690 results on '"Mohammadi, Saeed"'
Search Results
2. Graft failure after allogeneic hematopoietic stem cell transplantation in pediatric patients with acute leukemia: autologous reconstitution or second transplant?
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Rostami, Tahereh, Rostami, Mohammad Reza, Mirhosseini, Amir Hossein, Mohammadi, Saeed, Nikbakht, Mohsen, Alemi, Hediyeh, Khavandgar, Naghmeh, Rad, Soroush, Janbabai, Ghasem, Mousavi, Seied Asadollah, Kiumarsi, Azadeh, and Kasaeian, Amir
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- 2024
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3. Correction: Switching performance assessment of gate-all-around InAs–Si vertical TFET with triple metal gate, a simulation study
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Madadi, Dariush and Mohammadi, Saeed
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- 2024
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4. Fringe-fields-modulated double-gate tunnel-FET biosensor
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Chahardah Cherik, Iman and Mohammadi, Saeed
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- 2024
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5. Iranian patients with diabetes and COVID-19-associated mucormycosis: Characteristics, manifestations, and mortality risk factors
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Salehi, Mohammadreza, Esteghamati, Alireza, Khodavaisy, Sadegh, Khajavi Rad, Nasim, Abdollahi, Alireza, Alemzadeh, Sayyed Amirsina, Nasserisina, Sadaf, Tabari, Azin, Pakdel, Farzad, Mohammadi, Saeed, Joorabloo, Neda, Abdorahimi, Mahsa, Shavandi, Mehrdad, and Rabizadeh, Soghra
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- 2024
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6. Econometric Modeling of Intraday Electricity Market Price with Inadequate Historical Data
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Mohammadi, Saeed and Hesamzadeh, Mohammad Reza
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Electrical Engineering and Systems Science - Systems and Control ,Computer Science - Machine Learning ,Statistics - Applications - Abstract
The intraday (ID) electricity market has received an increasing attention in the recent EU electricity-market discussions. This is partly because the uncertainty in the underlying power system is growing and the ID market provides an adjustment platform to deal with such uncertainties. Hence, market participants need a proper ID market price model to optimally adjust their positions by trading in the market. Inadequate historical data for ID market price makes it more challenging to model. This paper proposes long short-term memory, deep convolutional generative adversarial networks, and No-U-Turn sampler algorithms to model ID market prices. Our proposed econometric ID market price models are applied to the Nordic ID price data and their promising performance are illustrated., Comment: 7 pages, 14 figures
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- 2022
7. A New Computational Approach for Solving Linear Bilevel Programs Based on Parameter-Free Disjunctive Decomposition
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Mohammadi, Saeed, Hesamzadeh, Mohammad Reza, Gabriel, Steven A., and Khastieva, Dina
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Electrical Engineering and Systems Science - Systems and Control ,Mathematics - Optimization and Control - Abstract
Linear bilevel programs (linear BLPs) have been widely used in computational mathematics and optimization in several applications. Single-level reformulation for linear BLPs replaces the lower-level linear program with its Karush-Kuhn-Tucker optimality conditions and linearizes the complementary slackness conditions using the big-M technique. Although the approach is straightforward, it requires finding the big-M whose computation is recently shown to be NP-hard. This paper presents a disjunctive-based decomposition algorithm which does not need finding the big-Ms whereas guaranteeing that obtained solution is optimal. Our experience shows promising performance of our algorithm., Comment: 16 pages, 3 figures
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- 2022
8. A Machine Learning Approach for Prosumer Management in Intraday Electricity Markets
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Mohammadi, Saeed and Hesamzadeh, Mohammad Reza
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Electrical Engineering and Systems Science - Systems and Control - Abstract
Prosumer operators are dealing with extensive challenges to participate in short-term electricity markets while taking uncertainties into account. Challenges such as variation in demand, solar energy, wind power, and electricity prices as well as faster response time in intraday electricity markets. Machine learning approaches could resolve these challenges due to their ability to continuous learning of complex relations and providing a real-time response. Such approaches are applicable with presence of the high performance computing and big data. To tackle these challenges, a Markov decision process is proposed and solved with a reinforcement learning algorithm with proper observations and actions employing tabular Q-learning. Trained agent converges to a policy which is similar to the global optimal solution. It increases the prosumer's profit by 13.39% compared to the well-known stochastic optimization approach., Comment: 5 pages, 6 figures
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- 2022
9. Assessing residential sustainable energy autonomous buildings for hot climate applications
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Mohammadi, Saeed and Bahman, Ammar M.
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- 2024
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10. A tunable graphene dual mode absorber for efficient terahertz radiation absorption and sensing applications
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Korani, Nastaran, Mohammadi, Saeed, Hocini, Abdesselam, and Danaie, Mohammad
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- 2024
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11. Vertical tunneling FET with Ge/Si doping-less heterojunction, a high-performance switch for digital applications
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Cherik, Iman Chahardah, Mohammadi, Saeed, and Maity, Subir Kumar
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- 2023
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12. Impact of trap-related non-idealities on the performance of a novel TFET-based biosensor with dual doping-less tunneling junction
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Cherik, Iman Chahardah and Mohammadi, Saeed
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- 2023
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13. Switching performance assessment of gate-all-around InAs–Si vertical TFET with triple metal gate, a simulation study
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Madadi, Dariush and Mohammadi, Saeed
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- 2023
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14. Back-bending and up-bending study in the Yrast states of 178−184Os isotopes using projected shell model
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Pourhasan, Samane, Mohammadi, Saeed, and Sajjadi, Zahra
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- 2023
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15. Targeted deep learning classification and feature extraction for clinical diagnosis
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Tsai, Yiting, Nanthakumar, Vikash, Mohammadi, Saeed, Baldwin, Susan A., Gopaluni, Bhushan, and Geng, Fei
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- 2023
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16. Side Effects of Brolucizumab
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Motevasseli, Tahmineh, Mohammadi, Saeed, Abdi, Fatemeh, and Freeman, William R
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Biomedical and Clinical Sciences ,Ophthalmology and Optometry ,Biotechnology ,Neurosciences ,Eye Disease and Disorders of Vision ,Neurodegenerative ,Macular Degeneration ,Development of treatments and therapeutic interventions ,5.1 Pharmaceuticals ,Eye ,Anti-vascular Endothelial Growth Factor ,Brolucizumab ,Wet Age-related Macular Degeneration ,Brolucizumab ,Wet Age-related Macular Degeneration ,Opthalmology and Optometry ,Ophthalmology and optometry - Abstract
Age-related macular degeneration and its complication, subretinal neovascularization, are common causes of progressive, irreversible impairment of central vision. Anti-vascular endothelial growth factor (anti-VEGF) therapy has improved the visual outcome and provided an evolution in the treatment of retinal disease. The current four anti-VEGF drugs - pegaptanib, ranibizumab, aflibercept, and bevacizumab - have been administered for many years. A new anti-VEGF agent, brolucizumab, was approved by the U.S. Food and Drug Administration (FDA) in late 2019 for the treatment of wet age-related macular degeneration. Brolucizumab is a novel single-chain fragment variable antibody that inhibits all isoforms of VEGF-A and has been suggested to have more tissue penetration. Despite all the benefits, there are some reports of serious side effects that need to be understood in managing patients. Brolucizumab has been reported to cause occlusive retinal vasculitis in the setting of intraocular inflammation, which has not been seen in other anti-VEGF medications. A PubMed and Scopus search was performed and all article types were included. In the present article, we have reviewed the reported side effects of brolucizumab.
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- 2021
17. Design, fabrication, and hypervelocity impact testing of screen-printed flexible micrometeoroid and orbital debris impact sensors for long-duration spacecraft health monitoring
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Hofmann, Douglas C., Bordeenithikasem, Punnathat, Zhu, Yuhang, Liu, Yufei, Conrad, Nathan J., Davis, B. Alan, Christiansen, Eric L., Shakouri, Ali, and Mohammadi, Saeed
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- 2023
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18. Study of nucleus staggering phenomenon for odd–even 159,161,163Er isotopes
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Firouzi, Zohreh, Mohammadi, Saeed, and Raghavi, Afzal
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- 2022
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19. A Novel Fin-Shape Double-Gate GaAs p-MOSFET With Intrinsic Source and Enhanced Switching Performance
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Cherik, Iman Chahardah, primary and Mohammadi, Saeed, additional
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- 2024
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20. Immunomodulation by glucocorticoid-induced leucine zipper in macrophages: enhanced phagocytosis, protection from pyroptosis, and altered mitochondrial function
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Legroux, Thierry M., primary, Schymik, Hanna S., additional, Gasparoni, Gilles, additional, Mohammadi, Saeed, additional, Walter, Jörn, additional, Libert, Claude, additional, Diesel, Britta, additional, Hoppstädter, Jessica, additional, and Kiemer, Alexandra K., additional
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- 2024
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21. On the caregiver effective dose analysis during I‑131 therapy in different situations using two mathematical phantoms and Monte Carlo code
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Morovati, Narges, Sajjadi, Zahra, and Mohammadi, Saeed
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- 2022
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22. Convolutional Graph Auto-encoder: A Deep Generative Neural Architecture for Probabilistic Spatio-temporal Solar Irradiance Forecasting
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Khodayar, Mahdi, Mohammadi, Saeed, Khodayar, Mohammad, Wang, Jianhui, and Liu, Guangyi
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Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
Machine Learning on graph-structured data is an important and omnipresent task for a vast variety of applications including anomaly detection and dynamic network analysis. In this paper, a deep generative model is introduced to capture continuous probability densities corresponding to the nodes of an arbitrary graph. In contrast to all learning formulations in the area of discriminative pattern recognition, we propose a scalable generative optimization/algorithm theoretically proved to capture distributions at the nodes of a graph. Our model is able to generate samples from the probability densities learned at each node. This probabilistic data generation model, i.e. convolutional graph auto-encoder (CGAE), is devised based on the localized first-order approximation of spectral graph convolutions, deep learning, and the variational Bayesian inference. We apply our CGAE to a new problem, the spatio-temporal probabilistic solar irradiance prediction. Multiple solar radiation measurement sites in a wide area in northern states of the US are modeled as an undirected graph. Using our proposed model, the distribution of future irradiance given historical radiation observations is estimated for every site/node. Numerical results on the National Solar Radiation Database show state-of-the-art performance for probabilistic radiation prediction on geographically distributed irradiance data in terms of reliability, sharpness, and continuous ranked probability score., Comment: 8 pages, 11 figures
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- 2018
23. Geological control for in-situ and recoverable resources assessment: A case study on Sarcheshmeh porphyry copper deposit, Iran
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Maleki, Mohammad, Mery, Nadia, Soltani-Mohammadi, Saeed, Khorram, Farzaneh, and Emery, Xavier
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- 2022
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24. Geostatistical modeling of heterogeneous geo-clusters in a copper deposit integrated with multinomial logistic regression: An exercise on resource estimation
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Madani, Nasser, Maleki, Mohammad, and Soltani-Mohammadi, Saeed
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- 2022
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25. Effect of gamma-irradiation on electrochemical properties of ZnCo2O4-rGO for supercapacitor application
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Samiei, Elham, Mohammadi, Saeed, and Torkzadeh-Mahani, Masoud
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- 2022
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26. Cylindrical electron–hole bilayer TFET with a single surrounding gate and induced quantum confinement
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Chahardah Cherik, Iman and Mohammadi, Saeed
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- 2022
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27. Serum and salivary tissue transglutaminase IGA (tTG-IGA) level in celiac patients
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Ajdani, Mehran, Mortazavi, Nazanin, Besharat, Sima, Mohammadi, Saeed, Amiriani, Taghi, Sohrabi, Ahmad, Norouzi, Alireza, and Edris, Ghezeljeh
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- 2022
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28. A large dataset of white blood cells containing cell locations and types, along with segmented nuclei and cytoplasm
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Kouzehkanan, Zahra Mousavi, Saghari, Sepehr, Tavakoli, Sajad, Rostami, Peyman, Abaszadeh, Mohammadjavad, Mirzadeh, Farzaneh, Satlsar, Esmaeil Shahabi, Gheidishahran, Maryam, Gorgi, Fatemeh, Mohammadi, Saeed, and Hosseini, Reshad
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- 2022
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29. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
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Brauer, M, Roth, G, Aravkin, A, Zheng, P, Abate, K, Abate, Y, Abbafati, C, Abbasgholizadeh, R, Abbasi, M, Abbasian, M, Abbasifard, M, Abbasi-Kangevari, M, Abd ElHafeez, S, Abd-Elsalam, S, Abdi, P, Abdollahi, M, Abdoun, M, Abdulah, D, Abdullahi, A, Abebe, M, Abedi, A, Abegaz, T, Abeldaño Zuñiga, R, Abiodun, O, Abiso, T, Aboagye, R, Abolhassani, H, Abouzid, M, Aboye, G, Abreu, L, Abualruz, H, Abubakar, B, Abu-Gharbieh, E, Abukhadijah, H, Aburuz, S, Abu-Zaid, A, Adane, M, Addo, I, Addolorato, G, Adedoyin, R, Adekanmbi, V, Aden, B, Adetunji, J, Adeyeoluwa, T, Adha, R, Adibi, A, Adnani, Q, Adzigbli, L, Afolabi, A, Afolabi, R, Afshin, A, Afyouni, S, Afzal, M, Afzal, S, Agampodi, S, Agbozo, F, Aghamiri, S, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, B, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, N, Ahmad, S, Ahmad, T, Ahmed, A, Ahmed, L, Ahmed, M, Ahmed, S, Ajami, M, Akalu, G, Akara, E, Akbarialiabad, H, Akhlaghi, S, Akinosoglou, K, Akinyemiju, T, Akkaif, M, Akkala, S, Akombi-Inyang, B, Al Awaidy, S, Al Hasan, S, Alahdab, F, AL-Ahdal, T, Alalalmeh, S, Alalwan, T, Al-Aly, Z, Alam, K, Alam, N, Alanezi, F, Alanzi, T, Albakri, A, Albataineh, M, Aldhaleei, W, Aldridge, R, Alemayohu, M, Alemu, Y, Al-Fatly, B, Al-Gheethi, A, Al-Habbal, K, Alhabib, K, Alhassan, R, Ali, A, Ali, B, Ali, I, Ali, L, Ali, M, Ali, R, Ali, S, Ali, W, Alicandro, G, Alif, S, Aljunid, S, Alla, F, Al-Marwani, S, Al-Mekhlafi, H, Almustanyir, S, Alomari, M, Alonso, J, Alqahtani, J, Alqutaibi, A, Al-Raddadi, R, Alrawashdeh, A, Al-Rifai, R, Alrousan, S, Al-Sabah, S, Alshahrani, N, Altaany, Z, Altaf, A, Al-Tawfiq, J, Altirkawi, K, Aluh, D, Alvis-Guzman, N, Alvis-Zakzuk, N, Alwafi, H, Al-Wardat, M, Al-Worafi, Y, Aly, H, Aly, S, Alzoubi, K, Al-Zyoud, W, Amaechi, U, Aman Mohammadi, M, Amani, R, Amiri, S, Amirzade-Iranaq, M, Ammirati, E, Amu, H, Amugsi, D, Amusa, G, Ancuceanu, R, Anderlini, D, Anderson, J, Andrade, P, Andrei, C, Andrei, T, Anenberg, S, Angappan, D, Angus, C, Anil, A, Anil, S, Anjum, A, Anoushiravani, A, Antonazzo, I, Antony, C, Antriyandarti, E, Anuoluwa, B, Anvari, D, Anvari, S, Anwar, S, Anwer, R, Anyabolo, E, Anyasodor, A, Apostol, G, Arabloo, J, Arabzadeh Bahri, R, Arafat, M, Areda, D, Aregawi, B, Aremu, A, Armocida, B, Arndt, M, Ärnlöv, J, Arooj, M, Artamonov, A, Artanti, K, Aruleba, I, Arumugam, A, Asbeutah, A, Asgary, S, Asgedom, A, Ashbaugh, C, Ashemo, M, Ashraf, T, Askarinejad, A, Assmus, M, Astell-Burt, T, Athar, M, Athari, S, Atorkey, P, Atreya, A, Aujayeb, A, Ausloos, M, Avila-Burgos, L, Awoke, A, Ayala Quintanilla, B, Ayatollahi, H, Ayestas Portugal, C, Ayuso-Mateos, J, Azadnajafabad, S, Azevedo, R, Azhar, G, Azizi, H, Azzam, A, Backhaus, I, Badar, M, Badiye, A, Bagga, A, Baghdadi, S, Bagheri, N, Bagherieh, S, Bahrami Taghanaki, P, Bai, R, Baig, A, Baker, J, Bakkannavar, S, Balasubramanian, M, Baltatu, O, Bam, K, Bandyopadhyay, S, Banik, B, Banik, P, Banke-Thomas, A, Bansal, H, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, S, Bärnighausen, T, Barone-Adesi, F, Barqawi, H, Barrero, L, Barrow, A, Barteit, S, Basharat, Z, Basiru, A, Basso, J, Bastan, M, Basu, S, Batchu, S, Batra, K, Batra, R, Baune, B, Bayati, M, Bayileyegn, N, Beaney, T, Behnoush, A, Beiranvand, M, Béjot, Y, Bekele, A, Belgaumi, U, Bell, A, Bell, M, Bello, M, Bello, O, Belo, L, Beloukas, A, Bendak, S, Bennett, D, Bennitt, F, Bensenor, I, Benzian, H, Beran, A, Berezvai, Z, Bernabe, E, Bernstein, R, Bettencourt, P, Bhagavathula, A, Bhala, N, Bhandari, D, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bhat, A, Bhat, V, Bhatti, G, Bhatti, J, Bhatti, M, Bhatti, R, Bhuiyan, M, Bhutta, Z, Bikbov, B, Bishai, J, Bisignano, C, Biswas, A, Biswas, B, Biswas, R, Bjørge, T, Boachie, M, Boakye, H, Bockarie, M, Bodolica, V, Bodunrin, A, Bogale, E, Bolla, S, Boloor, A, Bonakdar Hashemi, M, Boppana, S, Bora Basara, B, Borhany, H, Botero Carvajal, A, Bouaoud, S, Boufous, S, Bourne, R, Boxe, C, Braithwaite, D, Brant, L, Brar, A, Breitborde, N, Breitner, S, Brenner, H, Briko, A, Britton, G, Brown, C, Browne, A, Brunoni, A, Bryazka, D, Bulamu, N, Bulto, L, Buonsenso, D, Burkart, K, Burns, R, Busse, R, Bustanji, Y, Butt, N, Butt, Z, Caetano dos Santos, F, Cagney, J, Cahuana-Hurtado, L, Calina, D, Cámera, L, Campos, L, Campos-Nonato, I, Cao, C, Cao, F, Cao, Y, Capodici, A, Cárdenas, R, Carr, S, Carreras, G, Carrero, J, Carugno, A, Carvalho, F, Carvalho, M, Castaldelli-Maia, J, Castañeda-Orjuela, C, Castelpietra, G, Catalá-López, F, Catapano, A, Cattaruzza, M, Caye, A, Cederroth, C, Cegolon, L, Cenderadewi, M, Cercy, K, Cerin, E, Chadwick, J, Chakraborty, C, Chakraborty, P, Chakraborty, S, Chan, J, Chan, R, Chandan, J, Chandika, R, Chaturvedi, P, Chen, A, Chen, C, Chen, H, Chen, M, Chen, S, Cheng, C, Cheng, E, Cherbuin, N, Chi, G, Chichagi, F, Chimed-Ochir, O, Chimoriya, R, Ching, P, Chirinos-Caceres, J, Chitheer, A, Cho, W, Chong, B, Chopra, H, Chowdhury, R, Christopher, D, Chu, D, Chukwu, I, Chung, E, Chung, S, Chutiyami, M, Cioffi, I, Cogen, R, Cohen, A, Columbus, A, Conde, J, Corlateanu, A, Cortese, S, Cortesi, P, Costa, V, Costanzo, S, Criqui, M, Cruz, J, Cruz-Martins, N, Culbreth, G, da Silva, A, Dadras, O, Dai, X, Dai, Z, Daikwo, P, Dalli, L, Damiani, G, D'Amico, E, D'Anna, L, Darwesh, A, Das, J, Das, S, Dash, N, Dashti, M, Dávila-Cervantes, C, Davis Weaver, N, Davitoiu, D, De la Hoz, F, de la Torre-Luque, A, De Leo, D, Debopadhaya, S, Degenhardt, L, Del Bo', C, Delgado-Enciso, I, Delgado-Saborit, J, Demoze, C, Denova-Gutiérrez, E, Dervenis, N, Dervišević, E, Desai, H, Desai, R, Devanbu, V, Dewan, S, Dhali, A, Dhama, K, Dhane, A, Dhimal, M, Dhingra, S, Dhulipala, V, Dhungana, R, Dias da Silva, D, Diaz, D, Diaz, L, Diaz, M, Dima, A, Ding, D, Dinu, M, Djalalinia, S, Do, T, do Prado, C, Dodangeh, M, Dohare, S, Dokova, K, Dong, W, Dongarwar, D, D'Oria, M, Dorostkar, F, Dorsey, E, Doshi, R, Doshmangir, L, Dowou, R, Driscoll, T, Dsouza, A, Dsouza, H, Dumith, S, Duncan, B, Duraes, A, Duraisamy, S, Dushpanova, A, Dzianach, P, Dziedzic, A, Ebrahimi, A, Echieh, C, Ed-Dra, A, Edinur, H, Edvardsson, D, Edvardsson, K, Efendi, F, Eftekharimehrabad, A, Eini, E, Ekholuenetale, M, Ekundayo, T, El Arab, R, El Sayed Zaki, M, El-Dahiyat, F, Elemam, N, Elgar, F, Elgohary, G, Elhabashy, H, Elhadi, M, Elmehrath, A, Elmeligy, O, Elshaer, M, Elsohaby, I, Emeto, T, Esfandiari, N, Eshrati, B, Eslami, M, Esmaeili, S, Estep, K, Etaee, F, Fabin, N, Fagbamigbe, A, Fagbule, O, Fahimi, S, Falzone, L, Fareed, M, Farinha, C, Faris, M, Faris, P, Faro, A, Fasina, F, Fatehizadeh, A, Fauk, N, Fazylov, T, Feigin, V, Feng, X, Fereshtehnejad, S, Feroze, A, Ferrara, P, Ferrari, A, Ferreira, N, Fetensa, G, Feyisa, B, Filip, I, Fischer, F, Fitriana, I, Flavel, J, Flohr, C, Flood, D, Flor, L, Foigt, N, Folayan, M, Force, L, Fortuna, D, Foschi, M, Franklin, R, Freitas, A, Friedman, S, Fux, B, G, S, Gaal, P, Gaihre, S, Gajdács, M, Galali, Y, Gallus, S, Gandhi, A, Ganesan, B, Ganiyani, M, Garcia, V, Gardner, W, Garg, R, Gautam, R, Gebi, T, Gebregergis, M, Gebrehiwot, M, Gebremariam, T, Gebremeskel, T, Gerema, U, Getacher, L, Getahun, G, Getie, M, Ghadirian, F, Ghafarian, S, Ghaffari Jolfayi, A, Ghailan, K, Ghajar, A, Ghasemi, M, Ghasempour Dabaghi, G, Ghasemzadeh, A, Ghassemi, F, Ghazy, R, Gholami, A, Gholamrezanezhad, A, Gholizadeh, N, Ghorbani, M, Gil, A, Gil, G, Gilbertson, N, Gill, P, Gill, T, Gindaba, E, Girmay, A, Glasbey, J, Gnedovskaya, E, Göbölös, L, Godinho, M, Goel, A, Golechha, M, Goleij, P, Golinelli, D, Gomes, N, Gopalani, S, Gorini, G, Goudarzi, H, Goulart, A, Gouravani, M, Goyal, A, Graham, S, Grivna, M, Grosso, G, Guan, S, Guarducci, G, Gubari, M, Guha, A, Guicciardi, S, Gulati, S, Gulisashvili, D, Gunawardane, D, Guo, C, Gupta, A, Gupta, B, Gupta, M, Gupta, R, Gupta, S, Gupta, V, Habibzadeh, F, Habibzadeh, P, Hadaro, T, Hadian, Z, Haep, N, Haghi-Aminjan, H, Haghmorad, D, Hagins, H, Haile, D, Hailu, A, Hajj Ali, A, Halboub, E, Halimi, A, Hall, B, Haller, S, Halwani, R, Hamadeh, R, Hamdy, N, Hameed, S, Hamidi, S, Hammoud, A, Hanif, A, Hanifi, N, Haq, Z, Haque, M, Harapan, H, Hargono, A, Haro, J, Hasaballah, A, Hasan, I, Hasan, M, Hasan, S, Hasani, H, Hasanian, M, Hashmeh, N, Hasnain, M, Hassan, A, Hassan, I, Hassan Zadeh Tabatabaei, M, Hassani, S, Hassanipour, S, Hassankhani, H, Haubold, J, Havmoeller, R, Hay, S, Hebert, J, Hegazi, O, Hegena, T, Heidari, G, Heidari, M, Helfer, B, Hemmati, M, Henson, C, Herbert, M, Herteliu, C, Heuer, A, Hezam, K, Hinneh, T, Hiraike, Y, Hoan, N, Holla, R, Hon, J, Hoque, M, Horita, N, Hossain, S, Hosseini, S, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hoven, H, Hsairi, M, Hsu, J, Hu, C, Huang, J, Huda, M, Hulland, E, Hultström, M, Hushmandi, K, Hussain, J, Hussein, N, Huynh, C, Huynh, H, Ibitoye, S, Idowu, O, Ihler, A, Ikeda, N, Ikuta, K, Ilesanmi, O, Ilic, I, Ilic, M, Imam, M, Immurana, M, Inbaraj, L, Irham, L, Isa, M, Islam, M, Ismail, F, Ismail, N, Iso, H, Isola, G, Iwagami, M, Iwu, C, Iwu-Jaja, C, J, V, Jaafari, J, Jacob, L, Jacobsen, K, Jadidi-Niaragh, F, 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Bhawna, Gupta, Mohak, Gupta, Rahul, Gupta, Rajat Das, Gupta, Rajeev, Gupta, Sapna, Gupta, Veer Bala, Gupta, Vijai Kumar, Gupta, Vivek Kumar, Habibzadeh, Farrokh, Habibzadeh, Parham, Hadaro, Tesfahun Simon, Hadian, Zahra, Haep, Nils, Haghi-Aminjan, Hamed, Haghmorad, Dariush, Hagins, Hailey, Haile, Demewoz, Hailu, Alemayehu, Hajj Ali, Adel, Halboub, Esam S, Halimi, Aram, Hall, Brian J, Haller, Sebastian, Halwani, Rabih, Hamadeh, Randah R, Hamdy, Nadia M, Hameed, Sajid, Hamidi, Samer, Hammoud, Ahmad, Hanif, Asif, Hanifi, Nasrin, Haq, Zaim Anan, Haque, Md Rabiul, Harapan, Harapan, Hargono, Arief, Haro, Josep Maria, Hasaballah, Ahmed I, Hasan, Ikramul, Hasan, Mohammad Jahid, Hasan, S M Mahmudul, Hasani, Hamidreza, Hasanian, Mohammad, Hashmeh, Nadim, Hasnain, Md Saquib, Hassan, Amr, Hassan, Ikrama, Hassan Zadeh Tabatabaei, Mahgol Sadat, Hassani, Shokoufeh, Hassanipour, Soheil, Hassankhani, Hadi, Haubold, Johannes, Havmoeller, Rasmus J, Hay, Simon I, Hebert, Jeffrey J, Hegazi, Omar E, Hegena, Tadele Yohannes, Heidari, Golnaz, Heidari, Mohammad, Helfer, Bartosz, Hemmati, Mehdi, Henson, Claire A, Herbert, Molly E, Herteliu, Claudiu, Heuer, Austin, Hezam, Kamal, Hinneh, Thomas Kwadwo, Hiraike, Yuta, Hoan, Nguyen Quoc, Holla, Ramesh, Hon, Julia, Hoque, Mohammad Enamul, Horita, Nobuyuki, Hossain, Sahadat, Hosseini, Seyed Ehsan, Hosseinzadeh, Hassan, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hoven, Hanno, Hsairi, Mohamed, Hsu, Johnathan M, Hu, Chengxi, Huang, Junjie, Huda, Md Nazmul, Hulland, Erin N, Hultström, Michael, Hushmandi, Kiavash, Hussain, Javid, Hussein, Nawfal R, Huynh, Chantal K, Huynh, Hong-Han, Ibitoye, Segun Emmanuel, Idowu, Oluwatope Olaniyi, Ihler, Audrey L, Ikeda, Nayu, Ikuta, Kevin S, Ilesanmi, Olayinka Stephen, Ilic, Irena M, Ilic, Milena D, Imam, Mohammad Tarique, Immurana, Mustapha, Inbaraj, Leeberk Raja, Irham, Lalu Muhammad, Isa, Mustafa Alhaji, Islam, Md Rabiul, Ismail, Faisal, Ismail, Nahlah Elkudssiah, Iso, Hiroyasu, Isola, Gaetano, 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Kunle, Rout, Himanshu Sekhar, Roy, Bedanta, Roy, Nitai, Rubagotti, Enrico, Ruela, Guilherme de Andrade, Rumisha, Susan Fred, Runghien, Tilleye, Russo, Michele, Ruzzante, Sacha Walde, S N, Chandan, Saad, Aly M A, Saber, Korosh, Saber-Ayad, Maha Mohamed, Sabour, Siamak, Sacco, Simona, Sachdev, Perminder S, Sachdeva, Rajesh, Saddik, Basema, Saddler, Adam, Sadee, Bashdar Abuzed, Sadeghi, Ehsan, Sadeghi, Masoumeh, Sadeghi Majd, Elham, Saeb, Mohammad Reza, Saeed, Umar, Safari, Mehdi, Safi, Sare, Safi, Sher Zaman, Sagar, Rajesh, Sagoe, Dominic, Saheb Sharif-Askari, Fatemeh, Saheb Sharif-Askari, Narjes, Sahebkar, Amirhossein, Sahoo, Soumya Swaroop, Sahu, Monalisha, Saif, Zahra, Sajid, Mirza Rizwan, Sakshaug, Joseph W, Salam, Nasir, Salamati, Payman, Salami, Afeez Abolarinwa, Salaroli, Luciane B, Salehi, Leili, Salehi, Sana, Salem, Marwa Rashad, Salem, Mohammed Z Y, Salihu, Dauda, Salimi, Sohrab, Salum, Giovanni A, Samadi Kafil, Hossein, Samadzadeh, Sara, Samodra, Yoseph Leonardo, Samuel, Vijaya Paul, Samy, Abdallah M, Sanabria, Juan, Sanjeev, Rama Krishna, Sanna, Francesca, Santomauro, Damian Francesco, Santric-Milicevic, Milena M, Sarasmita, Made Ary, Saraswathy, Sivan Yegnanarayana Iyer, Saravanan, Aswini, Saravi, Babak, Sarikhani, Yaser, Sarmiento-Suárez, Rodrigo, Sarode, Gargi Sachin, Sarode, Sachin C, Sartorius, Benn, Sarveazad, Arash, Sathian, Brijesh, Sattin, Davide, Sawhney, Monika, Saya, Ganesh Kumar, Sayeed, Abu, Sayeed, Md Abu, Sayyah, Mehdi, Schinckus, Christophe, Schmidt, Maria Inês, Schuermans, Art, Schumacher, Austin E, Schutte, Aletta Elisabeth, Schwarzinger, Michaël, Schwebel, David C, Schwendicke, Falk, Selvaraj, Siddharthan, Semreen, Mohammad H, Senthilkumaran, Subramanian, Serban, Dragos, Serre, Marc L, Sethi, Yashendra, Shafie, Mahan, Shah, Humaira, Shah, Nilay S, Shah, Pritik A, Shah, Syed Mahboob, Shahbandi, Ataollah, Shaheen, Amira A, Shahid, Samiah, Shahid, Wajeehah, Shahsavari, Hamid R, Shahwan, Moyad Jamal, Shaikh, Masood Ali, Shaikh, Summaiya Zareen, Shalash, Ali S, Sham, Sunder, Shamim, Muhammad Aaqib, Shams-Beyranvand, Mehran, Shamshirgaran, Mohammad Ali, Shamsi, Mohammad Anas, Shanawaz, Mohd, Shankar, Abhishek, Sharfaei, Sadaf, Sharifan, Amin, Sharifi-Rad, Javad, Sharma, Manoj, Sharma, Ujjawal, Sharma, Vishal, Shastry, Rajesh P, Shavandi, Amin, Shehabeldine, Amr Mohamed Elsayed, Shehzadi, Somia, Sheikh, Aziz, Shen, Jiabin, Shetty, Adithi, Shetty, B Suresh Kumar, Shetty, Pavanchand H, Shiani, Amir, Shiferaw, Desalegn, Shigematsu, Mika, Shin, Min-Jeong, Shiri, Rahman, Shittu, Aminu, Shiue, Ivy, Shivakumar, K M, Shivarov, Velizar, Shool, Sina, Shorofi, Seyed Afshin, Shrestha, Rajan, Shrestha, Sunil, Shuja, Kanwar Hamza, Shuval, Kerem, Si, Yafei, Siddig, Emmanuel Edwar, Silva, Diego Augusto Santos, Silva, Luís Manuel Lopes Rodrigues, Silva, Soraia, Silva, Thales Philipe R, Simpson, Colin R, Singh, Abhinav, Singh, Balbir Bagicha, Singh, Baljinder, Singh, Garima, Singh, Harmanjit, Singh, Jasvinder A, Singh, Mahendra, Singh, Narinder Pal, Singh, Paramdeep, Singh, Surjit, Sinto, Robert, Sivakumar, Shravan, Siwal, Samarjeet Singh, Skhvitaridze, Natia, Skou, Søren T, Sleet, David A, Sobia, Farrukh, Soboka, Matiwos, Socea, Bogdan, Solaimanian, Shahabaddin, Solanki, Ranjan, Solanki, Shipra, Soliman, Sameh S M, Somayaji, Ranjani, Song, Yi, Sorensen, Reed J D, Soriano, Joan B, Soyiri, Ireneous N, Spartalis, Michael, Spearman, Sandra, Spencer, Cory N, Sreeramareddy, Chandrashekhar T, Stachteas, Panagiotis, Stafford, Lauryn K, Stanaway, Jeffrey D, Stanikzai, Muhammad Haroon, Stein, Caroline, Stein, Dan J, Steinbeis, Fridolin, Steiner, Caitlyn, Steinke, Sabine, Steiropoulos, Paschalis, Stockfelt, Leo, Stokes, Mark A, Straif, Kurt, Stranges, Saverio, Subedi, Narayan, Subramaniyan, Vetriselvan, Suleman, Muhammad, Suliankatchi Abdulkader, Rizwan, Sundström, Johan, Sunkersing, David, Sunnerhagen, Katharina S, Suresh, Vinay, Swain, Chandan Kumar, Szarpak, Lukasz, Szeto, Mindy D, Tabaee Damavandi, Payam, Tabarés-Seisdedos, Rafael, Tabatabaei, Seyyed Mohammad, Tabatabaei Malazy, Ozra, Tabatabaeizadeh, Seyed-Amir, Tabatabai, Shima, Tabche, Celine, Tabish, Mohammad, Tadakamadla, Santosh Kumar, Taheri Abkenar, Yasaman, Taheri Soodejani, Moslem, Taherkhani, Amir, Taiba, Jabeen, Takahashi, Ken, Talaat, Iman M, Tamuzi, Jacques Lukenze, Tan, Ker-Kan, Tang, Haosu, Tat, Nathan Y, Taveira, Nuno, Tefera, Yibekal Manaye, Tehrani-Banihashemi, Arash, Temesgen, Worku Animaw, Temsah, Mohamad-Hani, Teramoto, Masayuki, Terefa, Dufera Rikitu, Teye-Kwadjo, Enoch, Thakur, Ramna, Thangaraju, Pugazhenthan, Thankappan, Kavumpurathu Raman, Thapar, Rekha, Thayakaran, Rasiah, Thirunavukkarasu, Sathish, Thomas, Nihal, Thomas, Nikhil Kenny, Tian, Jing, Tichopad, Ales, Ticoalu, Jansje Henny Vera, Tiruye, Tenaw Yimer, Tobe-Gai, Ruoyan, Tolani, Musliu Adetola, Tolossa, Tadesse, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Fotis, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Trabelsi, Khaled, Tran, Jasmine T, Tran, Mai Thi Ngoc, Tran, Nghia Minh, Trico, Domenico, Trihandini, Indang, Troeger, Christopher E, Tromans, Samuel Joseph, Truyen, Thien Tan Tri Tai, Tsatsakis, Aristidis, Tsermpini, Evangelia Eirini, Tumurkhuu, Munkhtuya, Udoakang, Aniefiok John, Udoh, Arit, Ullah, Atta, Ullah, Saeed, Ullah, Sana, Umair, Muhammad, Umakanthan, Srikanth, Unim, Brigid, Unnikrishnan, Bhaskaran, Upadhyay, Era, Urso, Daniele, Usman, Jibrin Sammani, Vaithinathan, Asokan Govindaraj, Vakili, Omid, Valenti, Mario, Valizadeh, Rohollah, Van den Eynde, Jef, van Donkelaar, Aaron, Varga, Orsolya, Vart, Priya, Varthya, Shoban Babu, Vasankari, Tommi Juhani, Vasic, Milena, Vaziri, Siavash, Venketasubramanian, Narayanaswamy, Verghese, Nicholas Alexander, Verma, Madhur, Veroux, Massimiliano, Verras, Georgios-Ioannis, Vervoort, Dominique, Villafañe, Jorge Hugo, Villalobos-Daniel, Victor E, Villani, Leonardo, Villanueva, Gabriela Ines, Vinayak, Manish, Violante, Francesco S, Vlassov, Vasily, Vo, Bay, Vollset, Stein Emil, Volovat, Simona Ruxandra, Vos, Theo, Vujcic, Isidora S, Waheed, Yasir, Wang, Cong, Wang, Fang, Wang, Shu, Wang, Yanzhong, Wang, Yuan-Pang, Wanjau, Mary Njeri, Waqas, Muhammad, Ward, Paul, Waris, Abdul, Wassie, Emebet Gashaw, Weerakoon, Kosala Gayan, Weintraub, Robert G, Weiss, Daniel J, Weiss, Eli J, Weldetinsaa, Haftom Legese Legese, Wells, Katherine M, Wen, Yi Feng, Wiangkham, Taweewat, Wickramasinghe, Nuwan Darshana, Wilkerson, Caroline, Willeit, Peter, Wilson, Shadrach, Wong, Yen Jun, Wongsin, Utoomporn, Wozniak, Sarah, Wu, Chenkai, Wu, Dongze, Wu, Felicia, Wu, Zenghong, Xia, Juan, Xiao, Hong, Xu, Suowen, Xu, Xiaoyue, Xu, Yvonne Yiru, Yadav, Mukesh Kumar, Yaghoubi, Sajad, Yamagishi, Kazumasa, Yang, Lin, Yano, Yuichiro, Yaribeygi, Habib, Yasufuku, Yuichi, Ye, Pengpeng, Yesodharan, Renjulal, Yesuf, Subah Abderehim, Yezli, Saber, Yi, Siyan, Yiğit, Arzu, Yigzaw, Zeamanuel Anteneh, Yin, Dehui, Yip, Paul, Yismaw, Malede Berihun, Yon, Dong Keon, Yonemoto, Naohiro, You, Yuyi, Younis, Mustafa Z, Yousefi, Zabihollah, Yu, Chuanhua, Yu, Yong, Zadey, Siddhesh, Zadnik, Vesna, Zakham, Fathiah, Zaki, Nazar, Zakzuk, Josefina, Zamagni, Giulia, Zaman, Sojib Bin, Zandieh, Ghazal G Z, Zanghì, Aurora, Zar, Heather J, Zare, Iman, Zarimeidani, Fatemeh, Zastrozhin, Mikhail Sergeevich, Zeng, Youjie, Zhai, Chunxia, Zhang, Anthony Lin, Zhang, Haijun, Zhang, Liqun, Zhang, Meixin, Zhang, Yunquan, Zhang, Zhenyu, Zhang, Zhi-Jiang, Zhao, Hanqing, Zhao, Jeff T, Zhao, Xiu-Ju George, Zhao, Yang, Zhao, Yong, Zhong, Chenwen, Zhou, Jingjing, Zhou, Juexiao, Zhou, Shangcheng, Zhu, Bin, Zhu, Lei, Zhu, Zhaohua, Ziaeian, Boback, Ziafati, Makan, Zielińska, Magdalena, Zimsen, Stephanie R M, Zoghi, Ghazal, Zoller, Thomas, Zumla, Alimuddin, Zyoud, Sa'ed H, Zyoud, Samer H, Murray, Christopher J L, and Gakidou, Emmanuela
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- 2024
30. Ferroptosis‐Related Genes in IgA Nephropathy: Screening for Potential Targets of the Mechanism.
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Zhu, Wenhui, Chen, Yao, Xiao, Jing, Cheng, Chuchu, Ma, Guijie, Wang, Yang, Zhang, Yonggang, Chen, Ming, and Mohammadi, Saeed
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IGA glomerulonephritis ,GENE expression ,GENE ontology ,DATABASES ,ENCYCLOPEDIAS & dictionaries - Abstract
Aims: Exploring key genes and potential molecular pathways of ferroptosis in immunoglobulin A nephropathy (IgAN). Methods: The IgAN datasets and ferroptosis‐related genes (FRGs) were obtained in the Gene Expression Omnibus (GEO) and FerrDb database. Differentially expressed genes (DEGs) were identified using R software and intersected with FRGs to obtain differentially expressed FRGs (DE‐FRGs). After that, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis (PEA) and Gene Ontology (GO) functional annotation were performed on DE‐FRGs. In the Search Tool for the Retrieval of Interacting Genes (STRING) website, we construct a protein–protein interaction (PPI) network. The PPI network was further investigated with screening hub genes with Cytoscape software. The core genes were then subjected to gene set enrichment analysis (GSEA). Finally, the samples were analyzed for immune infiltration in R, and the correlation between hub genes and immune cells was analyzed. Results: A total of 347 DEGs were identified. CD44, CDO1, CYBB, IL1B, RRM2, AKR1C1, activated transcription factor‐3 (ATF3), CDKN1A, GDF15, JUN, MGST1, MIOX, MT1G, NR4A1, PDK4, TNFAIP3, and ZFP36 were determined as DE‐FRGs. JUN, IL1B, and ATF3 were then screened as hub genes. GSEA and immune infiltration analysis revealed that the hub genes were closely associated with immune inflammatory responses such as NOD‐like receptor signaling, IL‐17 signaling, and TNF signaling. Conclusions: Our results show that JUN and ATF3 are possibly critical genes in the process of IgAN ferroptosis and may be related with immune cell infiltration. [ABSTRACT FROM AUTHOR]
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- 2024
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31. Carbapenem Resistance in Acinetobacter calcoaceticus-baumannii Complex Isolates From Kathmandu Model Hospital, Nepal, Is Attributed to the Presence of blaOXA-23-like and blaNDM-1 Genes.
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Gurung, Anupama, Napit, Rajindra, Shrestha, Basudha, Lekhak, Binod, and Mohammadi, Saeed
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CARBAPENEMS ,CROSS-sectional method ,ACINETOBACTER infections ,MICROBIAL sensitivity tests ,RESEARCH funding ,DRUG resistance in microorganisms ,POLYMERASE chain reaction ,CHI-squared test ,LONGITUDINAL method ,DATA analysis software ,MOLECULAR diagnosis - Abstract
The Acinetobacter calcoaceticus-baumannii (ACB) complex, also known as ACB complex, consists of four bacterial species that can cause opportunistic infections in humans, especially in hospital settings. Conventional therapies for susceptible strains of the ACB complex include broad‐spectrum cephalosporins, β‐lactam/β‐lactamase inhibitors, and carbapenems. Unfortunately, the effectiveness of these antibiotics has declined due to increasing rates of resistance. The predominant resistance mechanisms identified in the ACB complex involve carbapenem‐resistant (CR) oxacillinases and metallo‐β‐lactamases (MBLs). This research, conducted at Kathmandu Model Hospital in Nepal, sought to identify genes associated with CR, specifically blaNDM‐1, blaOXA‐23‐like, and blaOXA‐24‐like genes in carbapenem‐resistant Acinetobacter calcoaceticus-baumannii (CR‐ACB) complex. Additionally, the study is aimed at identifying the ACB complex through the sequencing of the 16s rRNA gene. Among the 992 samples collected from hospitalized patients, 43 (approximately 4.334%) tested positive for the ACB complex. These positive samples were mainly obtained from different hospital units, including intensive care units (ICUs); cabins; and neonatal, general, and maternity wards. The prevalence of infection was higher among males (58.14%) than females (41.86%), with the 40–50 age group showing the highest infection rate. In susceptibility testing, colistin and polymyxin B exhibited a susceptibility rate of 100%, whereas all samples showed resistance to third‐generation cephalosporins. After polymyxins, gentamicin (30.23%) and amikacin (34.88%) demonstrated the highest susceptibility. A substantial majority (81.45%) of ACB complex isolates displayed resistance to carbapenems, with respiratory and pus specimens being the primary sources. Polymerase chain reaction (PCR) revealed that the primary CR gene within the ACB complex at this hospital was blaOXA-23-like, followed by blaNDM-1. To ensure the accuracy of the phenotypic assessment, 12 samples were chosen for 16s rRNA sequencing using Illumina MiSeq™ to confirm that they are Acinetobacter species. QIIME 2.0 analysis confirmed all 12 isolates to be Acinetobacter species. In the hospital setting, a substantial portion of the ACB complex carries CR genes, rendering carbapenem ineffective for treatment. [ABSTRACT FROM AUTHOR]
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- 2024
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32. The Relationship between the Lifestyle of the Allogeneic Stem Cell Donors and the Number of Donated CD34+ and CD3+ Cells.
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Sayadi, Leila, Mohammadi, Saeed, and Aminian, Parivash
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HEMATOPOIETIC stem cell transplantation , *STEM cell transplantation , *HEMATOPOIETIC stem cells , *STEM cell donors , *CELL separation - Abstract
Background: Hematopoietic stem cell transplantation (HSCT) is considered as the last treatment option in many life-threatening diseases. The number of donated cells can affect transplantation success. This study attempted to investigate the relationship between the health-promoting lifestyle of allogeneic stem cell donors and the number of donated CD34+ and CD3+ cells. Materials and Methods: The study was a descriptive correlational study in which 100 peripheral blood stem cells donors participated. A demographic form and health-promoting lifestyle profile-II questionnaire were distributed to participants, and then cell separation was started. Afterward, the results of CD34 + and CD3 + cell counts, as well as other clinical parameters of the participants, were recorded. The collected data were analyzed by descriptive and analytical statistical methods . Results: The results showed that the mean total health-promoting lifestyle profile score for hematopoietic stem cell donors was 2.876±0.461. There was no significant relationship between the health- promoting lifestyle score and the number of CD34+, CD3+ cells and CD3+/CD34+ ratio. A positive and significant correlation was found between the weight of the donors and the number of CD34+ (P < 0.001) and CD3+ cells (P = 0.001). The number of CD34+ cells was significantly different between women and men (P = 0.009). Conclusion: Lifestyle had no significant effect on the number of CD3+/CD34+ cells. Moreover, the number of CD34+ cells was significantly higher in men, so males should be preferentially recruited as donors for the HSCT procedure. [ABSTRACT FROM AUTHOR]
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- 2024
33. Analytical investigation on the electro-optical characteristics of white graphene
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Rahmani, Komeil, Mohammadi, Saeed, and Danaie, Mohammad
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- 2021
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34. The relationship between individual entrepreneurial orientation (IEO) and entrepreneurial bricolage: exploring passion and perseverance
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Mohammadi, Saeed
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- 2021
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35. Augmenting the Antitumor Efficacy of Natural Killer Cells via SynNotch Receptor Engineering for Targeted IL-12 Secretion
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Ahmadnia, Ali, primary, Mohammadi, Saeed, additional, Yamchi, Ahad, additional, Kalani, Mohamad Reza, additional, Farazmandfar, Touraj, additional, Khosravi, Ayyoub, additional, and Memarian, Ali, additional
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- 2024
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36. PRISMA hyperspectral imagery for mapping alteration zones associated with Kuhpanj porphyry copper deposit, Southern Iran
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Esmaeili, Maryam, primary, Fathianpour, Nader, additional, and Soltani-Mohammadi, Saeed, additional
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- 2024
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37. The migration of metastatic breast cancer cells is regulated by matrix stiffness via YAP signalling
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Chen, Wei, Park, Shihyun, Patel, Chrishma, Bai, Yuxin, Henary, Karim, Raha, Arjun, Mohammadi, Saeed, You, Lidan, and Geng, Fei
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- 2021
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38. Antimicrobial, Anti‐inflammatory, and Wound Healing Properties of Myrtus communis Leaf Methanolic Extract Ointment on Burn Wound Infection Induced by Methicillin‐Resistant Staphylococcus aureus in Rats.
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Jafari, Zohre, Bardania, Hassan, Barmak, Mehrzad Jafari, Eslami, Saba, Mahmoudi-Mourderaz, Yaser, Roustaei, Narges, Talebianpoor, Mohammad Sharif, Kokhdan, Esmaeel Panahi, Khoramrooz, Seyed Sajjad, and Mohammadi, Saeed
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ANTI-inflammatory agents ,WOUND healing ,BIOLOGICAL models ,BURNS & scalds ,NITRIC oxide ,T-test (Statistics) ,OINTMENTS ,METHICILLIN-resistant staphylococcus aureus ,WOUND infections ,TREATMENT effectiveness ,DESCRIPTIVE statistics ,PLANT extracts ,ANTI-infective agents ,RATS ,ANIMAL experimentation ,ANTIOXIDANTS ,ONE-way analysis of variance ,LEAVES ,COMPARATIVE studies ,DATA analysis software ,MALONDIALDEHYDE ,PHARMACODYNAMICS - Abstract
Objective(s). Given the increasing rate of methicillin‐resistant Staphylococcus aureus (MRSA) resistance to antibiotics, the use of plant‐based antimicrobials to treat the infection has been considered. This study is aimed at evaluating the effect of Myrtus communis leaf extract ointment and silver nanoparticles on the healing of burn wounds caused by MRSA in rats. Materials and Methods. In a research experiment, 48 male Wistar rats were anesthetized and second‐degree burns were induced on their backs. The rats' wounds were then uniformly inoculated with MRSA. Various treatments were applied to the burn wounds daily, including Myrtus ointment, silver nanoparticles, silver nanoparticles‐Myrtus ointment, silver sulfadiazine‐Myrtus ointment, silver sulfadiazine 1%, mupirocin ointment, and a positive control. The study measured the antimicrobial effects, wound area, percentage of wound healing, antioxidant capacities, malondialdehyde, and nitric oxide concentrations in the serum of the rats. Data analysis was performed using GraphPad software, with one‐way ANOVA and Tukey's tests used to determine the statistical significance of the results. Results. Rats treated with Myrtus ointment, silver nanoparticles‐Myrtus ointment, and mupirocin had reduced bacterial growth compared to the positive control group, nanoparticle ointment, and silver sulfadiazine (P < 0.05). The wound area of the Myrtus ointment group decreased significantly on the seventh and fourteenth days, as well as the level of MDA and nitric oxide, compared to the other groups. In Myrtus and silver sulfadiazine‐Myrtus ointment increased the thickness of the epidermis and dermis compared to the other groups. Conclusion. Based on the anti‐inflammatory, antimicrobial, and wound healing properties of Myrtus, with further studies, an ointment of this plant may be used as a main or complementary treatment for burn wound infections caused by MRSA. [ABSTRACT FROM AUTHOR]
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- 2024
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39. Rosuvastatin Intervention in Patients with Chronic Hepatitis B (CHB) Expands CD14+ CD16− Classical Monocytes via Aryl Hydrocarbon Receptor (AHR).
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Rahmati, Mina, Zare Ebrahimabad, Mojtaba, Langari, Alale, Najafi, Ali, Taziki, Shohreh, Norouzi, Alireza, Teimoorian, Mehrdad, Khorasani, Milad, and Mohammadi, Saeed
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CHRONIC hepatitis B ,ARYL hydrocarbon receptors ,CD14 antigen ,MONOCYTES ,MACROPHAGES - Abstract
Chronic hepatitis B (CHB) poses treatment challenges, with treatment response and disease outcome often determined by the immune response, particularly mononuclear phagocytes. Monocytes can differentiate into various subpopulations influenced by AHR. Statins, known for inflammation modulation, may impact monocyte function via AHR activation. This study explored rosuvastatin (RSV)'s effects on monocyte subtypes, inflammatory markers, and AHR in CHB patients. Fifteen CHB patients were randomly assigned to receive either 20 mg RSV or a placebo daily for three months. Flow cytometry assessed CD14+ CD16− (classical), CD14+ CD16+ (intermediate), and CD14dim CD16+ (patrolling) monocyte subtypes, along with AHR levels in each subset. ELISA quantified cytokines IL-6, IFN-γ, IL-12, IL-10, TNF-α, TGF-β, and IL-1β. RSV expanded CD14+ CD16− classical and reduced CD14+ CD16+ intermediate monocytes in CHB patients while increasing AHR+ cell percentages in all subsets. RSV treatment upregulated key AHR target genes (Cyp1a1, Cyp1b1, and ARNT), indicating robust AHR signaling activation. It also reduced pro-inflammatory cytokine levels (IL-6, IFNγ, IL-12, TNF-α) and elevated anti-inflammatory cytokines (IL-10, TGF-β). Thus, RSV may modulate the immune response by altering monocyte subtypes in CHB patients via AHR activation. [ABSTRACT FROM AUTHOR]
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- 2024
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40. Effect of Transcutaneous Electrical Nerve Stimulation on the Pain Intensity During Insertion of Needle in Patients Undergoing Spinal Anesthesia: A Randomized Controlled Study
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AminiSaman, Javad, Karimpour, Hasan A., Hemmatpour, Behzad, Mohammadi, Saeed, Darvishi, Saeed, and Kawyannejad, Rasool
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- 2020
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41. Effects of mobilized peripheral blood stem cells on treatment of primary lower extremity lymphedema
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Ehyaeeghodraty, Vida, Molavi, Behnam, Nikbakht, Mohsen, Malek Mohammadi, Ashraf, Mohammadi, Saeed, Ehyaeeghodraty, Navid, Fallahi, Babak, Mousavi, Seyed Asadollah, Vaezi, Mohammad, and Sefidbakht, Salma
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- 2020
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42. Corrections to “Reducing Screening Effect in Close-Packed Si Field Emitter Arrays” [Aug 23 4387-4393]
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Ghotbi, Shabnam, primary and Mohammadi, Saeed, additional
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- 2023
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43. Statistical Phantoms and Determining the Uncertainty of the Thyroid Mathematical Phantom in Internal Dosimetry Using the Monte Carlo Method
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Ragheb, Vahid, Sajjadi, Zahra, and Mohammadi, Saeed
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- 2020
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44. Molecular mechanisms of vitamin D plus Bisphenol A effects on adipogenesis in human adipose-derived mesenchymal stem cells
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Salehpour, Amin, Shidfar, Farzad, Hedayati, Mehdi, Farshad, Ali Asghar, Tehrani, Asal Neshatbini, and Mohammadi, Saeed
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- 2021
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45. 1,25-Dihydroxyvitamin D3 modulates adipogenesis of human adipose-derived mesenchymal stem cells dose-dependently
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Salehpour, Amin, Hedayati, Mehdi, Shidfar, Farzad, Neshatbini Tehrani, Asal, Farshad, Ali Asghar, and Mohammadi, Saeed
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- 2021
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46. Correction to: 1,25-Dihydroxyvitamin D3 modulates adipogenesis of human adipose-derived mesenchymal stem cells dose-dependently
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Salehpour, Amin, Hedayati, Mehdi, Shidfar, Farzad, Tehrani, Asal Neshatbini, Farshad, Ali Asghar, and Mohammadi, Saeed
- Published
- 2021
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47. Study of Back Bending in 157,158Er Isotopes by Using Electromagnetic Reduced Transition Probabilities
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Shahriarie, Mehran, Mohammadi, Saeed, and Firouzi, Zohreh
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- 2020
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48. Encapsulation of Leflunomide (LFD) in a novel niosomal formulation facilitated its delivery to THP-1 monocytic cells and enhanced Aryl hydrocarbon receptor (AhR) nuclear translocation and activation
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Hasani, Mahsa, Sani, Neda Abbaspour, Khodabakhshi, Behnaz, Arabi, Mehdi Sheikh, Mohammadi, Saeed, and Yazdani, Yaghoub
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- 2019
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49. Transcutaneous Electrical Nerve Stimulation at the Acupuncture Points to Relieve Pain of Patients Under Mechanical Ventilation: A Randomized Controlled Study
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AminiSaman, Javad, Mohammadi, Saeed, Karimpour, HasanAli, Hemmatpour, Behzad, Sharifi, Hengameh, and Kawyannejad, Rasool
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- 2018
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50. Assessment of Standard Operating Procedures (SOPs) Preparing Hygienic Condition in the Blood Donation Centers during the Outbreak of COVID-19
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Mohammadi, Saeed, primary, Tabatabaei Yazdi, Seyed Morteza, additional, Balagholi, Sahar, additional, Saremi, Saeid, additional, Dabbaghi, Rasul, additional, Ferdowsi, Shirin, additional, and Eshghi, Peyman, additional
- Published
- 2023
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