Background: Emerging evidence suggests that the immune system plays a crucial role in the regulation of the response to therapy and long-term outcomes of patients with breast cancer (BRCA). In this study, we aimed to identify a significant signature based on immune-related genes to predict the prognosis of BRCA patients. Methods: The expression data were downloaded from The Cancer Genome Atlas (TCGA). The immune-related gene list, the transcription factor (TF) gene list, and the immune infiltrate scores of samples in the TCGA database were acquired from the ImmPort database, the Cistrome Cancer database, and the TIMER database, respectively. Univariate Cox regression analysis was utilized to identify prognostic immune-related differentially expressed genes (DEGs) (PIRDEGs) in BRCA. A prognostic immune signature containing 15 PIRDEGs in BRCA was established using the least absolute shrinkage and selection operator (LASSO) model with 1,000 iterations followed by a stepwise Cox proportional hazards model with a training set of 508 samples in TCGA. An independent assessment of the prognostic prediction ability of the signature was conducted using Kaplan-Meier survival analysis with a testing set of 505 samples in TCGA. Results: We identified 466 PIRDEGs and 80 TFs among the DEGs. A gene signature containing 15 PIRDEGs was constructed. Risk scores of BRCA patients were calculated using this model, which showed a high accuracy of prognosis prediction in both the training set and testing set and could be an independent prognostic factor of BRCA patients. Conclusions: Our study revealed that a PIRDEG signature could be a candidate prognostic biomarker for predicting the overall survival (OS) of patients with BRCA.
In most engineering applications, the coefficients of thermal expansion (CTEs) of different materials in integrated structures are inconsistent, especially for the thin-film multilayered coatings. Therefore, mismatched thermal deformation is induced due to temperature variation, which leads to an extreme temperature gradient, stress concentration, and damage accumulation. Controlling the CTEs of materials can effectively eliminate the thermally induced stress within the layered structures and thus considerably improve the mechanical reliability and service life. In this paper, randomly distributed fibers are incorporated into the matrix material and thus utilized to tune the material CTE from the macroscopical viewpoint. To this end, finite element (FE) modeling is proposed for fiber-reinforced matrix composites. In order to overcome the challenges of creating numerical models at a mesoscale, the random distribution of fibers in three-dimensional space is realized by proposing a fiber growth algorithm with the control of the in-plane and out-of-plane angles of fibers. The homogenization method is adopted to facilitate the FE simulations by using the representative volume element (RVE) of composite materials. Periodic boundary conditions (PBC) are applied to realize the prediction of the equivalent CTE of macroscopic composite materials with randomly distributed fibers. In the established FE model, the random distribution of carbon fibers in the matrix makes it possible to tune the CTE of the composite material by considering the orientation of fibers in the matrix. The FE predictions show that the volume fraction of carbon fibers in the composite materials is found to be crucial to macroscopic CTE, but results in minor variations in Young’s modulus and shear modulus. With the developed ABAQUS plug-in program, the proposed tuning method for CTE is promising to be standardized for industrial practice.
Background: In Asia, the incidence of uterine fibroids (UFs) in women is as high as 1.278%. However, there are few analyses of the prevalence and independent risk factors for bleeding and recurrence after laparoscopic myomectomy (LM). This study aimed to analyze the clinical characteristics of patients with UF and identify the independent risk factors for postoperative bleeding and recurrence after LM, so as to provide a reference basis for improving the quality of life of patients. Methods: Based on our exclusion and inclusion criteria, we retrospectively analyzed a total of 621 patients who developed UF from April 2018 to June 2021. The t-test, analysis of variance (ANOVA), and chisquare test were used to analyze the relationship between the clinical characteristics of the patients and postoperative bleeding as well as recurrence. Binary logistic regression was used to analyze the independent risk factors for the occurrence of postoperative bleeding and fibroid recurrence in patients. Results: The rates of postoperative bleeding and recurrence after LM for uterine fibroids were 4.5% and 7.1%, respectively. Binary logistic regression analysis showed that fibroid size [odds ratio (OR) =5.502, P=0.003], maximum fibroid type (OR =0.293, P=0.048), pathological type (OR =3.673, P=0.013), preoperative prothrombin time level (OR =1.340, P=0.003), preoperative hemoglobin level (OR =0.227, P=0.036), surgery time (OR =1.066, P=0.022), intraoperative bleeding (OR =1.145, P=0.007), and postoperative infection (OR =9.540, P=0.010) were independent risk factors for postoperative bleeding; meanwhile, body mass index (BMI) (OR =1.268, P=0.001), age of menarche (OR =0.780, P=0.013), fibroid size (OR =4.519, P=0.000), fibroid number (OR =2.381, P=0.033), maximum fibroid type (OR =0.229, P=0.001), pathological type (OR =2.963, P=0.008), preoperative delivery (OR =3.822, P=0.003), preoperative C-reactive protein (CRP) level (OR =1.162, P=0.005), intraoperative ultrasonography (OR =0.271, P=0.002), postoperative gonadotropin-releasing hormone agonist treatment (OR =2.407, P=0.029), and postoperative infection (OR =7.402, P=0.005) were independent risk factors for recurrence. Conclusions: At present, there is still a high probability of postoperative bleeding and recurrence after LM for UF. Clinical work should pay close attention to clinical features. Adequate preoperative examination to improve surgical precision, and strengthen postoperative care and education, thus reducing the probability of postoperative bleeding and recurrence in patients.
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