ObjectiveTo investigate the migration and distribution characteristics of chemical constituents in blood and hippocampal tissues before and after vinegar processing of Citri Reticulatae Pericarpium Viride（CRPV）， and to explore the potential material basis and mechanisms underlying their regulatory effects on emotional disorders by comparing the effects of raw and vinegar-processed products of CRPV. MethodsUltra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was employed to characterize and identify the chemical constituents of raw and vinegar-processed products of CRPV extracts， as well as their migrating components in blood and hippocampal tissues after oral administration. Reference standards， databases， and relevant literature were utilized for compound annotation， with data processing performed using PeakView 1.2 software. Seventy male C57BL/6 mice were randomly divided into seven groups， including the blank group， model group， diazepam group（2.5 mg·kg^-1）， raw CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， and vinegar-processed CRPV low/high dose groups（0.6， 1.2 g·kg^-1）， with 10 mice per group. Except for the blank group， all other groups underwent chronic restraint stress（2 h·d^-1） for 20 d. Each drug-treated group received oral administration at the predetermined dose starting 10 d after modeling， with a total treatment duration of 10 d. Following model-based drug administration， mice underwent open-field， forced swimming， and elevated plus maze tests. After anesthesia with isoflurane， whole brains were collected from each group of mice， and hippocampi were dissected. Reactive oxygen species（ROS） level in hippocampal tissues was quantified by enzyme-linked immunosorbent assay（ELISA）. Hematoxylin-eosin（HE） staining was used to observe hippocampal tissue morphology. Immunofluorescence was performed to detect neuronal nuclei（NeuN） and peroxisome proliferator-activated receptor alpha（PPARα） expressions in hippocampal tissue. Then， pharmacodynamic evaluations were conducted to assess the effects of raw and vinegar-processed CRPV on mood disorders， exploring the potential mechanisms. ResultsVinegar processing caused significant changes in the chemical composition of CRPV， with 18 components showing increased relative content and 35 components showing decreased relative content. The primary changes occurred in flavonoid compounds， including 20 flavonoids， 20 flavonoid glycosides， 3 triterpenes， 3 phenolic acids， 1 alkaloid， and 6 other compounds. Twenty-one components were detected in blood（15 methoxyflavones， 4 flavonoid glycosides， and 2 phenolic acids）， with 17 shared between raw and vinegar-processed CRPV. Seven components reached hippocampal tissues（all common to both forms）. In regulating emotional disorders， Vinegar-processed CRPV exhibited superior antidepressant-like effects compared to raw products. HE staining revealed that both treatments improved hippocampal neuronal morphology， particularly in the damaged CA1 and CA3 regions. Immunofluorescence and ELISA analyses demonstrated that both raw and vinegar-processed CRPV significantly modulated NeuN and PPARα expressions in hippocampal tissue while alleviating oxidative stress induced by excessive ROS（P<0.05）. ConclusionThe chemical composition of CRPV undergoes changes after vinegar processing， but the migrating components in blood and hippocampus are primarily methoxyflavonoids. These components may serve as the potential material basis for activating the PPARα pathway， thereby negatively regulating ROS generation in the hippocampus， reducing oxidative stress， and promoting the development of NeuN-positive neurons. These findings provide experimental evidence for enhancing quality standards， pharmacodynamic material research， and active drug development of raw and vinegar-processed CRPV.

Objective:To construct and validate a prognostic model of colon cancer based on differentially expressed anoikis-related genes, and to preliminarily investigate the relationship between anoikis-related genes and the tumor immune microenvironment of colon cancer.Methods:A total of 472 cancer tissues samples of patients with colon cancer, RNA sequencing data and clinical data of 41 normal tissues samples were downloaded from the Cancer Genome Atlas (TCGA) database between the establishment time and July in 2024. A total of 919 genes related to anoikis were screened out from GeneCards database, and the common genes were selected from the RNA sequencing gene datasets of colon cancer and normal colon tissues in the TCGA database, among which the differentially expressed anoikis-related genes of colon cancer and normal colon tissues were screened out based on P < 0.05. Furthermore, genes related to the prognosis of 446 colon cancer patients with prognostic data in the TCGA database were screened by using univariate Cox proportional risk model; the genes with P < 0.05 were further screened out and a colon cancer prognosis model was constructed by using LASSO-Cox proportional risk model. The risk score of the above 446 colon cancer patients in the TCGA database was calculated according to the prognostic model, and the patients were divided into high-risk (≥ median value) group and low-risk (< median value) group according to the median risk score, and the overall survival of the 2 groups was analyzed by using the Kaplan-Meier method. The risk score based on R software-based time ROC program package was used to predict 1-year, 2-year, 3-year overall survival therapeutic efficacy of colon cancer patients in the TCGA database. According to the median risk score of colon cancer patients in the TCGA database, the patients in the International Cancer Genome Consortium (ICGC) database were divided into high-risk group and low-risk group. Kaplan-Meier method and receiver operating characteristic (ROC) curve were used to verify the predictive effect of the prognostic model. The differentially expressed genes between low-risk group and high-risk group stratified by prognostic model risk score in the TCGA database were used to perform single sample gene set enrichment analysis (ssGESA) of immune cells and immune function by using R software related programs. The differences in risk scores of patients with different immunophenotypes (including inflammator response type, wound healing type, interferon gamma dominant type and lymphocyte depletion type) were compared; and correlation analysis of infiltration and risk scores between immune cells and stromal cells in tumor microenvironment was made. Based on the tumor immune function and rejection (TIDE) database, the relationship between the prognostic model risk score and programmed death receptor ligand 1 (PD-L1) gene expression level was analyzed. Results:Based on anoikis-related genes in the GeneCards database, 236 differentially expressed anoikis-related genes between colon cancer tissues and normal tissues were obtained from the TCGA database. LASSO Cox regression was applied to establish a prognostic model constructed by 7 differentially expressed anoikis-related genes in cancer tissues and normal colon tissues related to the prognosis of colon cancer. Risk score = 0.366×TIMP1-0.404×NAT1+0.207×LTB4R2+0.075×INHBB+0.140×CD36-0.109×MMP3+2.994×OFCC1. The median risk score of 446 colon cancer patients in the TCGA database was 1.754 719 545. Survival analysis showed that the overall survival of colon cancer patients in high-risk group of the TCGA database was worse than that in low-risk group ( P < 0.001); ROC curve analysis showed that the area under the curve for predicting 1-year, 2-year and 3-year overall survival of patients in the TCGA database based on the prognostic model risk score was 0.705, 0.731 and 0.723, respectively. Kaplan-Meier method analysis showed that in the ICGC database, the overall survival of colon cancer patients in high-risk group was worse than that in low-risk group ( P = 0.041); ROC curve analysis showed that the area under the curve of prognostic model risk score for predicting 1-year and 2-year overall survival of colon cancer patients in the ICGC database was 0.663 and 0.966, respectively. ssGESA analysis showed that macrophage level in high-risk group was higher than that in low-risk group, helper T (Th) 1 cell and Th2 cell levels in high-risk group were lower than those in low-risk group (all P < 0.01). In terms of immune function, the cell killing activity and histocompatibility complex Ⅰ level in high-risk group were lower than those in low-risk group, and type Ⅱ interferon response score in high-risk group was higher than that in low-risk group (all P < 0.05). The analysis of immunophenotype showed that the risk score of inflammatory response type was higher than that of wound healing type ( P < 0.05), and there was no statistically significant difference in risk score between the other 2 types (all P > 0.05). Risk score was positively correlated with stromal cell infiltration score ( R = 0.340, P < 0.001) and immune cell infiltration score ( R = 0.148, P < 0.05); the expression level of PD-L1 in high-risk group was higher than that in low-risk group in the TCGA database ( P = 0.048), and the expression level of PD-L1 was positively correlated with risk score ( R = 0.130, P = 0.009). Conclusions:A prognostic model of colon cancer constructed by anoikis-related genes can better predict the prognosis of colon cancer patients, and anoikis-related genes may play an important role in tumor immunity of colon cancer.

ObjectiveTo investigate the effects of different fermentation methods and times on the fungal flora and chemical composition of Aurantii Fructus， in order to obtain the optimal fermentation conditions and flora structure， and to ensure the stability and controllability of the fermented varieties. MethodsScanning electron microscopy was used to observe and analyze the colony characteristics on the surface of Aurantii Fructus under different fermentation conditions. Internal transcribed spacer 2（ITS2） high-throughput sequencing， combined with fungal community diversity analysis and fungal community structure analysis， were used to obtain the fungal flora microbial categories of Aurantii Fructus under the conditions of traditional pressure-shelf fermentation and non-pressure-shelf natural fermentation for 7， 14， 21 d（numbered Y1-Y3 for the former， and numbered F1-F3 for the latter）， respectively. At the same time， the chemical components in the fermentation process were detected by ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）， combined with principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and compound retention time， parent ions， characteristic fragment ions and other information， the differential compounds between the different fermentation samples were screened and identified. ResultsThe analysis of fungal community diversity showed that the dominant flora did not change at different fermentation time points in the traditional pressure-shelf fermentation method， while in the non-pressure-shelf natural fermentation method， there was a significant difference with the fermentation process， and at the genus level， the dominant genus of samples Y1， Y2， Y3 and F2 was Aspergillus， while the dominant genera of samples F1 and F3 were both Rhizopus. This indicated that the microbial growth environment provided by the traditional fermentation method was more stable， and the microbial community structure was more stable， which was more conducive to the stable and controllable fermentation process and fermented products. A total of 155 compounds were identified by compositional analysis， including 70 flavonoids， 38 coumarins， 10 alkaloids， 34 organic acids and 3 other compounds. After fermentation， two new components of ribalinine and pranferin were produced. Different fermentation conditions also brought about differences in chemical composition， multivariate statistical analysis obtained 26 differential compounds under two different fermentation methods， mainly including flavonoids， organic acids and coumarins. Comprehensively， the microbial community structure of samples fermented by the traditional pressure-shelf method of Aurantii Fructus for 14 d was stable， the species richness was high and the overall content of differential compounds was high， which was the optimal processing condition. ConclusionCompared with non-pressure-shelf natural fermentation， the traditional method has obvious advantages in terms of the stability of the microbial community structure and the content of chemical compounds， and the optimal condition is 14 days of fermentation. This study is helpful to promote the quality stability and fermentation bioavailability of fermented products of Aurantii Fructus， as well as to provide an experimental basis for the further improvement of the quality control methods of this variety.

ObjectiveTo investigate the effects of different fermentation methods and times on the fungal flora and chemical composition of Aurantii Fructus， in order to obtain the optimal fermentation conditions and flora structure， and to ensure the stability and controllability of the fermented varieties. MethodsScanning electron microscopy was used to observe and analyze the colony characteristics on the surface of Aurantii Fructus under different fermentation conditions. Internal transcribed spacer 2（ITS2） high-throughput sequencing， combined with fungal community diversity analysis and fungal community structure analysis， were used to obtain the fungal flora microbial categories of Aurantii Fructus under the conditions of traditional pressure-shelf fermentation and non-pressure-shelf natural fermentation for 7， 14， 21 d（numbered Y1-Y3 for the former， and numbered F1-F3 for the latter）， respectively. At the same time， the chemical components in the fermentation process were detected by ultra-high performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）， combined with principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and compound retention time， parent ions， characteristic fragment ions and other information， the differential compounds between the different fermentation samples were screened and identified. ResultsThe analysis of fungal community diversity showed that the dominant flora did not change at different fermentation time points in the traditional pressure-shelf fermentation method， while in the non-pressure-shelf natural fermentation method， there was a significant difference with the fermentation process， and at the genus level， the dominant genus of samples Y1， Y2， Y3 and F2 was Aspergillus， while the dominant genera of samples F1 and F3 were both Rhizopus. This indicated that the microbial growth environment provided by the traditional fermentation method was more stable， and the microbial community structure was more stable， which was more conducive to the stable and controllable fermentation process and fermented products. A total of 155 compounds were identified by compositional analysis， including 70 flavonoids， 38 coumarins， 10 alkaloids， 34 organic acids and 3 other compounds. After fermentation， two new components of ribalinine and pranferin were produced. Different fermentation conditions also brought about differences in chemical composition， multivariate statistical analysis obtained 26 differential compounds under two different fermentation methods， mainly including flavonoids， organic acids and coumarins. Comprehensively， the microbial community structure of samples fermented by the traditional pressure-shelf method of Aurantii Fructus for 14 d was stable， the species richness was high and the overall content of differential compounds was high， which was the optimal processing condition. ConclusionCompared with non-pressure-shelf natural fermentation， the traditional method has obvious advantages in terms of the stability of the microbial community structure and the content of chemical compounds， and the optimal condition is 14 days of fermentation. This study is helpful to promote the quality stability and fermentation bioavailability of fermented products of Aurantii Fructus， as well as to provide an experimental basis for the further improvement of the quality control methods of this variety.

ObjectiveTo screen and evaluate the antidepressant compounds of Curcumae Rhizoma， and explore its mechanism of regulating the nuclear factor erythroid 2-related factor 2（Nrf2）/glutathione（GSH） peroxidase 4（GPX4）/GSH pathway from an antioxidant perspective. MethodsThe antioxidant activities in vitro of 11 characteristic components from Curcumae Rhizoma， including curcumol， curgerenone， curdione， curzerene， curcumenol， curcumenone， dehydrocurdione， isocurcumenol， furanodienone， furanodiene and zederone， were detected using 1，1-diphenyl-2-picrylhydrazyl（DPPH） and 2，2'-azinobis-（3-ethylbenzothiazoline-6-sulphonic acid） diammonium salt（ABTS） radical scavenging assays. The depression in Drosophila melanogaster was induced by chronic unpredictable mild stress（CUMS）， and W1118 wild-type male D. melanogaster were randomly divided into blank group， model group， curcumol group， curgerenone group， curdione group， curzerene group， curcumenol group，curcumenone group， dehydrocurdione group， isocurcumenol group， furanodienone group， furanodiene group， zederone group and fluoxetine group（10 μmol·L^-1）. The treatment groups received a dose of 0.1 g·L^-1 of 11 characteristic components from Curcumae Rhizoma， while the blank and model groups were administered equivalent volumes of solvent. The sucrose preference test， climbing test and forced swimming test were used to evaluate the behavioral indicators of depression in D. melanogaster. Liquid chromatography-mass spectrometry（LC-MS） was used to detect the levels of 5-hydroxytryptamine（5-HT） and dopamine（DA） in the brain of D. melanogaster， and the entropy weight method was used to comprehensively evaluate neurobehavioral and neurotransmitter indicators， resulting in the identification of the antidepressant active components of Curcumae Rhizoma. In addition， a mouse depression model was established by CUMS， and C57BL/6J mice were randomly divided into blank group， model group， low and high dose groups of curzerene（0.5， 1 mg·kg^-1）， and fluoxetine group（10 mg·kg^-1） to confirm the antidepressant effect of the optimal active ingredient by behavioral analysis. Flow cytometry was used to detect the content of reactive oxygen species（ROS） in the hippocampus of mice from each group. Enzyme-linked immunosorbent assay was used to detect the contents of adenosine triphosphate（ATP）， superoxide dismutase（SOD）， catalase（CAT） and GSH. Transmission electron microscope（TEM） was used to observe the effect of curzerene on the ultrastructure of mitochondria in hippocampal tissue. Western blot was performed to determine the level of Nrf2 protein， and Nrf2 inhibitor（ML385） was used to verify the relationship between the antidepressant effect of curzerene and regulation of Nrf2. Real time fluorescence quantitative polymerase chain reaction（Real-time PCR） was employed to detect the effect of curzerene on the mRNA expression level of GPX. ResultsIn vitro antioxidant experiments showed that curzerene and curgerenone exhibited the most significant ability to scavenge free radicals， and comprehensive evaluation results of entropy weight method indicated that curzerene stood out as the most promising active component. Compared with the blank group， the model group exhibited a significant decrease in sucrose preference coefficient and the number of times entering the open field center（P<0.01）， as well as a significant increase in immobility time in the forced swimming and tail suspension tests（P<0.01）， and the ROS content in hippocampus significantly elevated（P<0.01）， while the ATP content significantly reduced（P<0.01）. In the hippocampal neurons of the model group， mitochondrial cristae were disordered， with vacuolation of the inner membrane and severe damage. Nrf2 protein expression level in the model group was significantly decreased（P<0.05）， and the antioxidant enzymes SOD， CAT and GSH contents were also significantly reduced（P<0.05， P<0.01）， and the gene expression levels of GPX1， GPX4 and GPX7 were significantly decreased（P<0.01）. Compared with the model group， the high-dose group of curzerene showed a significant increase in the sucrose preference coefficient and the number of times entering the open field center（P<0.05）， as well as a significant decrease in immobility time in the forced swimming and tail suspension tests（P<0.05， P<0.01）. The ROS content in the hippocampus of the high-dose group of curzerene was significantly reduced（P<0.01）， while the ATP content was significantly increased（P<0.05）. The neuronal mitochondrial damage in the hippocampus of the high-dose group of curzerene was alleviated， and the expression level of Nrf2 protein was significantly increased（P<0.05）. The Nrf2 inhibitor ML385 reversed the improvement of curzerene on depressive behaviors in CUMS mice. The GSH content in the hippocampal neurons of the high-dose group of curzerene was significantly increased（P<0.01）， while there were no significant differences in SOD and CAT contents. The expression level of GPX4 gene in the hippocampal neurons of the high-dose group of curzerene was significantly increased（P<0.05）， while there were no significant differences in other GPX genes. ConclusionCurzerene is the best component with antidepressant activity in Curcumae Rhizoma. It may improve mitochondrial dysfunction to exert its antidepressant effect by regulating Nrf2 and its downstream GPX4/GSH pathway rather than CAT or SOD pathways.

Cerebral ischemia/reperfusion injury(CIRI)is a pathophysiological process affecting the prognosis of patients with acute ischemic stroke(AIS).Its mechanism is complex and remains unclear.Long non-coding RNA(LncRNA)are a class of non-coding RNA(ncRNA).Early studies of LncRNA focused on their relationship with tumor-related diseases,but recent studies have found that they are also closely related to the pathological process of CIRI.LncRNA participate in the damage and repair processes of CIRI by affecting oxidative stress,autophagy,and apoptosis of the nervous system,as well as the inflammatory response and other mechanisms.They can regulate the progression of CIRI in a positive or negative way,and they play an important role in the related signaling pathways.This review focuses on the mechanisms bv which LncRNA regulate CIRI.

Cerebral ischemia/reperfusion injury(CIRI)is a pathophysiological process affecting the prognosis of patients with acute ischemic stroke(AIS).Its mechanism is complex and remains unclear.Long non-coding RNA(LncRNA)are a class of non-coding RNA(ncRNA).Early studies of LncRNA focused on their relationship with tumor-related diseases,but recent studies have found that they are also closely related to the pathological process of CIRI.LncRNA participate in the damage and repair processes of CIRI by affecting oxidative stress,autophagy,and apoptosis of the nervous system,as well as the inflammatory response and other mechanisms.They can regulate the progression of CIRI in a positive or negative way,and they play an important role in the related signaling pathways.This review focuses on the mechanisms bv which LncRNA regulate CIRI.

Objective:To construct and validate a prognostic model of colon cancer based on differentially expressed anoikis-related genes, and to preliminarily investigate the relationship between anoikis-related genes and the tumor immune microenvironment of colon cancer.Methods:A total of 472 cancer tissues samples of patients with colon cancer, RNA sequencing data and clinical data of 41 normal tissues samples were downloaded from the Cancer Genome Atlas (TCGA) database between the establishment time and July in 2024. A total of 919 genes related to anoikis were screened out from GeneCards database, and the common genes were selected from the RNA sequencing gene datasets of colon cancer and normal colon tissues in the TCGA database, among which the differentially expressed anoikis-related genes of colon cancer and normal colon tissues were screened out based on P < 0.05. Furthermore, genes related to the prognosis of 446 colon cancer patients with prognostic data in the TCGA database were screened by using univariate Cox proportional risk model; the genes with P < 0.05 were further screened out and a colon cancer prognosis model was constructed by using LASSO-Cox proportional risk model. The risk score of the above 446 colon cancer patients in the TCGA database was calculated according to the prognostic model, and the patients were divided into high-risk (≥ median value) group and low-risk (< median value) group according to the median risk score, and the overall survival of the 2 groups was analyzed by using the Kaplan-Meier method. The risk score based on R software-based time ROC program package was used to predict 1-year, 2-year, 3-year overall survival therapeutic efficacy of colon cancer patients in the TCGA database. According to the median risk score of colon cancer patients in the TCGA database, the patients in the International Cancer Genome Consortium (ICGC) database were divided into high-risk group and low-risk group. Kaplan-Meier method and receiver operating characteristic (ROC) curve were used to verify the predictive effect of the prognostic model. The differentially expressed genes between low-risk group and high-risk group stratified by prognostic model risk score in the TCGA database were used to perform single sample gene set enrichment analysis (ssGESA) of immune cells and immune function by using R software related programs. The differences in risk scores of patients with different immunophenotypes (including inflammator response type, wound healing type, interferon gamma dominant type and lymphocyte depletion type) were compared; and correlation analysis of infiltration and risk scores between immune cells and stromal cells in tumor microenvironment was made. Based on the tumor immune function and rejection (TIDE) database, the relationship between the prognostic model risk score and programmed death receptor ligand 1 (PD-L1) gene expression level was analyzed. Results:Based on anoikis-related genes in the GeneCards database, 236 differentially expressed anoikis-related genes between colon cancer tissues and normal tissues were obtained from the TCGA database. LASSO Cox regression was applied to establish a prognostic model constructed by 7 differentially expressed anoikis-related genes in cancer tissues and normal colon tissues related to the prognosis of colon cancer. Risk score = 0.366×TIMP1-0.404×NAT1+0.207×LTB4R2+0.075×INHBB+0.140×CD36-0.109×MMP3+2.994×OFCC1. The median risk score of 446 colon cancer patients in the TCGA database was 1.754 719 545. Survival analysis showed that the overall survival of colon cancer patients in high-risk group of the TCGA database was worse than that in low-risk group ( P < 0.001); ROC curve analysis showed that the area under the curve for predicting 1-year, 2-year and 3-year overall survival of patients in the TCGA database based on the prognostic model risk score was 0.705, 0.731 and 0.723, respectively. Kaplan-Meier method analysis showed that in the ICGC database, the overall survival of colon cancer patients in high-risk group was worse than that in low-risk group ( P = 0.041); ROC curve analysis showed that the area under the curve of prognostic model risk score for predicting 1-year and 2-year overall survival of colon cancer patients in the ICGC database was 0.663 and 0.966, respectively. ssGESA analysis showed that macrophage level in high-risk group was higher than that in low-risk group, helper T (Th) 1 cell and Th2 cell levels in high-risk group were lower than those in low-risk group (all P < 0.01). In terms of immune function, the cell killing activity and histocompatibility complex Ⅰ level in high-risk group were lower than those in low-risk group, and type Ⅱ interferon response score in high-risk group was higher than that in low-risk group (all P < 0.05). The analysis of immunophenotype showed that the risk score of inflammatory response type was higher than that of wound healing type ( P < 0.05), and there was no statistically significant difference in risk score between the other 2 types (all P > 0.05). Risk score was positively correlated with stromal cell infiltration score ( R = 0.340, P < 0.001) and immune cell infiltration score ( R = 0.148, P < 0.05); the expression level of PD-L1 in high-risk group was higher than that in low-risk group in the TCGA database ( P = 0.048), and the expression level of PD-L1 was positively correlated with risk score ( R = 0.130, P = 0.009). Conclusions:A prognostic model of colon cancer constructed by anoikis-related genes can better predict the prognosis of colon cancer patients, and anoikis-related genes may play an important role in tumor immunity of colon cancer.

OBJECTIVE To investigate the effect of raw and wine-processed Schisandra chinensis on neuro-immune-endocrine network in insomnia mice and its mechanism. METHODS Fifty mice were randomly divided into blank group， model group， diazepam group， raw S. chinensis group and wine-processed S. chinensis group， with 10 mice in each group. Except for blank group， the mice in the other groups were intraperitoneally injected with thyroxine solution to establish mice model of insomnia； at the end of each day’s modeling， the corresponding doses of diazepam，raw and wine-processed S. chinensis were given by gavage. The blank group and model group were given constant volume of normal saline. The general state of the mice was observed and recorded， and the total activity distance and upright times of the mice were detected； the EEG and EMG signals of mice were recorded， and the time ratio of sleep wake time （wake）， non-rapid eye movement （NREM） and rapid eye movement （REM） was analyzed； the contents of neurotransmitters [γ-aminobutyric acid （GABA）， 5-hydroxytryptamine （5-HT）， dopamine （DA）， norepinephrine （NE）， cortisol （CORT）] in brain suprachiasmatic nucleus （SCN） were detected； and the expressions of tumor necrosis factor α （TNF-α） and interleukin 1β （IL-1β） were detected； the mRNA expressions of clock gene Bmal1， circadian clock gene Clock and cycle gene Per2 were all detected. RESULTS Compared with the blank group， the mental state of the model group mice was relatively depressed， the amount of food and water increased， the body mass decreased， the hair was rough and shiny， and the circadian rhythm was irregular； the total activity distance and upright times decreased significantly； the time ratio of wake increased significantly， while the time ratios of REM and NREM decreased significantly； the content of 5- HT in brain SCN decreased significantly， while the content of NE， DA and CORT increased significantly； the fluorescence intensity of IL-1β and TNF-α was significantly increased； the relative expression level of Bmal1 and Clock mRNA was significantly increased， while the relative expression level of Per2 mRNA was significantly decreased （P＜0.05 or P＜0.01）. Compared with the model group， the general state of mice in diazepam group， raw S. chinensis group and wine-processed S. chinensis group was improved obviously， and most of the above index levels were significantly reversed （P＜0.05 or P＜0.01）. CONCLUSIONS Raw and wine-processed S. chinensis have a certain therapeutic effect on insomnia mice， the mechanism of which may be related to the regulation of neuro-endocrine-immune system related biological indicators in insomnia mice.