This study was performed according to the Guide for the Care and Use of Laboratory Animals, which was published by the US National Institutes of Health (National Institutes of Health Publication No. 85 − 23, revised 1996) and was approved by the Ethics Committee of China Academy of Chinese Medical Sciences. Adult male Sprague-Dawley rats weighing 230–250 g were obtained from the Animal Breeding Centre of Beijing Vital River Laboratories Company (Beijing, China). All animals were housed individually at 22 ± 2°C with a relative humidity of 50 ± 10% and a 12-h light/12-h dark cycle. The animals were kept in a pathogen-free environment with free access to food and water. The experimental procedures were approved by the China Academy of Chinese Medical Science's Administrative Panel on Laboratory Animal Care.
Berberine (Purity ≥ 95.18%) was purchased from Xian yang Aviation 168 Bio-engineering Co., Ltd (Xian yang, China). Jasminoidin (Purity ≥ 99.68%) was purchased from Baoji Fangcheng Bio-engineering Co., Ltd (Baoji, China).Ginsenosides (Rg + Re + Rd ≥ 40.55%±5%) was purchased from Nanjing Zelang Co., Ltd (Nanjing, China). EGb761 was purchased from Dr. Willmar Schwabe (Karlsruhe, Germany, 4250213).
1.10 Animal models and experimental design
After 48h of acclimatization, the rats were anesthetized with chloral hydrate at a dose of 400×10− 3 g•kg− 1 (i.p.). The rectal temperature was recorded and maintained at 37 ± 0.5°C throughout the surgical procedure. The MCAO operation by the intraluminal filament method was performed according to a previously reported method with some modifications. Two timepoints, 6h and 8h were chosen after MCAO operation in this study,. The rats were randomly divided into 6 groups according to a uniform design (n = 3/group): 6h sham group, 6h vehicle control group, 6h YJ groups (25mg•kg− 1), 8h sham group, 8h vehicle control group, 8h YJ groups (25mg•kg− 1). The sham operation group was subjected to only preoperative anesthesia and blood vessel separation; the other groups were subjected to the MCAO model. After 6h, neurological function score was assessed, then the animals were sacrificed to obtain brain, spleen and blood respectively. Furthermore, brains and spleens were made as homogenate and white blood cells were separated from whole blood for further tests.
1.11 Microarray analysis
RNAs of the three parts of each rat were extracted with Qiagen RNA kit. Total RNA was reverse transcribed, amplified, labelled and hybridized to Rat Genome 1.0 arrays (Affymetrix). Microarray data sets were analysed with Agilent Genespring GS 11 software. RNA of different samples was prepared in the same procedure and used in microarray analysis.
1.12 Investigating of differential expression genes
Genes were standardized and interpreted functionally before comparison. Using RVM t-test (random variance model t-test) and the short-survival group as the control group, the P value and the false discovery rate (FDR) were calculated for each differential expression gene. FDR was calculated to correct the P-value, which controls type I errors. With a threshold of P value < 0.01 and FDR < 0.05, survival duration-related differential expression genes were picked out. The up-regulation genes and the down-regulation genes can be classified by the fold change of intensities
1.13 Enrichment analysis
1.13.1 Gene ontology (GO) analysis
Based on Gene Ontology Database (http://www.geneontology.org/
) and UniProt Database (http://www.uniprot.org/
), the significance level of GOs of the survival duration-related differentially expressed genes was analysed by two-side Fisher’s exact test and 2 test. The differential expression genes were analysed independently according to up- and down-regulation of these genes. We computed P-values for all the differential expression genes in all GO categories, and the threshold of significance was defined as P-value < 0.01 and FDR < 0.05. Each GO was also analysed by enrichment analysis using the following formula: Re = (nf/n)/(Nf/N), where nf refers to the number of differential expression genes within the particular category, n to the total number of genes within the same category, Nf to the number of differential expression genes in the entire microarray, and N to the total number of genes detected in the Microarray. Matlab (http://www.mathworks.com
) and Mysql (http://www.mysql.com/
) were used as the analysis platforms.
1.13.2 Pathway analysis
Data of signaling pathways were from KEGG (http://www.genome.jp/kegg/), Biocarta (http://www.biocarta.com/), Humancyc (http://humancyc.org/), Reactome (http://reactome.org/) and NCBI Database (http://www.ncbi.nlm.nih.gov/). All signaling pathways were analysed for the significance level, using P < 0.01 and FDR < 0.05 as the threshold, Matlab and Mysql as the analysis platforms. The enrichment was calculated like the equation above.
1.14 Dynamic gene network analysis
The normalized signal intensity of significant differential genes was used to build a co-expression network. At first, the Pearson’s correlation of each pair of genes was calculated as the basis of choosing the significant correlation gene pairs. Then the gene-gene interaction network was established according to the correlation between genes. Within the network analysis, nodes represent the genes, and the edges between genes depict the interaction between them. All the nodes were marked with degree, which is defined as the link numbers one node has to the other. Genes with higher degrees occupied more central positions in the network and had a stronger capacity of modulating adjacent genes. In addition, k-core in graph theory was applied to describe the characteristics of the network including, but not limited to, the centrality of genes within a network and the complexity of the sub-networks. According to the relationship between genes, they were divided into several sub-networks, and marked with different colours.
1.15 Validation of microarray data by Real-time PCR
To confirm the reliability and facticity of the background network, we chose 21 genes from different organs as the test genes. Three parameters, degree (the total inward and outward connections of one gene), fold change value (the ratio of sham group to model group) and p-value (the expression difference between sham group and model group) in detail respectively, were considered during the choose process. The threshold of degree is set greater than 3 folds, the fold change value is over 1.3 folds, and the p-value is under 0.05. Total RNA was extracted from sample organs as used in microarray assay including three independent experiments Trizol Reagent (Life Technologies). Following purification with an RNeasy kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s manual. M-MLV reverse transcription (Promega) was used to synthesize cDNA. Quantitative PCR analysis and data collection were performed on the ABI 7900HT qPCR system using the primer pairs listed below. The raw quantifications were normalized to 18s values for each sample and fold changes were shown as mean ± SD in three independent experiments with each triplicate.
1.16 Treatment group on inflammation network
Treatment group data were mapped onto the established inflammation networks ( established in 2.7). Different colours filled in circle stood for the sources from different organs.