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Prominent cycling reversibility and kinetics enabled by CaTiO3 protective layer on Zn metal for aqueous Zn-ion batteries

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Journal of Energy Chemistry 2025年第1期100卷 245-258页

作者： Gaeun Lee Yong Nam Ahn Seongjoon So Chanwoo Park Jong-Seong Bae Taehyun Park Il Tae Kim Jaehyun Hur School of Chemical Biological and Battery Engineering Gachon University Seongnam Busan Center Korea Basic Science Institute

Aqueous Zn-ion batteries （AZIBs） have received considerable attention owing to their various advantages such as safety,low cost,simple battery assembly conditions,and high ionic ***,they still suffer from serious problems,including uncontrollable dendrite growth,corrosion,hydrogen evolution reaction （HER） from water decomposition,electrode passivation,and unexpected *** creation of a uniform artificial nanocrystal layer on the Zn anode surface is a promising strategy for resolving these ***,we propose the use of a perovskite CaTiO3（CTO） protective layer on Zn（CTO@Zn） as a promising approach for improving the performance of *** CTO artificial layer provides an efficient pathway for Zn ion diffusion towards the Zn metal because of the high dielectric constant （εr=180） and ferroelectric characteristics that enable the alignment of dipole moments and redistribute the Zn2+ions in the CTO *** avoiding the direct contact of the Zn anode with the electrolyte solution,the uneven dendrite growth,corrosion,parasitic side reactions,and HER are mitigated,while CTO retains its mechanical and chemical robustness during ***,CTO@Zn demonstrates an improved lifespan in a symmetric cell configuration compared with bare ***@Zn shows steady overpotential （～68 m V） for 1500 h at 1 mA cm-2/0.5 mA h cm-2,excelling bare ***,when paired with the V2O5-C cathode,the CTO@Zn//V2O5-C full battery delivers 148.4 mA h g-1（based on the mass of the cathode） after 300 *** study provides new insights into Zn metal anodes and the development of high-performance AZIBs.

关键词： Artificial layer Dielectric constant Zn metal anode Zinc aqueous battery

Recovery of the injured neural system through gene delivery to surviving neurons in Parkinson’s disease

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Neural Regeneration Research 2025年第10期20卷 2855-2861页

作者： Chanchal Sharma Sehwan Kim Hyemi Eo Sang Ryong Kim School of Life science Kyungpook National UniversityDaeguKorea BK21 FOUR KNU Creative BioResearch Group Kyungpook National University DaeguKorea Brain science and Engineering institute Kyungpook National UniversityDaeguKorea

A critical unaddressed problem in Parkinson’s disease is the lack of therapy that slows or hampers *** medications effectively manage symptoms,they offer no long-term benefit because they fail to address the underlying neuronal *** highlights that the elusive goals of halting progression and restoring damaged neurons limit the long-term impact of current *** clinical trials using gene therapy have demonstrated the safety of various vector delivery systems,dosages,and transgenes expressed in the central nervous system,signifying tangible and substantial progress in applying gene therapy as a promising Parkinson’s disease ***,at diagnosis,many dopamine neurons remain in the substantia nigra,offering a potential window for recovery and *** propose that modulating these surviving dopamine neurons and axons in the substantia nigra and striatum using gene therapy offers a potentially more impactful therapeutic approach for future ***,innovative gene therapies that focus on preserving the remaining elements may have significant potential for enhancing long-term outcomes and the quality of life for patients with Parkinson’s *** this review,we provide a perspective on how gene therapy can protect vulnerable elements in the substantia nigra and striatum,offering a novel approach to addressing Parkinson’s disease at its core.

关键词： adeno-associated virus gene therapy neuroprotection neurorestoration neurotrophic factor nigrostriatal dopamine pathway pro-survival protein

Aligned Ion Conduction Pathway of Polyrotaxane‑Based Electrolyte with Dispersed Hydrophobic Chains for Solid‑State Lithium–Oxygen Batteries

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Nano-Micro Letters 2025年第2期17卷 169-186页

作者： Bitgaram Kim Myeong‑Chang Sung Gwang‑Hee Lee Byoungjoon Hwang Sojung Seo Ji‑Hun Seo Dong‑Wan Kim Department of Materials science and Engineering Korea University145 Anam‑RoSeongbuk‑GuSeoul 02841Republic of Korea School of Civil Environmental and Architectural EngineeringKorea University145 Anam‑RoSeongbuk‑GuSeoul 02841Republic of Korea Materials science and Chemical Engineering Center Institute for Advanced Engineering(IAE)Yongin 17180Republic of Korea

A critical challenge hindering the practical application of lithium–oxygen batteries(LOBs)is the inevitable problems associated with liquid electrolytes,such as evaporation and safety *** study addresses these problems by proposing a modified polyrotaxane(mPR)-based solid polymer electrolyte(SPE)design that simultaneously mitigates solvent-related problems and improves ***-SPE exhibits high ion conductivity(2.8×10^(−3)S cm^(−1)at 25℃)through aligned ion conduction pathways and provides electrode protection ability through hydrophobic chain *** this mPR-SPE into solid-state LOBs resulted in stable potentials over 300 *** situ Raman spectroscopy reveals the presence of an LiO_(2)intermediate alongside Li_(2)O_(2)during oxygen *** situ X-ray diffraction confirm the ability of the SPE to hinder the permeation of oxygen and moisture,as demonstrated by the air permeability *** present study suggests that maintaining a low residual solvent while achieving high ionic conductivity is crucial for restricting the sub-reactions of solid-state LOBs.

关键词： Solid polymer electrolyte Lithium-oxygen batteries Polyrotaxane ion conductivity Hydrophobic chain

Maximizing biomass utilization: An integrated strategy for coproducing multiple chemicals

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Journal of Energy Chemistry 2025年第1期100卷 180-191页

作者： Byeongchan Ahn Sua Jo Jonggeol Na J.Jay Liu Young-Ju Kim Wangyun Won Department of Chemical and Biological Engineering Korea University Department of Chemical Engineering (Integrated process) Kyung Hee University Department of Chemical Engineering and Materials science Ewha Womans University Department of Chemical Engineering Pukyong National University Resources Engineering Plant Research Department Korea Institute of Geoscience and Mineral Resources

Lignocellulosic biomass is one of the viable solutions to alleviate the global warming. However, the limited utilization of biomass majorly focused on cellulose and hemicellulose restricts the economic and environmental feasibilities. To cope with this issue, we proposed an integrated process of co-producing 1,6-hexanediol（1,6-HDO） with tetrahydrofuran and adipic acid from biomass, referred to as Strategy A. To compare the impacts of lignin upgrading and feedstock, Strategy B, which co-produces tetrahydrofuran alone, and Strategy C, which is the traditional route to produce 1,6-HDO from fossil fuels, were used. Heat networks are also designed to reduce operating costs and indirect carbon emissions due to energy consumption, saving 87% and 83% of the heat and cooling requirements, respectively, in Strategy A. The market competitiveness of Strategy A was evaluated by determining the minimum selling price through techno-economic analysis, and sustainability was thoroughly investigated by quantifying the environmental impacts through both midpoint and endpoint life-cycle assessments（LCAs）.Strategy A was found to be the most favorable both economically（USRDSCHARDOLLAR3,402/ton） and environmentally（-26.9 kg CO2eq.）. This indicates that lignin valorization is not only economically but also environmentally preferred. Finally, changes in economic and environmental feasibilities depending on economic, process, and environmental parameters were investigated using sensitivity and uncertainty analyses. The results of these analyses provide valuable insight into bio-based chemical production.

关键词： Biorefinery Carbon mitigation Climate change Global warming Lignin utilization Bioeconomy

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

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Computer Modeling in Engineering & sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software Engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical Engineering of Southern Medical University(SMU-dataset),and The National institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

Movement analysis in the diagnosis and management of Parkinson’s disease

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Neural Regeneration Research 2025年第2期20卷 485-486页

作者： Johannes Burtscher Nicolas Bourdillon Jules MJanssen Daalen Aurélien Patoz Julien FBally Martin Kopp Davide Malatesta Bastiaan RBloem institute of sport sciences University of LausanneLausanneSwitzerland Radboud University Medical Center Department of NeurologyDonders Institute for BrainCognition and BehaviorCenter of Expertise for Parkinson and Movement DisordersNijmegenThe Netherlands Radboud University Medical Center Department of Medical BioSciencesNijmegenThe Netherlands Research and Development Department Volodalen Swiss Sport LabAigleSwitzerland Service of Neurology Department of Clinical NeurosciencesLausanne University Hospital(CHUV)and University of Lausanne(UNIL)LausanneSwitzerland Department of sport science University of InnsbruckInnsbruckAustria

Challenges in the diagnosis and treatment of Parkinson’s disease:Parkinson’s disease(PD)is an increasingly prevalent neurodegenerative disease,at first sight primarily characterized by motor symptoms,although non-motor symptoms also constitute a major part of the overall ***,this disease cannot be diagnosed reliably until a large part of the vulnerable dopaminergic neurons has been irretrievably lost,and the disease progresses *** biological criteria for PD have been proposed recently and might eventually improve early diagnosis,but they require further validation,and their use will initially be restricted to a research environment(Darweesh et al.,2024).

关键词： diagnosis Clinical eventually

PGLYRP1 protein as a novel mediator of cellular dialogue in neuroinflammation

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Neural Regeneration Research 2025年第7期20卷 1993-1994页

作者： Anup Bhusal Won-Ha Lee Kyoungho Suk Department of Pharmacology School of MedicineKyungpook National UniversityDaeguRepublic of Korea BK21 Plus KNU Biomedical Convergence Program Department of Biomedical ScienceSchool of MedicineKyungpook National UniversityDaeguRepublic of Korea School of Life sciences BK21 plus KNU Creative BioResearch GroupKyungpook National UniversityDaeguRepublic of Korea Brain science and Engineering institute Kyungpook National UniversityDaeguRepublic of Korea

Neuroinflammation has been identified as a crucial element in several neurological disorders. Glial cells play a critical role in directing neuroinflammation, both in deleterious and beneficial ways.

关键词： inflammation considerably

Regulation of sleep by astrocytes in the hypothalamic ventrolateral preoptic nucleus

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Neural Regeneration Research 2025年第4期20卷 1098-1100页

作者： Jae-Hong Kim Ruqayya Afridi Il-Sung Jang Maan Gee Lee Kyoungho Suk Brain korea 21 four KNU Convergence Educational Program of Biomedical sciences for Creative Future Talents School of MedicineKyungpook National UniversityDaeguRepublic of Korea Department of Pharmacology School of MedicineKyungpook National UniversityDaeguRepublic of Korea Department of Pharmacology School of DentistryKyungpook National UniversityDaeguRepublic of Korea Brain science&Engineering institute Kyungpook National UniversityDaeguRepublic of Korea

Astrocytes are functionally dynamic cells that support neurons in multiple ways throughout an organism’s *** astrocytic regulation of neuronal activity has been increasingly recognized in recent *** are now recognized as playing a more complex role than mere bystanders in the central nervous ***,their role in regulating the sleep neurocircuitry is not well *** this perspective,we highlight the role of astrocytes in sleep modulation,with a particular focus on regulatory mechanisms related to the ventrolateral preoptic nucleus(VLPO)of the *** briefly discuss recent literature reporting the role of VLPO astrocytes in regulating sleep-associated behaviors.

关键词： sleep ventrolateral astrocytes

Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation Correction

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Computer Modeling in Engineering & sciences 2025年第1期142卷 299-327页

作者： A.Robert Singh Suganya Athisayamani Gyanendra Prasad Joshi Bhanu Shrestha Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203Tamil NaduIndia School of Computing Sastra Deemed to be UniversityThanjavur613401Tamil NaduIndia Department of Artificial Intelligence&Software Kangwon National UniversitySamcheok25913Republic of Korea Department of Information Convergence System Graduate School of Smart ConvergenceKwangwoon UniversitySeoul01897Republic of Korea

Myocardial perfusion imaging(MPI),which uses single-photon emission computed tomography(SPECT),is a well-known estimating tool for medical diagnosis,employing the classification of images to show situations in coronary artery disease(CAD).The automatic classification of SPECT images for different techniques has achieved near-optimal accuracy when using convolutional neural networks(CNNs).This paper uses a SPECT classification framework with three steps:1)Image denoising,2)Attenuation correction,and 3)Image *** denoising is done by a U-Net architecture that ensures effective image *** correction is implemented by a convolution neural network model that can remove the attenuation that affects the feature extraction process of ***,a novel multi-scale diluted convolution(MSDC)network is *** merges the features extracted in different scales and makes the model learn the features more *** scales of filters with size 3×3 are used to extract *** three steps are compared with state-of-the-art *** proposed denoising architecture ensures a high-quality image with the highest peak signal-to-noise ratio(PSNR)value of *** proposed classification method is compared with the five different CNN models,and the proposed method ensures better classification with an accuracy of 96%,precision of 87%,sensitivity of 87%,specificity of 89%,and F1-score of 87%.To demonstrate the importance of preprocessing,the classification model was analyzed without denoising and attenuation correction.

关键词： SPECT-MPI CAD MSDC denoising attenuation correction classification