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Meningeal lymphatic vessel crosstalk with central nervous system immune cells in aging and neurodegenerative diseases

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Neural Regeneration Research 2025年第3期20卷 763-778页

作者： Minghuang Gao Xinyue Wang Shijie Su Weicheng Feng Yaona Lai Kongli Huang Dandan Cao Qi Wang science and technology Innovation Center Guangzhou University of Chinese MedicineGuangzhouGuangdong ProvinceChina Institute of Clinical Pharmacology Guangzhou University of Chinese MedicineGuangzhouGuangdong ProvinceChina The Sixth Affiliated Hospital Sun Yat-sen UniversityGuangzhouGuangdong ProvinceChina

Meningeal lymphatic vessels form a relationship between the nervous system and periphery, which is relevant in both health and disease. Meningeal lymphatic vessels not only play a key role in the drainage of brain metabolites but also contribute to antigen delivery and immune cell activation. The advent of novel genomic technologies has enabled rapid progress in the characterization of myeloid and lymphoid cells and their interactions with meningeal lymphatic vessels within the central nervous system. In this review, we provide an overview of the multifaceted roles of meningeal lymphatic vessels within the context of the central nervous system immune network, highlighting recent discoveries on the immunological niche provided by meningeal lymphatic vessels. Furthermore, we delve into the mechanisms of crosstalk between meningeal lymphatic vessels and immune cells in the central nervous system under both homeostatic conditions and neurodegenerative diseases, discussing how these interactions shape the pathological outcomes. Regulation of meningeal lymphatic vessel function and structure can influence lymphatic drainage, cerebrospinal fluid-borne immune modulators, and immune cell populations in aging and neurodegenerative disorders, thereby playing a key role in shaping meningeal and brain parenchyma immunity.

关键词： central nervous system meningeal lymphatic vessels immunity myeloid cells lymphatic cells neurodegenerative disease

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A robust statistical prediction model for late-summer heavy precipitation days in North china

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science china Earth sciences 2025年第1期68卷 158-171页

作者： Shunli JIANG Tingting HAN Xin ZHOU Huijun WANG Zhicong YIN Xiaolei SONG Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education Nanjing University for Information Science and Technology Nansen-Zhu International Research Centre Institute of Atmospheric Physics Chinese Academy of Sciences Southern Marine science and Engineering guangdong Laboratory (Zhuhai)

Recently, heavy precipitation(HP) events have occurred frequently in North china(NC), causing devastating economic losses and human fatalities. However, the short-term climate prediction of HP is quite limited. Combining year-to-year increment(DY) method and sliding correlations, we developed a robust seasonal prediction model for late-summer HP days(HPDs) in NC during 1982–2022, utilizing three independent predictors—February sea surface temperature(SST) in the Indian Ocean(SST＿IO), February snow depth over North Asia(SDE＿NA), and May melted snow depth in NC(MSDE＿NC). The SST＿IO anomalies affect NC's precipitation through the Pacific-Japan pattern. The SDE＿NA anomalies are associated with East Asian anomalous anticyclone by southeastern propagation of Rossby wave at Eurasia. The MSDE＿NC anomalies are followed by vertical motion and moisture anomalies in situ and thereby cause precipitation anomalies. This prediction model can well simulate the variations of the HPDs, with a correlation coefficient(CC) of 0.81(0.65) between the observed and predicted HPDs＿DY(HPDs＿anomaly). The percentage with the same sign for 15 extreme HPDs＿anomaly years(PSSE) is 100%.Moreover, in the cross-validation test during 1982–2022, the PSSE for HPDs＿anomaly is as high as 100%, along with a low rootmean-square error of 1.14. For independent hindcasts during 2013–2022, the CC between the observed and predicted HPDs＿DY(HPDs＿anomaly) is 0.93(0.83), together with high Nash-Sutcliffe efficiency(0.82) and agreement index(0.89). Specifically, the predictions are broadly consistent with the observations for 2015, 2016, 2017, 2021, and 2022, reflecting excellent performance of this prediction model of HPDs in NC.

关键词： Heavy precipitation at North china Year-to-year increment approach Robust seasonal prediction Sea surface temperature Snow depth

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Early identification of stroke through deep learning with multi-modal human speech and movement data

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Neural Regeneration Research 2025年第1期20卷 234-241页

作者： Zijun Ou Haitao Wang Bin Zhang Haobang Liang Bei Hu Longlong Ren Yanjuan Liu Yuhu Zhang Chengbo Dai Hejun Wu Weifeng Li Xin Li School of Computer science and Engineering Sun Yat-sen UniversityGuangzhouGuangdong ProvinceChina Department of Neurology Guangdong Neuroscience InstituteGuangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina Department of Emergency Medicine Guangdong Provincial People’s Hospital(Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina

Early identification and treatment of stroke can greatly improve patient outcomes and quality of *** clinical tests such as the Cincinnati Pre-hospital Stroke Scale(CPSS)and the Face Arm Speech Test(FAST)are commonly used for stroke screening,accurate administration is dependent on specialized *** this study,we proposed a novel multimodal deep learning approach,based on the FAST,for assessing suspected stroke patients exhibiting symptoms such as limb weakness,facial paresis,and speech disorders in acute *** collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements,facial expressions,and speech tests based on the *** compared the constructed deep learning model,which was designed to process multi-modal datasets,with six prior models that achieved good action classification performance,including the I3D,SlowFast,X3D,TPN,TimeSformer,and *** found that the findings of our deep learning model had a higher clinical value compared with the other ***,the multi-modal model outperformed its single-module variants,highlighting the benefit of utilizing multiple types of patient data,such as action videos and speech *** results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke,thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

关键词： artificial intelligence deep learning diagnosis early detection FAST screening stroke

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Crustal magma oxidation state and endowments in porphyry copper deposits

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science china Earth sciences 2025年第1期68卷 226-236页

作者： Yumin AI Massimo CHIARADIA Chao WU Huayong CHEN Key Laboratory of Mineralogy and Metallogeny Guangzhou Institute of Geochemistry Chinese Academy of Sciences University of Chinese Academy of sciences Department of Earth sciences University of Geneva guangdong Provincial Key Laboratory of Mineral Physics and Materials

Porphyry copper deposits（PCDs） supply the majority of the world's copper（Cu） as well as significant amounts of molybdenum（Mo） and gold（Au）. The formation of these deposits is controlled by a variety of geological factors, among which the magmatic oxidation is one of the focuses of current research. This study investigates the redox characteristics of arc magmas by analyzing the ratio of vanadium（V） to scandium（Sc） and its correlation with the oxygen fugacity （fO2） of magmas from arcs of various crustal thicknesses globally. We compiled an extensive dataset of published V/Sc values and studied the partition coefficients of Vand Sc between minerals and silicate melts across various magmatic environments. The results demonstrate that fractional crystallization of magnetite markedly reduces V/Sc values of the residual melt. Furthermore, magnesium number（Mg#） at the onset of magnetite fractionation is strongly positively correlated with fO2of the equilibrium magma. Based on this,the oxidation of arc magmas from different crustal thicknesses can be evaluated. The result suggests that magmas generated in crusts thicker than 20 km tend to be more oxidized with increasing crust thickness. This trend is attributed to enhanced intracrustal differentiation processes involving garnet and amphibole, particularly in mature island and continental arcs. In contrast,magmas in thinner arc crusts（<20 km）, which are significantly influenced by subducted slab materials, display higher oxidation states than most of their thicker crust counterparts. These findings suggest that both subduction dynamics and crustal thickness play a vital role in determining the oxidation state of arc magmas and, consequently, their capacity to generate PCDs. Highly oxidized, primitive arc magmas are less favorable for PCD formation due to that they tend to experience magnetite fractionation and thus sulfide saturation in the early stage of magma evolution, a process leading to copper depletion. On the contra

关键词： Magma evolution V/Sc systematics Magnetite Oxygen fugacity Porphyry copper deposits

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Differential distribution of PINK1 and Parkin in the primate brain implies distinct roles

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Neural Regeneration Research 2025年第4期20卷 1124-1134页

作者： Yanting Liu Wei Huang Jiayi Wen Xin Xiong Ting Xu Qi Wang Xiusheng Chen Xianxian Zhao Shihua Li Xiaojiang Li Weili Yang guangdong Key Laboratory of Non-human Primate Research Key Laboratory of CNS Regeneration(Ministry of Education)Guangdong-Hongkong-Macao CNS Regeneration Institute of Jinan UniversityJinan UniversityGuangzhouGuangdong ProvinceChina

The vast majority of in vitro studies have demonstrated that PINK1 phosphorylates Parkin to work together in mitophagy to protect against neuronal ***,it remains largely unclear how PINK1 and Parkin are expressed in mammalian *** has been difficult to address because of the intrinsically low levels of PINK1 and undetectable levels of phosphorylated Parkin in small *** this issue is critical for elucidating the in vivo roles of PINK1 and ***,we showed that the PINK1 kinase is selectively expressed as a truncated form(PINK1–55)in the primate *** the present study,we used multiple antibodies,including our recently developed monoclonal anti-PINK1,to validate the selective expression of PINK1 in the primate *** found that PINK1 was stably expressed in the monkey brain at postnatal and adulthood stages,which is consistent with the findings that depleting PINK1 can cause neuronal loss in developing and adult monkey ***1 was enriched in the membrane-bound fractionations,whereas Parkin was soluble with a distinguishable *** double staining experiments showed that PINK1 and Parkin did not colocalize under physiological conditions in cultured monkey astrocytes,though they did colocalize on mitochondria when the cells were exposed to mitochondrial *** findings suggest that PINK1 and Parkin may have distinct roles beyond their well-known function in mitophagy during mitochondrial damage.

关键词： neurodegeneration Parkin Parkinson’s disease PINK1 subcellular distribution

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Exercise preconditioning alleviates ischemia-induced memory deficits by increasing circulating adiponectin

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Neural Regeneration Research 2025年第5期20卷 1445-1454页

作者： Meifeng Zheng Borui Zhang Sonata S Y Yau Kwok-Fai So Li Zhang Haining Ou Department of Rehabilitation Medicine Guangzhou Medical UniversityGuangzhouGuangdong ProvinceChina Department of Rehabilitation Medicine The Fifth Clinical College of Guangzhou Medical UniversityGuangzhouGuangdong ProvinceChina Key Laboratory of CNS Regeneration(Ministry of Education) Guangdong-Hong Kong-Macao Institute of CNS RegenerationJinan UniversityGuangzhouGuangdong ProvinceChina Department of Rehabilitation sciences The Hong Kong Polytechnic UniversityHong Kong Special Administrative RegionChina State Key Laboratory of Brain and Cognitive science Li Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina Center for Exercise and Brain science School of PsychologyShanghai University of SportShanghaiChina Neuroscience and Neurorehabilitation Institute University of Health and Rehabilitation SciencesQingdaoShandong ProvinceChina

Cerebral ischemia is a major health risk that requires preventive approaches in addition to drug *** exercise enhances neurogenesis and synaptogenesis,and has been widely used for functional rehabilitation after *** this study,we determined whether exercise training before disease onset can alleviate the severity of cerebral *** also examined the role of exercise-induced circulating factors in these *** mice were subjected to 14 days of treadmill exercise training before surgery for middle cerebral artery *** found that this exercise pre-conditioning strategy effectively attenuated brain infarct area,inhibited gliogenesis,protected synaptic proteins,and improved novel object and spatial memory *** analysis showed that circulating adiponectin plays a critical role in these preventive effects of *** activation of adiponectin receptors by Adipo Ron mimicked the effects of exercise,while inhibiting receptor activation abolished the exercise *** summary,our results suggest a crucial role of circulating adiponectin in the effects of exercise pre-conditioning in protecting against cerebral ischemia and supporting the health benefits of exercise.

关键词： adiponectin cerebral ischemia exercise pre-conditioning hippocampus memory function middle cerebral artery occlusion prefrontal cortex synaptic proteins treadmill exercise

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Reduced mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor contributes to neurodegeneration in a model of spinal and bulbar muscular atrophy pathology

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Neural Regeneration Research 2025年第9期20卷 2655-2666页

作者： Yiyang Qin Wenzhen Zhu Tingting Guo Yiran Zhang Tingting Xing Peng Yin Shihua Li Xiao-Jiang Li Su Yang guangdong Key Laboratory of Non-human Primate Research Key Laboratory of CNS Regeneration(Ministry of Education)Guangdong–HongKong–Macao Institute of CNS RegenerationJinan UniversityGuangzhouGuangdong ProvinceChina

Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto *** mutant androgen receptor protein,characterized by polyglutamine expansion,is prone to misfolding and forms aggregates in both the nucleus and cytoplasm in the brain in spinal and bulbar muscular atrophy *** aggregates alter protein-protein interactions and compromise transcriptional *** this study,we reported that in both cultured N2a cells and mouse brain,mutant androgen receptor with polyglutamine expansion causes reduced expression of mesencephalic astrocyte-de rived neurotrophic *** n of mesencephalic astrocyte-derived neurotrophic factor amelio rated the neurotoxicity of mutant androgen receptor through the inhibition of mutant androgen receptor *** down endogenous mesencephalic astrocyte-derived neurotrophic factor in the mouse brain exacerbated neuronal damage and mutant androgen receptor *** findings suggest that inhibition of mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor is a potential mechanism underlying neurodegeneration in spinal and bulbar muscular atrophy.

关键词： androgen receptor mesencephalic astrocyte-derived neurotrophic factor mouse model neurodegeneration neuronal loss neurotrophic factor polyglutamine disease protein misfolding spinal and bulbar muscular atrophy transcription factor

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A Multi-Objective Particle Swarm Optimization Algorithm Based on Decomposition and Multi-Selection Strategy

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Computers, Materials & Continua 2025年第1期82卷 997-1026页

作者： Li Ma Cai Dai Xingsi Xue Cheng Peng School of Computer science Shaanxi Normal UniversityXi’an710119China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of TechnologyFuzhou350118China Information Construction and Management Center and Institute of Artificial Intelligence and Educational New Productivity Ningxia Normal UniversityGuyuan756099China

The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization *** the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search ***,two update strategies based on decomposition are used to update the evolving population and external archive,***,a multiselection strategy is *** first strategy is for the subspace without a non-dominated *** the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global *** second strategy is for the subspace with a non-dominated *** the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local *** third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated *** the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to ***,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search ***,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test *** results show that the proposed algorithm has better performance.

关键词： Multi-objective optimization multi-objective particle swarm optimization decomposition multi-selection strategy

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Integration of perioperative features and intragraft TCF7L2 expression to predict lipid metabolic disorder in liver transplant recipients

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science china Life sciences 2025年第1期68卷 297-299页

作者： Junbin Zhou Rongli Wei Guanghan Fan Zhengxing Lian Xuanyu Zhang Linsong Tang Zhetuo Qi Haiyang Xie Shusen Zheng Qiang Wei Xiao Xu Department of Hepatobiliary and Pancreatic Surgery People's Hospital of LishuiAffiliated Lishui Hospital of Wenzhou Medical UniversityThe First Affiliated Hospital of Lishui University NHFPC Key Laboratory of Combined Multi-Organ Transplantation Key Laboratory of Integrated Oncology and Intelligent Medicine of Zhejiang province Department of Hepatobiliary and Pancreatic SurgeryHangzhou First People's Hospital Department of Hepatobiliary and Pancreatic Surgery The First Affiliated HospitalZhejiang University School of Medicine Department of Urology The Second Affiliated HospitalZhejiang University School of Medicine Department of Hepatobiliary and Pancreatic Surgery Department of Liver TransplantationShulan (Hangzhou) Hospital Hangzhou Medical College Zhejiang University School of Medicine

Dear Editor, Liver transplantation(LT) is the only curative therapy for patients with endstage liver disease(He et al., 2023; Ling et al., 2022). Post-transplant hypertriglyceridemia(PTHT), which has an incidence of up to 32.8% in 6 months after LT, is one of the major post-transplant complications(Toshima et al., 2020).

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A Lightweight Multiscale Feature Fusion Network for Solar Cell Defect Detection

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Computers, Materials & Continua 2025年第1期82卷 521-542页

作者： Xiaoyun Chen Lanyao Zhang Xiaoling Chen Yigang Cen Linna Zhang Fugui Zhang School of Mechanical Engineering Guizhou UniversityGuiyang550025China School of Computer science and technology Beijing Jiaotong UniversityBeijing100044China

Solar cell defect detection is crucial for quality inspection in photovoltaic power generation *** the production process,defect samples occur infrequently and exhibit random shapes and sizes,which makes it challenging to collect defective ***,the complex surface background of polysilicon cell wafers complicates the accurate identification and localization of defective *** paper proposes a novel Lightweight Multiscale Feature Fusion network(LMFF)to address these *** network comprises a feature extraction network,a multi-scale feature fusion module(MFF),and a segmentation ***,a feature extraction network is proposed to obtain multi-scale feature outputs,and a multi-scale feature fusion module(MFF)is used to fuse multi-scale feature information *** order to capture finer-grained multi-scale information from the fusion features,we propose a multi-scale attention module(MSA)in the segmentation network to enhance the network’s ability for small target ***,depthwise separable convolutions are introduced to construct depthwise separable residual blocks(DSR)to reduce the model’s parameter ***,to validate the proposed method’s defect segmentation and localization performance,we constructed three solar cell defect detection datasets:SolarCells,SolarCells-S,and *** and SolarCells-S are monocrystalline silicon datasets,and PVEL-S is a polycrystalline silicon *** results show that the IOU of our method on these three datasets can reach 68.5%,51.0%,and 92.7%,respectively,and the F1-Score can reach 81.3%,67.5%,and 96.2%,respectively,which surpasses other commonly usedmethods and verifies the effectiveness of our LMFF network.

关键词： Defect segmentation multi-scale feature fusion multi-scale attention depthwise separable residual block

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