Dynamics of glucose and insulin concentration connected to the β-cell cycle: model development and analysis

Dynamical modeling the effect of glucagon-like peptide on glucose-insulin regulatory system based on mice experimental observation

As an emerging global epidemic, type 2 diabetes mellitus (T2DM) represents one of the leading causes of morbidity and mortality worldwide. Existing evidences demonstrated that glucagon-like peptide-1 (GLP-1) modulate the glucose regulatory system by enhancing the β-cell function. However, the detailed process of GLP-1 in glycaemic regulator for T2DM remains to be clarified. Thus, in this study, we propose an Institute of Cancer Research (ICR) mice high fat and cholesterol dietary experimental data-driven mathematical model to investigate the secretory effect of GLP-1 on the dynamics of glucose-insulin regulatory system. Specifically, we develop a mathematical model of GLP-1 dynamics as part of the interaction model of β-cell, insulin, and glucose dynamics. The parameter estimation and data fitting are in agreement with the data in mice experiments In addition, uncertainty quantification is performed to explore the possible factors that influence the pathways leading to the pathological state. Model analyses reveal that the high fat or high cholesterol diet stimulated GLP-1 plays an important role in the dynamics of glucose, insulin and β cells in short-term. These results show that enhanced GLP-1 may mitigate the dysregulation of glucose-insulin regulatory system via promoting the β cells function and stimulating secretion of insulin, which offers an in-depth insights into the mechanistic of hyperglycemia from dynamical approach and provide the theoretical basis for GLP-1 served as a potential clinical targeted drug for treatment of T2DM.

Liver fat metabolism of broilers regulated by Bacillus amyloliquefaciens TL via stimulating IGF-1 secretion and regulating the IGF signaling pathway

Bacillus amyloliquefaciens TL (B.A-TL) is well-known for its capability of promoting protein synthesis and lipid metabolism, in particular, the abdominal fat deposition in broilers. However, the underlying molecular mechanism remains unclear. In our study, the regulations of lipid metabolism of broilers by B.A-TL were explored both in vivo and in vitro. The metabolites of B.A-TL were used to simulate in vitro the effect of B.A-TL on liver metabolism based on the chicken hepatocellular carcinoma cell line (i.e., LMH cells). The effects of B.A-TL on lipid metabolism by regulating insulin/IGF signaling pathways were investigated by applying the signal pathway inhibitors in vitro. The results showed that the B.A-TL metabolites enhanced hepatic lipid synthesis and stimulated the secretion of IGF-1. The liver transcriptome analysis revealed the significantly upregulated expressions of four genes (SI, AMY2A, PCK1, and FASN) in the B.A-TL treatment group, mainly involved in carbohydrate digestion and absorption as well as biomacromolecule metabolism, with a particularly prominent effect on fatty acid synthase (FASN). Results of cellular assays showed that B.A-TL metabolites were involved in the insulin/IGF signaling pathway, regulating the expressions of lipid metabolism genes (e.g., FASN, ACCα, LPIN, and ACOX) and the FASN protein, ultimately regulating the lipid metabolism via the IGF/PI3K/FASN pathway in broilers.

Islet Function and Insulin Sensitivity in Latent Autoimmune Diabetes in Adults Taking Sitagliptin: A Randomized Trial

CONTEXT

The long-term effects of dipeptidyl peptidase-4 inhibitors on β-cell function and insulin sensitivity in latent autoimmune diabetes in adults (LADA) are unclear.

OBJECTIVE

To investigate the effects of sitagliptin on β-cell function and insulin sensitivity in LADA patients receiving insulin.

DESIGN AND SETTING

A randomized controlled trial at the Second Xiangya Hospital.

METHODS

Fifty-one patients with LADA were randomized to sitagliptin + insulin (SITA) group or insulin alone (CONT) group for 24 months.

MAIN OUTCOME MEASURES

Fasting C-peptide (FCP), 2-hour postprandial C-peptide (2hCP) during mixed-meal tolerance test, △CP (2hCP - FCP), and updated homeostatic model assessment of β-cell function (HOMA2-B) were determined every 6 months. In 12 subjects, hyperglycemic clamp and hyperinsulinemic euglycemic clamp (HEC) tests were further conducted at 12-month intervals.

RESULTS

During the 24-month follow-up, there were no significant changes in β-cell function in the SITA group, whereas the levels of 2hCP and △CP in the CONT group were reduced at 24 months. Meanwhile, the changes in HOMA2-B from baseline were larger in the SITA group than in the CONT group. At 24 months, first-phase insulin secretion was improved in the SITA group by hyperglycemia clamp, which was higher than in the CONT group (P < .001), while glucose metabolized (M), insulin sensitivity index, and M over logarithmical insulin ratio in HEC were increased in the SITA group (all P < .01 vs baseline), which were higher than in the CONT group.

CONCLUSION

Compared with insulin intervention alone, sitagliptin plus insulin treatment appeared to maintain β-cell function and improve insulin sensitivity in LADA to some extent.

Determination of selected biochemical parameters in blood serum and egg quality of Czech and Slovak native hens depending on the housing system and hen age

The objective of this study was to determine and evaluate the impact of the age and housing system on blood indicators (triacylglycerides, total cholesterol, aspartate aminotransferase, total proteins, albumin, glucose) and physical egg quality parameters (egg weight, shape index and surface area, eggshell proportion, thickness, strength, and color, albumen proportion and index, Haugh units, yolk proportion, index and yolk-to-albumen ratio) in selected native breeds of the Czech Republic (the Czech Golden Spotted hens) and Slovakia (the Oravka hens). Furthermore, the concentration of cholesterol in the yolk was determined. A total of 132 animals were used. There were 60 eggs collected from each breed at each monitored period for the evaluation of egg quality. Blood samples were taken by puncture of a wing vein. The assessments were made when the hens were of 34, 42, and 50 weeks old. Enriched cages and floor pens with litter were used as housing systems. The effects of breed, housing system, and age were observed. Furthermore, interactions among these factors were calculated. The significant effect of housing system was found in total cholesterol (P = 0.098) and aspartate aminotransferase (P = 0.0343) and the significant effect of age in total protein (P = 0.0392). The significant effect of breed (P = 0.0199), housing system (P = 0.0001), and age (P = 0.0001) was found in concentration of cholesterol in the yolk. Regarding the egg quality, the significant effect of breed (P = 0.0001) was found in eggshell color, albumen index and Haugh units, whereas the significant effect of housing system was found in egg weight (P = 0.0002), egg surface area (P = 0.0003), eggshell proportion (P = 0.0460), thickness (P = 0.0216), strength (P = 0.0049), and color (P = 0.0009). The significant effect of age was determined in all parameters except for the eggshell proportion and strength. The results represent an interesting comparison of changes in biochemical blood and egg quality parameters. It is necessary to further evaluate these indicators, especially in other genetic resources of hens, where the data are often nonexisting.

Mechanistic evaluation of the effect of sodium-dependent glucose transporter 2 inhibitors on delayed glucose absorption in patients with type 2 diabetes mellitus using a quantitative systems pharmacology model of human systemic glucose dynamics

Sodium-dependent glucose transporter (SGLT) 2 is specifically expressed in the kidney, while SGLT1 is present in the kidneys and small intestine. SGLT2 inhibitors are a class of oral antidiabetic drugs that lower elevated plasma glucose levels by promoting the urinary excretion of excess glucose through the inhibition of renal glucose reuptake. The inhibition selectivity for SGLT2 over SGLT1 (SGLT2/1 selectivity) of marketed SGLT2 inhibitors is diverse, while SGLT2/1 selectivity of canagliflozin is relatively low. Although canagliflozin suppresses postprandial glucose levels, the degree of contribution for SGLT1 inhibition to this effect remains unproven. To analyze the effect of SGLT2 inhibitors on postprandial glucose level, we constructed a novel quantitative systems pharmacology (QSP) model, called human systemic glucose dynamics (HSGD) model, integrating intestinal absorption, metabolism, and renal reabsorption of glucose. This HSGD model reproduced the postprandial plasma glucose concentration-time profiles during a meal tolerance test under different clinical trial conditions. Simulations after canagliflozin administration showed a dose-dependent delay of time (T_max,glc ) to reach maximum concentration of glucose (C_max,glc ), and the delay of T_max,glc disappeared when inhibition of SGLT1 was negated. In addition, contribution ratio of intestinal SGLT1 inhibition to the decrease in C_max,glc was estimated to be 23%-28%, when 100 and 300 mg of canagliflozin are administered. This HSGD model enabled us to provide the partial contribution of intestinal SGLT1 inhibition to the improvement of postprandial hyperglycemia as well as to quantitatively describe the plasma glucose dynamics following SGLT2 inhibitors.

A closed-loop multi-level model of glucose homeostasis

BACKGROUND

The pathophysiologic processes underlying the regulation of glucose homeostasis are considerably complex at both cellular and systemic level. A comprehensive and structured specification for the several layers of abstraction of glucose metabolism is often elusive, an issue currently solvable with the hierarchical description provided by multi-level models. In this study we propose a multi-level closed-loop model of whole-body glucose homeostasis, coupled with the molecular specifications of the insulin signaling cascade in adipocytes, under the experimental conditions of normal glucose regulation and type 2 diabetes.

METHODOLOGY/PRINCIPAL FINDINGS

The ordinary differential equations of the model, describing the dynamics of glucose and key regulatory hormones and their reciprocal interactions among gut, liver, muscle and adipose tissue, were designed for being embedded in a modular, hierarchical structure. The closed-loop model structure allowed self-sustained simulations to represent an ideal in silico subject that adjusts its own metabolism to the fasting and feeding states, depending on the hormonal context and invariant to circadian fluctuations. The cellular level of the model provided a seamless dynamic description of the molecular mechanisms downstream the insulin receptor in the adipocytes by accounting for variations in the surrounding metabolic context.

CONCLUSIONS/SIGNIFICANCE

The combination of a multi-level and closed-loop modeling approach provided a fair dynamic description of the core determinants of glucose homeostasis at both cellular and systemic scales. This model architecture is intrinsically open to incorporate supplementary layers of specifications describing further individual components influencing glucose metabolism.

A Comparison of Deterministic and Stochastic Modeling Approaches for Biochemical Reaction Systems: On Fixed Points, Means, and Modes

In the mathematical modeling of biochemical reactions, a convenient standard approach is to use ordinary differential equations (ODEs) that follow the law of mass action. However, this deterministic ansatz is based on simplifications; in particular, it neglects noise, which is inherent to biological processes. In contrast, the stochasticity of reactions is captured in detail by the discrete chemical master equation (CME). Therefore, the CME is frequently applied to mesoscopic systems, where copy numbers of involved components are small and random fluctuations are thus significant. Here, we compare those two common modeling approaches, aiming at identifying parallels and discrepancies between deterministic variables and possible stochastic counterparts like the mean or modes of the state space probability distribution. To that end, a mathematically flexible reaction scheme of autoregulatory gene expression is translated into the corresponding ODE and CME formulations. We show that in the thermodynamic limit, deterministic stable fixed points usually correspond well to the modes in the stationary probability distribution. However, this connection might be disrupted in small systems. The discrepancies are characterized and systematically traced back to the magnitude of the stoichiometric coefficients and to the presence of nonlinear reactions. These factors are found to synergistically promote large and highly asymmetric fluctuations. As a consequence, bistable but unimodal, and monostable but bimodal systems can emerge. This clearly challenges the role of ODE modeling in the description of cellular signaling and regulation, where some of the involved components usually occur in low copy numbers. Nevertheless, systems whose bimodality originates from deterministic bistability are found to sustain a more robust separation of the two states compared to bimodal, but monostable systems. In regulatory circuits that require precise coordination, ODE modeling is thus still expected to provide relevant indications on the underlying dynamics.

Development, growth and maintenance of β-cell mass: models are also part of the story

Pancreatic β-cells in the islets of Langerhans play a crucial role in regulating glucose homeostasis in the circulation. Loss of β-cell mass or function due to environmental, genetic and immunological factors leads to the manifestation of diabetes mellitus. The mechanisms regulating the dynamics of pancreatic β-cell mass during normal development and diabetes progression are complex. To fully unravel such complexity, experimental and clinical approaches need to be combined with mathematical and computational models. In the natural sciences, mathematical and computational models have aided the identification of key mechanisms underlying the behavior of systems comprising multiple interacting components. A number of mathematical and computational models have been proposed to explain the development, growth and death of pancreatic β-cells. In this review, we discuss some of these models and how their predictions provide novel insight into the mechanisms controlling β-cell mass during normal development and diabetes progression. Lastly, we discuss a handful of the major open questions in the field.

A novel method for simulating insulin mediated GLUT4 translocation

Glucose transport in humans is a vital process which is tightly regulated by the endocrine system. Specifically, the insulin hormone triggers a cascade of intracellular signals in target cells mediating the uptake of glucose. Insulin signaling triggers cellular relocalization of the glucose transporter protein GLUT4 to the cell surface, which is primarily responsible for regulated glucose import. Pathology associated with the disruption of this pathway can lead to metabolic disorders, such as type II diabetes mellitus, characterized by the failure of cells to appropriately uptake glucose from the blood. We describe a novel simulation tool of the insulin intracellular response, incorporating the latest findings regarding As160 and GEF interactions. The simulation tool differs from previous computational approaches which employ algebraic or differential equations; instead, the tool incorporates statistical variations of kinetic constants and initial molecular concentrations which more accurately mimic the intracellular environment. Using this approach, we successfully recapitulate observed in vitro insulin responses, plus the effects of Wortmannin-like inhibition of the pathway. The developed tool provides insight into transient changes in molecule concentrations throughout the insulin signaling pathway, and may be employed to identify or evaluate potentially critical components of this pathway, including those associated with insulin resistance. In the future, this highly tractable platform may be useful for simulating other complex cell signaling pathways. Biotechnol. Bioeng. 2014;111: 2454-2465. © 2014 Wiley Periodicals, Inc.