Bivariate Flow Research Articles

Could free-floating bikeshare weed out station-based bikeshare? Analyzing the relationship between two bikeshare systems from bivariate flow clustering

Against the backdrop of the strong market expansion of free-floating bikeshare systems (FFBS), the future of government-funded station-based bikeshare system (SBBS) is a matter of controversy. Merely relying on point density analysis proves to be inadequate in reflecting the flow characteristic, this paper employs a flow clustering analysis to investigate the relationship between SBBS and FFBS. To recognize both bikeshare flow clusters with inhomogeneous density and shape in less time, we propose a two-step network-constrained bivariate flow clustering method that organically combines multiplex-network community detection and bivariate flow clustering method. The performance and applicability of the method in flow clustering detection is exemplified by the SBBS and FFBS systems in Nanjing. The results indicate that though FFBS outnumbers SBBS in terms of bikes, there are still specific flow clusters where SBBS performs better. Spatiotemporal patterns of flow clusters reveal that about one-third of flow clusters dominated by FFBS move from the metro station to the business district during the morning peak, while more SBBS-dominated flow clusters (55.4%) move from the residence to the metro station. Conversely, during the evening peak, flow clusters are observed in the opposite direction. Nevertheless, if the difference in bike numbers is significant, SBBS will be at a disadvantage. It is necessary for SBBS to prioritize resource allocation towards target groups and advantageous areas to prevent decentralized development. Our findings contribute to a more profound comprehension of the interplay between SBBS and FFBS, thereby offering more informed recommendations for strategically aligning the functions of bikeshare systems.

CRITICAL ANALYSIS OF POWDER FLOW BEHAVIOUR OF DIRECTLY COMPRESSIBLE COPROCESSED EXCIPIENTS

The aim of this pre-formulation study was to adopt simple linear regression modelling and correlation statistics to understand the associations between pharmacopoeial powder test methods using datasets generated from five commercial brands of directly compressible excipients with a specific focus to inferential implications in formulation design. Powder characterization was conducted using protocols defined in Chapter <1174> and <616> of the United States Pharmacopoeia (USP41-NF36). The study adopted a linear regression modelling analytics and correlation statistics using the fitting algorithm of OriginPro® (OriginPro, Version 2021b, OriginLab Corporation, Northampton, MA, USA). In the results, the modulus of Pearson’s product moment correlation coefficient was used to measure the strength of the linear association between test variables and a correlation matrix generated. Strong positive correlation modulus of Hausner’s Ratio (HR) with Carr’s index (r=+0.999) and static angle of repose (r=+0.932) were evident. Bulk density strongly correlates with tap density in the positive direction (r=+0.911). Tap density also shows a slight negative correlation with HR (r=-0.230), Carr’s index (r=-0.228), and static angle of repose (r==-0.421), while Carr’s index strongly correlated with static angle of repose (r=+0.933). In conclusion, modelling bivariate powder flow datasets has provided a powerful but simplistic statistical relationship for characterizing the modulus of association between HR, Carr’s index, and static angle of repose of the model excipients useful in preformulation design of pharmaceutical formulations.

Chromosome Analysis and Sorting Using Conventional Flow Cytometers.

The fluorescent dyes Hoechst (HO) and Chromomycin A3 (CA3) are commonly used for bivariate flow karyotyping to distinguish individual chromosomes from one another based on differences in base composition and DNA content. However, analysis of chromosomes using this fluorescent dye combination requires a flow cytometer equipped with lasers of specific wavelengths and higher power than is typical of conventional flow cytometers. This unit presents a chromosome staining technique with a dye combination of DAPI and propidium iodide (PI). Chromosomes stained using this dye combination can be analyzed on conventional flow cytometers equipped with a typical configuration of lasers and optics. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Cell culture and metaphase harvest of suspension cell line Alternate Protocol 1: Cell culture and metaphase harvest of adherent cell line Basic Protocol 2: Preparation of chromosome suspension using polyamine isolation buffer Basic Protocol 3: Staining chromosomes with DAPI and propidium iodide Alternate Protocol 2: Staining chromosomes with Hoechst and Chromomycin A3 Basic Protocol 4: Bivariate flow karyotyping on a cell analyzer Basic Protocol 5: Bivariate flow karyotyping on a cell sorter Basic Protocol 6: Purification of flow-sorted chromosomes.

Starch granular size and multi-scale structure determine population patterns in bivariate flow cytometry sorting

Bivariate flow cytometry (FC) sorting with forward scatter (FSC) and side scatter (SSC) is a recently established novel technique to separate starch granules. However, the forming mechanism of starch FC-dependent population patterns (i.e. the number of subgroups (NS) and FSC/SSC-dependent distribution patterns) remain partly elusive. For this, the correlation of granular size and multi-scale structure of native starches and FC-dependent population patterns was investigated through employing a wide range of native starches originating from different species involving cereal-, pulse-, and tuber crops. Results showed NS was pertinent with particle size, amylose content (AC), amylopectin chains length distribution, lamellar structure, short-range ordered structure. The distinct NS was determined by impacts of native starch FSC / SSC-dependent distribution patterns. Specifically, starch granular size significantly correlated with both FSC and SSC-dependent distribution patterns. The proportion of chains with DP 6–12 was the intra-molecular decisive factor to influence short-range ordered structure, finally leading to FSC-dependent distribution patterns. By contrast, AC was another intra-molecular index to determine SSC-dependent distribution patterns through affecting lamellar structure and short-range ordered structure.

Geographically Weighted Flow Cross K-Function for Network-Constrained Flow Data

Network-constrained spatial flows are usually used to describe movements between two spatial places on a road network. The analysis of the spatial associations between different types of network-constrained spatial flows plays a key role in understanding the spatial relationships among different movements. However, existing studies usually do not consider the effect of distance decay, which may reduce the effectiveness of the detected bivariate spatial flow patterns. Moreover, most existing studies are based on the planar space assumption, which is not suitable for network-constrained spatial flows. To overcome these problems, this study proposed a new statistical method, the Geographically Weighted Network Flow Cross K-function, which improves the Flow Cross K-Function method by taking the distance decay effect and the constraints of road networks into account. Both global and local versions are extended in this study: the global version measures the overall spatial association and the local version identifies the exact locations where a spatial association occurs. The experiments on simulated datasets show that the proposed method can identify predefined bivariate flow patterns. In a case study, the proposed method is also applied to flow data comprising Xiamen taxi and ride-hailing datasets. The results demonstrate that the proposed method effectively identifies the competitive relationships between taxi and ride-hailing services.

Flow karyotyping of wheat-Aegilops additions facilitate dissecting the genomes of Ae. biuncialis and Ae. geniculata into individual chromosomes.

Breeding of wheat adapted to new climatic conditions and resistant to diseases and pests is hindered by a limited gene pool due to domestication and thousands of years of human selection. Annual goatgrasses (Aegilops spp.) with M and U genomes are potential sources of the missing genes and alleles. Development of alien introgression lines of wheat may be facilitated by the knowledge of DNA sequences of Aegilops chromosomes. As the Aegilops genomes are complex, sequencing relevant Aegilops chromosomes purified by flow cytometric sorting offers an attractive route forward. The present study extends the potential of chromosome genomics to allotetraploid Ae. biuncialis and Ae. geniculata by dissecting their M and U genomes into individual chromosomes. Hybridization of FITC-conjugated GAA oligonucleotide probe to chromosomes suspensions of the two species allowed the application of bivariate flow karyotyping and sorting some individual chromosomes. Bivariate flow karyotype FITC vs. DAPI of Ae. biuncialis consisted of nine chromosome-populations, but their chromosome content determined by microscopic analysis of flow sorted chromosomes indicated that only 7Mb and 1Ub could be sorted at high purity. In the case of Ae. geniculata, fourteen chromosome-populations were discriminated, allowing the separation of nine individual chromosomes (1Mg, 3Mg, 5Mg, 6Mg, 7Mg, 1Ug, 3Ug, 6Ug, and 7Ug) out of the 14. To sort the remaining chromosomes, a partial set of wheat-Ae. biuncialis and a whole set of wheat-Ae. geniculata chromosome addition lines were also flow karyotyped, revealing clear separation of the GAA-rich Aegilops chromosomes from the GAA-poor A- and D-genome chromosomes of wheat. All of the alien chromosomes represented by individual addition lines could be isolated at purities ranging from 74.5% to 96.6% and from 87.8% to 97.7%, respectively. Differences in flow karyotypes between Ae. biuncialis and Ae. geniculata were analyzed and discussed. Chromosome-specific genomic resources will facilitate gene cloning and the development of molecular tools to support alien introgression breeding of wheat.

BiFlowAMOEBA for the identification of arbitrarily shaped clusters in bivariate flow data

A bivariate flow cluster is a group of two types of spatial flows, where both types of flows have high (or low) values, or one type of flow has a high value while the other has a low value. Identifying bivariate flow clusters aids in understanding the complex interactions between different flow patterns. Detecting bivariate flow clusters remains challenging because statistics for quantitatively assessing bivariate flow clusters are lacking and the shapes and sizes of clusters vary. This study proposes a novel bivariate flow clustering method (BiFlowAMOEBA) by improving a multidirectional optimum ecotope-based algorithm (AMOEBA) which embeds local Getis-Ord statistic in an iterative procedure to detect irregular-shaped clusters. We define a bivariate local Getis-Ord statistic for quantitatively assessing bivariate flow clusters, use a hierarchical clustering strategy to construct clusters, and evaluate the statistical significance of clusters using a Monte Carlo simulation. Experimental results of simulated datasets show that BiFlowAMOEBA can identify bivariate flow clusters of different shapes more accurately and completely, compared with two state-of-the-art methods. Two case studies show that BiFlowAMOEBA helps not only unveil the interactions between public transport and taxi services but also identifies competition patterns between taxis and ride-hailing services.

In Memoriam: Marvin A. Van Dilla: 1919-2019.

© 2020 International Society for Advancement of Cytometry.

BiFlowLISA: Measuring spatial association for bivariate flow data

Spatial flow data are often used to represent spatial interaction phenomena such as daily commuting trips, human or animal migrations, and the exchanges of commodities, capital, or even information between regions. With the increasingly available large volume of flow data in fine spatiotemporal resolution, exploratory spatial data analysis (ESDA) has become more important than ever to gain understanding of the data and the story behind it. A major group of flow-related ESDA methods focus on measuring spatial associations, which proves useful in improving the prediction power and interpretability of spatial interaction model (SIM), as well as in identifying local clusters and outliers of flow events. This paper introduces a new spatial statistical method called BiFlowLISA—a local indicator of spatial association of bivariate flow data. BiFlowLISA evaluates the association between two types of flows in close proximity, in other words, how the value of type-I flows associate with the value of nearby type-II flows. We develop BiFlowLISA by extending the local bivariate Moran's I to the flow context. We also put forth its global version to measure the global patterns, and another variant of BiFlowLISA to measure both spatial and in-situ correlations at the same time. Several flow-specific issues are discussed and solved, including flow neighbor definition, OD matrix sparsity, and conditional permutation. We experiment with synthetic datasets to verify its functionality and to summarize its characteristics. A case study of taxi and ride-hailing services in New York City demonstrates its usefulness in the comparative analysis of the spatial patterns of two types of travel flows. More applications of BiFlowLISA await to be explored in the future.

Властивості моделі обслуговування паралельної структури

The present article is devoted to research the multi-channelk model with the parallel structure. It means that we consider the model which consists of two infinite-server queues. The service time in the each system has general function of distribution. In this case the stochastic dynamic of our model cannot be defined by Markov chain. As a result, analysis of such models is much more difficult than that of the corresponding Markovian queueing models. Besides we assume that customers arrive to our model according a bivariate Poisson input flow. This input process is characterized by the fact that customers arrive according to a bivariate Poisson flow simultaneously. We consider the number of customers in the systems at time t. This stochastic process describes the state of our model. In present paper we find the limit joint distribution of the number of customers in the systems. In a general way (by differentiating the corresponding generating function.) we obtain the main characteristics of this distribution, such as the expected number of customers in the nodes, its variance and correlation. In the case when parameters of our model dependent on the parameter n (number of series) the limit normal distribution was obtained for the service process in the stationary regime.

The digital divide: Risk and protective factors and the differences in problematic use of digital devices among Hungarian youth

A number of psychological factors have been found to be relevant in terms of problematic use of digital devices. Some of them may serve as risk factors, while others mean protection. The main goal of present study was to determine user profiles and to examine differences among them based on several psychological variables using cluster analysis. Data were collected from high school and university students via an online questionnaire from November 2017 to January 2018 (N = 249; females: 62.2%, Mean age = 22.5 years, SD = 3.5). Based on bivariate correlations, sensation seeking, flow and boredom proneness acted as risk factors for developing problematic technological use. However, self-esteem, self-regulation and resilience were significant protective factors against problematic technological use. In an effort to develop a set of profiles that would capture this student population and their usage relative to risk, we identified four distinct user profiles through the use of cluster analysis. The first cluster was labeled as strongly protected sensation-seekers who were more prone to problematic use (18.5%) with moderately high levels of protection, but with the highest scores on the boredom proneness and sensation seeking scales. The second cluster consisted of more balanced and non-vulnerable users (26.1%), who achieved average scores on both risk and protective factors scales. The third cluster was labeled protected, conscious users who were slightly prone to problematic use (39.8%) with lower levels of problematic use and risk factors, and with higher levels of protective factors. The fourth cluster was labeled as strongly problematic, unprotected users (15.7%), who achieved the highest scores of problematic use, and were the less protected having the lowest levels of protective factors scores. We conclude that cluster analysis was suitable for detecting differences in vulnerability to problematic Internet and smartphone use. Psychological factors, such as sensation seeking, flow and boredom, self-esteem, self-regulation and resilience serve as useful tools for providing information to better understanding the role of risk and protective factors in the prevention of youth’s problematic use of digital devices.

Non-stationarity analysis of flood flows using copula based change-point detection method: Application to case study of Godavari river basin

This study investigates the change in dependence structure of bivariate flood flow characteristics namely magnitude, frequency and timing in the Godavari river basin using a copula based likelihood ratio (CLR) test. Parametric bootstrap was used to obtain critical values of CLR test for the best-fitted copula. The performance of the CLR method was also evaluated for simulated synthetic bivariate series with a known change-point location in the dependence (copula parameter). Then the methodology was applied to two streamflow monitoring sites Bhimkund and Wagholi-Butti, located in the Godavari river basin in India. Streamflow data for 33 years from 1977 to 2009 was analyzed, by extracting the series of flow characteristics of magnitude, frequency and timing. Initially univariate change-point detection (CPD) test namely standard normal homogeneity test was applied to detect abrupt change-point in mean of the flow series. At Bhimkund site, there was abrupt increase in mean of magnitude, frequency and timing series after the identified change-point year. However, at Wagoli-Butti site, there was abrupt decrease in mean of magnitude and frequency series although timing series got delayed (i.e., abrupt increase). After univariate CPD in mean, the bivariate series i.e., magnitude-frequency and magnitude-timing pairs for these sites were analyzed to detect the change-points in dependence in terms of copula parameters using the CLR method. The results showed that change-points in the copula parameters were detected at year 2003 and 2004 for Wagoli- Butti and Bhimkund sites respectively, and appear to be jointly non-stationary due to human induced change at these two sites. The results of study for detection of the change-point location in the dependency structure of flow characteristics would be useful for flood risk assessment in the basin.

Dissecting the Complex Genome of Crested Wheatgrass by Chromosome Flow Sorting.

Wheatgrass (Agropyron sp.) is a potential source of beneficial traits for wheat improvement. Among them, crested wheatgrass [A. cristatum (L.) Gaertn.] comprises a complex of diploid, tetraploid, and hexaploid forms with the basic genome P, with some accessions carrying supernumerary B chromosomes (Bs). In this work, we applied flow cytometry to dissect the complex genome of crested wheatgrass into individual chromosomes to facilitate its analysis. Flow karyotypes obtained after the analysis of 4',6-diamidino-2-phenylindole (DAPI)-stained mitotic chromosomes of diploid and tetraploid accessions consisted of three peaks, each corresponding to a group of two or three chromosomes. To improve the resolution, bivariate flow karyotyping after fluorescent labeling of chromosomes with fluorescein isothiocyanate (FITC)-conjugated probe (GAA) microsatellite was applied and allowed discrimination and sorting of P genome chromosomes from wheat-crested wheatgrass addition lines. Chromosomes 1P-6P and seven telomeric chromosomes could be sorted at purities ranging from 81.7 to 98.2% in disomics and from 44.8 to 87.3% in telosomics. Chromosome 7P was sorted at purities reaching 50.0 and 39.5% in diploid and tetraploid crested wheatgrass, respectively. In addition to the whole complement chromosomes (A), Bs could be easily discriminated and sorted from a diploid accession at 95.4% purity. The sorted chromosomes will streamline genome analysis of crested wheatgrass, facilitating gene cloning and development of molecular tools to support alien introgression into wheat.

Flow Cross K-function: a bivariate flow analytical method

ABSTRACTSpatial flow data represent meaningful interaction activities between pairs of corresponding locations, such as daily commuting, animal migration, and merchandise shipping. Despite recent advances in flow data analytics, there is a lack of literature on detecting bivariate or multivariate spatial flow patterns. In this paper we introduce a new spatial statistical method called Flow Cross K-function, which combines the Cross K-function that detects marked point patterns and the Flow K-function that detects univariate flow clustering patterns. Flow Cross K-function specifically assesses spatial dependence of two types of flow events, in other words, whether one type of flows is spatially associated with the other, and if so, whether this is according to a clustering or dispersion trend. Both a global version and a local version of Flow Cross K-function are developed. The former measures the overall bivariate flow patterns in the study area, while the latter can identify anomalies at local scales that may not follow the global trend. We test our method with carefully designed synthetic data that simulate the extreme situations. We exemplify the usefulness of this method with an empirical study that examines the distributions of taxi trip flows in New York City.

Squamate Chromosome Size and GC Content Assessed by Flow Karyotyping

Chromosome homologies in reptiles have been investigated extensively by gene mapping and chromosome painting. Relative chromosome size can be estimated roughly from conventional karyotypes, but chromosome GC content cannot be evaluated by any of these approaches. However, GC content can be obtained by whole-genome sequencing, although complete data are available only for a limited number of reptilian species. Chromosomes can be characterized by size and GC content in bivariate flow karyotypes, in which the distribution of peaks represents the differences. We have analysed flow karyotypes from 9 representative squamate species and show chromosome profiles for each species based on the relationship between size and GC content. Our results reveal that the GC content of macrochromosomes is invariable in the 9 species. A higher GC content was found in microchromosomes, similar to profiles previously determined in crocodile, turtle, and chicken. The findings suggest that karyotype evolution in reptiles is characterized by unique features of chromosome GC content.

Bivariate low flow return period analysis in the Mahanadi River basin, India using copula

ABSTRACTAssessments of low flows of major river of India are essential for effective management of drought and irrigation water demand/supply mechanism. In the present work, bivariate low flow frequency analysis of Mahanadi basin, that had significant variations in hydrological behaviour from upstream to downstream, was done for two major low flow characteristics, namely, severity and occurrence . Three Copulas have been tested for their applicability to estimate the joint return period of low flow at 2, 5, 10, 20, 50 years return periods. According to the Akaike information criterion (AIC) value, the Clayton Copula and the Frank Copula were found to be the most suitable for the stations in Basantapur and Kantamal, respectively. Further, the conditional low flow return periods were estimated and were found useful for low flow management and ecological analysis in the Mahanadi basin.

Chromosome Analysis Using Benchtop Flow Analysers and High Speed Cell Sorters.

The use of the DNA dyes Hoechst (HO) and chromomycin A3 (CA3) has become the preferred combination for the bivariate analysis of chromosomes from both human and animals. This analysis requires a flow cytometer equipped with lasers of specific wavelength and of higher power than is typical on a conventional bench top flow cytometer. In this study, we have investigated the resolution of chromosome peaks in a human cell line with normal flow karyotype using different combinations of DNA dyes on a number of flow cytometers available in a flow cytometry core facility. Chromosomes were prepared from the human cell line using a modified polyamine isolation buffer. The bivariate flow karyotypes of different DNA dyes combination; 4′‐6‐diamidino‐2‐phenylindole (DAPI) or Hoechst with propidium iodide (PI), obtained from different flow cytometers were compared to the reference flow karyotype of DAPI or Hoechst with chromomycin A3, generated from a Mo‐Flo cell sorter using laser power settings of 300 mW each of UV and 457 nm. Good chromosome separation was observed in most of the flow cytometers used in the study. This study demonstrates that chromosome analysis and sorting can also be performed on benchtop flow cytometers equipped with the standard solid state 488 and 355 nm lasers, using a DNA dye combination of DAPI or Hoechst with PI. © 2018 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Bivariate flow cytometric analysis and sorting of different types of maize starch grains.

Particle-size distribution, granular structure, and composition significantly affect the physicochemical properties, rheological properties, and nutritional function of starch. Flow cytometry and flow sorting are widely considered convenient and efficient ways of classifying and separating natural biological particles or other substances into subpopulations, respectively, based on the differential response of each component to stimulation by a light beam; the results allow for the correlation analysis of parameters. In this study, different types of starches isolated from waxy maize, sweet maize, high-amylose maize, pop maize, and normal maize were initially classified into various subgroups by flow cytometer and then collected through flow sorting to observe their morphology and particle-size distribution. The results showed that a 0.25% Gelzan solution served as an optimal reagent for keeping individual starch particles homogeneously dispersed in suspension for a relatively long time. The bivariate flow cytometric population distributions indicated that the starches of normal maize, sweet maize, and pop maize were divided into two subgroups, whereas high-amylose maize starch had only one subgroup. Waxy maize starch, conversely, showed three subpopulations. The subgroups sorted by flow cytometer were determined and verified in terms of morphology and granule size by scanning electron microscopy and laser particle distribution analyzer. Results showed that flow cytometry can be regarded as a novel method for classifying and sorting starch granules. © 2017 International Society for Advancement of Cytometry.

Application of JC1 for non-toxic isolation of cells with MDR transporter activity by flow cytometry.

The DNA intercalating dye Hoechst 33342 or its close analog DCV are actively removed from cells by the multidrug resistance transporter ABCG2, a protein overexpressed in metastatic cells and somatic stem cells. In bivariate blue-red flow cytometry fluorescent plots active Hoechst or DCV efflux combined with a concentration dependent bathochromic shifts of these nuclear dyes leads to the segregation of the transporter-rich cells into a distinct cell cohort tilted towards the shorter wavelength axis of the plot, the cohort is generically known as the side population (SP). This feature has facilitated the surface marker-independent isolation of live stem cells. A drawback, though, is the known toxicity of Hoechst dyes. In this study we show that JC1, a bathochromic mitochondrial membrane potential-sensitive dye applied at proper concentration, can yield flow cytometry fluorescent emission bivariate plots containing a low JC1 accumulation (JC1low) cohort. Using a combination of multiple cell lines, ABC-transporter inhibitors and viral vector-driven insertion of the ABCG2 gene or ABCG2 and ABCB1 shRNAs we demonstrate that JC1low can be generated by either of the two aforementioned multidrug resistance transporters. Complete wash out of mitochondrial bound JC1 required more than 24 h. In spite of this tight binding, the dye did not affect either the mitochondrial membrane potentials or the proliferation rate. In contrast, contemporaneous with its nuclear accumulation, Hoechst 33342 or DVC, caused changes in the fluorescent emission of mitochondrial membrane potential sensitive dyes resembling the effects caused by the mitochondrial uncoupler FCCP. In a number of cell lines exposure to Hoechst resulted in marked slow-down of proliferation and abolition of ABCG2 transport activity during the subsequent 2 days but in K562 cells the exposure induced cell extended death. Overall, its lack of toxicity vis. a vis. the toxicity and genotoxicity of the DNA intercalating dyes makes JC1 an ideal tool for isolating live cells expressing high multidrug resistance transport activity.

Anti-hepatoma activities of ethyl acetate extract from Ampelopsis sinica root.

Ampelopsissinica root(ASR) is a known hepatoprotective folk traditional Chinese medicine. The anti‑hepatoma activity of ethyl acetate extract from A.sinica root(ASRE) invitro and invivo and its possible mechanism were explored. This study was designed to investigate cytotoxicity by MTT assay, induction of apoptosis via Hoechst33258 staining, scanning electron microscopy and bivariate flow cytometric analysis(AnnexinV-FITC/PI), inflammation and apoptosis related genes expression by RT-PCR and p53 protein expression by immunofluorescence assay in HepG2cells. Then, the antitumor activity invivo was detected by hepatomaH22 xenograft tumor in mice. The results showed that ASRE had powerful anti‑hepatoma activity invitro without obvious toxicity on normal cells and could induce HepG2cell apoptosis. The mechanism may be associated with downregulation of inflammatory cytokines including cyclooxygenase-2, 5-lipoxygenase and FLAP, increase of the ratio of bax/bcl-2, activation caspase-3 and inhibition of survivin, and increased expression of p53protein. Furthermore, the HPLC assay showed the main compounds of ASRE were gallic acid, catechin and gallic acid ethyl ester. In animal experiments, ASR ethanol extract decreased the tumor weights of hepatomaH22 tumor-bearing mice. Therefore, ASR may be a potential therapeutic agent in the treatment of hepatocellular carcinoma.