The detection of single amino-acid variants （SAVs） usually depends on single-nucleotide polymorphisms （SNPs） database. Here, we describe a novel method that discovers SAVs at proteome level independent of SNPs dat...The detection of single amino-acid variants （SAVs） usually depends on single-nucleotide polymorphisms （SNPs） database. Here, we describe a novel method that discovers SAVs at proteome level independent of SNPs data. Using mass spectrometry-based de novo sequencing algorithm, peptide-candidates are identified and compared with theoretical protein database to generate SAVs under pairing strategy, which is followed by database re-searching to control false discovery rate. in human brain tissues, we can confidently identify known and novel protein variants with diverse origins. Combined with DNA/RNA sequencing, we verify SAVs derived from DNA mutations, RNA alternative splicing, and unknown post-transcriptional mechanisms. Furthermore, quantitative analysis in human brain tissues reveals several tissue-specific differential expressions of SAVs. This approach provides a novel access to high-throughput detection of protein variants, which may offer the potential for clinical biomarker discovery and mechanistic research.展开更多
The mobility landscape is experiencing major changes due to two emerging transportation trends,autonomous vehicles(AVs)and on-demand transportation,and the convergence of these smart mobility innovations as shared aut...The mobility landscape is experiencing major changes due to two emerging transportation trends,autonomous vehicles(AVs)and on-demand transportation,and the convergence of these smart mobility innovations as shared autonomous vehicles(SAVs)can considerably alter travel behavior and consequently the ecological and societal aspects of the transportation sector.On-demand autonomous mobility is a promising transportation mode,but further research is necessary to evaluate its various aspects and implications prior to widespread adoption.Thus,this study investigates the effects of integrating automation and on-demand mobility by analyzing the effects on the environment,public transportation,land use,vehicle ownership,and public acceptance.A comprehensive literature review was performed,and through a detailed review of 210 articles,the impacts of each of these categories were determined and classified according to their causes,and the number of publications with which they were cited in the literature was determined.The review showed that SAVs can either positively or negatively impact categories and have the potential to minimize mobility obstacles and transportation inequity if legislators use technology to develop a better transportation system by initiating effective policies that govern the four impacted areas.A list of 22 policy recommendations designed to avoid the negative consequences of SAVs by maximizing the benefits of the technology while limiting the associated risks was also identified.The findings of this review will be beneficial to AV manufacturers,transportation professionals,and especially policymakers,who play an integral role in shaping how society benefits from SAV technology.展开更多
文摘The detection of single amino-acid variants （SAVs） usually depends on single-nucleotide polymorphisms （SNPs） database. Here, we describe a novel method that discovers SAVs at proteome level independent of SNPs data. Using mass spectrometry-based de novo sequencing algorithm, peptide-candidates are identified and compared with theoretical protein database to generate SAVs under pairing strategy, which is followed by database re-searching to control false discovery rate. in human brain tissues, we can confidently identify known and novel protein variants with diverse origins. Combined with DNA/RNA sequencing, we verify SAVs derived from DNA mutations, RNA alternative splicing, and unknown post-transcriptional mechanisms. Furthermore, quantitative analysis in human brain tissues reveals several tissue-specific differential expressions of SAVs. This approach provides a novel access to high-throughput detection of protein variants, which may offer the potential for clinical biomarker discovery and mechanistic research.
文摘The mobility landscape is experiencing major changes due to two emerging transportation trends,autonomous vehicles(AVs)and on-demand transportation,and the convergence of these smart mobility innovations as shared autonomous vehicles(SAVs)can considerably alter travel behavior and consequently the ecological and societal aspects of the transportation sector.On-demand autonomous mobility is a promising transportation mode,but further research is necessary to evaluate its various aspects and implications prior to widespread adoption.Thus,this study investigates the effects of integrating automation and on-demand mobility by analyzing the effects on the environment,public transportation,land use,vehicle ownership,and public acceptance.A comprehensive literature review was performed,and through a detailed review of 210 articles,the impacts of each of these categories were determined and classified according to their causes,and the number of publications with which they were cited in the literature was determined.The review showed that SAVs can either positively or negatively impact categories and have the potential to minimize mobility obstacles and transportation inequity if legislators use technology to develop a better transportation system by initiating effective policies that govern the four impacted areas.A list of 22 policy recommendations designed to avoid the negative consequences of SAVs by maximizing the benefits of the technology while limiting the associated risks was also identified.The findings of this review will be beneficial to AV manufacturers,transportation professionals,and especially policymakers,who play an integral role in shaping how society benefits from SAV technology.
