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108 results for “model foods”
Data from: Thermal plasticity in protective wing pigmentation is modulated by genotype and food availability in an insect model of seasonal polyphenism
<p>Phenotypic variation in natural populations results from complex interactions between organisms and their changing environments. The environment shapes both phenotypic frequencies (during adaptation) and organismal phenotypes (through phenotypic plasticity). Developmental plasticity, in particular, refers to the phenomenon whereby an organism's phenotype depends on the environmental conditions during development. It can match phenotype to ecological conditions and help organisms to cope with environmental heterogeneity, including differences between alternating seasons. Experimental studies of developmental plasticity often focus on the impact of individual environmental cues and do not take explicit account of genetic variation. In contrast, natural environments are complex, comprising multiple variables with combined effects that are poorly understood and may vary among genotypes. We investigated the effects of multifactorial environments on the development of the seasonally plastic eyespots of <em>Bicyclus anynana</em> butterflies. Eyespot size depends on developmental temperature and is involved in alternative seasonal strategies for predator avoidance. In nature, both temperature and food availability undergo seasonal fluctuations. However, our understanding of how thermal plasticity in eyespot size varies in response to food availability and across genotypes remains limited. To address this, we investigated the combined effects of temperature (T; two levels: 20°C and 27°C) and food availability (N; two levels: control and limited) during development. We examined their impact on wing and eyespot size in adult males and females from multiple genotypes (G; 28 families). We found evidence of thermal and nutritional plasticity and temperature-by-nutrition interactions (significant TxN) on the size of eyespots in both sexes. Food limitation resulted in relatively smaller eyespots and tempered the effects of temperature. Additionally, we found differences among families for thermal plasticity (significant GxT effects), but not for nutritional plasticity (non-significant GxN effects) nor for the combined effects of temperature and food limitation (non-significant GxTxN effects). Our results reveal the context dependence of thermal plasticity, with the slope of thermal reaction norms varying across genotypes and across nutritional environments. We discuss these results in light of the ecological significance of pigmentation and the value of considering thermal plasticity in studies of the biological impact of climate change.</p>
Non-Conventional Time Domain (TD)-NMR Approaches for Food Quality: Case of Gelatin-Based Candies as a Model Food
<p>The TD-NMR technique mostly involves the use of T1 (spin-lattice) and T2 (spin-spin)<br> relaxation times to explain the changes occurring in food systems. However, these relaxation times<br> are affected by many factors and might not always be the best indicators to work with in food related<br> TD-NMR studies. In this study, the non-conventional TD-NMR approaches of Solid Echo<br> (SE)/Magic Sandwich Echo (MSE) and Spin Diffusion in food systems were used for the first time. Soft<br> confectionary gelatin gels were formulated and conventional (T1) and non-conventional (SE, MSE and<br> Spin Diffusion) TD-NMR experiments were performed. Corn syrups with different glucose/fructose<br> compositions were used to prepare the soft candies. Hardness, °Brix (°Bx), and water activity (aw)<br> measurements were also conducted complementary to NMR experiments. Relaxation times changed<br> (p < 0.05) with respect to syrup type with no obvious trend. SE/MSE experiments were performed to<br> calculate the crystallinity of the samples. Samples prepared with fructose had the lowest crystallinity<br> values (p < 0.05). Spin Diffusion experiments were performed by using Goldman–Shen pulse sequence<br> and the interface thickness (d) was calculated. Interface thickness values showed a wide range of<br> variation (p < 0.05). Results showed that non-conventional NMR approaches had a high potential to be<br> utilized in food systems for quality control purposes.</p>
Data from: Ecosystem function in predator-prey food webs - confronting dynamic models with empirical data
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Effects of enhanced productivity of resources shared by predators in a food-web module: Comparing results of a field experiment to predictions of mathematical models of intra-guild predation
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Energetic constraints imposed on trophic interaction strengths enhance resilience in empirical and model food webs
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Arthropod food webs in the foreland of a retreating Greenland glacier: Integrating molecular gut content analysis with Structural Equation Modelling
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Data from: Thermal plasticity in protective wing pigmentation is modulated by genotype and food availability in an insect model of seasonal polyphenism
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Large-scale multi-trophic co-response models and environmental control of pelagic food webs in Québec lakes
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Eco‐evolutionary dynamics driven by fishing: from single species models to dynamic evolution within complex food webs
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Model-based analysis of postprandial glycemic response dynamics for different types of food
<p>Background & aims</p> <p>Knowledge of postprandial glycemic response (PPGR) dynamics is important in nutrition management and diabetes research, care and (self)management. In daily life, food intake is the most important factor influencing the occurrence of hyperglycemia. However, the large variability in PPGR dynamics to different types of food is inadequately predicted by existing glycemic measures. The objective of this study was therefore to quantitatively describe PPGR dynamics using a systems approach.</p> <p>Methods</p> <p>Postprandial glucose and insulin data were collected from literature for many different food products and mixed meals. The predictive value of existing measures, such as the Glycemic Index, was evaluated. A physiology-based dynamic model was used to reconstruct the full postprandial response profiles of both glucose and insulin simultaneously.</p> <p>Results</p> <p>We collected a large range of postprandial glucose and insulin dynamics for 53 common food products and mixed meals. Currently available glycemic measures were found to be inadequate to describe the heterogeneity in postprandial dynamics. By estimating model parameters from glucose and insulin data, the physiology-based dynamic model accurately describes the measured data whilst adhering to physiological constraints.</p> <p>Conclusions</p> <p>The physiology-based dynamic model provides a systematic framework to analyze postprandial glucose and insulin profiles. By changing parameter values the model can be adjusted to simulate impaired glucose tolerance and insulin resistance.</p>
AWESOME Water and food demand (WATNEEDS crop model)
<p><span>In this record, we provide the results in terms of crop water requirements, calculated by the hydrological model WATNEEDS, and crop harvested area under the implemented crop replacement scenarios, that have been developed to optimize water use, crop production and agricultural value in present and future climate scenarios in the Nile Basin. These scenarios were designed, modeled and generated for the deliverable D2.3 of AWESOME WP2: <em>Dynamic and spatially distributed crop water use modeling.</em></span></p> <p><span>The analyses have been conducted at the mesoscale, with a specific focus has been reserved for Egypt, as it is particularly relevant for the AWESOME project because the demo sites of the innovative technologies are being build there. </span>In addition, we investigated present and future reallocation scenarios also for Ethiopia and Sudan, to cover the main cropland along the Nile River Basin.</p> <p><span>A baseline scenario is evaluated to quantify blue and green crop water requirements for the current climate conditions and current crop distribution (averaged for the period 2011-2016). </span>Future scenarios have been implemented using future climatic data for the average period around year 2050 (2048-2052) and year 2100 (2096-2100) under three different Representative Concentration Pathways (RCPs): RCP 4.5, RCP 2.6 and RCP 8.5.</p> <p> </p> <p><span>This record contains:</span></p> <p><span>- The Deliverable D2.3, where the optimization model and the calculation of the crop water requirements under different climatic scenarios are presented.</span></p> <p><span>- The results for each implemented scenario, in terms of harvested area and irrigation water consumption (.tif files and excel files), for the Nile River Basin and at the national level for each focus country (Ethiopia, Sudan and Egypt).</span></p> <p><span>- Description of the data (excel file and pdf file)</span></p> <p><span> </span></p>
Global food shock and trade model
<p>Main code to run global food shock and agricultural trade model, supporting the results of Verschuur et al. (under review), "The impacts of polycrisis on global grain availability and prices".</p> <p>This includes:<br>1/ The calibration procedure per crop to quantify the calibration constants per trade flow given the present-day trade network<br>2/ The simulation analysis of various shocks, including:<br>-(i) 54 years of baseline yield variability;<br>-(ii) (i) + Ukraine war supply shock;<br>-(iii) (i) + Energy price shock;<br>-(iv) (i) + Trade bans;<br>-(v) (i) + all shocks combined</p> <p> </p> <p>All optimisation is written in Pyomo (<a href="https://www.pyomo.org/" rel="nofollow">https://www.pyomo.org/</a>) with HSL's MA27 as (non-linear) solver:<br><a href="https://github.com/coin-or-tools/ThirdParty-HSL">https://github.com/coin-or-tools/ThirdParty-HSL</a><br>Alternatively, one can run the code using the standard ipopt solver in Pyomo.<br><br>Software requirements:<br>-Python Python 3.9.12<br>-Tested on MacOS Monterey v12.2.1<br><br>Runtime:<br>-Calibration runtime depends on crop but around 1-2h.<br>-To run the shocks, runtime is around 15 minutes per modelled year.<br><br>Demo:<br>Alongside the code for the paper, we uploaded a small demo model based on the AGRODEP Spatial trade model developed by IFPRI (<a href="https://www.agrodep.org/models/agrodep-spatial-equilibrium-model" rel="nofollow">https://www.agrodep.org/models/agrodep-spatial-equilibrium-model</a>), which can help users to get familiar with spatial price equilibrium modelling. We have modified the original AGRODEP model to be in line with the trade cost formulation adopted in our paper. Runtime should be minutes.</p>
Data: Trait-based food web model reveals the underlying mechanisms of biodiversity-ecosystem functioning relationships
<p>Data and code related to 'Trait-based food web model reveals the underlying mechanisms of biodiversity-ecosystem functioning relationships' to reproduce figures and analyses.</p>
Genetic Carbohydrate Maldigestion as a Model to Study Food Hypersensitivity
ClinicalTrials.gov study NCT05795049. IPD Sharing: NO. Countries: 1. Publications: 17.
Model Predictive Control (MPC) Artificial Pancreas vs. Sensor Augmented Pump (SAP)/Predictive Low Glucose Suspend (PLGS) With Different Food Choices in the Outpatient Setting
ClinicalTrials.gov study NCT03767790. IPD Sharing: NO. Countries: 1. Publications: 1.
FoodStep - a Sustainable Model for Food Services and Early Childhood Education and Care
ClinicalTrials.gov study NCT05249946. IPD Sharing: NO. Countries: 1. Publications: 0.
Use of Nutrigenomic Models for the Personalized Treatment With Medical Foods in Obese People
ClinicalTrials.gov study NCT02837367. IPD Sharing: NO. Countries: 1. Publications: 3.
Data from: Linking demographic and food‐web models to understand management trade‐offs
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Data from: Multiple predator species alter prey behavior, population growth and a trophic cascade in a model estuarine food web
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A modified niche model for generating food webs with stage-structured consumers: The stabilizing effects of life-history stages on complex food webs
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.