A general approach to composites containing nonmetallic fillers and liquid gallium

We report a versatile method to make liquid metal composites by vigorously mixing gallium (Ga) with non-metallic particles of graphene oxide (G-O), graphite, diamond, and silicon carbide that display either paste or putty-like behavior depending on the volume fraction. Unlike Ga, the putty-like mixtures can be kneaded and rolled on any surface without leaving residue. By changing temperature, these materials can be stiffened, softened, and, for the G-O-containing composite, even made porous. The gallium putty (GalP) containing reduced G-O (rG-O) has excellent electromagnetic interference shielding effectiveness. GalP with diamond filler has excellent thermal conductivity and heat transfer superior to a commercial liquid metal-based thermal paste. Composites can also be formed from eutectic alloys of Ga including Ga-In (EGaIn), Ga-Sn (EGaSn), and Ga-In-Sn (EGaInSn or Galinstan). The versatility of our approach allows a variety of fillers to be incorporated in liquid metals, potentially allowing filler-specific "fit for purpose" materials

Expression and Functional Analysis of Storage Protein 2 in the Silkworm, Bombyx mori

Storage protein 2 (SP2) not only is an important source of energy for the growth and development of silkworm but also has inhibitory effects on cell apoptosis. Endothelial cell (EC) apoptosis is an important contributing factor in the development of atherosclerosis; therefore, study of the antiapoptotic activity of SP2 on ECs provides information related to the treatment of atherosclerosis and other cardiovascular diseases. In this study, the sp2 gene was cloned and expressed in Escherichia coli to produce a 6xHis-tagged fusion protein, which was then used to generate a polyclonal antibody. Western blot results revealed that SP2 levels were higher in the pupal stage and hemolymph of fifth-instar larvae but low in the egg and adult stages. Subcellular localization results showed that SP2 is located mainly on the cell membrane. In addition, a Bac-to-Bac system was used to construct a recombinant baculovirus for SP2 expression. The purified SP2 was then added to a culture medium for human umbilical vein ECs (HUVECs), which were exposed to staurosporine. A cell viability assay demonstrated that SP2 could significantly enhance the viability of HUVEC. Furthermore, both ELISA and flow cytometry results indicated that SP2 has anti-apoptotic effects on staurosporine-induced HUVEC apoptosis

Development and validation of explainable machine-learning models for carotid atherosclerosis early screening

Abstract Background Carotid atherosclerosis (CAS), an important factor in the development of stroke, is a major public health concern. The aim of this study was to establish and validate machine learning (ML) models for early screening of CAS using routine health check-up indicators in northeast China. Methods A total of 69,601 health check-up records from the health examination center of the First Hospital of China Medical University (Shenyang, China) were collected between 2018 and 2019. For the 2019 records, 80% were assigned to the training set and 20% to the testing set. The 2018 records were used as the external validation dataset. Ten ML algorithms, including decision tree (DT), K-nearest neighbors (KNN), logistic regression (LR), naive Bayes (NB), random forest (RF), multiplayer perceptron (MLP), extreme gradient boosting machine (XGB), gradient boosting decision tree (GBDT), linear support vector machine (SVM-linear), and non-linear support vector machine (SVM-nonlinear), were used to construct CAS screening models. The area under the receiver operating characteristic curve (auROC) and precision-recall curve (auPR) were used as measures of model performance. The SHapley Additive exPlanations (SHAP) method was used to demonstrate the interpretability of the optimal model. Results A total of 6315 records of patients undergoing carotid ultrasonography were collected; of these, 1632, 407, and 1141 patients were diagnosed with CAS in the training, internal validation, and external validation datasets, respectively. The GBDT model achieved the highest performance metrics with auROC of 0.860 (95% CI 0.839–0.880) in the internal validation dataset and 0.851 (95% CI 0.837–0.863) in the external validation dataset. Individuals with diabetes or those over 65 years of age showed low negative predictive value. In the interpretability analysis, age was the most important factor influencing the performance of the GBDT model, followed by sex and non-high-density lipoprotein cholesterol. Conclusions The ML models developed could provide good performance for CAS identification using routine health check-up indicators and could hopefully be applied in scenarios without ethnic and geographic heterogeneity for CAS prevention

The Electromagnetic Absorption of a Na-Ethylenediamine Graphite Intercalation Compound

A sodium-ethylenediamine graphite intercalation compound (Na(ethylenediamine)C-15: "GIC") made from graphite flakes was used to study the microwave absorption performance of a GIC for the first time. Compared with the pristine graphite flakes, the neighboring layers in this GIC are pillared by Na(ethylenediamine)+ and possess a larger layer distance and improved electrical conductivity. Owing to the electrical conductivity of this GIC, only half of the loading content, compared to graphite flakes, is needed to achieve an outstanding absorption of -75.6 dB at 9.25 GHz (10.0 wt % GIC in paraffin in a 4.0 mm thick sample), but for graphite, 20.0 wt % is required for an absorption of -37.6 dB