Projects / Programmes source: ARIS

Multilayer network analysis of collective cellular activity in normal and diabetic pancreatic islets

Research activity

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
Evaluation (rules)
source: COBISS
Data for the last 5 years (citations for the last 10 years) on September 30, 2023; A3 for period 2017-2021
Data for ARIS tenders ( 04.04.2019 – Programme tender, archive )
Database Linked records Citations Pure citations Average pure citations
WoS  842  43,118  38,556  45.79 
Scopus  848  45,986  41,274  48.67 
Researchers (19)
no. Code Name and surname Research area Role Period No. of publicationsNo. of publications
1.  19411  PhD Vladimir Boštjan Bregar  Materials science and technology  Researcher  2022 - 2023  105 
2.  33148  PhD Maša Čater  Biotechnology  Technical associate  2022 - 2023  102 
3.  23415  PhD Jurij Dolenšek  Metabolic and hormonal disorders  Researcher  2021 - 2023  217 
4.  28405  PhD Marko Gosak  Physics  Head  2021 - 2023  278 
5.  32334  PhD Jasmina Kerčmar  Metabolic and hormonal disorders  Researcher  2021 - 2023  41 
6.  15413  PhD Dean Korošak  Physics  Researcher  2021 - 2023  225 
7.  24423  PhD Lidija Križančić Bombek  Metabolic and hormonal disorders  Researcher  2021 - 2023  144 
8.  13159  PhD Marko Marhl  Physics  Researcher  2021 - 2023  648 
9.  34480  PhD Rene Markovič  Physics  Researcher  2021 - 2023  102 
10.  23660  Rudi Mlakar  Manufacturing technologies and systems  Technical associate  2022 - 2023 
11.  54834  Nastja Murko  Metabolic and hormonal disorders  Junior researcher  2022 - 2023 
12.  50674  Eva Paradiž Leitgeb  Metabolic and hormonal disorders  Junior researcher  2022 - 2023  32 
13.  19225  PhD Mojca Pavlin  Systems and cybernetics  Researcher  2021 - 2023  253 
14.  23428  PhD Matjaž Perc  Physics  Researcher  2021 - 2023  652 
15.  39524  PhD Viljem Pohorec  Metabolic and hormonal disorders  Researcher  2021 - 2023  62 
16.  29565  PhD Maša Skelin Klemen  Metabolic and hormonal disorders  Researcher  2022 - 2023  141 
17.  12266  PhD Marjan Slak Rupnik  Metabolic and hormonal disorders  Researcher  2021 - 2023  346 
18.  32132  PhD Andraž Stožer  Metabolic and hormonal disorders  Researcher  2021 - 2023  402 
19.  52509  Marko Šterk  Metabolic and hormonal disorders  Researcher  2021 - 2023  34 
Organisations (3)
no. Code Research organisation City Registration number No. of publicationsNo. of publications
1.  1538  University of Ljubljana, Faculty of Electrical Engineering  Ljubljana  1626965  27,388 
2.  2334  University of Maribor, Faculty of Medicine  Maribor  5089638048  16,107 
3.  2547  University of Maribor, Faculty of natural sciences and mathematics  Maribor  5089638051  17,575 
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.
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