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The de Winter electrocardiogram (ECG) pattern indicates severe stenosis or occlusion of the left anterior descending artery (LAD). We present a 72-year-old female with 1.5-h chest pain. Angiography and optical coherence tomography (OCT) revealed 90 % LAD stenosis with plaque rupture, but no ST-segment elevation in the precordial leads. The de Winter pattern, characterized by upsloping ST-segment depression in V1-V6, appeared only in lead V2. Following successful percutaneous coronary intervention (PCI), the de Winter pattern disappeared. This case underscores the significance of the de Winter pattern in one precordial lead, necessitating prompt angiography and PCI for improved patient outcomes.

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Previous studies have suggested a potential association between allergic rhinitis (AR) and hypertension, but the genetic basis remains unclear. In this study, we aimed to explore the genetic correlation and potential causal association between AR and hypertension. Using a large-scale genome-wide association study (GWAS) public database, we conducted meticulous screening to acquire the most up-to-date GWAS data on single nucleotide polymorphisms (SNPs) relevant to AR and hypertension, with a significance threshold of P < 5 × 10-8. Then, we investigated the causal association between AR and hypertension through mendelian randomization (MR) analysis. We also performed reverse MR analysis to assess the possibility of reverse causality. Sensitivity analyses encompassed various factors, including horizontal pleiotropy, heterogeneity testing, and stepwise exclusion sensitivity checks. To investigate the causal relationship between AR and hypertension, we utilize the odds ratio (OR) and 95% confidence interval (CI) as our evaluative metric. This study leveraged a database comprising 112583 samples for AR and 461880 samples for hypertension. After meticulous screening, we identified 32 SNPs as instrumental variables. By employing the aforementioned 2-sample Mendelian randomization approaches, the estimated causal effects showed striking concordance. A discernible causal association between AR and hypertension was found using the IVW method (OR = 0.91, 95% CI: 0.86-0.98, P = .008), with horizontal pleiotropy and heterogeneity tests supporting the validity of our MR study. MR-Egger regression findings provided reassurance against bias stemming from genetic pleiotropy (intercept = -0.0006802, P = .6947). Interestingly, "leave-one-out" analysis yielded no evidence of nonspecific SNP influences, further consolidating our findings. Moreover, our reverse MR analysis yielded no indication of reverse causality from hypertension to AR, effectively discounting any influence from the latter on the former. Our study found evidence of a causal association between AR and hypertension in individuals of European ancestry. It demonstrated that AR reduced the risk of hypertension, suggesting a protective effect on hypertension due to the negative correlation with AR.

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Background: Insulin resistance(IR) and inflammation have been regarded as common potential mechanisms in coronary heart disease (CHD) and non-alcoholic fatty liver disease (NAFLD). Triglyceride-glucose (TyG) index is a novel biomarker of insulin resistance, System immune-inflammation index(SII) and Systemic inflammation response index(SIRI) are novel biomarkers of inflammation, these biomarkers have not been studied in CHD with NAFLD patients. This study investigated the correlation between the TyG index, SII index, and SIRI index and CHD risk among NAFLD patients. Methods: This cross-sectional study included 407 patients with NAFLD in the Department of Cardiology, The Second Hospital of Shanxi Medical University. Of these, 250 patients with CHD were enrolled in the NAFLD+CHD group and 157 patients without CHD were enrolled as NAFLD control. To balance covariates between groups, 144 patients were selected from each group in a 1:1 ratio based on propensity score matching (PSM). Potential influences were screened using Lasso regression analysis. Univariate and multivariate logistic regression analyses and the Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to assess independent risk and protective factors for CHD. Construction of nomogram using independent risk factors screened by machine learning. The receiver operating characteristic(ROC) curve was used to assess the ability of these independent risk factors to predict coronary heart disease. The relationship between the Gensini score and independent risk factors was reflected using the Sankey diagram. Results: The LASSO logistic regression analysis and Logistic regression analyses suggest that TyG index (OR, 2.193; 95% CI, 1.242-3.873; P = 0.007), SII index (OR, 1.002; 95% CI, 1.001-29 1.003; P <0.001), and SIRI index (OR,1.483;95%CI,1.058-2.079,P=0.022) are independent risk factors for CHD. At the same time, Neutrophils, TG, and LDL-C were also found to be independent risk factors in patients, HDL-C was a protective factor for CHD in patients with NAFLD. Further analysis using three machine learning algorithms found these independent risk factors to have good predictive value for disease diagnosis, SII index shows the highest predictive value. ROC curve analysis demonstrated that combining the SII index, SIRI index, and TyG index can improve the diagnostic ability of non-alcoholic liver cirrhosis patients with CHD.ROC curve analysis showed that the combined analysis of these independent risk factors improved the predictive value of CHD(AUC: 0.751; 95% CI: 0.704-0.798; P <0.001). Conclusion: TyG index, SII index, and SIRI index are all independent risk factors for CHD in patients with NAFLD and are strongly associated with prediction and the severity of CHD.

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Rolling bearing is an important part guaranteeing the normal operation of rotating machinery, which is also prone to various damages due to severe running conditions. However, it is usually difficult to extract the weak fault characteristic information from rolling bearing vibration signals and to realize a rolling bearing fault diagnosis. Hence, this paper offers a rolling bearing fault diagnosis method based on successive variational mode decomposition (SVMD) and the energy concentration and position accuracy (EP) index. Since SVMD decomposes a vibration signal of a rolling bearing into a number of modes, it is difficult to select the target mode with the ideal fault characteristic information. Comprehensively considering the energy concentration degree and frequency position accuracy of the fault characteristic component, the EP index is proposed to indicate the target mode. As the balancing parameter is crucial to the performance of SVMD and must be set properly, the line search method guided by the EP index is introduced to determine an optimal value for the balancing parameter of SVMD. The simulation and experiment results demonstrate that the proposed SVMD method is effective for rolling bearing fault diagnosis and superior to the variational mode decomposition (VMD) method.

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Gearboxes are widely used in drive systems of rotating machinery. The health status of gearboxes considerably influences the normal and reliable operation of rotating machinery. When a gearbox experiences tooth failure, a vibration signal with impulse features is excited. However, these impulse features tend to be relatively weak and difficult to extract. To solve this problem, a novel approach for gearbox fault feature extraction and fault diagnosis based on improved variational mode extraction (VME) is proposed. Since the initial value of the desired mode center frequency and the value of the penalty parameter in VME must be assigned, a short-time Fourier transform (STFT) was performed, and a new index, the standard deviation of differential values of envelope maxima positions (SDE), is proposed. The feasibility and effectiveness of the proposed approach was verified by a simulation signal and two datasets associated with a gearbox test bench. The results demonstrate that the VME-based approach outperforms the variational mode decomposition (VMD) approach.

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A visible-light-induced photoredox-catalyzed bromoetherification of alkenols is described. This approach, with CBr4 as the bromine source through generation of bromine in situ, provides a mild and operationally simple access to the synthesis of ß-bromotetrahydrofurans and -tetrahydropyrans with high efficiency and regioselectivity.