ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

Objective:To standardize the management of auditory hallucination symptoms in inpatients with mental illness and develop an expert consensus on the management of auditory hallucinations in hospitalized psychiatric patients.Methods:From March 2023 to July 2023, the Mental Health Committee of the Chinese Nursing Association focused on the key issues in the management of auditory hallucinations symptoms in inpatients with mental illness, based on clinical practice, using literature analysis combined with the work experience of mental health experts, and formed the first draft of the expert consensus on the management of auditory hallucinations in inpatients with mental illness (hereinafter referred to as the consensus). Through 3 rounds of expert consultation and 3 rounds of expert demonstration meeting, the draft was adjusted, revised, and improved.Results:37 experts were included in the Delphi expert consultation, 1 male and 36 females with 39-67(51.48 ± 6.61) years old. The positive coefficients of experts in 3 rounds of Delphi expert consultations were all 100%, and the degrees of expert authority were 0.924, 0.938 and 0.949, respectively. The average importance value of each item was higher than 4.00, the variation coefficient of each item was less than 0.25. The Kendall harmony coefficient of the experts were 0.179, 0.195 and 0.198, respectively (all P<0.05). There were 15, 12, 12 experts in the first, seeond, third rounds of expert demonstration meeting. Finally, a consensus was reached on the recommendation of 4 parts, included auditory hallucination assessment, management format, symptom management implementation, and precautions. Conclusions:The consensus covers all parts of the management of auditory hallucination symptoms in hospitalized patients with mental disorders, which is practical and scientific. It is helpful to guide mental health professionals to standardize the management of auditory hallucination symptoms, improve the quality of nursing and ensure the safety of patients.

Objective:To understand the serotype distribution, drug resistance and molecular characterization of invasive non-typhoid Salmonella (iNTS) in Guangdong Province from 2018 to 2022 and provide scientific evidence for the prevention and treatment of blood flow infection caused by Salmonella. Methods:Serological identification, antimicrobial susceptibility testing, multilocus sequence typing (MLST), and whole genome sequencing were performed on Salmonella isolated from blood and stool samples in Guangdong from 2018 to 2022. Simultaneously, annotated the sequencing results for drug resistance genes and virulence factors by a microbial gene annotation system. Results:The 136 iNTS strains were divided into 25 serotypes, and Salmonella enteritidis accounted for 38.24% (52/136). The OR of other iNTS serotypes were calculated with Salmonella typhimurium as the control. The OR values of Oreninburg, Rysson, and Pomona serotypes were the highest, which were 423.50, 352.92, and 211.75, respectively. The drug resistance rate of iNTS was 0.74%-66.91%, which was lower than that of non-iNTS (3.90%-77.21%). The main iNTS of drug resistance were ampicillin and tetracycline, with resistance rates of 66.91% (91/136) and 50.00% (68/136), respectively, while the resistance rates to ciprofloxacin (5.88%,8/136), ceftazidime (5.88%,8/136), gentamicin (5.13%,7/136) and cefoxitin (0.74%, 1/136) were relatively low. iNTS carried a variety of drug-resistance genes and virulence factors, but no standard virulence factor distribution has been found. MLST cluster analysis showed that iNTS was divided into 26 sequence types, and ST11 accounted for 38.24% (52/136). Conclusions:The iNTS strains in Guangdong were dominated by Salmonella enteritidis, of which three serotypes, Oreninburg, Rison, and Pomona, may be associated with a higher risk of invasive infection during 2018 to 2022 . iNTS was sensitive to clinical first-line therapeutic drugs (cephalosporins and fluoroquinolones), with highly diverse sequences and clear phylogenetic branches. ST11 was the local dominant clone group.

ObjectiveTo determine the pharmacodynamic substance basis of Epimedii Folium（EF） and Epimedii Wushanensis Folium（EWF） in promoting osteogenic differentiation， and to establish a method to analyze the material basis of Chinese materia medica based on the correlation between chemical fingerprint and cellular metabolomics. MethodThe chemical fingerprints of 15 batches of EF with 4 species and 3 batches of EWF were analyzed by ultra performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry（UPLC-Q-Exactive Orbitrap-MS）， and partial least squares-discriminant analysis（PLS-DA） was used to analyze the peak areas of chemical fingerprints of samples. The effects of different samples on proliferative activity of MC3T3-E1 osteoblast precursors， as well as the activity of alkaline phosphatase（ALP） in osteoblasts were detected by cell counting kit-8（CCK-8） and enzyme-linked immunosorbent assay（ELISA）. At the same time， UPLC-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was used to analyze the effects of different samples on the metabolomics of MC3T3-E1 cells， then metabolic peak table of osteogenic differentiation cells was constructed， and pharmacodynamic index mean Y₀ was introduced into the peak table. PLS was used to calculate mean Y₀ of each group， and the mean Y₀ was added to the peak table of chemical fingerprint to construct the correlation between chemical fingerprint and cell metabolome， the pharmacodynamic components of EF and EWF that promote bone differentiation were screened according to variable importance in the projection（VIP） value>1. The pharmacodynamic effects of EF and EWF were evaluated according to the mean Y₀ of each group. ResultThe chemical fingerprints of EF with different origins and EWF were completely separated. Compared with the blank group， the activity of MC3T3-E1 cells in EF and EWF groups was significantly increased， the activity of ALP in the Epimedium brevicornu（Gansu province）， E. koreanum and E. pubescens groups was significantly increased（P<0.05）. The results of cell metabolomics showed that the blank group and the model group had an obvious trend of separation. EF with different origins and EWF had different distance from the model group， indicating that EF with different origins and EWF had different effect on promoting osteogenic differentiation. Chemical fingerprint-cell metabolomics integration analysis screened 9 components closely related to the efficacy of EF and EWF， including diphylloside B， epimedin C， icariin， baohuoside Ⅰ， yinyanghuo B， β-anhydroicaritin， magnoflorine， cryptochlorogenic acid and quercetin. E. koreanum had the strongest effect on promoting osteogenic differentiation. ConclusionThis study determined that the material basis of EF and EWF promoting osteogenic differentiation were mostly flavonoids， alkaloids and organic acids， which provided ideas and methods for the screening of pharmacodynamic components and the prediction of therapeutic effect of Chinese materia medica.