Choline alleviates cognitive impairment in sleep-deprived young mice via reducing neuroinflammation and altering phospholipidomic profile by Si-Yu Huang, Zhi-Jun Yang, Jin Cheng, Hang-Yu Li, Si Chen, Zi-Hui Huang, Jie-Dong Chen, Ruo-Gu Xiong, Meng-Tao Yang, Chen Wang, Meng-Chu Li, Shuang Song, Wen-Ge Huang, Dong-Liang Wang, Hua-Bin Li, Qiu-Ye Lan

“…Choline supplementation significantly improves spatial learning ability. Functional MRI results reveal the hippocampus as a key region affected by sleep deprivation, where choline supplementation notably preserves hippocampal structural integrity and enhanced connectivity. …”
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Identification of m5C RNA modification-related gene signature for predicting prognosis and immune microenvironment-related characteristics of heart failure by Zirui Liu, Rui Feng, Ying Xu, Meili Liu, Haocheng Wang, Yu Lu, Weiqi Wang, Jikai Wang, Cao Zou

“…Four hub genes were identified by machine-learning algorithms and all verified by validation model. …”
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A large-scale MEG and EEG dataset for object recognition in naturalistic scenes by Guohao Zhang, Ming Zhou, Shuyi Zhen, Shaohua Tang, Zheng Li, Zonglei Zhen

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Proteomics‐Empowered Microfluidic‐SERS Immunoassay for Identifying and Detecting Biomarkers of Micropapillary Lung Adenocarcinoma by Dechun Zhang, Kaiming Peng, Hui Xu, Yanping Chen, Jing Wang

“…Machine learning models based on SERS detection effectively distinguish MPP⁺ from MPP⁻ LUAD patients, as well as LUAD patients from healthy donors. …”
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Explainable artificial intelligence of DNA methylation-based brain tumor diagnostics by Salvatore Benfatto, Martin Sill, David T. W. Jones, Stefan M. Pfister, Felix Sahm, Andreas von Deimling, David Capper, Volker Hovestadt

“…Abstract We have recently developed a machine learning classifier that enables fast, accurate, and affordable classification of brain tumors based on genome-wide DNA methylation profiles that is widely employed in the clinic. …”
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Precise Crop Pest Detection Based on Co-Ordinate-Attention-Based Feature Pyramid Module by Chenrui Kang, Lin Jiao, Kang Liu, Zhigui Liu, Rujing Wang

“…Fast and precise pest detection and counting are crucial measures in the management and mitigation of pest infestations. In this area, deep learning technologies have come to represent the method with the most potential. …”
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HindwingLib: A library of leaf beetle hindwings generated by Stable Diffusion and ControlNet by Yi Yang, WenJie Li, RuiZe Liu, ChengZhe Wu, Jing Ren, YiShi Shi, SiQin Ge

“…Abstract The utilization of datasets from beetle hindwings is prevalent in research of morphology and evolution of beetles, serving as a valuable tool for comprehending the evolutionary processes and functional adaptations under specific environmental conditions. …”
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The Efficiency of Chitosan Against Tert Butylhydroquinone (TBHQ)-Induced Neurobehavioral Changes and Toxicity Effects in Male Rats by Shahad Alahmadi, Mohammed Mufadhe Alanazi, Fawaz Alasmari, Wedad Saeed Al-Qahtani, Gadah Albasher

“…Behavioral tests, including the Morris Water Maze (MWM) as well as Passive Avoidance Learning (PAL) tasks, confirmed memory and learning deficits in the TBHQ group. …”
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Rapid and accurate prediction of protein homo-oligomer symmetry using Seq2Symm by Meghana Kshirsagar, Artur Meller, Ian R. Humphreys, Samuel Sledzieski, Yixi Xu, Rahul Dodhia, Eric Horvitz, Bonnie Berger, Gregory R. Bowman, Juan Lavista Ferres, David Baker, Minkyung Baek

“…Abstract The majority of proteins must form higher-order assemblies to perform their biological functions, yet few machine learning models can accurately and rapidly predict the symmetry of assemblies involving multiple copies of the same protein chain. …”
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UPBD: Construction and Evaluation Methods of the Underwater Polarization Benchmark Dataset for Complex Scenarios by Haihong Jin, Shangle Yao, Hao Yao, Wenjie Zhang, Zhiguo Fan

“…Existing underwater polarization datasets are primarily designed for deep learning training and lack diverse data types and corresponding evaluation methods for comprehensive algorithm assessment. …”
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Simultaneous EEG-fNIRS Data Classification Through Selective Channel Representation and Spectrogram Imaging by Chayut Bunterngchit, Jiaxing Wang, Zeng-Guang Hou

“…The integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) can facilitate the advancement of brain-computer interfaces (BCIs). …”
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Prescriptive Maintenance: A Systematic Literature Review and Exploratory Meta-Synthesis by Marko Orošnjak, Felix Saretzky, Slawomir Kedziora

“…We identify key enablers—artificial intelligence and machine learning, horizontal and vertical integration, and deep reinforcement learning—that map the functional space of PsM across industrial sectors. …”
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Systematic Review and Clinical Outcomes of new Robotic Systems in Urology by Iulia Andras, Federico Piramide, Carlo Andrea Bravi, Fabrizio Di Maida, Filippo Turri, Edward Lambert, Mike Wenzel, Danny Darlington, Marco Paciotti, Giuseppe Basile, Christoph Wurnschimmel, Nikolaos Liakos, Gabriele Sorce, Ruben De Groote, Marcio Covas Moschovas, Paolo Dell’Oglio, Nicolae Crisan, Alexandre Mottrie, Alessandro Larcher

“…However, all of them showed acceptable perioperative and oncologic outcomes during the learning curve and good safety profile. Functional outcomes were underreported Conclusions: The adoption of novel multi-port and single-port robotic systems in urologic surgery can offer new opportunities for enhanced precision, reduced invasiveness, and potentially improved patient outcomes. …”
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Dance Training Shapes Action Perception and Its Neural Implementation within the Young and Older Adult Brain by Louise P. Kirsch, Nadine Diersch, Dilini K. Sumanapala, Emily S. Cross

“…Here, we investigate how learning a complex motor skill shapes neural and behavioural responses among a dance-naïve sample of 20 young and 19 older adults. …”
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The Analysis of English Language Teaching of the Students with Intellectual Disabilities: A Review on the Program, English Course Book for 7th Graders, and the Teacher’s Guide by Ahmad Ramezani, Payvand Mihandoust

“…The vital strong points were presenting frequent language functions and social routines, and color printing of the student book. …”
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Disentangling High-Paced Alternating I/O in Gaze-Based Interaction by Yulia G. Shevtsova, Artem S. Yashin, Sergei L. Shishkin, Anatoly N. Vasilyev

“…To our knowledge, this is the first study that demonstrates the effectiveness of machine learning applied to gaze features in enhancing gaze-based interaction within visually challenging environments.…”
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Application of Predictive Modeling and Molecular Simulations to Elucidate the Mechanisms Underlying the Antimicrobial Activity of Sage (<i>Salvia officinalis</i> L.) Components in... by Dajana Vukić, Biljana Lončar, Lato Pezo, Vladimir Vukić

“…These findings underscore the value of integrating molecular modeling and machine learning approaches for the identification of bioactive compounds in functional food systems.…”
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Integrative analysis of mitochondrial and immune pathways in diabetic kidney disease: identification of AASS and CASP3 as key predictors and therapeutic targets by Xinxin Yu, Yongzheng Hu, Wei Jiang

“…Experimental validation was performed using a DKD rat model.Results WGCNA revealed significant gene modules associated with immune responses and mitochondrial functions. Machine learning analysis highlighted two central biomarkers: aminoadipate-semialdehyde synthase (AASS) and caspase-3 (CASP3). …”
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Dorsomedial and ventromedial prefrontal cortex lesions differentially impact social influence and temporal discounting. by Zhilin Su, Mona M Garvert, Lei Zhang, Todd A Vogel, Jo Cutler, Masud Husain, Sanjay G Manohar, Patricia L Lockwood

“…Several debates question whether different ventral mPFC (vmPFC) and dorsal mPFC (dmPFC) regions have specific functions or whether there is a gradient supporting social and nonsocial cognition. …”
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Implementing of artificial intelligence in a higher educational ecosystem by Y. B. Melnyk, I. S. Pypenko

“…This model include structural (universities, faculties, departments, institutes, centres, doctoral schools, clinics, and labs) and functional (internal – content of education, forms and methods of teaching, diagnosing of learning outcomes, administering of educational service, and eternal – include academic achievement: levels of knowledge, skills, and competences) components. …”
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