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| 1 | Cadmium-induced in fertility in male mice显示文摘 | Monsefi M Alaee S Moradshahi A | | 0，，01： | 1 |
| 2 | Cadmium-induced infertility in male mice显示文摘 | MONSEFI M ALAEE S MORADSHAHI A | 2009 | Environ Toxicol2009，25，1： | 1 |
| 3 | Lectins influence chondrogenesis and osteogenesis in limb bud mesenchymal cells显示文摘 | Talaei -Khozani T Monsefi M Ghasemi M | 2011 | Glycoconj J2011，28，2： | 1 |
| 4 | Cadmium - induced infer- tility in male mice显示文摘 | Monsefi M Alaee S Moradshahi A | 2010 | Environ Toxicol2010，25，1： | 1 |
| 5 | Cadmium - induced infertil- ity in male mice显示文摘 | Monsefi M Alaee S Moradshahi A | 2010 | Environ Toxicol2010，25，： | 1 |
| 6 | Online cost-sensitive neural network classifiers for non-stationary and imbalanced data streams 显示文摘 | Ghazikhani A Monsefi R Yazdi H S | 2013 | Neural Computing Applications2013，23，5： | 1 |
| 7 | High-dose chemotherapy followed by autologous stem cell transplantation for patients with relapsed or refractory Hodgkin lymphoma: a systematic review with meta-analysis 显示文摘 | RanceaM von TresckowB MonsefI | 2014 | Crit Rev Oncol Hematol2014，92，1： | 1 |
| 8 | Ensemble of online neural networks for nonstationary and imbalanced data streams显示文摘 | Ghazikhani A Monsefi R Yazdi H S | 2013 | Neurocomputing2013，122，： | 1 |
| 9 | Network-based identification of feedback modules that control RhoA activity and cell migration显示文摘Cancer cell migration enables metastatic spread causing most cancer deaths.Rho-family GTPases control cell migration,but being embedded in a highly interconnected feedback network,the control of their dynamical behavior during cell migration remains elusive.To address this question,wereconstructed the Rho-family GTPases signaling network involved in cell migration,and developed a Boolean network model to analyze the different states and emergent rewiring of the Rho-family GTPases signaling network at protrusions and during extracellular matrix-dependent cell migration.Extensive simulations and experimental validations revealed that the bursts of RhoA activity induced at protrusions by EGFare regulated by a negative-feedback module composed of Src,FAK,and CSK.Interestingly,perturbing this module interfered with cyclic Rho activation and extracellular matrix-dependent migration,suggesting that CSK inhibition can be a novel and effective intervention strategy for blocking extracellular matrix-dependent cancer cell migration,while Src inhibition might fail,depending on the genetic background of cells.Thus,this study provides new insights into the mechanisms that regulate the intricate activation states of Rho-family GTPases during extracellular matrix-dependent migration,revealing potential new targets for interfering with extracellular matrix-dependent cancer cell migration. | Tae-Hwan Kim Naser Monsefi Je-Hoon Song Alex von Kriegsheim Drieke Vandamme Olivier Pertz Boris NKholodenko Walter Kolch Kwang-Hyun Cho | 2015 | Journal of Molecular Cell Biology2015，7，3： | 0 |
| 10 | Smart and collaborative industrial IoT: A federated learning and data space approach显示文摘Industry 4.0 has become a reality by fusing the Industrial Internet of Things(IIoT)and Artificial Intelligence(AI),providing huge opportunities in the way manufacturing companies operate.However,the adoption of this paradigm shift,particularly in the field of smart factories and production,is still in its infancy,suffering from various issues,such as the lack of high-quality data,data with high-class imbalance,or poor diversity leading to inaccurate AI models.However,data is severely fragmented across different silos owned by several parties for a range of reasons,such as compliance and legal concerns,preventing discovery and insight-driven IIoT innovation.Notably,valuable and even vital information often remains unutilized as the rise and adoption of AI and IoT in parallel with the concerns and challenges associated with privacy and security.This adversely influences interand intra-organization collaborative use of IIoT data.To tackle these challenges,this article leverages emerging multi-party technologies,privacy-enhancing techniques(e.g.,Federated Learning),and AI approaches to present a holistic,decentralized architecture to form a foundation and cradle for a cross-company collaboration platform and a federated data space to tackle the creeping fragmented data landscape.Moreover,to evaluate the efficiency of the proposed reference model,a collaborative predictive diagnostics and maintenance case study is mapped to an edge-enabled IIoT architecture.Experimental results show the potential advantages of using the proposed approach for multi-party applications accelerating sovereign data sharing through Findable,Accessible,Interoperable,and Reusable(FAIR)principles. | Bahar Farahani Amin Karimi Monsefi | 2023 | Digital Communications and Networks2023，9，2： | 0 |
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