Self‐Powered Wireless Temperature Monitor System Based on Triboelectric Nanogenerator with Machine Learning

Triboelectric nanogenerator (TENG) can power wireless, real‐time sensing system with hybrid electromagnetic or piezoelectric power, or directly drive commercial LED without battery. However, it is a great challenge to directly drive wireless real‐time sensing system due to low energy density based on environment energy. Here, a self‐powered smart wireless temperature monitoring system that uses machine learning to accurately measure the ambient temperature is developed. A position modulation‐based TENG‐driven transmitter enables wireless communication and real‐time temperature monitoring. This machine learning‐based wireless sensor can accurately monitor the ambient temperature, with a recognition accuracy of up to 96.2%. This sensor architecture could potentially be used in low‐cost distributed sensors for environmental monitoring

DataSheet1_A metabolism-related gene signature for predicting the prognosis in thyroid carcinoma.docx

Metabolic reprogramming is one of the cancer hallmarks, important for the survival of malignant cells. We investigated the prognostic value of genes associated with metabolism in thyroid carcinoma (THCA). A prognostic risk model of metabolism-related genes (MRGs) was built and tested based on datasets in The Cancer Genome Atlas (TCGA), with univariate Cox regression analysis, LASSO, and multivariate Cox regression analysis. We used Kaplan-Meier (KM) curves, time-dependent receiver operating characteristic curves (ROC), a nomogram, concordance index (C-index) and restricted mean survival (RMS) to assess the performance of the risk model, indicating the splendid predictive performance. We established a three-gene risk model related to metabolism, consisting of PAPSS2, ITPKA, and CYP1A1. The correlation analysis in patients with different risk statuses involved immune infiltration, mutation and therapeutic reaction. We also performed pan-cancer analyses of model genes to predict the mutational value in various cancers. Our metabolism-related risk model had a powerful predictive capability in the prognosis of THCA. This research will provide the fundamental data for further development of prognostic markers and individualized therapy in THCA.</p

Applications of synchrotron-based X-ray diffraction in investigating thermal barrier coatings

Thermal barrier coatings play crucial roles in protecting the hot end components of aero-engines against high-temperature erosion. They must suffer extremely harsh environments including high temperatures, heavy loads, and large internal temperature gradients, which would result in various complex failures. Therefore, it is important to unveil these failure mechanisms to minimize and even prevent them for obvious reasons. Strain/stress evolution between different layers and foreign material erosion are the main failure mechanisms of thermal barrier coatings, which are well suited to be investigated using synchrotron X-ray diffraction. With its tunable energy, high flux, and many other advantages, synchrotron-based X-ray diffraction has become an advanced non-destructive characterization technique for engineering materials yielding important information including their compositions and residual stress which also provides spatial and temporal resolution that is vital for understanding their service performance. This paper presents a concise review of the applications of synchrotron-based X-ray diffraction in investigating thermal barrier coatings to explore their failure mechanisms

DataSheet_1_Gut microbiota and fecal metabolic signatures in rat models of disuse-induced osteoporosis.docx

BackgroundAssessing the correlation between gut microbiota (GM) and bone homeostasis has increasingly attracted research interest. Meanwhile, GM dysbiosis has been found to be associated with abnormal bone metabolism. However, the function of GM in disuse-induced osteoporosis (DIO) remains poorly understood. In our research, we evaluated the characteristics of GM and fecal metabolomics to explore their potential correlations with DIO pathogenesis.MethodsDIO rat models and controls (CON) underwent micro-CT, histological analyses, and three-point bending tests; subsequently, bone microstructures and strength were observed. ELISAs were applied for the measurement of the biochemical markers of bone turnover while GM abundance was observed using 16S rDNA sequencing. Metabolomic analyses were used to analyze alterations fecal metabolites. The potential correlations between GM, metabolites, and bone loss were then assessed.ResultsIn the DIO group, the abundance of GM was significantly altered compared to that in the CON group. Moreover, DIO significantly altered fecal metabolites. More specifically, an abnormally active pathway associated with bile acid metabolism, as well as differential bacterial genera related to bone/tissue volume (BV/TV), were identified. Lithocholic acid, which is the main secondary bile acid produced by intestinal bacteria, was then found to have a relationship with multiple differential bacterial genera. Alterations in the intestinal flora and metabolites in feces, therefore, may be responsible for DIO-induced bone loss.ConclusionsThe results indicated that changes in the abundance of GM abundance and fecal metabolites were correlated with DIO-induced bone loss, which might provide new insights into the DIO pathogenesis. The detailed regulatory role of GM and metabolites in DIO-induced bone loss needs to be explored further.</p