Development and validation of a nomogram to predict long-term cancer-specific survival for patients with osteosarcoma.

The present work aimed to establish a new model to accurately estimate overall survival (OS) as well as cancer-specific survival (CSS) of osteosarcoma. Osteosarcoma cases were collected from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2017 and randomized as training or validation sets. Then, the OS- and CSS-related variables were discovered through multivariate Cox regression analysis to develop new nomograms to predict the 1-, 3- and 5-year OS and CSS. Besides, consistency index (C-index), decision curve analysis (DCA), along with calibration curve were adopted for assessing the predicting ability of our constructed nomograms after calibrating for 1-, 3- and 5-year OS and CSS. Altogether, 1727 osteosarcoma cases were enrolled in the present study and randomly divided as training (n = 1149, 70%) or validation (n = 576, 30%) set. As shown by univariate as well as multivariate Cox regression analyses, age, grade, T stage, M stage, surgery, chemotherapy, and histological type were identified to be the adverse factors to independently predict OS and CSS among the osteosarcoma cases. Besides, based on results of multivariate Cox regression analysis, we constructed the OS and CSS prediction nomograms. The C-index in training set was 0.806 (95% CI 0.769-0.836) for OS nomogram and 0.807 (95% CI 0.769-0.836) for CSS nomogram. In the meantime, C-index value in validation set was 0.818 (95% CI 0.789-0.847) for OS nomogram, while 0.804 (95% CI 0.773-0.835) for CSS nomogram. Besides, those calibration curves regarding the 3- and 5-year CSS of our constructed nomogram were highly consistent between the predicted values and the measurements in the training set as well as the external validation set. Our constructed nomogram outperformed the TNM stage in prediction. Our constructed nomogram is facile, creditable, and feasible; it efficiently predicts OS and CSS for osteosarcoma cases and can assist clinicians in assessing the prognosis for individuals and making decisions.

SNHG10/miR-141-3p/WTAP axis promotes osteosarcoma proliferation and migration.

LncRNAs have been suggested to participate in the growth and metastasis of cancer through a variety of molecular mechanisms. Recently, SNHG10, a newly discovered lncRNA, is reported to play a role of an oncogene in osteosarcoma (OS) genesis. Nonetheless, the mechanism underlying OS remains unclear. The present work found that SNHG10 expression increased within OS cells and tissues, while suppressing its expression decreased OS cell proliferation, migration, invasion, but increased their apoptosis. As for the mechanism, we confirmed that SNHG10 could bind to miR-141-3p, while the latter could bind to WTAP. SNHG10 upregulated WTAP through decreasing miR-141-3p expression. More importantly, SNHG10 deletion remarkably reduced proliferation, migration, and invasion of cells, but accelerated their apoptosis. However, when cells were subjected to miR-141-3p inhibitor cotransfection or overexpressed WTAP, these effects were partially recovered. In summary, this study suggested that the expression of SNHG10 markedly elevated within OS, and the SNHG10/miR-141-3p/WTAP axis facilitated OS progression.

A Dual-Emission Nanohybrid of Gold Nanoclusters and Carbon Dots for Ratiometric Fluorescence Detection of Reactive Oxygen Species and Glucose.

Detecting reactive oxygen species (ROS) is critical for understanding the mechanisms of diseases. In this work, a convenient ratiometric fluorescent method for determination of ROS was developed basing on a nontoxic nanohybrid system which was constructed by carbon dots (CDs) and gold nanoclusters (Au NCs). The combination was prepared easily basing on self-assembly without any complex process, achieving maximum reservation of the two fluorescent properties. Thus the limit of detection (LOD) for hydrogen peroxide (H2O2) and hypochlorite (ClO-) was lower down to 0.1 µM after the experimental conditions were optimized. Being built to reflect H2O2, the test paper provided a method of convenient visual detection with double fluorescence of CDs/Au NCs. Furthermore, the biosensor was proven to be suitable for the detection of H2O2 and glucose (Glu) in human serum examples. The proportion of CDs and Au NCs was adjusted optionally to different color, while keeping the nanohybrid in high physiological stability and excellent biocompatibility. The excellent performance of this ratiometric biosensor is expected to facilitate further development of rapid and high-throughput detection of ROS.

Fast synthesis of fluorescent SiO2@CdTe nanoparticles with reusability in detection of H2O2.

In this study, highly fluorescent core/shell SiO2@CdTe nanoparticles (NPs) were synthesized conveniently and efficiently via a hydrothermal method. The as-prepared SiO2@CdTe NPs were uniform with good fluorescence preservation. The SiO2@CdTe NPs could be used for the rapid detection of H2O2 with good sensitivity within several minutes. Excellent linear relationships existed between the quenching degrees of the SiO2@CdTe NPs and the concentration of H2O2 in the range of 0.005 mM to 0.1 mM. The limit of detection (LOD) for H2O2 was 10 nM. Furthermore, it was proved that SiO2@CdTe NPs could be used repeatedly for H2O2 detection due to their easy separation, which is an important feature. The excellent performance of SiO2@CdTe NPs should facilitate their applications in chemistry or biology for detection of H2O2.