Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences最新文献

Paramyxoviruses are important respiratory pathogens with substantial clinical relevance in pediatric infectious diseases. During infection, multiple forms of programmed cell death (PCD) may be induced, and this plays pivotal roles in viral replication, dissemination, and host immune responses, thereby profoundly influencing the viral life cycle and disease progression. On one hand, PCD facilitates the clearance of infected cells, restricts viral spread, and activates host immune defenses, thereby enhancing antiviral immunity. On the other hand, excessive or dysregulated cell death may lead to tissue damage and immune imbalance, creating a microenvironment conducive to viral replication and exacerbating disease severity. For instance, apoptosis-mediated by both extrinsic and intrinsic pathways-contributes to infection control but may also be hijacked by viruses to promote dissemination. Pyroptosis, driven by inflammasome activation, triggers lytic cell death and the release of pro-inflammatory cytokines. Necroptosis, mediated by the RIPK1-RIPK3-MLKL signaling axis, and pyroptosis both amplify innate immune responses but may concurrently induce inflammatory dysregulation. Immunogenic cell death (ICD), characterized by the release of damage-associated molecular patterns and neoantigens, activates antigen-specific immune responses and holds therapeutic potential for antiviral and antitumor interventions. Emerging evidence suggests that ferroptosis, through the modulation of iron metabolism and associated transporters, may also participate in viral replication and infected cell clearance. This review comprehensively summarizes the roles of apoptosis, pyroptosis, necroptosis, ICD, and ferroptosis in paramyxovirus infection, aiming to deepen the understanding of paramyxovirus pathogenesis and to provide insights for developing novel antiviral strategies.

Objectives: To analyze the global disease burden of cervical cancer and the association between screening coverage and the quality of disease management.

Methods: The data of global burden of cervical cancer 2021 and the data of cervical cancer screening 2019 were obtained from IHME Global Burden of Disease (GBD) and the WHO global health observatory, respectively. The age-standardized disease burden index was calculated, the quality of care index (QCI) was determined with principal component analysis, and the correlation between QCI and cervical cancer screening coverage was examined with linear regression analysis by regions and populations.

Results: The burden of cervical cancer and the quality of management exhibited significant variability across countries with differing levels of social development. The indicators of cervical cancer burden in China were close to the average level of countries with higher socio-demographic index (SDI). The global QCI was 22.22 (10.50, 35.43), and that of China was 26.30. The global screening coverage rate for cervical cancer was 42% (12%, 86%) and that in China was 31%. After adjusting for the social development level of countries, the coverage level of cervical cancer screening was associated with QCI (β=0.27, P<0.01), with no difference between low and high SDI countries (P>0.05). The association was significantly stronger among 25-30 years old women (β=1.48, P<0.05).

Conclusions: There are discrepancies in both the disease burden of cervical cancer and the quality of disease management among countries with different socioeconomic levels, and there is still considerable room for improvement in China. Expanding coverage of cervical cancer screening may be an effective strategy to enhance the management quality of cervical cancer, particularly among younger women where the screening benefits are most pronounced.

Objectives: To develop a risk prediction model for the transformation of chronic atrophic gastritis to high-grade intraepithelial neoplasia (HGIN) based on traditional Chinese medicine (TCM) syndrome patterns.

Methods: Clinical data of 201 chronic atrophic gastritis patients who visited the Second People's Hospital Affiliated to Fujian University of Traditional Chinese Medicine and Dong'erhuan Branch between January 2022 and March 2023 were retrospectively analyzed, including 32 patients with HGIN (HGIN group) and 169 patients with moderate and severe chronic atrophic gastritis (non-HGIN group). The information of demographic characteristics, dietary habits, lifestyle factors, social and psychosocial factors, family history of tumors, medical history and comorbidities, long-term medication, endoscopic findings, histopathological examination results, as well as TCM syndrome types were collected. Potential HGIN risk factors were screened using LASSO regression, and the significant risk factors for establishing an HGIN risk prediction model were identified using logistic regression analysis. The final model was visually presented using a nomogram, and its diagnostic performance was evaluated through receiver operating characteristic curve analysis.

Results: Spleen-stomach Qi deficiency was the most common TCM syndrome in both HGIN and non-HGIN groups. LASSO-logistic regression model analysis showed that heavy alcohol consumption (X1), syndrome of static blood in stomach collaterals (X2), low-grade intraepithelial neoplasia (X3), high-salt diet (X4), and age (X5) were independent risk factors related to the occurrence of HGIN, and the predictive model was ln［P/(1－P)］=2.159X1+2.230X2+1.664X3+2.070X4+0.122X5- 11.096. The model demonstrated good discriminative ability, calibration, and goodness-of-fit, with area under the curve values of 0.940 and 0.891 in the training and validation sets, respectively.

Conclusions: The TCM syndrome of static blood in stomach collaterals shows correlation with the transformation from chronic atrophic gastritis to HGIN. The HGIN prediction model based on TCM syndrome patterns developed in the study demonstrates potential value in clinical application.

Sertoli cells play an important role in the process of spermatogenesis, and the abnormalities in spermatogenesis are closely related to disruptions in glycolipid metabolism. The metabolic environment of Sertoli cells is hypoxic, with glycolysis and fatty acid β-oxidation being the primary metabolic pathways. In Sertoli cells, glycolysis produces lactate to provide energy for spermatogenic cells, while fatty acid β-oxidation generates ATP. Currently, the relationship between glycolipid metabolism in Sertoli cells and spermatogenic cell development, as well as the interplay between glucose and lipid metabolism remain unclear. Various hormones, including sex hormones, can affect glucose metabolism in Sertoli cells by endocrine regulation. The activation or inhibition of signaling pathways such as AMPK, mTOR, and Akt can alter the expression levels of glycolysis-related transporter genes and the synthesis of fatty acids, thereby affecting glycolipid metabolism in Sertoli cells. Some transcription factors such as PPARγ can regulate downstream fatty acid metabolism-related genes by directly binding to their response elements and promoting the oxidation of fatty acids in Sertoli cells. In this article we elaborate on the key factors influencing glycolipid metabolism in Sertoli cells and their interconnections, as well as their potential clinical implications, offering new insights for precisely targeted treatments of male infertility.

Structural valve deterioration (SVD) refers to intrinsic and irreversible pathological changes in the components of prosthetic heart valves, manifesting as fibrosis, calcification, wear and tear, loosening, as well as strut fracture or deformation of the valve framework. These changes ultimately lead to valve stenosis and/or regurgitation.The mechanisms may be related to mechanical stress, immune response and abnormal calcium-phosphorus metabolism. Studies have shown that risk factors for SVD include patient factors (such as age, underlying cardiovascular disease and comorbidities), valve factors (such as material properties, processing techniques, and valve type), and surgical factors (such as valve injury, suboptimal stent expansion, and irregular stent release morphology). Clinical imaging assessment of SVD demonstrates complementary advantages among echocardiography, multi-detector spiral CT and cardiac magnetic resonance imaging, with distinct diagnostic objectives. The primary management strategies for SVD after trans-catheter aortic valve replacement (TAVR) include drug therapy, redo-TAVR, surgical aortic valve replacement (SAVR) and the novel SURPLUS technique. Among them, redo-TAVR has become a common method because of its minimally invasive nature, but it is still necessary to further clarify the patient indications and optimize the surgical strategy. SAVR is reserved for young, low-risk patients; SURPLUS combines the advantages of SAVR and TAVR, making it suitable for cases where redo-TAVR is unfeasible or contraindicated, while the risk of SAVR is excessively high. This article reviews the latest progress of SVD following TAVR treatment to provide reference for research into the durability of bioprosthetic valve and clinical intervention of SVD.

Objectives: To analyze the early clinical outcomes of the Xcor^TM transcatheter aortic valve replacement (TAVR) system in treating severe aortic stenosis. This study has been registered at Chinese Clinical Trial Registry (ChiCTR2200065593).

Methods: This single-arm, prospective clinical trial enrolled patients with severe aortic stenosis treated with the Xcor^TM TAVR system at the Section of Heart Valve & Coronary Artery Surgery, Guangdong Provincial People's Hospital. Perioperative and follow-up parameters were compared to evaluate differences in hemodynamic outcomes. All-cause mortality, aortic regurgitation, paravalvular leakage, cerebrovascular events, and reoperation were analyzed.

Results: Thirty-two patients with severe aortic stenosis were included (20 males, 12 females), with (70.9±4.3) years old and a Society of Thoracic Surgeons (STS) score of 6.45% (6.07%, 7.28%). Notably, 87.5% of patients had New York Heart Association (NYHA) class≥Ⅲ. All patients underwent successful Xcor^TM bioprosthesis implantation, achieving an immediate technical success rate of 100.0% and device success rate of 96.9%. Mean aortic valve gradient decreased from (55.21±23.17) mmHg (1 mmHg=0.133 kPa) to (8.45±5.30) mmHg, peak aortic jet velocity decreased from (4.66±0.85) m/s to (1.99±0.48) m/s, aortic valve area increased from (0.66±0.21) cm² to (2.09±0.67) cm² (all P<0.01). Intraoperative ventricular fibrillation occurred in one patient, while one case exhibited moderate prosthetic valve regurgitation and paravalvular leakage post-procedure. At 12-month follow-up, sustained improvements were observed in cardiac function, left ventricular ejection fraction, hemodynamic parameters, and SF-12 quality-of-life scores (all P<0.01). All-cause mortality was 12.5% (4/32), with 13.8% (4/29) developing moderate paravalvular leakage.

Conclusions: The Xcor^TM TAVR system demonstrated favorable early outcomes in severe aortic stenosis patients, significantly improving symptoms and hemodynamics while exhibiting excellent performance in preventing malignant arrhythmias and coronary obstruction.

A 72-year-old patient with quadricuspid aortic valve underwent transcatheter aortic valve replacement due to severe valve stenosis accompanied by moderate insufficiency. As initially planned, the right coronary artery was protected during the procedure. However, after the artificial valve was released, the left coronary artery was found to be blocked, so a coronary protection stent was implanted in the left coronary artery ostium under the guidance of intravascular ultrasonography. This case indicates that for patients with a quadricuspid aortic valve undergoing transcatheter aortic valve replacement, in addition to preoperative measurement of the aortic root, attention should also be paid to the coronary artery obstruction caused by the displacement of the artificial valve frame during the procedure.

Objectives: To analyze the association between biological aging markers (phenotypic age and phenotypic age acceleration) and valvular heart diseases.

Methods: Research subjects who met the inclusion and exclusion criteria were selected from the UK Biobank from 2006 to 2010. The phenotypic age and phenotypic age acceleration were calculated. Cox multivariate analysis was used to examine the relationship between the aging markers and valvular heart diseases. Sensitivity analysis was conducted by removing missing values and subgroup analysis. The predictive accuracy of phenotypic age and phenotypic age acceleration for valvular heart diseases was analyzed using receiver operating characteristic (ROC) curves, and a clinical decision curve was generated based on logistic regression.

Results: A total of 411 687 subjects were included in the study, among whom there were 14 258 patients with valvular heart diseases. The overall median follow-up time was 12.80 years, the median follow-up time for patients with non-rheumatic aortic valve diseases (n=5238), non-rheumatic mitral valve diseases (n=4558), and non-rheumatic tricuspid valve diseases (n=411) were 12.82 years, 12.83 years and 12.84 years, respectively. After adjusting for demographic factors (gender, race, education, Townsend deprivation index), anthropometric factors (body mass index), lifestyle factors (smoking, alcohol consumption, Dietary Approaches to Stop Hypertension score), hypertension and hyperlipidemia, Cox multivariate analysis showed phenotypic age and phenotypic age acceleration were independent risk factors for valvular heart diseases, including non-rheumatic aortic valve diseases, non-rheumatic mitral valve diseases, and non-rheumatic tricuspid valve diseases (phenotypic age: corrected HR=1.04, P<0.01; phenotypic age acceleration: corrected HR=1.03, P<0.01), which was also confirmed by sensitivity analysis. ROC curves and clinical decision curves demonstrated that compared with the phenotypic age acceleration, phenotypic age had higher accuracy (the areas and the curves were 0.721 and 0.599) and higher net benefit in predicting valvular heart diseases. Moreover, compared with a single indicator, the combination of the two indicators had higher accuracy (the area under the curve was 0.725) and higher net benefit.

Conclusions: Phenotypic age and phenotypic age acceleration,as markers of biological aging, are independent risk factors for valvular heart diseases. Compared with phenotypic age acceleration, phenotypic age has a greater advantage in predicting valvular heart diseases. Overall, the combination of the two indicators offers a more effective approach for predicting valvular heart diseases.

Scar formation is characterized by dynamic alterations in collagen secretion, which critically determine scar morphology and pathological progression. In fibroblasts, collagen secretion is initiated through the activation of cytokine- and integrin-mediated signaling pathways, which promote collagen gene transcription. The procollagen polypeptide α chains undergo extensive post-translational modifications, including hydroxylation and glycosylation, within the endoplasmic reticulum (ER), followed by folding and assembly into triple-helical procollagen. Subsequent intracellular trafficking involves the sequential transport of procollagen through the ER, Golgi apparatus, and plasma membrane, accompanied by further structural refinements prior to extracellular secretion. Once secreted, procollagen is enzymatically processed to form mature collagen fibrils, which drive scar tissue remodeling. Recent advances in elucidating regulation of collagen secretion have identified pivotal molecular targets, such as transforming growth factor-beta 1 (TGF-β1), prolyl 4-hydroxylase (P4H), heat shock protein 47 (HSP47), and transport and Golgi organization protein 1 (TANGO1), providing novel therapeutic strategies to mitigate pathological scar hyperplasia and improve regenerative outcomes. This review provides a comprehensive analysis of the molecular mechanisms governing collagen secretion during scar formation, with emphasis on signaling cascades, procollagen biosynthesis, intracellular transport dynamics, and post-translational modifications, thereby offering a framework for developing targeted anti-scar therapies.

Objectives: To create a mixed valvular heart disease (MVHD)-related age-adjusted comorbidity index (MVACI) model for predicting mortality risk of patients with MVHD.

Methods: A total of 4080 patients with moderate or severe MVHD in the China-VHD study were included. The primary endpoint was 2-year all-cause mortality. A MVACI model prediction model was constructed based on the mortality risk factors identified by univariate and multivariate Cox regression analysis. Restricted cubic splines were used to assess the relationship between MVACI scores and 2-year all-cause mortality. The optimal threshold, determined by the maximum Youden index from receiver operator characteristic (ROC) curve analysis, was used to stratify patients. Kaplan-Meier method was used to calculate 2-year all-cause mortality and compared using the Log-rank test. Univariate and multivariate Cox proportional hazards models were employed to calculate hazard ratios (HR) and 95% confidence intervals (CI), evaluating the association between MVACI scores and mortality. Paired ROC curves were used to compare the discriminative ability of MVACI scores with the European System for Cardiac Operative Risk Evaluation Ⅱ(EuroSCORE Ⅱ) or the age-adjusted Charlson comorbidity index (ACCI) in predicting 2-year clinical outcomes, while calibration curves assessed the calibration of these models. Internal validation was performed using the Bootstrap method. Subgroup analyses were conducted based on etiology, treatment strategies, and disease severity.

Results: Multivariate analysis identified the following variables independently associated with 2-year all-cause mortality in patients: pulmonary hypertension, myocardiopathy, heart failure, low body weight (body mass index <18.5 kg/m²), anaemia, hypoalbuminemia, renal insufficiency, cancer, New York Heart Association (NYHA) class and age. The score was independently associated with the risk of all-cause mortality, and exhibited good discrimination (AUC=0.777, 95%CI: 0.755-0.799) and calibration (Brier score 0.062), with significantly better predictive performance than EuroSCORE Ⅱ or ACCI (both adjusted P<0.01). The internal validation showed that the MVACI model's predicted probability of 2-year all-cause mortality was generally consistent with the actual probability. The AUCs for predicting all-cause mortality risk were all above 0.750, and those for predicting adverse events were all above 0.630. The prognostic value of the score remained consistent in patients regardless of their etiology, therapeutic option, and disease severity.

Conclusions: The MVACI was constructed in this study based on age and comorbidities, and can be used for mortality risk prediction and risk stratification of MVHD patients. It is a simple algorithmic index and easy to use.