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Obtaining statistical data

Projects / Programmes source: ARIS

Cell and tissue networks

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Periods
January 1, 2019 - December 31, 2027
Research activity

Code Science Field Subfield
3.07.00  Medical sciences  Metabolic and hormonal disorders   
1.02.00  Natural sciences and mathematics  Physics   

Code Science Field
B000  Biomedical sciences   

Code Science Field
3.02  Medical and Health Sciences  Clinical medicine 
1.03  Natural Sciences  Physical sciences 
Keywords
diabetes mellitus, cytosolic calcium, membrane potential, syncytium, confocal microscopy, complex network theory, spin glass model, phase flipping model, random matrix theory, time series analysis, big data, advanced analytics, networks
Evaluation (rules)
source: COBISS
Evaluation of bibliographic research performance indicators according to ARIS methodology
Points
4,643.91
A''
600.31
A'
2,563
A1/2
3,380.21
CI10
6,411
CImax
734
h10
36
A1
16.73
A3
0.44
Data for the last 5 years (citations for the last 10 years) on April 24, 2024; A3 for period 2018-2022
Data for ARIS tenders ( 04.04.2019 – Programme tender , archive )
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Database Linked records Citations Pure citations Average pure citations
WoS  277  7,901  6,811  24.59 
Scopus  269  8,635  7,477  27.8 
Researchers (16)
no. Code Name and surname Research area Role Period No. of publications
1.  33148  PhD Maša Čater  Biotechnology  Technical associate  2021 - 2022  109 
2.  23415  PhD Jurij Dolenšek  Metabolic and hormonal disorders  Researcher  2019 - 2024  233 
3.  28405  PhD Marko Gosak  Physics  Researcher  2019 - 2024  287 
4.  32334  PhD Jasmina Kerčmar  Metabolic and hormonal disorders  Researcher  2019 - 2024  46 
5.  15413  PhD Dean Korošak  Physics  Researcher  2019 - 2024  232 
6.  58052  Polona Kovačič  Metabolic and hormonal disorders  Junior researcher  2023 - 2024  0 
7.  24423  PhD Lidija Križančić Bombek  Metabolic and hormonal disorders  Researcher  2019 - 2024  157 
8.  39525  Zvezdana Lukaček    Technical associate  2023 - 2024  0 
9.  23660  Rudi Mlakar  Manufacturing technologies and systems  Technical associate  2019 - 2024  4 
10.  54834  Nastja Murko  Metabolic and hormonal disorders  Junior researcher  2020 - 2024  10 
11.  50674  PhD Eva Paradiž Leitgeb  Metabolic and hormonal disorders  Junior researcher  2019 - 2024  38 
12.  39524  PhD Viljem Pohorec  Metabolic and hormonal disorders  Researcher  2023 - 2024  68 
13.  20340  PhD Simon Sedej  Metabolic and hormonal disorders  Researcher  2019 - 2024  50 
14.  29565  PhD Maša Skelin Klemen  Metabolic and hormonal disorders  Researcher  2019 - 2024  151 
15.  12266  PhD Marjan Slak Rupnik  Metabolic and hormonal disorders  Former/secondary head  2019 - 2022  350 
16.  32132  PhD Andraž Stožer  Metabolic and hormonal disorders  Head  2019 - 2024  426 
Organisations (1)
no. Code Research organisation City Registration number No. of publications
1.  2334  University of Maribor, Faculty of Medicine  Maribor  5089638048  16,526 
Abstract
Collective activity presents a basic mode of operation in complex cell and tissue network rhythmicity and overall activity. Recently, technological advancements in biomarkers, microscopy optics, confocal scanning speed and novel, more sensitive detection systems allowed us to gather experimental data that could be assessed using various advanced computational tools (theory of complex networks, spin glass model, phase flipping model, random matrix theory, etc) and thus better understand organizational and functional principles of living organs across various scales. Based on previously published results, communication among cells through both short-range or long-range interactions shall be further upgraded with various forms of extracellular signaling by taking into account microfluidic principles and Big Data analytical solutions. Such an analysis shall eventually make it possible to stream calcium kinetics in realtime during varying physiological and pharmacological stimulation regimes as well as in pathophysiological conditions. A combination of intracellular dynamics and microfluidic analysis will aid reconstruction of functional multicellular 3D models of tissues and yield understanding of physiology and pathophysiology in the context of a spatial organization and signaling landscape. Access to human tissue will enable a direct evaluation of the relevance of results obtained in animal models and is important from an evolutionary biology point of view as well as from the perspective of possible future clinical application. The results of our experiments and network analyses in the framework of the proposed research program shall thus be applied to help prevent, diagnose and treat important health issues. Initial emphasis shall be on studying pancreatic islets, endocrine organs delivering critically important hormones, such as insulin, to other cellular systems in a body. Impairment in insulin signaling results in diabetes mellitus, a public health threat that is expected to become one of the most prevailing human illnesses.
Significance for science
The tissue slice preparation was due to its complexity rarely used tool to study tissue function. We have recently established a novel preparation to study the endocrine function in pancreas, its endocrine part being vital for the control of the blood nutrients and its dysfunction being critical in severe diseases, like diabetes mellitus. Our preparation is the first, where the electrical activity, oscillations in the concentration of free cytosolic calcium and hormone (e.g. insulin) release and can be assessed in the intact tissue environment with a single cell resolution and where important cellular characteristics, like ion channels and metabolic activity can be assessed together with the secretory competence. We expect that the use of wild type, metabolically compromised rodent models, gene ablated animals and human samples will give us key information of the defects causing an endocrine disease, like diabetes mellitus and help us develop new methods prevention, diagnostics and treatment. We innovatively optimized approaches for the use of fluorescent markers of dynamic changes in cytosolic calcium concentration and membrane potential. Using an interdisciplinary approach we shall upgrade original experimental data with advanced computational approaches (theory of complex networks, spin glass model, phase flipping model, random matrix theory, Big Data analysis).
Significance for the country
Endocrine disorders, like diabetes mellitus (DM), are widely spread in the developed world, where the Republic of Slovenia is no exception. Approximately 8% of the European population and more than 415 million people worldwide are afflicted by DM and due to its rising prevalence in developed as well as in developing countries this disease poses an ever greater public health problem (source: International Diabetes Federation, 2015). The etiology of DM is only insufficiently understood but it is considered to be a omnigenic and multifactorial disease that usually appears in middle age and is exacerbated by obesity. Due to epidemic dimensions of the disease and the way how it is diagnosed and treated at the moment it presents a serious threat for the public health system. Alternative and cost effective diagnosis and therapy of endocrine disease, like diabetes mellitus will be of significant advantage to unburden the public health system.
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