The application of synthetic polypeptides is greatly limited by the difficulty of the purification and polymerization of N-carboxyanhydrides (NCAs). Here, we report a streamlined, controlled synthesis of polypeptides directly from amino acids, avoiding the NCA purification, by adding small-molecular amine scavengers (AS) in situ to efficiently eliminate the remaining organic impurities in the emulsion polymerization system. Such a process enables controlled synthesis of PEG-containing, homo, block, and random polypeptides in a highly consistent manner under open-air condition, directly from amino acid derivatives in various formats and independent of NCA preparation methods.

The development of an efficient electrocatalyst for the hydrogen evolution reaction (HER) in alkaline media is of vital importance to water electrolysis. Herein, a facile surface reconstruction strategy of microwave radiation oxidation is reported to fabricate cobalt phosphide (CoP) multishelled hollow spheres with an amorphous cobalt oxide (CoO x ) species coating layer (denoted as CoP@CoO x ). The synergistic effect between multishelled hollow-structured CoP and amorphous CoO x can trigger strong electronic modulation on the heterointerface, leading to the increased electrochemical active surface area, the improved charge transfer, and the modification of the electronic structure. As a result, the significant improvements in the catalytic activity, long-term stability, and efficiency are achieved compared with pristine CoP. Especially, the CoP@CoO x composite by microwave radiation oxidation for 6 min on nickel foam (NF) displays significantly enhanced HER activity with a low overpotential of 35 mV at a current density of 10 mA cm–2 and, even more remarkably, of 109 mV at ultrahigh current density of 100 mA cm–2. The concept of interfacial electronic modulation by surface reconstruction can offer a unique approach for the rational design of hydrogen evolution catalysts and beyond.

This study aimed to explore the risk factors of bone mineral density (BMD) in American residents and further analyse the extent of effects, to provide preventive guidance for maintenance of bone health. A cross-sectional study analysis was carried out in this study, of which data validity was identified and ethics approval was exempted based on the National Health and Nutrition Examination Survey (NHANES) database. Candidates’ demographics, physical examination, laboratory indicators and part of questionnaire information were collected and merged from NHANES in 2015–2016 and 2017–2018. The least absolute shrinkage selection operator (lasso) was used to select initial variables with “glmnet” package of R, quantile regression model to analyze influence factors of BMD and their effects in different sites with “qreg” code in Stata. Among 2937 candidates, 17 covariates were selected by lasso regression (λ = 0.00032) in left arm BMD, with 16 covariates in left leg BMD (λ = 0.00052) and 14 covariates in total BMD (λ = 0.00065). Quantile regression results displayed several factors with different coefficients in separate sites and quantiles: gender, age, educational status, race, high-density lipoprotein (HDL), total cholesterol (TC), lead, manganese, ethyl mercury, smoking, alcohol use and body mass index (BMI) (p < 0.05). We constructed robust regression models to conclude that some demographic characteristics, nutritional factors (especially lipid levels, heavy metals) and unhealthy behaviors affected BMD in varying degrees. Gender and race differences, Low-fat food intake and low exposure to heavy metals (mostly lead, manganese and mercury) should be considered by both clinical doctors and people. There is still no consensus on the impact of smoking and alcohol use on bone mineral density in our study.

Rational passivation of the defects at the buried interface plays a significant role in reducing energy loss and improving the photovoltaic performance of perovskite solar cells (PSCs). Herein, we applied...

BackgroundLung adenocarcinoma (LUAD) is the most common type of Non-small-cell lung cancer (NSCLC). Distant metastasis of lung adenocarcinoma reduces the survival rate. we aim to develop a nomogram in order to predict the survival of patients with metastatic lung adenocarcinoma.MethodsWe retrospectively collected patients who were initially diagnosed as metastatic LUAD from 2010 to 2015 from SEER database. Based on the multivariate and univariate Cox regression analysis of the training cohorts, independent prognostic factors were assessed. The nomogram prediction model was then constructed based on these prognostic factors to predict the overall survival at 12, 24 and 36 months after surgery. Nomogram were identified and calibrated by c-index, time-dependent receiver operating characteristic curve (time-dependent AUC) and calibration curve. Decision curve analysis (DCA) was used to quantify the net benefit of the nomogram at different threshold probabilities, and to better compare with the TNM staging system, we calculated the c-index of this nomogram as well as the net reclassification improvement (NRI) and the integrated discrimination improvement (IDI).ResultA total of 1102 patients with metastatic LUAD who met the requirements were included for analysis. They were randomly divided into 774 in the training cohorts and 328 in the validation cohorts. As can be seen from the calibration plots, the predicted nomogram and the actual observations in both of the training and validation cohorts were generally consistent. The time dependent AUC values of 12 months, 24 months and 36 months were 0.707, 0.674 and 0.686 in the training cohorts and 0.690, 0.680 and 0.688 in the verification cohorts, respectively. C-indexes for the training and validation cohorts were 0.653 (95%CI 0.626-0.68)and 0.663 (95%CI 0.626-1), respectively. NRI and IDI show that the model is more clinical applicable than the existing staging system. In addition, our risk scoring system based on Kaplan Meier (K-M) survival curve can accurately divide patients into three hierarchy risk groups.ConclusionThis has led to the development and validation of a prognostic nomogram to assist clinicians in determining the prognosis of patients with metastatic lung adenocarcinoma after primary site surgery.