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    Fabrication of chitosan/poly(lactic acid)/graphene oxide/TiO2 composite nanofibrous scaffolds for sustained delivery of doxorubicin and treatment of lung cancer

    , Article International Journal of Biological Macromolecules ; 2017 ; 01418130 (ISSN) Samadi, S ; Moradkhani, M ; beheshti, H ; Irani, M ; Aliabadi, M ; Sharif University of Technology
    Elsevier B.V  2017
    Abstract
    In this work, the synthesized graphene oxide/TiO2/doxorubicin (GO/TiO2/DOX) composites were loaded into the chitosan/poly(lactic acid) (PLA) solutions to fabricate the electrospun chitosan/PLA/GO/TiO2/DOX nanofibrous scaffolds via electrospinning process. The synthesized composites and nanofibers were characterized using X-ray powder diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analysis. Three-factor three-level central composite design was used to determine the influence of PLA to chitosan ratio, TiO2/DOX content and GO/TiO2/DOX content on the release of DOX from nanofibrous scaffolds. Drug loading efficiency and drug release behavior from... 

    Fabrication of novel poly(N-vinylcaprolactam)-coated UiO-66-NH2 metal organic framework nanocarrier for the controlled release of doxorubicin against A549 lung cancer cells

    , Article Journal of Drug Delivery Science and Technology ; Volume 66 , 2021 ; 17732247 (ISSN) Rakhshani, N ; Hassanzadeh Nemati, N ; Ramazani Saadatabadi, A ; Sadrnezhaad, S. K ; Sharif University of Technology
    Editions de Sante  2021
    Abstract
    The nano metal-organic frameworks (NMOFs) have been developed for drug delivery systems due to their high porosity and large specific surface area. In this work, UiO-66-NH2 NMOFs were synthesized via the microwave heating method and doxorubicin (DOX) as an anticancer drug was incorporated into the UiO-66-NH2 NMOFs. Then, poly(N-vinylcaprolactam) (PNVCL) synthesized by the free radical polymerization was coated on the UiO-66-NH2 NMOFs surface to fabricate dual pH/temperature-responsive nanocomposite against A549 lung cancer cells death in vitro. The synthesized nanocarriers were characterized using FTIR, 1H NMR, DLS, XRD, SEM, FESEM, TGA, and BET analysis. The average particle sizes of... 

    Improving the 3D Segmentation of Nodules in Lung CT Images

    , M.Sc. Thesis Sharif University of Technology Moradi, Puria (Author) ; Jamzad, Mansour (Supervisor) ; Beigy, Hamid (Co-Supervisor)
    Abstract
    Lung cancer is one of the most common types of cancers, and its early diagnosis can save many lives. Due to the high number of computed tomography (CT) images used to detect lung cancer, it is difficult to accurately and rapidly diagnose this disease. Doing so requires high expertise by radiologists. Therefore the demand for computer aided diagnosis systems in this area has been increased. The core of all lung cancer detection systems is the distinction between cancer and non-cancerous tissues. The main objective of this study is to present a new method based on 3D convolutional neural networks (CNN) that can perform false positives reduction operations while providing high sensitivity. In... 

    Detecting lung cancer lesions in CT images using 3D convolutional neural networks

    , Article 4th International Conference on Pattern Recognition and Image Analysis, IPRIA 2019, 6 March 2019 through 7 March 2019 ; 2019 , Pages 114-118 ; 9781728116211 (ISBN) Moradi, P ; Jamzad, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    Early diagnosis of lung cancer is very important in improving patients life expectancies. Due to the high number of Computed Tomography (CT) images, fast and accurate diagnosis is difficult for radiologists. Therefore, there is an increasing demand for Computer-Aid Diagnosis (CAD) lung cancer. The core of all lung cancer detection systems is the distinction between cancer and non-cancerous tissues. This operation is performed in the false positive reduction phase, which is one of the most critical part of the lung cancer detection systems. The primary objective of this paper is to present a new method based on 3D Convolutional Neural Networks (CNN) that can reduce the false positives rate... 

    Using Surface Properties of Immiscible Fluids in Capillary Tubes for Identification and Separation of Cancerous Blood Cells

    , M.Sc. Thesis Sharif University of Technology Alinejad, Amin (Author) ; Ayatollahi, Shahabodin (Supervisor) ; Vossoughi, Manochehr (Supervisor)
    Abstract
    Cancer has been known as one of the main reasons for disease-related deaths in the last decades. Early diagnosis could significantly reduce the level of fatality chances. Among the known cancer types, lung cancer is one of the most malignant ones. The common diagnosticmethods are expensive and using high-technology methods; therefore, the introduction of simple and cheap methods is very urgent to detect it. In this project, surface and interfacial tension measurement of cancerous and normal lung cells have been investigated as an easy detection technique. Among the common measurement methods, Pendant Drop and Capillary height techniques have been utilized in this research work. The obtained... 

    Simulation and Study of Iso-Dose Curve for Asymmetrical Balloon in Balloon-Brachytherapy with Cs-131

    , M.Sc. Thesis Sharif University of Technology Mohebbi Kojidi, Mohammad Hossein (Author) ; Hosseini, Abolfazl (Supervisor) ; Shirmardi, Pejman (Supervisor)
    Abstract
    Incidence of brain metastases (BM) from any tumor varies according to the method of data collection and date reported, ranging from 8 to 14 per 100,000 people per year. According to current population, about 6400 to 11000 BM Patients per year is expected. Without treatment, prognosis is dismal with survival of only 1–2 months. However, survival can be extended to 3–6 months with whole-brain radiotherapy (WBRT) and to 11 months with either surgery followed by adjuvant WBRT or surgery plus adjuvant stereotactic radiosurgery (SRS). Intravascular brachytherapy (generally iodine-125 (125I)) into the surgical cavity is another treatment strategy. 125I has been shown to confer local control... 

    Detecting Metastatic Lung Cancer and Its Lesions From CT-Scan Images Using Deep Interpretable Networks

    , M.Sc. Thesis Sharif University of Technology Rasekh, Ali (Author) ; Rabiee, Hamid Reza (Supervisor)
    Abstract
    Using automated assistants in medical applications has been increased in recent years. One of the most popular methods are artificial intelligence and deep learning methods which are specifically used in medical images analysis. Using these methods can improve the diagnosis accuracy, while performing in a faster time. So these methods can reduce the economical costs, error rate, and response time. But one important challenge in deep learning methods, is the interpretability of neural networks. In this research we focused on introducing an interpretability method for our pixel-wise segmentation network which is applied to the lung nodules dataset. In this research we first implemented a... 

    Analysis and Modeling of Air Pollution using Big Data Methods in Tehran City

    , M.Sc. Thesis Sharif University of Technology Abrishambaf, Arman (Author) ; Boroushaki, Mehrdad (Supervisor) ; Avami, Akram (Supervisor) ; Nahvijou, Azin (Co-Supervisor)
    Abstract
    Air pollution is a prevalent and pressing issue in Tehran, with significant impacts on both the environment and human health. this study uses statistical techniques, such as Pearson correlation, to determine the direction of influence of meteorological parameters on air pollutant concentrations, and Convergent Cross Mapping to quantify the causal relationship between meteorological parameters and ambient air pollutant concentrations, as well as feedback effects. Additionally, the research delves into the correlation between consumption of fossil fuels and air pollutants, as well as the relationship between lung cancer incidence and mortality by histological subtype and long-term exposure to... 

    A k-NN method for lung cancer prognosis with the use of a genetic algorithm for feature selection

    , Article Expert Systems with Applications ; Volume 164 , 2021 ; 09574174 (ISSN) Maleki, N ; Zeinali, Y ; Akhavan Niaki, S. T ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    Lung cancer is one of the most common diseases for human beings everywhere throughout the world. Early identification of this disease is the main conceivable approach to enhance the possibility of patients’ survival. In this paper, a k-Nearest-Neighbors technique, for which a genetic algorithm is applied for the efficient feature selection to reduce the dataset dimensions and enhance the classifier pace, is employed for diagnosing the stage of patients’ disease. To improve the accuracy of the proposed algorithm, the best value for k is determined using an experimental procedure. The implementation of the proposed approach on a lung cancer database reveals 100% accuracy. This implies that one... 

    Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 29 cancer groups, 1990 to 2017: a systematic analysis for the global burden of disease study

    , Article JAMA Oncology ; Volume 5, Issue 12 , 2019 , Pages 1749-1768 ; 23742437 (ISSN) Fitzmaurice, C ; Abate, D ; Abbasi, N ; Abbastabar, H ; Abd Allah, F ; Abdel Rahman, O ; Abdelalim, A ; Abdoli, A ; Abdollahpour, I ; Abdulle, A. S. M ; Abebe, N. D ; Abraha, H. N ; Abu Raddad, L. J ; Abualhasan, A ; Adedeji, I. A ; Advani, S. M ; Afarideh, M ; Afshari, M ; Aghaali, M ; Agius, D ; Agrawal, S ; Ahmadi, A ; Ahmadian, E ; Ahmadpour, E ; Ahmed, M. B ; Akbari, M. E ; Akinyemiju, T ; Al Aly, Z ; Alabdulkader, A. M ; Alahdab, F ; Alam, T ; Alamene, G. M ; Alemnew, B. T. T ; Alene, K. A ; Alinia, C ; Alipour, V ; Aljunid, S. M ; Bakeshei, F. A ; Almadi, M. A. H ; Almasi Hashiani, A ; Alsharif, U ; Alsowaidi, S ; Alvis Guzman, N ; Amini, E ; Amini, S ; Amoako, Y. A ; Anbari, Z ; Anber, N. H ; Andrei, C. L ; Anjomshoa, M ; Ansari, F ; Ansariadi, A ; Appiah, S. C. Y ; Arab Zozani, M ; Arabloo, J ; Arefi, Z ; Aremu, O ; Areri, H. A ; Artaman, A ; Asayesh, H ; Asfaw, E. T ; Ashagre, A. F ; Assadi, R ; Ataeinia, B ; Atalay, H. T ; Ataro, Z ; Atique, S ; Ausloos, M ; Avila Burgos, L ; Avokpaho, E. F. G. A ; Awasthi, A ; Awoke, N ; Ayala Quintanilla, B. P ; Ayanore, M. A ; Ayele, H. T ; Babaee, E ; Bacha, U ; Badawi, A ; Bagherzadeh, M ; Bagli, E ; Balakrishnan, S ; Balouchi, A ; Barnighausen, T. W ; Battista, R. J ; Behzadifar, M ; Behzadifar, M ; Bekele, B. B ; Belay, Y. B ; Belayneh, Y. M ; Berfield, K. K. S ; Berhane, A ; Bernabe, E ; Beuran, M ; Bhakta, N ; Bhattacharyya, K ; Biadgo, B ; Bijani, A ; Bin Sayeed, M. S ; Birungi, C ; Bisignano, C ; Bitew, H ; Bjorge, T ; Bleyer, A ; Bogale, K. A ; Bojia, H. A ; Borzi, A. M ; Bosetti, C ; Bou Orm, I. R ; Brenner, H ; Brewer, J. D ; Briko, A. N ; Briko, N. I ; Bustamante-Teixeira, M. T ; Butt, Z. A ; Carreras, G ; Carrero, J. J ; Carvalho, F ; Castro, C ; Castro, F ; Catala Lopez, F ; Cerin, E ; Chaiah, Y ; Chanie, W. F ; Chattu, V. K ; Chaturvedi, P ; Chauhan, N. S ; Chehrazi, M ; Chiang, P. P. C ; Chichiabellu, T. Y ; Chido Amajuoyi, O. G ; Chimed Ochir, O ; Choi, J. Y. J ; Christopher, D. J ; Chu, D. T ; Constantin, M. M ; Costa, V. M ; Crocetti, E ; Crowe, C. S ; Curado, M. P ; Dahlawi, S. M. A ; Damiani, G ; Darwish, A. H ; Daryani, A ; Das Neves, J ; Demeke, F. M ; Demis, A. B ; Demissie, B. W ; Demoz, G. T ; Denova Gutierrez, E ; Derakhshani, A ; Deribe, K. S ; Desai, R ; Desalegn, B. B ; Desta, M ; Dey, S ; Dharmaratne, S. D ; Dhimal, M ; Diaz, D ; Dinberu, M. T. T ; Djalalinia, S ; Doku, D. T ; Drake, T. M ; Dubey, M ; Dubljanin, E ; Duken, E. E ; Ebrahimi, H ; Effiong, A ; Eftekhari, A ; El Sayed, I ; Zaki, M. E. S ; El Jaafary, S. I ; El Khatib, Z ; Elemineh, D. A ; Elkout, H ; Ellenbogen, R. G ; Elsharkawy, A ; Emamian, M. H ; Endalew, D. A ; Endries, A. Y ; Eshrati, B ; Fadhil, I ; Fallah, V ; Faramarzi, M ; Farhangi, M. A ; Farioli, A ; Farzadfar, F ; Fentahun, N ; Fernandes, E ; Feyissa, G. T ; Filip, I ; Fischer, F ; Fisher, J. L ; Force, L. M ; Foroutan, M ; Freitas, M ; Fukumoto, T ; Futran, N. D ; Gallus, S ; Gankpe, F. G ; Gayesa, R. T ; Gebrehiwot, T. T ; Gebremeskel, G. G ; Gedefaw, G. A ; Gelaw, B. K ; Geta, B ; Getachew, S ; Gezae, K. E ; Ghafourifard, M ; Ghajar, A ; Ghashghaee, A ; Gholamian, A ; Gill, P.S ; Ginindza, T. T. G ; Girmay, A ; Gizaw, M ; Gomez, R. S ; Gopalani, S. V ; Gorini, G ; Goulart, B. N. G ; Grada, A ; Ribeiro Guerra, M ; Guimaraes, A.L.S ; Gupta, P. C ; Gupta, R ; Hadkhale, K ; Haj Mirzaian, A ; Hamadeh, R. R ; Hamidi, S ; Hanfore, L. K ; Haro, J. M ; Hasankhani, M ; Hasanzadeh, A ; Hassen, H. Y ; Hay, R. J ; Hay, S. I ; Henok, A ; Henry, N. J ; Herteliu, C ; Hidru, H. D ; Hoang, C. L ; Hole, M. K ; Hoogar, P ; Horita, N ; Hosgood, H. D ; Hosseini, M ; Hosseinzadeh, M ; Hostiuc, M ; Hostiuc, S ; Househ, M ; Hussen, M. M ; Ileanu, B ; Ilic, M.D ; Innos, K ; Irvani, S. S. N ; Iseh, K. R ; Islam, S. M. S ; Islami, F ; Jafari Balalami, N ; Jafarinia, M ; Jahangiry, L ; Jahani, M. A ; Jahanmehr, N ; Jakovljevic, M ; James, S.L ; Javanbakht, M ; Jayaraman, S ; Jee, S. H ; Jenabi, E ; Jha, R. P ; Jonas, J. B ; Jonnagaddala, J ; Joo, T ; Jungari, S. B ; Jurisson, M ; Kabir, A ; Kamangar, F ; Karch, A ; Karimi, N ; Karimian, A ; Kasaeian, A ; Kasahun, G. G ; Kassa, B ; Kassa, T. D ; Kassaw, M. W ; Kaul, A ; Keiyoro, P. N ; Kelbore, A. G ; Kerbo, A. A ; Khader, Y. S ; Khalilarjmandi, M ; Khan, E. A ; Khan, G ; Khang, Y. H ; Khatab, K ; Khater, A ; Khayamzadeh, M ; Khazaee Pool, M ; Khazaei, S ; Khoja, A. T ; Khosravi, M. H ; Khubchandani, J ; Kianipour, N ; Kim, D ; Kim, Y. J ; Kisa, A ; Kisa, S ; Kissimova Skarbek, K ; Komaki, H ; Koyanagi, A ; Krohn, K. J ; Bicer, B. K ; Kugbey, N ; Kumar, V ; Kuupiel, D ; La Vecchia, C ; Lad, D. P ; Lake, E. A ; Lakew, A. M ; Lal, D. K ; Lami, F. H ; Lan, Q ; Lasrado, S ; Lauriola, P ; Lazarus, J. V ; Leigh, J ; Leshargie, C. T ; Liao, Y ; Limenih, M. A ; Listl, S ; Lopez, A. D ; Lopukhov, P. D ; Lunevicius, R ; Madadin, M ; Magdeldin, S ; El Razek, H. M. A ; Majeed, A ; Maleki, A ; Malekzadeh, R ; Manafi, A ; Manafi, N ; Manamo, W. A ; Mansourian, M ; Mansournia, M .A ; Mantovani, L. G ; Maroufizadeh, S ; Martini, S. M. S ; Mashamba Thompson, T. P ; Massenburg, B. B ; Maswabi, M. T ; Mathur, M. R ; McAlinden, C ; McKee, M ; Meheretu, H. A. A ; Mehrotra, R ; Mehta, V ; Meier, T ; Melaku, Y. A ; Meles, G. G ; Meles, H. G ; Melese, A ; Melku, M ; Memiah, P. T. N ; Mendoza, W ; Menezes, R. G ; Merat, S ; Meretoja, T. J ; Mestrovic, T ; Miazgowski, B ; Miazgowski, T ; Mihretie, K. M. M ; Miller, T. R ; Mills, E. J ; Mir, S. M ; Mirzaei, H ; Mirzaei, H. R ; Mishra, R ; Moazen, B ; Mohammad, D. K ; Mohammad, K. A ; Mohammad, Y ; Darwesh, A. M ; Mohammadbeigi, A ; Mohammadi, H ; Mohammadi, M ; Mohammadian, M ; Mohammadian Hafshejani, A ; Mohammadoo Khorasani, M ; Mohammadpourhodki, R ; Mohammed, A. S ; Mohammed, J. A ; Mohammed, S ; Mohebi, F ; Mokdad, A. H ; Monasta, L ; Moodley, Y ; Moosazadeh, M ; Moossavi, M ; Moradi, G ; Moradi Joo, M ; Sharif University of Technology
    American Medical Association  2019
    Abstract
    Importance: Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data.... 

    A selective chemiresistive sensor for the cancer-related volatile organic compound hexanal by using molecularly imprinted polymers and multiwalled carbon nanotubes

    , Article Microchimica Acta ; Volume 186, Issue 3 , 2019 ; 00263672 (ISSN) Janfaza, S ; Banan Nojavani, M ; Nikkhah, M ; Alizadeh, T ; Esfandiar, A ; Ganjali, M. R ; Sharif University of Technology
    Springer-Verlag Wien  2019
    Abstract
    A chemiresistive sensor is described for the lung cancer biomarker hexanal. A composite consisting of molecularly imprinted polymer nanoparticles and multiwalled carbon nanotubes was used in the sensor that is typically operated at a voltage of 4 V and is capable of selectively sensing gaseous hexanal at room temperature. It works in the 10 to 200 ppm concentration range and has a 10 ppm detection limit (at S/N = 3). The sensor signal recovers to a value close to its starting value without the need for heating even after exposure to relatively high levels of hexanal  

    Influence of indoor air conditions on radon concentration in a detached house

    , Article Journal of Environmental Radioactivity ; Volume 116 , February , 2013 , Pages 166-173 ; 0265931X (ISSN) Akbari, K ; Mahmoudi, J ; Ghanbari, M ; Sharif University of Technology
    2013
    Abstract
    Radon is released from soil and building materials and can accumulate in residential buildings. Breathing radon and radon progeny for extended periods hazardous to health and can lead to lung cancer. Indoor air conditions and ventilation systems strongly influence indoor radon concentrations. This paper focuses on effects of air change rate, indoor temperature and relative humidity on indoor radon concentrations in a one family detached house in Stockholm, Sweden.In this study a heat recovery ventilation system unit was used to control the ventilation rate and a continuous radon monitor (CRM) was used to measure radon levels. FLUENT, a computational fluid dynamics (CFD) software package was... 

    Fabrication of chitosan/poly(lactic acid)/graphene oxide/TiO2 composite nanofibrous scaffolds for sustained delivery of doxorubicin and treatment of lung cancer

    , Article International Journal of Biological Macromolecules ; Volume 110 , 2018 , Pages 416-424 ; 01418130 (ISSN) Samadi, S ; Moradkhani, M ; Beheshti, H ; Irani, M ; Aliabadi, M ; Sharif University of Technology
    Elsevier B.V  2018
    Abstract
    In this work, the synthesized graphene oxide/TiO2/doxorubicin (GO/TiO2/DOX) composites were loaded into the chitosan/poly(lactic acid) (PLA) solutions to fabricate the electrospun chitosan/PLA/GO/TiO2/DOX nanofibrous scaffolds via electrospinning process. The synthesized composites and nanofibers were characterized using X-ray powder diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM) analysis. Three-factor three-level central composite design was used to determine the influence of PLA to chitosan ratio, TiO2/DOX content and GO/TiO2/DOX content on the release of DOX from nanofibrous scaffolds. Drug loading efficiency and drug release behavior from... 

    CRISPR-Cas, a robust gene-editing technology in the era of modern cancer immunotherapy

    , Article Cancer Cell International ; Volume 20, Issue 1 , September , 2020 Miri, S. M ; Tafsiri, E ; Cho, W. C. S ; Ghaemi, A ; Sharif University of Technology
    BioMed Central Ltd  2020
    Abstract
    Cancer immunotherapy has been emerged as a promising strategy for treatment of a broad spectrum of malignancies ranging from hematological to solid tumors. One of the principal approaches of cancer immunotherapy is transfer of natural or engineered tumor-specific T-cells into patients, a so called "adoptive cell transfer", or ACT, process. Construction of allogeneic T-cells is dependent on the employment of a gene-editing tool to modify donor-extracted T-cells and prepare them to specifically act against tumor cells with enhanced function and durability and least side-effects. In this context, CRISPR technology can be used to produce universal T-cells, equipped with recombinant T cell...