The association between KLF4 as a tumor suppressor and the prognosis of hepatocellular carcinoma after curative resection.

Krüppel-like factor 4 (KLF4), a zinc-finger transcription factor in klfs family, is known for its crucial role in regulating cell growth, proliferation, and differentiation. This research aimed to explore the prognostic significance of KLF4 in hepatocellular carcinoma's (HCC) patients after curative resection and the role of KLF4 in HCC progression. There were 185 HCC patients who had hepatectomy from July 2010 to July 2011 included in this study. KLF4 expression was detected by microarray immunohistochemical technique, western blot, and qRT-PCR. Then, the correlation between the prognosis of patients and KLF4 expression was evaluated based on patients' follow-up data. The research found KLF4 expression was significantly downregulated in HCC tissues compared to para-tumorous tissues. More importantly, the overall survival rate (OS) and recurrence-free survival rate (RFS) of HCC patients with low KLF4 expression were both significantly decreased compared to those with a high level of KLF4. Further function and mechanism analysis showed that KLF4 could inhibit the proliferation, migration, invasion and epithelial-mesenchymal transition of HCC cells. The study revealed that KLF4 was not only a tumor suppressor in HCC but also can be regarded as a valuable prognostic factor and potential biological target for diagnosis and treatment in HCC patients.

Finding the de-carbonization potentials in the transport sector: application of scenario analysis with a hybrid prediction model.

De-carbonization of the transport sector is an important pathway to climate-change mitigation and presents the potential for future lower emissions. To assess the potential quantitatively under different optimization measures, this paper presents a hybrid model combining an integrated machine learning model with the scenario analysis. We compare the training accuracy of the back-propagation neural networks (BPNN), Gaussian process regression (GPR), and support vector machine (SVM) fitting model with different training datasets. The results indicate that the performance of the SVM model is superior to other methods. And the particle swarm optimization (PSO) algorithm is then used to optimize hyper-parameters of the SVM model. Two scenarios including business as usual (BAU) and best case (BC) are set according to the current trends and target trends of driving factors identified by the extended stochastic impacts by regression on population, affluence, and technology (STIRPAT) model. Finally, to find the de-carbonization potentials in the transport sector, the PSO-SVM model is applied to predict transport emissions from 2015 to 2030 under two scenarios. Results show that transport emissions reduce by about 131.36 million tons during 2015-2020 and 372.86 million tons during 2021-2025 in the BC scenario. The findings can effectively track, test, and predict the achievement of policy goals and provide practical guidance for de-carbonization development.

Krebs-Type {M2(WO2)2[B-ß-SbW9O33]2}n- (M = SbIII, (WO3)) Tungstoantimonate Possessing Unique Pseudo-Seesaw Sb-O Structure.

Two new Krebs-type tungstoantimonates (H2en)8H6{[Sb2(WO2)2(B-ß-SbW9O33)2][(WO2)2(WO3)2(B-ß-SbW9O33)2]}·22H2O (1) and (H2en)7[(WO2)2(WO3)2(B-ß-SbW9O33)2]·12H2O (2) were synthesized and characterized. Notably, crystal 1 possesses a specific pseudo-seesaw SbO4 subunit in the central metal belt of [Sb2(WO2)2(B-ß-SbW9O33)2]12- species, which is rare in reported Krebs-type polyoxometalates. One of the structural features is that there are two kinds of Krebs-type polyanionic clusters in crystal 1 labeled as {(WO2)2(WO3)2(B-ß-SbW9O33)2} (part A) and {Sb2(WO2)2(B-ß-SbW9O33)2} (part B), respectively. The subunits A and B are alternately connected through Sb-O-W bonds into a chain-like structure of inorganic clusters. Moreover, the catalytic property of crystals 1 and 2 for electron-transfer reaction were investigated by transferring K3[Fe(CN)6] into K4[Fe(CN)6].

An alignment-free measure based on physicochemical properties of amino acids for protein sequence comparison.

Sequence comparison is an important topic in bioinformatics. With the exponential increase of biological sequences, the traditional protein sequence comparison methods - the alignment methods become limited, so the alignment-free methods are widely proposed in the past two decades. In this paper, we considered not only the six typical physicochemical properties of amino acids, but also their frequency and positional distribution. A 51-dimensional vector was obtained to describe the protein sequence. We got a pairwise distance matrix by computing the standardized Euclidean distance, and discriminant analysis and phylogenetic analysis can be made. The results on the Influenza A virus and ND5 datasets indicate that our method is accurate and efficient for classifying proteins and inferring the phylogeny of species.

Exploring the Emerging Evolution Trends of Urban Resilience Research by Scientometric Analysis.

: Numerous studies in urban resilience have been published in the past decade. However, only a few publications have tracked the evolution trends of urban resilience research, the findings of which can serve as a useful guide for scholars to foresee worth-effort research areas and make the best use of precious time and resources. In order to fill the research gap, this study performed a scientometric analysis on the evolution trends of urban resilience research using a versatile software package-CiteSpace. The scientomentric analysis focuses on distribution of lead authors and their institutions, high frequency categories and keywords, high influential journals, author contribution, and evolutionary trends based on co-author analysis, co-word analysis, co-citation analysis and cluster analysis of documents. This study discoveries that first, the U.S., England, Australia, Canada, China and Sweden are the countries that make the most significant contributions in the advancement of urban resilience research; second, the existing urban resilience research focuses primarily on environmental studies, geography and planning development; third, hot topics of the urban resilience research keep shifting from 1993 to 2016; fourth, the knowledge body of urban resilience research consists of five clusters: resilience exploratory analysis, disaster resilience, urban resilience, urban resilience practice, and social-ecological systems; last, the emerging trends in urban resilience research include defining urban resilience, adaptation model, case studies, analytical methods and urban social-ecological systems, resulting in cutting-edge research areas in urban resilience.

Facile synthesis of Fe3O4@MOF-100(Fe) magnetic microspheres for the adsorption of diclofenac sodium in aqueous solution.

In this research, the adsorptive removal of diclofenac sodium, one of the representative pharmaceuticals and personal care products, from aqueous solution using Fe3O4@MOF-100(Fe) magnetic microspheres was studied for the first time. The Fe3O4@MOF-100(Fe) microspheres exhibit strong magnetism and stability, which were observed as a core-shell structure. The maximum adsorption capacity of Fe3O4@MOF-100(Fe) for diclofenac sodium can reach 377.36 mg L-1, which was higher than most of the adsorbents reported. The adsorption kinetics follows the pseudo-second-order kinetic equation. And the adsorption equilibrium of DCF can be described with Langmuir isotherm. In the cycle experiment, Fe3O4@MOF-100(Fe) material performed high adsorption efficiency for low-concentration diclofenac sodium solution, and the removal rate can still reach 80% after 5 cycles of adsorption without desorption. The mechanisms including electrostatic interaction, H-bond interaction, and π-π interaction that coexisted in the adsorption processes would be of benefit to enhance the adsorption capacity. The Fe3O4@MOF-100(Fe) magnetic microspheres offer exciting opportunities for further application.

Multi-Index Evaluation for Flood Disaster from Sustainable Perspective: A Case Study of Xinjiang in China.

The floods have undermined the sustainable construction of cities because of their sudden and destruction. To reduce the losses caused by floods, it is necessary to make a reasonable evaluation for historical floods and provide scientific guidance for future precaution. Previous research mainly used subjective/objective weights or barely made static analysis without considering the uncertainty and ambiguity of floods. Therefore, this study proposed a variable fuzzy recognition model, based on combined weights, to evaluate floods, including the determination of index weights and the choice of evaluation model. To make the index weights reflect both subjective experience and objective data, the combined weights were proposed and calculated based on the principle of minimum identification information. Then, the relative membership degree matrix and evaluation results can be worked out by the variable fuzzy recognition model. Conclusions indicated that the combined weights were more convincing than simply subjective or objective weights. Moreover, the variable fuzzy recognition model, by changing model parameters, got stable evaluation results of the sample data. Therefore, the model can improve the credibility of evaluation and the conclusions can provide reasonable suggestions for management departments.

The Impacts of Transportation Infrastructure on Sustainable Development: Emerging Trends and Challenges.

Transportation infrastructure has an enormous impact on sustainable development. To identify multiple impacts of transportation infrastructure and show emerging trends and challenges, this paper presents a scientometric review based on 2543 published articles from 2000 to 2017 through co-author, co-occurring and co-citation analysis. In addition, the hierarchy of key concepts was analyzed to show emerging research objects, methods and levels according to the clustering information, which includes title, keyword and abstract. The results expressed by visual graphs compared high-impact authors, collaborative relationships among institutions in developed and developing countries. In addition, representative research issues related to the economy, society and environment were identified such as cost overrun, spatial economy, prioritizing structure, local development and land value. Additionally, two future directions, integrated research of various effects and structure analysis of transportation network, are recommended. The findings of this study provide researchers and practitioners with an in-depth understanding of transportation infrastructure's impacts on sustainable development by visual expression.

Melatonin inhibits colon cancer RKO cell migration by downregulating Rho­associated protein kinase expression via the p38/MAPK signaling pathway.

Melatonin is predominately produced and secreted by the pineal gland, and inhibits cell growth in various cancer cell lines such as colorectal cancer. However, the precise mechanisms involved have not been fully elucidated. In the present study, the potential molecular mechanism underlying the efficacy of melatonin on migration in RKO colon cancer cells was investigated. The effects of melatonin and H­1152, a selective inhibitor of Rho­associated protein kinase (ROCK), on the migration of RKO cells were analyzed by an in vitro wound healing assay. The localization of zonula occludens­1 (ZO­1) and occludin were observed by immunofluorescence. Reverse transcription­quantitative polymerase chain reaction (qPCR) was performed to analyze the relative mRNA levels of ROCK, ZO­1 and occludin. In addition, western blot analysis was implemented to examine the expression of ROCK, phospho (p)­myosin phosphatase targeting subunit 1 (MYPT1), p­myosin light chains (MLC) and p­p38. The results revealed that the expression levels of ROCK2, p­MYPT1 and p­MLC in RKO cells were decreased, and the membrane protein expression of ZO­1 and occludin increased when the cells were treated with melatonin. qPCR demonstrated that melatonin downregulated ROCK2 gene expression, and upregulated the expression of the ZO­1 and occludin genes. The levels of ZO­1 and occludin localized in the tight junctions were markedly increased in the immunofluorescence assay. In addition, the phosphorylation levels of p38 were reduced when the cells were treated with melatonin, and treatment with H­1152 downregulated p38 phosphorylation. The results indicated that melatonin may inhibit the migration of RKO colon cancer cells by downregulating ROCK expression via the p38/mitogen­activated protein kinase signaling pathway.