Projects / Programmes
Multilayer network analysis of collective cellular activity in normal and diabetic pancreatic
islets
| Code |
Science |
Field |
Subfield |
| 3.07.00 |
Medical sciences |
Metabolic and hormonal disorders |
|
| Code |
Science |
Field |
| 3.02 |
Medical and Health Sciences |
Clinical medicine |
diabetes, islets of Langerhans, cellular signallization, confocal microscopy, intercellular coupling, calcium oscillations, mitochondria, cell metabolism, functional connectivity, complex networks, multilayer networks, computational models
Data for the last 5 years (citations for the last 10 years) on
April 18, 2024;
A3 for period
2018-2022
Data for ARIS tenders (
04.04.2019 – Programme tender,
archive
)
| Database |
Linked records |
Citations |
Pure citations |
Average pure citations |
| WoS |
865 |
45,850 |
41,167 |
47.59 |
| Scopus |
872 |
49,092 |
44,228 |
50.72 |
Researchers (21)
Organisations (3)
Abstract
Islets of Langerhans in the pancreas fine-tune insulin supply to the organism in response to changing metabolic demands. Lack of insulin function, due to impairment in insulin release or insulin-induced signaling or both results in diabetes mellitus, a public health threat that has become one of the most prevailing human illnesses world-wide, consuming around 10 % of healthcare budgets of westernized societies. A proper insulin supply is regulated by a complex multicellular dynamics occurring between insulin-secreting beta cells and other endocrine cell types that underlie regulated hormone secretion. Understanding how cell sub-populations in islets impact the function of the overall system at a higher organizational level is very challenging. Beta cells are multimodal oscillatory units that are intrinsically highly heterogeneous, they are electrically coupled into a functional syncytium and they are additionally engaged in homologous as well as heterologous paracrine interactions. Most importantly, intercellular connectivity within islets is not only necessary for ensuring coordinated cellular behavior resulting in proper pulsatile secretory responses, but its perturbations are also linked to metabolic diseases and impaired insulin secretion. Until recently, the richness of the aforementioned cell-cell interactions, which play a vital role in the pathogenesis of diabetes, was hard to assess. As an experimental solution, functional multicellular imaging in tissue slices introduced by our group made it possible to assess rather noninvasively the function of a large number of cells simultaneously over prolonged periods of time. However, the data acquired by high-frequency confocal microscopy techniques is rather complex and requires advanced computational resources that help to process and interpret the multicellular data. In the proposed project, we aim to push further these frontiers by combining innovative experimental approaches relying especially on high-quality confocal laser-scanning imaging in acute pancreatic tissue slices with cutting edge computational modelling and network science approaches to investigate the pancreatic cell behavior in their multicellular environment. By this means, we intend to explore the collective multifaceted oscillatory behavior of beta cells in mouse and human islets, link it with the mitochondrial activity and secretory responses and quantify different aspects of changes in cellular signaling associated with the pathogenesis of diabetes. Particular attention will be given to the crosstalk between alpha and beta cells and on how novel antidiabetic drugs and other pharmacological substances affect the complex dynamical patterns within the islets. We firmly believe that the inherently interdisciplinary nature of the proposed project, combining physiology and medicine with computational physics, is a great advantage and parallels well with the latest emerging trends in medicine and biomedical research. The expected findings on endocrine cell networks will unveil novel fundamental organizing principles in healthy and diabetic mouse and human islets, which could not be determined with conventional biomedical methods. This shall importantly validate the translational relevance of mouse models for the human situation, deepen our basic knowledge on islet (patho)biology, and also suggest new potential therapeutic targets for the prevention and treatment of diabetes, which are necessary to reduce the toll of this disease on individuals and healthcare systems.
