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A core scientific problem in the treatment of central nervous system diseases:newborn neurons

Neural Regeneration Research 2024年第12期19卷 2588-2601页

作者： peng hao Zhaoyang Yang Kwok-Fai So Xiaoguang Li Department of Neurobiology School of Basic Medical SciencesCapital Medical UniversityBeijingChina Guangdong-HongKong-Macao Institute of CNS Regeneration Ministry of Education CNS Regeneration Collaborative Joint LaboratoryJinan UniversityGuangzhouGuangdong ProvinceChina Bioland Laboratory(Guangzhou Regenerative Medicine and Health Guangdong Laboratory) GuangzhouGuangdong ProvinceChina Department of Ophthalmology and State Key Laboratory of Brain and Cognitive Sciences The University of Hong KongHong Kong Special Administration RegionChina Center for Brain Science and Brain-Inspired Intelligence Guangdong-Hong Kong-Macao Greater Bay AreaGuangzhouGuangdong ProvinceChina Co-innovation Center of Neuroregeneration Nantong UniversityNantongJiangsu ProvinceChina Department of Biomedical Engineering School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina

It has long been asserted that failure to recover from central nervous system diseases is due to the system's intricate structure and the regenerative incapacity of adult neurons.Yet over recent decades,numerous studies have established that endogenous neurogenesis occurs in the adult central nervous system,including humans'.This has challenged the long-held scientific consensus that the number of adult neurons remains constant,and that new central nervous system neurons cannot be created or renewed.Herein,we present a comprehensive overview of the alterations and regulatory mechanisms of endogenous neurogenesis following central nervous system injury,and describe novel treatment strategies that to rget endogenous neurogenesis and newborn neurons in the treatment of central nervous system injury.Central nervous system injury frequently results in alterations of endogenous neurogenesis,encompassing the activation,proliferation,ectopic migration,diffe rentiation,and functional integration of endogenous neural stem cells.Because of the unfavorable local microenvironment,most activated neural stem cells diffe rentiate into glial cells rather than neurons.Consequently,the injury-induced endogenous neurogenesis response is inadequate for repairing impaired neural function.Scientists have attempted to enhance endogenous neurogenesis using various strategies,including using neurotrophic factors,bioactive materials,and cell reprogramming techniques.Used alone or in combination,these therapeutic strategies can promote targeted migration of neural stem cells to an injured area,ensure their survival and diffe rentiation into mature functional neurons,and facilitate their integration into the neural circuit.Thus can integration re plenish lost neurons after central nervous system injury,by improving the local microenvironment.By regulating each phase of endogenous neurogenesis,endogenous neural stem cells can be harnessed to promote effective regeneration of newborn neurons.This offers a novel approach for treating central ne

关键词： bioactive materials brain trauma endogenous neurogenesis hippocampal dentate gyrus neural stem cells neurotrophic factors newborn neurons spinal cord injury stroke subventricular zone

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Adaptation analysis and fusion correction method of CMIP6 precipitation simulation data on the Qinghai-Tibetan Plateau

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Journal of Mountain Science 2024年第2期21卷 555-573页

作者： peng hao QIN Dahui WANG Zegen ZHANG Menghan YANG Yanmei YONG Zhiwei School of Civil Engineering and Geomatics Southwest Petroleum UniversityChengdu 610500China School of Geoscience and Technology Southwest Petroleum UniversityChengdu 610500China

In order to obtain more accurate precipitation data and better simulate the precipitation on the Tibetan Plateau,the simulation capability of 14 Coupled Model Intercomparison Project Phase 6(CMIP6)models of historical precipitation(1982-2014)on the Qinghai-Tibetan Plateau was evaluated in this study.Results indicate that all models exhibit an overestimation of precipitation through the analysis of the Taylor index,temporal and spatial statistical parameters.To correct the overestimation,a fusion correction method combining the Backpropagation Neural Network Correction(BP)and Quantum Mapping(QM)correction,named BQ method,was proposed.With this method,the historical precipitation of each model was corrected in space and time,respectively.The correction results were then analyzed in time,space,and analysis of variance(ANOVA)with those corrected by the BP and QM methods,respectively.Finally,the fusion correction method results for each model were compared with the Climatic Research Unit(CRU)data for significance analysis to obtain the trends of precipitation increase and decrease for each model.The results show that the IPSL-CM6A-LR model is relatively good in simulating historical precipitation on the Qinghai-Tibetan Plateau(R=0.7,RSME=0.15)among the uncorrected data.In terms of time,the total precipitation corrected by the fusion method has the same interannual trend and the closest precipitation values to the CRU data;In terms of space,the annual average precipitation corrected by the fusion method has the smallest difference with the CRU data,and the total historical annual average precipitation is not significantly different from the CRU data,which is better than BP and QM.Therefore,the correction effect of the fusion method on the historical precipitation of each model is better than that of the QM and BP methods.The precipitation in the central and northeastern parts of the plateau shows a significant increasing trend.The correlation coefficients between monthly precipitation and site-detected precipitation fo

关键词： GCM CMIP6 Precipitation correction BP-QM fusion correction Spatio-temporal characteristics

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Activation of endogenous neurogenesis and angiogenesis by basic fibroblast growth factor-chitosan gel in an adult rat model of ischemic stroke

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Neural Regeneration Research 2024年第2期19卷 409-415页

作者： Hongmei Duan Shulun Li peng hao Fei hao Wen Zhao Yudan Gao Hui Qiao Yiming Gu Yang Lv Xinjie Bao Kin Chiu Kwok-Fai So Zhaoyang Yang Xiaoguang Li Department of Neurobiology School of Basic Medical SciencesCapital Medical UniversityBeijingChina Beijing Key Laboratory for Biomaterials and Neural Regeneration School of Engineering MedicineBeihang UniversityBeijingChina Department of Epidemiology and Statistics School of Public Health and ManagementNingxia Medical UniversityYinchuanNingxia Hui Autonomous RegionChina Department of Physical Education Capital University of Economics and BusinessmBeijingChina Department of Neurosurgery Peking Union Medical College HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina Department of Psychology State Key Lab of Brain and Cognitive SciencesThe University of Hong KongHong Kong Special Administration RegionChina Guangdong-Hongkong-Macao Institute of CNS Regeneration Ministry of Education CNS Regeneration Collaborative Joint LaboratoryJinan UniversityGuangzhouGuangdong ProvinceChina Bioland Laboratory(Guangzhou Regenerative Medicine and Health Guangdong Laboratory) GuangzhouGuangdong ProvinceChina Department of Ophthalmology and State Key Laboratory of Brain and Cognitive Sciences The University of Hong KongHong Kong Special Administration RegionChina Center for Brain Science and Brain-Inspired Intelligence Guangdong-Hong Kong-Macao Greater Bay AreaGuangzhouGuangdong ProvinceChina Co-innovation Center of Neuroregeneration Nantong UniversityNantongJiangsu ProvinceChina Department of Biomedical Engineering School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina

Attempts have been made to use cell transplantation and biomaterials to promote cell proliferation,differentiation,migration,and survival,as well as angiogenesis,in the context of brain injury.However,whether bioactive materials can repair the damage caused by ischemic stroke by activating endogenous neurogenesis and angiogenesis is still unknown.In this study,we applied chitosan gel loaded with basic fibroblast growth factor to the stroke cavity 7 days after ischemic stroke in rats.The gel slowly released basic fibroblast growth factor,which improved the local microenvironment,activated endogenous neural stem/progenitor cells,and recruited these cells to migrate toward the penumbra and stroke cavity and subsequently differentiate into neurons,while enhancing angiogenesis in the penumbra and stroke cavity and ultimately leading to partial functional recovery.This study revealed the mechanism by which bioactive materials repair ischemic strokes,thus providing a new strategy for the clinical application of bioactive materials in the treatment of ischemic stroke.

关键词： adult endogenous neurogenesis angiogenesis basic fibroblast growth factor-chitosan gel chitosan functional recovery ischemic stroke neural stem cell newborn neuron

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Green manufacturing for achieving carbon neutrality goal requires innovative technologies:A bibliometric analysis from 1991 to 2022

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Journal of Environmental Sciences 2024年第6期140卷 255-269页

作者： Sheng Zhang Xintian Wang Jiayu Xu Qinqin Chen Meng peng Jiming hao School of Environment Tsinghua UniversityBeijing 100084China School of Environment&Natural Resources Renmin University of ChinaBeijing 100872China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084China

Recent years have seen a significant increase in interest in green manufacturing as a key driver of global carbon-neutral efforts and sustainable development.To find the research hotspots of green manufacturing and reveal future research trends,this study reviewed and analyzed research articles from the Web of Science database on green manufacturing from1991 to 2022 using a bibliometric method.The findings indicate a significant rise in the number of articles related to green manufacturing since the 2010s.Moreover,there has been an increase in the involvement of scholars from developing countries such as China and India in this field.Based on the literature review and bibliometric cluster analysis on green manufacturing,we believed that future research may continue following the lines of intelligent technology integration,adoption of frontier engineering techniques,and industry development in line with carbon reduction targets.A framework for future green manufacturing development is proposed,with a focus on Chinese policies.The framework could provide policy implications for developing countries looking to pursue opportunities for development in green manufacturing.

关键词： Green manufacturing Carbon neutrality Sustainable development Innovative technologies China

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Path-Following Control With Obstacle Avoidance of Autonomous Surface Vehicles Subject to Actuator Faults

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 956-964页

作者： Li-Ying hao Gege Dong Tieshan Li Zhouhua peng the School of Marine Electrical Engineering Dalian Maritime UniversityDalian 116026China the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731the Navigation CollegeDalian Maritime UniversityDalian 116026 the Yangtze Delta Region Institute(Huzhou) Huzhou 313001China

This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles inevitably suffer from actuator faults in complex sea environments,which may cause existing obstacle avoidance strategies to fail.To reduce the influence of actuator faults,an improved artificial potential function is constructed by introducing the lower bound of actuator efficiency factors.The nonlinear state observer,which only depends on measurable position information of the autonomous surface vehicle,is used to address uncertainties and external disturbances.By using a backstepping technique and adaptive mechanism,a path-following control strategy with obstacle avoidance and fault tolerance is designed which can ensure that the tracking errors converge to a small neighborhood of zero.Compared with existing results,the proposed control strategy has the capability of obstacle avoidance and fault tolerance simultaneously.Finally,the comparison results through simulations are given to verify the effectiveness of the proposed method.

关键词： Actuator faults autonomous surface vehicle(ASVs) improved artificial potential function nonlinear state observer obstacle avoidance

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Gigantic occipital epidermal cyst in a 56-year-old female:A case report

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World Journal of Clinical Cases 2024年第6期12卷 1169-1173页

作者： Yao Wei peng Chen hao Wu Department of Neurosurgery The Second Affiliated Hospital of Xi’an Medical UniversityXi'an 710038Shaanxi ProvinceChina

BACKGROUND Gigantic epidermal cysts(GECs)are rare benign skin appendicular tumours also known as keratinocysts.GECs have a high incidence and their wall is made up of epidermis.Epidermal cysts can occur in any part of the skin;clinical manifestations include skin colour hemispherical swelling;cystic;mobile;0.5 cm to several centimetres in diameter;and slow growth.CASE SUMMARY Herein,we report a case involving a 56-year-old female with a GEC in the occipitalia.On July 25,2023,a patient with a GEC was admitted to the neurosurgery Department of the Second Affiliated Hospital of Xi'an Medical University.The phyma was shown to be a solid mass during the operation and was confirmed to be a GEC based on pathological examination.CONCLUSION Epidermal cysts are common cystic nodules on the surface of the body,the aetiology is unclear,the clinical manifestations can vary,and the misdiagnosis rate is high.However,giant epidermal cysts are rare.In most cases,however,the prognosis is satisfactory.This paper analyses and summarizes the population,location,clinical and pathological characteristics and pathogenesis of the disease to strengthen the understanding of this disease and improve the accuracy of clinical diagnosis.

关键词： Epidermal cyst Occipital Brain Cyst Case report

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Neoantigen cancer vaccines:a new star on the horizon

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Cancer Biology & Medicine 2024年第4期21卷 274-311页

作者： Xiaoling Li Jian You Liping Hong Weijiang Liu peng Guo Xishan hao Cell Biotechnology Laboratory Tianjin Cancer Hospital Airport HospitalTianjin 300308China National Clinical Research Center for Cancer Tianjin 300060China Haihe Laboratory of Synthetic Biology Tianjin 300090China Department of Thoracic Oncology Tianjin Cancer Hospital Airport HospitalTianjin 300308China Department of Thoracic Oncology Surgery Tianjin Medical University Cancer Institute&HospitalTianjin 300060China Tianjin Medical University Cancer Institute&Hospital Tianjin 300060China

Immunotherapy represents a promising strategy for cancer treatment that utilizes immune cells or drugs to activate the patient's own immune system and eliminate cancer cells.One of the most exciting advances within this field is the targeting of neoantigens,which are peptides derived from non-synonymous somatic mutations that are found exclusively within cancer cells and absent in normal cells.Although neoantigen-based therapeutic vaccines have not received approval for standard cancer treatment,early clinical trials have yielded encouraging outcomes as standalone monotherapy or when combined with checkpoint inhibitors.Progress made in high-throughput sequencing and bioinformatics have greatly facilitated the precise and efficient identification of neoantigens.Consequently,personalized neoantigen-based vaccines tailored to each patient have been developed that are capable of eliciting a robust and long-lasting immune response which effectively eliminates tumors and prevents recurrences.This review provides a concise overview consolidating the latest clinical advances in neoantigen-based therapeutic vaccines,and also discusses challenges and future perspectives for this innovative approach,particularly emphasizing the potential of neoantigen-based therapeutic vaccines to enhance clinical efficacy against advanced solid tumors.

关键词： Immunotherapy neoantigen cancer vaccine solid tumors high-throughput sequencing bioinformatics PDOs AI HLA TCR

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Deep Learning and Tensor-Based Multiple Clustering Approaches for Cyber-Physical-Social Applications

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Computers, Materials & Continua 2024年第3期78卷 4109-4128页

作者： Hongjun Zhang hao Zhang Yu Lei hao Ye peng Li Desheng Shi School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing210023China China Communications Services Co. Ltd.Beijing100071China China Communications Services Hexin Science&Technology Co. Ltd.Hefei230031China

The study delves into the expanding role of network platforms in our daily lives, encompassing various mediums like blogs, forums, online chats, and prominent social media platforms such as Facebook, Twitter, and Instagram. While these platforms offer avenues for self-expression and community support, they concurrently harbor negative impacts, fostering antisocial behaviors like phishing, impersonation, hate speech, cyberbullying, cyberstalking, cyberterrorism, fake news propagation, spamming, and fraud. Notably, individuals also leverage these platforms to connect with authorities and seek aid during disasters. The overarching objective of this research is to address the dual nature of network platforms by proposing innovative methodologies aimed at enhancing their positive aspects and mitigating their negative repercussions. To achieve this, the study introduces a weight learning method grounded in multi-linear attribute ranking. This approach serves to evaluate the significance of attribute combinations across all feature spaces. Additionally, a novel clustering method based on tensors is proposed to elevate the quality of clustering while effectively distinguishing selected features. The methodology incorporates a weighted average similarity matrix and optionally integrates weighted Euclidean distance, contributing to a more nuanced understanding of attribute importance. The analysis of the proposed methods yields significant findings. The weight learning method proves instrumental in discerning the importance of attribute combinations, shedding light on key aspects within feature spaces. Simultaneously, the clustering method based on tensors exhibits improved efficacy in enhancing clustering quality and feature distinction. This not only advances our understanding of attribute importance but also paves the way for more nuanced data analysis methodologies. In conclusion, this research underscores the pivotal role of network platforms in contemporary society, emphasizing their potential for both positive contr

关键词： Network platform tensor-based clustering weight learning multi-linear euclidean

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A hybrid machine learning optimization algorithm for multivariable pore pressure prediction

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Petroleum Science 2024年第1期21卷 535-550页

作者： Song Deng hao-Yu Pan Hai-Ge Wang Shou-Kun Xu Xiao-peng Yan Chao-Wei Li Ming-Guo peng hao-Ping peng Lin Shi Meng Cui Fei Zhao School of Petroleum and Natural Gas Engineering Changzhou UniversityChangzhou213164JiangsuChina Tubular Goods Research Institute of CNPC Beijing102249China CNPC Engineering Technology R&D Company Limited Beijing102206China

Pore pressure is essential data in drilling design,and its accurate prediction is necessary to ensure drilling safety and improve drilling efficiency.Traditional methods for predicting pore pressure are limited when forming particular structures and lithology.In this paper,a machine learning algorithm and effective stress theorem are used to establish the transformation model between rock physical parameters and pore pressure.This study collects data from three wells.Well 1 had 881 data sets for model training,and Wells 2 and 3 had 538 and 464 data sets for model testing.In this paper,support vector machine(SVM),random forest(RF),extreme gradient boosting(XGB),and multilayer perceptron(MLP)are selected as the machine learning algorithms for pore pressure modeling.In addition,this paper uses the grey wolf optimization(GWO)algorithm,particle swarm optimization(PSO)algorithm,sparrow search algorithm(SSA),and bat algorithm(BA)to establish a hybrid machine learning optimization algorithm,and proposes an improved grey wolf optimization(IGWO)algorithm.The IGWO-MLP model obtained the minimum root mean square error(RMSE)by using the 5-fold cross-validation method for the training data.For the pore pressure data in Well 2 and Well 3,the coefficients of determination(R^(2))of SVM,RF,XGB,and MLP are 0.9930 and 0.9446,0.9943 and 0.9472,0.9945 and 0.9488,0.9949 and 0.9574.MLP achieves optimal performance on both training and test data,and the MLP model shows a high degree of generalization.It indicates that the IGWO-MLP is an excellent predictor of pore pressure and can be used to predict pore pressure.

关键词： Pore pressure Grey wolf optimization Multilayer perceptron Effective stress Machine learning

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Improvement in Tol2 transposon for efficient large-cargo capacity transgene applications in cultured cells and zebrafish(Danio rerio)

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Zoological Research 2024年第3期45卷 567-574页

作者： peng-Cheng Wang hao Deng Rang Xu Jiu-Lin Du Rongkun Tao Department of Pediatric Cardiology Xinhua HospitalShanghai Jiao Tong University School of MedicineShanghai 200092China Institute of Neuroscience State Key Laboratory of NeuroscienceCenter for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghai 200031China Medical School Kunming University of Science and TechnologyKunmingYunnan 650500China Scientific Research Center Xinhua HospitalShanghai Jiao Tong University School of MedicineShanghai 200092China University of Chinese Academy of Sciences Beijing 100049China School of Life Science and Technology ShanghaiTech UniversityShanghai 200031China

Most viruses and transposons serve as effective carriers for the introduction of foreign DNA up to 11 kb into vertebrate genomes.However,their activity markedly diminishes with payloads exceeding 11 kb.Expanding the payload capacity of transposons could facilitate more sophisticated cargo designs,improving the regulation of expression and minimizing mutagenic risks associated with molecular therapeutics,metabolic engineering,and transgenic animal production.In this study,we improved the Tol2 transposon by increasing protein expression levels using a translational enhancer(QBI SP163,ST)and enhanced the nuclear targeting ability using the nuclear localization protein H2B(SHT).The modified Tol2 and ST transposon efficiently integrated large DNA cargos into human cell cultures(H1299),comparable to the well-established super PiggyBac system.Furthermore,mRNA from ST and SHT showed a significant increase in transgene delivery efficiency of large DNA payloads(8 kb,14 kb,and 24 kb)into zebrafish(Danio rerio).This study presents a modified Tol2 transposon as an enhanced nonviral vector for the delivery of large DNA payloads in transgenic applications.

关键词： Zebrafish Tol2 transposase Transgene Large payload Synthetic biology

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