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 characteristics of fine motor deficits in the elderly individuals with MCI due to AD through a new wearable inertial motion capture device,and then construct a prediction model for MCI.Methods A total of 260 elderly subjects were recruited in community from November,2022 to April,2023,and based on diagnosis,they were divided into a MCI group(134 cases)and a control group(126 cases).A new wearable inertial motion capture device,which was self-designed and developed based on MEMS inertial sensor,was used to capture the fine mo-tor movements of the hands,and the obtained data were analyzed with a computerized assessment system to make the quantitative evaluation of fine motor.LASSO learning algorithm and logistic regression analysis were employed to identify the predictive factors for MCI,and then a nomo-gram was constructed based on these factors.ROC curve was plotted to evaluate the predictive ability of the model by calculating its AUC value.DC A,CIC,and Bootstrap method were applied to evaluate and validate the clinical utility and stability of the model.Results The total score of MoCA(22.18±2.84 vs 27.60±1.10)and scores of the dimensions were significantly lower in the MCI group than the control group(all P＜0.01).In the five digital assessment tasks,the MCI group showed obviously poorer fine motor performance of both hands than the control group(P＜0.05,P＜0.01).ROC curve analysis showed that the AUC value of our nomogram model in predicting MCI was 0.762(95％CI:0.705-0.819).DCA,CIC,and Bootstrap methods demonstra-ted good and relatively stable discrimination,calibration,and clinical applicability of the model.Conclusion MEMS inertial sensor motion capture technology can make digital evaluation of fine motor.For the elderly,fine motor deficits are significantly associated with risk for MCI.Our no-mogram model based on fine motion parameters shows good predictive efficacy in assessing the risk of MCI.

Aim To investigate the protective effect of liraglutide(LIRA)on acetaminophen(APAP)-in-duced hepatotoxicity at the in vivo level and to reveal the underlying mechanism.Methods Forty SPF grade male C57BL/6J mice were randomly divided into the Control,LIRA(200 μg·kg-1),APAP(500 mg·kg-1),LIRA+APAP,LIRA+APAP+3-methylade-nine(3-MA,30 mg·kg-1)groups,with eight mice in each group.The mice were administered for three con-secutive days,and the materials were taken after 24 h.The general condition and body weight of mice in each group were recorded,and liver morphology was ob-served.Serum ALT and AST levels,as well as SOD ac-tivity,MDA,and GSH content in liver homogenates,were measured using biochemical assay kits.The levels of inflammatory cytokines IL-6,TNF-α,and IL-1β in serum were detected by ELISA.Liver pathological changes were assessed by HE staining,while mitochon-drial and autophagosome structures in liver tissues were observed using transmission electron microscopy.The number of PCNA-positive cells in liver tissues was e-valuated using immunohistochemical staining.The pro-tein expression levels of LC3Ⅱ,p62,Bax,Bcl-2,PC-NA,and CyclinD1 in liver tissues were determined by Western blot.Results LIRA pretreatment can im-prove the general condition of mice with acetamino-phen-induced liver injury(AILI),reduce serum ALT and AST levels,and effectively ameliorate the appear-ance and morphology of the liver as well as the patho-logical damage to liver tissue.Simultaneously,the lev-els of inflammatory cytokines IL-6,TNF-α,and IL-1βare significantly decreased;SOD activity and GSH con-tent are significantly increased,while MDA content is significantly reduced.Transmission electron microsco-py observations reveal the presence of numerous auto-phagosomes in the cytoplasm of liver tissue.Immuno-histochemical staining results indicate a significant in-crease in the number of PCNA-positive cells.Further-more,the expression of LC3Ⅱ,Bcl-2,PCNA,and Cy-clinD1 proteins in liver tissue is significantly upregulat-ed,while the expression of p62 and Bax proteins is significantly downregulated.However,after interven-tion with the autophagy inhibitor 3-MA,the aforemen-tioned protective effects of LIRA are significantly.Conclusions LIRA pretreatment can significantly im-prove liver injury in AILI mice.Its protective mecha-nism may be related to enhancing autophagy in hepato-cytes,thereby reducing oxidative stress,inflammatory response and apoptosis in liver of AILI mice.

Colorectal adenoma is a definite precancerous lesion,and the"inflammation-cancer transformation"is a key pathological link in the process of colorectal adenoma-cancer evolution.Under the guidance of the theory of"preventive treatment of diseases"in TCM,prevention before disease onset and preventing the development of the occurred disease has become the consensus and the important subject of clinical research to block the"inflammation-cancer transformation"and prevent the precancerous lesions of colorectal cancer.This article discussed the effectiveness of TCM in preventing and treating the"inflammation-cancer transformation"from different aspects.Its advantages are reflected in improving the symptoms of TCM and improving the quality of life,etc.Its mechanism may be related to inhibiting the activation of cancer-promoting signals,regulating inflammation,maintaining intestinal microbial homeostasis,and protecting the intestinal barrier.By explaining the pathogenesis of adenoma-cancer transformation in TCM,this article discussed the efficacy and advantages of TCM to block"inflammation-cancer transformation",analyzed its intervention targets and pathways,providing references for the intervention of TCM in the management of precancerous lesions of colorectal cancer and the synergistic prevention and treatment of traditional Chinese and Western medicine.

Objective:To investigate gut microbiota differences between individuals with and without colorectal adenoma(CRA)and to identify gut microbes associated with CRA.Methods:This cross-sectional study analyzed the gut microbiota of 100 patients with CRA and 68 individuals without CRA(aged 40-75 years)who underwent colonoscopies between March 2021 and March 2022 at Tianjin Nankai Hospital.Fecal samples were sequenced for the V3-V4 region of the bacterial 16S rRNA gene using the Illumina NovaSeq platform.Results:Compared to the non-CRA group,the CRA group exhibited reduced relative abundances of identified and unidentified Lachnospiraceae,with increased Faecalibacterium and Streptococcus.In the non-CRA group,the relative abundances of Coprococcus,unidentified Clostridiaceae,and Clostridium were higher.LEfSe analysis revealed significant enrichment of Gammaproteobacteria,Proteobacteria,Enterobacteriales,and Faecalibacterium in the CRA group,while the non-CRA group was enriched for Moraxellaceae,Acinetobacter,and Anaerostipes.Conclusions:These findings suggest a discernible disparity in the gut microbiota structure between CRA patients and individuals without adenoma.The enrichment of potential pathogenic taxa,such as Faecalibacterium and Streptococcus,in the CRA group suggests a possible association with adenoma development.

Objective To explore the characteristics of fine motor deficits in the elderly individuals with MCI due to AD through a new wearable inertial motion capture device,and then construct a prediction model for MCI.Methods A total of 260 elderly subjects were recruited in community from November,2022 to April,2023,and based on diagnosis,they were divided into a MCI group(134 cases)and a control group(126 cases).A new wearable inertial motion capture device,which was self-designed and developed based on MEMS inertial sensor,was used to capture the fine mo-tor movements of the hands,and the obtained data were analyzed with a computerized assessment system to make the quantitative evaluation of fine motor.LASSO learning algorithm and logistic regression analysis were employed to identify the predictive factors for MCI,and then a nomo-gram was constructed based on these factors.ROC curve was plotted to evaluate the predictive ability of the model by calculating its AUC value.DC A,CIC,and Bootstrap method were applied to evaluate and validate the clinical utility and stability of the model.Results The total score of MoCA(22.18±2.84 vs 27.60±1.10)and scores of the dimensions were significantly lower in the MCI group than the control group(all P＜0.01).In the five digital assessment tasks,the MCI group showed obviously poorer fine motor performance of both hands than the control group(P＜0.05,P＜0.01).ROC curve analysis showed that the AUC value of our nomogram model in predicting MCI was 0.762(95％CI:0.705-0.819).DCA,CIC,and Bootstrap methods demonstra-ted good and relatively stable discrimination,calibration,and clinical applicability of the model.Conclusion MEMS inertial sensor motion capture technology can make digital evaluation of fine motor.For the elderly,fine motor deficits are significantly associated with risk for MCI.Our no-mogram model based on fine motion parameters shows good predictive efficacy in assessing the risk of MCI.

Objective:To seek any correlation between hypoesthesia and sensory disturbance to motor function among stroke survivors.Methods:One hundred and two stroke survivors with hyperalgesia were treated with sinusoidal alternating current at 2000Hz, 250Hz or 5Hz to stimulate the fingers and toes on their healthy and hemiplegic sides. Current perception thresholds (CPTs) and pain tolerance thresholds (PTTs) were recorded. The correlation between the degree of sensory disturbance in the hemiplegic limb and muscle strength was explored.Results:①The degree of sensory impairment in those who had suffered a cerebral hemorrhage was significantly greater than among those with cerebral infarction, without significant difference in pain tolerance between different genders and affected sides. ②All of the patients with sensory impairment showed significantly higher CPT and PTT values at the different frequencies, with a positive correlation between them. ③The CPT values of the affected hand and foot at the different frequencies were negatively correlated with muscle strength on the affected side.Conclusions:Both CPT and PTT can usefully represent the degree of sensory disturbance after a stroke. The CPT values of patients with different types of stroke are significantly different, and the degree of sensory disturbance is correlated with the muscle strength of the affected side. Therefore, it is helpful for prognostic judgment and individualized rehabilitation treatment planning by quantifying the degree of sensory disturbance.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Objective To design an 8-channel gene analyzer to take the place of the widely used gene analyzer with problems in inconvenient consumable replacement and short storage time of electrophoresis polymer.Methods The 8-channel gene analyzer had its mechanical components composed of an automatic sample loading table,a polymer injection module,a high-voltage temperature control module,an optical module and an integrated U box,its electrical control system made up of a host computer(an embedded computer)and three slave computers(a sampling control board,a polymer injection control board and a high-voltage temperature control board).The automatic sample loading table involved in four motors and transmission systems for x,y,z directions and optical alignment,the transmission systems adopted mainly belt drive mode and the optical alignment motor had its threads with an anti-backlash structure;the polymer injuection module was manipulated by the polymer injection control board,and the polymer block was made of highly transparent acrylic material;the high-voltage temperature control module realized the regulation of electrophoresis voltage and the detection of electrophoresis current by the low-ripple precision high-voltage power supply,and controlled the temperature of the heating furnace by the proportional-integral-differential(PID)algorithm;the optical module consisted of an excitation module and a light-receiving module,which had the base of the reflector made of low expansion coefficient alloy material;the integrated U box had the electrophoresis polymer,capillary array,polymer block and anode buffer in a plastic housing;the host computer had the data acquisition software programmed with C# and C++,and the slave computers were controlled by STM32 SCM.Results The 8-channel gene analyzer had no significant differences with the widely used ABI3500 gene analyzer in resolution,precision accuracy and clinical results.Conclusion The 8-channel gene analyzer gains advantages in consumable replacement and storage time of electrophoresis polymer,and can meet the requirements for gene sequencing.[Chinese Medical Equipment Journal,2025,46(2):24-30]