Objective:To discuss the clinical characteristics of the patients with hypertrophic cardiomyopathy(HCM)complicated with microcirculatory dysfunction(CMD),and to analyze the impact of concurrent CMD on the prognosis of the HCM patients.Methods:A total of 211 patients diagnosed with HCM and having complete cardiac magnetic resonance imaging(CMR)examination results from January 1,2019 to September 30,2023 were collected.They were divided into HCM complicated with CMD group(68 cases)and HCM complicated without CMD group(143 cases)based on CMR assessment.The clinical data such as age,gender,admission symptoms,and past medical history,blood test data such as troponin,electrocardiogram,echocardiography,and CMR data including abnormal Q wave,ST segment depression,inverted T wave,PR interval,QRS wavelength,corrected QT interval,ejection fraction(EF),left atrial diameter(LAD),left and right ventricular end-diastolic diameters,cardiac output,E peak,A peak,and maximum wall thickness(MWT)of the patients were compared between two groups.Logistic regression was used to analyze the clinical characteristics of the HCM patients complicated with CMD;multivariate modified Poisson regression was used to analyze the risk factors for major adverse cardiovascular events(MACE)in the HCM patients.Results:Compared with HCM complicated without CMD group,the percentage of palpitation patients in HCM complicated with CMD group was significantly increased(P<0.05),the percentage of tachycardia episode patients was significantly increased(P<0.05),the troponin level was significantly increased(P<0.05),and the percentage with a history of hypertension patients was significantly decreased(P<0.05).Compared with HCM complicated without CMD group,the percentage of abnormal Q wave on electrocardiogram in the patients in HCM complicated with CMD group were significantly increased(P<0.05),the percentage of inverted T wave and the EF of the patients was significantly decreased(P<0.05),the LAD was significantly increased(P<0.05),and the MWT was significantly increased(P<0.05).The multivariate Logistic regression analysis results showed that increased LAD(OR=1.05,95％CI:1.00-1.11,P=0.048)and increased MWT(OR=1.11,95％CI:1.03-1.19,P=0.007)were the risk factors for concurrent CMD in the HCM patients;history of hypertension(OR=0.40,95％CI:0.20-0.80,P=0.010)was a protective factor for concurrent CMD in the HCM patients.The average follow-up time in this study was 20.5 months.A total of 27 patients experienced MACE,with an overall incidence of 12.80％,including 12 patients in HCM complicated with CMD group and 15 patients in HCM complicated without CMD group.The multivariate modified Poisson regression analysis results showed that history of diabetes(RR=2.34,95％CI:1.09-5.06,P=0.030),history of arrhythmia(RR)=4.00,95％CI:1.82-8.83,P=0.001),and decreased ejection fraction(RR=0.96,95％CI:0.94-0.99,P=0.001)were risk factors for MACE in the HCM patients.Conclusion:The HCM patients complicated with CMD have unique clinical characteristics,including higher symptom burden,left atrial enlargement,myocardial hypertrophy,and increased troponin levels.Concurrent CMD does not increase the short-term risk of adverse events;diabetes,arrhythmia,and decreased EF are key risk factors for prognosis;early intervention and complication management for HCM complicated with CMD patients may improve the long-term prognosis of the HCM patients.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, with few effective treatments currently available. The multifactorial nature of AD, shaped by genetic, environmental, and biological factors, complicates both research and clinical management. Recent advances in artificial intelligence (AI) and multi-omics technologies provide new opportunities to elucidate the molecular mechanisms of AD and identify early biomarkers for diagnosis and prognosis. AI-driven approaches such as machine learning, deep learning, and network-based models have enabled the integration of large-scale genomic, transcriptomic, proteomic, metabolomic, and microbiomic datasets. These efforts have facilitated the discovery of novel molecular signatures and therapeutic targets. Methods including deep belief networks and joint deep semi-non-negative matrix factorization have contributed to improvements in disease classification and patient stratification. However, ongoing challenges remain. These include data heterogeneity, limited interpretability of complex models, a lack of large and diverse datasets, and insufficient clinical validation. The absence of standardized multi-omics data processing methods further restricts progress. This review systematically summarizes recent advances in AI-driven multi-omics research in AD, highlighting achievements in early diagnosis and biomarker discovery while discussing limitations and future directions needed to advance these approaches toward clinical application.

Objective:To retrospectively analyze the results of second-trimester serological prenatal screening and explore the factors which may influence the false-positive rate (FPR).Methods:From January 2013 to December 2022, false-positive samples with follow-up outcomes from 632, 825 second-trimester serological prenatal screening samples tested at Sichuan Provincial Maternity and Child Health Care Hospital were selected as the study group, while true-negative samples were 1 : 1 matched as the control group by propensity-score matching (PSM). Univariate and Multivariate Logistic Regression Models were used to analyze the influencing factors. The study has approved by the Medical Ethics Committee of the Sichuan Provincial Maternity and Child Health Care Hospital (Ethic No.20240607-270).Results:The study and control groups were each matched with 305, 998 cases. Univariate analysis showed that sampling season, the difference between ultrasound and gestational weeks calculated by last menstrual period (LMP), monthly median multiple of the median (mMoM) of alpha-fetoprotein (AFP), and monthly mMoM of free β-human chorionic gonadotropin (free β-hCG) were significantly different between the two groups ( P<0.05). Multivariate Logistic Regression analysis showed that winter ( OR=0.938; 95% CI: 0.893~0.985), monthly AFP mMoM ≥ 1.11 ( OR=0.846; 95% CI: 0.761~0.941), monthly free β-hCG mMoM ≤ 0.89 ( OR=0.827; 95% CI: 0.737~0.929) are protective factors for FPR increase, whilst spring ( OR=1.124; 95% CI: 1.072~1.179), summer ( OR=1.121; 95% CI: 1.062~1.183), the difference between ultrasound and gestational weeks calculated by LMP of 8~14 days ( OR=1.319; 95% CI: 1.241~1.402), > 14 days ( OR=1.689; 95% CI: 1.542~1.850), monthly AFP mMoM of 0.90~0.94 ( OR=1.088; 95% CI: 1.046~1.131), and monthly free β-hCG mMoM of 1.05~1.10 ( OR=1.046; 95% CI: 1.000~1.094), ≥ 1.11 ( OR=1.062; 95% CI: 1.002~1.126) are risk factors for FPR increase. Conclusion:Sampling season, difference between ultrasound and gestational weeks by LMP, monthly AFP mMoM, and monthly free β-hCG mMoM are risk factors for FPR during serological prenatal screening. Screening laboratories should look for the cause of abnormal FPR through such factors and adjust them accordingly.

Objective:To retrospectively analyze the results of second-trimester serological prenatal screening and explore the factors which may influence the false-positive rate (FPR).Methods:From January 2013 to December 2022, false-positive samples with follow-up outcomes from 632, 825 second-trimester serological prenatal screening samples tested at Sichuan Provincial Maternity and Child Health Care Hospital were selected as the study group, while true-negative samples were 1 : 1 matched as the control group by propensity-score matching (PSM). Univariate and Multivariate Logistic Regression Models were used to analyze the influencing factors. The study has approved by the Medical Ethics Committee of the Sichuan Provincial Maternity and Child Health Care Hospital (Ethic No.20240607-270).Results:The study and control groups were each matched with 305, 998 cases. Univariate analysis showed that sampling season, the difference between ultrasound and gestational weeks calculated by last menstrual period (LMP), monthly median multiple of the median (mMoM) of alpha-fetoprotein (AFP), and monthly mMoM of free β-human chorionic gonadotropin (free β-hCG) were significantly different between the two groups ( P<0.05). Multivariate Logistic Regression analysis showed that winter ( OR=0.938; 95% CI: 0.893~0.985), monthly AFP mMoM ≥ 1.11 ( OR=0.846; 95% CI: 0.761~0.941), monthly free β-hCG mMoM ≤ 0.89 ( OR=0.827; 95% CI: 0.737~0.929) are protective factors for FPR increase, whilst spring ( OR=1.124; 95% CI: 1.072~1.179), summer ( OR=1.121; 95% CI: 1.062~1.183), the difference between ultrasound and gestational weeks calculated by LMP of 8~14 days ( OR=1.319; 95% CI: 1.241~1.402), > 14 days ( OR=1.689; 95% CI: 1.542~1.850), monthly AFP mMoM of 0.90~0.94 ( OR=1.088; 95% CI: 1.046~1.131), and monthly free β-hCG mMoM of 1.05~1.10 ( OR=1.046; 95% CI: 1.000~1.094), ≥ 1.11 ( OR=1.062; 95% CI: 1.002~1.126) are risk factors for FPR increase. Conclusion:Sampling season, difference between ultrasound and gestational weeks by LMP, monthly AFP mMoM, and monthly free β-hCG mMoM are risk factors for FPR during serological prenatal screening. Screening laboratories should look for the cause of abnormal FPR through such factors and adjust them accordingly.

OBJECTIVE: To retrospectively analyze the results of second-trimester serological prenatal screening and explore the factors which may influence the false-positive rate (FPR). METHODS: From January 2013 to December 2022, false-positive samples with follow-up outcomes from 632,825 second-trimester serological prenatal screening samples tested at Sichuan Provincial Maternity and Child Health Care Hospital were selected as the study group, while true-negative samples were 1 : 1 matched as the control group by propensity-score matching (PSM). Univariate and binary logistic regression models were used to analyze the influencing factors. This study was approved by the Medical Ethic Committee of Sichuan Provincial Maternity and Child Health Care Hospital (Ethic No. 20240607-270). RESULTS: The study and control groups were each matched with 305,998 cases. Univariate analysis showed that sampling season, the difference between ultrasound and gestational weeks calculated by last menstrual period (LMP), monthly median multiple of the median (mMoM) of alpha-fetoprotein (AFP), and monthly mMoM of free β -human chorionic gonadotropin (free β -hCG) were significantly different between the two groups (P < 0.05). Binary logistic regression analysis showed that Winter (OR = 0.938; 95%CI: 0.893 ~ 0.985), monthly AFP mMoM ≥ 1.11 (OR = 0.846; 95%CI: 0.761 ~ 0.941), monthly free β -hCG mMoM ≥ 0.89 (OR = 0.827; 95%CI: 0.737 ~ 0.929) are protective factors for FPR increase, whilst Spring (OR = 1.124; 95%CI: 1.072 ~ 1.179), Summer (OR = 1.121; 95%CI: 1.062 ~ 1.183), the difference between ultrasound and gestational weeks calculated by LMP of 8 ~ 14 days (OR = 1.319; 95%CI: 1.241 ~ 1.402), < 14 days (OR = 1.689; 95%CI: 1.542 ~ 1.850), monthly AFP mMoM of 0.90 ~ 0.94 (OR = 1.088; 95%CI: 1.046 ~ 1.131), and monthly free β -hCG mMoM of 1.05 ~ 1.10 (OR = 1.046; 95%CI: 1.000 ~ 1.094), ≥ 1.11 (OR = 1.062; 95%CI: 1.002 ~ 1.126) are risk factors for FPR increase. CONCLUSION Sampling season, difference between ultrasound and gestational weeks by LMP, monthly AFP mMoM, and monthly free β -hCG mMoM are risk factors for FPR during serological prenatal screening. Screening laboratories should look for the cause of abnormal FPR through such factors and adjust them accordingly.
Humans ; Female ; Pregnancy ; Propensity Score ; Pregnancy Trimester, Second/blood* ; Retrospective Studies ; China ; False Positive Reactions ; Adult ; Prenatal Diagnosis/methods* ; alpha-Fetoproteins/analysis* ; Logistic Models ; Chorionic Gonadotropin, beta Subunit, Human/blood*

Objective:To investigate the effect of lanatoside C on autophagy in hepatocellular carcinoma Huh-7 cells,and the possible mechanism of action.Methods:After Huh-7 cells were treated with gradient concentration of lanatoside C for 24 h,the IC50 value of lanatoside C on Huh-7 cells was detected by CCK-8 assay,and the role of intervention of gradient concentration of lanatoside C in the proliferation and clone formation of Huh-7 cells was analyzed by CCK-8 assay and clone formation assay.Western blotting was used to detect the expression levels of autophagy markers in Huh-7 cells,such as microtubule-associated protein light chain 3(LC3)-II,LC3-Ⅰ,p62,Beclin1,vacuolar protein sorting 34(VPS30),VPS15 and autophagy-related protein 3(ATG3)in Huh-7 cells,and the changes of LC3-II/LC3-Ⅰ ratio were analyzed.The effects of lanatoside C on the formation of autophagic vesicles in Huh-7 cells were observed by laser confocal microscopy,and the effects of lanatoside C on the formation of autophagic vesicles in Huh-7 cells were confirmed by artificial intelligence image analysis.Finally,the effects of lanatoside C on the interaction between Beclin1,VPS34 and VPS15 on the formation of autophagic vesicles in Huh-7 cells were detected by co-immunoprecipitation.Results:The IC50 value of lanatoside C on Huh-7 cells at 24 h was(0.49±0.07)μg/mL.The results of the CCK-8 assay and clone formation assay suggested that lanatoside C had a significant inhibitory effect on the growth of Huh-7 cells in a concentration-dependent manner(both P<0.01).The results of Western blotting assay showed that the LC3-II/LC3-Ⅰ ratio was significantly increased with the increase in the concentration of lanatoside C(P<0.01),while the expression level of Beclin1 protein was up-regulated(P<0.05),and the expression level of p62 protein was significantly down-regulated(P<0.01).The results of laser confocal microscopy showed that lanatoside C could significantly induce autophagic vesicle formation in Huh-7 cells(P<0.01).The results of artificial intelligence image analysis confirmed this effect of lanatoside C(all P<0.01).The results of co-immunoprecipitation confirmed that lanatoside C was able to promote the binding of Beclin1 to VPS34 and VPS15 with each other(both P<0.01).Conclusion:Lanatoside C significantly inhibits the proliferation of Huh-7 cells and and induces Huh-7 cells autophagy,the mechanism of this effect may be related to up-regulating Beclin1 expression and promoting the combination of Beclin1 protein with VPS34 and VPS15 proteins.

Objective:To investigate the effect of lanatoside C on autophagy in hepatocellular carcinoma Huh-7 cells,and the possible mechanism of action.Methods:After Huh-7 cells were treated with gradient concentration of lanatoside C for 24 h,the IC50 value of lanatoside C on Huh-7 cells was detected by CCK-8 assay,and the role of intervention of gradient concentration of lanatoside C in the proliferation and clone formation of Huh-7 cells was analyzed by CCK-8 assay and clone formation assay.Western blotting was used to detect the expression levels of autophagy markers in Huh-7 cells,such as microtubule-associated protein light chain 3(LC3)-II,LC3-Ⅰ,p62,Beclin1,vacuolar protein sorting 34(VPS30),VPS15 and autophagy-related protein 3(ATG3)in Huh-7 cells,and the changes of LC3-II/LC3-Ⅰ ratio were analyzed.The effects of lanatoside C on the formation of autophagic vesicles in Huh-7 cells were observed by laser confocal microscopy,and the effects of lanatoside C on the formation of autophagic vesicles in Huh-7 cells were confirmed by artificial intelligence image analysis.Finally,the effects of lanatoside C on the interaction between Beclin1,VPS34 and VPS15 on the formation of autophagic vesicles in Huh-7 cells were detected by co-immunoprecipitation.Results:The IC50 value of lanatoside C on Huh-7 cells at 24 h was(0.49±0.07)μg/mL.The results of the CCK-8 assay and clone formation assay suggested that lanatoside C had a significant inhibitory effect on the growth of Huh-7 cells in a concentration-dependent manner(both P<0.01).The results of Western blotting assay showed that the LC3-II/LC3-Ⅰ ratio was significantly increased with the increase in the concentration of lanatoside C(P<0.01),while the expression level of Beclin1 protein was up-regulated(P<0.05),and the expression level of p62 protein was significantly down-regulated(P<0.01).The results of laser confocal microscopy showed that lanatoside C could significantly induce autophagic vesicle formation in Huh-7 cells(P<0.01).The results of artificial intelligence image analysis confirmed this effect of lanatoside C(all P<0.01).The results of co-immunoprecipitation confirmed that lanatoside C was able to promote the binding of Beclin1 to VPS34 and VPS15 with each other(both P<0.01).Conclusion:Lanatoside C significantly inhibits the proliferation of Huh-7 cells and and induces Huh-7 cells autophagy,the mechanism of this effect may be related to up-regulating Beclin1 expression and promoting the combination of Beclin1 protein with VPS34 and VPS15 proteins.

Glycogen storage disease (GSD) - type Ib is an autosomal recessive disease, often accompanied by inflammatory bowel disease. A case of GSD -Ib combined with Crohn′s disease-like enterocolitis is reported. The diagnosis and treatment of this patient is helpful to improve the understanding of this rare disease.

Glycogen storage disease (GSD) - type Ib is an autosomal recessive disease, often accompanied by inflammatory bowel disease. A case of GSD -Ib combined with Crohn′s disease-like enterocolitis is reported. The diagnosis and treatment of this patient is helpful to improve the understanding of this rare disease.

OBJECTIVE：To comprehensi vely evaluate the application progress of network pharmacology methods in TCM compound prescription research ，and to provide reference for modernization of TCM compound prescription research. METHODS ： Taking“network pharmacology ”and“TCM compound prescription ”as keywords ，the literatures were retrieved from CNKI ， Wanfang database and VIP during May 2006 to May 2020. Screening literature ，the databases ，analysis platforms ，and software used of the literature were summarized ；on the basis of quantitative analysis ，the application of network pharmacology in the research of traditional Chinese medicine compound were summarized. RESULTS & CONCLUSIONS ：There were a total of 761 valid literatures ，among which the number of literatures that could be retrieved in 2019 reached 313. In the modernization research of TCM compound prescription ，network pharmacology methods were mainly usedmechanism ，material basis of pharmacodynamics ， compatibility law ，compound optimization ，and“effect-toxic”network. Commonly used databasesand platforms included traditional chinese medicine information database （TCMSP and TCMID ），therapeutic target database （TTD，OMIM），drug targets and target prediction platform （Drugbank，SwissTargetPrediction，TargetNet，PharmMapper），network pharmacology analysis and prediction software and platform （CytoScape），etc. Network pharmacology method was widely used in the field of TCM compound prescription research ，and provided new ideas and methods for the modernization of TCM compound prescription research. In the future，the related research can be combined with the pharmacokinetic parameters ，the efficacy of active compounds and related basic experiments ，use the weighted method to carry out network pharmacology analysis ，and integrate the information of multiple databases to improve the scientificity of research results.