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Tuning metal–support interaction has been considered as an effective approach to modulate the electronic structure and catalytic activity of supported metal catalysts. At the atomic level, the understanding of the structure–activity relationship still remains obscure in heterogeneous catalysis, such as the conversion of water (alkaline) or hydronium ions (acid) to hydrogen (hydrogen evolution reaction, HER). Here, we reveal that the fine control over the oxidation states of single-atom Pt catalysts through electronic metal–support interaction significantly modulates the catalytic activities in either acidic or alkaline HER. Combined with detailed spectroscopic and electrochemical characterizations, the structure–activity relationship is established by correlating the acidic/alkaline HER activity with the average oxidation state of single-atom Pt and the Pt–H/Pt–OH interaction. This study sheds light on the atomic-level mechanistic understanding of acidic and alkaline HER, and further provides guidelines for the rational design of high-performance single-atom catalysts. Insights into the rational design of single-atom metal catalysts remains obscure in heterogeneous catalysis. Here, the authors establish the atomic-level structure–activity relationship for a wide-pH-range hydrogen evolution reaction through the electronic metal–support interaction modulation.

A method is described for the determination of ascorbic acid (AA) in complex biological fluids. It based on maganese(II)-doped zinc/germanium oxide nanoparticles (Mn@ZnGe NPs) with appealing time-resolved phosphorescence (TRP). TRP can provide a background-free reporter signal in analytical methods. The absorption of AA overlaps the excitation band of Mn@ZnGe NPs at 254 nm. This reduces the intensity of fluorescence via an inner filter effect (IFE) with increasing concentration of AA. Typical experimental conditions include an emission peak at 536 nm, a delay time of 50 μs and a counting time of 2 ms. This method can detect AA in a range of 5–500 μM with a 0.13 μM limit of detection. If AA is oxidized by the enzyme AA oxidase (AAOx), dehydroascorbic acid will be formed which doesn’t absorb at 254 nm. Hence, the IFE cannot occur and fluorescence is not reduced. The strategy can be used to quantify AAOx in the activity range of 1–4 U·mL −1 . By using a handheld UV lamp and a smart phone with a color-scanning feature, the feasibility for visual detection and real-time/onsite quantitative scanometric monitoring of AA and AAOx is demonstrated. Graphical abstract Schematic presentation of a fluorometric method for determination of ascorbic acid (AA) and ascorbic oxidase and a scanometric visual assay. It based on the use of maganese(II)-doped zinc/germanium oxide nanoparticles (Mn@ZnGe NPs) with appealing time-resolved phosphorescence (TRP) and the inner-filter effect (IFE) between AA and Mn@ZnGe NPs.

N7-methylguanosine (m7G) is one of the most common RNA posttranscriptional modifications; however, its potential role in hepatocellular carcinoma (HCC) remains unknown. We developed a prediction signature based on m7G-related long noncoding RNAs (lncRNAs) to predict HCC prognosis and provide a reference for immunotherapy and chemotherapy. RNA-seq data from The Cancer Genome Atlas (TCGA) database and relevant clinical data were used. Univariate and multivariate Cox regression analyses were conducted to identify m7G-related lncRNAs with prognostic value to build a predictive signature. We evaluated the prognostic value and clinical relevance of this signature and explored the correlation between the predictive signature and the chemotherapy treatment response of HCC. Moreover, an in vitro study to validate the function of CASC19 was performed. Six m7G-related lncRNAs were identified to create a signature. This signature was considered an independent risk factor for the prognosis of patients with HCC. TIDE analyses showed that the high-risk group might be more sensitive to immunotherapy. ssGSEA indicated that the predictive signature was strongly related to the immune activities of HCC. HCC in high-risk patients was more sensitive to the common chemotherapy drugs bleomycin, doxorubicin, gemcitabine, and lenalidomide. In vitro knockdown of CASC19 inhibited the proliferation, migration and invasion of HCC cells. We established a 6 m7G-related lncRNA signature that may assist in predicting the prognosis and response to chemotherapy and immunotherapy of HCC.

[This corrects the article DOI: 10.1371/journal.pone.0289552.].

Increasing evidence suggests that immune modulation contributes to the pathogenesis and progression of diabetic nephropathy (DN). However, the role of immune modulation in DN has not been elucidated. The purpose of this study was to search for potential immune-related therapeutic targets and molecular mechanisms of DN. Gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database. A total of 1793 immune-related genes were acquired from the Immunology Database and Analysis Portal (ImmPort). Weighted gene co-expression network analysis (WGCNA) was performed for GSE142025, and the red and turquoise co-expression modules were found to be key for DN progression. We utilized four machine learning algorithms, namely, random forest (RF), support vector machine (SVM), adaptive boosting (AdaBoost), and k-nearest neighbor (KNN), to evaluate the diagnostic value of hub genes. Immune infiltration patterns were analyzed using the CIBERSORT algorithm, and the correlation between immune cell type abundance and hub gene expression was also investigated. A total of 77 immune-related genes of advanced DN were selected for subsequent analyzes. Functional enrichment analysis showed that the regulation of cytokine-cytokine receptor interactions and immune cell function play a corresponding role in the progression of DN. The final 10 hub genes were identified through multiple datasets. In addition, the expression levels of the identified hub genes were corroborated through a rat model. The RF model exhibited the highest AUC. CIBERSORT analysis and single-cell sequencing analysis revealed changes in immune infiltration patterns between control subjects and DN patients. Several potential drugs to reverse the altered hub genes were identified through the Drug-Gene Interaction database (DGIdb). This pioneering work provided a novel immunological perspective on the progression of DN, identifying key immune-related genes and potential drug targets, thus stimulating future mechanistic research and therapeutic target identification for DN.

Elemental Carbon (EC) has a significant impact on human health and climate change. In order to evaluate the size segregation of EC emission in the EUCAARI inventory and investigate its influence on the simulation of EC long-range transportation in Europe, we used the fully coupled online Weather Research and Forecasting/Chemistry model (WRF-Chem) at a resolution of 2 km focusing on a region in Germany, in conjunction with a high-resolution EC emission inventory. The ground meteorology conditions, vertical structure and wind pattern were well reproduced by the model. The simulations of particle number and/or mass size distributions were evaluated with observations at the central European background site Melpitz. The fine mode particle concentration was reasonably well simulated, but the coarse mode was substantially overestimated by the model mainly due to the plume with high EC concentration in coarse mode emitted by a nearby point source. The comparisons between simulated EC and Multi-angle Absorption Photometers (MAAP) measurements at Melpitz, Leipzig-TROPOS and Bösel indicated that the coarse mode EC (ECc) emitted from the nearby point sources might be overestimated by a factor of 2–10. The fraction of ECc was overestimated in the emission inventory by about 10–30 % for Russia and 5–10 % for Eastern Europe (e.g., Poland and Belarus). This incorrect size-dependent EC emission results in a shorter atmospheric life time of EC particles and inhibits the long-range transport of EC. A case study showed that this effect caused an underestimation of 20–40 % in the EC mass concentration in Germany under eastern wind pattern.

In this paper we introduce the concepts of well-posedness and generalized well-posedness for a system of equilibrium problems. We derive a metric characterization of well-posedness by considering the diameter of approximating solution set and a Furi-Vignoli type characterization of generalized well-posedness by considering the Kuratowski noncompactness measure of approximating solution set. Under suitable conditions, we prove that the well-posedness of a system of equilibrium problems is equivalent to the existence and uniqueness of its solution.

N7-methylguanosine (m7G) is one of the most common RNA posttranscriptional modifications; however, its potential role in hepatocellular carcinoma (HCC) remains unknown. We developed a prediction signature based on m7G-related long noncoding RNAs (lncRNAs) to predict HCC prognosis and provide a reference for immunotherapy and chemotherapy. RNA-seq data from The Cancer Genome Atlas (TCGA) database and relevant clinical data were used. Univariate and multivariate Cox regression analyses were conducted to identify m7G-related lncRNAs with prognostic value to build a predictive signature. We evaluated the prognostic value and clinical relevance of this signature and explored the correlation between the predictive signature and the chemotherapy treatment response of HCC. Moreover, an in vitro study to validate the function of CASC19 was performed. Six m7G-related lncRNAs were identified to create a signature. This signature was considered an independent risk factor for the prognosis of patients with HCC. TIDE analyses showed that the high-risk group might be more sensitive to immunotherapy. ssGSEA indicated that the predictive signature was strongly related to the immune activities of HCC. HCC in high-risk patients was more sensitive to the common chemotherapy drugs bleomycin, doxorubicin, gemcitabine, and lenalidomide. In vitro knockdown of CASC19 inhibited the proliferation, migration and invasion of HCC cells. We established a 6 m7G-related lncRNA signature that may assist in predicting the prognosis and response to chemotherapy and immunotherapy of HCC.