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Background: Previous epidemiological studies have reported associations between vitamin D and postpartum depression (PPD); however, the findings are inconsistent. This study employs bidirectional Mendelian Randomization (MR) to investigate the causal link between serum 25-hydroxyvitamin D [25(OH)D] levels and PPD. By utilizing genetic data from cohorts, this research aims to provide a more robust understanding of the potential relationship between vitamin D and PPD, addressing a critical gap in the current literature. Methods: A bidirectional MR analysis was conducted to investigate the genetic association between serum 25(OH)D and PPD using summary statistics extracted from GWAS datasets. The study included data from 15,668 patients with PPD and 376,755 healthy controls of European ancestry. The GWAS data for 25(OH)D were obtained from two studies within the UK Biobank, encompassing 496,946 and 79,366 participants. The primary analysis employed the inverse-variance weighted (IVW) method, while supplementary MR estimates were derived through the MR-Egger and weighted median (WME) methods. Furthermore, sensitivity analyses were implemented to ensure robustness and reliability, including Cochran's Q test, MR-PRESSO, MR-Egger intercept test, and the leave-one-out test. Results: The MR study revealed no substantial genetic correlation between serum 25(OH)D levels and PPD (OR = 1.065, 95%CI = 0.878-1.293, P = 0.522 for set A; OR = 0.978, 95 % CI = 0.669-1.430, P = 0.910 for set B). Additionally, in the reverse analysis, we did not observe a significant causal impact of PPD on serum 25(OH)D (OR = 1.001, 95%CI = 0.974-1.028, P = 0.951 for set A; OR = 1.011, 95%CI = 0.992-1.031, P = 0.261 for set B). The results obtained from MR-Egger and WME analyses concord with those derived from the IVW method. Conducting leave-one-out tests did not identify any single nucleotide polymorphism that might have influenced the MR results, confirming the robustness and reliability of the findings. Conclusions: The results suggest the absence of a causal link between vitamin D concentrations and PPD. Inconsistent observations in previous observational studies may be attributed to residual confounding.
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Objective and Impact Statement: High-intensity focused ultrasound (HIFU) therapy is a promising noninvasive method that induces coagulative necrosis in diseased tissues through thermal and cavitation effects, while avoiding surrounding damage to surrounding normal tissues. Introduction: Accurate and real-time acquisition of the focal region temperature field during HIFU treatment marked enhances therapeutic efficacy, holding paramount scientific and practical value in clinical cancer therapy. Methods: In this paper, we initially designed and assembled an integrated HIFU system incorporating diagnostic, therapeutic, and temperature measurement functionalities to collect ultrasound echo signals and temperature variations during HIFU therapy. Furthermore, we introduced a novel multimodal teacher-student model approach, which utilizes the shared self-expressive coefficients and the deep canonical correlation analysis layer to aggregate each modality data, then through knowledge distillation strategies, transfers the knowledge from the teacher model to the student model. Results: By investigating the relationship between the phantoms, in vitro, and in vivo ultrasound echo signals and temperatures, we successfully achieved real-time reconstruction of the HIFU focal 2D temperature field region with a maximum temperature error of less than 2.5 °C. Conclusion: Our method effectively monitored the distribution of the HIFU temperature field in real time, providing scientifically precise predictive schemes for HIFU therapy, laying a theoretical foundation for subsequent personalized treatment dose planning, and providing efficient guidance for noninvasive, nonionizing cancer treatment.
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The mechanism involved in the pathogenesis of endometriosis is poorly understood. The purpose of this study is to identify key deubiquitinating enzymes (DUBs) for endometriosis diagnosis and elucidate the possible mechanism, offering novel insights for noninvasive early diagnosis and treatment. Four gene expression datasets were employed from the Gene Expression Omnibus to identify differentially expressed genes (DEGs) between endometriosis and normal controls. GO and KEGG pathways were performed for enrichment analysis. Calibration curves, ROC, DCA, and clinical impact curves verified the clinical usefulness of the nomogram model. In addition, the ssGSEA method was conducted to estimate 23 types of immune cells. A specific DUB gene signature was constructed with Lasso regression, univariate logistic regression, and SVM analysis. RT-qPCR validated the expression of biomarkers. A total of 85 endometriosis-related DUBs were identified in the eutopic endometrium. Among them, 20 DUBs were found to be correlated with the severity of endometriosis. A diagnostic risk model based on five DUB-related genes (USP21, USP48, ZRANB1, COPS5, and EIF3F) was developed using lasso-cox regression analysis. The nomogram model exhibited a strong predictive ability to diagnose endometriosis. KEGG analysis revealed that ubiquitin-mediated proteolysis was activated in patients suffering from severe symptoms. Analysis of immune cell infiltration revealed a positive correlation between USP21 and multiple immune cells in the eutopic endometrium. However, EIF3F showed an opposite relationship. Dysregulation of DUBs was related to the immune microenvironment in endometriosis. Results from RT-qPCR confirmed the expression of DEGs in clinical samples. In summary, the diagnostic model for endometriosis constructed using five differentially expressed DUB genes demonstrates strong diagnostic capability, suggesting that these genes could serve as potential candidate biomarkers and therapeutic targets.
