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Spontaneous bursts in neuronal networks with propagation involving a large number of synchronously firing neurons are considered to be a crucial feature of these networks both in vivo and in vitro. Recently, learning has been shown to improve the association and synchronization of spontaneous events in neuronal networks by promoting the firing of spontaneous bursts. However, little is known about the relationship between the learning phase and spontaneous bursts. By combining highresolution measurement with a 4,096-channel complementary metaloxide-semiconductor (CMOS) microelectrode array (MEA) and graph theory, we studied how the learning phase influenced the initiation of spontaneous bursts in cultured networks of rat cortical neurons in vitro. We found that a small number of selected populations carried most of the stimulus information and contributed to learning. Moreover, several new burst propagation patterns appeared in spontaneous firing after learning. Importantly, these "learning populations" had more hubs in the functional network that governed the initiation of spontaneous burst activity. These results suggest that changes in the functional structure of learning populations may be the key mechanism underlying increased bursts after learning. Our findings could increase understanding of the important role that synaptic plasticity plays in the regulation of spontaneous activity. [ABSTRACT FROM AUTHOR]

Photovoltaic performances of Cu-chalcogenides solar cells are strongly correlated with the absorber fundamental properties such as optimal bandgap, desired band alignment with window material, and high photon absorption ability. According to these criteria, we carry out a successive screening for 90 Cu-chalcogenides using efficient theoretical approaches. Besides the well-recognized CuInSe2 and Cu2ZnSnSe4 materials, several novel candidates are identified to have optimal bandgaps of around 1.0-1.5 eV, spike-like band alignments with CdS window layer, sharp photon absorption edges, and high absorption coefficients. These new systems have great potential to be superior absorbers for photovolatic applications if their carrrier transport and defect properties are properly optimized. [ABSTRACT FROM AUTHOR]

The traditional photon absorbers Cu2-xX (X=S, Se, and Te) have regained significant research attention in the search of earth-abundant photovoltaic materials. These moderate- and narrow-gap materials have also been shown to exhibit excellent thermoelectric properties recently. However, semimetallic band structures with inverted band orderings are predicted for antifluorite structure Cu2X using density functional theory with the local density approximation or the generalized gradient approximation. We find that semiconducting band structures and normal band orderings can be obtained using the modified Becke-Johnson potential plus an on-site Coulomb U (the mBJ+U approach), which is consistent with our earlier finding for diamond-like Cu-based multinary semiconductors [Y. Zhang, J. Zhang,W. Gao, T. A. Abtew, Y.Wang, P. Zhang, andW. Zhang, J. Chem. Phys. 139, 184706 (2013)]. The trend of the chemical bonding of Cu2X is analyzed, which shows that the positions of the valence band maximum and conduction band minimum are strongly affected by the inter-site pd and intra-site sp hybridizations, respectively. The calculated gaps of Cu2S and Cu2Se still seem to be underestimated compared with experimental results. We also discuss the effects of different structural phases and Cu disordering and deficiency on the bandgaps of these materials. [ABSTRACT FROM AUTHOR]

Fossil resources are valuable wealth given to human beings by nature. Many mysteries related to them have been revealed such as the origin time and distribution area, but their vertical distribution depth has not been confirmed for people’s different understanding of their origin and the big depth variations from basin to basin. Geological and geochemical data of 13,634 source rock samples from 1,286 exploration wells in six representative petroliferous basins are examined to study their Active Source Rock Depth Limits (ASDL), defined in this study as the maximum burial depth of active source rocks beyond which the source rocks no longer generate or expel hydrocarbons and become inactive, to identify the maximum depth for fossil fuel resources distribution. Theoretically, the maximum depth for the ASDLs of fossil fuel resources ranges from 3,000 m to 16,000 m, while their thermal maturities (Ro) are almost the same with Ro≈3.5±0.5 %. A higher heat flow and more oil-prone kerogen are associated with a shallower ASDL. Active source rocks and the discovered 21.6 billion tons of reserves in six representative basins in China and 52,926 oil and gas reservoirs in the 1,186 basins over the world are found to be distributed above the ASDL, illustrating the universality of such kind of depth limit. The data are deposited in the repository of the PANGAEA database: https://doi.org/10.1594/PANGAEA.900865 (Pang et al., 2019). [ABSTRACT FROM AUTHOR]

Energy storage technologies, such as fuel cells, ammonia production and lithium-air batteries, are important strategies for addressing the global challenge of energy crisis and environmental pollution. Taking overpotential as a direct criterion, we illustrate in theory and experiment that the adsorption energies of charged species such as Li+ +e- and H+ +e- are a central parameter to describe catalytic activities related to electricity-in/electricity-out efficiencies. The essence of catalytic activity is revealed to relate with electronic coupling between catalysts and charged species. Based on adsorption energy, some activity descriptors such as d-band center, eg-electron number and charge-transfer capacity are further defined by electronic properties of catalysts that directly affect interaction between catalysts and charged species. The present review is helpful for understanding the catalytic mechanisms of these electrocatalytic reactions and developing accurate catalytic descriptors, which can be employed to screen high-activity catalysts in future high-throughput calculations and experiments. [ABSTRACT FROM AUTHOR]

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In text classification field, many classifiers cannot deal with the features with large dimensions, thus it is very important to filter the redundant information from the original feature space efficiently and achieve the features with best qualities. On this basis, a new two-step based feature selection method is proposed in this paper. Firstly, some definitions (word semantic correlation, set semantic correlation, semantic correlative and semantic correlative set) are introduced, and the algorithm of generating the semantic correlative sets is given. Secondly, the process of the two-step based feature selection method is described: in the first step, a feature subset is obtained by using an optimal feature selection method, and a set of semantic correlative sets is generated by using the selected feature subset; in the second step, the redundant information of the selected features is filtered by using the generated semantic correlative sets. Finally, in order to avoid local optimum when searching the best threshold, the conception of memory recall position is introduced and an improved memory recall mechanism based fruit fly optimization algorithm is proposed. In the experiments, two typical classifiers: support vector machine and naïve bayes are used on four datasets: Reuters50, SMSSPAS, WebKB and 20-Newsgroups, and the 10-cross validation is carried out when the measurements of F1 and receiver operating curve are used. Experimental results show that the proposed method achieves higher accuracy than several representative traditional feature selection methods and runs faster than typical mutual information based feature selection methods, illustrating its effectiveness on achieving the best features in text classification filed. [ABSTRACT FROM AUTHOR]

Natural killer (NK) cells are an essential component of innate immunity against cancer development. Many studies have been conducted to evaluate immune-modulating effects using dietary compounds. Our laboratory has been investigating the chemopreventive potential of black raspberries (BRBs) and previously demonstrated their beneficial modulation of genetic and epigenetic biomarkers in patients with colorectal cancer (CRC). The current study investigated their potential on modulating NK cells. To avoid the excessive inflammation caused by the dextran sulfate sodium (DSS) treatment that leads to colitis, we treated the mice with overnight DSS so that it would slightly irritate the colon but still promote colon carcinogenesis with 100% incidence in both the ApcMin/+ mice and azoxymethane (AOM)-treated mice. A significant decrease of tissue-infiltrating NK cells along the progression of microadenoma-to-adenoma and adenoma-to-adenocarcinoma was observed in the ApcMin/+/DSS and AOM/DSS mice, respectively. Depletion of NK cells significantly promoted the development of CRC, suggesting a critical role of NK cells in combating CRC progression. BRBs significantly suppressed the CRC progression and increased the number of tissue-infiltrating NK cells in both mouse models. Moreover, we further determined BRBs' effects on NK cells in the human biopsy specimens collected from our previously completed clinical trial, in which CRC patients consumed BRBs for an average of 4 weeks during a presurgical window. We observed an increased number and an enhanced cytotoxicity of NK cells by BRB intervention. The current study provides evidence that BRBs have the potential to enhance the tumor immunesurveillance of NK cells that can be beneficial in the setting of CRC prevention and treatment. [ABSTRACT FROM AUTHOR]

Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles and large-scale power grids, stimulate the development of highperformance battery materials with high energy density, high power, good safety and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future highthroughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials. [ABSTRACT FROM AUTHOR]

Feature selection, which can reduce the dimension of feature space without sacrificing the performance of the classifier, is an effective technique in text categorization. As many classifiers cannot deal with the features with large dimensions, the noisy, irrelevant and redundant information must be filtered from the original feature space. On this basis, a random walk algorithm based feature selection method (called RWFS) is proposed in this paper. Firstly, an optimal feature selection method (called OPFS) is used to select some features from the training set. Secondly, the redundant features are filtered by combining the random walk algorithm and a pre-determined threshold. Moreover, in order to search the optimal threshold, an improved artificial bee colony method (called IMABC) is proposed for parameter optimization. In the experiments, support vector machine (SVM) and k-Nearest Neighbor (KNN) classifiers are used on four corpuses. The experimental results show that, the proposed method is significantly superior to six typical feature selections, and can greatly reduce the dimension of vector space while guaranteeing the classification accuracy as measured by F1 measurement. [ABSTRACT FROM AUTHOR]

Numerous studies have demonstrated that interferon-γ (IFN-γ) is an important inflammatory cytokine, which may activate the immunomodulatory abilities of mesenchymal stem cells (MSCs), and may influence certain other functions of these cells. MicroRNAs are small non-coding RNAs that regulate the majority of the biological functions of cells and are important in a variety of biological processes. However, few studies have been performed to investigate whether IFN-γ affects the microRNA profile of MSCs. The aim of the present study was to analyze the microRNA profile of MSCs derived from the umbilical cord (UC-MSCs) cultured in the presence or absence of IFN-γ (IFN-UC-MSCs). An array that detects 754 microRNAs was used to determine the expression profiles. Statistical analysis of the array data revealed that 8 microRNAs were significantly differentially expressed in UC-MSCs and IFN-UC-MSCs. Reverse transcription-quantitative polymerase chain reaction validated the differential expression of the 8 identified microRNAs. The target genes of the 8 microRNAs were predicted through two online databases, TargetScan and miRanda, and the predicted results were screened by bioinformatics analysis. The majority of the target genes were involved in the regulation of transcription, signal transduction, proliferation, differentiation and migration. These results may provide insight into the mechanism underlying the regulation of the biological functions of MSCs by IFN-γ, in particular the immunomodulatory activity. [ABSTRACT FROM AUTHOR]

In order to improve the classification speed without sacrificing the email classification accuracy seriously, a novel online spam classification method is proposed. Firstly, the conceptions of term frequency based interest sets are introduced, and emails are classified by combining term frequency based interest sets and Naïve Bayes classifier. Secondly, based on the active learning theory, a novel boundary density based email classification certainty evaluating method is proposed to select and recommend emails to users for labeling by combining the user interests. Finally, the emails which are labeled and classified with the greatest possibilities are used for retraining based on the incremental learning theory. In the experiments, Support Vector Machine (SVM), Naïve Bayesian (NB) and K-Nearest Neighbors (KNN) classifiers are used on two corpuses:Trec2007 and Enron-spam. Comparing with six typical active learning based incremental learning methods, the proposed method greatly reduces the consuming time of email classification while guaranteeing the accuracy. Moreover, the proposed method brings very small sample labeling burden to the users, proving its high value on online application. [ABSTRACT FROM AUTHOR]

Introduction Mesenchymal stem cells (MSCs) are widely investigated in clinical researches to treat various diseases. Classic culture medium for MSCs, even for clinical use, contains fetal bovine serum. The serum-containing medium (SCM) seems a major obstacle for MSCsrelated therapies due to the risk of contamination of infectious pathogens. Some studies showed that MSCs could be expanded in serum free medium (SFM); however, whether SFM would change the biological characteristics and safety issues of MSCs has not been well answered. Methods Human umbilical cord mesenchymal stem cells (hUC-MSCs) were cultured in a chemical defined serum free medium. Growth, multipotency, surface antigen expression, telomerase, immunosuppressive ability, gene expression profile and genomic stability of hUC-MSCs cultured in SFM and SCM were analyzed and compared side by side. Results hUC-MSCs propagated more slowly and senesce ultimately in SFM. SFM-expanded hUCMSCs were different from SCM-expanded hUC-MSCs in growth rate, telomerase, gene expression profile. However, SFM-expanded hUC-MSCs maintained multipotency and the profile of surface antigen which were used to define human MSCs. Both SFM- and SCMexpanded hUC-MSCs gained copy number variation (CNV) in long-term in vitro culture. Conclusion hUC-MCSs could be expanded in SFM safely to obtain enough cells for clinical application, meeting the basic criteria for human mesenchymal stem cells. hUC-MSCs cultured in SFM were distinct from hUC-MSCs cultured in SCM, yet they remained therapeutic potentials for future regenerative medicine. [ABSTRACT FROM AUTHOR]

Background To study the expression of D2R, MGMT and VEGF for clinical significance in pituitary adenomas, and to predict the potential curative medical therapy of dopamine agonists, temozolomide and bevacizumab on pituitary adenomas. Methods Immunohistochemistry and western blot were performed to detect the expression of expression of D2R, MGMT and VEGF in pituitary adenoma tissue samples. The ratio of high expression of D2R, MGMT or VEGF in different subtypes of PA was compared by the use of chi-squared tests. The relationships between D2R, MGMT and VEGF expression were assessed by the Spearman rank correlation test. The association between their expression and clinical parameters was analyzed using a chi-squared test, or Fisher's exact probability test when appropriate. Results The data showed that in 197 different histological subtypes of pituitary adenomas (PAs), 64.9 % of them were D2R high expression, 86.3 % were MGMT low expression and 58.9 % were VEGF high expression. D2R high expression existed more frequently in PRL- and GH-secreting PAs. MGMT low expression existed in all PA subtypes. VEGF high expression existed more frequently in PRL, ACTH, FSH secreting and non-functioning PAs. The data of western blot also support the results. Spearman's rank correlation analysis showed that expression of MGMT was positively associated with D2R (r = 0.154, P = 0.031) and VEGF (r = 0.161, P = 0.024) in PAs, but no correlation was showed between D2R and VEGF expression (r = -0.025, P = 0.725 > 0.05). The association between their expression and clinical parameters was analyzed using a chi-squared test, or Fisher's exact probability test when appropriate, but the result showed no significant association. Conclusions PRL-and GH-secreting PAs exist high expression of D2R, responding to dopamine agonists; Most PAs exist low expression of MGMT and high expression of VEGF, TMZ or bevacizumab treatment could be applied under the premise of indications. [ABSTRACT FROM AUTHOR]

Mesenchymal stem cells (MSCs) hold great promise as therapeutic agents in regenerative medicine and autoimmune diseases, based on their differentiation abilities and immunosuppressive properties. However, the therapeutic applications raise a series of questions about the safety of culture-expanded MSCs for human use. This paper summarized recent findings about safety issues of MSCs, in particular their genetic stability in long-term in vitro expansion, their cryopreservation, banking, and the role of serum in the preparation of MSCs. [ABSTRACT FROM AUTHOR]

The essential oil extracted from the seeds of dill (Anethum graveolens L.) was demonstrated in this study as a potential source of an eco-friendly antifungal agent. To elucidate the mechanism of the antifungal action further, the effect of the essential oil on the plasma membrane and mitochondria of Aspergillus flavus was investigated. The lesion in the plasma membrane was detected through flow cytometry and further verified through the inhibition of ergosterol synthesis. The essential oil caused morphological changes in the cells of A. flavus and a reduction in the ergosterol quantity. Moreover, mitochondrial membrane potential (MMP), acidification of external medium, and mitochondrial ATPase and dehydrogenase activities were detected. The reactive oxygen species (ROS) accumulation was also examined through fluorometric assay. Exposure to dill oil resulted in an elevation of MMP, and in the suppression of the glucose-induced decrease in external pH at 4 μl/ml. Decreased ATPase and dehydrogenase activities in A. flavus cells were also observed in a dose-dependent manner. The above dysfunctions of the mitochondria caused ROS accumulation in A. flavus. A reduction in cell viability was prevented through the addition of L-cysteine, which indicates that ROS is an important mediator of the antifungal action of dill oil. In summary, the antifungal activity of dill oil results from its ability to disrupt the permeability barrier of the plasma membrane and from the mitochondrial dysfunction-induced ROS accumulation in A. flavus. [ABSTRACT FROM AUTHOR]

The inflorescence of cultivated Coptis chinensis has been valued for tea production for many years in China. The antioxidant activities of C. chinensis inflorescence extracts prepared by various solvents were investigated by using several established in vitro systems: 2,2′-azinobis(3-ethylbenzthiazoline-6-sulphonic acid (ABTS), α,α-diphenyl-β-picrylhydrazyl (DPPH) and superoxide radical scavenging assays, reducing power assay, and ferrothiocyanate (FTC) and thiobarbituric acid (TBA) assays. The results showed that the 70% ethanol extract (EE) had the strongest antioxidant activity in vitro among the various extracts. Based on the in vitro results, EE was used to evaluate the antioxidant activity of C. chinensis inflorescence in vivo. The liver and kidney of intoxicated animals showed a significant decrease in superoxide dismutase (SOD), catalase (CAT) and glutathione (GSH) levels, while the malondialdehyde (MDA) level showed a significant increase. These changes were significantly reversed after treatment with EE and the standard vitamin E. Thus, the C. chinensis inflorescence may be a valuable natural source that can be applicable to food industries. [ABSTRACT FROM AUTHOR]

An innovative model to measure the influence among scientific journals is developed in this study. This model is based on the path analysis of a journal citation network, and its output is a journal influence matrix that describes the directed influence among all journals. Based on this model, an index of journals' overall influence, the quality-structure index (QSI), is derived. Journal ranking based on QSI has the advantage of accounting for both intrinsic journal quality and the structural position of a journal in a citation network. The QSI also integrates the characteristics of two prevailing streams of journal-assessment measures: those based on bibliometric statistics to approximate intrinsic journal quality, such as the Journal Impact Factor, and those using a journal's structural position based on the PageRank-type of algorithm, such as the Eigenfactor score. Empirical results support our finding that the new index is significantly closer to scholars' subjective perception of journal influence than are the two aforementioned measures. In addition, the journal influence matrix offers a new way to measure two-way influences between any two academic journals, hence establishing a theoretical basis for future scientometrics studies to investigate the knowledge flow within and across research disciplines. [ABSTRACT FROM AUTHOR]

A conference paper on the study on the relationship between perceived usefulness (PU) and relative advantage (RA) in Information and Communication Technology (ICT) adoption is presented. It discusses the significance of ICT in enhancing job performance and the examination of PU and RA using measurement model. It states that RA is intended to study ICT adoption and allows to integrate other technologies such as electronic-mail (e-mail) and mobile-mail (m-mail), while PU serves as proxy of RA.

Abstract   Magnolia officinalis subsp. biloba, a traditional Chinese medicinal plant, experienced severe declines in the number of populations and the number of individuals in the late 20th century due to the widespread harvest of the subspecies. A large-scale cultivation program was initiated and cultivated populations rapidly recovered the loss in individual plant numbers, but wild populations remained small as a consequence of cutting. In this study, the levels of genetic variation and genetic structure of seven wild populations and five domestic populations of M. officinalis subsp. biloba were estimated employing an AFLP methodology. The plant exhibited a relatively high level of intra-population genetic diversity (h = 0.208 and H j = 0.268). The cultivated populations maintained approximately 95% of the variation exhibited in wild populations, indicating a slight genetic bottleneck in the cultivated populations. The analysis of genetic differentiation revealed that most of the AFLP diversity resided within populations both for the wild group (78.22%) and the cultivated group (85.92%). Genetic differentiation among populations in the wild group was significant (F ST = 0.1092, P  [ABSTRACT FROM AUTHOR]

The objective of this research is to optimize the link structure of webpages for an e-supermarket. Customers are looking for greater convenience in shopping when they visit the website of an e-supermarket, while e-supermarket managers prefer webpages that contain information about profitable products to be visited more frequently. In order to balance the interests of both parties and to aid the webmaster in updating the website regularly, we present a mathematical model with the objective of minimizing the overall weighted distances between webpages. An updating algorithm is used to determine the distance between pages. It is proved to be more efficient under certain special circumstances. We propose the statistical Hopfield neural-network and the strategic oscillation-based tabu-search algorithms as solving methods. The former is appropriate for optimizing small-scale problems. The latter is good at solving large-scale problems approximately. The preliminary validity of the model and the performance of the algorithms is demonstrated by experiments on a small website and several large websites, using randomly generated data. The destination pages that customers and website managers preferred are proved to be more accessible after optimization. [ABSTRACT FROM AUTHOR]