地方高校有机化学实验评价方式概述与实践

有机化学实验实践性强、耗时长、危险系数高,所以制定科学合理的成绩评定体系具有重要意义。传统评价方式主要采用实验过程与实验报告相结合,该评价方式存在评价主体单一、方式单一、标准模糊、内容单一等问题,明显与新型人才培养要求有差距。因此,评价方式改革与创新势在必行。本文首先系统梳理了当前地方高校有机化学实验不同的评价方式,包括综合评价方式、指标评价方式、竞赛模式评价方式、多元化评价方式以及形成性评价方式等。其次,详细介绍了我校有机化学实验“三阶段五维度”的评价方式,该方式充分利用课前、课中、课后三个阶段,以培养会查阅、会设计、会操作、会写作、会主持的“五会”应用型人才为中心。最后,本文通过梳理不同评价方法,旨在为后续构建更科学的有机化学实验评价体系提供参考借鉴,更好地服务于人才培养。

Multi-Omics-Guided Discovery of Omicsynins Produced by Streptomyces sp.1647:Pseudo-Tetrapeptides Active Against Influenza A Viruses and Coronavirus HCoV-229E

Many microorganisms have mechanisms that protect cells against attack from viruses.The fermentation components of Streptomyces sp.1647 exhibit potent anti-influenza A virus(IAV)activity.This strain was isolated from soil in southern China in the 1970s,but the chemical nature of its antiviral substance(s)has remained unknown until now.We used an integrated multi-omics strategy to identify the antiviral agents from this streptomycete.The antibiotics and Secondary Metabolite Analysis Shell(antiSMASH)analysis of its genome sequence revealed 38 biosynthetic gene clusters(BGCs)for secondary metabolites,and the target BGCs possibly responsible for the production of antiviral components were narrowed down to three BGCs by bioactivity-guided comparative transcriptomics analysis.Through bioinformatics analysis and genetic manipulation of the regulators and a biosynthetic gene,cluster 36 was identified as the BGC responsible for the biosynthesis of the antiviral compounds.Bioactivity-based molecular networking analysis of mass spectrometric data from different recombinant strains illustrated that the antiviral compounds were a class of structural analogues.Finally,18 pseudo-tetrapeptides with an internal ureido linkage,omicsynins A1–A6,B1–B6,and C1–C6,were identified and/or isolated from fermentation broth.Among them,11 compounds(omicsynins A1,A2,A6,B1–B3,B5,B6,C1,C2,and C6)are new compounds.Omicsynins B1–B4 exhibited potent antiviral activity against IAV with the 50%inhibitory concentration(IC_(50))of approximately 1μmol·L^(-1)and a selectivity index(SI)ranging from 100 to 300.Omicsynins B1–B4 also showed significant antiviral activity against human coronavirus HCoV-229E.By integrating multi-omics data,we discovered a number of novel antiviral pseudo-tetrapeptides produced by Streptomyces sp.1647,indicating that the secondary metabolites of microorganisms are a valuable source of novel antivirals.

Environmental applications of graphene oxide composite membranes

Graphene oxide(GO)has been widely used in the modification of membranes due to its excellent properties,i.e.,huge specific surface area,good electrical conductivity,good hydrophilicity and various functional groups.The addition of GO in membranes were proved to exhibit improved properties in water permeability,molecular selectivity,membrane fouling mitigation and contaminants decomposition.Recently,the development of laminated GO in membranes achieved both high selectivity and high water permeability,conquering the limitations of conventional polymeric or inorganic membranes.By analyzing the separation mechanisms and the performance of GO composite membranes,this review systematically summarized the applications of GO composite membranes in three highlighted areas of environmental fields:desalination,gas separation and wastewater treatment,with challenges discussed faced with GO composite membranes.

Exploration of the contributing factors to the walking and biking travel frequency using multi-level joint models with endogeneity

The enormous advantages of active transportation lead the transportation research focus towards enhancing the walking and biking trips.The present study explored the influential factors to the walking and biking travel frequency based on data obtained from the National Household Travel Survey California add-on survey.The study features some highlights.First,bivariate models were used to account for the common unobserved heterogeneity shared at both household and personal levels.Second,endogeneity was explicitly considered.Third,both variable importance ranking and correlation analysis are employed to determine the different features to be fed into each of the joint models.The results illustrated that the models developed with endogeneity performed better than the models without endogeneity.Four influential variables which includes mode to work by bicycle,public transit usage,count of household members,and multiple race responses,tend to have statistically significant impacts on walking and biking trips.