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 explore the associations of moderate to vigorous intensity physical activity (MVPA) and sedentary behavior (SB) among primary and secondary school students and their parents, so as to provide a scientific basis for formulating targeted physical activity promotion strategies for children and adolescents. Methods: From 2021 to 2022, basic information and 24 h movement behaviors of 2 484 pairs of students and their parents were collected from five primary and secondary schools in Haizhu District, Guangzhou City, with a convenient sampling combining with cluster sampling method. Component regression models were constructed to analyze the relationship between parental MVPA, SB and primary and secondary school students MVPA and SB, and a component isochronous substitution model was used to explore the effects of mutual substitution between parental MVPA, residual components (time use components other than SB during the 24 h period), and SB on the behavioral activities of MVPA and SB in primary and secondary school students. Results: Parental MVPA and SB of students in grade 1 to 3 were positively correlated with both students MVPA and SB ( β=0.06, 0.12, P <0.01). The component isochronous substitution model showed that substituting 10 and 20 minutes of MVPA for SB by parents in grade 1 to 3 was associated with an increase in MVPA of students, and substituting 10 and 20 minutes of residual ingredients for SB was associated with a decrease in SB of students, with mean changes of 0.8 (95% CI =0.4-1.2) and 1.4 (95% CI =0.7-2.2) and -1.4 (95% CI =-1.7 to -1.1) and -2.9 (95% CI =-3.4 to -2.3)( P <0.05). No statistically significant associations were observed between parents of students in grades 4 to 6 and 7 to 9 and students physical activity and sedentary behaviour ( P >0.05). Conclusions Parents of students in grades 1 to 3 increases MVPA and decrease SB are beneficial to increase MVPA and decrease SB of students. Parents could promote physical activity among primary and secondary school students, and the intervention gateway should be advanced, with the low grades as the optimal intervention period.

ObjectiveTo develop a predictive model and application for spontaneous passage of common bile duct stones using automated machine learning algorithms given the complexity of treatment decision-making for patients with common bile duct stones， and to reduce unnecessary endoscopic retrograde cholangiopancreatography （ERCP） procedures. MethodsA retrospective analysis was performed for the data of 835 patients who were scheduled for ERCP after a confirmed diagnosis of common bile duct stones based on imaging techniques in Changshu First People’s Hospital （dataset 1） and Changshu Traditional Chinese Medicine Hospital （dataset 2）. The dataset 1 was used for the training and internal validation of the machine learning model and the development of an application， and the dataset 2 was used for external testing. A total of 22 potential predictive variables were included for the establishment and internal validation of the LASSO regression model and various automated machine learning models. The area under the receiver operating characteristic curve （AUC）， sensitivity， specificity， and accuracy were used to assess the performance of models and identify the best model. Feature importance plots， force plots， and SHAP plots were used to interpret the model. The Python Dash library and the best model were used to develop a web application， and external testing was conducted using the dataset 2. The Kolmogorov-Smirnov test was used to examine whether the data were normally distributed， and the Mann-Whitney U test was used for comparison between two groups， while the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. ResultsAmong the 835 patients included in the study， 152 （18.20%） experienced spontaneous stone passage. The LASSO model achieved an AUC of 0.875 in the training set （n=588） and 0.864 in the validation set （n=171）， and the top five predictive factors in terms of importance were solitary common bile duct stones， non-dilated common bile duct， diameter of common bile duct stones， a reduction in serum alkaline phosphatase （ALP）， and a reduction in gamma-glutamyl transpeptidase （GGT）. A total of 55 models were established using automated machine learning， among which the gradient boosting machine （GBM） model had the best performance， with an AUC of 0.891 （95% confidence interval： 0.859‍ ‍—‍ ‍0.927）， outperforming the extreme randomized tree mode， the deep learning model， the generalized linear model， and the distributed random forest model. The GBM model had an accuracy of 0.855， a sensitivity of 0.846， and a specificity of 0.857 in the test set （n=76）. The variable importance analysis showed that five factors had important influence on the prediction of spontaneous stone passage， i.e.， were solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， a reduction in serum ALP， and a reduction in GGT. The SHAP analysis of the GBM model showed a significant increase in the probability of spontaneous stone passage in patients with solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， and a reduction in serum ALP or GGT. ConclusionThe GBM model and application developed using automated machine learning algorithms exhibit excellent predictive performance and user-friendliness in predicting spontaneous stone passage in patients with common bile duct stones. This application can help avoid unnecessary ERCP procedures， thereby reducing surgical risks and healthcare costs.

ObjectiveTo explore the distribution pattern of tongue image characteristics in patients with glucolipid metabolic disorders and its main syndromes. MethodsA total of 841 patients with glucolipid metabolic disorders （disease group）， and 380 healthy subjects （control group） were included. The disease group was classified into three syndrome types： 283 cases of liver depression and spleen deficiency syndrome， 311 cases of phlegm-dampness obstruction syndrome， and 247 cases of qi stagnation and blood stasis syndrome. Tongue image data were collected using the TFDA-1 Tongue Diagnosis Instrument， and the TDAS V3.0 software was used to analyze the color， texture， and morphological features of the tongue body （TB） and tongue coating （TC） in patents with different syndromes of disease group （including lightness （L）， red-green axis （a）， yellow-blue axis （b）， luminance （Y）， difference between red signal and brightness （Cr）， difference between blue signal and brightness （Cb）， contrast （CON）， angular second moment （ASM）， entropy （ENT）， mean value （MEAN）， tongue coating area/tongue surface area （perAll）， and tongue coating area/non-coated area （perPart））. Logistic regression analysis was conducted to identify influencing factors for different syndrome types of glucolipid metabolic disorders. ResultsThe tongue body indicators TB-L， TB-Y， and TB-Cb in the disease group were significantly higher than those in the control group， while TB-a， TB-b， and TB-Cr were significantly lower. The tongue coating indicators TC-L， TC-Y， TC-Cb， perAll， and perPart in the disease group were significantly higher than those in the control group， while TC-a， TC-b， and TC-Cr were significantly lower （P＜0.05）. Comparing with the different syndromes in disease group， the TB-L and TB-Y of the liver depression and spleen deficiency syndrome， and the phlegm-damp obstruction syndrome were higher than those of the qi stagnation and blood stasis syndrome； the TB-a and TB-Cr of the phlegm-damp obstruction syndrome were lower than those of the qi stagnation and blood stasis syndrome； the perAll of the phlegm-damp obstruction syndrome was higher than that of the qi stagnation and blood stasis syndrome （P＜0.05）. In the analysis of the morphological characteristics of tongue signs， more spotted tongue in disease group compared with control group， more teeth-marked tongue in liver depression and spleen deficiency syndrome than the other two syndromes， more greasy coating in phlegm-damp obstruction syndrome， and more stasis spots of tongue in qi stagnation and blood stasis syndrome （P＜0.05）. Logistic regression analysis identified that greasy coating， spotted tongue， stasis spots of tongue， tooth-marked tongue， perAll， and TB-Cb are the influencing factors of liver depression and spleen deficiency syndrome； greasy coating， tooth-marked tongue， TC-Cb， and TC-Cr are the influencing factors of phlegm-damp obstruction syndrome； cracked tongue， stasis spots of tongue， tooth-marked tongue， and TB-Y are the influencing factors of qi stagnation and blood stasis syndrome （P＜0.05）. ConclusionCompared to healthy individuals， patients with glycolipid metabolic disorder have darker tongue color and thicker， greasy tongue coating. Glycolipid metabolic disorder patients of liver depression and spleen deficiency syndrome exhibit a reddish tongue with finer textures and more tooth marks； patients of phlegm-damp obstruction syndrome have lighter tongue coating with a coarser texture and a higher prevalence of greasy coating； patients of qi stagnation and blood stasis syndrome display lower tongue brightness with a higher prevalence of blood stasis spots.

ObjectiveTo identify the main chemical constituents of Anmeidan （AMD） and to explore the mechanism of AMD in regulating the extracellular signal-regulated kinase 1/2 （ERK1/2）/mitogen-activated protein kinase （MAPK）-interacting serine/threonine-protein kinase （MNK）/eukaryotic translation initiation factor 4E （eIF4E） signaling pathway to improve circadian rhythm disturbances in insomnia rats. MethodsThe main chemical constituents of AMD were identified using ultra-high-performance liquid chromatography-linear ion trap-electrostatic orbital trap mass spectrometry （UPLC-LTQ/Orbitrap/MS） in combination with reference standards. Sixty male Sprague-Dawley （SD） rats were randomly divided into control， model， melatonin， and AMD low-， medium-， and high-dose groups， with 10 rats in each group. Except for the control group， all rats were administered p-chlorophenylalanine via intraperitoneal injection to establish an insomnia model. The activity-rest rhythm of rats was assessed using the open field test and circadian rhythm test. Hematoxylin-eosin （HE） staining and Nissl staining were used to observe structural changes in hypothalamic neurons. Immunofluorescence， real-time quantitative polymerase chain reaction （Real-time PCR）， and Western blot analysis were employed to detect mRNA and protein expression levels of ERK1/2， MNK， and eIF4E in the hypothalamus. ResultsA total of 50 chemical components， including flavonoids， phenylpropanoids， triterpenoid saponins， alkaloids， and lignans， were identified in AMD. Compared with the control group， the model group exhibited significantly increased total distance traveled， average speed， central area residence time， and cumulative rearing time （P<0.01）， as well as prolonged cumulative activity time and total activity time in both light and dark phases （P<0.01）. Hypothalamic neurons in the model group were sparsely arranged， reduced in number， and exhibited nuclear disappearance or nucleolar rupture， with a significantly increased apoptosis index （P<0.01）. The cytoplasm appeared turbid， Nissl body staining was lighter， and the Nissl body apoptosis index was significantly increased （P<0.01）. The mRNA expression levels of ERK1/2， MNK， and eIF4E were significantly decreased （P<0.01）， along with a significant reduction in protein expression levels of ERK1/2， phosphorylated ERK1/2 （p-ERK1/2）， MNK， phosphorylated MNK （p-MNK）， eIF4E， and phosphorylated eIF4E （p-eIF4E） （P<0.01）. Compared with the model group， the total distance， average speed， central area residence time and body upright cumulative time of the AMD high-dose group were significantly reduced （P<0.01）. The total distance， average speed and body upright cumulative time of the AMD medium-dose group were significantly reduced （P<0.01）. The cumulative time of light activity and total time of activity in each dose group of AMD were significantly shortened （P<0.01）. The cumulative time of dark activity in the high-dose group of AMD was prolonged （P<0.01）. The neurons in the middle and high dose groups of AMD were closely arranged， the number of neurons increased， and the apoptosis index of hypothalamic cells decreased significantly （P<0.05， P<0.01）. The cytoplasm of the low， middle and high dose groups of AMD was clear， the color of Nissl body became darker， and the apoptosis index of Nissl body decreased significantly （P<0.01）. The expression of ERK1/2， MNK and eIF4E mRNA and protein in the hypothalamus of the middle and high dose groups of AMD increased significantly （P<0.05， P<0.01）. ConclusionAMD primarily contains 50 chemical constituents， including flavonoids， phenylpropanoids， and triterpenoid saponins. It exhibits a "synergistic enhancement" effect through multiple components and multiple pathways to improve insomnia. AMD ameliorates circadian rhythm disturbances in p-chlorophenylalanine-induced insomnia rats by upregulating ERK1/2/MNK/eIF4E signaling pathway-related proteins.

BACKGROUND:Degenerative scoliosis is defined as a condition that occurs in adulthood with a coronal cobb angle of the spine>10° accompanied by sagittal deformity and rotational subluxation,which often produces symptoms of spinal cord and nerve compression,such as lumbar pain,lower limb pain,numbness,weakness,and neurogenic claudication.The finite element method is a mechanical analysis technique for computer modelling,which can be used for spinal mechanics research by building digital models that can realistically restore the human spine model and design modifications. OBJECTIVE:To review the application of finite element method in the etiology and treatment of degenerative scoliosis. METHODS:The literature databases CNKI,PubMed,and Web of Science were searched for articles on the application of finite element method in degenerative scoliosis published before October 2023.Search terms were"finite element analysis,biomechanics,stress analysis,degenerative scoliosis,adult spinal deformity"in Chinese and English.Fifty-four papers were finally included. RESULTS AND CONCLUSION:(1)The biomechanical findings from the degenerative scoliosis model constructed using the finite element method were identical to those from the in vivo experimental studies,which proves that the finite element method has a high practical value in degenerative scoliosis.(2)The study of the etiology and treatment of degenerative scoliosis by the finite element method is conducive to the prevention of the occurrence of the scoliosis,slowing down the progress of the scoliosis,the development of a more appropriate treatment plan,the reduction of complications,and the promotion of the patients'surgical operation.(3)The finite element method has gradually evolved from a single bony structure to the inclusion of soft tissues such as muscle ligaments,and the small sample content is increasingly unable to meet the research needs.(4)The finite element method has much room for exploration in degenerative scoliosis.

Objective To explore the effective induction scheme for differentiation of adipose-derived mesenchymal stem cell (ADMSC) to insulin producing cell (IPC). Methods Different schemes of small molecule compound were used to induce the differentiation of ADMSC. The purity of cells was analyzed by flow cytometry and the morphological changes of cells were observed under the microscope. The quality, performance and insulin related indicators of cells were detected by hematoxylin-eosin and immunohistochemical staining. The maturity and activity of cells were detected by dithizone (DTZ) and diacetylfluorescein/propidium iodide staining. The induction effect of ADMSC differentiated into IPC was analyzed. Results The purity of ADMSC reached more than 99%, and the sphere forming properties of schemes Ⅰ, Ⅱ and Ⅲ were good. Cell induction mass, the expression effects of pancreatic and duodenal homeobox 1 (PDX1), musculoaponeurotic fibrosarcoma oncogene homolog A (MAFA) and insulin and C peptide of schemes Ⅰ were both better than those of other schemes. The DTZ staining depth may be related to IPC maturity, among which the number of apoptotic cells in scheme Ⅰ was significantly less than that of scheme Ⅱ and Ⅲ. Conclusions Induction scheme Ⅰ may improve the differentiation efficiency of ADMSC to IPC and lay a certain foundation for future clinical IPC transplantation applications.

Testicular radiation injury is a structural and functional abnormality of the testes caused directly or indirectly by radiation, which disrupts spermatogenesis and compromises male fertility. The development of effective preventive and therapeutic interventions is essential because of the high prevalence of this condition in clinical settings and its profound effect on patients′ reproductive health and overall well-being. The concept of "the struggle between vital qi and pathogen" is first seen in the Treatise on Cold Pathogenic Diseases. It denotes the dynamic struggle between vital and pathogenic qi. The occurrence, development, and sequelae of all diseases reflect this ongoing conflict. In this context, this study defines the "vital qi" of the testis as its capacity to generate and preserve the essence of reproduction and to resist damage. The pathogenic qi associated with testicular radiation injury is categorized into two types: ionizing poison and retaining evil. The pathogenesis of testicular radiation damage is delineated into three stages by integrating the characteristics of vital and pathogenic qi: the injury, adhesion, and recovery phases. Based on the theoretical framework advanced by this study, the therapeutic approach for testicular radiation injury should adhere to the fundamental principle of strengthening vital qi and eliminating pathogenic factors. Although the primary focus of treatment should be on strengthening vital qi, it should also be complemented by strategies to eliminate pathogenic influences. This paper aims to provide a novel perspective and strategic approach to the traditional Chinese medicine diagnosis, prevention, and treatment of testicular radiation injury. By elucidating the process of testicular radiation injury and its corresponding treatment principles, it seeks to offer valuable insights for clinical practice.

BACKGROUND:Post and core restoration is a common choice for tooth defects,but the repair effects of various post and core materials are different. OBJECTIVE:To evaluate the stress distribution at the post and core,tooth root,and bonding agent site of post and core models made of different elastic modulus post and core materials using finite element method. METHODS:A three-dimensional root canal treated maxillary central incisor model was built using three-dimensional modeling software,which was restored with a full ceramic crown.The post and core materials in the restoration used nanoceramic resin(elastic modulus=12.8 GPa),composite resin(elastic modulus=16 GPa),hybrid ceramic(elastic modulus=34.7 GPa),glass ceramic(elastic modulus=95 GPa),titanium alloy(elastic modulus=112 GPa),and zirconia(elastic modulus=209.3 GPa).The model was fixed in cortical bone.A 100 N concentrated force of 45° from the long axis of the tooth was applied to 1/3 of the crown and tongue side of the central incisor.The stress distribution of the post and core,dentin,and tooth-root bonding agent in the model was repaired by the maximum principal stress criterion. RESULTS AND CONCLUSION:(1)When the post and core materials with higher elastic modulus was used,the post-core stress in the repair model was more concentrated.When the elastic modulus of the post and core materials(nanoceramic resin and composite resin)was close to dentin,the stress distribution of the post and core was more uniform.The stress distribution of dentin in all restoration models was similar regardless of post and core materials.When the post and core with higher elastic modulus was used,more stress concentration was shown at the post and root bonding agent in the repair model.(2)The maximum stress values at the post and core,tooth root,and the bonding agent site of post and tooth root in the nanoceramic resin model were 31.00,33.21,and 0.51 MPa,respectively.The maximum stress values at the post and core,tooth root,and the bonding agent between the post and tooth root in the composite resin model were 36.84,33.14,and 0.59 MPa,respectively.In the mixed ceramic model,the maximum stress values at the post and core,tooth root,and the bonding agent between the post and tooth root were 64.05,32.83,and 1.00 MPa,respectively.In the glass ceramic model,the maximum stress values at the post and core,tooth root,and the bonding agent between the post and tooth root were 112.30,32.69,and 1.73 MPa,respectively.In the titanium alloy model,the maximum stress values of the post and core,tooth root,and the bonding agent between the post and tooth root were 120.00,32.17,and 1.86 MPa,respectively.In the zirconia model,the maximum stress values of the post and core,tooth root,and the bonding agent between the post and tooth root were 148.80,31.85,and 2.28 MPa,respectively.(3)The higher the elastic modulus of the post and core material,the higher the maximum stress at the post and core during restoration.The elastic modulus of the post and core material had no significant effect on the maximum stress of the dental bonding agent and dentin.