Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
10,662
result(s) for
"Huang, Rui"
Sort by:
DNA damage response signaling pathways and targets for radiotherapy sensitization in cancer
Radiotherapy is one of the most common countermeasures for treating a wide range of tumors. However, the radioresistance of cancer cells is still a major limitation for radiotherapy applications. Efforts are continuously ongoing to explore sensitizing targets and develop radiosensitizers for improving the outcomes of radiotherapy. DNA double-strand breaks are the most lethal lesions induced by ionizing radiation and can trigger a series of cellular DNA damage responses (DDRs), including those helping cells recover from radiation injuries, such as the activation of DNA damage sensing and early transduction pathways, cell cycle arrest, and DNA repair. Obviously, these protective DDRs confer tumor radioresistance. Targeting DDR signaling pathways has become an attractive strategy for overcoming tumor radioresistance, and some important advances and breakthroughs have already been achieved in recent years. On the basis of comprehensively reviewing the DDR signal pathways, we provide an update on the novel and promising druggable targets emerging from DDR pathways that can be exploited for radiosensitization. We further discuss recent advances identified from preclinical studies, current clinical trials, and clinical application of chemical inhibitors targeting key DDR proteins, including DNA-PKcs (DNA-dependent protein kinase, catalytic subunit), ATM/ATR (ataxia–telangiectasia mutated and Rad3-related), the MRN (MRE11-RAD50-NBS1) complex, the PARP (poly[ADP-ribose] polymerase) family, MDC1, Wee1, LIG4 (ligase IV), CDK1, BRCA1 (BRCA1 C terminal), CHK1, and HIF-1 (hypoxia-inducible factor-1). Challenges for ionizing radiation-induced signal transduction and targeted therapy are also discussed based on recent achievements in the biological field of radiotherapy.
Journal Article
Confession and greenwashing: the impact of water information disclosure on firm value
Water pollution has become a serious problem in recent years, and firms are one of the main culprits for this environmental issue. Encouraging companies to improve water management behavior is necessary to protect water resources. Based on panel data of Chinese A-share listed companies in water-sensitive industries, this study used text analysis techniques to study the impact of corporate water information disclosure on pollutant emissions, strategy on firm value, and the U-shaped moderating role of local governments’ environmental regulation. The results show that (1) an increase in the amount of emission information texts to confess the water status can help enhance firm value. (2) The increase in the amount of strategic information texts, both the tone of emission, and strategic information texts have negative impacts on firm value, which help enterprises greenwash. Further analyses find a U-shaped moderating effect of governments’ environmental regulation on the relationships between emission information disclosure, strategic information disclosure and firm value, and varies under the different ISO14001 certification situations and life cycles. This research explains the effectiveness of corporate water information disclosure and the influence of governments’ environmental regulation, which plays a vital role in promoting firms to improve their environmental behaviors, reduce water pollution, and further achieve green development.
Journal Article
Soluble E-cadherin promotes tumor angiogenesis and localizes to exosome surface
The limitations of current anti-angiogenic therapies necessitate other targets with complimentary mechanisms. Here, we show for the first time that soluble E-cadherin (sE-cad) (an 80-kDa soluble form), which is highly expressed in the malignant ascites of ovarian cancer patients, is a potent inducer of angiogenesis. In addition to ectodomain shedding, we provide further evidence that sE-cad is abundantly released in the form of exosomes. Mechanistically, sE-cad-positive exosomes heterodimerize with VE-cadherin on endothelial cells and transduce a novel sequential activation of β-catenin and NFκB signaling. In vivo and clinical data prove the relevance of sE-cad-positive exosomes for malignant ascites formation and widespread peritoneal dissemination. These data advance our understanding of the molecular regulation of angiogenesis in ovarian cancer and support the therapeutic potential of targeting sE-cad. The exosomal release of sE-cad, which represents a common route for externalization in ovarian cancer, could potentially be biomarkers for diagnosis and prognosis.
A soluble form E-cadherin is highly expressed in ovarian cancer. Here, the authors show that soluble E-cadherin is released by ovarian cancer cells packaged in exosomes and promotes tumor angiogenesis through β-catenin and NFkB signaling activation.
Journal Article
Intermediate-sized molecular sieving of styrene from larger and smaller analogues
Molecular sieving can lead to ultrahigh selectivity and low regeneration energy because it completely excludes all larger molecules via a size restriction mechanism. However, it allows adsorption of all molecules smaller than the pore aperture and so separations of complicated mixtures can be hindered. Here, we report an intermediate-sized molecular sieving (iSMS) effect in a metal–organic framework (MAF-41) designed with restricted flexibility, which also exhibits superhydrophobicity and ultrahigh thermal/chemical stabilities. Single-component isotherms and computational simulations show adsorption of styrene but complete exclusion of the larger analogue ethylbenzene (because it exceeds the maximal aperture size) and smaller toluene/benzene molecules that have insufficient adsorption energy to open the cavity. Mixture adsorption experiments show a high styrene selectivity of 1,250 for an ethylbenzene/styrene mixture and 3,300 for an ethylbenzene/styrene/toluene/benzene mixture (orders of magnitude higher than previous reports). This produces styrene with a purity of 99.9%+ in a single adsorption–desorption cycle. Controlling/restricting flexibility is the key for iSMS and can be a promising strategy for discovering other exceptional properties.
Journal Article
Comparison and Analysis of Sustainable Development between China and America
In recent years, sustainable development has been widely discussed. This article primarily explores the reasons behind the necessity for sustainable development. The inevitable environmental degradation resulting from rapid economic development is a crucial factor. Economic development is closely tied to the demand for energy, and sustainable development reduces environmental pollution and alleviates energy shortages. The environmental benefits brought about by sustainable development, in turn, positively impact economic growth. Therefore, sustainable development is indispensable. The strategic approaches to sustainable development in China and the United States differ due to their respective national conditions. This article also delves into the disparities in the sustainable development strategies between China and the U.S. China’s sustainable development leans towards technological advancement, energy conservation, and environmental protection, while the U.S. prioritizes addressing social inequality. Post-COVID-19 pandemic, the sustainable development strategies of China and the U.S. have become increasingly apparent. The article explores what sustainable development strategies China and the U.S. have chosen post-pandemic to swiftly recover their economies. It also analyzes the characteristics of social inequality in China and the U.S., noting that China’s economic inequality is regional, whereas the economic inequality in the U.S. stems from differences in educational attainment. The article further proposes solutions for these economic inequalities. In sustainable development strategies, despite differing national conditions, addressing economic inequality is a crucial component. China requires balancing the allocation of resources across its regions, while the U.S. needs to alleviate wealth disparities resulting from educational differences and address the issue of higher education accessibility.
Journal Article
Link prediction of heterogeneous complex networks based on an improved embedding learning algorithm
Link prediction in heterogeneous networks is an active research topic in the field of complex network science. Recognizing the limitations of existing methods, which often overlook the varying contributions of different local structures within these networks, this study introduces a novel algorithm named SW-Metapath2vec. This algorithm enhances the embedding learning process by assigning weights to meta-path traces generated through random walks and translates the potential connections between nodes into the cosine similarity of embedded vectors. The study was conducted using multiple real-world and synthetic datasets to validate the proposed algorithm’s performance. The results indicate that SW-Metapath2vec significantly outperforms benchmark algorithms. Notably, the algorithm maintains high predictive performance even when a substantial proportion of network nodes are removed, demonstrating its resilience and potential for practical application in analyzing large-scale heterogeneous networks. These findings contribute to the advancement of link prediction techniques and offer valuable insights and tools for related research areas.
Journal Article
Spatial-temporal distribution of COVID-19 in China and its prediction: A data-driven modeling analysis
Currently, the outbreak of COVID-19 is rapidly spreading especially in Wuhan city, and threatens 14 million people in central China. In the present study we applied the Moran index, a strong statistical tool, to the spatial panel to show that COVID-19 infection is spatially dependent and mainly spread from Hubei Province in Central China to neighbouring areas. Logistic model was employed according to the trend of available data, which shows the difference between Hubei Province and outside of it. We also calculated the reproduction number R0 for the range of [2.23, 2.51] via SEIR model. The measures to reduce or prevent the virus spread should be implemented, and we expect our data-driven modeling analysis providing some insights to identify and prepare for the future virus control.
Journal Article
Exploring the roles of self-determined motivation and perceived organizational support in organizational change
PurposeThe primary purpose of this study is not only to examine the connections between self-determined motivation, attitudes toward change and participation in change, but also to explore the moderating impact of perceived organizational support on organizational change, and the mediating role of attitudes toward change in the link between perceived competence and participation in change.Design/methodology/approachThe data were collected from one semiconductor manufacturing company (study 1) and one logistics service company (study 2). Employees who experienced organizational change before were invited to finish the survey. The partial least squares-structural equation modelling (PLS-SEM) technique and SPSS PROCESS (model 14) were utilized to analyze the data.FindingsThe study findings indicated that the perceived autonomy and relatedness were positively connected with perceived competence, which in turn would lead to better attitude toward change. Additionally, it was found that the perceived competence and attitude toward change would positively predict participation in change. More importantly, perceived organizational support would reinforce the positive relationship between attitude toward change and participation in change.Originality/valueAlthough there are many organizational change reports, relatively little attention has been paid not only to the mediating role of attitudes toward change in the implication of organizational change but also to the moderating impact of perceived organizational support on the final success of organizational change.
Journal Article
Geometric and arithmetic characterization of D-module flatness with applications to tensor products
This paper establishes a comprehensive framework for studying flatness properties and tensor products of D -modules across algebraic, geometric, and arithmetic contexts. We develop new criteria characterizing flatness through Lagrangian geometry, homological algebra, and irregular Hodge theory, revealing deep connections between these perspectives. The work introduces a geometric obstruction theory for globalizing pointwise flat modules and proves fundamental results about the monoidal structure of the derived tensor product category. Applications include compatibility theorems for Beilinson-Bernstein localization and arithmetic characterizations of flatness in characteristic p . The methods combine microlocal analysis, irregular Riemann-Hilbert correspondence, and p -adic techniques to yield new insights into the interplay between local and global properties of differential systems.
Journal Article