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Abstract Background Community-Acquired Pneumonia (CAP) remains a significant global health concern, with a subset of cases progressing to Severe Community-Acquired Pneumonia (SCAP). This study aims to develop and validate a CT-based radiomics model for the early detection of SCAP to enable timely intervention and improve patient outcomes. Methods A retrospective study was conducted on 115 CAP and SCAP patients at Southern Medical University Shunde Hospital from January to December 2021. Using the Pyradiomics package, 107 radiomic features were extracted from CT scans, refined via intra-class and inter-class correlation coefficients, and narrowed down using the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. The predictive performance of the radiomics-based model was assessed through receiver operating characteristic (ROC) analysis, employing machine learning classifiers such as k-Nearest Neighbors (KNN), Support Vector Machine (SVM), Logistic Regression (LR), and Random Forest (RF), trained and validated on datasets split 7:3, with a training set (n = 80) and a validation set (n = 35). Results The radiomics model exhibited robust predictive performance, with the RF classifier achieving superior precision and accuracy compared to LR, SVM, and KNN classifiers. Specifically, the RF classifier demonstrated a precision of 0.977 (training set) and 0.833 (validation set), as well as an accuracy of 0.925 (training set) and 0.857 (validation set), suggesting its superior performance in both metrics. Decision Curve Analysis (DCA) was utilized to evaluate the clinical efficacy of the RF classifier, demonstrating a favorable net benefit within the threshold ranges of 0.1 to 0.8 for the training set and 0.2 to 0.7 for the validation set. Conclusions The radiomics model developed in this study shows promise for early SCAP detection and can improve clinical decision-making.

Abstract Background In 2016, the “universal two-child” policy, allowing each couple to have two children, was introduced in China. The characteristic change of the long-term period after the implementation of the universal two-child policy was unclear. We studied trends in the obstetric characteristics and their potential impact on the rates of cesarean section and preterm birth in the era of China’s universal two-child policy. Methods A tertiary center-based study (2010–2021) retrospectively focused single high-risk pregnancies who delivered from the one-child policy period (OCP, 2010–2015) to the universal two-child policy period (TCP, 2016–2021). A total of 39, 016 pregnancies were enrolled. Maternal demographics, complications, delivery mode and obstetric outcomes were analyzed. Furthermore, logistic regression analysis was used to explore the association between the cesarean section rate, preterm birth and implementation of the universal two-child policy, adjusting maternal age, parity, and fetal distress. Results Ultimately a total of 39,016 pregnant women met the criteria and were included in this analysis. The proportion of women with advanced maternal age (AMA) increased from 14.6% in the OCP to 31.6% in the TCP. The number of multiparous women increased 2-fold in the TCP. In addition, the overall rate of cesarean section significantly decreased over the policy change, regardless of maternal age, whereas the risk of preterm birth significantly increased in the TCP. Adjusting for maternal age, parity and fetal distress, the universal two-child policy showed a significantly favorable impact on the cesarean section rate (RR 0.745, 95%CI (0.714–0.777), P

Abstract Background The morbidity and mortality of community-acquired pneumonia (CAP) remain high among infectious diseases. It was reported that angiopoietin-like 4 (ANGPTL4) could be a diagnostic biomarker and a therapeutic target for pneumonia. This study aimed to develop a more objective, specific, accurate, and individualized scoring system to predict the severity of CAP. Methods Totally, 31 non-severe community-acquired pneumonia (nsCAP) patients and 14 severe community-acquired pneumonia (sCAP) patients were enrolled in this study. The CURB-65 and pneumonia severity index (PSI) scores were calculated from the clinical data. Serum ANGPTL4 level was measured by enzyme-linked immunosorbent assay (ELISA). After screening factors by univariate analysis and receiver operating characteristic (ROC) curve analysis, multivariate logistic regression analysis of ANGPTL4 expression level and other risk factors was performed, and a nomogram was developed to predict the severity of CAP. This nomogram was further internally validated by bootstrap resampling with 1000 replications through the area under the ROC curve (AUC), the calibration curve, and the decision curve analysis (DCA). Finally, the prediction performance of the new nomogram model, CURB-65 score, and PSI score was compared by AUC, net reclassification index (NRI), and integrated discrimination improvement (IDI). Results A nomogram for predicting the severity of CAP was developed using three factors (C-reactive protein (CRP), procalcitonin (PCT), and ANGPTL4). According to the internal validation, the nomogram showed a great discrimination capability with an AUC of 0.910. The Hosmer–Lemeshow test and the approximately fitting calibration curve suggested a satisfactory accuracy of prediction. The results of DCA exhibited a great net benefit. The AUC values of CURB-65 score, PSI score, and the new prediction model were 0.857, 0.912, and 0.940, respectively. NRI comparing the new model with CURB-65 score was found to be statistically significant (NRI = 0.834, P

Abstract Background Wear resistance affects dental ceramics longevity and the functions of the opposing teeth. However, data for the effect of aqueous environment on wear resistance of dental ceramics are lacking. This study evaluated the effect of aqueous environment on wear resistance of typical dental glass–ceramics. Methods Disk specimens were prepared from lithium disilicate glass–ceramics (LD) and leucite reinforced glass–ceramics (LEU). The disk specimens paired with steatite antagonists were tested in a pin-on-disk tribometer under both wet and dry conditions with 10 N up to 500,000 wear cycles. The wear analysis of glass–ceramics was performed using a 3D profilometer after 100,000, 300,000 and 500,000 wear cycles. Wear morphologies were analyzed by employing scanning electron microscopy (SEM). The crystalline compositions of specimens stored in a dry environment and subsequently immersed in distilled water for 40 h were separately determined using X-ray diffraction (XRD). The chemical states of the wear surfaces for LD were analyzed by X-ray photoelectron spectroscopy (XPS). The data analysis and multiple pair-wise comparisons of means were performed by using one-way analysis of variance (ANOVA) and Tukey’s post-hoc test. Results LEU in a wet environment exhibited less wear volume loss than that in a dry environment (p

Abstract Background Circular RNAs (circRNAs) has emerged as vital regulator involved in various diseases. In this study, we identified and investigated the potential circRNAs involved in gestational diabetes mellitus (GDM). Methods High-throughput sequencing was used to collect the plasma circRNAs expression profiles of GDM patients. Quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) was used to measure the expressions of circ_0008285 and circ_0001173 in the plasma specimens. The Pearson’s correlation test was employed to assess the correlation between 2 circRNAs expression and the clinicopathologic data. Two circRNAs expression was verified in high glucose (HG)-induced HTR-8/SVneo cells. MTS, transwell assay was used to evaluate the effects of circ_0008285 expression on HG-induced HTR-8/SVneo cells. The network of circ_0008285 was constructed using cytocape. Results In GDM patients, the expression of circ_0008285 was significantly upregulated, while that of circ_0001173 was decreased. Circ_0008285 was significantly correlated with the total cholesterol and LDL-C levels. Circ_0001173 was significantly correlated with glycated hemoglobin. HG promoted the proliferation, invasion, and migration in HTR-8/SVneo cells, while the knockdown of circ_0008285 exerted reverse effects. In addition, network construction exhibited that circ_0008285 had 45 miRNA binding sites, which correlated with 444 mRNA. Conclusions circ_0008285 plays an important role and provides a clue for the usage of therapeutic targets in the development of GDM.