TY  - JOUR
AU  - Virijević, Katarina
AU  - Živanović, Marko N.
AU  - Nikolić, Dalibor
AU  - Milivojević, Nevena
AU  - Pavić, Jelena
AU  - Morić, Ivana
AU  - Šenerović, Lidija
AU  - Dragačević, Luka
AU  - Thurner, Philipp J.
AU  - Rufin, Manuel
AU  - Andriotis, Orestis G.
AU  - Ljujić, Biljana
AU  - Miletić Kovačević, Marina
AU  - Papić, Miloš
AU  - Filipović, Nenad
PY  - 2024
UR  - https://doi.org/10.1021/acsami.4c03266
UR  - https://imagine.imgge.bg.ac.rs/handle/123456789/2360
AB  - Here, an artificial intelligence (AI)-based approach was employed to optimize the production of electrospun scaffolds for in vivo wound healing applications. By combining polycaprolactone (PCL) and poly(ethylene glycol) (PEG) in various concentration ratios, dissolved in chloroform (CHCl3) and dimethylformamide (DMF), 125 different polymer combinations were created. From these polymer combinations, electrospun nanofiber meshes were produced and characterized structurally and mechanically via microscopic techniques, including chemical composition and fiber diameter determination. Subsequently, these data were used to train a neural network, creating an AI model to predict the optimal scaffold production solution. Guided by the predictions and experimental outcomes of the AI model, the most promising scaffold for further in vitro analyses was identified. Moreover, we enriched this selected polymer combination by incorporating antibiotics, aiming to develop electrospun nanofiber scaffolds tailored for in vivo wound healing applications. Our study underscores three noteworthy conclusions: (i) the application of AI is pivotal in the fields of material and biomedical sciences, (ii) our methodology provides an effective blueprint for the initial screening of biomedical materials, and (iii) electrospun PCL/PEG antibiotic-bearing scaffolds exhibit outstanding results in promoting neoangiogenesis and facilitating in vivo wound treatment.
PB  - American Chemical Society
T2  - ACS Applied Materials & Interfaces
T1  - AI-Driven Optimization of PCL/PEG Electrospun Scaffolds for Enhanced In Vivo Wound Healing
DO  - 10.1021/acsami.4c03266
ER  - 

@article{
author = "Virijević, Katarina and Živanović, Marko N. and Nikolić, Dalibor and Milivojević, Nevena and Pavić, Jelena and Morić, Ivana and Šenerović, Lidija and Dragačević, Luka and Thurner, Philipp J. and Rufin, Manuel and Andriotis, Orestis G. and Ljujić, Biljana and Miletić Kovačević, Marina and Papić, Miloš and Filipović, Nenad",
year = "2024",
abstract = "Here, an artificial intelligence (AI)-based approach was employed to optimize the production of electrospun scaffolds for in vivo wound healing applications. By combining polycaprolactone (PCL) and poly(ethylene glycol) (PEG) in various concentration ratios, dissolved in chloroform (CHCl3) and dimethylformamide (DMF), 125 different polymer combinations were created. From these polymer combinations, electrospun nanofiber meshes were produced and characterized structurally and mechanically via microscopic techniques, including chemical composition and fiber diameter determination. Subsequently, these data were used to train a neural network, creating an AI model to predict the optimal scaffold production solution. Guided by the predictions and experimental outcomes of the AI model, the most promising scaffold for further in vitro analyses was identified. Moreover, we enriched this selected polymer combination by incorporating antibiotics, aiming to develop electrospun nanofiber scaffolds tailored for in vivo wound healing applications. Our study underscores three noteworthy conclusions: (i) the application of AI is pivotal in the fields of material and biomedical sciences, (ii) our methodology provides an effective blueprint for the initial screening of biomedical materials, and (iii) electrospun PCL/PEG antibiotic-bearing scaffolds exhibit outstanding results in promoting neoangiogenesis and facilitating in vivo wound treatment.",
publisher = "American Chemical Society",
journal = "ACS Applied Materials & Interfaces",
title = "AI-Driven Optimization of PCL/PEG Electrospun Scaffolds for Enhanced In Vivo Wound Healing",
doi = "10.1021/acsami.4c03266"
}

Virijević, K., Živanović, M. N., Nikolić, D., Milivojević, N., Pavić, J., Morić, I., Šenerović, L., Dragačević, L., Thurner, P. J., Rufin, M., Andriotis, O. G., Ljujić, B., Miletić Kovačević, M., Papić, M.,& Filipović, N.. (2024). AI-Driven Optimization of PCL/PEG Electrospun Scaffolds for Enhanced In Vivo Wound Healing. in ACS Applied Materials & Interfaces
American Chemical Society..
https://doi.org/10.1021/acsami.4c03266

Virijević K, Živanović MN, Nikolić D, Milivojević N, Pavić J, Morić I, Šenerović L, Dragačević L, Thurner PJ, Rufin M, Andriotis OG, Ljujić B, Miletić Kovačević M, Papić M, Filipović N. AI-Driven Optimization of PCL/PEG Electrospun Scaffolds for Enhanced In Vivo Wound Healing. in ACS Applied Materials & Interfaces. 2024;.
doi:10.1021/acsami.4c03266 .

Virijević, Katarina, Živanović, Marko N., Nikolić, Dalibor, Milivojević, Nevena, Pavić, Jelena, Morić, Ivana, Šenerović, Lidija, Dragačević, Luka, Thurner, Philipp J., Rufin, Manuel, Andriotis, Orestis G., Ljujić, Biljana, Miletić Kovačević, Marina, Papić, Miloš, Filipović, Nenad, "AI-Driven Optimization of PCL/PEG Electrospun Scaffolds for Enhanced In Vivo Wound Healing" in ACS Applied Materials & Interfaces (2024),
https://doi.org/10.1021/acsami.4c03266 . .

TY  - CONF
AU  - Virijević, Katarina
AU  - Živanović, Marko
AU  - Gazdić Janković, Marina
AU  - Ramović Hamzagić, Amra
AU  - Milivojević, Nevena
AU  - Pecić, Katarina
AU  - Šeklić, Dragana
AU  - Jovanović, Milena
AU  - Kastratović, Nikolina
AU  - Mirić, Ana
AU  - Đukić, Tijana
AU  - Petrović, Ivica
AU  - Jurišić, Vladimir
AU  - Ljujić, Biljana
AU  - Filipović, Nenad
PY  - 2023
UR  - https://belbi.bg.ac.rs/
UR  - https://imagine.imgge.bg.ac.rs/handle/123456789/2010
AB  - Biomedicine is a multidisciplinary branch of science that requires a clear approach to the
study and analysis of various life processes necessary for a deeper understanding of
human health. This research focuses on the use of numerical simulations with the aim of an
improved comprehension of cancer viability and apoptosis during treatment with commercial
chemotherapeutic agents. In recent times, the usage of numerical models was successfully
applied to predict the behavior of tumors. This study includes a wide range of numerical results
that have been obtained by examining cell viability in real-time, determining the type of cell
death and the genetic factors that control these processes. The results of the in vitro test were
used to develop a numerical model that provides a new perspective on the proposed problem.
In this study, colon, and breast cancer cell lines (HCT-116 and MDA-MB-231), as well as healthy
lung fibroblast cell line (MRC-5) were treated with commercial chemotherapeutic agents. The
obtained results showed a decrease in viability and the occurrence of predominantly late
apoptosis upon treatment, as well as a strong correlation between parameters. A mathematical
model was developed and used to gain a better understanding of the investigated processes.
This method can accurately simulate the behavior of cancer cells and reliably predict their
growth.
PB  - Belgrade : Institute of molecular genetics and genetic engineering
C3  - 4th Belgrade Bioinformatics Conference
T1  - Numerical and Biological Modeling Approach in the Analysis of the Cancer Viability and Apoptosis
EP  - 70
SP  - 70
VL  - 4
UR  - https://hdl.handle.net/21.15107/rcub_imagine_2010
ER  - 

@conference{
author = "Virijević, Katarina and Živanović, Marko and Gazdić Janković, Marina and Ramović Hamzagić, Amra and Milivojević, Nevena and Pecić, Katarina and Šeklić, Dragana and Jovanović, Milena and Kastratović, Nikolina and Mirić, Ana and Đukić, Tijana and Petrović, Ivica and Jurišić, Vladimir and Ljujić, Biljana and Filipović, Nenad",
year = "2023",
abstract = "Biomedicine is a multidisciplinary branch of science that requires a clear approach to the
study and analysis of various life processes necessary for a deeper understanding of
human health. This research focuses on the use of numerical simulations with the aim of an
improved comprehension of cancer viability and apoptosis during treatment with commercial
chemotherapeutic agents. In recent times, the usage of numerical models was successfully
applied to predict the behavior of tumors. This study includes a wide range of numerical results
that have been obtained by examining cell viability in real-time, determining the type of cell
death and the genetic factors that control these processes. The results of the in vitro test were
used to develop a numerical model that provides a new perspective on the proposed problem.
In this study, colon, and breast cancer cell lines (HCT-116 and MDA-MB-231), as well as healthy
lung fibroblast cell line (MRC-5) were treated with commercial chemotherapeutic agents. The
obtained results showed a decrease in viability and the occurrence of predominantly late
apoptosis upon treatment, as well as a strong correlation between parameters. A mathematical
model was developed and used to gain a better understanding of the investigated processes.
This method can accurately simulate the behavior of cancer cells and reliably predict their
growth.",
publisher = "Belgrade : Institute of molecular genetics and genetic engineering",
journal = "4th Belgrade Bioinformatics Conference",
title = "Numerical and Biological Modeling Approach in the Analysis of the Cancer Viability and Apoptosis",
pages = "70-70",
volume = "4",
url = "https://hdl.handle.net/21.15107/rcub_imagine_2010"
}

Virijević, K., Živanović, M., Gazdić Janković, M., Ramović Hamzagić, A., Milivojević, N., Pecić, K., Šeklić, D., Jovanović, M., Kastratović, N., Mirić, A., Đukić, T., Petrović, I., Jurišić, V., Ljujić, B.,& Filipović, N.. (2023). Numerical and Biological Modeling Approach in the Analysis of the Cancer Viability and Apoptosis. in 4th Belgrade Bioinformatics Conference
Belgrade : Institute of molecular genetics and genetic engineering., 4, 70-70.
https://hdl.handle.net/21.15107/rcub_imagine_2010

Virijević K, Živanović M, Gazdić Janković M, Ramović Hamzagić A, Milivojević N, Pecić K, Šeklić D, Jovanović M, Kastratović N, Mirić A, Đukić T, Petrović I, Jurišić V, Ljujić B, Filipović N. Numerical and Biological Modeling Approach in the Analysis of the Cancer Viability and Apoptosis. in 4th Belgrade Bioinformatics Conference. 2023;4:70-70.
https://hdl.handle.net/21.15107/rcub_imagine_2010 .

Virijević, Katarina, Živanović, Marko, Gazdić Janković, Marina, Ramović Hamzagić, Amra, Milivojević, Nevena, Pecić, Katarina, Šeklić, Dragana, Jovanović, Milena, Kastratović, Nikolina, Mirić, Ana, Đukić, Tijana, Petrović, Ivica, Jurišić, Vladimir, Ljujić, Biljana, Filipović, Nenad, "Numerical and Biological Modeling Approach in the Analysis of the Cancer Viability and Apoptosis" in 4th Belgrade Bioinformatics Conference, 4 (2023):70-70,
https://hdl.handle.net/21.15107/rcub_imagine_2010 .