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Lunch Pitches with Cemal Erdem and Elin Chorell

To encourage cross pollination of ideas between researchers from different disciplines, IceLab hosts interdisciplinary research lunches with the vision of allowing ideas to meet and mate. During the Lunch Pitch Season, the creative lunches take place at KBC on a Wednesday.
Place: KBC Glasburen
Time: Wednesday 28 February at 12:00.

Pitch 1: Cemal Erdem: Make computational models great again

Assistant professor, Department of Medical Biosciences
Development of a single cancer drug, on average, costs more than half a billion US dollars and takes years to go into the market. However, so far underutilized large-scale computational models can help prioritize lead candidates and stratify potentially responsive patients. Computational models are also critical to re-purpose available drugs, reveal new mechanisms to target, and design better clinical regimens. For these models to become useful and predictive, they need to be trained on experimental and clinical data. One thing that the famous ChatGPT showed is that (machine learning) models can become quite successful if they are trained with large enough (!) data. So, in this talk, I will show snippets of computational models we can build in our lab and will inquire about any and all datasets the audience has or knows about. Only together, we can merge machine learning and mechanistic models with (patient) data to create clinically predictive computational models for cancer and other diseases.
What I am looking for: Introducing our newly established lab to the community, finding future collaborators and experimental data generators

Pitch 2: Elin Chorell: The sphinx of our metabolism

Assistant Professor, Department of Public Health and Clinical Medicine

The global rise in obesity and type 2 diabetes poses a significant health risk, accompanied by comorbidities like cardiovascular diseases and certain cancers. Recent findings challenge the notion of type 2 diabetes as a lifelong condition, revealing that a reduction of organ fat can induce disease remission meaning that lipid mechanisms are of key importance to both disease progression and remission. While diabetes can be managed with lifestyle changes and medication, the underlying mechanism remains unclear, hindering efficient risk prediction and treatment.

 Our expertise lies in mass spectrometry-based lipidomics screening, focusing on insulin signaling tissues, disease progression, and remission. We explore obesity-related states, studying the impact of exercise and diet through human studies, mouse models, and cell experiments. Our research indicates that sphingolipid metabolism, specifically in pancreatic islets and skeletal muscle, are detrimental for the insulin signaling machinery. The sphingolipid metabolism, like its namesake ‘the Sphinx’, remain an enigma due to their diverse chemical composition and therefore a challenge to measure.

In the quest to understand obesity-associated disease, we are focused on unraveling bioactive lipids chemical composition for better understanding of biological activity. Our current focus involves connecting altered tissue metabolism with circulating markers, providing insights into tissue-crosstalk and potential therapeutic markers for risk assessment and monitoring of this global health threat.


Interested in: We are seeking collaborators experienced in sorting cell populations and/or tissue/single cell bioimaging to further unravel the spatial orientation of the bioactive sphingolipid derivatives we have identified in our model systems.

Our overall aim is to deepen our understanding of the clearance and production of sphingolipid derivatives, which may interfere with insulin signaling mechanisms and contribute to disease progression.



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