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• Research PaperVolume 13, Issue 11pp 15320-15335

  Cistanche deserticola polysaccharides alleviate cognitive decline in aging model mice by restoring the gut microbiota-brain axis

  Relevance score: 0.00

  Yuan Gao, Bing Li, Hong Liu, Yajuan Tian, Chao Gu, Xiaoli Du, Ren Bu, Jie Gao, Yang Liu, Gang Li

  Keywords: learning and memory deterioration, CDPS, gut microbiota

  Published in Aging on June 3, 2021

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• Research PaperVolume 11, Issue 2pp 401-422

  3,4,5-Tricaffeoylquinic acid induces adult neurogenesis and improves deficit of learning and memory in aging model senescence-accelerated prone 8 mice

  Relevance score: 0.00

  Kazunori Sasaki, Julie Davies, Noelia Geribaldi Doldán, Sayo Arao, Farhana Ferdousi, Francis G. Szele, Hiroko Isoda

  Keywords: TCQA, SAMP8, spatial learning and memory, neurogenesis, BMP signaling

  Published in Aging on January 17, 2019

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• Research PaperVolume 13, Issue 5pp 7549-7569

  Preclinical systematic review of ginsenoside Rg1 for cognitive impairment in Alzheimer’s disease

  Relevance score: 0.00

  Hai-Yong Liang, Pei-Pei Zhang, Xi-Le Zhang, Yan-Yan Zheng, Yan-Ran Huang, Guo-Qing Zheng, Yan Lin

  Keywords: ginsenoside Rg1, Alzheimer's disease, learning and memory, preclinical evidence, potential mechanisms

  Published in Aging on March 3, 2021

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• Research PaperVolume 12, Issue 14pp 14205-14218

  Lowered levels of nicotinic acetylcholine receptors and elevated apoptosis in the hippocampus of brains from patients with type 2 diabetes mellitus and db/db mice

  Relevance score: 0.00

  Yi Xu, Kun Cao, Bing Guo, Jie Xiang, Yang-Ting Dong, Xiao-Lan Qi, Wen-Feng Yu, Yan Xiao, Zhi-Zhong Guan

  Keywords: type 2 diabetes mellitus, postmortem human brain, mice db/db, nicotinic acetylcholine receptors, learning and memory

  Published in Aging on July 23, 2020

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• Research PaperVolume 12, Issue 1pp 481-501

  A novel rhamnoside derivative PL402 up-regulates matrix metalloproteinase 3/9 to promote Aβ degradation and alleviates Alzheimer’s-like pathology

  Relevance score: 0.00

  Tingting Hu, Yue Zhou, Jing Lu, Peng Xia, Yue Chen, Xin Cao, Gang Pei

  Keywords: Alzheimer’s disease, Aβ degradation, matrix metalloproteinase 3/9, learning and memory deficits, natural products derivate

  Published in Aging on January 5, 2020

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• Research PaperVolume 15, Issue 4pp 932-946

  Isoform-specific effects of neuronal repression of the AMPK catalytic subunit on cognitive function in aged mice

  Relevance score: 0.00

  Xueyan Zhou, Wenzhong Yang, Xin Wang, Tao Ma

  Keywords: AMPK, aging, protein synthesis, learning and memory, proteomics

  Published in Aging on February 26, 2023

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• Research PaperVolume 14, Issue 8pp 3554-3568

  Claudin-5 relieves cognitive decline in Alzheimer’s disease mice through suppression of inhibitory GABAergic neurotransmission

  Relevance score: 0.00

  Ning Zhu, Meidan Wei, Linguang Yuan, Xiaodan He, Chunli Chen, Aimin Ji, Guozeng Zhang

  Keywords: Alzheimer’s disease, tight junction, claudin-5, learning and memory, GABAergic neurotransmission

  Published in Aging on April 26, 2022

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• Research PaperVolume 14, Issue 3pp 1280-1291

  Predicting neuropsychiatric symptoms of persons with dementia in a day care center using a facial expression recognition system

  Relevance score: 0.00

  Liang-Yu Chen, Tsung-Hsien Tsai, Andy Ho, Chun-Hsien Li, Li-Ju Ke, Li-Ning Peng, Ming-Hsien Lin, Fei-Yuan Hsiao, Liang-Kung Chen

  Keywords: artificial intelligence, behavioral and psychological symptoms of dementia, dementia, facial expression recognition system, machine learning

  Published in Aging on February 3, 2022

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• Research PaperVolume 12, Issue 14pp 14593-14619

  Radiomics-based prediction of survival in patients with head and neck squamous cell carcinoma based on pre- and post-treatment ¹⁸F-PET/CT

  Relevance score: 0.00

  Zheran Liu, Yuan Cao, Wei Diao, Yue Cheng, Zhiyun Jia, Xingchen Peng

  Keywords: F-PET/CT ¹⁸, head and neck squamous cell carcinoma, radiomics, prognosis, machine learning

  Published in Aging on July 16, 2020

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• EditorialVolume 15, Issue 19pp 9894-9895

  Learning by motor imagery in older adults

  Relevance score: 0.00

  Arnaud Saimpont, Angèle Métais, Christian Collet

  Keywords: motor imagery, motor sequence learning (MSL), tDCS, aging

  Published in Aging on October 13, 2023

• ReviewVolume 17, Issue 1pp 251-275

  Deep learning and generative artificial intelligence in aging research and healthy longevity medicine

  Relevance score: 0.00

  Dominika Wilczok

  Keywords: aging, generative artificial intelligence, deep learning, deep aging clocks, healthy longevity medicine

  Published in Aging on January 16, 2025

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• Research PaperVolume 16, Issue 7pp 6455-6477

  Machine learning for identifying tumor stemness genes and developing prognostic model in gastric cancer

  Relevance score: 0.00

  Guo-Xing Li, Yun-Peng Chen, You-Yang Hu, Wen-Jing Zhao, Yun-Yan Lu, Fu-Jian Wan, Zhi-Jun Wu, Xiang-Qian Wang, Qi-Ying Yu

  Keywords: gastric cancer, cancer stemness, machine learning, ssGSEA

  Published in Aging on April 12, 2024

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• Research PaperVolume 16, Issue 7pp 6314-6333

  Machine learning identifies novel coagulation genes as diagnostic and immunological biomarkers in ischemic stroke

  Relevance score: 0.00

  Jinzhi Liu, Zhihua Si, Ju Liu, Xu Zhang, Cong Xie, Wei Zhao, Aihua Wang, Zhangyong Xia

  Keywords: ischemic stroke, coagulation genes, immune infiltration analysis, machine learning, diagnosis

  Published in Aging on April 3, 2024

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• Research PaperVolume 16, Issue 5pp 4563-4578

  Machine learning-based endoplasmic reticulum-related diagnostic biomarker and immune microenvironment landscape for osteoarthritis

  Relevance score: 0.00

  Tingting Liu, Xiaomao Li, Mu Pang, Lifen Wang, Ye Li, Xizhe Sun

  Keywords: osteoarthritis, endoplasmic reticulum, diagnostic biomarker, immune microenvironment, machine learning

  Published in Aging on February 28, 2024

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• Research PaperVolume 16, Issue 4pp 3856-3879

  An assessment system for clinical and biological interpretability in ulcerative colitis

  Relevance score: 0.00

  Shiqian Zhang, Ge Zhang, Wenxiu Wang, Song-Bin Guo, Pengpeng Zhang, Fuqi Wang, Quanbo Zhou, Zhaokai Zhou, Yujia Wang, Haifeng Sun, Wenming Cui, Shuaixi Yang, Weitang Yuan

  Keywords: machine learning, diagnosis model, regulatory landscape, computational biology, biological interpretability

  Published in Aging on February 16, 2024

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• Research PaperVolume 16, Issue 3pp 2774-2788

  Machine learning-based B cell-related diagnostic biomarker signature and molecular subtypes characteristic of ulcerative colitis

  Relevance score: 0.00

  Guo-Liang Wu, Li Li, Xiao-Yao Chen, Wei-Feng Zhang, Jun-Bo Wu, Xiaoning Yu, Hong-Jin Chen

  Keywords: ulcerative colitis, B cell-related genes, diagnostic biomarker, immune infiltration, machine learning

  Published in Aging on February 5, 2024

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• Research PaperVolume 15, Issue 20pp 11162-11183

  Machine learning developed a PI3K/Akt pathway-related signature for predicting prognosis and drug sensitivity in ovarian cancer

  Relevance score: 0.00

  Xiaofang Han, Liu Yang, Hui Tian, Yuanyuan Ji

  Keywords: immunotherapy, prognostic signature, ovarian cancer, machine learning, PI3K/Akt pathway

  Published in Aging on October 17, 2023

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• Research PaperVolume 15, Issue 14pp 6848-6864

  The integration of machine learning and multi-omics analysis provides a powerful approach to screen aging-related genes and predict prognosis and immunotherapy efficacy in hepatocellular carcinoma

  Relevance score: 0.00

  Jiahui Shen, Han Gao, Bowen Li, Yan Huang, Yinfang Shi

  Keywords: machine learning, aging, hepatocellular carcinoma, prognostic model, immunotherapy

  Published in Aging on July 28, 2023

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• Research PaperVolume 15, Issue 13pp 6152-6162

  Machine learning models predict the mTOR signal pathway-related signature in the gastric cancer involving 2063 samples of 7 centers

  Relevance score: 0.00

  Hao Zhang, Huiqin Zhuo, Jingjing Hou, Jianchun Cai

  Keywords: mTOR, machine learning, cellular senescence, ming classification

  Published in Aging on June 20, 2023

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• Research PaperVolume 15, Issue 11pp 5007-5031

  Machine learning and single cell RNA sequencing analysis identifies regeneration-related hepatocytes and highlights a Birc5-related model for identifying cell proliferative ability

  Relevance score: 0.00

  Yuan Du, Shuqin Jian, Xicheng Wang, Chao Yang, Hua Qiu, Kang Fang, Yehong Yan, Jun Shi, Jianfeng Li

  Keywords: liver regeneration, Hmgb1, Birc5, hdWGCNA, machine learning

  Published in Aging on June 14, 2023

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