OBJECTIVES: To develop a risk prediction model for left ventricular adverse remodeling (LVAR) based on cardiac magnetic resonance (CMR) parameters in patients undergoing percutaneous coronary intervention (PCI) for acute ST-segment elevation myocardial infarction (STEMI). METHODS: A total of 329 acute STEMI patients undergoing primary PCI at 8 medical centers from January, 2018 to December, 2021 were prospectively enrolled. The parameters of CMR, performed at 7±2 days and 6 months post-PCI, were analyzed using CVI42 software. LVAR was defined as an increase >20% in left ventricular end-diastolic volume or >15% in left ventricular end-systolic volume at 6 months compared to baseline. The patients were randomized into training (n=230) and validation (n=99) sets in a 7∶3 ratio. In the training set, potential predictors were selected using LASSO regression, followed by univariate and multivariate logistic regression to construct a nomogram. Model performance was evaluated using receiver-operating characteristic (ROC) curves, area under the curve (AUC), calibration curves, and decision curve analysis. RESULTS: LVAR occurred in 100 patients (30.40%), who had a higher incidence of major adverse cardiovascular events than those without LVAR (58.00% vs 16.16%, P<0.001). Left ventricular global longitudinal strain (LVGLS; OR=0.76, 95% CI: 0.61-0.95, P=0.015) and left atrial active strain (LAAS; OR=0.78, 95% CI: 0.67-0.92, P=0.003) were protective factors for LVAR, while infarct size (IS; OR=1.05, 95% CI: 1.01-1.10, P=0.017) and microvascular obstruction (MVO; OR=1.26, 95% CI: 1.01-1.59, P=0.048) were risk factors for LVAR. The nomogram had an AUC of 0.90 (95% CI: 0.86-0.94) in the training set and an AUC of 0.88 (95% CI: 0.81-0.94) in the validation set. CONCLUSIONS LVGLS, LAAS, IS, and MVO are independent predictors of LVAR in STEMI patients following PCI. The constructed nomogram has a strong predictive ability to provide assistance for management and early intervention of LVAR.
Humans ; Percutaneous Coronary Intervention ; Prospective Studies ; ST Elevation Myocardial Infarction/diagnostic imaging* ; Ventricular Remodeling ; Magnetic Resonance Imaging ; Male ; Female ; Middle Aged ; Risk Factors ; Aged ; Risk Assessment

Objective:To investigate the effect of β-elemene on mitochondrial structure and function of the A549 cells of non-small cell lung cancer(NSCLC),and to elucidate the mechanism of β-elemene in the treatment of NSCLC.Methods:The A549 cells at logarithmic growth stage were divided into blank control group(0 mng·L-1 β-elemene),low,medium and high doses of β-elemene groups(10,25 and 50 mg·L-1),and solvent control group(0.5％ethanol in equal volume).After treatment for 24 h,the cell activities in various groups were detected by MTT assay;the morphology changes of mitochondria in the cells in various groups was observed by transmission electron microscope;the levels of adenosine 5′-triphosphate(ATP)in the cells in various groups were detected by colorimetry;the mitochondrial membrane potential of the A549 cells in various groups were detected by JC-1 flow cytometry;mitochondrial membrane permeability transfer hole assay was used to detect the mitochondrial membrane permeabilities of the cells in various groups.Results:The MTT results showed that compared with blank control group,the cell activities in low,medium and high doses of β-elemene groups were decreased gradually(P＜0.05),while the cell activity in solvent control group had no significant change,and the difference was not significant(P＞0.05).The transmission electron microscope results showed that compared with blank control group,the mitochondria of A549 cells in low,medium and high doses ofβ-elemene groups showed swelling,vacuolation,disordered arrangement and dissolution,while the mitochondrial morphology of the A549 cells in solvent control group had no significant changes.The colorimetric method results showed that compared with blank control group,the ATP levels in the A549 cells in low,medium and high dose β-elemene groups were gradually decreased(P＜0.05),while the ATP level in the A549 cells in solvent control group had no significant change,and the difference was not significant(P＞0.05).The JC-1 flow cytometry method results showed that compared with blank control group,the mitochondrial membrane potential of the A549 cells in low,medium and high doses ofβ-elemene groups were decreased,and the percentages of the cells in Q2-4 region were increased(P＜0.05);the percentage of the A549 cells in the Q2-4 region in solvent control group had no significant change.The results of mitochondrial membrane permeability transfer hole experiment showed that compared with blank control group,the mitochondrial membrane permeabilities of the A549 cells in low,medium and high doses of β-elemene groups were increased,and the percentages of the cells in M4 region were increased(P＜0.05);the mitochondrial membrane permeability of the A549 cells and the percentage of the M4 cells in solvent control group had no significant changes,and the difference was not significant(P＞0.05).Conclusion:β-elemene can inhibit the proliferation of the A549 cells,and the mechanism may be that the mitochondrial structure of A549 cells is damaged by reducing the level of ATP and mitochondrial membrane potential,changing the mitochondrial morphology and increasing the mitochondrial membrane permeability.

Objective To investigate the expression of Tropomyosin 4(TPM4)in thyroid cancer and its effects on the invasion and migration of thyroid cancer cells.Methods The expression level and prognostic value of TPM4 in thyroid cancer were analyzed based on bioinformatics,and its functional involvement was explored through Gene Set Enrichment Analysis(GSEA).In thyroid cancer K1 cells,lentiviral transfection was performed to establish the experimental group(TPM4 shRNA),the negative control group(empty lentiviral transfection),and the control group(untreated).Cell viability and proliferation were assessed using CCK-8 and BrdU assays.Transwell migration and invasion assays were performed to evaluate the effects of TPM4 on the migratory and invasive capacities of thyroid cancer cells.Results TPM4 expression was significantly upregulated in thyroid cancer(P<0.05)and correlated with TNM staging(P<0.05).Patients with higher TPM4 expression in advanced TNM stages exhibited poorer prognosis(P<0.05).GSEA results indicated that high TPM4 expression was enriched in gene sets associated with epithelial-mesenchymal transition,inflammatory response,P53 signaling pathway,and cell cycle.Following TPM4 knockdown in K1 cells,thyroid cancer cell growth was slowed(P<0.01),proliferative activity was decreased(P<0.001),and invasion and migration abilities were significantly impaired(P<0.001).Conclusion TPM4 is highly expressed in thyroid cancer and promotes the invasion and migration capabilities of thyroid cancer cells.

Objective: To explore the mechanism of cistanche deserticola(meat cistanche) in treating Alzheimer′s disease(AD) through network pharmacology, molecular docking, and animal experiments. Methods : Effective components of meat cistanche were mined from the TCMSP database, and AD-related targets were filtered using the SwissTargetPrediction, DisGeNET, and GeneCards databases. The intersection of these targets was analyzed using protein-protein interaction(PPI) networks. Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses were conducted via the Metascape database. Molecular docking of meat cistanche′s active components with core targets was performed using AutoDock Vina. Based on network pharmacology predictions, an AD model was established using 8-month-old SAMP8 mice, with Morris water maze tests assessing learning and cognitive functions, Nissl staining observing hippocampal neuron morphology, and enzyme-linked immunosorbent assays and Western blotting detecting the expression levels of cAMP signaling pathway-related proteins in hippocampal tissues. Results : Network pharmacology analysis predicted that meat cistanche might act on 74 AD targets through 8 active components. Molecular docking showed high affinity of active components like acteoside with core targets such as ESR1, BDNF, MAPK1, and APP. KEGG analysis indicated involvement in pathways related to cancer, cAMP signaling, and AD. Animal experiments demonstrated that meat cistanche effectively improved learning and cognitive impairments in AD mice and alleviated hippocampal neuron damage. ELISA and Western blotting results indicated that meat cistanche significantly increased the expression levels of cAMP, PKA, P-CREB in the cAMP pathway and promoted the expression of downstream neurotrophic factor BDNF. Conclusion Meat cistanche can improve learning and cognitive disorders in AD model mice and may exert therapeutic effects on AD by up-regulating the cAMP signaling pathway and the expression of downstream BDNF protein targets, thereby improving hippocampal neuron injury.

Objective To evaluate the predictive value of global longitudinal strain(GLS)measured by cardiac magnetic resonance(CMR)feature-tracking technique for left ventricular remodeling(LVR)after percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 403 patients undergoing PCI for acute STEMI were prospectively recruited from multiple centers in China.CMR examinations were performed one week(7±2 days)and 6 months after myocardial infarction to obtain GLS,global radial strain(GRS),global circumferential strain(GCS),ejection fraction(LVEF)and infarct size(IS).The primary endpoint was LVR,defined as an increase of left ventricle end-diastolic volume by≥20%or an increase of left ventricle end-systolic volume by≥15%from the baseline determined by CMR at 6 months.Logistic regression analysis was performed to evaluate the predictive value of CMR parameters for LVR.Results LVR occurred in 101 of the patients at 6 months after myocardial infarction.Compared with those without LVR(n=302),the patients in LVR group exhibited significantly higher GLS and GCS(P<0.001)and lower GRS and LVEF(P<0.001).Logistic regression analysis indicated that both GLS(OR=1.387,95%CI:1.223-1.573;P<0.001)and LVEF(OR=0.951,95%CI:0.914-0.990;P=0.015)were independent predictors of LVR.ROC curve analysis showed that at the optimal cutoff value of-10.6%,GLS had a sensitivity of 74.3%and a specificity of 71.9%for predicting LVR.The AUC of GLS was similar to that of LVEF for predicting LVR(P=0.146),but was significantly greater than those of other parameters such as GCS,GRS and IS(P<0.05);the AUC of LVEF did not differ significantly from those of the other parameters(P>0.05).Conclusion In patients receiving PCI for STEMI,GLS measured by CMR is a significant predictor of LVR occurrence with better performance than GRS,GCS,IS and LVEF.

Objective:To explore the value of predicting new-onset heart failure events in patients with hypertrophic cardiomyopathy (HCM) using clinical and cardiac magnetic resonance (CMR) features based on machine learning algorithms.Methods:The study was a retrospective cohort study. Patients with a confirmed diagnosis of HCM who underwent CMR examinations at Beijing Anzhen Hospital from May 2017 to March 2021 were selected and randomly divided into the training set and the validation set in a ratio of 7∶3. Clinical data and CMR parameters (including conventional parameters and radiomics features) were collected. The endpoint events were heart failure hospitalization and heart failure death, with follow-up ending in January 2023. Features with high stability and P value<0.05 in univariate Cox regression analysis were selected. Subsequently, three machine learning algorithms—random forest, decision tree, and XGBoost—were used to build heart failure event prediction models in the training set. The model performance was then evaluated using the independent validation set, with the performance assessed based on the concordance index. Results:A total of 462 patients were included, with a median age of 51 (39, 62) years, of whom 332 (71.9%) were male. There were 323 patients in the training set and 139 in the validation set. The median follow-up time was 42 (28, 52) months. A total of 44 patients (9.5% (44/462)) experienced endpoint events (8 cases of heart failure death and 36 cases of heart failure hospitalization), with 31 events in the training set and 13 in the validation set. Univariate Cox regression analysis identified 39 radiomic features, 4 conventional CMR parameters (left ventricular end-diastolic volume index, left ventricular end-systolic volume index, left ventricular ejection fraction, and late gadolinium enhancement ratio), and 1 clinical feature (history of non-sustained ventricular tachycardia) that could be included in the machine learning model. In the prediction models built with the training set, the concordance indices for the random forest, decision tree, and XGBoost models were 0.966 (95% CI 0.813-0.995), 0.956 (95% CI 0.796-0.992), and 0.973 (95% CI 0.823-0.996), respectively. In the validation set, the concordance indices for the random forest, decision tree, and XGBoost models were 0.854 (95% CI 0.557-0.964), 0.706 (95% CI 0.399-0.896), and 0.703 (95%CI 0.408-0.890), respectively. Conclusion:Integrating clinical and CMR features of HCM patients through machine learning aids in predicting heart failure events, with the random forest model showing superior performance.

【Objective】 To explore the effectiveness of intraovarian injection of platelet-rich plasma(PRP) in the treatment of patients with diminished ovarian reserve(DOR), aiming to provide new diagnostic and therapeutic ideas for the treatment. 【Methods】 A total of 22 patients with DOR who underwent autologous PRP ovarian injection at the Reproductive Medical and Genetic Center of Qinzhou Maternal and Child Health Hospital from January 2021 to December 2023 were collected. Among them, 12 patients underwent assisted reproductive technology for pregnancy. The patient′s anti-Müllerian hormone (AMH), antral follicle count (AFC), basal follicle-stimulating hormone (FSH), basal luteinizing hormone (LH) and basal estradiol (E2) levels were observed. 【Results】 The levels of AMH, AFC, basal FSH, basal LH and basal E2 in 22 patients improved after treatment compared with those before treatment. Of the 12 patients who received assisted reproduction, 2 had IVF cycle canceled due to poor ovarian reaction. Ten patients obtained embryos, of which 5 obtained high-quality embryos. 【Conclusion】 Intraovarian injection of autologous PRP can effectively improve ovarian reserve function in patients with DOR.

Objective To study the correlation between semen quality and bacterial infection in men with abnormal fer-tility,and provide clinical basis for guiding the reproductive health of men with abnormal fertility.Methods 200 male semen samples with abnormal fertility were collected,and then separated and cultured for 48 hours.According to the culture results,they were divided into three groups:the non-pathogenic group,the pathogenic group,and the sterile group.The bacterial resist-ance analysis of the pathogenic group was conducted,and the semen quality between each group was compared.Results After 48 hours of isolation and cultivation,200 semen samples had been tested,non-pathogenic bacteria was detected in 163 semen samples,accounting for 81.5% ;pathogenic bacteria was detected in 33 semen samples,accounting for 16.5% ;and bacteria was not detected in 4 semen samples,accounting for 2.0% .The top three strains of pathogenic bacteria in 33 cases were Escherichia coli,Streptococcus agalactiae,and Enterococcus faecalis,with drug resistance rates of 80.0% ,87.5% ,and 100.0% ,respec-tively.Conclusion The detection rate of bacterial culture in semen of men with abnormal fertility is relatively high,and patho-genic bacteria can affect semen quality.

Objective:To construct a diabetes foot prediction model for adult patients with type 2 diabetes based on retrospective cohort study using data from a regional health data platform.Methods:Using Yinzhou Health Information Platform of Ningbo, adult patients with newly diagnosed type 2 diabetes from January 1, 2015 to December 31, 2022 were included in this study and divided randomly the train and test sets according to the ratio of 7∶3. LASSO regression model and bidirectional stepwise regression model were used to identify risk factors, and model comparisons were conducted with net reclassification index, integrated discrimination improvement and concordance index. Univariate and multivariate Cox proportional hazard regression models were constructed, and a nomogram plot was drawn. Area under the curve (AUC) was calculated as a discriminant evaluation indicator for model validation test its calibration ability, and calibration curves were drawn to test its calibration ability.Results:No significant difference existed between LASSO regression model and bidirectional stepwise regression model, but the better bidirectional stepwise regression model was selected as the final model. The risk factors included age of onset, gender, hemoglobin A1c, estimated glomerular filtration rate, taking angiotensin receptor blocker and smoking history. AUC values (95% CI) of risk outcome prediction at year 5 and 7 were 0.700 (0.650-0.749) and 0.715(0.668-0.762) for the train set and 0.738 (0.667-0.801) and 0.723 (0.663-0.783) for the test set, respectively. The calibration curves were close to the ideal curve, and the model discrimination and calibration powers were both good. Conclusions:This study established a convenient prediction model for diabetic foot and classified the risk levels. The model has strong interpretability, good discrimination power, and satisfactory calibration and can be used to predict the incidence of diabetes foot in adult patients with type 2 diabetes to provide a basis for self-assessment and clinical prediction of diabetic foot disease risk.

Objective:To develop a prediction model for the risk of diabetic retinopathy (DR) in patients with newly diagnosed type 2 diabetes mellitus (T2DM).Methods:Patients with new diagnosis of T2DM recorded in Yinzhou Regional Health Information Platform between January 1, 2015 and December 31, 2022 were included in the study. The predictor variables were selected by using Lasso-Cox proportional hazards regression model. Cox proportional hazards regression models were used to establish the prediction model for the risk of DR. Bootstrap method (500 resamples) was used for internal validation, and the performance of the model was assessed by C-index, the receiver operating characteristic curve and area under the curve (AUC), and calibration curve.Results:The predictor variables included in the final model were age of T2DM onset, education level, fasting plasma glucose, glycated hemoglobin A1c, urinary albumin, estimated glomerular filtration rate, and history of lipid-lowering agent and angiotensin converting enzyme inhibitor uses. The C-index of the final model was 0.622, and the mean corrected C-index was 0.623 (95% CI: 0.607-0.634). The AUC values for predicting the risk of DR after 3, 5, and 7 years were 0.631, 0.620, and 0.624, respectively, with a high degree of overlap of the calibration curves with the ideal curves. Conclusion:In this study, a simple and practical risk prediction model for DR risk prediction was developed, which could be used as a reference for individualized DR screening and intervention in newly diagnosed T2DM patients.