Diabetes systems biology : quantitative methods for understanding beta-cell dynamics and function / edited by Anmar Khadra.

Format:

Book

Contributor:

Khadra, Anmar, editor.

Series:

Biophysical Society-IOP Series

Language:

English

Subjects (All):

Diabetes--Alternative treatment.

Diabetes.

Physical Description:

1 online resource (277 pages)

Edition:

First edition.

Place of Publication:

Bristol, England : IOP Publishing, [2020]

Summary:

Diabetes Systems Biology provides a detailed overview of the mathematical modelling techniques and quantitative tools used to analyse the dynamics of pancreatic islets and beta cells during health and disease.

Contents:

Intro

Description of the aims, scope and the audience

Editor biography

Anmar Khadra

List of contributors

Chapter 1 Introduction

Chapter 2 An introduction to beta cell electrophysiology and modeling

2.1 Basic physics of membrane potential and ion conductances

2.1.1 Voltage clamp, current clamp, and ionic currents: 'there's no place like Ohm'

2.1.2 Hodgkin-Huxley and Morris-Lecar models

2.1.3 A tale of tail currents

2.1.4 Space clamp, and difficulties in voltage clamping structures having complex geometries

2.1.5 Beta cells and islets as preparations for electrophysiological studies

2.2 Spiking, bursting and beyond with Morris-Lecar (a beta-cell DIY)

2.2.1 Negative feedback due to calcium

2.2.2 Bursting via Ca2+ feedback (the Chay-Keizer model)

2.2.3 Introducing metabolic oscillations

2.3 Concluding thoughts

2.3.1 References for further reading

Appendix A Linear systems

A.1 Nonlinear systems

Exercises

References

Chapter 3 Recent advances in mathematical modeling and statistical analysis of exocytosis in endocrine cells

3.1 Cell biology of exocytosis

3.2 Experimental techniques for investigations of exocytosis

3.2.1 Measuring whole-cell exocytosis as capacitance increases

3.2.2 Recording single exocytotic events with imaging

3.3 Local control of exocytosis by Ca2+ microdomains

3.4 From microdomains to whole-cell modeling of exocytosis

3.4.1 Distinguishing pool depletion from Ca2+ channel inactivation

3.5 Granule pool dynamics

3.5.1 Newcomer granules and the highly Ca2+-sensitive pool

Chapter 4 Islet architecture

4.1 Islets of Langerhans

4.2 Differential adhesion hypothesis

4.3 Analytical method

4.4 Monte-Carlo sampling method

4.5 Islet structure data

4.6 Inverse problem

References.

Chapter 5 Intra-islet network

5.1 Introduction

5.2 Reduced islet model

5.3 Oscillator-based model

5.3.1 α-β model

5.3.2 α-β-δ model

5.3.3 Population model

Chapter 6 The role of islet cell network in insulin secretion

6.1 Rhythmicity in insulin and glucose and the basis for it

6.2 Islet cell network and beta cell oscillation

6.2.1 High and ultradian insulin rhythms originate at the level of pancreatic islet beta cells

6.2.2 Beta cell oscillation and its mathematical model

6.2.3 The role of islet cell network structure in beta-cell oscillation

6.3 Intracellular insulin granule trafficking during glucose-stimulated insulin secretion

6.3.1 A new mathematical model of insulin granule trafficking and insulin secretion with glucose-dependent granule mobilization, priming and fusion

6.3.2 Model outcomes in comparison to experimental observations

6.4 The role of islet network structure in insulin secretion rate and pulsatility

6.4.1 A model of a network of coupled beta cells that incorporates glucose-dependent membrane potential, and intracellular Ca2+ and granule dynamics

6.4.2 Electrical response and insulin secretion as glucose is raised in a single step

6.5 Future work: application to diabetes and fundamental research of nonlinear dynamical systems

6.5.1 Beta cell mass and beta cell function: islet is the basic unit

6.5.2 Beta cell exhaustion

6.5.3 Mathematical modeling of glucose tolerance and disease risk prediction

6.5.4 Beta cell mass and beta cell function around disease onset: is T1D a geometric phase transition?

6.5.5 Islet as a model system to study nonlinear dynamical systems

Chapter 7 Insulin release in health and disease

7.1 Minimal and multiscale models of insulin release.

7.1.1 The C-peptide minimal model during IVGTT

7.1.2 The C-peptide minimal model during OGTT

7.2 Mechanistic modelling of pancreatic insulin secretion

7.2.1 Phenomenological modelling

7.2.2 A mechanistic pancreatic model of insulin secretion

7.3 Multiscale modelling of insulin secretion

7.3.1 Multiscale analysis of the IVGTT

7.3.2 Multiscale analysis of the MTT/OGTT

7.3.3 Confronting multiscale analyses of insulin release

7.4 Type 2 diabetes and insulin release

7.4.1 The glucose minimal model during IVGTT

7.4.2 The glucose minimal model during OGTT

7.4.3 The concept of disposition index

Chapter 8 Applying systems biology to the genetics of age-of-onset dependent heterogeneity in type 1 diabetes

8.1 The design of an integrative genomics approach to study T1D age-at-onset (AAO)

8.1.1 Challenges in the genetic study of T1D

8.1.2 The design of an integrative genomics approach to study a focused problem in T1D: the age-at-onset heterogeneity in T1D

8.2 Mathematical modeling of AAO heterogeneity of T1D and disease pathway identification

8.2.1 The Copenhagen model of T1D pathogenesis and its extension

8.2.2 The extended model is able to reproduce the AAO-dependent heterogeneity

8.2.3 Critical quantitative traits, pathways and candidate disease genes

8.2.4 Bioinformatics of disease pathway identification

8.3 Candidate disease genes prioritization and validation for T1D AOO

8.3.1 Compile candidate disease genes of T1D AOO

8.3.2 Candidate gene prioritization

8.3.3 Genotyping of predicted candidate genes

8.4 Summary and discussion

Chapter 9 Immune-cell dynamics in type 1 diabetes

9.1 Introduction

9.2 Protein processing in T1D

9.2.1 The model

9.2.2 Derivation of the equation for P2

9.2.3 Protein steady states.

9.2.4 Rescaling the model

9.2.5 Interpretations of dimensionless parameters

9.2.6 Model reduction

9.2.7 Steady states and stability analysis

9.2.8 Details of parameter estimates

9.2.9 Bifurcation analysis

9.3 Phagocytosis in macrophages during T1D

9.3.1 Markov chain models

9.3.2 Model 1

9.3.3 Model comparisons

9.4 Autoimmune dynamics and transient stability

9.4.1 One-clone model

9.4.2 Model rescaling

9.4.3 Phase-plane analysis

9.4.4 Stability analysis

9.4.5 Model simulations

Chapter 10 Diabetes implications on kidneys

10.1 Introduction

10.2 Basics of transepithelial transport

10.2.1 Paracellular versus transcellular pathways

10.2.2 Passive versus active transport

10.3 Principal classes of transepithelial transporters

10.3.1 Na/K-ATPase pumps

10.3.2 Non-equilibrium thermodynamic formalism

10.4 Model equations

10.4.1 Conservation for water and solute

10.4.2 Conservation of electric charge

10.5 A simple cell model

10.6 Perspectives

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

Includes bibliographical references.

ISBN:

9780750341028

0750341025

OCLC:

1429722558