution, psychological variables, or in age. In women baseline cortisol concentrations were age-dependent

A solid high-protein meal evokes stronger hunger suppression than a liquefied high-protein meal.

Hunger is a potential problem for compliance with an energy-restricted diet. Relatively high-protein meal-replacement products have been shown to diminish this problem; they are available as liquid and solid meals, yet their physical state can affect hunger suppression. The objective was to investigate the differences in appetite profile and physiological parameters after consumption of a single-macronutrient, subject-specific, high-protein meal in liquefied vs. solid form, controlled for energy density, weight, and volume. Ten male subjects (age: 21.1 +/- 3.9 years; BMI: 22.4 +/- 1.2 kg/m(2)) were offered lunch subject-specifically as 15% of daily energy requirement (DER), consisting of solid (steamed chicken breast + 750 ml water) or liquefied protein (steamed chicken breast blended in 500 ml water + 250 ml water). Appetite profiles, insulin, glucose, and ghrelin were measured over 3 h. Comparing the solid vs. liquefied condition, oral exposure time did not differ between conditions (19.2 +/- 0.4 and 18.8 +/- 0.6 min, respectively; P = 0.13). Area under the curve (AUC) effects were observed for thirst; statistically significant condition x time interactions and statistically significant differences at several time points were observed for desire to eat (condition x time P < 0.05; 31 +/- 6 mm vs. 53 +/- 8 mm; P < 0.04 at 115 min) and thirst (condition x time P < 0.01; 27 +/- 8 mm vs. 41 +/- 8 mm; P < 0.05 at 30 min and 23 +/- 6 mm vs. 41 +/- 8 mm; P < 0.02 at 70 min) to be lower, while hunger suppression (79 +/- 3 mm and 52 +/- 10 mm; P < 0.03 at 20 min and 61 +/- 7 mm and 44 +/- 8 mm; P < 0.03 at 115 min) was higher in the solid condition. Glucose, insulin, and ghrelin concentration curves were similar for both conditions. In conclusion, solid protein evokes a stronger suppression of hunger and desire to eat than liquefied protein

Satiating Capacity and Post-Prandial Relationships between Appetite Parameters and Gut-Peptide Concentrations with Solid and Liquefied Carbohydrate

BACKGROUND: Differences in satiating capacity of liquid and solid meals are unclear. OBJECTIVE: Investigating appetite parameters, physiological measurements and within-subject relationships after consumption of a single macronutrient, subject-specific carbohydrate meal in liquefied versus solid form, controlled for energy density, weight and volume. DESIGN: In a cross-over design, ten male subjects (age = 21.1+/-3.9 y, BMI = 22.4+/-1.2 kg/m(2)) consumed a solid (CS, whole peaches +750 ml water) and liquefied carbohydrate (CL, peach blended in 500 ml water +250 ml water) lunch. Appetite profiles, insulin-, glucose- and ghrelin concentrations were measured over three hours. Post-prandial relationships between appetite and blood parameters were calculated using subject-specific regression analyses. RESULTS: Fullness ratings were higher in the CL (85+/-5 mm) compared to the CS condition (73+/-8 mm) at 20 min (p<0.03). Glucose concentrations peaked 20 to 30 min after the start of the lunch in the CL condition, and 30 to 40 min after start of the CS condition. Correspondingly, insulin concentrations were peaked at 20-30 min in the CL condition, and at 30-40 min in the CS condition. AUC or condition x time interactions were not different comparing the CL and the CS condition. Insulin was significantly higher in the CS compared to the CL condition 40 min after the start of the lunch (p<0.05). Fullness scores were significantly related to insulin concentrations but not to glucose concentrations; desire to eat scores were significantly associated with ghrelin concentrations in both, the CL and the CS condition. The relationship between fullness scores and glucose concentrations was not statistically significant. CONCLUSION: Liquefied and solid carbohydrate meals do not differ in satiating capacity, supported by appetite profile and relevant blood parameters. Postprandially, fullness and desire to eat were associated with respectively insulin and ghrelin concentrations

Influence of Consumption of a High-Protein vs. High-Carbohydrate Meal on the Physiological Cortisol and Psychological Mood Response in Men and Women

Consumption of meals with different macronutrient contents, especially high in carbohydrates, may influence the stress-induced physiological and psychological response. The objective of this study was to investigate effects of consumption of a high-protein vs. high-carbohydrate meal on the physiological cortisol response and psychological mood response. Subjects (n = 38, 19m/19f, age = 25+/-9 yrs, BMI = 25.0+/-3.3 kg/m(2)) came to the university four times, fasted, for either condition: rest-protein, stress-protein, rest-carbohydrate, stress-carbohydrate (randomized cross-over design). Stress was induced by means of a psychological computer-test. The test-meal was either a high-protein meal (En% P/C/F 65/5/30) or a high-carbohydrate meal (En% P/C/F 6/64/30), both meals were matched for energy density (4 kJ/g) and daily energy requirements (30%). Per test-session salivary cortisol levels, appetite profile, mood state and level of anxiety were measured. High hunger, low satiety (81+/-16, 12+/-15 mmVAS) confirmed the fasted state. The stress condition was confirmed by increased feelings of depression, tension, anger, anxiety (AUC stress vs. rest p0.1). Consumption of the test-meals increased cortisol levels in men in all conditions (p<0.01), and in women in the rest-protein and stress-protein condition (p<0.03). Men showed higher cortisol levels than women (AUC nmol.min/L p<0.0001). Consumption of meals with different macronutrient contents, i.e. high-protein vs. high-carbohydrate, does not influence the physiological and psychological response differentially. Men show a higher meal-induced salivary cortisol response compared with women

Protein v. carbohydrate intake differentially affects liking- and wanting-related brain signalling

Extreme macronutrient intakes possibly lead to different brain signalling. The aim of the present study was to determine the effects of ingesting high-protein v. high-carbohydrate food on liking and wanting task-related brain signalling (TRS) and subsequent macronutrient intake. A total of thirty female subjects (21.6 (sd 2.2) years, BMI 25.0 (sd 3.7) kg/m2) completed four functional MRI scans: two fasted and two satiated on two different days. During the scans, subjects rated all food items for liking and wanting, thereby choosing the subsequent meal. The results show that high-protein (PROT) v. high-carbohydrate (CARB) conditions were generated using protein or carbohydrate drinks at the first meal. Energy intake and hunger were recorded. PROT (protein: 53.7 (sd 2.1) percentage of energy (En%); carbohydrate: 6.4 (sd 1.3) En%) and CARB conditions (protein: 11.8 (sd 0.6) En%; carbohydrate: 70.0 (sd 2.4) En%) were achieved during the first meal, while the second meals were not different between the conditions. Hunger, energy intake, and behavioural liking and wanting ratings were decreased after the first meal (P < 0.001). Comparing the first with the second meal, the macronutrient content changed: carbohydrate - 26.9 En% in the CARB condition, protein - 37.8 En% in the PROT condition. After the first meal in the CARB condition, wanting TRS was increased in the hypothalamus. After the first meal in the PROT condition, liking TRS was decreased in the putamen (P < 0.05). The change in energy intake from the first to the second meal was inversely related to the change in liking TRS in the striatum and hypothalamus in the CARB condition and positively related in the PROT condition (P < 0.05). In conclusion, wanting and liking TRS were affected differentially with a change in carbohydrate or protein intake, underscoring subsequent energy intake and shift in macronutrient composition