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The aim of this study was to develop a model that could be used to forecast the bleeding risk of ITP based on proinflammatory and anti-inflammatory factors. One hundred ITP patients were recruited to build a new predictive nomogram, another eighty-eight ITP patients were enrolled as validation cohort, and data were collected from January 2016 to January 2019. Four demographic characteristics and fifteen clinical characteristics were taken into account. Eleven cytokines (IFN-γ, IL-1, IL-4, IL-6, IL-8, IL-10, IL-17A, IL-22, IL-23, TNF-α and TGF-β) were used to study and the levels of them were detected by using a cytometric bead array (CBA) human inflammation kit. The least absolute shrinkage and selection operator regression model was used to optimize feature selection. Multivariate logistic regression analysis was applied to build a new predictive nomogram based on the results of the least absolute shrinkage and selection operator regress ion model. The application of C-index, ROC curve, calibration plot, and decision curve analyses were used to assess the discrimination, calibration, and clinical practicability of the predictive model. Bootstrapping validation was used for testing and verifying the predictive model. After feature selection, cytokines IL-1, IL-6, IL-8, IL-23 and TGF-β were excluded, cytokines IFN-γ, IL-4, IL-10, IL-17A, IL-22, TGF-β, the count of PLT and the length of time of ITP were used as predictive factors in the predictive nomogram. The model showed good discrimination with a C-index of 0.82 (95% confidence interval 0.73376–0.90 624) in training cohortn and 0.89 (95% CI 0.868, 0.902) in validation cohort, an AUC of 0.795 in training cohort, 0.94 in validation cohort and good calibration. A high C-index value of 0.66 was reached in the interval validation assessment. Decision curve analysis showed that the bleeding risk nomogram was clinically useful when intervention was decided at the possibility threshold of 16–84%. The bleeding risk model based on IFN-γ, IL-4, IL-10, IL-17A, IL-22, TGF-β, the count of PLT and the length of time of ITP could be conveniently used to predict the bleeding risk of ITP.

Exosomes have shown increasing potential as delivery vesicles for therapy, but challenges like cost/yield, drug payload, and targeting specificity still exist. Plant derived exosome-like nanoparticles have been reported as a promising substitution and exhibit biocompatibility through oral, intranasal administration; however, systemic delivery of siRNA by exosome-like nanoparticles directly isolated from plants has not been reported. Recently, we reported the control of RNA orientation to decorate human derived exosome with cell targeting ligands for specific delivery of siRNA to tumors. Here, we expand to the application of arrowtail RNA nanoparticles for displaying ligands on ginger derived exosome-like nanovesicles (GDENs) for siRNA delivery and tumor inhibition through IV administration. Cushion ultracentrifugation coupled with equilibrium density gradient ultracentrifugation were used for purifying GDENs that displayed size, density, and morphology similar to human derived exosomes. Folic acid (FA), as a ligand, was displayed on the surface of GDENs for targeted delivery of survivin siRNA to KB cancer models. In vitro gene knockdown efficacy by FA-3WJ/GDENs/siRNA complex was comparable to transfection. We observed inhibition of tumor growth on a xenograft model by intravenous administration, which reveals the potential of GDENs as an economic delivery system for siRNA.

Ovarian cancer has a high death rate and is often not detected until late stages. While some studies found high expressions of MMPs correlated with cancer invasion, metastasis, and poor prognosis, however, several other studies indicated MMPs might inhibit cancer rather than promote cancer in certain situations. Thus, the role of different MMPs in different cancer types needs a systematic re-evaluation. In this study, we used RNA-Seq and corresponding clinical data downloaded from TCGA and analyzed the correlations between MMP expressions and the clinicopathologic characteristics and outcome in ovarian serous cystadenocarcinoma (OSC) patients. Among the MMPs investigated, MMP-3 was significantly increased in high-grade and high-stage tumors compared with low-grade and low-stage ones. Using univariate analysis and multivariate Cox model, high expressions of MMP-19 and -20 were found to associate with poor overall survival independent of clinicopathologic characteristics. Moreover, using in vitro studies, we found ovarian cancer cell lines with higher MMP-19 and -20 protein expressing levels were associated with anti-cancer drugs resistance, while knockdown of MMP-19 or -20 increased ovarian cancer cell sensitivities to several clinical using chemotherapy agents. Finally, knockdown of MMP-19 or -20 also decreased the invasion abilities of several ovarian cancer cell lines. These in vitro studies provided potential mechanisms of high MMP-19 and -20 expressions in the poor prognosis of ovarian cancer.

We developed a book-shaped triboelectric nanogenerator (TENG) that consists of electrospun polyvinylidene fluoride (PVDF) and poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) nanofibers to effectively harvest mechanical energy. The dispersed graphene oxide in the PVDF nanofibers acts as charge trapping sites, which increased the interface for charge storage as well as the output performance of the TENG. The book-shaped TENG was used as a direct power source to drive small electronics such as LED bulbs. This study proved that it is possible to improve the performance of TENGs using composite materials.

Mechanical actuators driven by water that respond to multiple stimuli, exhibit fast responses and large deformations and generate high stress have potential in artificial muscles, motors and generators. Meeting all these requirements in a single device remains a challenge. We report a graphene monolayer paper that undergoes reversible deformation. Its graphene oxide cells wrinkle and extend in response to water desorption and absorption, respectively. Its fast (~0.3 s), powerful (>100 MPa output stress, 7.5 × 105 N kg−1 unit mass force) and controllable actuation can be triggered by moisture, heat and light. The graphene monolayer paper has potential in artificial muscles, robotic hands and electromagnetic-free generators.

Graphene fibres are continuously prepared from universal graphene oxide precursors by a novel hydrogel-assisted spinning method. With assistance of a rolling process, meters of ribbon-like GFs, or GRs with improved conductivity, tensile strength, and a long-range ordered compact layer structure are successfully obtained. Furthermore, we refined our spinning process to obtained elastic GRs with a mixing microstructure and exceptional elasticity, which may provide a platform for electronic skins and wearable electronics, sensors, and energy devices.

Artificial skin, which mimics the functions of natural skin, will be very important in the future for robots used by humans in daily life. However, combining skin's pressure sensitivity and mechanical self-healing properties in a man-made material remains a challenging task. Here, we show that graphene and polymers can be integrated into a thin film which mimics both the mechanical self-healing and pressure sensitivity behavior of natural skin without any external power supply. Its ultimate strain and tensile strength are even two and ten times larger than the corresponding values of human skin, respectively. It also demonstrates highly stable sensitivity to a very light touch (0.02 kPa), even in bending or stretching states.