Poly(ethylene)glycol(PEG)has been widely used as an antifouling coating material for nanomedicines to improve their stability and safety.However,a growing number of studies have indicated that PEG is immunogenic and c...Poly(ethylene)glycol(PEG)has been widely used as an antifouling coating material for nanomedicines to improve their stability and safety.However,a growing number of studies have indicated that PEG is immunogenic and can cause unwanted immune responses,highlighting the need to develop alternative antifouling polymers for applications in nanomedicine.In this study,we report an innovative polymer,poly(2-(methylsulfinyl)ethyl glycidyl ether)(PMSOEGE),composed of a PEG backbone structure with sulfoxide-containing side chains.We demonstrated that PMSOEGE is highly biocompatible and more hydrophilic than conventional PEG due to the presence of highly polar and hydrophilic sulfoxide structures.Furthermore,PMSOEGE exhibits a much lower association with anti-PEG antibodies,as confirmed by an in vitro competitive enzyme-linked immunosorbent assay(ELISA).We applied PMSOEGE as a coating material for iron oxide nanoparticles(IONPs)and demonstrated that the PMSOEGE-coated IONPs showed significantly lower cellular uptake by macrophages compared with PEGylated IONPs.Protein corona analysis indicated that fewer proteins were associated with IONP@PMSOEGE.The results highlight the superior antifouling properties of PMSOEGE and highlight its potential to serve as a PEG alternative for various biological applications.展开更多
Vehicle Color Recognition(VCR)plays a vital role in intelligent traffic management and criminal investigation assistance.However,the existing vehicle color datasets only cover 13 classes,which can not meet the current...Vehicle Color Recognition(VCR)plays a vital role in intelligent traffic management and criminal investigation assistance.However,the existing vehicle color datasets only cover 13 classes,which can not meet the current actual demand.Besides,although lots of efforts are devoted to VCR,they suffer from the problem of class imbalance in datasets.To address these challenges,in this paper,we propose a novel VCR method based on Smooth Modulation Neural Network with Multi-Scale Feature Fusion(SMNN-MSFF).Specifically,to construct the benchmark of model training and evaluation,we first present a new VCR dataset with 24 vehicle classes,Vehicle Color-24,consisting of 10091 vehicle images from a 100-hour urban road surveillance video.Then,to tackle the problem of long-tail distribution and improve the recognition performance,we propose the SMNN-MSFF model with multiscale feature fusion and smooth modulation.The former aims to extract feature information from local to global,and the latter could increase the loss of the images of tail class instances for training with class-imbalance.Finally,comprehensive experimental evaluation on Vehicle Color-24 and previously three representative datasets demonstrate that our proposed SMNN-MSFF outperformed state-of-the-art VCR methods.And extensive ablation studies also demonstrate that each module of our method is effective,especially,the smooth modulation efficiently help feature learning of the minority or tail classes.Vehicle Color-24 and the code of SMNN-MSFF are publicly available and can contact the author to obtain.展开更多
基金the Australian Research Council(DP210101496,CE140100036,CE230100017)the National Health and Medical Research Council(APP1196168,APP1158026)for financial support.
文摘Poly(ethylene)glycol(PEG)has been widely used as an antifouling coating material for nanomedicines to improve their stability and safety.However,a growing number of studies have indicated that PEG is immunogenic and can cause unwanted immune responses,highlighting the need to develop alternative antifouling polymers for applications in nanomedicine.In this study,we report an innovative polymer,poly(2-(methylsulfinyl)ethyl glycidyl ether)(PMSOEGE),composed of a PEG backbone structure with sulfoxide-containing side chains.We demonstrated that PMSOEGE is highly biocompatible and more hydrophilic than conventional PEG due to the presence of highly polar and hydrophilic sulfoxide structures.Furthermore,PMSOEGE exhibits a much lower association with anti-PEG antibodies,as confirmed by an in vitro competitive enzyme-linked immunosorbent assay(ELISA).We applied PMSOEGE as a coating material for iron oxide nanoparticles(IONPs)and demonstrated that the PMSOEGE-coated IONPs showed significantly lower cellular uptake by macrophages compared with PEGylated IONPs.Protein corona analysis indicated that fewer proteins were associated with IONP@PMSOEGE.The results highlight the superior antifouling properties of PMSOEGE and highlight its potential to serve as a PEG alternative for various biological applications.
基金This work was supported by the National Natural Science Foundation of China(Grant No.62071378)the Shaanxi Province International Science and Technology Cooperation Program(2022KW-04)the Xi’an Science and Technology Plan Project(21XJZZ0072).
文摘Vehicle Color Recognition(VCR)plays a vital role in intelligent traffic management and criminal investigation assistance.However,the existing vehicle color datasets only cover 13 classes,which can not meet the current actual demand.Besides,although lots of efforts are devoted to VCR,they suffer from the problem of class imbalance in datasets.To address these challenges,in this paper,we propose a novel VCR method based on Smooth Modulation Neural Network with Multi-Scale Feature Fusion(SMNN-MSFF).Specifically,to construct the benchmark of model training and evaluation,we first present a new VCR dataset with 24 vehicle classes,Vehicle Color-24,consisting of 10091 vehicle images from a 100-hour urban road surveillance video.Then,to tackle the problem of long-tail distribution and improve the recognition performance,we propose the SMNN-MSFF model with multiscale feature fusion and smooth modulation.The former aims to extract feature information from local to global,and the latter could increase the loss of the images of tail class instances for training with class-imbalance.Finally,comprehensive experimental evaluation on Vehicle Color-24 and previously three representative datasets demonstrate that our proposed SMNN-MSFF outperformed state-of-the-art VCR methods.And extensive ablation studies also demonstrate that each module of our method is effective,especially,the smooth modulation efficiently help feature learning of the minority or tail classes.Vehicle Color-24 and the code of SMNN-MSFF are publicly available and can contact the author to obtain.
