Date/Time
Date(s) - 29/02/2024
5:30 pm - 7:00 pm
Location
BT2 Détente / Kitchenette 1st Floor room 101
Categories
Do you like scientific discussion? And how about Pizza?
If we gained your attention with ‘scientific’, or at least with ‘Pizza’, then you are already looking forward to the right event!
Pizza Club is a regularly held Journal Club event co-organized by The Representatives of the Doctoral Programme in Systems and Molecular Biomedicine, part of the Doctoral School in Science and Engineering (DSSE); and the Uni.lu student association ISCB RSG Luxembourg.
In short, Students (PhD candidates) present a scientific paper (+- 20 mins) they find interesting or that inspired the development of their individual PhD project (doesn’t need to be authored by the speaker).
There will be a open discussion round after each scientific presentation (2-3 students per event), followed by informal and fun chatting with some pizzas around!
Moreover, each presentation of peer-reviewed papers will be rewarded by 0.5 ECTS!
_____________
Speakers :
Abir ELBEJI (https://lu.linkedin.com/in/abir-elb%C3%A9ji)
Introduction: Abir is a 3rd year PhD student at the Luxembourg Institue of Health. Her research focus is on the identification of vocal biomarkers for symptoms/disease monitoring using AI methods.
Article: ‘Acoustic Analysis and Prediction of Type 2 Diabetes Mellitus Using Smartphone-Recorded Voice Segments’, Kaufman et al. 2023 (https://doi.org/10.1016/j.mcpdig.2023.08.005)
Article description: This study explores the potential of using voice analysis as a tool for prescreening or monitoring type 2 diabetes mellitus (T2DM). It involved analyzing voice recordings from participants, both nondiabetic and those diagnosed with T2DM, to identify differences in their vocal features. The participants, recruited in India, used a smartphone app to record a specific phrase multiple times a day over two weeks, generating a large dataset of recordings. The research found significant vocal differences between the two groups, which varied by gender. The study developed predictive models that showed a good level of accuracy in determining T2DM status. The findings suggest that voice analysis could serve as a non-invasive, convenient method for early detection or ongoing management of T2DM, especially when used alongside other indicators of the disease.
Evelyn GONZALEZ (https://www.linkedin.com/in/evelyn-gonzalez-754996209)
Introduction: Evelyn is a first year PhD student participating in NextImmune 2 DTU and under supervision of Prof. Thomas Sauter at the System Biology Group, DSLM deparment, University of Luxembourg. I’m working in metabolic modeling at the single cell resolution.
Article: ‘Identifying and targeting cancer-specific metabolism with network-based drug target prediction’, Pacheco et al. 2019 (https://doi.org/10.1016/j.ebiom.2019.04.046)
Article description: The study utilized the rFASTCORMICS RNA-seq workflow to construct high-resolution metabolic models from the TCGA dataset, focusing on colorectal cancer (CRC). The analysis revealed cancer-specific essential genes enriched for known drug targets, leading to the identification and
experimental validation of naftifine, ketoconazole, and mimosine as potential drugs for CRC, demonstrating the efficacy of the rFASTCORMICS workflow in predicting drug targets based on metabolic rewiring in cancer cells.
___________
If we attracted your interest by now, feel free to join the monthly Pizza Club, either as part of Audience or as a registered Speaker. For the latter, please kindly use this form to sign up as an upcoming Speaker, by choosing your category of paper and desired month to present. Looking forward to seeing you at the next Pizza Club!
