Single-Molecule Nanocatalysis Reveals Catalytic Activation Energy of Single Nanocatalysts

By monitoring the temperature-dependent catalytic activity of single Au nanocatalysts for a fluorogenic reaction, we derive the activation energies via multiple methods for two sequential catalytic steps (product formation and dissociation) on single nanocatalysts. The wide distributions of activation energies across multiple individual nanocatalysts indicate a huge static heterogeneity among the individual nanocatalysts. The compensation effect and isokinetic relationship of catalytic reactions are observed at the single particle level. This study exemplifies another function of single-molecule nanocatalysis and improves our understanding of heterogeneous catalysis

Observing the Heterogeneous Electro-redox of Individual Single-Layer Graphene Sheets

Electro-redox-induced heterogeneous fluorescence of an individual single-layer graphene sheet was observed in real time by a total internal reflection fluorescence microscope. It was found that the fluorescence intensity of an individual sheet can be tuned reversibly by applying periodic voltages to control the redox degree of graphene sheets. Accordingly, the oxidation and reduction kinetics of an individual single-layer graphene sheet was studied at different voltages. The electro-redox-induced reversible variation of fluorescence intensity of individual sheets indicates a reversible band gap tuning strategy. Furthermore, correlation analysis of redox rate constants on individual graphene sheets revealed a redox-induced spatiotemporal heterogeneity or dynamics of graphene sheets. The observed controllable redox kinetics can rationally guide the precise band gap tuning of individual graphene sheets and then help their extensive applications in optoelectronics and devices for renewable energy

Performance Comparison of Systematic Methods for Rigorous Definition of Coarse-Grained Sites of Large Biomolecules

Construction of coarse-grained (CG) models for large biomolecules used for multiscale simulations demands a rigorous definition of CG sites for them. Several coarse-graining methods such as the simulated annealing and steepest descent (SASD) based on the essential dynamics coarse-graining (ED-CG) or the stepwise local iterative optimization (SLIO) based on the fluctuation maximization coarse-graining (FM-CG), were developed to do it. However, the practical applications of these methods such as SASD based on ED-CG are subject to limitations because they are too expensive. In this work, we extend the applicability of ED-CG by combining it with the SLIO algorithm. A comprehensive comparison of optimized results and accuracy of various algorithms based on ED-CG show that SLIO is the fastest as well as the most accurate algorithm among them. ED-CG combined with SLIO could give converged results as the number of CG sites increases, which demonstrates that it is another efficient method for coarse-graining large biomolecules. The construction of CG sites for Ras protein by using MD fluctuations demonstrates that the CG sites derived from FM-CG can reflect the fluctuation properties of secondary structures in Ras accurately

Regeneration and Enhanced Catalytic Activity of Pt/C Electrocatalysts

By adding pure carbon support to improve the redispersion of platinum (Pt), a sintered Pt/C electrocatalyst for methanol electrooxidation was effectively regenerated in activity and doubled in amount on the basis of a one-step liquid oxychlorination. The apparent activity (mA mg_cata.^–1) of the optimal Pt/C regenerated (Pt 3.3 wt %) is close to the initial fresh Pt/C (Pt 10 wt %) and about two times that of fresh Pt/C (Pt 3.3 wt %), making Pt utilization doubled and then the resource-limited Pt potentially sustainable. The new nucleation of metal atoms on added pure support surface was found to be the key for both the improved redispersion of metal nanoparticles and the effective regeneration of catalytic activity in situ

Additional file 1 of Multi-functional conductive hydrogels based on heparin–polydopamine complex reduced graphene oxide for epidermal sensing and chronic wound healing

Additional file 1: Table S1. Content of various components in conductive hydrogel. Figure S1. Dispersion stability of different component nanosheets in water. Figure S2. Particle size distribution and potential of GO nanosheets in water. Table S2. Particle size and potential of rGO nanosheets at different ratios

Additional file 1 of Circulating levels of asprosin in children with obesity: a systematic review and meta-analysis

Supplementary Material 1

DataSheet2_Development and validation of an interpretable radiomic signature for preoperative estimation of tumor mutational burden in lung adenocarcinoma.PDF

Background:Tumor mutational burden (TMB) is a promising biomarker for immunotherapy. The challenge of spatial and temporal heterogeneity and high costs weaken its power in clinical routine. The aim of this study is to estimate TMB preoperatively using a volumetric CT–based radiomic signature (rMB).Methods:Seventy-one patients with resectable lung adenocarcinoma (LUAD) who underwent whole-exome sequencing (WXS) from 2011 to 2014 were enrolled from the institutional biobank of Tianjin Medical University Cancer Institute and Hospital (TMUCIH). Forty-nine LUAD patients with WXS from the Cancer Genome Atlas Program (TCGA) served as the external validation cohort. Computed tomography (CT) volumes were resampled to 1-mm isotropic, semi-automatically segmented, and manually adjusted by two radiologists. A total of 3,108 radiomic features were extracted via PyRadiomics and then harmonized across cohorts by ComBat. Features with inter-segmentation intra-class correlation coefficient (ICC) > 0.8, low collinearity, and significant univariate power were passed to the least absolute shrinkage and selection operator (LASSO)–logistic classifier to discriminate TMB-high/TMB-low at a threshold of 10 mut/Mb. The receiver operating characteristic (ROC) curve analysis and calibration curve were used to determine its efficiency. Shapley values (SHAP) attributed individual predictions to feature contributions. Clinical variables and circulating biomarkers were collected to find potential associations with TMB and rMB.Results:The top frequently mutated genes significantly differed between the Chinese and TCGA cohorts, with a median TMB of 2.20 and 3.46 mut/Mb and 15 (21.12%) and 9 (18.37%) cases of TMB-high, respectively. After dimensionality reduction, rMB comprised 21 features, which reached an AUC of 0.895 (sensitivity = 0.867, specificity = 0.875, and accuracy = 0.873) in the discovery cohort and 0.878 (sensitivity = 1.0, specificity = 0.825, and accuracy = 0.857 in a consist cutoff) in the validation cohort. rMB of TMB-high patients was significantly higher than rMB of TMB-low patients in both cohorts (p Conclusion:rMB, an intra-tumor radiomic signature, could predict lung adenocarcinoma patients with higher TMB. Insights from the Shapley values may enhance persuasiveness of the purposed signature for further clinical application. rMB could become a promising tool to triage patients who might benefit from a next-generation sequencing test.</p

Single-Molecule Nanocatalysis of Pt Nanoparticles

Because of the inhomogeneous structure of nanoparticles, many underlying catalytic details of these catalysts are hidden in the ensemble-averaged measurements. The single-molecule approach enables studying the catalytic behavior of nanoparticles at the single-particle level in single-turnover resolution. Here, on the basis of such a method, we study the catalytic behaviors of individual Pt nanoparticles to reveal the catalytic properties of nanoparticles of the product formation and desorption process. It is found that the catalytic reaction on Pt nanoparticles follows competitive mechanism in product formation process, while the product desorption process shows no selectivity between the indirect and direct desorption pathways. Moreover, the dynamic heterogeneity of Pt nanoparticles in product formation and desorption process is revealed to be due to the catalysis-induced surface restructuring. Surprisingly, it is found both experimentally and theoretically that the tiny difference in substrate molecules could lead to a huge difference in surface restructuring even on the same type of nanoparticle

DataSheet1_Development and validation of an interpretable radiomic signature for preoperative estimation of tumor mutational burden in lung adenocarcinoma.XLSX

Background:Tumor mutational burden (TMB) is a promising biomarker for immunotherapy. The challenge of spatial and temporal heterogeneity and high costs weaken its power in clinical routine. The aim of this study is to estimate TMB preoperatively using a volumetric CT–based radiomic signature (rMB).Methods:Seventy-one patients with resectable lung adenocarcinoma (LUAD) who underwent whole-exome sequencing (WXS) from 2011 to 2014 were enrolled from the institutional biobank of Tianjin Medical University Cancer Institute and Hospital (TMUCIH). Forty-nine LUAD patients with WXS from the Cancer Genome Atlas Program (TCGA) served as the external validation cohort. Computed tomography (CT) volumes were resampled to 1-mm isotropic, semi-automatically segmented, and manually adjusted by two radiologists. A total of 3,108 radiomic features were extracted via PyRadiomics and then harmonized across cohorts by ComBat. Features with inter-segmentation intra-class correlation coefficient (ICC) > 0.8, low collinearity, and significant univariate power were passed to the least absolute shrinkage and selection operator (LASSO)–logistic classifier to discriminate TMB-high/TMB-low at a threshold of 10 mut/Mb. The receiver operating characteristic (ROC) curve analysis and calibration curve were used to determine its efficiency. Shapley values (SHAP) attributed individual predictions to feature contributions. Clinical variables and circulating biomarkers were collected to find potential associations with TMB and rMB.Results:The top frequently mutated genes significantly differed between the Chinese and TCGA cohorts, with a median TMB of 2.20 and 3.46 mut/Mb and 15 (21.12%) and 9 (18.37%) cases of TMB-high, respectively. After dimensionality reduction, rMB comprised 21 features, which reached an AUC of 0.895 (sensitivity = 0.867, specificity = 0.875, and accuracy = 0.873) in the discovery cohort and 0.878 (sensitivity = 1.0, specificity = 0.825, and accuracy = 0.857 in a consist cutoff) in the validation cohort. rMB of TMB-high patients was significantly higher than rMB of TMB-low patients in both cohorts (p Conclusion:rMB, an intra-tumor radiomic signature, could predict lung adenocarcinoma patients with higher TMB. Insights from the Shapley values may enhance persuasiveness of the purposed signature for further clinical application. rMB could become a promising tool to triage patients who might benefit from a next-generation sequencing test.</p

Single-Molecule Nanocatalysis of Pt Nanoparticles

Because of the inhomogeneous structure of nanoparticles, many underlying catalytic details of these catalysts are hidden in the ensemble-averaged measurements. The single-molecule approach enables studying the catalytic behavior of nanoparticles at the single-particle level in single-turnover resolution. Here, on the basis of such a method, we study the catalytic behaviors of individual Pt nanoparticles to reveal the catalytic properties of nanoparticles of the product formation and desorption process. It is found that the catalytic reaction on Pt nanoparticles follows competitive mechanism in product formation process, while the product desorption process shows no selectivity between the indirect and direct desorption pathways. Moreover, the dynamic heterogeneity of Pt nanoparticles in product formation and desorption process is revealed to be due to the catalysis-induced surface restructuring. Surprisingly, it is found both experimentally and theoretically that the tiny difference in substrate molecules could lead to a huge difference in surface restructuring even on the same type of nanoparticle