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4. Nanozymes—An Overview

Author

Alaei, Loghman, primary, Izadi, Zhila, additional, Jafari, Samira, additional, Lotfabadi, Alireza, additional, Barzegari, Ebrahim, additional, Jaymand, Mehdi, additional, and Derakhshankhah, Hossein, additional

Published
2021
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9. Recent Advances in Nanodentistry

Author

Izadi, Zhila, primary, Derakhshankhah, Hossein, additional, Alaei, Loghman, additional, Karkazis, Emelia, additional, Jafari, Samira, additional, and Tayebi, Lobat, additional

Published
2019
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12. The Application of Ultrasonic Vibration in Human Sperm Cryopreservation as a Novel Method for the Modification of Physicochemical Characteristics of Freezing Media

Author

Shahverdi Abdolhossein, Ghaffari Seyed Mahmood, Riazi Gholamhossein, Alaei Loghman, Gholami Dariush, Sharafi Mohsen, and Fathi Rouhollah

Subjects
0301 basic medicine, Male, Embryology, Chemical Phenomena, Sperm cryopreservation, Motility, lcsh:Medicine, Semen, Apoptosis, Cryopreservation, Article, 03 medical and health sciences, 0302 clinical medicine, Tubulin, Ultrasonic vibration, Zeta potential, Humans, lcsh:Science, Membrane potential, Multidisciplinary, Chromatography, Molecular medicine, Chemistry, Biological techniques, lcsh:R, Spermatozoa, 030104 developmental biology, Membrane, Ultrasonic Waves, Sperm Motility, lcsh:Q, 030217 neurology & neurosurgery, DNA Damage, Semen Preservation
Abstract

The application of ultrasonic vibration was performed to modify the water molecules as the main compositions of the freezing medium used for human sperm cryopreservation. Different time periods of ultrasonic vibration (ULV) at the frequency of 28 kHz were applied for the evaluation of physicochemical properties of the water molecules. The most significant bubble size, zeta potential, and pH were obtained for the water molecules exposed to ultrasonic vibrations for 18 minutes and this time period was selected for further experiments due to the optimum results. In the next stage, semen samples were diluted with freezing medium containing ULV-exposed water and then cryopreserved. All the semen parameters were significantly reduced in cryopreserved groups as compared with the fresh control group. The highest percentage of total and progressive motility, viability, membrane and DNA integrity, and mitochondrial membrane potential were observed in frozen ULV compared with the frozen control. The rate of apoptosis in frozen ULV was significantly lower than that of in the frozen control. Furthermore, the gene expression ratios of α- and β-tubulins were significantly increased during cryopreservation, while the expression ratio of the tubulin polymerization promoting protein (TPPP) gene was decreased. Similar results were also observed when the protein levels of the genes mentioned earlier were evaluated by the ELISA method. Therefore, the changes in physicochemical properties of the freezing medium of human sperm cryopreservation using ULV can improve the quality of frozen products.

Published
2019
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14. Irreversible thermal inactivation and conformational lock of alpha glucosidase

Author

Alaei, Loghman, primary, Izadi, Zhila, additional, Jafari, Samira, additional, Jahanshahi, Fatemeh, additional, Jaymand, Mehdi, additional, Mohammadi, Pantea, additional, Paray, Bilal Ahamad, additional, Hasan, Anwarul, additional, Falahati, Mojtaba, additional, Varnamkhasti, Behrang Shiri, additional, Saboury, Ali Akbar, additional, Moosavi-Nejad, Zahra, additional, Sheikh-Hosseini, Mehrnaz, additional, and Derakhshankhah, Hossein, additional

Published
2020
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21. Comparison of QSAR models based on combinations of genetic algorithm, stepwise multiple linear regression, and artificial neural network methods to predict K of some derivatives of aromatic sulfonamides as carbonic anhydrase II inhibitors.

Author

Maleki, Afshin, Daraei, Hiua, Alaei, Loghman, and Faraji, Aram

Subjects
REGRESSION analysis, GENETIC algorithms, ARTIFICIAL neural networks, SULFONAMIDES, CARBONIC anhydrase inhibitors
Abstract

Four stepwise multiple linear regressions (SMLR) and a genetic algorithm (GA) based multiple linear regressions (MLR), together with artificial neural network (ANN) models, were applied for quantitative structure-activity relationship (QSAR) modeling of dissociation constants ( K) of 62 arylsulfonamide (ArSA) derivatives as human carbonic anhydrase II (HCA II) inhibitors. The best subsets of molecular descriptors were selected by SMLR and GA-MLR methods. These selected variables were used to generate MLR and ANN models. The predictability power of models was examined by an external test set and cross validation. In addition, some tests were done to examine other aspects of the models. The results show that for certain purposes GA-MLR is better than SMLR and for others, ANN overcomes MLR models. [ABSTRACT FROM AUTHOR]

Published
2014
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22. Synthesis of ZnO nano-sono-catalyst for degradation of reactive dye focusing on energy consumption: operational parameters influence, modeling, and optimization

Author

Daraei, Hiua, Maleki, Afshin, Mahvi, Amir Hossein, Zandsalimi, Yahya, Alaei, Loghman, and Gharibi, Fardin

Abstract

AbstractSimple synthesized Nano-sized ZnO powder in the absence of high-temperature activation treatments was studied to act as sono-catalyst. Effects of six operational parameters such as initial solution pH (pH0), initial concentration of dye stuff (C0), additional dose of nano-sized ZnO powder (DSC), ultrasound (US) irradiation frequency (FrSC), US irradiation power (PSC), and treatment time (tSC) were examined. Synthetic wastewater containing Reactive Red 198 (RR198) was used as the sample model. Combined design of experiments was done and experiments were conducted according to protocols. The experimental data were collected in a laboratory-scaled batch reactor equipped with ultrasonic bath cleaner as the ultrasonic source. The measured CR% ranging from 0.8 to 100 and EnC (wh) from 0.3 to 13.6 gained under given conditions. The data used for modeling were used in two more common models in this type of studies: Multiple linear regression (MLR) and artificial neural network (ANN). The ANN models obviously outperformed MLR models. Finally, Multi-objective optimization of CR% and EnC was carried out using genetic algorithm (GA) over the outperformed ANN models. The optimization procedure causes non-dominated optimal points which give an insight of the optimal operating conditions.

Published
2014
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23. Comparison of QSAR models based on combinations of genetic algorithm, stepwise multiple linear regression, and artificial neural network methods to predict Kd of some derivatives of aromatic sulfonamides as carbonic anhydrase II inhibitors.

Author

Maleki A, Daraei H, Alaei L, and Faraji A

Subjects
Algorithms, Humans, Linear Models, Neural Networks, Computer, Reproducibility of Results, Sulfonamides pharmacology, Carbonic Anhydrase II antagonists & inhibitors, Carbonic Anhydrase Inhibitors chemistry, Carbonic Anhydrase Inhibitors pharmacology, Quantitative Structure-Activity Relationship, Sulfonamides chemistry
Abstract

Four stepwise multiple linear regressions (SMLR) and a genetic algorithm (GA) based multiple linear regressions (MLR), together with artificial neural network (ANN) models, were applied for quantitative structure-activity relationship (QSAR) modeling of dissociation constants (Kd) of 62 arylsulfonamide (ArSA) derivatives as human carbonic anhydrase II (HCA II) inhibitors. The best subsets of molecular descriptors were selected by SMLR and GA-MLR methods. These selected variables were used to generate MLR and ANN models. The predictability power of models was examined by an external test set and cross validation. In addition, some tests were done to examine other aspects of the models. The results show that for certain purposes GA-MLR is better than SMLR and for others, ANN overcomes MLR models.

Published
2014

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