We previously demonstrated that inhibiting neural stem cells necroptosis enhances functional recovery after spinal cord injury.While exosomes are recognized as playing a pivotal role in neural stem cells exocrine func...We previously demonstrated that inhibiting neural stem cells necroptosis enhances functional recovery after spinal cord injury.While exosomes are recognized as playing a pivotal role in neural stem cells exocrine function,their precise function in spinal cord injury remains unclear.To investigate the role of exosomes generated following neural stem cells necroptosis after spinal cord injury,we conducted singlecell RNA sequencing and validated that neural stem cells originate from ependymal cells and undergo necroptosis in response to spinal cord injury.Subsequently,we established an in vitro necroptosis model using neural stem cells isolated from embryonic mice aged 16-17 days and extracted exosomes.The results showed that necroptosis did not significantly impact the fundamental characteristics or number of exosomes.Transcriptome sequencing of exosomes in necroptosis group identified 108 differentially expressed messenger RNAs,104 long non-coding RNAs,720 circular RNAs,and 14 microRNAs compared with the control group.Construction of a competing endogenous RNA network identified the following hub genes:tuberous sclerosis 2(Tsc2),solute carrier family 16 member 3(Slc16a3),and forkhead box protein P1(Foxp1).Notably,a significant elevation in TSC2 expression was observed in spinal cord tissues following spinal cord injury.TSC2-positive cells were localized around SRY-box transcription factor 2-positive cells within the injury zone.Furthermore,in vitro analysis revealed increased TSC2 expression in exosomal receptor cells compared with other cells.Further assessment of cellular communication following spinal cord injury showed that Tsc2 was involved in ependymal cellular communication at 1 and 3 days post-injury through the epidermal growth factor and midkine signaling pathways.In addition,Slc16a3 participated in cellular communication in ependymal cells at 7 days post-injury via the vascular endothelial growth factor and macrophage migration inhibitory factor signaling pathways.Collectively,these findings confirm that exosomes derived from neural stem cells undergoing necroptosis play an important role in cellular communication after spinal cord injury and induce TSC2 upregulation in recipient cells.展开更多
Battery management systems(BMSs) play a vital role in ensuring efficient and reliable operations of lithium-ion batteries.The main function of the BMSs is to estimate battery states and diagnose battery health using b...Battery management systems(BMSs) play a vital role in ensuring efficient and reliable operations of lithium-ion batteries.The main function of the BMSs is to estimate battery states and diagnose battery health using battery open-circuit voltage(OCV).However,acquiring the complete OCV data online can be a challenging endeavor due to the time-consuming measurement process or the need for specific operating conditions required by OCV estimation models.In addressing these concerns,this study introduces a deep neural network-combined framework for accurate and robust OCV estimation,utilizing partial daily charging data.We incorporate a generative deep learning model to extract aging-related features from data and generate high-fidelity OCV curves.Correlation analysis is employed to identify the optimal partial charging data,optimizing the OCV estimation precision while preserving exceptional flexibility.The validation results,using data from nickel-cobalt-magnesium(NCM) batteries,illustrate the accurate estimation of the complete OCV-capacity curve,with an average root mean square errors(RMSE) of less than 3 mAh.Achieving this level of precision for OCV estimation requires only around 50 s collection of partial charging data.Further validations on diverse battery types operating under various conditions confirm the effectiveness of our proposed method.Additional cases of precise health diagnosis based on OCV highlight the significance of conducting online OCV estimation.Our method provides a flexible approach to achieve complete OCV estimation and holds promise for generalization to other tasks in BMSs.展开更多
The open-circuit fault is one of the most common faults of the automatic ramming drive system(ARDS),and it can be categorized into the open-phase faults of Permanent Magnet Synchronous Motor(PMSM)and the open-circuit ...The open-circuit fault is one of the most common faults of the automatic ramming drive system(ARDS),and it can be categorized into the open-phase faults of Permanent Magnet Synchronous Motor(PMSM)and the open-circuit faults of Voltage Source Inverter(VSI). The stator current serves as a common indicator for detecting open-circuit faults. Due to the identical changes of the stator current between the open-phase faults in the PMSM and failures of double switches within the same leg of the VSI, this paper utilizes the zero-sequence voltage component as an additional diagnostic criterion to differentiate them.Considering the variable conditions and substantial noise of the ARDS, a novel Multi-resolution Network(Mr Net) is proposed, which can extract multi-resolution perceptual information and enhance robustness to the noise. Meanwhile, a feature weighted layer is introduced to allocate higher weights to characteristics situated near the feature frequency. Both simulation and experiment results validate that the proposed fault diagnosis method can diagnose 25 types of open-circuit faults and achieve more than98.28% diagnostic accuracy. In addition, the experiment results also demonstrate that Mr Net has the capability of diagnosing the fault types accurately under the interference of noise signals(Laplace noise and Gaussian noise).展开更多
基金supported by the National Natural Science Foundation of China,No.81801907(to NC)Shenzhen Key Laboratory of Bone Tissue Repair and Translational Research,No.ZDSYS20230626091402006(to NC)+2 种基金Sanming Project of Medicine in Shenzhen,No.SZSM201911002(to SL)Foundation of Shenzhen Committee for Science and Technology Innovation,Nos.JCYJ20230807110310021(to NC),JCYJ20230807110259002(to JL)Science and Technology Program of Guangzhou,No.2024A04J4716(to TL)。
文摘We previously demonstrated that inhibiting neural stem cells necroptosis enhances functional recovery after spinal cord injury.While exosomes are recognized as playing a pivotal role in neural stem cells exocrine function,their precise function in spinal cord injury remains unclear.To investigate the role of exosomes generated following neural stem cells necroptosis after spinal cord injury,we conducted singlecell RNA sequencing and validated that neural stem cells originate from ependymal cells and undergo necroptosis in response to spinal cord injury.Subsequently,we established an in vitro necroptosis model using neural stem cells isolated from embryonic mice aged 16-17 days and extracted exosomes.The results showed that necroptosis did not significantly impact the fundamental characteristics or number of exosomes.Transcriptome sequencing of exosomes in necroptosis group identified 108 differentially expressed messenger RNAs,104 long non-coding RNAs,720 circular RNAs,and 14 microRNAs compared with the control group.Construction of a competing endogenous RNA network identified the following hub genes:tuberous sclerosis 2(Tsc2),solute carrier family 16 member 3(Slc16a3),and forkhead box protein P1(Foxp1).Notably,a significant elevation in TSC2 expression was observed in spinal cord tissues following spinal cord injury.TSC2-positive cells were localized around SRY-box transcription factor 2-positive cells within the injury zone.Furthermore,in vitro analysis revealed increased TSC2 expression in exosomal receptor cells compared with other cells.Further assessment of cellular communication following spinal cord injury showed that Tsc2 was involved in ependymal cellular communication at 1 and 3 days post-injury through the epidermal growth factor and midkine signaling pathways.In addition,Slc16a3 participated in cellular communication in ependymal cells at 7 days post-injury via the vascular endothelial growth factor and macrophage migration inhibitory factor signaling pathways.Collectively,these findings confirm that exosomes derived from neural stem cells undergoing necroptosis play an important role in cellular communication after spinal cord injury and induce TSC2 upregulation in recipient cells.
基金This work was supported by the National Key R&D Program of China(2021YFB2402002)the Beijing Natural Science Foundation(L223013)the Chongqing Automobile Collaborative Innovation Centre(No.2022CDJDX-004).
文摘Battery management systems(BMSs) play a vital role in ensuring efficient and reliable operations of lithium-ion batteries.The main function of the BMSs is to estimate battery states and diagnose battery health using battery open-circuit voltage(OCV).However,acquiring the complete OCV data online can be a challenging endeavor due to the time-consuming measurement process or the need for specific operating conditions required by OCV estimation models.In addressing these concerns,this study introduces a deep neural network-combined framework for accurate and robust OCV estimation,utilizing partial daily charging data.We incorporate a generative deep learning model to extract aging-related features from data and generate high-fidelity OCV curves.Correlation analysis is employed to identify the optimal partial charging data,optimizing the OCV estimation precision while preserving exceptional flexibility.The validation results,using data from nickel-cobalt-magnesium(NCM) batteries,illustrate the accurate estimation of the complete OCV-capacity curve,with an average root mean square errors(RMSE) of less than 3 mAh.Achieving this level of precision for OCV estimation requires only around 50 s collection of partial charging data.Further validations on diverse battery types operating under various conditions confirm the effectiveness of our proposed method.Additional cases of precise health diagnosis based on OCV highlight the significance of conducting online OCV estimation.Our method provides a flexible approach to achieve complete OCV estimation and holds promise for generalization to other tasks in BMSs.
基金supported by the Natural Science Foundation of Jiangsu Province (Grant Nos. BK20210347)。
文摘The open-circuit fault is one of the most common faults of the automatic ramming drive system(ARDS),and it can be categorized into the open-phase faults of Permanent Magnet Synchronous Motor(PMSM)and the open-circuit faults of Voltage Source Inverter(VSI). The stator current serves as a common indicator for detecting open-circuit faults. Due to the identical changes of the stator current between the open-phase faults in the PMSM and failures of double switches within the same leg of the VSI, this paper utilizes the zero-sequence voltage component as an additional diagnostic criterion to differentiate them.Considering the variable conditions and substantial noise of the ARDS, a novel Multi-resolution Network(Mr Net) is proposed, which can extract multi-resolution perceptual information and enhance robustness to the noise. Meanwhile, a feature weighted layer is introduced to allocate higher weights to characteristics situated near the feature frequency. Both simulation and experiment results validate that the proposed fault diagnosis method can diagnose 25 types of open-circuit faults and achieve more than98.28% diagnostic accuracy. In addition, the experiment results also demonstrate that Mr Net has the capability of diagnosing the fault types accurately under the interference of noise signals(Laplace noise and Gaussian noise).
