Background:Renalfibrosis is an important process in the development of chronic kidney disease.Understanding the pathogenesis andfinding effective treatments for renalfibrosis is crucial.This study aims to investigate whe...Background:Renalfibrosis is an important process in the development of chronic kidney disease.Understanding the pathogenesis andfinding effective treatments for renalfibrosis is crucial.This study aims to investigate whether a newly discovered long non-coding RNA(lncRNA)called LOC103694972 could be a potential target for treatingfibrosis of NRK-49F cells.Methods:LncRNA Chip was used to identify differentially expressed lncRNAs between TGF-β1-induced NRK-49F cells and normal cells.The dual-luciferase assay confirmed the binding between miR-29c-3p and signal transducer and activator of transcription(STAT3),as well as between miR-29c-3p and lncRNA LOC103694972.Si-LOC103694972 and miR-29c-3p mimic were then transfected into TGF-β1-induced NRK-49F cells.Results:The study found that LOC103694972 was highly expressed in TGF-β1-induced NRK-49F cells.These cells exhibited increased cell length and activity compared to the control group.The expression levels of Collagen I,α-Smooth muscle actin(α-SMA),and tissue inhibitor of metalloproteinase(TIMP-1)were increased,while matrix Metalloproteinase 2(MMP2)and matrix Metalloproteinase 9(MMP9)expression was decreased.However,transfection with si-LOC103694972 and miR-29c-3p mimics restored cell morphology and reduced cell viability.This led to a decrease in the levels of Collagen I,α-SMA,and TIMP-1,as well as an increase in MMP2 and MMP9 expression.Additionally,TGF-β1-induced NRK-49F cells transfected with miR-29c-3p mimics activated the STAT3-Smad3/CTGF pathway.Conclusion:Based on thesefindings,lncRNA LOC103694972 shows promise as a target for treating renalfibrosis.It negatively regulates miR-29c-3p and activates the STAT3-Smad3/CTGF pathway.展开更多
In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression （PPR） is one of most applicable methods. But generally, the algorithm structure of the PPR is ...In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression （PPR） is one of most applicable methods. But generally, the algorithm structure of the PPR is very complicated. By partial smooth regressions for many times, it has a large amount of calculation and complicated extrapolation, so it is easily trapped in partial solution. On the basis of the algorithm features of the PPR method, some solutions are given as below to aim at some shortcomings in the PPR calculation： to optimize project direction by using particle swarm optimization instead of Gauss-Newton algorithm, to simplify the optimal process with fitting ridge function by using Hermitian polynomial instead of piecewise linear regression. The overall optimal ridge function can be obtained without grouping the parameter optimization. The modeling capability and calculating accuracy of projection pursuit method are tested by means of numerical emulation technique on the basis of particle swarm optimization and Hermitian polynomial, and then applied to the seismic comprehensive forecasting models of poly-dimensional seismic time series and general disorder seismic samples. The calculation and analysis show that the projection pursuit model in this paper is characterized by simplicity, celerity and effectiveness. And this model is approved to have satisfactory effects in the real seismic comprehensive forecasting, which can be regarded as a comprehensive analysis method in seismic comprehensive forecast.展开更多
基金This work was supported by the Hunan Provincial Education Department General Project Research Fund(No.20C1412)the Hunan Graduate Scientific Research Innovation Project(No.CX2018B474)the National Famous Elderly Chinese Medicine Experts Xinyu Chen Inheritance Workshop Construction Project(No.[2022]75).
文摘Background:Renalfibrosis is an important process in the development of chronic kidney disease.Understanding the pathogenesis andfinding effective treatments for renalfibrosis is crucial.This study aims to investigate whether a newly discovered long non-coding RNA(lncRNA)called LOC103694972 could be a potential target for treatingfibrosis of NRK-49F cells.Methods:LncRNA Chip was used to identify differentially expressed lncRNAs between TGF-β1-induced NRK-49F cells and normal cells.The dual-luciferase assay confirmed the binding between miR-29c-3p and signal transducer and activator of transcription(STAT3),as well as between miR-29c-3p and lncRNA LOC103694972.Si-LOC103694972 and miR-29c-3p mimic were then transfected into TGF-β1-induced NRK-49F cells.Results:The study found that LOC103694972 was highly expressed in TGF-β1-induced NRK-49F cells.These cells exhibited increased cell length and activity compared to the control group.The expression levels of Collagen I,α-Smooth muscle actin(α-SMA),and tissue inhibitor of metalloproteinase(TIMP-1)were increased,while matrix Metalloproteinase 2(MMP2)and matrix Metalloproteinase 9(MMP9)expression was decreased.However,transfection with si-LOC103694972 and miR-29c-3p mimics restored cell morphology and reduced cell viability.This led to a decrease in the levels of Collagen I,α-SMA,and TIMP-1,as well as an increase in MMP2 and MMP9 expression.Additionally,TGF-β1-induced NRK-49F cells transfected with miR-29c-3p mimics activated the STAT3-Smad3/CTGF pathway.Conclusion:Based on thesefindings,lncRNA LOC103694972 shows promise as a target for treating renalfibrosis.It negatively regulates miR-29c-3p and activates the STAT3-Smad3/CTGF pathway.
文摘In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression （PPR） is one of most applicable methods. But generally, the algorithm structure of the PPR is very complicated. By partial smooth regressions for many times, it has a large amount of calculation and complicated extrapolation, so it is easily trapped in partial solution. On the basis of the algorithm features of the PPR method, some solutions are given as below to aim at some shortcomings in the PPR calculation： to optimize project direction by using particle swarm optimization instead of Gauss-Newton algorithm, to simplify the optimal process with fitting ridge function by using Hermitian polynomial instead of piecewise linear regression. The overall optimal ridge function can be obtained without grouping the parameter optimization. The modeling capability and calculating accuracy of projection pursuit method are tested by means of numerical emulation technique on the basis of particle swarm optimization and Hermitian polynomial, and then applied to the seismic comprehensive forecasting models of poly-dimensional seismic time series and general disorder seismic samples. The calculation and analysis show that the projection pursuit model in this paper is characterized by simplicity, celerity and effectiveness. And this model is approved to have satisfactory effects in the real seismic comprehensive forecasting, which can be regarded as a comprehensive analysis method in seismic comprehensive forecast.
