TY  - JOUR
AU  - Krstić, Marko
AU  - Teslić, Nemanja
AU  - Bošković, Perica
AU  - Obradović, Darija
AU  - Zeković, Zoran P.
AU  - Milić, Anita
AU  - Pavlić, Branimir
PY  - 2023
UR  - http://cherry.chem.bg.ac.rs/handle/123456789/5815
AB  - Garlic (Allium sativum L.) is widely used in various food products and traditional medicine. Besides unique taste and flavour, it is well known for its chemical profile and bioactive potential. The aim of this study was to apply subcritical water extraction (SWE) and pressurized liquid extraction (PLE) for the extraction of bioactive compounds from the Ranco genotype of garlic. Moreover, PLE process was optimized using response surface methodology (RSM) in order to determine effects and optimize ethanol concentration (45–75%), number of cycles (1–3), extraction time (1–3 min) and temperature (70–110 °C) for maximized total phenols content (TP) and antioxidant activity evaluated by various in vitro assays. Furthermore, temperature effect in SWE process on all responses was evaluated, while allicin content (AC), as a major organosulphur compound, was determined in all samples. Results indicated that PLE provided tremendous advantage over SWE in terms of improved yield and antioxidant activity of garlic extracts. Therefore, high-pressure processes could be used as clean and green procedures for the isolation of garlic bioactives.
PB  - MDPI
T2  - Molecules
T1  - Isolation of Garlic Bioactives by Pressurized Liquid and Subcritical Water Extraction
VL  - 28
IS  - 1
SP  - 369
DO  - 10.3390/molecules28010369
ER  - 

@article{
author = "Krstić, Marko and Teslić, Nemanja and Bošković, Perica and Obradović, Darija and Zeković, Zoran P. and Milić, Anita and Pavlić, Branimir",
year = "2023",
abstract = "Garlic (Allium sativum L.) is widely used in various food products and traditional medicine. Besides unique taste and flavour, it is well known for its chemical profile and bioactive potential. The aim of this study was to apply subcritical water extraction (SWE) and pressurized liquid extraction (PLE) for the extraction of bioactive compounds from the Ranco genotype of garlic. Moreover, PLE process was optimized using response surface methodology (RSM) in order to determine effects and optimize ethanol concentration (45–75%), number of cycles (1–3), extraction time (1–3 min) and temperature (70–110 °C) for maximized total phenols content (TP) and antioxidant activity evaluated by various in vitro assays. Furthermore, temperature effect in SWE process on all responses was evaluated, while allicin content (AC), as a major organosulphur compound, was determined in all samples. Results indicated that PLE provided tremendous advantage over SWE in terms of improved yield and antioxidant activity of garlic extracts. Therefore, high-pressure processes could be used as clean and green procedures for the isolation of garlic bioactives.",
publisher = "MDPI",
journal = "Molecules",
title = "Isolation of Garlic Bioactives by Pressurized Liquid and Subcritical Water Extraction",
volume = "28",
number = "1",
pages = "369",
doi = "10.3390/molecules28010369"
}

Krstić, M., Teslić, N., Bošković, P., Obradović, D., Zeković, Z. P., Milić, A.,& Pavlić, B.. (2023). Isolation of Garlic Bioactives by Pressurized Liquid and Subcritical Water Extraction. in Molecules
MDPI., 28(1), 369.
https://doi.org/10.3390/molecules28010369

Krstić M, Teslić N, Bošković P, Obradović D, Zeković ZP, Milić A, Pavlić B. Isolation of Garlic Bioactives by Pressurized Liquid and Subcritical Water Extraction. in Molecules. 2023;28(1):369.
doi:10.3390/molecules28010369 .

Krstić, Marko, Teslić, Nemanja, Bošković, Perica, Obradović, Darija, Zeković, Zoran P., Milić, Anita, Pavlić, Branimir, "Isolation of Garlic Bioactives by Pressurized Liquid and Subcritical Water Extraction" in Molecules, 28, no. 1 (2023):369,
https://doi.org/10.3390/molecules28010369 . .

TY  - DATA
AU  - Obradović, Darija
AU  - Andrić, Filip
AU  - Zlatović, Mario
AU  - Agbaba, Danica G.
PY  - 2018
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/3239
PB  - Wiley, Hoboken
T2  - Journal of Chemometrics
T1  - Supplementary material for the article: Obradović, D.; Andrić, F.; Zlatović, M.; Agbaba, D. Modeling of Hansen’s Solubility Parameters of Aripiprazole, Ziprasidone, and Their Impurities: A Nonparametric Comparison of Models for Prediction of Drug Absorption Sites. Journal of Chemometrics 2018, 32 (4). https://doi.org/10.1002/cem.2996
UR  - https://hdl.handle.net/21.15107/rcub_cherry_3239
ER  - 

@misc{
author = "Obradović, Darija and Andrić, Filip and Zlatović, Mario and Agbaba, Danica G.",
year = "2018",
publisher = "Wiley, Hoboken",
journal = "Journal of Chemometrics",
title = "Supplementary material for the article: Obradović, D.; Andrić, F.; Zlatović, M.; Agbaba, D. Modeling of Hansen’s Solubility Parameters of Aripiprazole, Ziprasidone, and Their Impurities: A Nonparametric Comparison of Models for Prediction of Drug Absorption Sites. Journal of Chemometrics 2018, 32 (4). https://doi.org/10.1002/cem.2996",
url = "https://hdl.handle.net/21.15107/rcub_cherry_3239"
}

Obradović, D., Andrić, F., Zlatović, M.,& Agbaba, D. G.. (2018). Supplementary material for the article: Obradović, D.; Andrić, F.; Zlatović, M.; Agbaba, D. Modeling of Hansen’s Solubility Parameters of Aripiprazole, Ziprasidone, and Their Impurities: A Nonparametric Comparison of Models for Prediction of Drug Absorption Sites. Journal of Chemometrics 2018, 32 (4). https://doi.org/10.1002/cem.2996. in Journal of Chemometrics
Wiley, Hoboken..
https://hdl.handle.net/21.15107/rcub_cherry_3239

Obradović D, Andrić F, Zlatović M, Agbaba DG. Supplementary material for the article: Obradović, D.; Andrić, F.; Zlatović, M.; Agbaba, D. Modeling of Hansen’s Solubility Parameters of Aripiprazole, Ziprasidone, and Their Impurities: A Nonparametric Comparison of Models for Prediction of Drug Absorption Sites. Journal of Chemometrics 2018, 32 (4). https://doi.org/10.1002/cem.2996. in Journal of Chemometrics. 2018;.
https://hdl.handle.net/21.15107/rcub_cherry_3239 .

Obradović, Darija, Andrić, Filip, Zlatović, Mario, Agbaba, Danica G., "Supplementary material for the article: Obradović, D.; Andrić, F.; Zlatović, M.; Agbaba, D. Modeling of Hansen’s Solubility Parameters of Aripiprazole, Ziprasidone, and Their Impurities: A Nonparametric Comparison of Models for Prediction of Drug Absorption Sites. Journal of Chemometrics 2018, 32 (4). https://doi.org/10.1002/cem.2996" in Journal of Chemometrics (2018),
https://hdl.handle.net/21.15107/rcub_cherry_3239 .

TY  - JOUR
AU  - Obradović, Darija
AU  - Andrić, Filip
AU  - Zlatović, Mario
AU  - Agbaba, Danica G.
PY  - 2018
UR  - https://cherry.chem.bg.ac.rs/handle/123456789/2133
AB  - Aripiprazole and ziprasidone are atypical antipsychotic drugs with the effect on positive and negative symptoms of schizophrenia, mania, and mixed states of bipolar disorder. Hansen's solubility parameters, (d), (p), and (h), which account for dispersive, polarizable, and hydrogen bonding contributions to the overall cohesive energy of a compound, are often used to assess pharmacokinetic properties of drugs. However, no data exist of solubility parameters for the drugs of interest in this study. Therefore, in the present study, partial least square regression (PLS), artificial neural networks (ANNs), regression trees (RT), boosted trees (BT), and random forests (RF) were applied to estimate Hansen's solubility parameters of ziprasidone, aripiprazole, and their impurities/metabolic derivatives, targeting their biopharmaceutical classes and absorption routes. A training set of 47 structurally diverse and pharmacologically active compounds and 290 molecular descriptors and pharmaceutically important properties were used to build the prediction models. The modeling approaches were compared by the sum of ranking differences, using the consensus values as a reference for the unknowns and the experimentally determined values as a gold standard for the calibration set. In both instances, the PLS models, together with ANNs, demonstrated better performance than RT, BT and especially RF. Based on the best scored models, we were able to pinpoint the most probable absorption sites for each drug and the corresponding metabolite, i.e., the upper parts of the gastrointestinal tract, small intestine, or absorption along entire length of gastrointestinal tract.
PB  - Wiley, Hoboken
T2  - Journal of Chemometrics
T1  - Modeling of Hansen's solubility parameters of aripiprazole, ziprasidone, and their impurities: A nonparametric comparison of models for prediction of drug absorption sites
VL  - 32
IS  - 4
DO  - 10.1002/cem.2996
ER  - 

@article{
author = "Obradović, Darija and Andrić, Filip and Zlatović, Mario and Agbaba, Danica G.",
year = "2018",
abstract = "Aripiprazole and ziprasidone are atypical antipsychotic drugs with the effect on positive and negative symptoms of schizophrenia, mania, and mixed states of bipolar disorder. Hansen's solubility parameters, (d), (p), and (h), which account for dispersive, polarizable, and hydrogen bonding contributions to the overall cohesive energy of a compound, are often used to assess pharmacokinetic properties of drugs. However, no data exist of solubility parameters for the drugs of interest in this study. Therefore, in the present study, partial least square regression (PLS), artificial neural networks (ANNs), regression trees (RT), boosted trees (BT), and random forests (RF) were applied to estimate Hansen's solubility parameters of ziprasidone, aripiprazole, and their impurities/metabolic derivatives, targeting their biopharmaceutical classes and absorption routes. A training set of 47 structurally diverse and pharmacologically active compounds and 290 molecular descriptors and pharmaceutically important properties were used to build the prediction models. The modeling approaches were compared by the sum of ranking differences, using the consensus values as a reference for the unknowns and the experimentally determined values as a gold standard for the calibration set. In both instances, the PLS models, together with ANNs, demonstrated better performance than RT, BT and especially RF. Based on the best scored models, we were able to pinpoint the most probable absorption sites for each drug and the corresponding metabolite, i.e., the upper parts of the gastrointestinal tract, small intestine, or absorption along entire length of gastrointestinal tract.",
publisher = "Wiley, Hoboken",
journal = "Journal of Chemometrics",
title = "Modeling of Hansen's solubility parameters of aripiprazole, ziprasidone, and their impurities: A nonparametric comparison of models for prediction of drug absorption sites",
volume = "32",
number = "4",
doi = "10.1002/cem.2996"
}

Obradović, D., Andrić, F., Zlatović, M.,& Agbaba, D. G.. (2018). Modeling of Hansen's solubility parameters of aripiprazole, ziprasidone, and their impurities: A nonparametric comparison of models for prediction of drug absorption sites. in Journal of Chemometrics
Wiley, Hoboken., 32(4).
https://doi.org/10.1002/cem.2996

Obradović D, Andrić F, Zlatović M, Agbaba DG. Modeling of Hansen's solubility parameters of aripiprazole, ziprasidone, and their impurities: A nonparametric comparison of models for prediction of drug absorption sites. in Journal of Chemometrics. 2018;32(4).
doi:10.1002/cem.2996 .

Obradović, Darija, Andrić, Filip, Zlatović, Mario, Agbaba, Danica G., "Modeling of Hansen's solubility parameters of aripiprazole, ziprasidone, and their impurities: A nonparametric comparison of models for prediction of drug absorption sites" in Journal of Chemometrics, 32, no. 4 (2018),
https://doi.org/10.1002/cem.2996 . .