Aitor is a PhD student at the University of the Basque Country.
During his visit, that will last until the 19 of August, he will focus on machine learning for image analysis.
Author: Agnese Callegari
Robert Sosa Principe joins the Soft Matter Lab
Robert is a PostDoc in the group of Prof. Carlos Bustamante at the University of California, Berkeley.
During his visit, he will focus on experiments of single-molecule biophysics.
Invited talk by L. Viaene at the first PhD Conference at the University of Gothenburg, 25 April 2025
Linde Viaene
Date: 25th of April
Time: 13:00
Place: Veras Gräsmatta, Gothenburg
The importance of protein folding and misfolding is indicated by the broad range of clinical manifestations that have protein aggregation at the base, such as neurodegenerative diseases, cancer and type II diabetes. A key factor in (energy) homeostasis is the DNA configuration of chromatin which allows for essential gene expression and adaptation to environmental factors. The Rpd3 deacetylase histone complex (DHAC) plays a crucial role in gene regulation and its disruption impairs stress-induced gene activation, highlighting its importance in cellular adaptation.
Using Saccharomyces cerevisiae as a model system, we aim to investigate the role of chromatin remodelling components in protein aggregation and cellular rejuvenation, which may influence aggregate retention and recovery speed. We will expose yeast cells to stressors such as heat shock, metabolic shifts, and oxidative stress to assess their effects on protein homeostasis and chromatin regulation. Growth assays will evaluate survival rates, while Western blotting will measure Hsp104 expression, a key heat shock protein involved in aggregate clearance. By employing our bespoke single-molecule fluorescence microscope, we will track aggregate formation, clearance, and spatial localization in live cells at molecular precision.
Our preliminary results indicate that some components of the Rpd3L complex, respectively alter the recovery rate after heat stress exposure. Hence, the goal is to explore further candidate genes and to determine their role in the stress-induced response. By elucidating the role of chromatin remodelers in stress adaptation, our findings may inform novel therapeutic strategies for age-related diseases.
Invited Talk by G. Volpe at OPIC/OMC 2025, Yokohama, Japan, 21 April 2025 (Online, Pre-recorded)
Giovanni Volpe
Optics & Photonics International Congress 2025 (OPIC 2025), The 11th Optical Manipulation and Structured Materials Conference (OMC2025)
Date: 21 April 2025
Time: 13:45 JST
Place: Yokohama, Japan (Online, Pre-recorded)
Yan Chen joins the Soft Matter Lab
Yan received a Ph.D. degree in Materials Physics and Chemistry, Fudan University, China
In her research, she focuses on multistimuli-responsive microrobots.
Computational memory capacity predicts aging and cognitive decline published in Nature Communications
Mite Mijalkov, Ludvig Storm, Blanca Zufiria-Gerbolés, Dániel Veréb, Zhilei Xu, Anna Canal-Garcia, Jiawei Sun, Yu-Wei Chang, Hang Zhao, Emiliano Gómez-Ruiz, Massimiliano Passaretti, Sara Garcia-Ptacek, Miia Kivipelto, Per Svenningsson, Henrik Zetterberg, Heidi Jacobs, Kathy Lüdge, Daniel Brunner, Bernhard Mehlig, Giovanni Volpe, Joana B. Pereira
Nature Communications 16, 2748 (2025)
doi: 10.1038/s41467-025-57995-0
Memory is a crucial cognitive function that deteriorates with age. However, this ability is normally assessed using cognitive tests instead of the architecture of brain networks. Here, we use reservoir computing, a recurrent neural network computing paradigm, to assess the linear memory capacities of neural-network reservoirs extracted from brain anatomical connectivity data in a lifespan cohort of 636 individuals. The computational memory capacity emerges as a robust marker of aging, being associated with resting-state functional activity, white matter integrity, locus coeruleus signal intensity, and cognitive performance. We replicate our findings in an independent cohort of 154 young and 72 old individuals. By linking the computational memory capacity of the brain network with cognition, brain function and integrity, our findings open new pathways to employ reservoir computing to investigate aging and age-related disorders.
Retina electronic paper with video-rate-tunable 45000 pixels per inch on ArXiv
Ade Satria Saloka Santosa, Yu-Wei Chang, Andreas B. Dahlin, Lars Osterlund, Giovanni Volpe, Kunli Xiong
arXiv: 2502.03580
As demand for immersive experiences grows, displays are moving closer to the eye with smaller sizes and higher resolutions. However, shrinking pixel emitters reduce intensity, making them harder to perceive. Electronic Papers utilize ambient light for visibility, maintaining optical contrast regardless of pixel size, but cannot achieve high resolution. We show electrically tunable meta-pixels down to ~560 nm in size (>45,000 PPI) consisting of WO3 nanodiscs, allowing one-to-one pixel-photodetector mapping on the retina when the display size matches the pupil diameter, which we call Retina Electronic Paper. Our technology also supports video display (25 Hz), high reflectance (~80%), and optical contrast (~50%), which will help create the ultimate virtual reality display.
Ade Satria Saloka Santosa joins the Soft Matter Lab
Ade holds a Master of Science degree in Industrial Chemistry from Pukyong National University, South Korea, and has research experience at the Korea Institute of Materials Science (KIMS).
During his PhD, he will focus on nanofabrication and e-paper technology.
Mathilda Gustafsson joins the Soft Matter Lab
Mathilda is a master student in Complex Adaptive Systems at Chalmers University of Technology.
During her time at the Soft Matter Lab, she will work on a project about tracking bacteria in sequences of microscopic images. In particular she will try to solve problems with overlapping bacteria using recurrent neural networks.
Brian Senabulya Joins the Soft Matter Lab
Brian is a master student in Physics at the Physics Department of Gothenburg University.
During his time at the Soft Matter Lab, he will work on a project about deep learning based particle tracking and trajectory linking.