A5072748271- Adipose Tissue and Metabolism
- Diet and metabolism studies
- Diabetes Management and Research
- Gene expression and cancer classification
- Protein Structure and Dynamics
- Liver Disease Diagnosis and Treatment
- Pancreatic function and diabetes
- Model Reduction and Neural Networks
- Metabolism, Diabetes, and Cancer
- Molecular Biology Techniques and Applications
- Lipid metabolism and disorders
- Domain Adaptation and Few-Shot Learning
- Diabetes and associated disorders
- Viral Infectious Diseases and Gene Expression in Insects
- Muscle metabolism and nutrition
- Metabolomics and Mass Spectrometry Studies
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
- Cancer, Lipids, and Metabolism
- Computational Drug Discovery Methods
- Nutrition and Health in Aging
- Probabilistic and Robust Engineering Design
- Diet, Metabolism, and Disease
- Cardiovascular Function and Risk Factors
Eindhoven University of Technology
2022-2025
Wageningen University & Research
2019-2023
Maastricht University
2019-2023
University College Cork
2019
Abstract Universal differential equations (UDEs) are an emerging approach in biomedical systems biology, integrating physiology-driven mathematical models with machine learning for data-driven model discovery areas where knowledge of the underlying physiology is limited. However, current approaches to training UDEs do not directly accommodate heterogeneity data. As a approach, also vulnerable overfitting and consequently cannot sufficiently generalise heterogeneous populations. We propose...
Systems biology tackles the challenge of understanding high complexity in internal regulation homeostasis human body through mathematical modelling. These models can aid discovery disease mechanisms and potential drug targets. However, on one hand development validation knowledge-based mechanistic is time-consuming does not scale well with increasing features medical data. On other hand, data-driven approaches such as machine learning require large volumes data to produce generalisable...
Objective The study investigated the diurnal variance in metabolic resilience (i.e., robustness, recovery and re-orientation of metabolism) flexibility glucose fat oxidation rates to three identical test meals. Methods Eight young, healthy subjects consumed liquid mixed meals times a day (33 % energy requirement each), followed by defined bout physical activity conducted whole-room indirect calorimeter continuously assess expenditure postprandial changes substrate rates, as measure...
Abstract The Muscle Insulin Sensitivity Index (MISI) has been developed to estimate muscle-specific insulin sensitivity based on oral glucose tolerance test (OGTT) data. To date, the score implemented with considerable variation in literature and initial positive evaluations were not reproduced subsequent studies. In this study, we investigate computation of MISI OGTT data differing sampling schedules aim standardise improve its calculation. Seven time point for 2631 individuals from...
Little is known about gene regulation by fasting in human adipose tissue. Accordingly, the objective of this study was to investigate effects on tissue expression humans. To that end, subcutaneous biopsies were collected from 11 volunteers 2 and 26 h after consumption a standardized meal. For comparison, epididymal C57Bl/6J mice ab libitum-fed state 16 fast. The timing sampling roughly corresponds with near depletion liver glycogen. Transcriptome analysis carried out using Affymetrix...
The intricate dependency structure of biological “omics” data, particularly those originating from longitudinal intervention studies with frequently sampled repeated measurements renders the analysis such data challenging. high-dimensionality, inter-relatedness multiple outcomes, and heterogeneity in studied systems all add to difficulty deriving meaningful information. In addition, subtle differences dynamics often deemed nutritional can be challenging quantify. this work we demonstrate use...
Current computational models of whole-body glucose homeostasis describe physiological processes by which insulin regulates circulating concentrations. While these perform well in response to oral challenges, interaction with other nutrients that impact postprandial metabolism, such as amino acids (AAs), is not considered. Here, we developed a model the human glucose-insulin system, incorporates effects AAs on secretion and hepatic production. This was applied time-series data following...
A personalized Meal Model can be generated by fitting to meal response data The model quantifies insulin resistance, b-cell functionality, and liver fat reduces a threedimensional measure of metabolic health Personalized Models reveal changes in after an intervention
Abstract Continuous glucose monitoring (CGM) is a promising, minimally invasive alternative to plasma measurements for calibrating physiology-based mathematical models of insulin-regulated metabolism, reducing the reliance on in-clinic measurements. However, use CGM glucose, particularly in combination with insulin measurements, develop personalized regulation remains unexplored. Here, we simultaneously measured interstitial concentrations using as well and during an oral tolerance test...
Plasma glucose and insulin responses following an oral challenge are representative of tolerance resistance, key indicators type 2 diabetes mellitus pathophysiology. A large heterogeneity in individuals’ test has been shown to underlie the effectiveness lifestyle intervention. Currently, this is overlooked due a lack methods quantify interconnected dynamics time-courses. Here, physiology-based mathematical model human glucose-insulin system personalized elucidate using population...
Despite the pivotal role played by elevated circulating triglyceride levels in pathophysiology of cardio-metabolic diseases many indices used to quantify metabolic health focus on deviations glucose and insulin alone. We present Mixed Meal Model, a computational model describing systemic interplay between triglycerides, free fatty acids, glucose, insulin. show that Model can capture post-meal excursions plasma insulin, are indicative features resilience; quantifying resistance liver fat;...
Given the association of disturbances in non-esterified fatty acid (NEFA) metabolism with development Type 2 Diabetes and Non-Alcoholic Fatty Liver Disease, computational models glucose-insulin dynamics have been extended to account for interplay NEFA. In this study, we use arteriovenous measurement across subcutaneous adipose tissue during a mixed meal challenge test evaluate performance underlying assumptions three existing construct new, refined model metabolism. Our introduces new terms,...
Computational models of human glucose homeostasis can provide insight into the physiological processes underlying observed inter-individual variability in regulation. Modelling approaches ranging from “bottom-up” mechanistic to “top-down” data-driven techniques have been applied untangle complex interactions progressive disturbances homeostasis. While both offer distinct benefits, a combined approach taking best worlds has yet be explored. Here, we propose sequential combination and modeling...
In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing human trials. However, relating results in vitro model exposures relevant outcomes vivo system still proves challenging, relying on putative orthologs. recent years, multiple studies have demonstrated that repeated dose rodent bioassay, current gold standard field, lacks sufficient sensitivity specificity predicting pharmaceuticals...
Abstract Systems biology tackles the challenge of understanding high complexity in internal regulation homeostasis human body through mathematical modelling. These models can aid discovery disease mechanisms and potential drug targets. However, on one hand development validation knowledge-based mechanistic is time-consuming does not scale well with increasing features medical data. On other hand, more data-driven approaches such as machine learning require large volumes data to produce...
The liver is the primary site for metabolism and detoxification of many compounds, including pharmaceuticals. Consequently, it also location adverse reactions. As not readily accessible sampling in humans; rodent or cell line models are often used to evaluate potential toxic effects a novel compound candidate drug. However, relating results animal vitro studies relevant clinical outcomes human vivo situation still proves challenging. In this study, we incorporate principles transfer learning...