Emerging evidence supports that stem cells are regulated by both intrinsic and extrinsic mechanisms. However, factors that determine the fate of stem cells remain incompletely understood. The Drosophila testis provides an exclusive powerful model in searching for potential important regulatory factors and their underlying mechanisms for controlling the fate of germline stem cells (GSCs). In this study, we have found that Drosophila gilgamesh (gish), which encodes a homologue of human CK1-γ (casein kinase 1-gamma), is required intrinsically for GSC maintenance. Our genetic analyses indicate gish is not required for Dpp/Gbb signaling silencing of bam and is dispensable for Dpp/Gbb signaling-dependent Dad expression. Finally, we show that overexpression of gish fail to dramatically increase the number of GSCs. These findings demonstrate that gish controls the fate of GSCs in Drosophila testis by a novel Dpp/Gbb signaling-independent pathway.

The synthesis of ultrasmall-sized nanoparticles (NPs) has attracted serious attention in the past several years because of the largely increased surface-to-volume ratio of these NPs. Ligands are necessarily used to synthesize these NPs. However, the traditional ligands employed in the colloidal synthesis process would be strongly adsorbed on the surface of the metal NPs, leading to incomplete exposure of catalytically active sites. Here, we develop an efficient solid-state method to synthesize carbon-supported extrasmall ligand-free Pt nanoparticles (Pt SNPs/C) or Pd SNPs/C on a large scale (up to gram equivalent). The strong interfacial interaction between the modified carbon support and inorganometallic precursor is believed to successfully prepare this Pt SNPs/C catalyst. In particular, the fabricated Pt SNPs/C catalyst is ligand-free, which is carefully verified by different techniques (thermogravimetric analysis, X-ray photoelectron spectroscopy, and "electrochemical surface area (ECSA)" measurement). Because of the higher ECSA, Pt SNPs/C exhibits better catalytic activities toward methanol oxidation and hydrogen evolution than commercial Pt/C. By applying the catalyst as both the anode and cathode in a methanol-assisted water splitting system, the cell displays much better efficiency to produce highly valued hydrogen compared to that of commercial Pt/C components.

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BackgroundThe study aimed to investigate the prognostic factors of spinal cord astrocytoma (SCA) and establish a nomogram prognostic model for the management of patients with SCA.MethodsPatients diagnosed with SCA between 1975 and 2016 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training and testing datasets (7:3). The primary outcomes of this study were overall survival (OS) and cancer-specific survival (CSS). Cox hazard proportional regression model was used to identify the prognostic factors of patients with SCA in the training dataset and feature importance was obtained. Based on the independent prognostic factors, nomograms were established for prognostic prediction. Calibration curves, concordance index (C-index), and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the calibration and discrimination of the nomogram model, while Kaplan-Meier (KM) survival curves and decision curve analyses (DCA) were used to evaluate the clinical utility. Web-based online calculators were further developed to achieve clinical practicability.ResultsA total of 818 patients with SCA were included in this study, with an average age of 30.84 ± 21.97 years and an average follow-up time of 117.57 ± 113.51 months. Cox regression indicated that primary site surgery, age, insurance, histologic type, tumor extension, WHO grade, chemotherapy, and post-operation radiotherapy (PRT) were independent prognostic factors for OS. While primary site surgery, insurance, tumor extension, PRT, histologic type, WHO grade, and chemotherapy were independent prognostic factors for CSS. For OS prediction, the calibration curves in the training and testing dataset illustrated good calibration, with C-indexes of 0.783 and 0.769. The area under the curves (AUCs) of 5-year survival prediction were 0.82 and 0.843, while 10-year survival predictions were 0.849 and 0.881, for training and testing datasets, respectively. Moreover, the DCA demonstrated good clinical net benefit. The prediction performances of nomograms were verified to be superior to that of single indicators, and the prediction performance of nomograms for CSS is also excellent.ConclusionsNomograms for patients with SCA prognosis prediction demonstrated good calibration, discrimination, and clinical utility. This result might benefit clinical decision-making and patient management for SCA. Before further use, more extensive external validation is required for the established web-based online calculators.