Objective To observe the effects of Yixintai on lipid metabolism and the protein expressions of CPT-1 and CD36 in rats with heart failure;To explore the mechanism of its treatment of heart failure.Methods 106 out of 120 SD rats were selected to establish the heart failure model induced by myocardial infarction by ligating the left anterior descending coronary artery,and 14 rats were selected as the sham-operation group.The successful model rats were randomly divided into model group,trimetazidine group and Yixintai low-,medium-and high-dosage groups,with 14 rats in each group.The administration group was given corresponding drugs by gavage once a day for 4 weeks.LVEF,LVFS,LVIDd and LVIDs were measured by color doppler ultrasonography,the contents of ANP,BNP,LA and FFA in serum were detected by ELISA,the contents of TG,TC,LDL and HDL were detected by automatic biochemical analyzer,HE and Masson staining were used to observe the morphology of myocardial tissue,the expressions of CPT-1 and CD36 protein in myocardial tissue were detected by Western blot.Results Compared with the sham-operation group,LVEF and LVFS in the model group decreased(P<0.05),the LVIDs and LVIDd increased(P<0.05);the contents of serum ANP,BNP,LA,FFA,TG,TC and LDL increased(P<0.05),while the content of HDL decreased(P<0.05),with myocardial edema,irregular arrangement of myocardial fibers,increased inflammatory cell infiltration and collagen fiber deposition;the protein expressions of CPT-1 and CD36 in myocardial tissue decreased(P<0.05).Compared with the model group,the LVEF and LVFS in Yixintai each dosage groups and trimetazidine group increased(P<0.05),LVIDs and LVIDd decreased(P<0.05);the contents of ANP,BNP,LA,FFA,TG,TC and LDL in serum of Yixintai medium-and high-dosage groups and trimetazidine group decreased(P<0.05),the content of HDL increased(P<0.05);myocardial edema was improved,inflammatory cell infiltration was reduced,collagen fiber deposition was reduced,and the protein expressions of CPT-1 and CD36 in myocardial tissue increased(P<0.05).Conclusion Yixintai may improve myocardial energy metabolism and treat heart failure by increasing the expression of CPT-1 and CD36 protein in myocardial tissue and promoting fatty acid β oxidation.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

Varicocele is a common disease of the male reproductive system, and the pampiniform plexus in the spermatic cord manifests abnormal dilatation, extension, and circuity, which is a vasculopathy. In this article, we believe that the relevance of the essence chamber collaterals to the spermatic vein in terms of anatomical morphology and physiological function is high and that when pathogenic qi invades the essence chamber, the qi and collaterals of the essence chamber are out of harmony, the fluid collaterals are impassable, and the blood collaterals are obstrcuted, and the essence chamber collaterals are blockaded with several pathological products, and even intermingled phlegm and blood stasis in the blood collaterals and form vascular clusters, resulting in the formation and development of varicocele. Based on this, this article proposes the core treatment principle of healing, harmonizing, activating, and dredging the collaterals, with the basic treatment method of nourishing qi and harmonizing collaterals, activating blood collaterals, and dredging blood stasis to, respectively treat degree Ⅰ, Ⅱ, and Ⅲ varicocele, aiming to prevent the change of the varicocele, dredge the curvature of the varicocele, and dissipate the knots of the varicocele. The proposal of essence chamber collaterals is of great significance to understanding the common law and pathological aspects of the occurrence and development of essence collateral and vascular lesions from the perspective of integrated traditional Chinese and Western medicine.

ObjectiveTo investigate the effects of artemisinin （ART） on histopathological damage and salivary secretion in the submandibular gland （SMG） of mice with Sjögren's syndrome （SS） model，and on the expression of aquaporin 5 （AQP5） in SMG cells. MethodsThe NOD/Ltj mice were used as a model of SS and randomly divided into the SS model group，the ART group，and the hydroxychloroquine sulfate （HCQ） group，with six mice per group. Another 6 female BALB/c mice at the same week were selected as the control group. Mice in the ART group was fed with the ART solution daily in the dosage of 50 mg·kg^-1，and mice in the HCQ group was given with the HCQ solution （1 300 mg·kg^-1）. Mice in the SS model and control groups were given saline daily. The treatment lasted for 8 weeks. The 24-hour average water intake，salivary flow rate，SMG pathology scores of mice in each group were measured，as well as the expression levels of AQP5 protein and gene in the SMG tissues. ResultsCompared with the control group，the 24-hour average water intake of mice in the model group was significantly increased （P<0.01），and the saliva flow rate was significantly decreased （P<0.01）. Compared to the SS model group，the 24-hour average water intake of mice in the ART and HCQ groups was significantly reduced （P<0.01），and the salivary flow rate was significantly increased in the ART group（P<0.01），comparisons between groups showed that the ART was superior to the HCQ in reducing water intake and improving saliva flow rate in SS model mice （P<0.05）. The HE staining results showed that，compared with the normal group，the number of lymphocyte infiltration foci in SMG tissue in the model group increased，and the pathological score increased （P<0.01）. Compared to the SS model group，after the intervention of the ART and HCQ，the number of lymphocytic infiltration foci in the SMG tissue decreased，the area of the lymphocytic infiltration foci was reduced，and the pathology score of the SMG tissues was lowered in the ART group（P<0.01）. However，there was no difference in pathological scores between the ART and HCQ groups . The results of IHC，Western blot，and Real-time PCR showed that，compared with the normal group，the expression levels of AQP5 protein and gene in SMG tissue in the model group significantly decreased （P<0.05）. Comparing with the SS model group，the ART and HCQ groups could significantly up-regulated the expression levels of AQP5 protein and mRNA in the SMG tissue，and the treatment effect was better than that of HCQ. ConclusionART was able to ameliorate SMG structural damage and salivary secretion function in SS model mice，and its mechanism of action may be related to the up-regulation of AQP5 protein and gene expression levels in SMG cells.

Based on the pathogenesis of erectile dysfunction (ED) from the meridian-zangfu relationship and the "brain-heart-kidney-essence chamber" axis, it proposes that dysfunction of the "brain-heart-kidney-essence chamber" axis is closely related to the occurrence of ED. Among these, brain-heart disharmony is the key pathogenic factor, kidney deficiency and essence depletion constitute an important basis, and essence chamber stasis is a critical mechanism. The treatment approach emphasizes harmonizing the brain and heart, regulating the mind, tonifying the kidney and replenishing qi, unblocking qi and blood to harmonize the essence chamber. The primary acupoints include Baihui (GV20)-Neiguan (PC6)-Shenmen (HT7), Taixi (KI3)-Guanyuan (CV4)-Sanyinjiao (SP6), and Zhongji (CV3)-Dahe (KI12)-Gongsun (SP4), with additional acupoints selected based on syndrome differentiation. This approach aims to restore the clarity of the brain and heart, replenish kidney qi, and unblock the essence chamber, thereby facilitating the restoration of normal functions of the brain, heart, kidney, and essence chamber, and alleviating ED symptoms and improving overall clinical efficacy.
Humans ; Male ; Meridians ; Erectile Dysfunction/physiopathology* ; Kidney/physiopathology* ; Brain/physiopathology* ; Acupuncture Therapy ; Acupuncture Points ; Heart/physiopathology*

BACKGROUND:Poly(lactic-co-glycolic acid)copolymer with good biosafety,biodegradability,and superior mechanical properties has become a focal point of research in stomatology.OBJECTIVE:To review the advance in stomatology of poly(lactic-co-glycolic acid)copolymer.METHODS:Using a computer-assisted search of relevant literature published in the China National Knowledge Infrastructure(CNKI)and PubMed databases,the search terms included"polylactic acid-hydroxyacetic acid,PLGA,oral defect,tissue engineering"in Chinese,and"PLGA,polylactic acid-hydroxyacetic acid copolymer,poly(lactic-co-glycolic acid)copolymer,dent*,regeneration,caries,periodontal,pulp,implant,alveolar bone"in English.Preliminary screening was conducted by reading titles and abstracts,excluding literature unrelated to the theme of the article.Based on the inclusion and exclusion criteria,a total of 119 articles were included for review.RESULTS AND CONCLUSION:In the field of stomatology,the application scope of poly(lactic-co-glycolic acid)copolymer is rapidly expanding,gradually replacing the traditional therapeutic drugs and restorative materials.Poly(lactic-co-glycolic acid)copolymer nanoparticles/microspheres can carry a variety of hydrophobic and hydrophilic active substances,demonstrating excellent delivery capabilities in caries prevention,root canal disinfection,and pulp capping treatment.In periodontal therapy,poly(lactic-co-glycolic acid)copolymer is widely used as a barrier membrane and drug carrier for periodontal tissue regeneration.Poly(lactic-co-glycolic acid)copolymer used for surface modification of implants not only enhances the antibacterial ability of the implant surface but also improves the bio-inert nature of the implant surface.The effect of pure poly(lactic-co-glycolic acid)copolymer scaffolds on treating bone defects is limited and requires the integration of 3D printing,various bioactive components,and inorganic materials to enhance scaffold performance.The combination of poly(lactic-co-glycolic acid)copolymer and stem cells can improve the effectiveness of nerve therapy,meeting clinical needs.Based on the great potential of poly(lactic-co-glycolic acid)copolymer in the field of stomatology,it is expected that in the future,repair materials with specific functions for different diseases will be produced according to different needs of oral tissue engineering.

BACKGROUND:Poly(lactic-co-glycolic acid)copolymer with good biosafety,biodegradability,and superior mechanical properties has become a focal point of research in stomatology.OBJECTIVE:To review the advance in stomatology of poly(lactic-co-glycolic acid)copolymer.METHODS:Using a computer-assisted search of relevant literature published in the China National Knowledge Infrastructure(CNKI)and PubMed databases,the search terms included"polylactic acid-hydroxyacetic acid,PLGA,oral defect,tissue engineering"in Chinese,and"PLGA,polylactic acid-hydroxyacetic acid copolymer,poly(lactic-co-glycolic acid)copolymer,dent*,regeneration,caries,periodontal,pulp,implant,alveolar bone"in English.Preliminary screening was conducted by reading titles and abstracts,excluding literature unrelated to the theme of the article.Based on the inclusion and exclusion criteria,a total of 119 articles were included for review.RESULTS AND CONCLUSION:In the field of stomatology,the application scope of poly(lactic-co-glycolic acid)copolymer is rapidly expanding,gradually replacing the traditional therapeutic drugs and restorative materials.Poly(lactic-co-glycolic acid)copolymer nanoparticles/microspheres can carry a variety of hydrophobic and hydrophilic active substances,demonstrating excellent delivery capabilities in caries prevention,root canal disinfection,and pulp capping treatment.In periodontal therapy,poly(lactic-co-glycolic acid)copolymer is widely used as a barrier membrane and drug carrier for periodontal tissue regeneration.Poly(lactic-co-glycolic acid)copolymer used for surface modification of implants not only enhances the antibacterial ability of the implant surface but also improves the bio-inert nature of the implant surface.The effect of pure poly(lactic-co-glycolic acid)copolymer scaffolds on treating bone defects is limited and requires the integration of 3D printing,various bioactive components,and inorganic materials to enhance scaffold performance.The combination of poly(lactic-co-glycolic acid)copolymer and stem cells can improve the effectiveness of nerve therapy,meeting clinical needs.Based on the great potential of poly(lactic-co-glycolic acid)copolymer in the field of stomatology,it is expected that in the future,repair materials with specific functions for different diseases will be produced according to different needs of oral tissue engineering.

Obesity is a common chronic disease associated with an increased risk of multiple comorbidities and premature mortality. Tirzepatide, a glucose-dependent insulinotropic polypeptide (GIP)/glucagon-like peptide 1 (GLP-1) receptor agonist, has demonstrated significant efficacy in multiple studies in reducing body weight and fat mass, improving body composition and metabolic parameters, lowering the risk of obesity-related complications and improving health and quality of life. This review summarizes the underlying mechanisms of tirzepatide and recent advances in its clinical research, providing a reference for clinical practice.

Obesity is a common chronic disease associated with an increased risk of multiple comorbidities and premature mortality. Tirzepatide, a glucose-dependent insulinotropic polypeptide (GIP)/glucagon-like peptide 1 (GLP-1) receptor agonist, has demonstrated significant efficacy in multiple studies in reducing body weight and fat mass, improving body composition and metabolic parameters, lowering the risk of obesity-related complications and improving health and quality of life. This review summarizes the underlying mechanisms of tirzepatide and recent advances in its clinical research, providing a reference for clinical practice.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.