41 research outputs found
Advances in microfluidic in vitro systems for neurological disease modeling
Neurological disorders are the leading cause of disability and the second largest cause of death worldwide. Despite significant research efforts, neurology remains one of the most failureâprone areas of drug development. The complexity of the human brain, boundaries to examining the brain directly in vivo, and the significant evolutionary gap between animal models and humans, all serve to hamper translational success. Recent advances in microfluidic in vitro models have provided new opportunities to study human cells with enhanced physiological relevance. The ability to precisely microâengineer cellâscale architecture, tailoring form and function, has allowed for detailed dissection of cell biology using microphysiological systems (MPS) of varying complexities from single cell systems to âOrganâonâchipâ models. Simplified neuronal networks have allowed for unique insights into neuronal transport and neurogenesis, while more complex 3D heterotypic cellular models such as neurovascular unit mimetics and âOrganâonâchipâ systems have enabled new understanding of metabolic coupling and bloodâbrain barrier transport. These systems are now being developed beyond MPS toward disease specific microâpathophysiological systems, moving from âOrganâonâchipâ to âDiseaseâonâchip.â This review gives an outline of current state of the art in microfluidic technologies for neurological disease research, discussing the challenges and limitations while highlighting the benefits and potential of integrating technologies. We provide examples of where such toolsets have enabled novel insights and how these technologies may empower future investigation into neurological diseases
Artificial intelligence for neurodegenerative experimental models
INTRODUCTION: Experimental models are essential tools in neurodegenerative disease research. However, the translation of insights and drugs discovered in model systems has proven immensely challenging, marred by high failure rates in human clinical trials. METHODS: Here we review the application of artificial intelligence (AI) and machine learning (ML) in experimental medicine for dementia research. RESULTS: Considering the specific challenges of reproducibility and translation between other species or model systems and human biology in preclinical dementia research, we highlight best practices and resources that can be leveraged to quantify and evaluate translatability. We then evaluate how AI and ML approaches could be applied to enhance both cross-model reproducibility and translation to human biology, while sustaining biological interpretability. DISCUSSION: AI and ML approaches in experimental medicine remain in their infancy. However, they have great potential to strengthen preclinical research and translation if based upon adequate, robust, and reproducible experimental data. Highlights: There are increasing applications of AI in experimental medicine. We identified issues in reproducibility, cross-species translation, and data curation in the field. Our review highlights data resources and AI approaches as solutions. Multi-omics analysis with AI offers exciting future possibilities in drug discovery.</p
Artificial intelligence for neurodegenerative experimental models
INTRODUCTION: Experimental models are essential tools in neurodegenerative disease research. However, the translation of insights and drugs discovered in model systems has proven immensely challenging, marred by high failure rates in human clinical trials. METHODS: Here we review the application of artificial intelligence (AI) and machine learning (ML) in experimental medicine for dementia research. RESULTS: Considering the specific challenges of reproducibility and translation between other species or model systems and human biology in preclinical dementia research, we highlight best practices and resources that can be leveraged to quantify and evaluate translatability. We then evaluate how AI and ML approaches could be applied to enhance both cross-model reproducibility and translation to human biology, while sustaining biological interpretability. DISCUSSION: AI and ML approaches in experimental medicine remain in their infancy. However, they have great potential to strengthen preclinical research and translation if based upon adequate, robust, and reproducible experimental data. HIGHLIGHTS: There are increasing applications of AI in experimental medicine. We identified issues in reproducibility, cross-species translation, and data curation in the field. Our review highlights data resources and AI approaches as solutions. Multi-omics analysis with AI offers exciting future possibilities in drug discovery
Apoptose neuronale et ceramide: signalisation intracellulaire. Apoptose neuronale et second messager ceramide: etude des voies de signalisation intracellulaires
La mort de neurones par apoptose est un phĂ©nomĂšne intervenant au cours du dĂ©veloppement du systĂšme nerveux, ainsi que dans de nombreuses pathologies neurodĂ©gĂ©nĂ©ratives. La dĂ©termination des mĂ©canismes dâactivation du processus apoptotique est intĂ©ressante dâun point de vue de lâanalyse du dĂ©veloppement dâun systĂšme nerveux fonctionnel, mais Ă©galement dâun point de vue thĂ©rapeutique, dans le cas des maladies neurodĂ©gĂ©nĂ©ratives comme la maladie dâAlzheimer ou de Parkinson. La transmission dâun signal apoptotique de la membrane cellulaire au noyau, pour dĂ©clencher le programme dâapoptose neuronale impliquant notamment une activation de gĂšnes, implique des seconds messagers et des voies de signalisation intracellulaires.Le cĂ©ramide, second messager lipidique, intervient dans diffĂ©rents processus cellulaires comme la survie, la diffĂ©renciation et lâapoptose. Il intervient Ă©galement dans la mise en place du programme dâapoptose neuronale, qui a lieu au cours du dĂ©veloppement ou dans des pathologies neurodĂ©gĂ©nĂ©ratives. Le cĂ©ramide pourrait ainsi ĂȘtre un point de choix entre diffĂ©rentes adaptations cellulaires Ă des stimuli cellulaires, mais Ă©galement point de convergence pour plusieurs stimuli apoptotiques avant de dĂ©clencher un mĂ©canisme commun dâapoptose neuronale.Le but de notre travail est dâĂ©tudier les voies de transduction au cours de lâapoptose neuronale induite par le cĂ©ramide. Nous avons ainsi Ă©tudiĂ© la modulation des voies de signalisation lors de lâapoptose de neurones corticaux en culture primaire, induite par le cĂ©ramide. Dans les neurones corticaux, la voie des MAP kinases ERK est inhibĂ©e par le cĂ©ramide alors que les voies JNK et p38 sont activĂ©es. Lâactivation des voies JNK et p38 est nĂ©cessaire Ă lâexĂ©cution du programme apoptotique enclenchĂ© par le cĂ©ramide, alors que lâinhibition de la voie ERK ne semble pas jouer de rĂŽle dans lâapoptose induite par le cĂ©ramide. Lors de cette apoptose, lâexpression de gĂšnes Ă rĂ©ponse prĂ©coce comme c jun et c fos, ainsi que celle du gĂšne p53, est augmentĂ©e. Ces facteurs de transcription peuvent ensuite rĂ©guler dâautres gĂšnes impliquĂ©s dans lâexĂ©cution du programme apoptotique. Nous nous sommes Ă©galement intĂ©ressĂ©s aux voies de transduction impliquĂ©es dans lâinhibition de lâapoptose. La surexpression de Bcl 2, protĂ©ine mitochondriale anti apoptotique, protĂšge les neurones corticaux de lâapoptose induite par le cĂ©ramide. Sa rĂ©gulation gĂ©nique peut ĂȘtre contrĂŽlĂ©e par lâInsulin like Growth Factor I (IGF-I) par la voie IGF I/PI 3K/Akt/CREB/bcl 2. De mĂȘme, lâIGF I, facteur de survie et facteur mitogĂ©nique, protĂšge les neurones corticaux. La protection par lâIGF I implique la voie de signalisation PI 3K/Akt, alors que la kinase Akt est inhibĂ©e lors du traitement au cĂ©ramide. Lâensemble de ces rĂ©sultats montre que lâapoptose induite par le cĂ©ramide implique un dĂ©sĂ©quilibre en faveur des voies de signalisation pro apoptotiques (JNK, p38) par rapport aux voies anti apoptotiques (ERK, Akt) et que ce dĂ©sĂ©quilibre est modifiĂ© lors de la protection par lâIGF I. <br/
Maternal protein restriction around conception increases foetal neuronal differentiation and is associated with adult memory deficits
Maternal malnutrition during pregnancy is detrimental to foetal development and increases the risk of many chronic diseases in later life i.e. increased risk of schizophrenia. Previous studies have shown maternal protein malnutrition during pregnancy and lactation compromises brain development in late gestation and after birth, affecting structural, biochemical and pathway dynamics with lasting consequences for motor and cognitive function. However, the importance of nutrition during embryogenesis for early brain development is unknown. We have previously shown maternal low protein diet confined to the preimplantation period (Emb-LPD) in mice is sufficient to induce cardiometabolic and behavioural abnormalities in adult offspring. Using the same diet model, female mice were fed different diets from conception to the end of pregnancy: normal protein diet (NPD), low protein diet (LPD) or embryonic LPD (Emb-LPD: LPD for 3.5 days, NPD thereafter). Foetal brains were analysed during gestation with in vivo analysis using FACS and immunofluorescence for neurogenesis markers, and in vitro techniques using the neurosphere assay. Follow up behavioural tests in the offspring were performed, including the short-term memory novel object recognition. We have shown that Emb-LPD and sustained LPD reduce neural stem and progenitor cell numbers through decreased proliferation in both ganglionic eminences and cortex of the foetal brain at E12.5, E14.5 & E17.5 (p=0.001). Moreover, Emb-LPD causes remaining neural stem cells to upregulate the neuronal differentiation rate in compensation beyond control levels during gestation, independently of sex (p<0.001). When analysing the adult offspring behaviour, the Emb-LPD males and females show a clear deficit in short-term memory (p=0.00001). Our data are the first to demonstrateclearly that poor maternal nutrition around conception has adverse effects on early brain development and is associated with adult memory deficits
Apoptose neuronale et second messager céramide (étude des voies de signalisation intracellulaires)
PARIS-BIUSJ-ThĂšses (751052125) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF
Dataset for the Southampton Doctoral Thesis "A 3D- Induced Pluripotent Stem Cell-Derived Human Neural Culture Model to Study Certain Molecular and Biochemical Aspects of Alzheimer’s Disease."
This dataset contains all the experimental data used to generate the figures included in Chapter 2- Human Neural 3D culture - Optimization and
Validation of 3D Culture method, of the Thesis</span
Dataset in support of the thesis 'The Effect of High-Fat Diet During Mouse Preimplantation and Pregnancy-Lactation on Uterine Fluid Protein Composition, Maternal Metabolism and Offspring Health''
Dataset and omic data from Thesis entitled: The Effect of High-Fat Diet During Mouse Preimplantation and Pregnancy-Lactation on Uterine Fluid Protein Composition, Maternal Metabolism and Offspring Health. Author: Irene Peral-Sanchez
The added dataset included raw data generated from the period from Oct 2019 to December 2023.
As explained in the thesis, the data were analyzed using SPSS syntax (hierarchical model) and Prism. The omics data (RNA seq and Proteomics) were additionally studied by String and Gene Ontology, apart from R (collaborators).
If any other questions or clarification is needed, contact the author or main supervisor. </span