ObjectiveThis study aimed to establish a monocrotaline （MCT）-induced pulmonary arterial hypertension （PAH） rat model to systematically evaluate the protective effect of Xiao Qinglongtang （XQLT） on right cardiac function in model rats and further elucidate the underlying regulatory mechanism. MethodsSixty male SD rats were randomly assigned to the normal group， model group， XQLT low-， medium-， and high-dose groups （XQLT-L/M/H）， and the beraprost sodium tablet group （BST）. Except for the normal group， rats in all other groups were given a single subcutaneous injection of MCT （60 mg·kg^-1） to induce PAH. Three weeks after injection， rats in the XQLT-L/M/H groups were administered XQLT intragastrically at 3.07， 6.14， 12.28 g·kg^-1·d^-1， respectively. Rats in the BST group received beraprost sodium at 12.6 μg·kg^-1·d^-1， and rats in the model group received an equal volume of saline. All treatments lasted for 3 weeks. Right ventricular systolic pressure （RVSP） was measured by right ventricular catheterization. Cardiac function was assessed by echocardiography. The right ventricle was weighed to calculate the right ventricular hypertrophy index （RVHI）. Hematoxylin-eosin （HE） staining， Masson staining， and transmission electron microscopy were used to observe myocardial morphology. Serum metabolomic changes were analyzed using ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）. Data-independent acquisition （DIA） proteomics was used to detect differentially expressed （DE） proteins in the right ventricle， and Western blot was used to measure the expression of uncoupling protein 3 （UCP3）， phosphatidylinositol 3-kinase catalytic subunit p110α （PIK3CA）， L1 cell adhesion molecule （L1CAM）， and quinone oxidoreductase （CRYZ）. UPLC-MS/MS was used to analyze the chemical components of XQLT. ResultsCompared with the normal group， the model group showed significantly increased RVSP and RVHI （P<0.05）， along with pathological changes in myocardial morphology. Compared with the model group， all XQLT-treated groups exhibited reductions in RVSP and RVHI as well as significant improvements in cardiac function and myocardial morphology. Among the XQLT groups， XQLT-M showed the most pronounced effects （P<0.05）， comparable to the BST group. Serum metabolomics revealed 105 differential metabolites in the XQLT groups versus the model group ［variable importance in projection （VIP） >1， P<0.05］， including 58 upregulated and 47 downregulated metabolites. KEGG enrichment analysis indicated that XQLT intervention downregulated phenylalanine metabolism （P<0.01） and upregulated unsaturated fatty acid biosynthesis （P<0.05）. Proteomics analysis showed that 982 DE proteins were identified in the MCT groups versus the normal group， including 455 upregulated and 527 downregulated proteins （|fold change （FC）| >1.3， P<0.05）. Compared with the model group， 237 DE proteins were identified in the XQLT groups， including 124 upregulated and 113 downregulated proteins （|FC| >1.3， P<0.05）， with 57 overlapping DE proteins. KEGG enrichment suggested that XQLT mainly modulated pathways related to mineral absorption， ribosomal biogenesis， peroxisomes， glycolysis/gluconeogenesis， spliceosomes， and thyroid hormone signaling. Western blot analysis showed that， compared with the model group， XQLT increased the expression of UCP3， PIK3CA， and L1CAM， while decreasing the expression of CRYZ （P<0.05）. ConclusionXQLT exerts a protective effect on right heart function in MCT-induced PAH rats， and its mechanism is associated with maintaining myocardial homeostasis and alleviating right ventricular remodeling.

ObjectiveTo investigate whether intestinal deficiency of lanosterol synthase （LSS）， a key enzyme in cholesterol synthesis， influences the progression of metabolic dysfunction-associated steatotic liver disease （MASLD） by regulating intestinal cholesterol absorption and immune response. MethodsLSS heterozygous knockout （LSS^+/-） mice and wild-type （WT） controls were generated using CRISPR/Cas9 technology and fed either a high-fat diet （HFD） or regular chow （CHOW）. The model was validated by genotyping. Hepatic steatosis was assessed by HE and oil red O staining. Immunohistochemistry was used to detect the localization and expression of NPC1L1 and CD36 proteins in the intestine. Western blot analysis was performed to measure JNK phosphorylation and TLR4 protein levels in intestinal tissues. Real-time quantitative polymerase chain reaction （qPCR） was employed to examine the mRNA expression of TLR4 and IL-6. ResultsLSS^+/- mice were successfully validated by genotyping and reduced intestinal LSS protein expression. HE and oil red O staining of liver sections showed that， compared with WT mice fed a CHOW diet， WT mice fed a HFD exhibited a marked increase in hepatic lipid vacuoles. In contrast， compared with HFD-fed WT mice， HFD-fed LSS^+/- mice displayed significantly attenuated hepatic lipid deposition and reduced serum ALT levels （P<0.05）. Immunohistochemical analysis revealed that， compared with WT mice， the expression of the cholesterol absorption protein NPC1L1 in the intestinal villi of LSS^+/- mice was downregulated under both CHOW and HFD conditions （P_HFD<0.001）. Conversely， the expression of the fatty acid transporter CD36 was upregulated in the intestines of LSS^+/- mice （P_CHOW<0.05， P_HFD<0.01）. Western blot analysis demonstrated that， compared with WT mice， TLR4 protein expression in the intestines of LSS^+/- mice significantly increased under both CHOW and HFD conditions （both P<0.05）. JNK phosphorylation level was significantly elevated in LSS^+/- mice under CHOW condition （both P<0.05）. Under HFD condition， total JNK protein expression increased， but its phosphorylation level showed no significant change. qPCR analysis showed that， compared with WT mice， the mRNA levels of TLR4 （P_CHOW<0.01， P_HFD<0.000 1） and IL-6 （P_CHOW<0.001， P_HFD<0.01） were significantly upregulated in the intestines of LSS^+/-mice. ConclusionLSS deficiency counteracts hepatic lipid deposition by orchestrating a synergistic reprogramming involving restricted intestinal cholesterol absorption， enhanced fatty acid utilization， and activation of immune pathways， suggesting intestinal LSS as a potential therapeutic target of MASLD.

Objective To explore the regularity of prescriptions for epidemic disease in Taiping Huimin Heji Ju Fang based on the latent structure model and association rules analysis,and to provide references for modern epidemic treatment.Methods Prescriptions for epidemic diseases were extracted from Taiping Huimin Heji Ju Fang.A high-frequency herb matrix(frequency≥10)was constructed,and high-frequency herbs were analyzed using MicrosoftExcel 2016,Lantern 5.0,and IBM SPSS Modeler 18.0 for efficacy classification,property/flavor/channel tropism statistics,latent structure modeling,and association rule analysis.Results Among the 200 collected herbal prescriptions,46 high-frequency medicinal materials were identified,such as licorice,fresh ginger,dried ginger,poriae,and ginseng.The top 3 drugs efficacy were tonifying deficiency,relieving surface and warming inner.The medicinal properties were mainly warm,and the medicinal flavors were pungent,bitter,and sweet.The meridian tropisms mainly included the spleen meridian,lung meridian and stomach meridian.The analysis of latent structure model suggested that there were 8 types of common symptoms of epidemic disease,such as wind evil attack exterior,wind-cold-dampness,wind-heat,excess-heat in triple energizer,dampness inhibits qi stagnation,yang deficiency,blockage and spleen-qi deficiency.Theanalysis of association rules obtained licorice-ephedra and licorice-atractylodes,which with a core of licorice medicine,and the 16 association rules such as dried ginger-cinnamon,pericarpium citri reticulatae-mangnolia officinalis and poriae-ginseng-atractylodes macrocephala after eliminating ginger,jujube and licorice.Conclusion Most of the medicines used in the treatment of epidemic diseases in Taiping Huimin Heji Ju Fang are pungent,bitter and dispelling evil,the treatment should follow the principle of dispelling evil,warming yang to dissipate cold,dispelling dampness,clearing heat and expelling fire,inducing resuscitation,supporting the right and supplementing deficiency,which embodies the treatment principle of dispelling evil and supporting right,and provides reference and ideas for the treatment of clinical diseases based on syndrome differentiation.

Objective:To assess the humanistic caring ability of clinical interns, analyze its influencing factors, explore the correlation between humanistic caring ability and narrative ability, and provide a basis for formulating narrative medical education scheme for clinical interns.Methods:A total of 163 clinical interns from the Class of 2020 completing internships at a Grade A tertiary hospital in Zhuhai were enrolled as research subjects using convenience sampling. A questionnaire survey was conducted using a baseline demographic survey, a humanistic caring ability inventory, and a medical narrative ability scale. Pearson correlation analysis and multiple linear regression analysis were conducted to explore the influencing factors for humanistic caring ability and its correlation with narrative ability.Results:The overall score of humanistic caring ability was (187.52±20.30). There were significant differences between groups in self-evaluation of humanistic caring ability, degree of satisfaction with the major, and relationship with classmates ( P<0.05). There was a positive correlation between narrative ability and caring ability in both total score and individual dimensions ( r=0.600, P<0.01). After adjusting for demographic differences, relationship with classmates ( β=0.138, P=0.042), attentive listening ( β=0.354, P<0.01), and reflective representation ( β=0.259, P=0.008) exhibited a significant positive impact on humanistic caring ability. However, this impact was not observed for the understanding-response dimension. Conclusions:The humanistic caring ability of clinical interns is low and their medical narrative ability is positively correlated with their humanistic caring ability. Therefore, narrative medical education should focus on training medical students' attentive listening and reflective representation to enhance humanistic literacy and promote their career development.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective To explore the regularity of prescriptions for epidemic disease in Taiping Huimin Heji Ju Fang based on the latent structure model and association rules analysis,and to provide references for modern epidemic treatment.Methods Prescriptions for epidemic diseases were extracted from Taiping Huimin Heji Ju Fang.A high-frequency herb matrix(frequency≥10)was constructed,and high-frequency herbs were analyzed using MicrosoftExcel 2016,Lantern 5.0,and IBM SPSS Modeler 18.0 for efficacy classification,property/flavor/channel tropism statistics,latent structure modeling,and association rule analysis.Results Among the 200 collected herbal prescriptions,46 high-frequency medicinal materials were identified,such as licorice,fresh ginger,dried ginger,poriae,and ginseng.The top 3 drugs efficacy were tonifying deficiency,relieving surface and warming inner.The medicinal properties were mainly warm,and the medicinal flavors were pungent,bitter,and sweet.The meridian tropisms mainly included the spleen meridian,lung meridian and stomach meridian.The analysis of latent structure model suggested that there were 8 types of common symptoms of epidemic disease,such as wind evil attack exterior,wind-cold-dampness,wind-heat,excess-heat in triple energizer,dampness inhibits qi stagnation,yang deficiency,blockage and spleen-qi deficiency.Theanalysis of association rules obtained licorice-ephedra and licorice-atractylodes,which with a core of licorice medicine,and the 16 association rules such as dried ginger-cinnamon,pericarpium citri reticulatae-mangnolia officinalis and poriae-ginseng-atractylodes macrocephala after eliminating ginger,jujube and licorice.Conclusion Most of the medicines used in the treatment of epidemic diseases in Taiping Huimin Heji Ju Fang are pungent,bitter and dispelling evil,the treatment should follow the principle of dispelling evil,warming yang to dissipate cold,dispelling dampness,clearing heat and expelling fire,inducing resuscitation,supporting the right and supplementing deficiency,which embodies the treatment principle of dispelling evil and supporting right,and provides reference and ideas for the treatment of clinical diseases based on syndrome differentiation.

Objective:To assess the humanistic caring ability of clinical interns, analyze its influencing factors, explore the correlation between humanistic caring ability and narrative ability, and provide a basis for formulating narrative medical education scheme for clinical interns.Methods:A total of 163 clinical interns from the Class of 2020 completing internships at a Grade A tertiary hospital in Zhuhai were enrolled as research subjects using convenience sampling. A questionnaire survey was conducted using a baseline demographic survey, a humanistic caring ability inventory, and a medical narrative ability scale. Pearson correlation analysis and multiple linear regression analysis were conducted to explore the influencing factors for humanistic caring ability and its correlation with narrative ability.Results:The overall score of humanistic caring ability was (187.52±20.30). There were significant differences between groups in self-evaluation of humanistic caring ability, degree of satisfaction with the major, and relationship with classmates ( P<0.05). There was a positive correlation between narrative ability and caring ability in both total score and individual dimensions ( r=0.600, P<0.01). After adjusting for demographic differences, relationship with classmates ( β=0.138, P=0.042), attentive listening ( β=0.354, P<0.01), and reflective representation ( β=0.259, P=0.008) exhibited a significant positive impact on humanistic caring ability. However, this impact was not observed for the understanding-response dimension. Conclusions:The humanistic caring ability of clinical interns is low and their medical narrative ability is positively correlated with their humanistic caring ability. Therefore, narrative medical education should focus on training medical students' attentive listening and reflective representation to enhance humanistic literacy and promote their career development.

Objective To explore the value of MRI radiomics based on the frontal and temporal lobes combined with multiple machine learning algorithms in the diagnosis of mild cognitive impairment(MCI).Methods Patients who underwent cranial MR examination were retrospectively selected.According to the inclusion and exclusion criteria,a total of 173 subjects were finally included and randomly divided into training set and test set in a ratio of 7∶3.After delineating the regions of interest(ROI)of the frontal and temporal lobes on T2-fluid attenuated inversion recovery(FLAIR)images,radiomics features were extracted based on the Pyradiomics data package.Features were screened through inter-and intraclass correlation coefficient(ICC),independent samples t-test,and the LightGBM algorithm.Diagnostic models were constructed using support vector machine(SVM),random forest(RF),decision tree(DT),K-nearest neighbor(KNN),gradient boosting decision tree(GBDT),and extreme gradient boosting(XGBoost)combined with 10-fold cross-validation respectively.The training set was further divided into 9 training data sets and 1 validation data set through 10-fold cross-validation,and the hyperparameters were optimized through iterative cycles.The diagnostic efficacy of the model was evaluated by receiver operating characteristic(ROC)curve and area under the curve(AUC),and the DeLong test was applied to compare the differences between different models.Results The AUC of the radiomics models constructed by SVM,DT,RF,KNN,GBDT,XGBoost in the training set were 0.951,0.992,0.998,0.957,1.000,and 1.000 respectively,in the validation set were 0.890,0.843,0.934,0.878,0.930,and 0.945 respectively,and in the test set were 0.902,0.711,0.899,0.849,0.889,and 0.882 respectively.Conclusion MRI radiomics based on the frontal and temporal lobes combined with multiple machine learning algorithms can diagnose MCI,and the model constructed based on SVM shows the highest diagnostic value.

Objective To explore the value of MRI radiomics based on the frontal and temporal lobes combined with multiple machine learning algorithms in the diagnosis of mild cognitive impairment(MCI).Methods Patients who underwent cranial MR examination were retrospectively selected.According to the inclusion and exclusion criteria,a total of 173 subjects were finally included and randomly divided into training set and test set in a ratio of 7∶3.After delineating the regions of interest(ROI)of the frontal and temporal lobes on T2-fluid attenuated inversion recovery(FLAIR)images,radiomics features were extracted based on the Pyradiomics data package.Features were screened through inter-and intraclass correlation coefficient(ICC),independent samples t-test,and the LightGBM algorithm.Diagnostic models were constructed using support vector machine(SVM),random forest(RF),decision tree(DT),K-nearest neighbor(KNN),gradient boosting decision tree(GBDT),and extreme gradient boosting(XGBoost)combined with 10-fold cross-validation respectively.The training set was further divided into 9 training data sets and 1 validation data set through 10-fold cross-validation,and the hyperparameters were optimized through iterative cycles.The diagnostic efficacy of the model was evaluated by receiver operating characteristic(ROC)curve and area under the curve(AUC),and the DeLong test was applied to compare the differences between different models.Results The AUC of the radiomics models constructed by SVM,DT,RF,KNN,GBDT,XGBoost in the training set were 0.951,0.992,0.998,0.957,1.000,and 1.000 respectively,in the validation set were 0.890,0.843,0.934,0.878,0.930,and 0.945 respectively,and in the test set were 0.902,0.711,0.899,0.849,0.889,and 0.882 respectively.Conclusion MRI radiomics based on the frontal and temporal lobes combined with multiple machine learning algorithms can diagnose MCI,and the model constructed based on SVM shows the highest diagnostic value.

Autism spectrum disorder(ASD) is a neurodevelopmental disorder, and social impairment was one of the core symptoms of ASD, which can seriously affects the social life of patients.The pathogenesis of social impairment in ASD is unclear and it may involves many brain abnormalities.The related theories and hypotheses are numerous and there is no unified conclusion. Studies have shown that the cerebellum has extensive connections with brain networks and is involved in the regulation of social cognition, but its role in ASD has not been fully emphasized.The structural and functional abnormalities of the cerebellar-cortex (CC) loop in ASD patients can lead to language communication disorders, empathy disorders, difficulties in interpreting social cues, abnormal social reward processing and emotional regulation disorders, which are closely related to ASD social impairment. Noninvasive brain stimulation of the superficial cerebellum can improve the abnormal CC circuit in ASD patients, and the cerebellum can be considered as a target for the treatment of social disorders in ASD in the future.Based on the clinical and basic researches on social impairment in ASD in recent years, this article reviews the relevant manifestations of disorders which cerebellar and CC circuit involved, aiming to promote the development of related research in the future.