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About the WorkshopGene expression is regulated through a series of complex, coordinated events, including the localization of specific RNA molecules to distinct subcellular locations. This subcellular organization of RNA facilitates the local production of protein and is critical for cellular function in a wide range of organisms. However, the mechanisms that underlie the localization of many RNAs and how their localization contributes to organismal fitness remain poorly understood. To gain new insights into these processes, several new techniques have been recently developed that allow unprecedented study and quantification of RNA-based processes inside living cells. This EMBO Workshop will bring together scientists from a variety of fields with complementary areas of expertise to share recent work on the causes and consequences of subcellular RNA localization as well as applications of new technologies and the discoveries they permit. Additionally, this EMBO Workshop will provide ample opportunity for professional development and networking, particularly for junior scientists.

Synthetic Biology (SynBio) has become a maturing field: after more than two decades of development, available tools and knowledge allow wider and more systematic capabilities of designing, engineering, assembling and controlling biological systems for an increasing number of applications. This course will focus on equipping students with hands-on experience on cutting-edge SynBio tools, while supported by lectures from across the field: discussing different aspects of the engineering cycle that also highlight how those are converging towards a better understanding of biology. The program of this course involves different disciplines relevant for SynBio, such as genetic engineering, cell biology and machine-learning.In this course you will learn how they can be integrated to learn about biological complexity and especially how they can be used to design and engineer biological systems. We will focus on diverse natural organisms, including bacteria, eukaryotic organisms, and also synthetic cell-like systems. The schedule includes lectures by experts, student poster presentations and our proposed experimental program:-multiplex genome and plasmid engineering in bacteria-RNA tools for system-wide control in mammalian cells-AI-based modeling approaches to predict and design gene expression.

OverviewLung function tests are routinely used to diagnose and monitor chronic lung diseases, supplementing a detailed clinical and symptom history. Full lung function tests (including gas transfer and lung volumes) are typically performed in secondary or specialist care, while spirometry is routinely available in primary care settings. Historical challenges with availability and quality of spirometry have led to variability in performance and interpretation, contributing to over, under and misdiagnosis of respiratory disease.The complexity of technical interpretation standards has been highlighted by many clinicians and can further limit both confidence and competence in interpretation.Studies have demonstrated the potential of artificial intelligence (AI) decision support software in the assessment of full lung function tests, including the grading of technical quality and diagnostic prediction. More recently, AI software has been validated to identify cases of COPD using primary care spirometry data and shown to significantly improve the diagnostic prediction performance of primary care clinicians in identifying respiratory conditions, particularly COPD.AI can be an enabler in healthcare systems and is growing in use across different services. It is important to understand the evidence, opportunities and challenges in utilising AI to support lung function testing.There is a growing body of literature around this topic in European and international respiratory journals:Stanojevic, S. et al. ERS/ATS technical standard on interpretive strategies for routine lung function tests. European Respiratory Journal 60 (2022).Das, N. et al. Deep-learning algorithm helps to standardise ATS/ERS spirometric acceptability and usability criteria. European Respiratory Journal 56, 2000603 (2020). https://doi.org/10.1183/13993003.00603-2020Topalovic, M. et al. Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function tests. Eur Respir J 53 (2019). https://doi.org/10.1183/13993003.01660-2018Sunjaya, A. et al. Validation of artificial intelligence spirometry diagnostic support software in primary care: a blinded diagnostic accuracy study. ERJ Open Research, 00116-02025 (2025). https://doi.org/10.1183/23120541.00116-2025Doe, G. et al. AI-Assisted Spirometry Interpretation in Primary Care: A Randomized Controlled Trial. NEJM AI 2, AIoa2400804 (2025). https://doi.org/doi:10.1056/AIoa2400804Doe, G. et al. Spirometry services in England post-pandemic and the potential role of AI support software: a qualitative study of challenges and opportunities. British Journal of General Practice 73, e915-e923 (2023). https://doi.org/10.3399/bjgp.2022.0608Topics:ERS/ATS technical standard on interpretive strategies for routine lung function tests, including discussion about reference values and GLI 2022 - Sanja StanojevicAutomated interpretation of pulmonary function tests in secondary care - Wim JanssensCan artificial intelligence (AI) help in the interpretation of spirometry in primary care? Dissemination of an NIHR AI in Healthcare Award programme of research - Gillian DoeFormatOne-hour webinar structured as follows:Opening remarks - Introduction by Chairs (2 min)Presentation 1: ERS/ATS technical standard on interpretive strategies for routine lung function tests, including discussion about reference values and GLI 2022 - Sanja Stanojevic (14 min)Presentation 2: Automated interpretation of pulmonary function tests in secondary care - Wim Janssens (14 min)Presentation 3: Can Artificial Intelligence (AI) help in the interpretation of spirometry in primary care? Dissemination of an NIHR AI in Healthcare Award programme of research - Gillian Doe (14 min)Live Q&A and round table - moderated by Chairs (15 min)Wrap-up (1 min)Learning outcomesFollowing this webinar, participants will be able to:Understand the principles in the ATS/ERS 2022 international standards for interpretation of lung function tests.Understand how automated interpretation of lung function tests can be used effectively in secondary/specialist care.Have awareness of the challenges and opportunities of using AI in quality assessment and interpretation of lung function tests.Consider the application of AI supported spirometry in their own clinical practice, where the value and barriers might be.CME creditAn application for accreditation of this webinar has been made to the European Board for Accreditation in Pneumology (EBAP) for 1 CME credit per 1-hour attendance. If accredited, the CME credit will be granted upon attendance of at least 60 minutes during the live webinar only.