The silk gland cells of silkworm are special cells which only replicate DNA in the nucleus without cell division throughout the larval stage. The extrachromosomal circular DNAs (eccDNAs) have not yet been reported in ...The silk gland cells of silkworm are special cells which only replicate DNA in the nucleus without cell division throughout the larval stage. The extrachromosomal circular DNAs (eccDNAs) have not yet been reported in the silk gland of silkworms. Herein, we have explored the characterization of eccDNAs in the posterior silk gland of silkworms. A total of 35 346 eccDNAs were identified with sizes ranging from 30 to 13 569 549 bp. Motif analysis revealed that dual direct repeats are flanking the 5′ and 3′ breaking points of eccDNA. The sequences exceeding 1 kb length in eccDNAs present palindromic sequence characteristics flanking the 5′ and 3′ breaking points of the eccDNA. These motifs might support possible models for eccDNA generation. Genomic annotation of the eccDNA population revealed that most eccDNAs (58.6%) were derived from intergenic regions, whereas full or partial genes were carried by 41.4% of eccDNAs. It was found that silk protein genes fib-H, fib-L, and P25, as well as the transcription factors SGF and sage, which play an important regulatory role in silk protein synthesis, could be carried by eccDNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the genes carried by eccDNAs were mainly associated with the development and metabolism-related signaling pathways. Moreover, it was found that eccDNAfib-L could promote the transcription of fib-L gene. Overall, the results of the present study not only provide a novel perspective on the mechanism of silk gland development and silk protein synthesis but also complement previously reported genome-scale eccDNA data supporting that eccDNAs are common in eukaryotes.展开更多
Aging is a contributor to liver disease.Hence,the concept of liver aging has become prominent and has attracted considerable interest,but its underlying mechanism remains poorly understood.In our study,the internal me...Aging is a contributor to liver disease.Hence,the concept of liver aging has become prominent and has attracted considerable interest,but its underlying mechanism remains poorly understood.In our study,the internal mechanism of liver aging was explored via multi-omics analysis and molecular experiments to support future targeted therapy.An aged rat liver model was established with D-galactose,and two other senescent hepatocyte models were established by treating HepG2 cells with D-galactose and H2O2.We then performed transcriptomic and metabolomic assays of the aged liver model and transcriptome analyses of the senescent hepatocyte models.In livers,genes related to peroxisomes,fatty acid elongation,and fatty acid degradation exhibited down-regulated expression with aging,and the hepatokine Fgf21 expression was positively correlated with the down-regulation of these genes.In senescent hepatocytes,similar to the results found in aged livers,FGF21 expression was also decreased.Moreover,the expressions of cell cycle-related genes were significantly down-regulated,and the down-regulated gene E2F8 was the key cell cycle-regulating transcription factor.We then validated that FGF21 overexpression can protect against liver aging and that FGF21 can attenuate the declines in the antioxidant and regenerative capacities in the aging liver.We successfully validated the results from cellular and animal experiments using human liver and blood samples.Our study indicated that FGF21 is an important target for inhibiting liver aging and suggested that pharmacological prevention of the reduction in FGF21 expression due to aging may be used to treat liver aging-related diseases.展开更多
Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors...Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice.展开更多
基金funded by National Key R&D Program of China(2019YFA0905200)the Natural Science Founda-tion of the Jiangsu Higher Education Institutions ofChina(22KJB23003)+2 种基金the National Natural Science Foundation of China(31872424,31972620,and 32072792)China Postdoctoral Science Foundation(2019M661937)Priority Academic Program of Development of Jiangsu Higher Education Institutions.
文摘The silk gland cells of silkworm are special cells which only replicate DNA in the nucleus without cell division throughout the larval stage. The extrachromosomal circular DNAs (eccDNAs) have not yet been reported in the silk gland of silkworms. Herein, we have explored the characterization of eccDNAs in the posterior silk gland of silkworms. A total of 35 346 eccDNAs were identified with sizes ranging from 30 to 13 569 549 bp. Motif analysis revealed that dual direct repeats are flanking the 5′ and 3′ breaking points of eccDNA. The sequences exceeding 1 kb length in eccDNAs present palindromic sequence characteristics flanking the 5′ and 3′ breaking points of the eccDNA. These motifs might support possible models for eccDNA generation. Genomic annotation of the eccDNA population revealed that most eccDNAs (58.6%) were derived from intergenic regions, whereas full or partial genes were carried by 41.4% of eccDNAs. It was found that silk protein genes fib-H, fib-L, and P25, as well as the transcription factors SGF and sage, which play an important regulatory role in silk protein synthesis, could be carried by eccDNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the genes carried by eccDNAs were mainly associated with the development and metabolism-related signaling pathways. Moreover, it was found that eccDNAfib-L could promote the transcription of fib-L gene. Overall, the results of the present study not only provide a novel perspective on the mechanism of silk gland development and silk protein synthesis but also complement previously reported genome-scale eccDNA data supporting that eccDNAs are common in eukaryotes.
基金the Research Unit Project of the Chinese Academy of Medical Sciences(No.2019-I2M-5-030)the Research Project of Jinan Microecological Biomedicine Shandong Laboratory(China)(No.JNL2022002A)the Fundamental Research Funds for the Central Universities(China)(No.226-2023-00107).
文摘Aging is a contributor to liver disease.Hence,the concept of liver aging has become prominent and has attracted considerable interest,but its underlying mechanism remains poorly understood.In our study,the internal mechanism of liver aging was explored via multi-omics analysis and molecular experiments to support future targeted therapy.An aged rat liver model was established with D-galactose,and two other senescent hepatocyte models were established by treating HepG2 cells with D-galactose and H2O2.We then performed transcriptomic and metabolomic assays of the aged liver model and transcriptome analyses of the senescent hepatocyte models.In livers,genes related to peroxisomes,fatty acid elongation,and fatty acid degradation exhibited down-regulated expression with aging,and the hepatokine Fgf21 expression was positively correlated with the down-regulation of these genes.In senescent hepatocytes,similar to the results found in aged livers,FGF21 expression was also decreased.Moreover,the expressions of cell cycle-related genes were significantly down-regulated,and the down-regulated gene E2F8 was the key cell cycle-regulating transcription factor.We then validated that FGF21 overexpression can protect against liver aging and that FGF21 can attenuate the declines in the antioxidant and regenerative capacities in the aging liver.We successfully validated the results from cellular and animal experiments using human liver and blood samples.Our study indicated that FGF21 is an important target for inhibiting liver aging and suggested that pharmacological prevention of the reduction in FGF21 expression due to aging may be used to treat liver aging-related diseases.
基金The work was supported by National Key Research and Development Program of China(2020YFB1708700)the National Natural Science Foundation of China(Grant Nos.61922055,61872233,61829201,61532012,61325012,61428205).
文摘Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice.
