Development and validation of matrix metalloproteinase for predicting prognosis and tumour microenvironment immune profiles in uterine corpus endometrial carcinoma.

Background: Matrix metalloproteinases (MMPs) are involved in many processes of tumour progression and invasion. However, few studies have analysed the effects of MMP expression patterns on endometrial cancer (EC) development from the perspective of the tumour microenvironment (TME). we quantified MMP expression in individual by constructing an MMP score and found MMP score effectively predict the prognosis of EC patients. Methods: MMPs expression profiles were determined based on the differential expression of 12 MMP-related regulators. Principal component analysis (PCA) was used to construct an MMP scoring system which can quantify the MMPs expression patterns individually of EC patients. Kaplan-Meier analysis, the log-rank test, and time-dependent receiver operating characteristic (ROC) curve analysis were used to evaluate the value of MMPs expression in predicting prognosis. Single-cell RNA sequencing (scRNA-seq) dataset was used to verify correlation between MMPs and progression of EC. Gene Ontology (GO) analysis was used to investigate the pathways and functions underlying MMPs expression. Tumour immune dysfunction, exclusion prediction, and pharmacotherapy response analyses were performed to assess the potential response to pharmacotherapy based on MMPs patterns. Results: We downloaded the MMPs expression data, somatic mutation data and corresponding clinical information of EC patients from the TCGA website and ICGC portal. Based on the MMP-related differentially expressed genes (DEGs), the MMP score was constructed, and EC patients were divided into high and low MMP score groups. There was a positive correlation between MMP score and prognosis of EC patients. Patients with high MMP scores had better prognosis, more abundant immune cell infiltration and stronger antitumoor immunity. Although prognosis is worse with the lower group than the high, patients with low MMP score had better response to immunotherapy, which means they could prolong the survival time through Immunological checkpoint blockade (ICB) therapy. scRNA-seq analysis identified significant heterogeneity between MMP score and classical pathways in EC. Conclusion: Our work indicates that the MMP score could be a potential tool to evaluate MMP expression patterns, immune cell infiltration, response to pharmacotherapy, clinicopathological features, and survival outcomes in EC. This will provide the more effective guide to select immunotherapeutic strategies of EC in the future.

ILSHIP: An interpretable and predictive model for hypothyroidism.

Hypothyroidism is one of the common endocrine diseases, and its incidence is increasing year by year. Due to the insidious nature of this disease, it often leads to delayed treatment and even misdiagnosis. This paper proposes ILSHIP, an interpretable predictive model for hypothyroidism, to reduce its diagnostic complexity as well as improve the predictive performance and interpretability of existing models. First, the ILSHIP prediction model was built based on label encoding, missing value processing, feature selection, and data enhancement of the dataset. Second, the comprehensive performance of ILSHIP was compared with twelve existing related study models and eleven mainstream models, such as XGBoost and MLP. The experimental results showed that, based on the optimal hyperparameters the ILSHIP model can achieve 99.392%, 99.437%, 99.348%, 99.381%, and 99.960% in accuracy, recall, specificity, F1, and AUC, respectively. The accuracy of the ILSHIP model was about 0.7%-15.4% higher than the existing models. By introducing the SHAP framework into the ILSHIP model, important features affecting hypothyroidism such as thyroid stimulating hormone (TSH) and free thyroxine index (FTI) were also identified, and the influencing factors for different individuals were finally analyzed to provide a basis for medical personnel to monitor the condition.

DHDIP: An interpretable model for hypertension and hyperlipidemia prediction based on EMR data.

BACKGROUND AND OBJECTIVE: Traditional hypertension and hyperlipidemia prediction models suffer from uneven modeling data sources, small sample sizes, and a lack of uniform standards for the index system, resulting in the model failing to fulfill clinical applications. To address this issue, this work will offer DHDIP, an interpretable hypertension and hyperlipidemia prediction model based on EMR data. METHODS: First, we will select massive high-dimensional, unstructured EMR data as a unified modeling data source, and propose a pre-processing algorithm for EMR data to solve the problem that EMR data cannot be directly processed by machine learning algorithms. Second, a variety of mainstream models such as XGBoost, CatBoost, and RandomForest are selected for modeling, and the best adaptation algorithms are identified by performance comparison. Finally, the SHAP framework was introduced into the DHDIP model, thus identifying the main factors contributing to hypertension and hyperlipidemia, effectively enhancing the interpretability of the model. RESULTS: The DHDIP model's MSE value is 0.0285, and its LOSS value is 0.0054, both of which are better than previous studies. CONCLUSION: The model balances performance and interpretability. Multi-objective learning allows for a more thorough analysis and prediction of the condition, which not only lowers the cost of disease prediction but also aids physicians in clinical diagnosis. In addition, the datasets and source code are available from this link: https://github.com/Xiaoyao-Jia/DHDIP.

Mechanical Performance of Single-Graded Copolymer-Modified Pervious Concrete in a Corrosive Environment.

Polymer-modified cement has found numerous applications due to its excellent tensile strength. When cement was modified with a single polymer, its tensile strength and performance marginally increased. However, when a small amount of the flexible polymer latex was added to cement, the mechanical performance of cement considerably improved. In this study, single-graded copolymer-modified pervious concrete was prepared by mixing styrene-butadiene rubber (SBR) with different acrylate polymers, and its mechanical performance and durability were systematically studied through mechanical tests and theoretical analyses. The main findings are as follows: (1) When a waterborne emulsion was added, the freeze resistance of cement concrete increased, and its mass loss rate decreased. Cement concrete with two latexes had higher sulphate corrosion resistance and substantially lower dry shrinkage strain than ordinary cement concrete. (2) Through scanning electron microscopy, the microstructural changes in the cement binder, ordinary polymer-modified concrete, and the copolymer-modified cement concrete used in this study were observed, and the findings were compared with those reported in the literature. (3) Single-graded copolymer-modified pervious concrete exhibited excellent shrinkage performance. This study showed that single-graded copolymer-modified pervious concrete satisfied the performance requirements for use as a paving material for special cases.

Toughness Behavior of SBR Acrylate Copolymer-Modified Pervious Concrete with Single-Sized Aggregates.

Pervious concrete is an eco-efficient concrete but has problems regarding its mechanical performance and permeability balance. This research investigated the feasibility of using a combination of styrene-butadiene rubber (SBR) and acrylate polymer to improve the toughness of pervious concrete while keeping its permeability. Single-sized aggregate and no sand were considered in the concrete mixture. Acrylate polymers with different solid content, PH, density, and viscosity were emulsion copolymerized with an SBR polymer. Eleven scenarios with different mix proportions and 220 specimens for compressive strength, flexural strength, flexural stiffness, impact resistance, and fracture toughness tests were selected to evaluate the effects of the copolymer on the toughness of copolymer-modified pervious concrete (CMPC). The studies showed that (1) the influence trend of the copolymers generally varied according to different mechanical indexes; (2) XG-6001 acrylate polymer mainly and comprehensively enhanced the toughness of the CMPC; (3) it was difficult to increase the enhancing property of the XG-6001 acrylate polymer with the growth of its mix proportion; (4) the zero-sand pervious concrete with 90% SBR and 10% XG-6001 acrylate emulsion copolymerization proved to have relatively high toughness. The proposed CMPC holds promising application value in sustainability traffic road construction.