Objective: To explore the relationship of family function with sleep and externalizing problem behaviors of preschool children, so as to provide a guidance for externalizing problem prevention and intervention among preschool children. Methods: From October 2023 to January 2024, a convenience sampling method was used to select 5 138 preschool children from kindergartens in 8 districts of Wuhan City, Hubei Province. Parents completed the survey for Family Adaptability and Cohesion Scale, children s sleep habits and Child Behavior Checklist (CBCL). Spearman correlation analysis was used to examine the correlation of family function with scores of sleep quality and externalizing problem behaviors among preschool children. A mediation model analysis and bootstrap test were conducted to further investigate the mediating role of sleep quality between family function and externalizing problem behaviors. Mplus 8.7 software was used for latent profile analysis of family function. Results: The reported rates of poor sleep quality and externalizing problem behaviors among preschool children were 11.8% ( n =607), 20.0% ( n =1 026). The relevant analysis results showed that family function was negatively correlated with sleep quality and externalizing problem behaviors ( r = -0.20, -0.23), and sleep quality was positively correlated with externalizing problem behaviors ( r =0.27) ( P <0.01). The mediation effect test showed that family function negatively predicted externalizing problem behaviors ( β =-0.079) and sleep quality ( β = -0.075), while sleep quality positively predicted externalizing problem behaviors ( β =0.215) ( P <0.01). The latent profile analysis results showed that family function could be classified into 4 categories: high family function group (23.01%), upper middle family function group (44.65%), moderate family function group (26.24%) and low family function group (6.11%). Compared to high family function, the other three categories significantly positively predicted externalizing problem behaviors, and the mediating effects of sleep quality on different categories of family function were statistically significant [upper middle family function: mediation effect value was 0.022 (95% CI =0.004-0.041) and direct effect value was 0.329 (95% CI =0.263-0.396); middle family function: mediation effect value was 0.087 (95% CI =0.063-0.115) and direct effect value was 0.491 (95% CI =0.416-0.565); low family function: mediation effect value was 0.144 (95% CI =0.107-0.185) and direct effect 0.621 (95% CI =0.503-0.740)] ( P < 0.05 ). Conclusion Family function negatively predicts the externalizing problem behaviors of preschool children, and sleep quality plays a partial mediating role.

ObjectiveTo study the changing law of appearance color and physicochemical properties of Angelicae Sinensis Radix Carbonisata（ASRC） during the processing by color space method combined with statistical analysis， so as to provide reference for determining the processing endpoint and evaluating the quality of the decoction pieces. MethodsTaking processing time（4， 8， 12， 16 min） and temperature（180， 200， 220， 240 ℃） as factors， ASRC decoction pieces with different processing degrees were prepared in a completely randomized design. Then， the brightness value（L^*）， red-green value（a^*）， yellow-blue value（b^*）， and total chromaticity value （E^*ab） of the decoction pieces were determined by spectrophotometer， the color difference value（ΔE） was calculated， and the data of colorimetric values were analyzed by discriminant analysis. At the same time， the pH， charcoal adsorption， and contents of tannins， 5-hydroxymethylfurfural（5-HMF）， tryptophan， chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H and ligustilide of ASRC with different processing degrees were determined by pH meter， ultraviolet and visible spectrophotometry and ultra-high performance liquid chromatography（UPLC）. Principal component analysis（PCA） was used to analyze the data of physicochemical indexes， after determining the processing technology of ASRC， the canonical discriminant function was established to distinguish the decoction pieces with different processing degrees， and leave-one-out cross validation was conducted. Finally， Pearson correlation analysis was used to explore the correlation between various physicochemical indexes and chromaticity values. ResultsWith the prolongation of the processing time， L^*， a^*， b^* and E^*ab all showed a decreasing trend， and the established discriminant model based on color parameters was able to distinguish ASRC with different processing degrees. The pH showed an increasing trend with the prolongation of processing time， and the charcoal adsorption， and the contents of tannins， 5-HMF， and tryptophan all showed an increasing and then decreasing trend. Among them， the charcoal adsorption， contents of tannin and 5-HMF reached their maximum values successively after processing for 8-12 min. While the contents of chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H and ligustilide decreased with the increase of processing time， with a decrease of 60%-80% at 8 min of processing. Therefore， the optimal processing time should be determined to be 8-12 min. PCA could clearly distinguish ASRC with different processing degrees， while temperature had no significant effect on the processing degree. The 12 batches of process validation results（10 min， 180-240 ℃） showed that except for 3 batches identified as class Ⅱ light charcoal， all other batches were identified as class Ⅲ standard charcoal， and the chromaticity values of each batch of ASRC were within the reference range of class Ⅱ-Ⅲ sample chromaticity values. The correlation analysis showed that the chromaticity values were negatively correlated with pH and charcoal adsorption， and positively correlated with contents of tryptophan， chlorogenic acid， ferulic acid， senkyunolide I， senkyunolide H， and ligustilide. And both pH and charcoal adsorption were negatively correlated with the contents of the above components， but the charcoal adsorption was positively correlated with the content of 5-HMF. ConclusionThe chromaticity values and the contents of various physicochemical indicators of ASRC undergo significant changes with the prolongation of processing time， and there is a general correlation between chromaticity values and various physicochemical indicators. Based on the changes in color and physicochemical indicators， the optimal processing time for ASRC is determined to be 8-12 min. This study reveals the dynamic changes of the relevant indexes in the processing of ASRC， which can provide a reference for the discrimination of the processing degree and the quantitative study of the processing endpoint.

ObjectiveTo establish a method for the identification of Haliotidis Concha and its counterfeits， and to improve its quality evaluation method. MethodsA total of 17 batches of Haliotis discus hannai， 4 batches of H. ruber， 3 batches of H. laevigata， 3 batches of H. ovina， 3 batches of H. diversicolor， 3 batches of H. asinina， 3 batches of H. iris were collected. Ultra-high performance liquid chromatography-quadrupole/electrostatic field orbitrap high-resolution mass spectrometry（UPLC-Q-Exactive-Orbitrap-MS/MS） was used to analyze the hydrolysates of different original Haliotidis Concha and its counterfeits， and the potential characteristic ions of each species were screened by Venn diagram. UPLC-triple quadrupole tandem mass spectrometry（UPLC-QqQ-MS/MS） was used to validate the characteristic ions， and the specific detection method of the characteristic ions was established. ResultsA total of 1 182， 167， 47， 89， 104， 203， 424 potential characteristic ions were screened from H. discus hannai， H. ruber， H. laevigata， H. ovina， H. diversicolor， H. asinina and H. iris， respectively. And 9 characteristic ions were selected. The precision， stability and repeatability of the 9 characteristic ions in the established identification method met the requirements. Different original Haliotidis Concha and its counterfeits could detect their own characteristic ions， including m/z 631.83-886.48（double charge） and m/z 631.83-443.74（double charge） of H. discus hannai， m/z 699.28-232.11（double charge） and m/z 699.28-544.27（double charge） of H. ruber， m/z 535.76-752.37（double charge） and m/z 535.76-548.28（double charge） of H. laevigata， m/z 708.35-442.28（double charge） and m/z 708.35-215.14（double charge） of H. ovina， m/z 561.33-614.86（triple charge）， m/z 561.33-468.28（triple charge）， m/z 608.29-618.32（double charge） and m/z 608.29-390.21（double charge） of H. diversicolor， m/z 769.85-274.10（double charge）， m/z 769.85-532.75（double charge）， m/z 827.43-646.36（single charge）， m/z 827.43-257.12（single charge） of H. asinina， and m/z 468.24-576.29（double charge） and m/z 468.24-505.26（double charge） of H. iris. ConclusionIn this study， a total of 9 characteristic ions are screened from 6 kinds of original Haliotidis Concha and its counterfeits， and a specific identification method is established， which is helpful to solve the limitations of the existing quality evaluation methods of Haliotidis Concha， and provide a basis for the production， circulation and medication quality.

ObjectiveTo establish a method for the identification of Haliotidis Concha and its counterfeits， and to improve its quality evaluation method. MethodsA total of 17 batches of Haliotis discus hannai， 4 batches of H. ruber， 3 batches of H. laevigata， 3 batches of H. ovina， 3 batches of H. diversicolor， 3 batches of H. asinina， 3 batches of H. iris were collected. Ultra-high performance liquid chromatography-quadrupole/electrostatic field orbitrap high-resolution mass spectrometry（UPLC-Q-Exactive-Orbitrap-MS/MS） was used to analyze the hydrolysates of different original Haliotidis Concha and its counterfeits， and the potential characteristic ions of each species were screened by Venn diagram. UPLC-triple quadrupole tandem mass spectrometry（UPLC-QqQ-MS/MS） was used to validate the characteristic ions， and the specific detection method of the characteristic ions was established. ResultsA total of 1 182， 167， 47， 89， 104， 203， 424 potential characteristic ions were screened from H. discus hannai， H. ruber， H. laevigata， H. ovina， H. diversicolor， H. asinina and H. iris， respectively. And 9 characteristic ions were selected. The precision， stability and repeatability of the 9 characteristic ions in the established identification method met the requirements. Different original Haliotidis Concha and its counterfeits could detect their own characteristic ions， including m/z 631.83-886.48（double charge） and m/z 631.83-443.74（double charge） of H. discus hannai， m/z 699.28-232.11（double charge） and m/z 699.28-544.27（double charge） of H. ruber， m/z 535.76-752.37（double charge） and m/z 535.76-548.28（double charge） of H. laevigata， m/z 708.35-442.28（double charge） and m/z 708.35-215.14（double charge） of H. ovina， m/z 561.33-614.86（triple charge）， m/z 561.33-468.28（triple charge）， m/z 608.29-618.32（double charge） and m/z 608.29-390.21（double charge） of H. diversicolor， m/z 769.85-274.10（double charge）， m/z 769.85-532.75（double charge）， m/z 827.43-646.36（single charge）， m/z 827.43-257.12（single charge） of H. asinina， and m/z 468.24-576.29（double charge） and m/z 468.24-505.26（double charge） of H. iris. ConclusionIn this study， a total of 9 characteristic ions are screened from 6 kinds of original Haliotidis Concha and its counterfeits， and a specific identification method is established， which is helpful to solve the limitations of the existing quality evaluation methods of Haliotidis Concha， and provide a basis for the production， circulation and medication quality.

ObjectiveTo explore the mechanisms associated with Mahoniae Caulis alkaloids （MA） in ameliorating depression by network pharmacology， molecular docking， and animal experiments. MethodsThe component targets of MA were obtained through Swiss Target Prediction and TCMIP database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. Protein-protein interaction （PPI） network was constructed by protein interaction analysis （STRING） database. Gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed through Bioinformatics （DAVID） database. The docking of components and targets was performed by AGFR. The mouse model of depression was established by intraperitoneal injection of corticosterone （CORT） once a day for 35 consecutive days. Sixty mice were randomly allocated into control （0.9% normal saline）， model （CORT， 20 mg·kg^-1）， positive control （fluoxetine hydrochloride， 3.6 mg·kg^-1）， and MA （10， 5， and 2.5 mg·kg^-1） groups. Each group was administrated with corresponding medicine or normal saline once a day for 28 consecutive days. The depression-like behavior of mice was observed. The pathological changes of prefrontal cortex in mice were observed by hematoxylin-eosin staining. Terminal deoxynucleotidyl dUTP transferase nick end labeling （TUNEL） was employed to observe the apoptosis of neurons in the prefrontal cortex. Enzyme-linked immunosorbent assay was employed to assess the serum levels of brain-derived neurotrophic factor （BDNF）， dopamine （DA）， 5-hydroxytryptamine （5-HT）， and norepinephrine （NE） in mice. The mRNA levels of cyclic adenosine monophosphate （cAMP） pathway-related factors and inflammatory factors were determined by Real-time PCR. Western blot was employed to determine the expression of cAMP pathway-related factors and connexin 43 （Cx43）. ResultsA total of 434 component targets and 545 depression targets were obtained， including 84 common targets， among which 10 core targets were screened out. GO analysis predicted 34 biological processes， 15 cell components， and 11 molecular functions. The KEGG pathways were mainly related to gap junction and cAMP signaling pathway. The core components had good binding affinity with the core targets. The results of animal experiments showed that compared with the control group， CORT prolonged the immobility time of mice in forced swimming and tail suspension tests （P<0.01）， lowered the serum levels of NE， BDNF， and 5-HT （P<0.05）， up-regulated the mRNA levels of nuclear factor-κB （NF-κB） and interleukin-6 （IL-6） in the brain tissue （P<0.05）， and down-regulated the mRNA levels of cyclic adenosine monophosphate effector binding protein （CREB） and BDNF （P<0.05） and the protein levels of protein kinase （PRKACA）， phosphorylation （p）-CREB/CREB， BDNF， and Cx43 （P<0.05） in the brain tissue. Compared with the model group， high-dose MA reduced the immobility time of mice in forced swimming （P<0.05） and tail suspension （P<0.01） tests， raised the serum levels of NE， BDNF， and 5-HT （P<0.01）， down-regulated the mRNA level of NF-κB （P<0.01）， and up-regulated the mRNA level of BDNF （P<0.01） and protein levels of PRKACA， p-CREB/CREB， BDNF， and Cx43 （P<0.05）. ConclusionMA alleviates the CORT-induced depressive behavior of mice. It may play an antidepressant role by regulating cAMP signaling pathway and gap junction pathway， improving synaptic plasticity and gap junction function， and reducing neuroinflammation.

ObjectiveTo explore the mechanisms associated with Mahoniae Caulis alkaloids （MA） in ameliorating depression by network pharmacology， molecular docking， and animal experiments. MethodsThe component targets of MA were obtained through Swiss Target Prediction and TCMIP database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. The depression targets were collected through TCMIP， Genecards， HPO， DrugBank and OMIM database. Protein-protein interaction （PPI） network was constructed by protein interaction analysis （STRING） database. Gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses were performed through Bioinformatics （DAVID） database. The docking of components and targets was performed by AGFR. The mouse model of depression was established by intraperitoneal injection of corticosterone （CORT） once a day for 35 consecutive days. Sixty mice were randomly allocated into control （0.9% normal saline）， model （CORT， 20 mg·kg^-1）， positive control （fluoxetine hydrochloride， 3.6 mg·kg^-1）， and MA （10， 5， and 2.5 mg·kg^-1） groups. Each group was administrated with corresponding medicine or normal saline once a day for 28 consecutive days. The depression-like behavior of mice was observed. The pathological changes of prefrontal cortex in mice were observed by hematoxylin-eosin staining. Terminal deoxynucleotidyl dUTP transferase nick end labeling （TUNEL） was employed to observe the apoptosis of neurons in the prefrontal cortex. Enzyme-linked immunosorbent assay was employed to assess the serum levels of brain-derived neurotrophic factor （BDNF）， dopamine （DA）， 5-hydroxytryptamine （5-HT）， and norepinephrine （NE） in mice. The mRNA levels of cyclic adenosine monophosphate （cAMP） pathway-related factors and inflammatory factors were determined by Real-time PCR. Western blot was employed to determine the expression of cAMP pathway-related factors and connexin 43 （Cx43）. ResultsA total of 434 component targets and 545 depression targets were obtained， including 84 common targets， among which 10 core targets were screened out. GO analysis predicted 34 biological processes， 15 cell components， and 11 molecular functions. The KEGG pathways were mainly related to gap junction and cAMP signaling pathway. The core components had good binding affinity with the core targets. The results of animal experiments showed that compared with the control group， CORT prolonged the immobility time of mice in forced swimming and tail suspension tests （P<0.01）， lowered the serum levels of NE， BDNF， and 5-HT （P<0.05）， up-regulated the mRNA levels of nuclear factor-κB （NF-κB） and interleukin-6 （IL-6） in the brain tissue （P<0.05）， and down-regulated the mRNA levels of cyclic adenosine monophosphate effector binding protein （CREB） and BDNF （P<0.05） and the protein levels of protein kinase （PRKACA）， phosphorylation （p）-CREB/CREB， BDNF， and Cx43 （P<0.05） in the brain tissue. Compared with the model group， high-dose MA reduced the immobility time of mice in forced swimming （P<0.05） and tail suspension （P<0.01） tests， raised the serum levels of NE， BDNF， and 5-HT （P<0.01）， down-regulated the mRNA level of NF-κB （P<0.01）， and up-regulated the mRNA level of BDNF （P<0.01） and protein levels of PRKACA， p-CREB/CREB， BDNF， and Cx43 （P<0.05）. ConclusionMA alleviates the CORT-induced depressive behavior of mice. It may play an antidepressant role by regulating cAMP signaling pathway and gap junction pathway， improving synaptic plasticity and gap junction function， and reducing neuroinflammation.

OBJECTIVES: Recent evidence suggests that the gut may be a primary site of metformin action. However, studies on the effects of metformin on gut microbiota remain limited, and its impact on gut microbial metabolites such as short-/medium-chain fatty acids is unclear. This study aims to investigate the effects of metformin on gut microbiota, short-/medium-chain fatty acids, and associated metabolic benefits in high-fat diet rats. METHODS: Twenty-four Sprague-Dawley rats were randomly divided into 3 groups: 1) Normal diet group (ND group), fed standard chow; 2) high-fat diet group (HFD group), fed a high-fat diet; 3) high-fat diet + metformin treatment group (HFD+Met group), fed a high-fat diet for 8 weeks, followed by daily intragastric administration of metformin solution (150 mg/kg body weight) starting in week 9. At the end of the experiment, all rats were sacrificed, and serum, liver, and colonic contents were collected for assessment of glucose and lipid metabolism, liver pathology, gut microbiota composition, and the concentrations of short-/medium-chain fatty acids. RESULTS: Metformin significantly improved HFD-induced glucose and lipid metabolic disorders and liver injury. Compared with the HFD group, the HFD+Met group showed reduced abundance of Blautia, Romboutsia, Bilophila, and Bacteroides, while Lactobacillus abundance significantly increased (all P<0.05). Colonic contents of butyric acid, 2-methyl butyric acid, valeric acid, octanoic acid, and lauric acid were significantly elevated (all P<0.05), whereas acetic acid, isoheptanoic acid, and nonanoic acid levels were significantly decreased (all P<0.05). Spearman correlation analysis revealed that Lactobacillus abundance was negatively correlated with body weight gain and insulin resistance, while butyrate and valerate levels were negatively correlated with insulin resistance and liver injury (all P<0.05). CONCLUSIONS Metformin significantly increases the abundance of beneficial bacteria such as Lactobacillus and promotes the production of short-/medium-chain fatty acids including butyric, valeric, and lauric acid in the colonic contents of HFD rats, suggesting that metformin may regulate host metabolism through modulation of the gut microbiota.
Animals ; Metformin/pharmacology* ; Rats, Sprague-Dawley ; Diet, High-Fat/adverse effects* ; Rats ; Gastrointestinal Microbiome/drug effects* ; Male ; Fatty Acids, Volatile/metabolism* ; Fatty Acids/metabolism*

To study the clinical correlation between fasting plasma glucose, lipid metabolism, prostate-specific antigen and prostate volume in patients with benign prostatic hyperplasia, and to explore the combined effect as diagnostic indicators. A total of 108 patients with benign prostatic hyperplasia treated in Beijing University of Chinese Medicine Third Affiliated Hospital from June 2021 to March 2023 were retrospectively analyzed as the hyperplasia group, and 98 healthy physical examination personnel were selected as the control group during the same period. Compare the differences in levels of fasting plasma glucose (FPG), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), small and dense low-density lipoprotein cholesterol (sdLDL-C), homocysteine, lipoprotein a (LPa), prostate specific antigen (PSA), and free prostate specific antigen (fPSA) between two groups of patients. Using Pearson analysis method to analyze the correlation between the above indicators and the size of prostate volume in patients with benign prostatic hyperplasia; using multiple linear regression to analyze the influencing factors of prostate volume enlargement; draw receiver operating characteristic (ROC) curves and analyze the application value of individual and combined detection of HDL, FPG, PSA, and fPSA. The results showed that there were significant differences in HDL, FPG, PSA, and fPSA levels between the control group and the proliferative group( P<0.05). The size of prostate volume is negatively correlated with HDL( r=-0.183, P<0.05) and positively correlated with FPG ( r=0.202, P<0.05), PSA( r=0.412, P<0.05), and fPSA( r=0.425, P<0.05). The results of multiple linear regression analysis showed that HDL( P=0.000), FPG( P=0.048), PSA( P=0.044), and fPSA ( P=0.012) were risk factors for increased volume of benign prostatic hyperplasia; ROC curve analysis shows that the AUC of HDL, FPG, PSA, and fPSA combined detection is 0.823, which is better than individual detection. In conclusion,HDL, FPG, PSA, fPSA has close correlation with hyperplasia of prostate, the joint detection may has better prediction for benign prostatic hyperplasia.

To study the clinical correlation between fasting plasma glucose, lipid metabolism, prostate-specific antigen and prostate volume in patients with benign prostatic hyperplasia, and to explore the combined effect as diagnostic indicators. A total of 108 patients with benign prostatic hyperplasia treated in Beijing University of Chinese Medicine Third Affiliated Hospital from June 2021 to March 2023 were retrospectively analyzed as the hyperplasia group, and 98 healthy physical examination personnel were selected as the control group during the same period. Compare the differences in levels of fasting plasma glucose (FPG), total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), small and dense low-density lipoprotein cholesterol (sdLDL-C), homocysteine, lipoprotein a (LPa), prostate specific antigen (PSA), and free prostate specific antigen (fPSA) between two groups of patients. Using Pearson analysis method to analyze the correlation between the above indicators and the size of prostate volume in patients with benign prostatic hyperplasia; using multiple linear regression to analyze the influencing factors of prostate volume enlargement; draw receiver operating characteristic (ROC) curves and analyze the application value of individual and combined detection of HDL, FPG, PSA, and fPSA. The results showed that there were significant differences in HDL, FPG, PSA, and fPSA levels between the control group and the proliferative group( P<0.05). The size of prostate volume is negatively correlated with HDL( r=-0.183, P<0.05) and positively correlated with FPG ( r=0.202, P<0.05), PSA( r=0.412, P<0.05), and fPSA( r=0.425, P<0.05). The results of multiple linear regression analysis showed that HDL( P=0.000), FPG( P=0.048), PSA( P=0.044), and fPSA ( P=0.012) were risk factors for increased volume of benign prostatic hyperplasia; ROC curve analysis shows that the AUC of HDL, FPG, PSA, and fPSA combined detection is 0.823, which is better than individual detection. In conclusion,HDL, FPG, PSA, fPSA has close correlation with hyperplasia of prostate, the joint detection may has better prediction for benign prostatic hyperplasia.

Objective:To establish the HPLC fingerprint of Bolbostemmatis Rhizoma standard decoction; To determine the three effective components with similar structure by quantitative analysis of multi-components by single marker (QAMS); To evaluate the quality of Bolbostemmatis Rhizoma standard decoction.Methods:HPLC was adopted to establish the fingerprints of 15 batches of Bolbostemmatis Rhizoma standard decoction. The Chromatographic column was Waters XBridge Phenyl (4.6 mm×250 mm, 5 μm). The mobile phase was acetonitrile-0.1% phosphoric acid solution with gradient elution. Cluster analysis (HCA) and principal component analysis (PCA) were conducted based on the relative peak area of common peaks. The same method as the fingerprint was used to establish QAMS of tubeimoside A, B, C on Bolbostemmatis Rhizoma standard decoction.Results:There were 14 common peaks in the fingerprint of Bolbostemmatis Rhizoma standard decoction. It was confirmed that the peak 3 was L-tryptophan, the peak 11 was tubeimoside B, the peak 12 was tubeimoside C, and the peak 13 was tubeimoside A. 15 batches of Bolbostemmatis Rhizoma standard decoction from different origins were divided into 3 categories by HCA and PCA. There was no significant difference between QAMS and the external standard method (ESM) through the system suitability inspection. Conclusion:This method is accurate, reliable and has good specificity, which can effectively evaluate the quality of Bolbostemmatis Rhizoma standard decoction.