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Experimental evaluation and computational modeling of the effects of encapsulation on the time-profile of glucose-stimulated insulin release of pancreatic islets.

Buchwald P, Cechin SR, Weaver JD, Stabler CL - Biomed Eng Online (2015)

Bottom Line: Within this framework, it is of considerable interest to characterize the effect encapsulation has on the insulin response of pancreatic islets.The present high-resolution GSIR experiments allowed for direct characterization of the effect microencapsulation has on the time-profile of insulin secretion.The multiphysics model, further validated here with the help of these experimental results, can be used to increase our understanding of the challenges that have to be faced in the design of bioartificial pancreas-type devices and to advance their further optimization.

View Article: PubMed Central - PubMed

Affiliation: Diabetes Research Institute, University of Miami, DRI, 1450 NW 10th Ave (R-134), Miami, FL, 33136, USA. pbuchwald@med.miami.edu.

ABSTRACT

Background: In type 1 diabetic patients, who have lost their ability to produce insulin, transplantation of pancreatic islet cells can normalize metabolic control in a manner that is not achievable with exogenous insulin. To be successful, this procedure has to address the problems caused by the immune and autoimmune responses to the graft. Islet encapsulation using various techniques and materials has been and is being extensively explored as a possible approach. Within this framework, it is of considerable interest to characterize the effect encapsulation has on the insulin response of pancreatic islets.

Methods: To improve our ability to quantitatively describe the glucose-stimulated insulin release (GSIR) of pancreatic islets in general and of micro-encapsulated islets in particular, we performed dynamic perifusion experiments with frequent sampling. We used unencapsulated and microencapsulated murine islets in parallel and fitted the results with a complex local concentration-based finite element method (FEM) computational model.

Results: The high-resolution dynamic perifusion experiments allowed good characterization of the first-phase and second-phase insulin secretion, and we observed a slightly delayed and blunted first-phase insulin response for microencapsulated islets when compared to free islets. Insulin secretion profiles of both free and encapsulated islets could be fitted well by a COMSOL Multiphysics model that couples hormone secretion and nutrient consumption kinetics with diffusive and convective transport. This model, which was further validated and calibrated here, can be used for arbitrary geometries and glucose stimulation sequences and is well suited for the quantitative characterization of the insulin response of cultured, perifused, transplanted, or encapsulated islets.

Conclusions: The present high-resolution GSIR experiments allowed for direct characterization of the effect microencapsulation has on the time-profile of insulin secretion. The multiphysics model, further validated here with the help of these experimental results, can be used to increase our understanding of the challenges that have to be faced in the design of bioartificial pancreas-type devices and to advance their further optimization.

No MeSH data available.


Related in: MedlinePlus

Model-calculated insulin concentrations in response to increasing glucose concentrations. Calculated insulin concentrations for two illustrative free and encapsulated islets (left and right, respectively; d = 100 (top) & 150 μm (bottom), lcaps = 150 μm) under normoxic conditions. Data shown as surface plot are insulin concentration (color-coded from blue for low to red for high. Streamlines show the flow of the perifusion fluid (color-coded for velocity; flow from left to right) and colored contour lines show isolevels for the perifusing glucose (from light blue for low to light red for high). Model calculated values are shown during the increase of the glucose concentration from 3 mM to 11 mM; first phase response is noticeably delayed and blunted in the encapsulated islet.
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Fig5: Model-calculated insulin concentrations in response to increasing glucose concentrations. Calculated insulin concentrations for two illustrative free and encapsulated islets (left and right, respectively; d = 100 (top) & 150 μm (bottom), lcaps = 150 μm) under normoxic conditions. Data shown as surface plot are insulin concentration (color-coded from blue for low to red for high. Streamlines show the flow of the perifusion fluid (color-coded for velocity; flow from left to right) and colored contour lines show isolevels for the perifusing glucose (from light blue for low to light red for high). Model calculated values are shown during the increase of the glucose concentration from 3 mM to 11 mM; first phase response is noticeably delayed and blunted in the encapsulated islet.

Mentions: Another important goal of the present work was to verify if these data can be fitted by our recently developed complex FEM-based computational model [21]. This local concentration-based model predicted a similar behavior for hydrogel-encapsulated islets. Figure 3 shows the theoretical predicted values for a setup mimicking the present experimental conditions. Two perifused islets that are in the center of spherical capsules were used in the model, and the capsule thickness was varied from 50 to 350 μm. The model assumes that the insulin-secreting β-cells act as sensors of both the local glucose concentration and its change. Hence, a first-phase response related to the change in (local) glucose concentration as well as a second-phase response related to the (local) glucose concentration is incorporated [21]. Insulin is released within the islets following Hill–type sigmoid response-functions of the local (i.e., cellular level) glucose concentration, cgluc, and its time-gradient, ∂cgluc/∂t, resulting in second– and first–phase insulin responses, respectively (Figure 1). Oxygen and glucose consumption by the islet cells are incorporated in the model using Michaelis-Menten–type kinetics (i.e., Hill equation with n = 1). Since lack of oxygen (hypoxia) can be an important limiting factor in avascular islets [26], oxygen concentrations are also allowed to limit the rate of insulin secretion, following again a Hill–type equation. Finally, all the local (cellular-level) oxygen, glucose, and insulin concentrations are combined together with solute transfer equations to calculate observable, external concentrations as a function of time and incoming glucose and oxygen concentrations (see Computational methods and Additional file 1: Appendix 1 for further details). Calculations were done using the same model parameterized originally based on perifusion data from human islets [21], except the kinetics of insulin release was increased slightly (kinsL = 0.006 s−1 vs. the original 0.003 s−1) to account for the somewhat sharper first phase response of murine islets observed here as compared to human islets [34,43]. The effect of this change on the predicted insulin release profile of free islets is shown in Figure 4. An important advantage of this model is that it allows for calculation of the distribution of all concentrations of interest at any time-point during the perifusion; an illustrative example of insulin concentration during the increase of incoming glucose concentration is shown in Figure 5 comparing the response of free and encapsulated islets.Figure 3


Experimental evaluation and computational modeling of the effects of encapsulation on the time-profile of glucose-stimulated insulin release of pancreatic islets.

Buchwald P, Cechin SR, Weaver JD, Stabler CL - Biomed Eng Online (2015)

Model-calculated insulin concentrations in response to increasing glucose concentrations. Calculated insulin concentrations for two illustrative free and encapsulated islets (left and right, respectively; d = 100 (top) & 150 μm (bottom), lcaps = 150 μm) under normoxic conditions. Data shown as surface plot are insulin concentration (color-coded from blue for low to red for high. Streamlines show the flow of the perifusion fluid (color-coded for velocity; flow from left to right) and colored contour lines show isolevels for the perifusing glucose (from light blue for low to light red for high). Model calculated values are shown during the increase of the glucose concentration from 3 mM to 11 mM; first phase response is noticeably delayed and blunted in the encapsulated islet.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4403786&req=5

Fig5: Model-calculated insulin concentrations in response to increasing glucose concentrations. Calculated insulin concentrations for two illustrative free and encapsulated islets (left and right, respectively; d = 100 (top) & 150 μm (bottom), lcaps = 150 μm) under normoxic conditions. Data shown as surface plot are insulin concentration (color-coded from blue for low to red for high. Streamlines show the flow of the perifusion fluid (color-coded for velocity; flow from left to right) and colored contour lines show isolevels for the perifusing glucose (from light blue for low to light red for high). Model calculated values are shown during the increase of the glucose concentration from 3 mM to 11 mM; first phase response is noticeably delayed and blunted in the encapsulated islet.
Mentions: Another important goal of the present work was to verify if these data can be fitted by our recently developed complex FEM-based computational model [21]. This local concentration-based model predicted a similar behavior for hydrogel-encapsulated islets. Figure 3 shows the theoretical predicted values for a setup mimicking the present experimental conditions. Two perifused islets that are in the center of spherical capsules were used in the model, and the capsule thickness was varied from 50 to 350 μm. The model assumes that the insulin-secreting β-cells act as sensors of both the local glucose concentration and its change. Hence, a first-phase response related to the change in (local) glucose concentration as well as a second-phase response related to the (local) glucose concentration is incorporated [21]. Insulin is released within the islets following Hill–type sigmoid response-functions of the local (i.e., cellular level) glucose concentration, cgluc, and its time-gradient, ∂cgluc/∂t, resulting in second– and first–phase insulin responses, respectively (Figure 1). Oxygen and glucose consumption by the islet cells are incorporated in the model using Michaelis-Menten–type kinetics (i.e., Hill equation with n = 1). Since lack of oxygen (hypoxia) can be an important limiting factor in avascular islets [26], oxygen concentrations are also allowed to limit the rate of insulin secretion, following again a Hill–type equation. Finally, all the local (cellular-level) oxygen, glucose, and insulin concentrations are combined together with solute transfer equations to calculate observable, external concentrations as a function of time and incoming glucose and oxygen concentrations (see Computational methods and Additional file 1: Appendix 1 for further details). Calculations were done using the same model parameterized originally based on perifusion data from human islets [21], except the kinetics of insulin release was increased slightly (kinsL = 0.006 s−1 vs. the original 0.003 s−1) to account for the somewhat sharper first phase response of murine islets observed here as compared to human islets [34,43]. The effect of this change on the predicted insulin release profile of free islets is shown in Figure 4. An important advantage of this model is that it allows for calculation of the distribution of all concentrations of interest at any time-point during the perifusion; an illustrative example of insulin concentration during the increase of incoming glucose concentration is shown in Figure 5 comparing the response of free and encapsulated islets.Figure 3

Bottom Line: Within this framework, it is of considerable interest to characterize the effect encapsulation has on the insulin response of pancreatic islets.The present high-resolution GSIR experiments allowed for direct characterization of the effect microencapsulation has on the time-profile of insulin secretion.The multiphysics model, further validated here with the help of these experimental results, can be used to increase our understanding of the challenges that have to be faced in the design of bioartificial pancreas-type devices and to advance their further optimization.

View Article: PubMed Central - PubMed

Affiliation: Diabetes Research Institute, University of Miami, DRI, 1450 NW 10th Ave (R-134), Miami, FL, 33136, USA. pbuchwald@med.miami.edu.

ABSTRACT

Background: In type 1 diabetic patients, who have lost their ability to produce insulin, transplantation of pancreatic islet cells can normalize metabolic control in a manner that is not achievable with exogenous insulin. To be successful, this procedure has to address the problems caused by the immune and autoimmune responses to the graft. Islet encapsulation using various techniques and materials has been and is being extensively explored as a possible approach. Within this framework, it is of considerable interest to characterize the effect encapsulation has on the insulin response of pancreatic islets.

Methods: To improve our ability to quantitatively describe the glucose-stimulated insulin release (GSIR) of pancreatic islets in general and of micro-encapsulated islets in particular, we performed dynamic perifusion experiments with frequent sampling. We used unencapsulated and microencapsulated murine islets in parallel and fitted the results with a complex local concentration-based finite element method (FEM) computational model.

Results: The high-resolution dynamic perifusion experiments allowed good characterization of the first-phase and second-phase insulin secretion, and we observed a slightly delayed and blunted first-phase insulin response for microencapsulated islets when compared to free islets. Insulin secretion profiles of both free and encapsulated islets could be fitted well by a COMSOL Multiphysics model that couples hormone secretion and nutrient consumption kinetics with diffusive and convective transport. This model, which was further validated and calibrated here, can be used for arbitrary geometries and glucose stimulation sequences and is well suited for the quantitative characterization of the insulin response of cultured, perifused, transplanted, or encapsulated islets.

Conclusions: The present high-resolution GSIR experiments allowed for direct characterization of the effect microencapsulation has on the time-profile of insulin secretion. The multiphysics model, further validated here with the help of these experimental results, can be used to increase our understanding of the challenges that have to be faced in the design of bioartificial pancreas-type devices and to advance their further optimization.

No MeSH data available.


Related in: MedlinePlus