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8 Research products, page 1 of 1

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  • Open Access
    Authors: 
    Zizic, Jovana B.; Vukovic, Nenad L.; Jadranin, Milka; Anđelković, Boban D.; Tešević, Vele; Kacaniova, Miroslava M.; Sukdolak, Slobodan B.; Marković, Snežana D.;
    Publisher: Wiley, Hoboken
    Country: Serbia
    Project: MESTD | Natural products of wild,... (172053), MESTD | Preclinical investigation... (41010)

    BACKGROUND Propolis is a complex resinous sticky substance that honeybees collect from buds and exudates of various plants. Owing to its versatile biological and pharmacological activities, propolis is widely used in medicines, cosmetics and foods. The aim of this study was to evaluate the cytotoxic and antioxidative effects of various ethanolic extracts of propolis (EEPs) on human colon cancer cell line HCT-116 and compare them with their composition determined by HPLC-DAD. RESULTS The most abundant flavonoids in all samples were chrysin, pinocembrin and galangin (12.697-40.811 mu gmg(-1)), while the main phenolic acids were caffeic acid, ferulic acid and isoferulic acid. Dose- and time-dependent inhibition of growth of HCT-116 cells was observed for all propolis samples, with IC50 values ranging from 26.33 to 143.09 mu gmL(-1). Differences in cytotoxic activity of propolis samples were associated with differences in their composition. All EEP samples reduced both superoxide anion radical and nitrite levels and also had strong DPPH-scavenging activity. CONCLUSION All tested propolis samples had pronounced cytotoxic and antioxidative activities. This is the peer-reviewed version of the following article: Žižić, J. B.; Vuković, N. L.; Jadranin, M.; Anđelković, B. D.; Tešević, V.; Kacaniova, M. M.; Sukdolak, S. B.; Markovic, S. D. Chemical Composition, Cytotoxic and Antioxidative Activities of Ethanolic Extracts of Propolis on HCT-116 Cell Line. Journal of the Science of Food and Agriculture 2013, 93 (12), 3001–3009. [https://doi.org/10.1002/jsfa.6132] [http://cer.ihtm.bg.ac.rs/handle/123456789/1213]

  • Publication . Other literature type . Article . Preprint . 2019
    Open Access
    Authors: 
    Marija Mitrović Dankulov; Bosiljka Tadić; Roderick Melnik;
    Country: Spain
    Project: MESTD | Modeling and Numerical Si... (171017)

    Cooperative self-assembly can result in complex nano-networks with new hyperbolic geometry. However, the relation between the hyperbolicity and spectral and dynamical features of these structures remains unclear. Using the model of aggregation of simplexes introduced in I [Sci. Rep., 8:1987, 2018], here we study topological and spectral properties of a large class of self-assembled structures consisting of monodisperse building blocks (cliques of size $n=3,4,5,6$) which self-assemble via sharing the geometrical shapes of a lower order. The size of the shared sub-structure is tunned by varying the chemical affinity $\nu$ such that for significant positive $\nu$ sharing the largest face is the most probable, while for $\nu 4$ can be reached for $n\geq 5$ and sufficiently large $\nu$. For the aggregates of triangles and tetrahedra, the spectral dimension remains in the range $d_s\in [2,4)$, as well as for the higher cliques at vanishing affinity. On the other end, for $\nu < 0$, we find $d_s\eqsim 1.57$ independently on $n$. Moreover, the spectral distribution of the normalised Laplacian eigenvalues has a characteristic shape with peaks and a pronounced minimum, representing the hierarchical architecture of the simplicial complexes. These findings show how the structures compatible with complex dynamical properties can be assembled by controlling the higher-order connectivity among the building blocks. Comment: 9 pages, 7 figures included

  • Open Access English
    Authors: 
    Bosiljka Tadić; Marija Mitrović Dankulov; Roderick Melnik;
    Project: MESTD | Modeling and Numerical Si... (171017)

    In the online social dynamics, a robust scaling behaviour appears as a key feature of many collaborative efforts that lead to the new social value. The underlying empirical data thus offer a unique opportunity to study the origin of self-organised criticality in social systems. In contrast to physical systems in the laboratory, various human attributes of the actors play an essential role in the process along with the contents (cognitive, emotional) of the communicated artefacts. As a prototypal example, we consider the social endeavour of knowledge creation via Questions\ \& Answers (Q\&A). Using a large empirical dataset from one of such Q\&A sites and theoretical modelling, we examine the temporal correlations at all scales and the role of cognitive contents to the avalanches of the knowledge creation process. Our analysis shows that the long-range correlations and the event clustering are primarily determined by the universal social dynamics, providing the external driving of the system by the arrival of new users. While the involved cognitive contents (systematically annotated in the data and observed in the model) are crucial for a fine structure of the developing knowledge networks, they only affect the values of the scaling exponents and the geometry of large avalanches and shape the multifractal spectrum. Furthermore, we find that the level of the activity of the communities that share the knowledge correlates with the fluctuations of the innovation rate, implying that the increase of innovation may serve as the active principle of self-organisation. To identify relevant parameters and unravel the role of the network evolution underlying the process in the social system under consideration, we compare the social avalanches to the avalanche sequences occurring in the field-driven physical model of disordered solids. 14 pages, 9 figures

  • Open Access
    Authors: 
    Marija Mitrović Dankulov; Roderick Melnik; Bosiljka Tadić;
    Publisher: Springer Science and Business Media LLC
    Project: MESTD | Modeling and Numerical Si... (171017)

    Collective knowledge as a social value may arise in cooperation among actors whose individual expertise is limited. The process of knowledge creation requires meaningful, logically coordinated interactions, which represents a challenging problem to physics and social dynamics modeling. By combining two-scale dynamics model with empirical data analysis from a well-known Questions & Answers system Mathematics, we show that this process occurs as a collective phenomenon in an enlarged network (of actors and their artifacts) where the cognitive recognition interactions are properly encoded. The emergent behavior is quantified by the information divergence and innovation advancing of knowledge over time and the signatures of self-organization and knowledge sharing communities. These measures elucidate the impact of each cognitive element and the individual actor’s expertise in the collective dynamics. The results are relevant to stochastic processes involving smart components and to collaborative social endeavors, for instance, crowdsourcing scientific knowledge production with online games.

  • Open Access
    Authors: 
    Milenković, Milica R.; Papastavrou, Agyro T.; Radanović, Dušanka D.; Pevec, Andrej; Jagličić, Zvonko; Zlatar, Matija; Gruden-Pavlović, Maja; Vougioukalakis, Georgios C.; Turel, Iztok; Anđelković, Katarina K.; +1 more
    Publisher: Elsevier
    Country: Serbia
    Project: MESTD | Interactions of natural p... (172055)

    Related to accepted version: [http://cherry.chem.bg.ac.rs/handle/123456789/2865] Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2858] Supplementary material for: [https://www.sciencedirect.com/science/article/pii/S0277538719301664?via%3Dihub]

  • Closed Access
    Authors: 
    Dragan Jovanovic; Matjaž Šraml; Boško Matović; Spasoje Mićić;
    Publisher: Elsevier BV
    Project: MESTD | Development and applicati... (36007)

    The present study deals with the problem of speeding behavior on rural roads. The purpose of the paper is to examine the construct validity and the internal consistency and reliability of a questionnaire that measures the determinants of speeding behavior. In addition, it aimed to test the predictive validity of a modified theoretical framework of a theory of planned behavior (TPB) in relation to speeding behavior. A total of 546 car drivers from five local communities in the Republic of Srpska successfully completed the questionnaire after reading the scenario. The principal component analysis revealed seven components interpreted as: personal norm, perceived behavioral control, affective attitude toward speeding, subjective norm, habit, descriptive norm, and cognitive attitude toward speeding. A speeding behavior model was developed by structural equation modeling. Personal norm, subjective norm, and affective attitudes were shown to be important variables within the modified TPB in understanding speeding behavior. Overall, the present findings provide significant support for the concept of the modified theoretical framework of TPB in relation to speeding behavior on rural roads. Implications for a speeding behavior model and interventions are discussed.

  • Publication . Article . Other literature type . 2019
    Open Access English
    Authors: 
    Bosiljka Tadić; Miroslav Andjelković; Roderick Melnik;
    Publisher: Nature Portfolio
    Countries: Spain, Serbia
    Project: MESTD | Advanced analytical, nume... (174014), NSERC

    Mapping the brain imaging data to networks, where nodes represent anatomical brain regions and edges indicate the occurrence of fiber tracts between them, has enabled an objective graph-theoretic analysis of human connectomes. However, the latent structure on higher-order interactions remains unexplored, where many brain regions act in synergy to perform complex functions. Here we use the simplicial complexes description of human connectome, where the shared simplexes encode higher-order relationships between groups of nodes. We study consensus connectome of 100 female (F-connectome) and of 100 male (M-connectome) subjects that we generated from the Budapest Reference Connectome Server v3.0 based on data from the Human Connectome Project. Our analysis reveals that the functional geometry of the common F&M-connectome coincides with the M-connectome and is characterized by a complex architecture of simplexes to the 14th order, which is built in six anatomical communities, and linked by short cycles. The F-connectome has additional edges that involve different brain regions, thereby increasing the size of simplexes and introducing new cycles. Both connectomes contain characteristic subjacent graphs that make them 3/2-hyperbolic. These results shed new light on the functional architecture of the brain, suggesting that insightful differences among connectomes are hidden in their higher-order connectivity. © 2019, The Author(s).

  • Open Access English
    Authors: 
    Miroslav Andjelković; Bosiljka Tadić; Marija Mitrović Dankulov; Milan Rajković; Roderick Melnik;
    Publisher: Public Library of Science (PLoS)
    Country: Serbia
    Project: MESTD | Modeling and Numerical Si... (171017), MESTD | Advanced analytical, nume... (174014), NSERC

    The communication processes of knowledge creation represent a particular class of human dynamics where the expertise of individuals plays a substantial role, thus offering a unique possibility to study the structure of knowledge networks from online data. Here, we use the empirical evidence from questions-and-answers in mathematics to analyse the emergence of the network of knowledge contents (or tags) as the individual experts use them in the process. After removing extra edges from the network-associated graph, we apply the methods of algebraic topology of graphs to examine the structure of higher-order combinatorial spaces in networks for four consecutive time intervals. We find that the ranking distributions of the suitably scaled topological dimensions of nodes fall into a unique curve for all time intervals and filtering levels, suggesting a robust architecture of knowledge networks. Moreover, these networks preserve the logical structure of knowledge within emergent communities of nodes, labeled according to a standard mathematical classification scheme. Further, we investigate the appearance of new contents over time and their innovative combinations, which expand the knowledge network. In each network, we identify an innovation channel as a subgraph of triangles and larger simplices to which new tags attach. Our results show that the increasing topological complexity of the innovation channels contributes to networks architecture over different time periods, and is consistent with temporal correlations of the occurrence of new tags. The methodology applies to a wide class of data with the suitable temporal resolution and clearly identified knowledge-content units. Supplementary material: Dataset [https://vinar.vin.bg.ac.rs/handle/123456789/9420] Supplementary material: Dataset [https://vinar.vin.bg.ac.rs/handle/123456789/9421]

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Include:
The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
8 Research products, page 1 of 1
  • Open Access
    Authors: 
    Zizic, Jovana B.; Vukovic, Nenad L.; Jadranin, Milka; Anđelković, Boban D.; Tešević, Vele; Kacaniova, Miroslava M.; Sukdolak, Slobodan B.; Marković, Snežana D.;
    Publisher: Wiley, Hoboken
    Country: Serbia
    Project: MESTD | Natural products of wild,... (172053), MESTD | Preclinical investigation... (41010)

    BACKGROUND Propolis is a complex resinous sticky substance that honeybees collect from buds and exudates of various plants. Owing to its versatile biological and pharmacological activities, propolis is widely used in medicines, cosmetics and foods. The aim of this study was to evaluate the cytotoxic and antioxidative effects of various ethanolic extracts of propolis (EEPs) on human colon cancer cell line HCT-116 and compare them with their composition determined by HPLC-DAD. RESULTS The most abundant flavonoids in all samples were chrysin, pinocembrin and galangin (12.697-40.811 mu gmg(-1)), while the main phenolic acids were caffeic acid, ferulic acid and isoferulic acid. Dose- and time-dependent inhibition of growth of HCT-116 cells was observed for all propolis samples, with IC50 values ranging from 26.33 to 143.09 mu gmL(-1). Differences in cytotoxic activity of propolis samples were associated with differences in their composition. All EEP samples reduced both superoxide anion radical and nitrite levels and also had strong DPPH-scavenging activity. CONCLUSION All tested propolis samples had pronounced cytotoxic and antioxidative activities. This is the peer-reviewed version of the following article: Žižić, J. B.; Vuković, N. L.; Jadranin, M.; Anđelković, B. D.; Tešević, V.; Kacaniova, M. M.; Sukdolak, S. B.; Markovic, S. D. Chemical Composition, Cytotoxic and Antioxidative Activities of Ethanolic Extracts of Propolis on HCT-116 Cell Line. Journal of the Science of Food and Agriculture 2013, 93 (12), 3001–3009. [https://doi.org/10.1002/jsfa.6132] [http://cer.ihtm.bg.ac.rs/handle/123456789/1213]

  • Publication . Other literature type . Article . Preprint . 2019
    Open Access
    Authors: 
    Marija Mitrović Dankulov; Bosiljka Tadić; Roderick Melnik;
    Country: Spain
    Project: MESTD | Modeling and Numerical Si... (171017)

    Cooperative self-assembly can result in complex nano-networks with new hyperbolic geometry. However, the relation between the hyperbolicity and spectral and dynamical features of these structures remains unclear. Using the model of aggregation of simplexes introduced in I [Sci. Rep., 8:1987, 2018], here we study topological and spectral properties of a large class of self-assembled structures consisting of monodisperse building blocks (cliques of size $n=3,4,5,6$) which self-assemble via sharing the geometrical shapes of a lower order. The size of the shared sub-structure is tunned by varying the chemical affinity $\nu$ such that for significant positive $\nu$ sharing the largest face is the most probable, while for $\nu 4$ can be reached for $n\geq 5$ and sufficiently large $\nu$. For the aggregates of triangles and tetrahedra, the spectral dimension remains in the range $d_s\in [2,4)$, as well as for the higher cliques at vanishing affinity. On the other end, for $\nu < 0$, we find $d_s\eqsim 1.57$ independently on $n$. Moreover, the spectral distribution of the normalised Laplacian eigenvalues has a characteristic shape with peaks and a pronounced minimum, representing the hierarchical architecture of the simplicial complexes. These findings show how the structures compatible with complex dynamical properties can be assembled by controlling the higher-order connectivity among the building blocks. Comment: 9 pages, 7 figures included

  • Open Access English
    Authors: 
    Bosiljka Tadić; Marija Mitrović Dankulov; Roderick Melnik;
    Project: MESTD | Modeling and Numerical Si... (171017)

    In the online social dynamics, a robust scaling behaviour appears as a key feature of many collaborative efforts that lead to the new social value. The underlying empirical data thus offer a unique opportunity to study the origin of self-organised criticality in social systems. In contrast to physical systems in the laboratory, various human attributes of the actors play an essential role in the process along with the contents (cognitive, emotional) of the communicated artefacts. As a prototypal example, we consider the social endeavour of knowledge creation via Questions\ \& Answers (Q\&A). Using a large empirical dataset from one of such Q\&A sites and theoretical modelling, we examine the temporal correlations at all scales and the role of cognitive contents to the avalanches of the knowledge creation process. Our analysis shows that the long-range correlations and the event clustering are primarily determined by the universal social dynamics, providing the external driving of the system by the arrival of new users. While the involved cognitive contents (systematically annotated in the data and observed in the model) are crucial for a fine structure of the developing knowledge networks, they only affect the values of the scaling exponents and the geometry of large avalanches and shape the multifractal spectrum. Furthermore, we find that the level of the activity of the communities that share the knowledge correlates with the fluctuations of the innovation rate, implying that the increase of innovation may serve as the active principle of self-organisation. To identify relevant parameters and unravel the role of the network evolution underlying the process in the social system under consideration, we compare the social avalanches to the avalanche sequences occurring in the field-driven physical model of disordered solids. 14 pages, 9 figures

  • Open Access
    Authors: 
    Marija Mitrović Dankulov; Roderick Melnik; Bosiljka Tadić;
    Publisher: Springer Science and Business Media LLC
    Project: MESTD | Modeling and Numerical Si... (171017)

    Collective knowledge as a social value may arise in cooperation among actors whose individual expertise is limited. The process of knowledge creation requires meaningful, logically coordinated interactions, which represents a challenging problem to physics and social dynamics modeling. By combining two-scale dynamics model with empirical data analysis from a well-known Questions & Answers system Mathematics, we show that this process occurs as a collective phenomenon in an enlarged network (of actors and their artifacts) where the cognitive recognition interactions are properly encoded. The emergent behavior is quantified by the information divergence and innovation advancing of knowledge over time and the signatures of self-organization and knowledge sharing communities. These measures elucidate the impact of each cognitive element and the individual actor’s expertise in the collective dynamics. The results are relevant to stochastic processes involving smart components and to collaborative social endeavors, for instance, crowdsourcing scientific knowledge production with online games.

  • Open Access
    Authors: 
    Milenković, Milica R.; Papastavrou, Agyro T.; Radanović, Dušanka D.; Pevec, Andrej; Jagličić, Zvonko; Zlatar, Matija; Gruden-Pavlović, Maja; Vougioukalakis, Georgios C.; Turel, Iztok; Anđelković, Katarina K.; +1 more
    Publisher: Elsevier
    Country: Serbia
    Project: MESTD | Interactions of natural p... (172055)

    Related to accepted version: [http://cherry.chem.bg.ac.rs/handle/123456789/2865] Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2858] Supplementary material for: [https://www.sciencedirect.com/science/article/pii/S0277538719301664?via%3Dihub]

  • Closed Access
    Authors: 
    Dragan Jovanovic; Matjaž Šraml; Boško Matović; Spasoje Mićić;
    Publisher: Elsevier BV
    Project: MESTD | Development and applicati... (36007)

    The present study deals with the problem of speeding behavior on rural roads. The purpose of the paper is to examine the construct validity and the internal consistency and reliability of a questionnaire that measures the determinants of speeding behavior. In addition, it aimed to test the predictive validity of a modified theoretical framework of a theory of planned behavior (TPB) in relation to speeding behavior. A total of 546 car drivers from five local communities in the Republic of Srpska successfully completed the questionnaire after reading the scenario. The principal component analysis revealed seven components interpreted as: personal norm, perceived behavioral control, affective attitude toward speeding, subjective norm, habit, descriptive norm, and cognitive attitude toward speeding. A speeding behavior model was developed by structural equation modeling. Personal norm, subjective norm, and affective attitudes were shown to be important variables within the modified TPB in understanding speeding behavior. Overall, the present findings provide significant support for the concept of the modified theoretical framework of TPB in relation to speeding behavior on rural roads. Implications for a speeding behavior model and interventions are discussed.

  • Publication . Article . Other literature type . 2019
    Open Access English
    Authors: 
    Bosiljka Tadić; Miroslav Andjelković; Roderick Melnik;
    Publisher: Nature Portfolio
    Countries: Spain, Serbia
    Project: MESTD | Advanced analytical, nume... (174014), NSERC

    Mapping the brain imaging data to networks, where nodes represent anatomical brain regions and edges indicate the occurrence of fiber tracts between them, has enabled an objective graph-theoretic analysis of human connectomes. However, the latent structure on higher-order interactions remains unexplored, where many brain regions act in synergy to perform complex functions. Here we use the simplicial complexes description of human connectome, where the shared simplexes encode higher-order relationships between groups of nodes. We study consensus connectome of 100 female (F-connectome) and of 100 male (M-connectome) subjects that we generated from the Budapest Reference Connectome Server v3.0 based on data from the Human Connectome Project. Our analysis reveals that the functional geometry of the common F&M-connectome coincides with the M-connectome and is characterized by a complex architecture of simplexes to the 14th order, which is built in six anatomical communities, and linked by short cycles. The F-connectome has additional edges that involve different brain regions, thereby increasing the size of simplexes and introducing new cycles. Both connectomes contain characteristic subjacent graphs that make them 3/2-hyperbolic. These results shed new light on the functional architecture of the brain, suggesting that insightful differences among connectomes are hidden in their higher-order connectivity. © 2019, The Author(s).

  • Open Access English
    Authors: 
    Miroslav Andjelković; Bosiljka Tadić; Marija Mitrović Dankulov; Milan Rajković; Roderick Melnik;
    Publisher: Public Library of Science (PLoS)
    Country: Serbia
    Project: MESTD | Modeling and Numerical Si... (171017), MESTD | Advanced analytical, nume... (174014), NSERC

    The communication processes of knowledge creation represent a particular class of human dynamics where the expertise of individuals plays a substantial role, thus offering a unique possibility to study the structure of knowledge networks from online data. Here, we use the empirical evidence from questions-and-answers in mathematics to analyse the emergence of the network of knowledge contents (or tags) as the individual experts use them in the process. After removing extra edges from the network-associated graph, we apply the methods of algebraic topology of graphs to examine the structure of higher-order combinatorial spaces in networks for four consecutive time intervals. We find that the ranking distributions of the suitably scaled topological dimensions of nodes fall into a unique curve for all time intervals and filtering levels, suggesting a robust architecture of knowledge networks. Moreover, these networks preserve the logical structure of knowledge within emergent communities of nodes, labeled according to a standard mathematical classification scheme. Further, we investigate the appearance of new contents over time and their innovative combinations, which expand the knowledge network. In each network, we identify an innovation channel as a subgraph of triangles and larger simplices to which new tags attach. Our results show that the increasing topological complexity of the innovation channels contributes to networks architecture over different time periods, and is consistent with temporal correlations of the occurrence of new tags. The methodology applies to a wide class of data with the suitable temporal resolution and clearly identified knowledge-content units. Supplementary material: Dataset [https://vinar.vin.bg.ac.rs/handle/123456789/9420] Supplementary material: Dataset [https://vinar.vin.bg.ac.rs/handle/123456789/9421]