Autophagy plays a pivotal role in diverse biological processes,including the maintenance and differentiation of neural stem cells(NSCs).Interestingly,while complete deletion of Fip200 severely impairs NSC maintenance ...Autophagy plays a pivotal role in diverse biological processes,including the maintenance and differentiation of neural stem cells(NSCs).Interestingly,while complete deletion of Fip200 severely impairs NSC maintenance and differentiation,inhibiting canonical autophagy via deletion of core genes,such as Atg5,Atg16l1,and Atg7,or blockade of canonical interactions between FIP200 and ATG13(designated as FIP200-4A mutant or FIP200 KI)does not produce comparable detrimental effects.This highlights the likely critical involvement of the non-canonical functions of FIP200,the mechanisms of which have remained elusive.Here,utilizing genetic mouse models,we demonstrated that FIP200 mediates non-canonical autophagic degradation of p62/sequestome1,primarily via TAX1BP1 in NSCs.Conditional deletion of Tax1bp1 in fip200hGFAP conditional knock-in(cKI)mice led to NSC deficiency,resembling the fip200hGFAP conditional knockout(cKO)mouse phenotype.Notably,reintroducing wild-type TAX1BP1 not only restored the maintenance of NSCs derived from tax1bp1-knockout fip200hGFAP cKI mice but also led to a marked reduction in p62 aggregate accumulation.Conversely,a TAX1BP1 mutant incapable of binding to FIP200 or NBR1/p62 failed to achieve this restoration.Furthermore,conditional deletion of Tax1bp1 in fip200hGFAP cKO mice exacerbated NSC deficiency and p62 aggregate accumulation compared to fip200hGFAP cKO mice.Collectively,these findings illustrate the essential role of the FIP200-TAX1BP1 axis in mediating the non-canonical autophagic degradation of p62 aggregates towards NSC maintenance and function,presenting novel therapeutic targets for neurodegenerative diseases.展开更多
Objective:To analyze the factors related to vessel vasovagal reaction(VVR)in apheresis donors,establish a mathematical model for predicting the correlation factors and occurrence risk,and use the prediction model to i...Objective:To analyze the factors related to vessel vasovagal reaction(VVR)in apheresis donors,establish a mathematical model for predicting the correlation factors and occurrence risk,and use the prediction model to intervene in high-risk VVR blood donors,improve the blood donation experience,and retain blood donors.Methods:A total of 316 blood donors from the Xi'an Central Blood Bank from June to September 2022 were selected to statistically analyze VVR-related factors.A BP neural network prediction model is established with relevant factors as input and DRVR risk as output.Results:First-time blood donors had a high risk of VVR,female risk was high,and sex difference was significant(P value<0.05).The blood pressure before donation and intergroup differences were also significant(P value<0.05).After training,the established BP neural network model has a minimum RMS error of o.116,a correlation coefficient R=0.75,and a test model accuracy of 66.7%.Conclusion:First-time blood donors,women,and relatively low blood pressure are all high-risk groups for VVR.The BP neural network prediction model established in this paper has certain prediction accuracy and can be used as a means to evaluate the risk degree of clinical blood donors.展开更多
基金National Natural Science Foundation of China(U2004138,81773132,81820108021)University Excellent Teaching Team of“Qinglan Project”in Jiangsu Province(2022-25)+1 种基金Henan Province Key Research and Development Project(232102521028)Excellent Youth Foundation of Henan Scientific Committee(21230040016)。
文摘Autophagy plays a pivotal role in diverse biological processes,including the maintenance and differentiation of neural stem cells(NSCs).Interestingly,while complete deletion of Fip200 severely impairs NSC maintenance and differentiation,inhibiting canonical autophagy via deletion of core genes,such as Atg5,Atg16l1,and Atg7,or blockade of canonical interactions between FIP200 and ATG13(designated as FIP200-4A mutant or FIP200 KI)does not produce comparable detrimental effects.This highlights the likely critical involvement of the non-canonical functions of FIP200,the mechanisms of which have remained elusive.Here,utilizing genetic mouse models,we demonstrated that FIP200 mediates non-canonical autophagic degradation of p62/sequestome1,primarily via TAX1BP1 in NSCs.Conditional deletion of Tax1bp1 in fip200hGFAP conditional knock-in(cKI)mice led to NSC deficiency,resembling the fip200hGFAP conditional knockout(cKO)mouse phenotype.Notably,reintroducing wild-type TAX1BP1 not only restored the maintenance of NSCs derived from tax1bp1-knockout fip200hGFAP cKI mice but also led to a marked reduction in p62 aggregate accumulation.Conversely,a TAX1BP1 mutant incapable of binding to FIP200 or NBR1/p62 failed to achieve this restoration.Furthermore,conditional deletion of Tax1bp1 in fip200hGFAP cKO mice exacerbated NSC deficiency and p62 aggregate accumulation compared to fip200hGFAP cKO mice.Collectively,these findings illustrate the essential role of the FIP200-TAX1BP1 axis in mediating the non-canonical autophagic degradation of p62 aggregates towards NSC maintenance and function,presenting novel therapeutic targets for neurodegenerative diseases.
基金Xi'an Municipal Bureau of Science and Technology,Science and Technology Program,Medical Research Project。
文摘Objective:To analyze the factors related to vessel vasovagal reaction(VVR)in apheresis donors,establish a mathematical model for predicting the correlation factors and occurrence risk,and use the prediction model to intervene in high-risk VVR blood donors,improve the blood donation experience,and retain blood donors.Methods:A total of 316 blood donors from the Xi'an Central Blood Bank from June to September 2022 were selected to statistically analyze VVR-related factors.A BP neural network prediction model is established with relevant factors as input and DRVR risk as output.Results:First-time blood donors had a high risk of VVR,female risk was high,and sex difference was significant(P value<0.05).The blood pressure before donation and intergroup differences were also significant(P value<0.05).After training,the established BP neural network model has a minimum RMS error of o.116,a correlation coefficient R=0.75,and a test model accuracy of 66.7%.Conclusion:First-time blood donors,women,and relatively low blood pressure are all high-risk groups for VVR.The BP neural network prediction model established in this paper has certain prediction accuracy and can be used as a means to evaluate the risk degree of clinical blood donors.
