Efficient Bayesian automatic calibration of a functional-structural wheat model using an adaptive design and a metamodelling approach.

Functional-structural plant models are increasingly being used by plant scientists to address a wide variety of questions. However, the calibration of these complex models is often challenging, mainly because of their high computational cost, and, as a result, error propagation is usually ignored. Here we applied an automatic method to the calibration of WALTer: a functional-structural wheat model that simulates the plasticity of tillering in response to competition for light. We used a Bayesian calibration method to jointly estimate the values of five parameters and quantify their uncertainty by fitting the model outputs to tillering dynamics data. We made recourse to Gaussian process metamodels in order to alleviate the computational cost of WALTer. These metamodels are built from an adaptive design that consists of successive runs of WALTer chosen by an efficient global optimization algorithm specifically adapted to this particular calibration task. The method presented here performed well on both synthetic and experimental data. It is an efficient approach for the calibration of WALTer and should be of interest for the calibration of other functional-structural plant models.

Pipecolate and Taurine are Rat Urinary Biomarkers for Lysine and Threonine Deficiencies.

BACKGROUND: The consumption of poor-quality protein increases the risk of essential amino acid (EAA) deficiency, particularly for lysine and threonine. Thus, it is necessary to be able to detect easily EAA deficiency. OBJECTIVES: The purpose of this study was to develop metabolomic approaches to identify specific biomarkers for an EAA deficiency, such as lysine and threonine. METHODS: Three experiments were performed on growing rats. In experiment 1, rats were fed for 3 weeks with lysine (L30), or threonine (T53)-deficient gluten diets, or nondeficient gluten diet (LT100) in comparison with the control diet (milk protein, PLT). In experiments 2a and 2b, rats were fed at different concentrations of lysine (L) or threonine (T) deficiency: L/T15, L/T25, L/T40, L/T60, L/T75, P20, L/T100 and L/T170. Twenty-four-hour urine and blood samples from portal vein and vena cava were analyzed using LC-MS. Data from experiment 1 were analyzed by untargeted metabolomic and Independent Component - Discriminant Analysis (ICDA) and data from experiments 2a and 2b by targeted metabolomic and a quantitative Partial Least- Squares (PLS) regression model. Each metabolite identified as significant by PLS or ICDA was then tested by 1-way ANOVA to evaluate the diet effect. A two-phase linear regression analysis was used to determine lysine and threonine requirements. RESULTS: ICDA and PLS found molecules that discriminated between the different diets. A common metabolite, the pipecolate, was identified in experiments 1 and 2a, confirming that it could be specific to lysine deficiency. Another metabolite, taurine, was found in experiments 1 and 2b, so probably specific to threonine deficiency. Pipecolate or taurine breakpoints obtained give a value closed to the values obtained by growth indicators. CONCLUSIONS: Our results showed that the EAA deficiencies influenced the metabolome. Specific urinary biomarkers identified could be easily applied to detect EAA deficiency and to determine which AA is deficient.

Functional-Structural Plant Modeling Highlights How Diversity in Leaf Dimensions and Tillering Capability Could Promote the Efficiency of Wheat Cultivar Mixtures.

Increasing the cultivated diversity has been identified as a major leverage for the agroecological transition as it can help improve the resilience of low input cropping systems. For wheat, which is the most cultivated crop worldwide in terms of harvested area, the use of cultivar mixtures is spreading in several countries, but studies have seldom focused on establishing mixing rules based on plant architecture. Yet, the aerial architecture of plants and the overall canopy structure are critical for field performance as they greatly influence light interception, plant interactions and yield. The very high number of trait combinations in wheat mixtures makes it difficult to conduct experimentations on this issue, which is why a modeling approach appears to be an appropriate solution. In this study, we used WALTer, a functional structural plant model (FSPM), to simulate wheat cultivar mixtures and try to better understand how differences between cultivars in key traits of the aerial architecture influence mixture performance. We simulated balanced binary mixtures of cultivars differing for different critical plant traits: final height, leaf dimensions, leaf insertion angle and tillering capability. Our study highlights the impact of the leaf dimensions and the tillering capability on the performance of the simulated mixtures, which suggests that traits impacting the plants' leaf area index (LAI) have more influence on the performance of the stand than traits impacting the arrangement of the leaves. Our results show that the performance of mixtures is very variable depending on the values of the explored architectural traits. In particular, the best performances were achieved by mixing cultivars with different leaf dimensions and different tillering capability, which is in agreement with numerous studies linking the diversity of functional traits in plant communities to their productivity. However, some of the worst performances were also achieved by mixing varieties differing in their aerial architecture, which suggests that diversity is not a sufficient criterion to design efficient mixtures. Overall, these results highlight the importance of simulation-based explorations for establishing assembly rules to design efficient mixtures.

Perinatal exposure of rats to a maternal diet with varying protein quantity and quality affects the risk of overweight in female adult offspring.

The maternal protein diet during the perinatal period can program the health of adult offspring. This study in rats evaluated the effects of protein quantity and quality in the maternal diet during gestation and lactation on weight and adiposity in female offspring. Six groups of dams were fed a high-protein (HP; 47% protein) or normal-protein (NP; 19% protein) isocaloric diet during gestation (G) using either cow's milk (M), pea (P) or turkey (T) proteins. During lactation, all dams received the NP diet (protein source unchanged). From postnatal day (PND) 28 until PND70, female pups (n=8) from the dam milk groups were exposed to either an NP milk diet (NPMW) or to dietary self-selection (DSS). All other pups were only exposed to DSS. The DSS design was a choice between five food cups containing HPM, HPP, HPT, carbohydrates or lipids. The weights and food intakes of the animals were recorded throughout the study, and samples from offspring were collected on PND70. During the lactation and postweaning periods, body weight was lower in the pea and turkey groups (NPG and HPG) versus the milk group (P<.0001). DSS groups increased their total energy and fat intakes compared to the NPMW group (P<.0001). In all HPG groups, total adipose tissue was increased (P=.03) associated with higher fasting plasma leptin (P<.05). These results suggest that the maternal protein source impacted offspring body weight and that protein excess during gestation, irrespective of its source, increased the risk of adiposity development in female adult offspring.

Increased Susceptibility to Obesity and Glucose Intolerance in Adult Female Rats Programmed by High-Protein Diet during Gestation, But Not during Lactation.

Fetal and early postnatal nutritional environments contribute to lifelong health. High-protein (HP) intake in early life can increase obesity risk in response to specific feeding conditions after weaning. This study investigated the effects of a maternal HP diet during pregnancy and/or lactation on the metabolic health of offspring. Three groups of dams received a normal-protein (NP, 20E% proteins) diet during gestation and lactation (Control group), an HP diet (55E% proteins) during gestation (HPgest group), or an HP diet during lactation (HPlact group). From weaning until 10 weeks, female pups were exposed to the NP, the HP or the western (W) diet. HPgest pups had more adipocytes (p = 0.009), more subcutaneous adipose tissue (p = 0.04) and increased expression of genes involved in liver fatty acid synthesis at 10 weeks (p < 0.05). HPgest rats also showed higher food intake and adiposity under the W diet compared to the Control and HPlact rats (p ≤ 0.04). The post-weaning HP diet reduced weight (p < 0.0001), food intake (p < 0.0001), adiposity (p < 0.0001) and glucose tolerance (p < 0.0001) compared to the NP and W diets; this effect was enhanced in the HPgest group (p = 0.04). These results show that a maternal HP diet during gestation, but not lactation, leads to a higher susceptibility to obesity and glucose intolerance in female offspring.

Patterns of amino acid intake are strongly associated with cardiovascular mortality, independently of the sources of protein.

BACKGROUND: The intake of specific amino acids (AA) has been associated with cardiovascular health, but amino acids are consumed together as dietary protein. Here we investigated the association between identified patterns of amino acid intake and cardiovascular mortality. METHODS: A total of 2216 cardiovascular deaths among 79 838 men and women from the Adventist Health Study-2 were included in our analysis. Baseline dietary patterns based on the participants' amino acids intakes were derived by factor analysis. Using Cox regression analyses, we estimated multivariate-adjusted hazard ratios (HRs) adjusted for sociodemographic and lifestyle factors and other dietary components. RESULTS: Three patterns of amino acids were identified. Factor 1 was positively associated with cardiovascular disease (CVD) mortality [hazard ratio (HR)Q5-Q1: 1.62, 98.75% confidence interval (CI): 1.15, 2.28; P-trend <0.001]; and Factors 2 and 3 were inversely associated with CVD mortality (HR Q5-Q1 Factor 2: 0.74, 98.75% CI: 0.53, 1.04; P-trend <0.01 and HR Q5-Q1 Factor 3: 0.65, 98.75% CI: 0.44, 0.95; P-trend <0.05]. The associations with Factor 1 (with high loadings on indispensable amino acids such as branched chain amino acids, lysine, methionine) and Factor 3 (with high loadings on non-indispensable amino acids, namely arginine, glycine, aspartate+asparagine) remained significant after further adjustment for nutrient intake and for the five protein source patterns identified previously (HR Q5-Q1: 1.56 (0.99, 2.45) and 0.55 (0.35, 0.85); P-trends < 0.01). CONCLUSIONS: Indispensable AA have a positive and some non-indispensable AA have a negative, independent, strong association with the risk of cardiovascular mortality.

Maternal High-Protein Diet during Pregnancy Modifies Rat Offspring Body Weight and Insulin Signalling but Not Macronutrient Preference in Adulthood.

Diet of mothers during gestation may impact offspring phenotype. This study evaluated the consequences of a maternal High-Protein (HP) diet during gestation on food preferences and phenotypic characteristics in adult rat offspring. Dams were fed a HP or a Normal-Protein (NP) isocaloric diet during gestation only. Weaned female pups were divided into 3 diet groups: NP control or one of two dietary self-selection (DSS) conditions. In DSS1, offspring had a free choice between proteins (100%) or a mix of carbohydrates (88%) and lipids (12%). In DSS2, the choice was between proteins (100%), carbohydrate (100%) or lipids (100%). DSS2 groups consumed more of their energy from protein and lipids, with a decreased carbohydrate intake (p < 0.0001) compared to NP groups, regardless of the maternal diet. Offspring from HP gestation dams fed the DSS2 diet (HPDSS2) had a 41.2% increase of total adiposity compared to NPDSS2 (p < 0.03). Liver Insulin receptor and Insulin substrate receptor 1 expression was decreased in offspring from HP compared to NP gestation dams. These results showed the specific effects of DSS and maternal diet and data suggested that adult, female offspring exposed to a maternal HP diet during foetal life were more prone to adiposity development, in response to postweaning food conditions.

WALTer: a three-dimensional wheat model to study competition for light through the prediction of tillering dynamics.

BACKGROUND AND AIMS: Branching is a main morphogenetic process involved in the adaptation of plants to the environment. In grasses, tillering is divided into three phases: tiller emergence, cessation of tillering and tiller regression. Understanding and prediction of the tillering process is a major challenge to better control cereal yields. In this paper, we present and evaluate WALTer, an individual-based model of wheat built on simple self-adaptive rules for predicting the tillering dynamics at contrasting sowing densities. METHODS: WALTer simulates the three-dimensional (3-D) development of the aerial architecture of winter wheat. Tillering was modelled using two main hypotheses: (H1) a plant ceases to initiate new tillers when a critical Green Area Index (GAIc) is reached, and (H2) the regression of a tiller occurs if its interception of light is below a threshold (PARt). The development of vegetative organs follows descriptive rules adapted from the literature. A sensitivity analysis was performed to evaluate the impact of each parameter on tillering and GAI dynamics. WALTer was parameterized and evaluated using an initial dataset providing an extensive description of GAI dynamics, and another dataset describing tillering dynamics under a wide range of sowing densities. KEY RESULTS: Sensitivity analysis indicated the predominant importance of GAIc and PARt. Tillering and GAI dynamics of expt 1 were well fit by WALTer. Once calibrated based on the agronomic density of expt 2, tillering parameters allowed an adequate prediction of tillering dynamics at contrasting sowing densities. CONCLUSIONS: Using simple rules and a small number of parameters, WALTer efficiently simulated the wheat tillering dynamics observed at contrasting densities in experimental data. These results show that the definition of a critical GAI and a threshold of PAR is a relevant way to represent, respectively, cessation of tillering and tiller regression under competition for light.

Patterns of plant and animal protein intake are strongly associated with cardiovascular mortality: the Adventist Health Study-2 cohort.

Background: Current evidence suggests that plant and animal proteins are intimately associated with specific large nutrient clusters that may explain part of their complex relation with cardiovascular health. We aimed at evaluating the association between specific patterns of protein intake with cardiovascular mortality. Methods: We selected 81 337 men and women from the Adventist Health Study-2. Diet was assessed between 2002 and 2007, by using a validated food frequency questionnaire. Dietary patterns based on the participants' protein consumption were derived by factor analysis. Cox regression analysis was used to estimate multivariate-adjusted hazard ratios (HRs) adjusted for sociodemographic and lifestyle factors and dietary components. Results: There were 2276 cardiovascular deaths during a mean follow-up time of 9.4 years. The HRs for cardiovascular mortality were 1.61 [98.75% confidence interval (CI), 1.12 2.32; P-trend < 0.001] for the 'Meat' protein factor and 0.60 (98.75% CI, 0.42 0.86; P-trend < 0.001) for the 'Nuts & Seeds' protein factor (highest vs lowest quintile of factor scores). No significant associations were found for the 'Grains', 'Processed Foods' and 'Legumes, Fruits & Vegetables' protein factors. Additional adjustments for the participants' vegetarian dietary pattern and nutrients related to cardiovascular disease outcomes did not change the results. Conclusions: Associations between the 'Meat' and 'Nuts & Seeds' protein factors and cardiovascular outcomes were strong and could not be ascribed to other associated nutrients considered to be important for cardiovascular health. Healthy diets can be advocated based on protein sources, preferring low contributions of protein from meat and higher intakes of plant protein from nuts and seeds.

A clear trade-off exists between the theoretical efficiency and acceptability of dietary changes that improve nutrient adequacy during early pregnancy in French women: Combined data from simulated changes modeling and online assessment survey.

BACKGROUND: During pregnancy, the diet of a mother-to-be should be adapted to meet increases in nutrient requirements. We analyzed the theoretical efficiency and acceptability of different types of tailored dietary changes for pregnant women. METHODS: The nutrient adequacy of the diet was evaluated using the PANDiet score, by comparing the nutrient intakes of 344 non-pregnant premenopausal women (18-44y) with dietary reference intakes for the first trimester of pregnancy. Simulations were performed to evaluate the theoretical efficiency of three types of ten successive tailored dietary changes in improving nutrient adequacy, with graded difficulty in implementation. The acceptability (declared intention to use in the diet) of most efficient dietary changes was evaluated during an online randomized study including 115 French pregnant women (22-41y). RESULTS: Modifying the amount consumed of foods (type-1) did not modify the food repertoire and resulted in the smallest theoretical efficiency (increase in the PANDiet score of 9.8±0.2 points), but changes were the most acceptable (probability of the intention to use: 0.30-0.78). Conversely, replacing food items by items from the same group or eaten at the same time (type-3) broadened the food repertoire (3.6±1.3 food subgroups added) and resulted in the greatest theoretical efficiency (+23.9±0.3) but changes were the least acceptable (0.07-0.23). Replacing food items within the same subgroup (type-2) slightly broadened the food repertoire (+8.0±1.3 foods) and resulted in moderate theoretical efficiency (+14.8±0.2) and intermediate acceptability (0.11-0.35). CONCLUSION: A clear trade-off exists between the theoretical efficiency and acceptability of dietary changes, with a graded broadening of the food repertoire.

High-Protein Exposure during Gestation or Lactation or after Weaning Has a Period-Specific Signature on Rat Pup Weight, Adiposity, Food Intake, and Glucose Homeostasis up to 6 Weeks of Age.

BACKGROUND: Early-life nutrition has a programming effect on later metabolic health; however, the impact of exposure to a high-protein (HP) diet is still being investigated. OBJECTIVE: This study evaluated the consequences on pup phenotype of an HP diet during gestation and lactation and after weaning. METHODS: Wistar rat dams were separated into 2 groups fed an HP (55% protein) or normal protein (NP) (control; 20% protein) isocaloric diet during gestation, and each group subsequently was separated into 2 subgroups that were fed an HP or NP diet during lactation. After weaning, male and female pups from each mother subgroup were separated into 2 groups that were fed either an NP or HP diet until they were 6 wk old. Measurements included weight, food intake, body composition, blood glucose, insulin, glucagon, leptin, insulin-like growth factor I, and lipids. RESULTS: Feeding mothers the HP diet during gestation or lactation induced lower postweaning pup weight (gestation diet × time, P < 0.0001; lactation diet × time, P < 0.0001). Regardless of dams' diets, pups receiving HP compared with NP diet after weaning had 7% lower weight (NP, 135.0 ± 2.6 g; HP, 124.4 ± 2.5 g; P < 0.0001), 16% lower total energy intake (NP, 777 ± 14 kcal; HP, 649 ± 13 kcal; P < 0.0001) and 31% lower adiposity (P < 0.0001). Pups receiving HP compared with NP diet after weaning had increased blood glucose, insulin, and glucagon when food deprived (P < 0.0001 for all). The HP compared with the NP diet during gestation induced higher blood glucose in food-deprived rats (NP, 83.2 ± 2.1 mg/dL; HP, 91.2 ± 2.1 mg/dL; P = 0.046) and increased plasma insulin in fed pups receiving the postweaning NP diet (gestation diet × postweaning diet, P = 0.02). CONCLUSION: Increasing the protein concentration of the rat dams' diet during gestation, and to a lesser extent during lactation, and of the pups' diet after weaning influenced pup phenotype, including body weight, fat accumulation, food intake, and glucose tolerance at 6 wk of age.

The satiating effects of eggs or cottage cheese are similar in healthy subjects despite differences in postprandial kinetics.

Studies have reported a better satiating effect of eggs when compared with common cereal-based breakfasts, an effect that can be attributed to their macronutrient composition. Our aim was to compare the satiating power of an omelette and cottage cheese, both being common food snacks with similar nutrient compositions (containing proteins and lipids) but in different food forms. Thirty healthy volunteers participated in a randomized crossover trial. On each test day, the subjects consumed one of the two snacks, both providing 1346 kJ, 26 g protein, 21 g lipids, and 8 g lactose. The elapsed time between the snack and lunch request, their food intake at lunch, and their satiety scores were recorded. In a subgroup of 10 volunteers, blood was sampled to measure plasma metabolites and hormones. The two preloads were similar in terms of the time between the snack and a request for the buffet (167 ± 8 min), energy intake at the buffet (3988 ± 180 kJ) and appetite ratings. Plasma amino acid and urea concentrations indicated a marked delay in kinetic delivery after the eggs compared with the cottage cheese. In contrast, glucose, triglycerides and cholesterol displayed similar profiles after the snack. GIP and insulin secretions increased significantly after the cottage cheese, while glucagon and GLP-1 secretions were delayed with the omelette. We conclude that despite important differences in protein kinetics and their subsequent effects on hormone secretion, eggs and cottage cheese had a similar satiating power. This strongly suggests that with dose of proteins that is compatible to supplement strategies, i.e. 20-30 g, a modulation of protein kinetics is ineffective in increasing satiety.

Network impact on persistence in a finite population dynamic diffusion model: application to an emergent seed exchange network.

Dynamic extinction colonisation models (also called contact processes) are widely studied in epidemiology and in metapopulation theory. Contacts are usually assumed to be possible only through a network of connected patches. This network accounts for a spatial landscape or a social organization of interactions. Thanks to social network literature, heterogeneous networks of contacts can be considered. A major issue is to assess the influence of the network in the dynamic model. Most work with this common purpose uses deterministic models or an approximation of a stochastic Extinction-Colonisation model (sEC) which are relevant only for large networks. When working with a limited size network, the induced stochasticity is essential and has to be taken into account in the conclusions. Here, a rigorous framework is proposed for limited size networks and the limitations of the deterministic approximation are exhibited. This framework allows exact computations when the number of patches is small. Otherwise, simulations are used and enhanced by adapted simulation techniques when necessary. A sensitivity analysis was conducted to compare four main topologies of networks in contrasting settings to determine the role of the network. A challenging case was studied in this context: seed exchange of crop species in the Réseau Semences Paysannes (RSP), an emergent French farmers׳ organisation. A stochastic Extinction-Colonisation model was used to characterize the consequences of substantial changes in terms of RSP׳s social organization on the ability of the system to maintain crop varieties.