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DTSTART:20260329T010000
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DTSTART:20261025T010000
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DTSTART;VALUE=DATE:20260618
DTEND;VALUE=DATE:20260620
DTSTAMP:20260618T071522
CREATED:20260305T131731Z
LAST-MODIFIED:20260305T131731Z
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SUMMARY:Using Conditional Transgenic Models
DESCRIPTION:This course is designed for anyone working with conditional mouse models\, including the Cre-Lox system and alternative recombinase platforms such as Flp\, Dre\, and Vika. These technologies provide researchers with the ability to manipulate gene expression in a spatially and/or temporally controlled manner\, enabling precise investigation of biological processes that cannot be interrogated using traditional constitutive knockout models. \nBy allowing genes to be selectively turned on or off in specific tissues\, cell types\, or developmental stages\, conditional systems offer powerful means to dissect the roles of individual genes within complex physiological networks. Moreover\, combining multiple recombinase systems expands the experimental possibilities even further – for example\, enabling the controlled exchange of a wild type exon for a mutant variant at a defined point in time to model disease progression with exceptional precision. \nHowever\, the intricate mechanisms underlying conditional systems make them particularly vulnerable to errors and misinterpretation. \nWhile the biology behind these approaches is elegant\, in practice there are numerous pitfalls that can compromise experimental outcomes. Many of these issues are not immediately apparent from the literature on conditional models\, nor are they always obvious within an experiment unless you know what to look for. Consequently\, researchers may unknowingly draw inaccurate conclusions\, with errors that can propagate and compromise downstream studies. \nThis course aims to equip trainees with a clear understanding of how these models function biologically\, as well as the practical ways in which they can fail. We will cover how to anticipate and control for confounding effects\, how to troubleshoot unexpected results\, and how to proceed when a model does not behave as expected. \nWho is this for? \nAnyone who is using or planning to use conditional models\, that has previous knowledge of advanced mouse genetics\, including researchers\, PhD students and colony managers. \nAfter this course\, you will be able to: \n\nUnderstand the basic principles of conditional transgenesis\nUnderstand how cre expressing and floxed alleles are produced and the potential impact on the experimental outcome\nIdentify the advantages and challenges of these systems\nAnalyse recombinase (Cre) expression\nUnderstand how to establish colonies for conditional transgenesis and the importance of background strain within this\nPlan breeding schemes with consideration of control strategies and cohort numbers\n\n\nRegister
URL:https://www.dementiaresearcher.nihr.ac.uk/event/using-conditional-transgenic-models/
LOCATION:MRC Harwell\, Becquerel Avenue\, Harwell\, Didcot\, Oxfordshire\, OX11 0RD\, United Kingdom
CATEGORIES:Training
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20260622
DTEND;VALUE=DATE:20260627
DTSTAMP:20260618T071522
CREATED:20260612T144611Z
LAST-MODIFIED:20260612T144611Z
UID:10002287-1782086400-1782518399@www.dementiaresearcher.nihr.ac.uk
SUMMARY:Introduction to Longitudinal Data Analysis
DESCRIPTION:Longitudinal data is essential in a number of research fields as it enables analysts to concurrently understand aggregate and individual level change in time\, the occurrence of events and improves our understanding of causality in the social sciences.  \nIn this course you will learn both how to clean longitudinal data as well as the main statistical models used to analyse it. The course will cover three fundamental frameworks for analysing longitudinal data: multilevel modelling\, structural equation modelling and event history analysis. \nThe course is organized as a mixture of lectures and hands on practicals using real world data. During the course there will also be opportunities to discuss also how to apply these models in your own research. \nObjectives: \n\nTo gain competence in the concepts\, designs and terms of longitudinal research;\nTo be able to apply a range of different methods for longitudinal data analysis;\nTo have a general understanding of how each method represents different kinds of longitudinal processes;\nTo be able to choose a design\, a plausible model and an appropriate method of analysis for a range of research questions.\n\nThe course consists of five sessions running from Monday 22 to Friday 26 June 2026. \nTopics covered by day: \n\n22.06.2026  – Data cleaning and visualization of longitudinal data\n23.06.2026 – Cross-lagged models (covering also an introduction to Structural Equation Modelling and auto-regressive models)\n24.06.2026 – Multilevel model of change (covering also an introduction to multilevel modelling)\n25.06.2026 –  Latent Growth Modelling\n26.06.2026  – Survival models (also known as event history analysis)\n\nTeaching will take place online (using Zoom) between 09:00 to 16:00 UK time. There will be 1 hour lunch break from 12:00 to 13:00. \nIMPORTANT: Please note that this course includes computer workshops. Before registering please check that you will be able to access the software noted below. Please bear in mind minimum system requirements to run software and administration restrictions imposed by your institution or employer with may block the installation of software. \nPrerequisites \n\nGood knowledge of regression modelling\nBasic knowledge of R or good programming experience with a different statistical software\n\nRecommended reading \n\nCernat\, A. (in press). Longitudinal Data Analysis using R. LeanPub.\nWickham\, H.\, & Grolemund\, G. (2016). R for data science: Import\, tidy\, transform\, visualize\, and model data (First edition). O’Reilly. (also available free online)\nSinger\, J.\, & Willett\, J. (2003). Applied longitudinal data analysis: modeling change and event occurrence. Oxford University Press.\nNewsom\, J. T. (2015). Longitudinal Structural Equation Modeling: A Comprehensive Introduction. Routledge.\n\nCost: \nThe fee per teaching day is: \n• £60 per day for students\n• £150 per day for staff working for academic institutions\, Research Councils and other recognised research institutions\, registered charity organisations and the public sector\n• £350 per day for all other participants \nIn the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. NO refunds are available after this date. \nIf it is no longer possible to run a course due to circumstances beyond its control\, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. \nNCRM shall not be liable for any costs\, losses or expenses that may be incurred as a result of its cancellation of a course\, including but not limited to any travel or accommodation costs.
URL:https://www.dementiaresearcher.nihr.ac.uk/event/introduction-to-longitudinal-data-analysis/
LOCATION:Online\, United Kingdom
CATEGORIES:Training
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DTSTART;TZID=Europe/London:20260622T160000
DTEND;TZID=Europe/London:20260622T170000
DTSTAMP:20260618T071522
CREATED:20260415T142807Z
LAST-MODIFIED:20260415T142807Z
UID:10002190-1782144000-1782147600@www.dementiaresearcher.nihr.ac.uk
SUMMARY:ISTAART - MRI Assessment of Myelin & Iron Change in AD
DESCRIPTION:Join our the ISTAART Neuroimaging Professional Interest Area (PIA) for the new Neuroimaging Primer Series\, launching in June as an extension of the ISTAART’s The Basics webinars. \nThis webinar covers the core concepts of Chi-separation MRI for assessing myelin and iron. We will explore real-world applications and provide a practical guide to using our toolbox to process your neuroimaging data. \nSpeaker: \n\nJongho Lee\, Ph.D.; Laboratory for Imaging Science and Technology (LIST)\, Seoul National University\, Republic of Korea\n\nModerators: \n\nMichael Ewers\, Ph.D.; Institute for Stroke and Dementia Research\, University Hospital\, Ludwig Maximilian University\, Munich\, Germany\nSamuel N. Lockhart\, Ph.D.; Perceptive Inc.\, United States\n\nSign up here and join us on Monday\, June 22\, 2026 at 10 a.m. C.T.
URL:https://www.dementiaresearcher.nihr.ac.uk/event/istaart-mri-assessment-of-myelin-iron-change-in-ad/
LOCATION:Online\, United Kingdom
CATEGORIES:Training
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BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260625T150000
DTEND;TZID=Europe/London:20260625T160000
DTSTAMP:20260618T071522
CREATED:20260611T094315Z
LAST-MODIFIED:20260611T094315Z
UID:10002285-1782399600-1782403200@www.dementiaresearcher.nihr.ac.uk
SUMMARY:Integrated Characterization of iPSC-Derived CNS Co-Culture Models
DESCRIPTION:Join Proteintech Group for a webinar exploring advanced workflows for culturing human iPSC-derived neurons\, astrocytes\, and microglia\, and how co-culture systems can enhance physiologically relevant CNS modeling. \nDr Semra Sahin\, Applications Scientist at BrainXell\, will present strategies for robust characterization and validation of these models\, emphasizing the importance of cell identity\, purity\, and reproducibility. \nDr. Sahin will also cover: \n\nKey challenges in iPSC-derived neuronal and glial cell cultures and practical solutions\nOptimized protocols for co-culture systems\nBest practices for combining structural and functional readouts in translational CNS research\, supported by high-quality\, validated antibody tools\n\nAttendees will receive: \n\nIn-depth Q&A session with Dr. Sahin\nCertificate of attendance\nRecording of the session\nFree product sample\n\n\nRegister
URL:https://www.dementiaresearcher.nihr.ac.uk/event/integrated-characterization-of-ipsc-derived-cns-co-culture-models/
LOCATION:Online\, United Kingdom
CATEGORIES:Training
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ORGANIZER;CN="Proteintech Group":MAILTO:rebecca@ptglab.com
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