| 2 | Comparison of gut microbiota in autism spectrum disorders and neurotypical boys in China:A case-control study显示文摘Background:Autism spectrum disorders(ASDs)are a set of complex neurobiological disorders.Growing evidence has shown that the microbiota that resides in the gut can modulate brain development via the gut–brain axis.However,direct clinical evidence of the role of the microbiota–gut–brain axis in ASD is relatively limited.Methods:A case-control study of 71 boys with ASD and 18 neurotypical controls was conducted at China-Japan Friendship Hospital.Demographic information and fecal samples were collected,and the gut microbiome was evaluated and compared by 16S ribosomal RNA gene sequencing and metagenomic sequencing.Results:A higher abundance of operational taxonomic units(OTUs)based on fecal bacterial profiling was observed in the ASD group.Significantly different microbiome profiles were observed between the two groups.At the genus level,we observed a decrease in the relative abundance of Escherichia,Shigella,Veillonella,Akkermansia,Provindencia,Dialister,Bifidobacterium,Streptococcus,Ruminococcaceae UCG_002,Megasphaera,Eubacterium_coprostanol,Citrobacter,Ruminiclostridium_5,and Ruminiclostridium_6 in the ASD cohort,while Eisenbergiella,Klebsiella,Faecalibacterium,and Blautia were significantly increased.Ten bacterial strains were selected for clinical discrimination between those with ASD and the neurotypical controls.The highest AUC value of the model was 0.947.Conclusion:Significant differences were observed in the composition of the gut microbiome between boys with ASD and neurotypical controls.These findings contribute to the knowledge of the alteration of the gut microbiome in ASD patients,which opens the possibility for early identification of this disease. | Fang Ye Xinying Gao Zhiyi Wang Shuman Cao Guangcai Liang Danni He Zhitang Lv Liming Wang Pengfei Xu Qi Zhang | 2021 | Synthetic and Systems Biotechnology2021，6，2： | 2 |
| 3 | In-memory computing based on phase change memory for high energy efficiency显示文摘The energy efficiency issue caused by the memory wall in traditional von Neumann architecture is difficult to reconcile.In-memory computing(CIM)based on emerging nonvolatile memory(NVM)is a promising solution to avoid data movement between storage and processors and realize highly energy-efficient computing.Compared with other NVM technologies,phase change random access memory(PCM)exhibits comprehensive performance for analog computing.In this paper,we review advanced PCM techniques,including phase-change materials,mechanisms,and unique properties,as a foundation and inspiration for implementing CIM architecture.Meanwhile,state-of-the-art PCM-based CIM systems are well discussed for high energy efficiency in artificial neural networks,spiking neural networks,and other artificial intelligence(AI)applications.Finally,we present the remaining challenges and potential solutions of CIM for further investigation. | Luchang HE Xi LI Chenchen XIE Zhitang SONG | 2023 | Science China(Information Sciences)2023，66，10： | 0 |
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