BackgroundAlthough integrins have been implicated in the progression of breast cancer, the exact mechanism whereby they exert this regulation is clearly not understood. To understand the role of integrins in breast cancer, we examined the expression levels of several integrins in mouse breast cancer cell lines by flow cytometry and the data were validated by Western and RT-PCR analysis. The importance of integrins in cell migration and cell invasion was examined by in vitro assays. Further the effect of integrins on metastasis was investigated by in vivo experimental metastasis assays using mouse models.ResultsIntegrin α5 subunit is highly expressed in the nonmetastatic cell line 67NR and is significantly low in the highly invasive cell line 4T1. In contrast, expression levels of integrin α6 subunit are high in 4T1 cells and low in 67NR cells. In vitro data indicated that overexpression of α5 subunit and knockdown of α6 integrin subunit inhibited cell proliferation, migration, and invasion. Our in vivo findings indicated that overexpression of integrin α5 subunit and knockdown of α6 subunit decreased the pulmonary metastasis property of 4T1 cells. Our data also indicated that overexpression of alpha 5 integrin subunit and suppression of alpha6 integrin subunit inhibited cells entering into S phase by up-regulating p27, which results in downregulation of cyclinE/CDK2 complexes, This suggests that these integrins regulate cell growth through their effects on cell-cycle-regulated proteins. We also found that modulation of these integrins upregulates E2F, which may induce the expression of chk1 to regulate cdc25A/cyclin E/CDK2/Rb in a feedback loop mechanism.ConclusionThis study indicates that Integrin α5 subunit functions as a potential metastasis suppressor, while α6 subunit functions as a metastasis promoter. The modulation of integrins reduces cdc25 A, another possible mechanism for downregulation of CDK2. Taken together we demonstrate a link between integrins and the chk1-cdc25-cyclin E/CDK2-Rb pathway.
Nitric oxide (NO) acts in a concentration and redox-dependent manner to counteract oxidative stress either by directly acting as an antioxidant through scavenging reactive oxygen species (ROS), such as superoxide anions (O(2)(-)*), to form peroxynitrite (ONOO(-)) or by acting as a signaling molecule, thereby altering gene expression. NO can interact with different metal centres in proteins, such as heme-iron, zinc-sulfur clusters, iron-sulfur clusters, and copper, resulting in the formation of a stable metal-nitrosyl complex or production of varied biochemical signals, which ultimately leads to modification of protein structure/function. The thiols (ferrous iron-thiol complex and nitrosothiols) are also involved in the metabolism and mobilization of NO. Thiols bind to NO and transport it to the site of action whereas nitrosothiols release NO after intercellular diffusion and uptake into the target cells. S-nitrosoglutathione (GSNO) also has the ability to transnitrosylate proteins. It is an NO˙ reservoir and a long-distance signaling molecule. Tyrosine nitration of proteins has been suggested as a biomarker of nitrosative stress as it can lead to either activation or inhibition of target proteins. The exact molecular mechanism(s) by which exogenous and endogenously generated NO (or reactive nitrogen species) modulate the induction of various genes affecting redox homeostasis, are being extensively investigated currently by various research groups. Present review provides an in-depth analysis of the mechanisms by which NO interacts with and modulates the activity of various ROS scavenging enzymes, particularly accompanying ROS generation in plants in response to varied abiotic stress.
State-of-the-art knowledge base completion (KBC) models predict a score for every known or unknown fact via a latent factorization over entity and relation embeddings. We observe that when they fail, they often make entity predictions that are incompatible with the type required by the relation. In response, we enhance each base factorization with two type-compatibility terms between entityrelation pairs, and combine the signals in a novel manner. Without explicit supervision from a type catalog, our proposed modification obtains up to 7% MRR gains over base models, and new state-of-the-art results on several datasets. Further analysis reveals that our models better represent the latent types of entities and their embeddings also predict supervised types better than the embeddings learned by baseline models.
Background: This work examines the importance of interaction between Nischarin and LKB1. Results: Nischarin and LKB1 interact in vivo. Absence of Nischarin and LKB1 increases cell migration and tumor growth. Conclusion: This is the first report showing that two suppressors work in concert to inhibit cell migration. Significance: Understanding the mechanisms of regulation of tumor suppressors may have many therapeutic advantages.
Research on temporal knowledge bases, which associate a relational fact (s, r, o) with a validity time period (or time instant), is in its early days. Our work considers predicting missing entities (link prediction) and missing time intervals (time prediction) as joint Temporal Knowledge Base Completion (TKBC) tasks, and presents TIMEPLEX, a novel TKBC method, in which entities, relations and, time are all embedded in a uniform, compatible space. TIMEPLEX exploits the recurrent nature of some facts/events and temporal interactions between pairs of relations, yielding stateof-the-art results on both prediction tasks.We also find that existing TKBC models heavily overestimate link prediction performance due to imperfect evaluation mechanisms. In response, we propose improved TKBC evaluation protocols for both link and time prediction tasks, dealing with subtle issues that arise from the partial overlap of time intervals in gold instances and system predictions.
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