SPS BSI Webinar: MIR137 polygenic risk for schizophrenia and ephrin-regulated pathway: Role in brain morphology
May 29, 2024
Date: 31 May 2024
Time: 1:00 PM ET (New York Time)
Presenter(s): Dr. Elisabetta C. del Re
Meeting information:
Meeting number: 2632 269 5821
Password: hPFwSbt7H36 (47397287 when dialing from a phone or video system)
Join by phone:
+1-415-655-0002 US Toll
Access code: 263 226 95821
Join us Friday, May 31st, 2024, at 1:00 PM ET for an exciting virtual talk by Dr. Elisabetta C. del Re entitled: “MIR137 polygenic risk for schizophrenia and ephrin-regulated pathway: Role in brain morphology” as part of the activities of the Brain Space Initiative, co-sponsored by the Center for Translational Research in Neuroimaging and Data Science (TReNDS) and the Data Science Initiative, IEEE Signal Processing Society.
Abstract
MIR137 polygenic risk for schizophrenia and ephrin-regulated pathway: Role in brain morphology Background/Objective. Enlarged lateral ventricle (LV) volume and decreased volume in the corpus callosum (CC) are hallmarks of schizophrenia (SZ). We previously showed an inverse correlation between LV and CC volumes in SZ, with global functioning decreasing with increased LV volume. This study investigates the relationship between LV volume, CC abnormalities, and the microRNA MIR137 and its regulated genes in SZ, because of MIR137’s essential role in neurodevelopment.
Results: Increased LV volumes and decreased CC central, mid-anterior, and mid-posterior volumes were observed in SZ probands. The MIR137-regulated ephrin pathway was significantly associated with CC:LV ratio, explaining a significant proportion (3.42 %) of CC:LV variance, and more than for LV and CC separately. Other pathways explained variance in either CC or LV, but not both. CC:LV ratio was also positively correlated with Global Assessment of Functioning, supporting previous subsample findings. SNP-based heritability estimates were higher for CC central:LV ratio (0.79) compared to CC or LV separately.
Discussion: Our results indicate that the CC:LV ratio is highly heritable, influenced in part by variation in the MIR137-regulated ephrin pathway. Findings suggest that.
Biography
Elisabetta del Re is an Assistant Professor of Psychiatry at Harvard Medical School and Principal Investigator of NIMH funded research. She has multidisciplinary training in basic science, mental health, neuroimaging, including electrophysiology, and genetics. She holds a MA and PhD in Biochemistry and Experimental Pathology from Boston University; A MA in Mental Health from BGSP. Dr. del Re’s interest is in understanding psychosis and other serious mental illnesses, by looking at the genetics informing neural processes.
Recommended Articles:
Blokland, Gabriëlla Antonina Maria, et al. "MIR137 polygenic risk for schizophrenia and ephrin-regulated pathway: Role in lateral ventricles and corpus callosum volume." International Journal of Clinical and Health Psychology 24.2 (2024): 100458. (Link to Paper)
Heller, Carina, et al. "Smaller subcortical volumes and enlarged lateral ventricles are associated with higher global functioning in young adults with 22q11. 2 deletion syndrome with prodromal symptoms of schizophrenia." Psychiatry Research 301 (2021): 113979. (Link to Paper)
Call for Proposals: IEEE MLSP 2026
May 21, 2024
Submission Deadline: 15 August 2024
IEEE Signal Processing Society’s Machine Learning for Signal Processing Technical Committee (MLSP TC) is soliciting proposals from researchers interested in organizing the 2026 MLSP Workshop. The MLSP Workshop is a four-day workshop and will include tutorials on the first day.
Proposing teams are asked to create a proposal that follows the following outline:
Location and Venue: Give an idea on the venue size and facilities.
Conference Dates: Ensure they do not conflict with major holidays, or other SPS conferences and workshops. Typically, the workshop is held during the period of mid-September to mid-October.
Organizing Committee Members: Build the organizing committee considering factors including (a) active SPS members; (b) diversity in geographical, industry and academia, age, and gender; (c) conference and/or workshop experience; (d) event management experience. For examples, refer to the MLSP Workshops page.
Technical Program: Consider the overall structure and conference model; innovative initiatives; student and young professional initiatives; and industry-participation/support initiatives.
Budget including registration fees.
Hotels in the area that cater to different attendee budget levels.
Travel and transportation between the nearest airport and the conference venue.
Any other relevant information about the venue or the organization.
The intention letter deadline is August 1, 2024, and the deadline for submission of proposals is August 15, 2024.
Please submit your proposal to the MLSP TC Chair, Wenwu Wang, and the MLSP Workshop Sub-Committee Chair, Roland Hostettler, via email. We encourage you to contact them with questions or to obtain further details about the content of the proposals.
Proposals will be reviewed by the MLSP TC, and the selection results will be announced in October 2024.
Two Post Doctoral Researchers and One PhD Student in Advanced Medical Image Analysis
May 20, 2024
Project Description
We are glad to announce the launch of a new research project based on the collaboration between the Mathematics and Data Science (MADS) research group at Vrije Universiteit Brussel (VUB) and the Centre for Reproductive Medicine at UZ Brussel (Brussels IVF). This project aims at helping the field of assisted reproductive technology (ART) by developing innovative AI-driven frameworks for the analysis of high-dimensional oocyte/embryo images. By integrating advanced deep learning and mathematical modeling, we seek to investigate, understand and potentially improve decision-making in ART procedures. The ultimate objective of this interdisciplinary research is to push the boundaries of current reproductive treatment, potentially offering new insights and tools for clinicians.
Open Positions
We are opening the following research positions in Digital Mathematics (DIMA), a research group chaired by Prof. Ann Dooms from MADS, VUB.
1. Post-doctoral Researchers (2 vacancies)
Focus Area: Advanced deep learning and machine intelligence for medical image analysis.
Duration: Full-time position for 2 years (with possibility for extending to 30 month). Starting from 1stSeptember 2024.
Key Responsibilities:
Conceptualize, develop and implement deep learning and mathematical modeling algorithms for analyzing high-dimensional medical images.
Collaborate with embryologists and clinicians to integrate biological motivations into AI models.
Publish research findings in high-impact journals and present at conferences.
Requirements:
PhD in Applied Mathematics, Computer Science, Electrical/Electronic/Information Engineering, or related fields.
Strong background in deep learning, machine learning, computer vision and image processing.
Proven track record of publications in top-tier conferences and journals.
Excellent programming skills in Python/MATLAB and rich experiences with deep learning frameworks (e.g., PyTorch).
English as official working language.
2. Doctoral Candidate (1 position)
Focus Area: Mathematical modeling and machine learning for image analysis.
Duration: Full-time for 3 years (with possibility for extending to 4 years). Starting from 1st August 2024.
Key Responsibilities:
Develop mathematical models to assist/enhance AI-driven (e.g., deep learning based) image analysis.
Work closely with embryologists and post-doctoral researchers to integrate these models into the overall framework.
Data collection, preprocessing, and annotation.
Contribute to writing research papers and project reports.
Obtain a PhD diploma following the regulations of VUB.
Requirements:
Master's degree in (Applied) Mathematics, Computer Science, Electronic and Information Engineering, or related fields.
Strong analytical and problem-solving skills, being able to conduct independent research and development with strong self-motivation.
Experiences with mathematical modeling, machine learning and computer vision.
Proficiency in programming languages such as Python or MATLAB.
English as official working language.
How to Apply
If you are a highly motivated individual with a passion for advancing medical technology through AI and mathematical modeling, we encourage you to apply. Please send your CV and a cover letter detailing your research experience and interests to Prof. Ann Dooms ([email protected]) and Prof. Tan Lu ([email protected]).
All applications must be sent before 1st July 2024.
Two Post Doctoral Researchers and One PhD Student in Advanced Medical Image Analysis
May 20, 2024
Project Description
We are glad to announce the launch of a new research project based on the collaboration between the Mathematics and Data Science (MADS) research group at Vrije Universiteit Brussel (VUB) and the Centre for Reproductive Medicine at UZ Brussel (Brussels IVF). This project aims at helping the field of assisted reproductive technology (ART) by developing innovative AI-driven frameworks for the analysis of high-dimensional oocyte/embryo images. By integrating advanced deep learning and mathematical modeling, we seek to investigate, understand and potentially improve decision-making in ART procedures. The ultimate objective of this interdisciplinary research is to push the boundaries of current reproductive treatment, potentially offering new insights and tools for clinicians.
Open Positions
We are opening the following research positions in Digital Mathematics (DIMA), a research group chaired by Prof. Ann Dooms from MADS, VUB.
1. Post-doctoral Researchers (2 vacancies)
Focus Area: Advanced deep learning and machine intelligence for medical image analysis.
Duration: Full-time position for 2 years (with possibility for extending to 30 month). Starting from 1stSeptember 2024.
Key Responsibilities:
Conceptualize, develop and implement deep learning and mathematical modeling algorithms for analyzing high-dimensional medical images.
Collaborate with embryologists and clinicians to integrate biological motivations into AI models.
Publish research findings in high-impact journals and present at conferences.
Requirements:
PhD in Applied Mathematics, Computer Science, Electrical/Electronic/Information Engineering, or related fields.
Strong background in deep learning, machine learning, computer vision and image processing.
Proven track record of publications in top-tier conferences and journals.
Excellent programming skills in Python/MATLAB and rich experiences with deep learning frameworks (e.g., PyTorch).
English as official working language.
2. Doctoral Candidate (1 position)
Focus Area: Mathematical modeling and machine learning for image analysis.
Duration: Full-time for 3 years (with possibility for extending to 4 years). Starting from 1st August 2024.
Key Responsibilities:
Develop mathematical models to assist/enhance AI-driven (e.g., deep learning based) image analysis.
Work closely with embryologists and post-doctoral researchers to integrate these models into the overall framework.
Data collection, preprocessing, and annotation.
Contribute to writing research papers and project reports.
Obtain a PhD diploma following the regulations of VUB.
Requirements:
Master's degree in (Applied) Mathematics, Computer Science, Electronic and Information Engineering, or related fields.
Strong analytical and problem-solving skills, being able to conduct independent research and development with strong self-motivation.
Experiences with mathematical modeling, machine learning and computer vision.
Proficiency in programming languages such as Python or MATLAB.
English as official working language.
How to Apply
If you are a highly motivated individual with a passion for advancing medical technology through AI and mathematical modeling, we encourage you to apply. Please send your CV and a cover letter detailing your research experience and interests to Prof. Ann Dooms ([email protected]) and Prof. Tan Lu ([email protected]).
All applications must be sent before 1st July 2024.