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Perfluoropentane-based oxygen-loaded nanodroplets reduce microglial activation through metabolic reprogramming

Neural Regeneration Research 2025年第4期20卷 1178-1191页

作者： Wanxian Luo Chuanhui Xu Linxi Li Yunxiang Ji Yezhong Wang Yingjia Li Yongyi Ye Department of Medicine Ultrasonics Nanfang HospitalSouthern Medical UniversityGuangzhouGuangdong ProvinceChina Institute of Neuroscience Department of NeurosurgeryThe Second Affiliated Hospital of Guangzhou Medical UniversityGuangzhouGuangdong ProvinceChina

Microglia,the primary immune cells within the brain,have gained recognition as a promising therapeutic target for managing neurodegenerative diseases within the central nervous system,including Parkinson’s *** perfluorocarbon droplets have been reported to not only possess a high oxygen-carrying capacity,but also exhibit remarkable anti-inflammatory ***,the role of perfluoropentane in microglia-mediated central inflammatory reactions remains poorly *** this study,we developed perfluoropentane-based oxygen-loaded nanodroplets(PFP-OLNDs)and found that pretreatment with these droplets suppressed the lipopolysaccharide-induced activation of M1-type microglia in vitro and in vivo,and suppressed microglial activation in a mouse model of Parkinson’s *** suppression led to a reduction in the inflammatory response,oxidative stress,and cell migration capacity in ***,the neurotoxic effects were mitigated,which alleviated neuronal ***,ultrahigh-performance liquid chromatography–tandem mass spectrometry showed that the anti-inflammatory effects of PFP-OLNDs mainly resulted from the modulation of microglial metabolic *** further showed that PFP-OLNDs regulated microglial metabolic reprogramming through the AKT-mTOR-HIF-1α***,our findings suggest that the novel PFP-OLNDs constructed in this study alleviate microglia-mediated central inflammatory reactions through metabolic reprogramming.

关键词： metabolic reprogramming microglia microglial migration nanotherapy neurodegenerative diseases neuroinflammation oxygen-loaded nanodroplets Parkinson’s disease perfluoropentane ultra-performance liquid chromatography–mass spectrometry

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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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Small modifications of endo-functionalized cavities lead to large changes in molecular interaction in water

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Science China Chemistry 2025年第1期68卷 369-376页

作者： Song-Meng Wang Hao Nian Yan-Fang Wang Li-Shuo Zheng Yu-Tao Zheng Yi-Wei Dong Liping Huang Xiaoping Wang Wei Jiang Liu-Pan Yang Department of Chemistry Southern University of Science and TechnologyShenzhen 518055China School of Pharmaceutical Science Hengyang Medical SchoolUniversity of South ChinaHengyang 421001China School of Chemistry and Pharmaceutical Sciences State Key Laboratory for Chemistry and Molecular Engineering of Medicinal ResourcesGuangxi Normal UniversityGuilin 541004China

Studying molecular recognition in aqueous environments is crucial for understanding biological ***,we present a series of N-doped endo-functionalized anthracene-based cavities by introducing inward-directed pyridine *** subtle modifications can significantly affect the binding properties of these receptors,which is similar to the mutations in biological *** theoretical calculations and molecular recognition experiments demonstrated that these“mutations”have an impact on the hydrophobicity and charge distribution of the hosts,consequently significantly influencing molecular *** is crucial for understanding the intricate mechanisms of molecular-level interactions in biological receptors.

关键词： host-guest interaction hydrophobic effect endo-functionalized cavity mutation pyridine

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Immunoassay development guidelines for neurodegenerative disorders:lessons from a failed pS129-α-synuclein electrochemiluminescence immunoassay

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Neural Regeneration Research 2025年第10期20卷 2906-2908页

作者： Hash Brown Taha Alanna Morris Leonard Davis School of Gerontology University of Southern CaliforniaLos AngelesCAUSA Deparmtent of Neurobiology David Geffen School of MedicineUniversity of California Los AngelesLos AngelesCAUSA

An aging population is a double-edged *** one hand,advancements in biotechnology and healthcare allow more people to enjoy longer *** the other hand,increases in the aging population accompany a surge in age-associated diseases,particularly neurodegenerative *** aging is the primary risk factor for many neurodegenerative disorders,living longer does not necessarily equate to maintaining a reasonable quality of life(Feigin et al.,2020).

关键词： aging degenerative necessarily

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Quantum walks advantage on the dihedral group for uniform sampling problem

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Communications in Theoretical Physics 2025年第2期77卷 89-100页

作者： Shyam Dhamapurkar Yuhang Dang Saniya Wagh Xiu-Hao Deng Shenzhen Institute for Quantum Science and Engineering (SIQSE) Southern University of Science and Technology Department of Mathematics Tata Institute of Fundamental Research International Quantum Academy (SIQA) Futian District

Random walk algorithms are crucial for sampling and approximation problems in statistical physics and theoretical computer *** mixing property is necessary for Markov chains to approach stationary distributions and is facilitated by *** walks show promise for faster mixing times than classical methods but lack universal proof,especially in finite group ***,we investigate the continuous-time quantum walks on Cayley graphs of the dihedral group D2nfor odd n,generated by the smallest inverse closed symmetric *** present a significant finding that,in contrast to the classical mixing time on these Cayley graphs,which typically takes at least order Ω(n2log（1/2■）),the continuous-time quantum walk mixing time on D2nis of order O(n（log n）5log（1/■）),achieving a quadratic improvement over the classical *** paper advances the general understanding of quantum walk mixing on Cayley graphs,highlighting the improved mixing time achieved by continuous-time quantum walks on *** work has potential applications in algorithms for a class of sampling problems based on non-abelian groups.

关键词： continuous time quantum walks Cayley graphs non-abelian groups mixing time

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Cortico-striatal gamma oscillations are modulated by dopamine D3 receptors in dyskinetic rats

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Neural Regeneration Research 2025年第4期20卷 1164-1177页

作者： Pengfei Wang Yuewei Bi Min Li Jiazhi Chen Zhuyong Wang Huantao Wen Ming Zhou Minjie Luo Wangming Zhang Neurosurgery Center Department of Pediatric NeurosurgeryGuangdong Provincial Key Laboratory on Brain Function Repair and RegenerationZhujiang HospitalSouthern Medical UniversityGuangzhouGuangdong ProvinceChina

Long-term levodopa administration can lead to the development of levodopa-induced *** oscillations are a widely recognized hallmark of abnormal neural electrical activity in levodopa-induced ***,studies have reported increased oscillation power in cases of levodopa-induced ***,little is known about how the other electrophysiological parameters of gamma oscillations are altered in levodopa-induced ***,the role of the dopamine D3 receptor,which is implicated in levodopa-induced dyskinesia,in movement disorder-related changes in neural oscillations is *** found that the cortico-striatal functional connectivity of beta oscillations was enhanced in a model of Parkinson’s ***,levodopa application enhanced cortical gamma oscillations in cortico-striatal projections and cortical gamma aperiodic components,as well as bidirectional primary motor cortex(M1)↔dorsolateral striatum gamma *** of PD128907(a selective dopamine D3 receptor agonist)induced dyskinesia and excessive gamma oscillations with a bidirectional M1↔dorsolateral striatum ***,administration of PG01037(a selective dopamine D3 receptor antagonist)attenuated dyskinesia,suppressed gamma oscillations and cortical gamma aperiodic components,and decreased gamma causality in the M1→dorsolateral striatum *** findings suggest that the dopamine D3 receptor plays a role in dyskinesia-related oscillatory activity,and that it has potential as a therapeutic target for levodopa-induced dyskinesia.

关键词： aperiodic components dopamine D3 receptor dorsolateral striatum functional connectivity gamma oscillations levodopa-induced-dyskinesia local field potentials neuromodulation Parkinson’s disease primary motor cortex

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Prediction of velocity and pressure of gas-liquid flow using spectrum-based physics-informed neural networks

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Applied Mathematics and Mechanics(English Edition) 2025年第2期46卷 341-356页

作者： Nanxi DING Hengzhen FENG H.Z. LOU Shenghua FU Chenglong LI Zihao ZHANG Wenlong MA Zhengqian ZHANG School of Mechanical Engineering Beijing Institute of Technology university of southern California Xi'an Institute of Electromechanical Information Technology

This research introduces a spectrum-based physics-informed neural network (SP-PINN) model to significantly improve the accuracy of calculation of two-phase flow parameters, surpassing existing methods that have limitations in global and continuous data sampling. SP-PINNs address the challenges of traditional methods in terms of continuous sampling by integrating the spectral analysis and pressure correction into the Navier-Stokes (N-S) equations, enhancing the predictive accuracy especially in critical regions like gas-phase boundaries and velocity peaks. The novel introduction of a pressure-correction module within SP-PINNs mitigates prediction errors, achieving a substantial reduction to 1‰compared with the conventional physics-informed neural network (PINN) approaches. Experimental applications validate the model’s ability to accurately and rapidly predict flow parameters with different sampling time intervals,with the computation time of predicting unsampled data less than 0.01 s. Such advancements signify a 100-fold improvement over traditional DNS calculations, underscoring the model’s potential in the real-time calculation and analysis of multiphase flow dynamics.

关键词： physics-informed neural network (PINN) spectral method two-phase flow parameter prediction O359

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The quest for good research ideas

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Earthquake Science 2025年第2期38卷 152-155页

作者： John Emilio Vidale university of southern California Los Angeles USA

The search for new research ideas is a central challenge for many scientists. Over the past four decades, I have formed opinions on methods for discerning promising paths from how my own work has advanced in fits and ... 详细信息

关键词： own utility list

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Microdynamic modulation through Pt–O–Ni proton and electron “superhighway” for pH-universal hydrogen evolution

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Journal of Energy Chemistry 2025年第2期101卷 808-815页

作者： Dewen Wang Yuting Chen Bohan Yao Tian Meng Yanchao Xu Dongxu Jiao Zhicai Xing Xiurong Yang State Key Laboratory of Electroanalytical Chemistry Changchun Institute of Applied Chemistry Chinese Academy of Sciences university of Science and Technology of China Department of Chemistry Shenzhen Grubbs Institute and Guangdong Provincial Key Laboratory of Energy Materials for Electric Power Southern University of Science and Technology State Key Laboratory of Automotive Simulation and Control School of Materials Science and Engineering Jilin University

Optimizing the microdynamics in alkaline and neutral conditions is a significant but challenging task in developing pH-universal hydrogen evolution（HER） ***,a unique Pt-O-Ni bridge has been constructed to alter the coordination and electronic environment between Pt nanoparticles（Pt_n）and nickel metaphosphate（NPO） substrate（Pt-NPO）.Sufficient electron transfer from NPO to Pt_n to maintain an electron-rich environment and a low valence state of Pt_***,H*is produced from the H2O dissociation on Ni site and then spillover toward Pt sites to bind into H2,which makes up for the insufficient H2O dissociation ability of Pt in Volmer ***-NPO exhibits long-term stability and only need the overpotentials of 22.3,33.0 and 30.5 mV to attain 10 mA cm-2in alkaline,neutral and acidic media,*** anion-exchange membrane（AEM） water electrolyzer catalyzed by Pt-NPO shows high water electrolysis performance that a cell voltage of 1.73 V is needed to obtain the current density of500 mA cm-2in 1 M KOH at 80℃,at the same time maintains good stability for 350 *** regulation strategy proposed in this work is helpful for the design and synthesis of highly efficient pH-universal HER electrocatalysts.

关键词： Atomic and electronic regulation Hydrogen evolution reactions Metal-support interactions Microdynamics pH-universal HER electrocatalysts

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Model Predictive Control Scheduling Strategy for Hydrogen-doped Integrated Energy System Considering Ladder Carbon Trading

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Journal of Thermal Science 2025年第02期 337-351页

作者： JI Zhishi ZHANG Hanqing WANG Pei School of engineering Southern Methodist University Lyle College of Electrical and Power Engineering Hohai University Engineering Research Center of Renewable Power Generation Technologies of Ministry of Education Hohai University

To achieve low-carbon economic operation of hydrogen-doped integrated energy systems while mitigating the stochastic impact of new energy outputs on the system,the coordinated operation mode of hydrogen-doped gas turbines and electrolyzers is focused on,as well as a hybrid energy storage scheme involving both hydrogen and heat storage and an optimized scheduling model for integrated energy systems encompassing electricity-hydrogen-heat-cooling conversions is established.A model predictive control strategy based on deep learning prediction and feedback is proposed,and the effectiveness and superiority of the proposed strategy are demonstrated using error penalty ***,the introduction of hydrogen energy exchange and ladder carbon trading is shown to effectively guide the low-carbon economic operation of hydrogen-doped integrated energy systems across multiple typical scenarios.A sensitivity analysis is conducted based on this framework,revealing that increases in the hydrogen doping ratio of turbines and the carbon base price led to higher system operation costs but effectively reduce carbon emissions.

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