Boosting the Antioxidant Potential of Polymeric Proanthocyanidins in Litchi (Litchi chinensis Sonn.) Pericarp via Biotransformation of Utilizing Lactobacillus Plantarum.

In order to enhance the efficient utilization of polymeric proanthocyanidins from litchi pericarp, a process for transforming litchis' polymeric proanthocyanidins (LPPCs) by using Lactobacilli has been established for products with highly antioxidative properties. Lactobacillus plantarum was selected to enhance the transformation effect. The transformation rate of LPPCs reached 78.36%. The content of litchis' oligomeric proanthocyanidins (LOPCs) in the products achieved 302.84 µg grape seed proanthocyanidins (GPS)/mg DW, while that of total phenols was 1077.93 gallic acid equivalents (GAE) µg/mg DW. Seven kinds of substances have been identified in the products by using the HPLC-QTOF-MS/MS method, among which 4-hydroxycinnamic acid, 3,4-dihydroxy-cinnamic acid, and proanthocyanidin A2 were major components. The in vitro antioxidative activity of the products after transformation was significantly (p < 0.05) higher than those of LOPCs and LPPCs. The scavenging activity of the transformed products for DPPH free radicals was 1.71 times that of LOPCs. The rate of inhibiting conjugated diene hydroperoxides (CD-POV) was 2.0 times that of LPPCs. The scavenging activity of the products for ABTS free radicals was 11.5 times that of LPPCs. The ORAC value of the products was 4.13 times that of LPPCs. In general, this study realizes the transformation of polymeric proanthocyanidins into high-activity small-molecule substances.

The Workability and Mechanical Performance of Fly Ash Cenosphere-Desert Sand Ceramsite Concrete: An Experimental Study and Analysis.

In order to alleviate the shortage of sand resources for construction, make full use of industrial waste and promote the development of green lightweight aggregate concrete in the desert and surrounding areas, this paper proposes a new lightweight ceramsite concrete, fly ash cenospheres and desert sand ceramsite concrete (FDCC). An orthogonal test was conducted to analyze the effects of the desert sand (DS) replacing ratio, fly ash cenosphere (FAC) replacing ratio and polymer emulsion (PLE) addition on the damage patterns, slump, apparent density and compressive strength of the FDCC. The results showed that the most influential factors for the slump, apparent density and compressive strength of the FDCC were the FAC replacing ratio, FAC replacing ratio and DS replacing ratio, respectively. Meanwhile, the PLE addition had little effect on the workability or mechanical performance of the FDCC. With the increase in the DS replacing ratio, the slump decreased rapidly and the compressive strength reached its peak value, increasing by 20.6% when the DS replacing ratio was 20%. With the increase in the FAC replacing ratio, the slump increased by 106%, the apparent density decreased gradually and the compressive decreased and then increased, reaching its lowest value when the FAC replacing ratio was 20%. According to the synthetic evaluation analysis, the optimum DS replacing ratio, FAC replacing ratio and PLE addition of the FDCC were 20%, 30% and 1%, respectively.

Physiological Status Prediction Based on a Novel Hybrid Intelligent Scheme.

Physiological status plays an important role in clinical diagnosis. However, the temporal physiological data change dynamically with time, and the amount of data is large; furthermore, obtaining a complete history of data has become difficult. We propose a hybrid intelligent scheme for physiological status prediction, which can be effectively utilized to predict the physiological status of patients and provide a reference for clinical diagnosis. Our proposed scheme initially extracted the attribute information of nonlinear dynamic changes in physiological signals. The maximum discriminant feature subset was selected by employing conditional relevance mutual information feature selection. An optimal subset of features was fed into the particle swarm optimization-support vector machine classifier to perform classification. For the prediction task, the proposed hybrid intelligent scheme was tested on the Sleep Heart Health Study dataset for sleep status prediction. Experimental results demonstrate that our proposed intelligent scheme outperforms the conventional machine learning classification methods.

Intake of Sugar Substitute Gummy Candies Benefits the Glycemic Response in Healthy Adults: A Prospective Crossover Clinical Trial.

Sugar reduction in food has attracted great health concerns worldwide. Gummies have been one of the most popular and highly favored candies due to their chewable properties, simplicity to swallow, and delicious taste. The general perception is that gummies raise blood sugar levels, but the truth is that gummies with the right formula can control glycemic response. The purpose of this study is to investigate the effects of the gummy dosage form and sugar types on the glycemic response control. Maltitol and erythritol as sweetener alternatives were applied in gummy candies (total and partial sugar substitutes gummy, T-SG and P-SG), with sucrose-based gummies used as comparisons (CG). A prospective crossover study was then conducted on 17 healthy adults. The effects of different types of gummies on glycemic response in healthy adults were evaluated on the basis of the participants' glycemic index (GI) and glycemic load (GL) values. Every three-day interval, participants took CG, P-SG, T-SG, and glucose solution, respectively, and the theoretical glucose conversion content was kept the same in all groups for each trial. Each participant performed four tests with each sample and recorded the changes in blood glucose after food consumption. It was found that all three types of gummies slowed down subjects' glycemic response when not taken in excess, and the improvement effect was in the trend of T-SG > P-SG > CG. Both P-SG and T-SG were low-GI candies (54.1 and 49.9). CG that was not consumed in excess of 17.2 g had a high GI (81.9) but a low GL (<10). Texture analysis and in vitro digestion were used to explore the effect of gummy matrix on glucose release. T-SG and P-SG retained a higher hardness and were less hydrolyzed to release glucose during digestion compared with CG. Additionally, experiments have revealed that gummies can reverse the poor glucose tolerance in women. In conclusion, gummies are a good carrier for dietary supplements due to their sustained-release characteristic of available carbohydrates and provide healthier options for people in control of glucose homeostasis.

Internal or External Word-of-Mouth (WOM), Why Do Patients Choose Doctors on Online Medical Services (OMSs) Single Platform in China?

(1) Background: Word-of-mouth (WOM) can influence patients' choice of doctors in online medical services (OMSs). Previous studies have explored the relationship between internal WOM in online healthcare communities (OHCs) and patients' choice of doctors. There is a lack of research on external WOM and position ranking in OMSs. (2) Methods: We develop an empirical model based on the data of 4435 doctors from a leading online healthcare community in China. We discuss the influence of internal and external WOM on patients' choice of doctors in OMSs, exploring the interaction between internal and external WOM and the moderation of doctor position ranking. (3) Results: Both internal and external WOM had a positive impact on patients' choice of doctors; there was a significant positive interaction between internal and third-party generated WOM, but the interaction between internal and relative-generated WOM, and the interaction between internal and doctor-generated WOM were both nonsignificant. The position ranking of doctors significantly enhanced the impact of internal WOM, whereas it weakened the impact of doctor recommendations on patients' choice of doctors. (4) The results emphasize the importance of the research on external WOM in OMSs, and suggest that the moderation of internal WOM may be related to the credibility and accessibility of external WOM, and the impact of doctor position ranking can be explained by information search costs.

Impact of a probiotic chewable tablet on stool habits and microbial profile in children with functional constipation: A randomized controlled clinical trial.

Constipation is a common and typically multifactorial childhood complaint, and the clinical management of childhood functional constipation (FC) is challenging. A randomized, single-blind, placebo-controlled, multi-center clinical trial was conducted in 92 children (47 from Beijing, China and 45 from Shanghai, China) aged 4-12 with FC according to Rome III criteria. Children were assigned to receive a probiotic chewable tablet (5 × 109 CFU/day, n = 47), consisting of Lactobacillus acidophilus DDS-1® and Bifidobacterium animalis subsp. lactis UABla-12™ or placebo (n = 45), twice daily for 4 weeks, followed by a week follow-up period. Results suggested that the probiotic group showed a faster and more pronounced normalization of stool frequency over the intervention period (3.15 vs. 1.83) when compared to placebo group (2.51 vs. 1.87). Meanwhile, the percentage of subjects with hard defecation decreased from 43 to 14% in the probiotic group, while the percentage of subjects with normal defecation increased from 56 to 80% in the probiotic group, further confirming the normalization of stools habits. This randomized controlled trial demonstrated the potential of a probiotic chewable tablet containing L. acidophilus DDS-1® and B. Lactis UABla-12™ as a daily probiotic dosage form for children with FC.

Cyclic Behavior of Gabled Frames with Web-Tapered Columns and Rafters.

Cyclic loading tests were conducted on three 1/2-scale, half-bay steel gabled frames (SGFs) to investigate their seismic performance. The three specimens with reduced joint stiffness were designed based on the prototype drawing shown in China design guideline 02SG518-1: specimen SV1 with a reduced thickness of the joint end-plate and bolt diameter, specimen SV2 with a reduced number of bolts, and specimen SV3 with a reduced bolt diameter. The load capacity, rotational stiffness, rotational capacity, and ultimate failure mode of specimens SV1, SV2, and SV3 were investigated. The experimental results showed that specimen SV1 failed due to the local buckling of the lower flange of the rafter, and specimens SV2 and SV3 due to the local buckling of upper flange of the rafter. The joint zone of all specimens kept well, indicating that the prototype joint had a large margin of safety. The hysteresis curves of all specimens were not full, and the ductility and energy dissipation capacity were limited. The end-plate thickness, bolt diameter, and steel grade affected the hysteresis performance of the SGF little. A refined finite element model was established, and the predicted results compared well with the test results. The test and analysis results demonstrated that there was slight utilization and distribution of post-buckling strength.

A Hybrid Method to Predict Postoperative Survival of Lung Cancer Using Improved SMOTE and Adaptive SVM.

Predicting postoperative survival of lung cancer patients (LCPs) is an important problem of medical decision-making. However, the imbalanced distribution of patient survival in the dataset increases the difficulty of prediction. Although the synthetic minority oversampling technique (SMOTE) can be used to deal with imbalanced data, it cannot identify data noise. On the other hand, many studies use a support vector machine (SVM) combined with resampling technology to deal with imbalanced data. However, most studies require manual setting of SVM parameters, which makes it difficult to obtain the best performance. In this paper, a hybrid improved SMOTE and adaptive SVM method is proposed for imbalance data to predict the postoperative survival of LCPs. The proposed method is divided into two stages: in the first stage, the cross-validated committees filter (CVCF) is used to remove noise samples to improve the performance of SMOTE. In the second stage, we propose an adaptive SVM, which uses fuzzy self-tuning particle swarm optimization (FPSO) to optimize the parameters of SVM. Compared with other advanced algorithms, our proposed method obtains the best performance with 95.11% accuracy, 95.10% G-mean, 95.02% F1, and 95.10% area under the curve (AUC) for predicting postoperative survival of LCPs.

A novel prognostic model based on multi-omics features predicts the prognosis of colon cancer patients.

BACKGROUND: As a common malignant tumor in the colon, colon cancer (CC) has high incidence and recurrence rates. This study is designed to build a prognostic model for CC. METHODS: The gene expression dataset, microRNA-seq dataset, copy number variation (CNV) dataset, DNA methylation dataset, and transcription factor (TF) dataset of CC were downloaded from UCSC Xena database. Using limma package, the differentially methylated genes (DMGs), and differentially expressed genes (DEGs) and miRNAs (DEMs) were identified. Based on random forest method, prognostic model for each omics dataset were constructed. After the omics features related to prognosis were selected using logrank test, the prognostic model based on multi-omics features was built. Finally, the clinical phenotypes correlated with prognosis were screened using Kaplan-Meier survival analysis, and the nomogram model was established. RESULTS: There were 1625 DEGs, 268 DEMs, and 386 DMGs between the tumor and normal samples. A total of 105, 29, 159, five, and six genes/sites significantly correlated with prognosis were identified in the gene expression dataset (GABRD), miRNA-seq dataset (miR-1271), CNV dataset (RN7SKP247), DNA methylation dataset (cg09170112 methylation site [located in SFSWAP]), and TF dataset (SIX5), respectively. The prognostic model based on multi-omics features was more effective than those based on single omics dataset. The number of lymph nodes, pathologic_M stage, and pathologic_T stage were the clinical phenotypes correlated with prognosis, based on which the nomogram model was constructed. CONCLUSION: The prognostic model based on multi-omics features and the nomogram model might be valuable for the prognostic prediction of CC.

Quyushengxin Formula Causes Differences in Bacterial and Phage Composition in Ulcerative Colitis Patients.

BACKGROUND: Ulcerative colitis (UC) is a chronic inflammatory disease that affects the colon and the rectum. Recently, some studies have shown that microorganisms in the gut play important roles in many chronic diseases such as UC. METHODS: To study the candidate viruses and bacteria involved in UC and to investigate the therapeutic mechanism of Quyushengxin formula (QYSX) in UC patients, metagenomic sequencing was performed on the feces from healthy donors and UC patients before and after QYSX treatment. RESULTS: QYSX improved the symptoms of UC. In all participants, Caudovirales and Herpesvirales were the most dominant viruses. The abundance of Caudovirales in UC patients was significantly higher than that in the normal controls, while QYSX restored Caudovirales abundance. Furthermore, the abundance of crAssphage was enhanced in UC patients compared with the normal control, while the diversity was then decreased after QYSX treatment. However, there was no significant difference (P > 0.05). Additionally, other non-crAssphage bacteriophages including phiST, SP-10, and phi17:2 were higher in UC patients and QYSX decreased these viruses, while the trends of MED4-213, P-HM1, and P-HM2 were adverse. Interestingly, PhiDP23.1 was only found in UC patients before and after QYSX treatment. In addition, Bifidobacterium, Bacteroidetes, Prevotellaceae, Actinobacteria, and Corynebacteriales were the biomarkers in UC patients after QYSX treatment due to their high abundance. GO terms and KEGG analysis showed that the identified gut microbiome was involved in many biological processes and pathways. CONCLUSIONS: QYSX could regulate disordered gut microbiome and phages, indicating that QYSX has great therapeutic potential for UC.

Immune-Related Prognostic Model in Colon Cancer: A Gene Expression-Based Study.

Mounting evidence supports that the malignant phenotypes of cancers are defined not only by the intrinsic activity of tumor cells but also by immune cells that are recruited and activated in tumor-related microenvironment. Here, we developed a diagnostic and prognostic model for colon cancer, based on expression profiles of immune-related genes and immune cell component. As a result, we found that B cell infiltration ratio, CD4+ T cells, as well as immune-related genes of TRIB3, CHGA, CASP7, LGALS4, LEP, NOX4, IL17A, and HSPD1 may be highly relevant with clinical outcome of colon cancer.

A 6 lncRNA-Based Risk Score System for Predicting the Recurrence of Colon Adenocarcinoma Patients.

Colon adenocarcinoma (COAD) is a common type of colon cancer, and post-operative recurrence and metastasis may occur in COAD patients. This study is designed to build a risk score system for COAD patients. The Cancer Genome Atlas (TCGA) dataset of COAD (the training set) was downloaded, and GSE17538 and GSE39582 (the validation sets) from Gene Expression Omnibus database were obtained. The differentially expressed RNAs (DERs) were analyzed by limma package. Using survival package, the independent prognosis-associated long non-coding RNAs (lncRNAs) were selected for constructing risk score system. After the independent clinical prognostic factors were screened out using survival package, a nomogram survival model was constructed using rms package. Furthermore, competitive endogenous RNA (ceRNA) regulatory network and enrichment analyses separately were performed using Cytoscape software and DAVID tool. Totally 404 DERs between recurrence and non-recurrence groups were identified. Based on the six independent prognosis-associated lncRNAs (including H19, KCNJ2-AS1, LINC00899, LINC01503, PRKAG2-AS1, and SRRM2-AS1), the risk score system was constructed. After the independent clinical prognostic factors (Pathologic M, pathologic T, and RS model status) were identified, the nomogram survival model was built. In the ceRNA regulatory network, there were three lncRNAs, four miRNAs, and 77 mRNAs. Additionally, PPAR signaling pathway and hedgehog signaling pathway were enriched for the mRNAs in the ceRNA regulatory network. The risk score system and the nomogram survival model might be used for predicting COAD recurrence. Besides, PPAR signaling pathway and hedgehog signaling pathway might affect the recurrence of COAD patients.

Association of a novel seven-gene expression signature with the disease prognosis in colon cancer patients.

Older patients who are diagnosed with colon cancer face unique challenges, specifically regarding to cancer treatment. The aim of this study was to identify prognostic signatures to predicting prognosis in colon cancer patients through a detailed transcriptomic analysis. RNA-seq expression profile, miRNA expression profile, and clinical phenotype information of all the samples of TCGA colon adenocarcinoma were downloaded and differentially expressed mRNAs (DEMs), differentially expressed lncRNAs (DELs) and differentially expressed miRNAs (DEMis) were identified. A competing endogenous RNA (ceRNA) network was constructed further and DEMs related with prognosis in the ceRNA network was screened using Cox regression analysis. Risk score models for predicting the prognosis of colon cancer patients were built using these DEMs. A total of 1476 DEMs, 9 DELs, and 243 DEMis between the tumor and normal samples were identified and functional enrichment analyses showed that the DEMs were significantly enriched in the nervous system development, ribosome biogenesis pathways in eukaryotes, and drug metabolism cytochrome P450. Twelve DEMs related with prognosis were screened from the ceRNA network. Thereafter, the risk score models of prognostic DEMs were obtained, involving seven DEMs (SGCG, CLDN23, SLC4A4, CCDC78, SLC17A7, OTOP3, and SMPDL3A). Additionally, cancer stage was identified as a prognostic clinical factor. This prognostic signature was further validated in two independent datasets. Our study developed a seven-mRNA and one-clinical factor signature that are associated with prognosis in colon cancer patients, which may serve as possible biomarkers and therapeutic targets in the future.

Adaptive Learning Emotion Identification Method of Short Texts for Online Medical Knowledge Sharing Community.

The medical knowledge sharing community provides users with an open platform for accessing medical resources and sharing medical knowledge, treatment experience, and emotions. Compared with the recipients of general commodities, the recipients in the medical knowledge sharing community pay more attention to the intensity or overall evaluation of emotional vocabularies in the comments, such as treatment effects, prices, service attitudes, and other aspects. Therefore, the overall evaluation is not a key factor in medical service comments, but the semantics of the emotional polarity is the key to affect recipients of the medical information. In this paper, we propose an adaptive learning emotion identification method (ALEIM) based on mutual information feature weight, which captures the correlation and redundancy of features. In order to evaluate the proposed method's effectiveness, we use four basic corpus libraries crawled from the Haodf's online platform and employ Taiwan University NTUSD Simplified Chinese Emotion Dictionary for emotion classification. The experimental results show that our proposed ALEIM method has a better performance for the identification of the low-frequency words' redundant features in comments of the online medical knowledge sharing community.

Network Pharmacology-Based Investigation into the Mechanisms of Quyushengxin Formula for the Treatment of Ulcerative Colitis.

OBJECTIVE: Ulcerative colitis (UC) is a chronic idiopathic inflammatory bowel disease whose treatment strategies remain unsatisfactory. This study aims to investigate the mechanisms of Quyushengxin formula acting on UC based on network pharmacology. METHODS: Ingredients of the main herbs in Quyushengxin formula were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Absorption, distribution, metabolism, and excretion properties of all ingredients were evaluated for screening out candidate bioactive compounds in Quyushengxin formula. Weighted ensemble similarity algorithm was applied for predicting direct targets of bioactive ingredients. Functional enrichment analyses were performed for the targets. In addition, compound-target network, target-disease network, and target-pathway network were established via Cytoscape 3.6.0 software. RESULTS: A total of 41 bioactive compounds in Quyushengxin formula were selected out from the TCMSP database. These bioactive compounds were predicted to target 94 potential proteins by weighted ensemble similarity algorithm. Functional analysis suggested these targets were closely related with inflammatory- and immune-related biological progresses. Furthermore, the results of compound-target network, target-disease network, and target-pathway network indicated that the therapeutic effects of Quyushengxin on UC may be achieved through the synergistic and additive effects. CONCLUSION: Quyushengxin may act on immune and inflammation-related targets to suppress UC progression in a synergistic and additive manner.

In Vitro Study of Bacteriophage AB3 Endolysin LysAB3 Activity Against Acinetobacter baumannii Biofilm and Biofilm-Bound A. baumannii.

BACKGROUND: The increase in the prevalence of drug-resistant Acinetobacter baumannii is a serious public health concern, which is closely linked to the formation of biofilm. It is reported that the bacteriophage and its endolysin have a good ability to degrade biofilms. The goals of this study were to compare the ability of A. baumannii bacteriophage AB3, its endolysin AB3, and three antibiotics to degrade A. baumannii biofilm and biofilm-bound A. baumannii and to understand the antibacterial mechanism of LysAB3. METHODS: The 558-bp sequence of the LysAB3 gene was amplified by polymerase chain reaction (PCR); the fragment was cloned into pET28a (+) to construct the recombinant plasmid pET28a-LysAB3, which was then expressed in E. coli BL21 (DE3) to obtain the LysAB3. Differences in A. baumannii biofilm and biofilm-bound A. baumannii after treatment with bacteriophage AB3, LysAB3 or three antibiotics were examined using the crystal violet staining method and an MTT (3-[4,5-dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide) assay. Changes in biofilm morphology and thickness in each treatment group were observed by laser scanning confocal microscopy. In addition, a LysAB3 construct with the amphiphilic peptide structural region removed (LysAB3-D) was assessed for its antibacterial activity. RESULTS: After 24-hour treatment with either bacteriophage AB3 and its LysAB3, A. baumannii biofilms were significantly degraded, and the number of viable biofilm-bound A. baumannii were also significantly decreased. After removing the amphiphilic peptide structure motif from LysAB3, the antibacterial activity decreased from 95.8% to 33.3%. CONCLUSIONS: Thus, LysAB3 can effectively degrade A. baumannii biofilm and biofilm-bound A. baumannii in vitro. The antibacterial mechanism of LysAB3 may be associated with the ability of the amphiphilic peptide structural region to enhance the permeability of cytoplasmic membrane of A. baumannii by degradation of bacterial wall peptidoglycan.

Altered Norbin Expression in Patients with Epilepsy and a Rat Model.

Norbin is widely distributed in neuronal tissues, is a regulator of Ca2+/calmodulin-dependent protein kinase II (CaMKII) phosphorylation. Norbin is also an important endogenous modulator of metabotropic glutamate receptor 5 (mGluR5) signaling, and nervous system-specific homozygous gene disruptions, result in epileptic seizures. In this study, we aimed to investigate norbin expression patterns in epilepsy and to elucidate the relationships between norbin and mGluR5 and p-CaMKII in epilepsy. Double-immunolabeling, immunohistochemistry and immunoblotting studies showed that norbin was downregulated in the temporal neocortex of patients with temporal lobe epilepsy (TLE) compared with control subjects. Moreover, in a rat model of lithium chloride-pilocarpine-induced epilepsy, norbin expression began to decrease at 6 h after the onset of status epilepticus and remained at a low level until 60 days. In addition, p-CaMKII expression was significantly increased in both patients with TLE and in animal model. Norbin and mGluR5 were found to be co-expressed in neurons of epileptic tissues. Finally, norbin over-expression facilitated by injections of adeno-associated viral vector into the rat hippocampus increased latency and survival in the lithium chloride-pilocarpine model. Thus, our results indicate norbin participates in the pathogenesis of epilepsy, perhaps by modulating mGluR5 signaling, regulating CaMKII phosphorylation, and may exert antiepileptic effects.

Preparation, preliminary characterization and inhibitory effect on human colon cancer HT-29 cells of an acidic polysaccharide fraction from Stachys floridana Schuttl. ex Benth.

A polysaccharide fraction (SFPSA) was obtained from the rhizomes of Stachys floridana Schuttl. ex Benth. by hot water extraction and sequential purification of anion-exchange chromatography and gel-filtration chromatography. SFPSA was found to be an acidic polysaccharide fraction with an average molecular weight of 168kDa and composed of rhamnose, glucuronic acid, galacturonic acid, glucose, galactose and arabinose in a molar percentage of 7.75:1.65:14.92:1.87:33.17:40.64, respectively. SFPSA could inhibit the proliferation and growth of human colon cancer HT-29 cells in a time- and dose-dependent manner within 48h, induce the apoptosis and increase the accumulation in G2/M phase of HT-29 cells. Furthermore, it was found that SFPSA could decrease Bcl-2 mRNA level, and increase the mRNA expressions of Bax and p53 and the activity of caspase-3. These results indicated that SFPSA might induce apoptosis of HT-29 cells through regulation of apoptosis-associated gene expressions such as Bcl-2, Bax and p53 and the activation of caspase-3.

Antioxidant activity and potential hepatoprotective effect of polysaccharides from Cyclina sinensis.

In the present study, we investigated the preliminary structure, in vitro antioxidant and in vivo hepatoprotective activities of polysaccharides from Cyclina sinensis (CSPS). The analytic results of Fourier transform-infrared spectroscopy indicated the presence of α-type glycosidic linkages in CSPS-1 or CSPS-2, and the average molecular weights for CSPS-1, CSPS-2 and CSPS-3 were 69, 81 and 101 kDa, respectively. For antioxidant activities in vitro, crude CSPS, CSPS-1, CSPS-2 and CSPS-3 showed moderate H(2)O(2) scavenging activity, lipid peroxidation inhibition effect and strong Fe(2+) chelating activity. For hepatoprotective activity in vivo, the administration of CSPS significantly decreased serum levels of alanine aminotransferase and aspartate aminotransferase, inhibited the formation of malondialdehyde and enhanced the activities of liver superoxide dismutase and glutathione peroxidase in carbon tetrachloride-induced liver injury mice. These results suggested that CSPS had potent antioxidant and hepatoprotective activities.