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Experimental modeling of Alzheimer's disease: Translational lessons from cross-taxon analyses

Alzheimer's and Dementia 2025年第5期21卷 e70273页

作者： Yenkoyan, Konstantin B. Kotova, Maria M. Apukhtin, Kirill V. Galstyan, David S. Amstislavskaya, Tamara G. Strekalova, Tatyana de Abreu, Murilo S. Chavushyan, Vergine A. Lim, Lee Wei Yang, Longen Rosemberg, Denis D. Kalueff, Allan V. Neuroscience Laboratory COBRAIN Center Yerevan State Medical University after M. Heratsi Yerevan Armenia Neuroscience Program Sirius University of Science and Technology Sochi Russian Federation Institute of Translational Biomedicine St. Petersburg State University St. Petersburg Russian Federation Institute of Experimental Medicine Almazov National Medical Research Centre Ministry of Healthcare of Russian Federation St. Petersburg Russian Federation Scientific Research Institute of Neurosciences and Medicine Novosibirsk Russian Federation Research Institute of General Pathology and Pathophysiology Moscow Russian Federation Graduate Program in Health Sciences Federal University of Health Sciences of Porto Alegre Porto Alegre Brazil Department of Biosciences and Bioinformatics School of Science Xi'an Jiaotong-Liverpool University Suzhou China Suzhou Municipal Key Laboratory of Neurobiology and Cell Signaling School of Science Xi'an Jiaotong-Liverpool University Suzhou China Laboratory of Experimental Neuropsychobiology Department of Biochemistry and Molecular Biology Natural and Exact Sciences Center Federal University of Santa Maria Santa Maria Brazil Graduate Program in Biological Sciences: Toxicological Biochemistry Federal University of Santa Maria Santa Maria Brazil The International Zebrafish Neuroscience Research Consortium (ZNRC) Slidell LA United States

Alzheimer's disease (AD) is a severely debilitating neurodegenerative disease with a rapidly increasing global prevalence, poorly understood causes, and no efficient treatments. Experimental models are valuable for studying AD pathogenesis, including amyloid beta and tau accumulation, synaptic dysfunction, and neuroinflammation. While no model fully reproduces the disease, we take an evolutionary biology approach to discuss available models across taxa, from mammals (rodents, primates) to zebrafish, Drosophila melanogaster, and Caenorhabditis elegans. Evaluating their strengths and limitations provides insight into disease mechanisms and may refine research strategies for improved diagnostics and therapeutic screening. Traditional models have significantly contributed to AD research, yet their translational limitations highlight the need for physiologically relevant alternatives. Integrating humanized rodent models, zebrafish, organoids, and induced pluripotent stem cell–based systems—along with advances in bioengineering and genetic editing—may offer a more comprehensive framework to bridge the gap between preclinical research and clinical application. Highlights: Experimental models across rodents, primates, zebrafish, fruit flies, and worms provide key insights into Alzheimer's disease (AD). Cross-taxon comparisons assess strengths and weaknesses in AD models. Evolutionary biology approaches refine experimental strategies for AD research. Diverse animal models improve understanding of AD pathogenesis. Cross-species models enhance diagnostics and therapeutic strategy development. © 2025 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.

关键词： Alzheimer's disease animal models cross-taxon analyses evolutionary psychiatry translation medicine

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Functional neuroplasticity of facilitation and interference effects on inhibitory control following 3-month physical exercise in aging

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Scientific Reports 2024年第1期14卷 1-13页

作者： Wu, Hong-Yi Huang, Chih-Mao Hsu, Ai-Ling Chen, Chiao-Nan Wu, Changwei W. Chen, Jyh-Horng Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan Bachelor Program in Artificial Intelligence Chang Gung University Taoyuan Taiwan Department of Psychiatry Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan Department of Physical Therapy and Assistive Technology National Yang Ming Chiao Tung University Taipei Taiwan Graduate Institute of Mind Brain and Consciousness Taipei Medical University New Taipei Taiwan Research Center of Sleep Medicine Taipei Medical University Hospital Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan

Preservation of executive function, like inhibition, closely links to the quality of life in senior adults. Although neuroimaging literature has shown enhanced inhibitory function followed by aerobic exercise, current evidence implies inconsistent neuroplasticity patterns along different time durations of exercise. Hence, we conducted a 12-week exercise intervention on 12 young and 14 senior volunteers and repeatedly measured the inhibitory functionality of distinct aspects (facilitation and interference effects) using the numerical Stroop task and functional Magnetic Resonance Imaging. Results showcased improved accuracy and reduced reaction times (RT) after 12-week exercise, attributed to frontoparietal and default mode network effects. In young adults, the first phase (0 to six weeks) exercise increased the activation of the right superior medial frontal gyrus, associated with reduced RT in interference, but in the second intervention phase (six to twelve weeks), the decreased activation of the left superior medial frontal gyrus positively correlated with reduced RT in facilitation. In senior adults, the first six-week intervention led to reduced activations of the inferior frontal gyrus, inferior parietal gyrus, and default mode network regions, associated with the reduced RT in interference. Still, in the second intervention phase, only the visual area exhibited increased activity, associated with reduced RT in interference. Except for the distinctive brain plasticity between the two phases of exercise intervention, the between-group comparison also presented that the old group gained more cognitive benefits within the first six weeks of exercise intervention;however, the cognitive improvements in the young group occurred after six weeks of intervention. Limited by the sample size, these preliminary findings corroborated the benefits of aerobic exercise on the inhibitory functions, implying an age × exercise interaction on the brain plasticity for both facilita

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Network insights into childhood obesity: unveiling methylated-differentially expressed genes and pathways through integrative bioinformatics analysis

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Endocrine connections 2025年第6期14卷 EC-25页

作者： Felipe Mateus Pellenz Guilherme Coutinho Kullmann Duarte Giovanna Câmara Giudicelli Thayne Woycinck Kowalski Tais Silveira Assmann Daisy Crispim F Pellenz Faculty of Medicine Department of Internal Medicine Graduate Program in Medical Sciences: Endocrinology Universidade Federal do Rio Grande do Sul Porto Alegre Brazil. G Duarte Faculty of Medicine Department of Internal Medicine Graduate Program in Medical Sciences: Endocrinology Universidade Federal do Rio Grande do Sul Porto Alegre Brazil. G Giudicelli Bioinformatics Core Hospital de Clínicas de Porto Alegre Porto Alegre Brazil. T Kowalski Bioinformatics Core Hospital de Clínicas de Porto Alegre Porto Alegre Brazil. T Assmann Faculty of Medicine Department of Internal Medicine Graduate Program in Medical Sciences: Endocrinology Universidade Federal do Rio Grande do Sul Porto Alegre Brazil. D Crispim Endocrine Division Hospital de Clínicas de Porto Alegre Porto Alegre Brazil.

BACKGROUND:Childhood obesity, a global epidemic with profound impacts on physical and psychological health, remains a complex challenge with elusive underlying mechanisms. This study aimed to unravel the epigenetic landscape of this disease by identifying methylated-differentially expressed genes (MeDEGs) in childhood obesity through integrated bioinformatics approaches. METHODS:Expression profiling (GSE9624) and methylation profiling (GSE25301, GSE27860, and GSE57484) datasets containing data on children with obesity (cases) and eutrophic children (control group) were obtained from the Gene Expression Omnibus (GEO) repository. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) between the groups were identified using GEO2R. MeDEGs were identified by superimposing the lists of DEGs and DMGs. The protein-protein interaction (PPI) network was constructed using the STRING database and analyzed using Cytoscape. Topological and modular PPI network analyses were carried out using the CytoHubba and MCODE plugins, respectively. Functional enrichment analyses were performed based on Gene Ontology terms and KEGG pathways. RESULTS:A total of 70 MeDEGs were identified, including 45 hypomethylated-high expression and 25 hypermethylated-low expression genes. The PPI network highlighted three hub-bottleneck genes (CCL5, STAT1, and GATA3) and two functional modules. Overall, the 70 MeDEGs were associated with KEGG pathways related to cellular differentiation, inflammation, chemokine signaling, lipid and glucose metabolism, insulin resistance, and apoptosis. CONCLUSION:This study, employing integrative bioinformatics approaches, provides insights into the methylation-mediated mechanisms contributing to childhood obesity, advancing our understanding of this multifaceted chronic disease.

关键词： childhood obesity differentially methylated genes methylation-regulated differentially expressed genes (MeDEGs) bioinformatics systems biology

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Deep Hierarchical Embedding for Simultaneous Modeling of GPCR Proteins in a Unified Metric Space

Research Square

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Research Square 2021年

作者： Lee, Taeheon Lee, Sangseon Kang, Minji Kim, Sun Looxid Labs Seoul06099 Korea Republic of BK21 FOUR Intelligence Computing Seoul National University Seoul08826 Korea Republic of Department of Computer Science Stanford University StanfordCA94305 United States Bioinformatics Institute Seoul National University Seoul08826 Korea Republic of Department of Computer Science and Engineering Seoul National University Seoul08826 Korea Republic of Interdisciplinary Program in Bioinformatics Seoul National University Seoul08826 Korea Republic of Department of Computer Science and Engineering Institute of Engineering Research Seoul National University Seoul08826 Korea Republic of

GPCR proteins belong to diverse families of proteins that are defined at multiple hierarchical levels. Inspecting relationships between GPCR proteins on the hierarchical structure is important, since characteristics of the protein can be inferred from proteins in similar hierarchical information. However, modeling of GPCR families has been performed separately at each level. Relationships between GPCR proteins are ignored in these approaches as they process the information in the proteins with several disconnected models. In this study, we propose a deep learning model to simultaneously learn representations of GPCR family hierarchy from the protein sequences with a unified single model. Novel loss term based on metric learning is introduced to incorporate hierarchical relations between proteins. We tested our approach using a public GPCR sequence dataset. Metric distances in the deep feature space corresponded to the hierarchical family relation between GPCR proteins. Furthermore, we demonstrated that further downstream tasks, like phylogenetic reconstruction and motif discovery, are feasible in the constructed embedding space. These results show that hierarchical relations between sequences were successfully captured in both of technical and biological aspects. © 2021, CC BY.

关键词： Proteins

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Microglial SIRT2 deficiency aggravates cognitive decline and amyloid pathology in Alzheimer's disease

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Brain, behavior, and immunity 2025年 129卷 223-243页

作者： Noemi Sola-Sevilla Maider Garmendia-Berges Mikel Aleixo MCarmen Mera-Delgado Maite Solas Rosa M Tordera Lucía García-Carracedo Sara Expósito Elena Anaya-Cubero Joaquín Fernández-Irigoyen Elisabeth Guruceaga Enrique Santamaria Eduardo D Martin Elena Puerta Department of Pharmaceutical Sciences Division of Pharmacology University of Navarra 31008 Pamplona Spain IdISNA Navarra Institute for Health Research 31008 Pamplona Spain Department of Neurology Research Center for Immunotherapy (FZI) and Focus Program Translational Neuroscience (FTN) Rhine Main Neuroscience Network (rmn2) University Medical Centre of the Johannes Gutenberg University Mainz 55131 Mainz Germany. IdISNA Navarra Institute for Health Research 31008 Pamplona Spain. Laboratory of Neurophysiology and Synaptic Plasticity Instituto Cajal Consejo Superior de Investigaciones Científicas Madrid Spain. Clinical Neuroproteomics Unit Navarrabiomed Hospital Universitario de Navarra (HUN) Universidad Pública de Navarra (UPNA) IdiSNA 31008 Pamplona Spain. Bioinformatics Platform CIMA University of Navarra Pamplona Spain. IdISNA Navarra Institute for Health Research 31008 Pamplona Spain. Electronic address: epuerta@unav.es.

Sirtuin 2 (SIRT2), a NAD+-dependent deacetylase, has been implicated in aging and neurodegenerative diseases such as Alzheimer's disease (AD). While global SIRT2 inhibition has shown promise in reducing amyloid-beta pathology and cognitive deficits in different mouse models of AD, peripheral SIRT2 inhibition has been associated with adverse effects, such as increased inflammation. This suggests that targeted inhibition of specific cellular populations within the brain may represent a more precise and effective approach for the treatment of AD. To explore this hypothesis, we generated a conditional microglial SIRT2 knockout mouse model in the context of AD. Our results reveal that microglial SIRT2 reduction does not confer protective effects in the APP/PS1 model; rather, it aggravates cognitive decline, accelerates amyloid plaque deposition, and increases levels of pro-inflammatory cytokines at early stages of AD pathology. Transcriptomic analysis further indicates that SIRT2-deficient microglia exhibit altered expression of genes associated with aging and synaptic dysfunction. This phenotype was accompanied by increased phagocytosis of PSD95 and impaired long-term potentiation. These findings suggest that while SIRT2 inhibition in some contexts may be beneficial, targeted inhibition within microglia could accelerate AD progression, underscoring the need for cell-specific approaches when considering SIRT2 as a therapeutic target.

关键词： Aging Alzheimer’s disease Microglia Neurodegenerative diseases Neuroinflammation Sirtuin 2

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Data Mining for Predicting Customer Satisfaction Using Clustering Techniques

Data Mining for Predicting Customer Satisfaction Using Clust...

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International Conference on Information Management and Technology (ICIMTech)

作者： Kartika Purwandari Join W. C. Sigalingging Muhammad Fhadli Shinta Nur Arizky Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia National Central University Taoyuan Taiwan BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

Managing customer satisfaction has become an important business trend, including restaurants business. This study aims to determine the application of the K-means, Spectral Clustering (SC), and Agglomerative Clustering (AC) method for measuring customer satisfaction on a family restaurant in Taiwan. We contribute the data collection process and application of data mining in a family restaurant. The clustering analysis based on agglomerative clustering approach performs as well as the K-means approach to cluster the same characteristics of the customers. At last, this study shows the measurement result of customer satisfaction and provides improvement suggestion to the restaurant concerned.

关键词： Data mining Customer satisfaction Principal component analysis Computer science Reliability Data visualization

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Cyclic alternation of quiet and active sleep states in the octopus

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iScience 2021年第4期24卷 102223页

作者： Medeiros, Sylvia Lima de Souza Paiva, Mizziara Marlen Matias de Lopes, Paulo Henrique Blanco, Wilfredo Lima, Françoise Dantas de Oliveira, Jaime Bruno Cirne de Medeiros, Inácio Gomes Sequerra, Eduardo Bouth de Souza, Sandro Leite, Tatiana Silva Ribeiro, Sidarta Brain Institute Federal University of Rio Grande do Norte Natal Rio Grande do Norte Brazil Graduate Program in Psychobiology Federal University of Rio Grande do Norte Natal Rio Grande do Norte Brazil Graduate Program in Neuroscience Federal University of Rio Grande do Norte Natal Rio Grande do Norte Brazil Computer Science Department State University of Rio Grande do Norte Natal Rio Grande do Norte Brazil Bioinformatics Multidisciplinary Environment Federal University of Rio Grande do Norte Natal Rio Grande do Norte Brazil Department of Ecology and Zoology Federal University of Santa Catarina Florianópolis Santa Catarina Brazil Graduate Program in Bioinformatics Federal University of Rio Grande do Norte Natal Rio Grande do Norte Brazil

Previous observations suggest the existence of ‘Active sleep’ in cephalopods. To investigate in detail the behavioral structure of cephalopod sleep, we video-recorded four adult specimens of Octopus insularis and quantified their distinct states and transitions. Changes in skin color and texture and movements of eyes and mantle were assessed using automated image processing tools, and arousal threshold was measured using sensory stimulation. Two distinct states unresponsive to stimulation occurred in tandem. The first was a ‘Quiet sleep’ state with uniformly pale skin, closed pupils, and long episode durations (median 415.2 s). The second was an ‘Active sleep’ state with dynamic skin patterns of color and texture, rapid eye movements, and short episode durations (median 40.8 s). ‘Active sleep’ was periodic (60% of recurrences between 26 and 39 min) and occurred mostly after ‘Quiet sleep’ (82% of transitions). These results suggest that cephalopods have an ultradian sleep cycle analogous to that of amniotes. © 2021 The Authors

关键词： Biological Sciences Ethology Zoology

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THE TEMPORAL STRUCTURE OF LANGUAGE PROCESSING IN THE HUMAN BRAIN CORRESPONDS TO THE LAYERED HIERARCHY OF DEEP LANGUAGE MODELS

arXiv

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arXiv 2023年

作者： Goldstein, Ariel Ham, Eric Schain, Mariano Nastase, Samuel A. Zada, Zaid Grinstein-Dabus, Avigail Aubrey, Bobbi Gazula, Harshvardhan Feder, Amir Doyle, Werner Devore, Sasha Dugan, Patricia Friedman, Daniel Reichart, Roi Brenner, Michael Hassidim, Avinatan Devinsky, Orrin Flinker, Adeen Levy, Omer Hasson, Uri Department of Psychology The Neuroscience Institute Princeton University PrincetonNJ United States Google Research United States New York University Grossman School of Medicine New YorkNY United States School of Engineering and Applied Science Harvard University CambridgeMA United States New York University Tandon School of Engineering BrooklynNY United States Blavatnik School of Computer Science Tel-Aviv University Israel Department of Cognitive and Brain Sciences Business School Hebrew University of Jerusalem Israel Bioinformatics Interdepartmental Program University of California Los Angeles Los AngelesCA United States Technion - Israel Institute of Technology Haifa Israel

Deep Language Models (DLMs) provide a novel computational paradigm for understanding the mechanisms of natural language processing in the human brain. Unlike traditional psycholinguistic models, DLMs use layered sequences of continuous numerical vectors to represent words and context, allowing a plethora of emerging applications such as human-like text generation. In this paper we show evidence that the layered hierarchy of DLMs may be used to model the temporal dynamics of language comprehension in the brain by demonstrating a strong correlation between DLM layer depth and the time at which layers are most predictive of the human brain. Our ability to temporally resolve individual layers benefits from our use of electrocorticography (ECoG) data, which has a much higher temporal resolution than noninvasive methods like fMRI. Using ECoG, we record neural activity from participants listening to a 30-minute narrative while also feeding the same narrative to a high-performing DLM (GPT2-XL). We then extract contextual embeddings from the different layers of the DLM and use linear encoding models to predict neural activity. We first focus on the Inferior Frontal Gyrus (IFG, or Broca’s area) and then extend our model to track the increasing temporal receptive window along the linguistic processing hierarchy from auditory to syntactic and semantic areas. Our results reveal a connection between human language processing and DLMs, with the DLM’s layer-by-layer accumulation of contextual information mirroring the timing of neural activity in high-order language areas. © 2023, CC BY-NC-ND.

关键词： Brain

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Caco-2 Cell-Derived Biomimetic Electrochemical Biosensor for Cholera Toxin Detection

SSRN

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SSRN 2022年

作者： Kim, Yonghwan Lee, Dongtak Seo, Youngjun Jung, Hyo Gi Jang, Jae Won Park, Dongsung Kim, Insu Lee, Gyudo Hwang, Kyo Seon Kim, Seung-Hyun Lee, Sang Won Lee, Jeong Hoon Yoon, Dae Sung School of Biomedical Engineering Korea University Seoul02841 Korea Republic of Interdisciplinary Program in Precision Public Health Korea University Seoul02841 Korea Republic of Department of Clinical Pharmacology and Therapeutics College of Medicine Kyung Hee University Seoul02447 Korea Republic of Department of Biotechnology and Bioinformatics Korea University Sejong30019 Korea Republic of Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Korea University Sejong30019 Korea Republic of School of Engineering Brown University ProvidenceRI02912 United States Department of Electrical Engineering and Computer Science University of California IrvineCA92697 United States Department of Electrical Engineering Kwangwoon University Seoul01897 Korea Republic of Astrion Inc Seoul02841 Korea Republic of

Cholera is a highly contagious and lethal waterborne disease induced by an infection with Vibrio cholerae (V. cholerae) secreting cholera toxin (CTx). Cholera toxin subunit B (CTxB) from the CTx specifically binds with monosialo-tetra-hexosyl-ganglioside (GM1) found on the exterior cell membrane of an enterocyte. Owing to the pathological process of CTx, a biomimetic electrochemical biosensor (CCB) was developed by applying GM1-expressing Caco-2 cell membrane (CCM) on the electrode surface of the biosensor for CTx detection. Briefly, the electrode surface was functionalized with CCM using the vesicle fusion method. The specific binding between GM1 and CTxB on the electrode surface was verified using confocal laser scanning microscopy and atomic force microscopy. The CTxB detection performances of the CCB, including sensitivity, selectivity, and long-term stability, were determined using electrochemical impedance spectroscopy (EIS). Based on the results, the CCB had an excellent limit of detection of ~11.46 nM and a detection range spanning 100 ng/mL - 1 mg/mL. Further, the CCB had high selectivity for the CTxB compared to different interfering molecules, which are abundant constituents of intestinal fluid and fecal matter in the human body. The long-term stability of the CCBs was also verified for 3 weeks using EIS. Overall, the CCB was found to have an excellent potential for application to point-of-care and cost-effective testing for CTxB detection in developing countries. © 2022, The Authors. All rights reserved.

关键词： Electrochemical impedance spectroscopy

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54 Real-World Evaluation of Healthcare Utilization in Patients with a Positive Molecular Diagnosis for Inborn Errors of Immunity

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Clinical Immunology 2024年 262卷 109996-109996页

作者： Rider, Nicholas Platt, Craig Ting, Yi-Lee Khayat, Michael Moretz, Chad Facio, Flavia Abraham, Roshini Johnson, Britt Professor/Virginia Tech Carilion School of Medicine Attending Physician Division of Immunology/Boston Children’s Hospital Clinical Program Manager/Invitae Corporation Clinical Bioinformatics Analyst/Invitae Corporation HEOR Lead/Invitae Corporation Professor Clinical Pathology and Director Diagnostic Immunology Laboratory/Nationwide Children’s Hospital Senior Medical Affairs Director/Invitae Corporation

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