Breast cancer has grown to be the second leading cause of cancer-related deaths in women. Only a few treatment options are available for breast cancer due to the widespread occurrence of ...chemoresistance, which emphasizes the need to discover and develop new methods to treat this disease. Signal transducer and activator of transcription 3 (STAT3) is an early tumor diagnostic marker and is known to promote breast cancer malignancy. Recent clinical and preclinical data indicate the involvement of overexpressed and constitutively activated STAT3 in the progression, proliferation, metastasis and chemoresistance of breast cancer. Moreover, new pathways comprised of upstream regulators and downstream targets of STAT3 have been discovered. In addition, small molecule inhibitors targeting STAT3 activation have been found to be efficient for therapeutic treatment of breast cancer. This systematic review discusses the advances in the discovery of the STAT3 pathways and drugs targeting STAT3 in breast cancer. Video abstract.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Many physical and social systems are best described by networks. And the structural properties of these networks often critically determine the properties and function of the resulting mathematical ...models. An important method to infer the correlations between topology and function is the detection of community structure, which plays a key role in the analysis, design, and optimization of many complex systems. The nonnegative matrix factorization has been used prolifically to that effect in recent years, although it cannot guarantee balanced partitions, and it also does not allow a proactive computation of the number of communities in a network. This indicates that the nonnegative matrix factorization does not satisfy all the nonnegative low-rank approximation conditions. Here we show how to resolve this important open problem by optimizing the identifiability of community structure. We propose a new form of nonnegative matrix decomposition and a probabilistic surrogate learning function that can be solved according to the majorization-minimization principle. Extensive in silico tests on artificial and real-world data demonstrate the efficient performance in community detection, regardless of the size and complexity of the network.
The preparation of fire-safe and high-performance carbon fiber reinforced composites with reprocessable resin matrix and recyclable reinforced fibers is of great importance and particularly urgent to ...solve the current overreliance on petrochemical resources for composite raw materials. Herein, we propose an effective strategy to simultaneously solve the flammability and nonrecyclability of the epoxy resin-based composites, in the form of fire-safe and catalyst-free dynamic transesterification networks by introducing a phosphaphenanthrene-derived diol as a multifunctional modifier for transesterification without using any toxic catalysts. In this strategy, the phosphaphenanthrene moieties enhanced the fire safety; while the hydroxy groups promoted the construction of catalyst-free dynamic transesterification networks. To our delight, the generated epoxy resin and its composite exhibit excellent mechanical properties, high thermal stability, fire safety, fast repairability and malleability. Furthermore, the resin matrix can be dissolved as the low-mass diol molecules participate in bond exchange reactions to achieve CFs with nearly 100% recyclability.
A new strategy was proposed to design a fire-safe vitrimer with catalyst-free adaptable ester-linked networks and its composite. Furthermore, the vitrimer matrix in the composite was degraded to achieve carbon fibers with nearly 100% recyclability.
In many electronic commerce systems, detecting significant clusters is of great value to the analysis, design, and optimization of the commerce behaviors. In this article, we propose a new dynamical ...approach to detect the cluster configuration fast and accurately which can be applied to electronic commerce systems. First, we analyze the two-stage game in which the leader group members make contributions prior to the follower group, and propose an exact index, i.e., the leadership , to characterize the key leaders. Then an efficient dynamical system is used to guarantee the cluster configuration converges to an optimal state, which assigns each node to the corresponding cluster based on quality optimization, repeatedly. Our method is of high efficiency-the exponential term in the proposed dynamical system makes the convergence to be very fast with a nearly linear time. Extensive experiments on multiple types of datesets demonstrate the state-of-the-art performance of proposed method.
The studies of multiplex networks are increasingly popular in recent years. Modeling multiple complex systems as a multiplex network has refreshed our understanding about the structure and dynamics ...of various real-world systems. As an important variant of the voter models, belief formation dynamics such as the asynchronous belief percolation (ABP) model has attracted much attention from statistical physics and network science communities. Existing studies of the ABP model mainly focus on the applications to single networks, whereas how the structure of multiplex networks affects its dynamical behavior is still not well understood. To close this gap, we propose a multi-scale ABP model that takes into account the differential velocities of belief propagation at different subnetworks within the multiplex network. Using extensive computer simulations, we find that (i) increasing the degree correlation between subnetworks can promote nodes with minority belief to form stable clusters and (ii) minority nodes require less initial supports to survive in multiplex networks with respect to single networks. Our conclusion is robust against the detailed topology of the subnetworks that constitute the multiplex network.
Flame retardancy and recyclability are two important issues in the research field of thermosets, particularly for epoxy resin (EP) with the biggest market share. It is of great importance, but rarely ...achievable, to integrate these properties simultaneously into EP. Herein, we report a facile way to prepare intrinsically flame-retardant epoxy vitrimers combining rapid recycling and multiple shape memory effects by introducing dynamic ester-linkages with catalytic transesterification activity into the crosslinking networks of EP. The flame-retardant epoxy vitrimers exhibited high Tg (∼110.7 °C), desirable thermal stability and excellent flame retardancy with UL-94 V-0 rating, and high LOI of ∼34%. Also, the value of the peak heat release rate (PHRR) and the total heat release (THR) showed 63% and 32% reduction, respectively. Meanwhile, flame-retardant epoxy vitrimers showed high malleability that could be reprocessed in 15 min at 200 °C without sacrificing the mechanical properties and flame retardancy. Moreover, the dynamic transesterification network allowed flame-retardant EP to access multiple shape memory effect. The design of flame-retardant epoxy vitrimers provide a prime example to foster the cyclic utilization of flame-retardant thermosetting polymers.
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•A facile strategy was proposed to prepare intrinsically flame-retardant epoxy vitrimers.•The epoxy vitrimers owned high Tg, desirable thermal stability and excellent flame retardancy.•The epoxy vitrimers displayed fast recyclability (∼15 min) without loss in flame retardancy and mechanical properties.•The multiple shape memory performance of the epoxy vitrimers was easily manipulated.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Well-being is a crucial necessity within the educational setting that is also taken into account as a central aspect of people's inclination in the subject of positive psychology (PP) study which is ...vital for the learners' affective equilibrium and proper development and improvement. Likewise, learners' engagement has been demonstrated to have a fundamental function in education. A great amount of attention has been given to this concept and its possible indicators because of its role at the core of learners' educational achievement. Alternatively, it is commonly maintained that self-efficacy has turned into a significant mental concept enhancing the educational cycle and educational presentation that influences learners' decisions regarding their educational assignment and manners and their way of thinking and feeling when it comes to education. This review attempts to survey the role of learners' self-efficacy as a mediator on their well-being and academic engagement. In conclusion, some suggestions and commendations have been proposed for language-teaching participants in scholastic situations.
Mining communities or clusters in networks is valuable in analyzing, designing, and optimizing many natural and engineering complex systems, e.g., protein networks, power grid, and transportation ...systems. Most of the existing techniques view the community mining problem as an optimization problem based on a given quality function(e.g., modularity), however none of them are grounded with a systematic theory to identify the central nodes in the network. Moreover, how to reconcile the mining efficiency and the community quality still remains an open problem. In this paper, we attempt to address the above challenges by introducing a novel algorithm. First, a kernel function with a tunable influence factor is proposed to measure the leadership of each node, those nodes with highest local leadership can be viewed as the candidate central nodes. Then, we use a discrete-time dynamical system to describe the dynamical assignment of community membership; and formulate the serval conditions to guarantee the convergence of each node's dynamic trajectory, by which the hierarchical community structure of the network can be revealed. The proposed dynamical system is independent of the quality function used, so could also be applied in other community mining models. Our algorithm is highly efficient: the computational complexity analysis shows that the execution time is nearly linearly dependent on the number of nodes in sparse networks. We finally give demonstrative applications of the algorithm to a set of synthetic benchmark networks and also real-world networks to verify the algorithmic performance.
Liver fibrosis is a reversible wound-healing process aimed at maintaining organ integrity, and presents as the critical pre-stage of liver cirrhosis, which will eventually progress to hepatocellular ...carcinoma in the absence of liver transplantation. Fibrosis generally results from chronic hepatic injury caused by various factors, mainly viral infection, schistosomiasis, and alcoholism; however, the exact pathological mechanisms are still unknown. Although numerous drugs have been shown to have antifibrotic activity in vitro and in animal models, none of these drugs have been shown to be efficacious in the clinic. Importantly, hepatic stellate cells(HSCs) play a key role in the initiation, progression, and regression of liver fibrosis by secreting fibrogenic factors that encourage portal fibrocytes, fibroblasts, and bone marrow-derived myofibroblasts to produce collagen and thereby propagate fibrosis. These cells are subject to intricate cross-talk with adjacent cells, resulting in scarring and subsequent liver damage. Thus, an understanding of the molecular mechanisms of liver fibrosis and their relationships with HSCs is essential for the discovery of new therapeutic targets. This comprehensive review outlines the role of HSCs in liver fibrosis and details novel strategies to suppress HSC activity, thereby providing new insights into potential treatments for liver fibrosis.
Traditional Chinese medicine (TCM) is a precious treasure of the Chinese nation and has unique advantages in the prevention and treatment of diseases. The holistic view of TCM coincides with the new ...generation of medical research paradigm characterized by network and system. TCM gave birth to a new method featuring holistic and systematic “network target”, a core theory and method of network pharmacology. TCM is also an important research object of network pharmacology. TCM network pharmacology, which aims to understand the network-based biological basis of complex diseases, TCM syndromes and herb treatments, plays a critical role in the origin and development process of network pharmacology. This review introduces new progresses of TCM network pharmacology in recent years, including predicting herb targets, understanding biological foundation of diseases and syndromes, network regulation mechanisms of herbal formulae, and identifying disease and syndrome biomarkers based on biological network. These studies show a trend of combining computational, experimental and clinical approaches, which is a promising direction of TCM network pharmacology research in the future. Considering that TCM network pharmacology is still a young research field, it is necessary to further standardize the research process and evaluation indicators to promote its healthy development.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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