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Poster by X. Zhang at at the Protein Folding in Real Time conference, Stockholm, 11 March 2026

Reconstructed field of LCD2–CTPR4-Func1 condensates with LC3 at the sample plane (shown here as the imaginary component of the complex field). The condensates increase in size through Ostwald ripening and recruitment of LC3. (Image by X. Zhang.)
Quantitative Characterization of Biomolecular Condensates Using Off-Axis Holographic Microscopy
Xinwen Zhang, Nora Haanaes, Berenice García Rodríguez, Giovanni Volpe,  Janet Kumita and Daniel Midtvedt
Date: 11 March 2026
Time: 18:00-20:00
Place: Aula Medica, Karolinska Institute, Solna
Conference Protein Folding in Real Time, 11-13 March 2026, Stockholm, Sweden

Biomolecular condensates formed through liquid–liquid phase separation (LLPS) play important roles in cellular organization, yet quantitative and label-free characterization of their physical properties remains challenging. In this work, we apply off-axis holographic microscopy to study a synthetic biomolecular condensate platform based on the LCD2-CTPR protein system. These proteins, composed of modular consensus-designed tetratricopeptide repeat (CTPR) domains fused to intrinsically disordered regions, undergo phase separation under varying salt concentrations. By incorporating short binding motifs such as ATG13 or Func1, the condensates can specifically recruit the autophagy-related protein LC3. Using label-free quantitative phase measurements, we analyze changes in condensate optical radius and refractive index during LC3 recruitment and over time. Our results show measurable variations in condensate size and optical properties, highlighting the sensitivity of these systems to compositional changes. This work demonstrates the applicability of holographic microscopy for quantitative characterization of synthetic biomolecular condensates and provides a framework for studying protein phase separation in a non-invasive manner.

Poster by E. A. Duta Costache at the Protein Folding in Real Time conference, Stockholm, 11 March 2026

Pointwise absolute error plots for the heat equation tested across five architectures. The plots show the mean absolute error achieved by each architecture on a periodic-mode initial condition. Errors are shown on a logarithmic scale. Blue colors indicate smaller errors. (Image by E. A. Duta Costache.)
The optimization autopsy of PINNs
Eduard Duta Costache, Benjamin Girault
Date: 11 March 2026
Time: 18:00-20:00
Place: Aula Medica, Karolinska Institute, Solna
Conference Protein Folding in Real Time, 11-13 March 2026, Stockholm, Sweden

Physics-Informed Neural Networks (PINNs) have emerged as a promising method for solving Partial Differential Equations (PDEs) by combining data-driven learning with physical laws. However, the spectral bias and optimization challenges limit their efficacy. This work investigates these issues and whether the advantages of classical spectral methods translate to the non-convex neural network optimization landscape. We show that gradient imbalance greatly affect learning and we study the Hessian conditioning under different settings. Our results indicate that spectral priors stabilize training, reduce error, and improve parameter efficiency. We also identify that learnable-basis models act as implicit regularizers under sparse sampling.

Poster by Sreekanth K Manikandan at the Protein Folding in Real Time conference, Stockholm, 11 March 2026

Recent advances in nonequilibrium physics allow extracting thermodynamic quantities, such as entropy production, directly from dynamical information in microscopic movies. (Figure by S. Manikandan, adapted from Manikandan et al., Phys. Rev. Research 6, 023310 (2024).)
Probing the Non-equilibrium Dynamics of Living Matter
Sreekanth K Manikandan
Date: 11 March 2026
Time: 18.00-20.00
Place: Aula Medica, Stockholm Sweden
Conference Protein Folding in Real Time, 11-13 March 2026, Stockholm, Sweden

Identifying whether a process is in equilibrium, quantifying its distance from equilibrium, and constructing optimal reduced descriptions of non-equilibrium dynamics remain central challenges in the study of living matter. Here, we discuss how data-driven approaches grounded in stochastic thermodynamics enable these features to be inferred directly from experimental data. In particular, we show how entropy production can be localized in space and time, and how maximally dissipative coordinates emerge as effective low-dimensional descriptions of non-equilibrium processes. We highlight applications to experimental biophysical systems and discuss key challenges and limitations.

Poster by M. Selin at the Protein Folding in Real Time conference, Stockholm, 11 March 2026

Illustration of three different experiments autonomously performed by the SmartTrap system: DNA pulling experiments (top), red blood cell stretching (bottom left), and particle-particle interaction measurements (bottom right). (Image by M. Selin.)
SmartTrap: Automation of single molecule experiments
Martin Selin, Antonio Ciarlo, Giuseppe Pesce, Lars Bengtsson, Joan Camunas-Soler, Vinoth Sundar Rajan, Fredrik Westerlund, L. Marcus Wilhelmsson, Isabel Pastor, Felix Ritort, Steven B. Smith, Carlos Bustamante, and Giovanni Volpe
Date: 11th March 2026
Time: 18:00 – 20:00
Place: Aula Medica, Karolinska Institute, Solna
Conference Protein Folding in Real Time, 11-13 March 2026, Stockholm, Sweden

Single-molecule studies are vital for understanding fundamental biological processes, including protein folding, DNA transcription, and replication. However, performing these experiments manually on individual molecules is notoriously time-consuming and costly. To address this challenge, we have developed a fully autonomous single-molecule force spectroscopy platform by integrating a custom-built optical tweezers instrument with real-time deep-learning-based image analysis and adaptive control protocols. Our system achieves human-level throughput in terms of experiments per hour while remaining robust enough to operate continuously for hours without intervention. We demonstrate the versatility of our platform by having it perform DNA pulling experiments fully autonomously. By making the software open source we democratize high-throughput data collection in single-molecule biophysics, paving the way for merging single-molecule studies with large-scale, data-driven approaches—ultimately enabling new insights into the dynamic, transient states of complex biological systems.

Poster by A. Schiano di Colella at the Protein Folding in Real Time conference, Stockholm, 11 March 2026

Schematic representation of the architecture of a quantum circuit for application in variational problems. (Image by A. Schiano di Colella.)
Quantum computing for variational problems
Andrea Schiano di Colella, Antonio Ciarlo, Mats Granath, Giovanni Volpe
Date: 11 March 2026
Time: 18:00 – 20:00
Place: Aula Medica, Karolinska Institutet, Stockholm, Sweden
Conference: Protein Folding in Real Time

Quantum computing is a field of study that aims to exploit quantum mechanical effects for the purposes of computation. Due to the intrinsic capacity of qubits of efficiently represent an exponentially large configuration space, quantum computation has been identified as a promising candidate for complex physical chemistry simulations, including investigating the dynamics of protein folding. This work illustrates the use of quantum computing for variational problems, and the use of alternative training methods such as genetic algorithms to avoid the “barren plateau” phenomenon, which prevents the training of general quantum circuits by means of the usual gradient descent.

Poster by J. Dominguez at the Protein Folding in Real Time conference, Stockholm, 11 March 2026

Brightfield image of biofilm inside the droplet where motile aggregates are highlighted in yellow, biofilm mass in blue, and open patches in the structures due to dispersal in orange. (Image from D. Pérez and J. Domínguez)
Quantitative Analysis of Dynamic Biofilm Structures via Time-Resolved Droplet Microfluidics and Artificial Intelligence
Daniela Pérez Guerrero, Jesús Manuel Antúnez Domínguez, Aurélie Vigne, Daniel Midtvedt, Wylie Ahmed, Lisa Muiznieks, Giovanni Volpe and Caroline Beck Adiels
Date: 11th March 2026
Time: 18:00 – 20:00
Place: Aula Medica, Karolinska Institute, Solna
Conference Protein Folding in Real Time, 11-13 March 2026, Stockholm, Sweden

Droplet Microfluidics offers a powerful approach to study the spatiotemporal dynamics of biofilm formation at high resolution and throughput. By encapsulating microbial communities within controlled microenvironments, it becomes possible to monitor biofilm development continuously using time-lapse imaging, capturing transitions from initial attachment to maturation and dispersal. To make sense of these complex, high-dimensional datasets, we are developing an unsupervised variational autoencoder framework that can automatically identify and separate distinct stages of biofilm growth without prior labeling. This approach enables the extraction of latent features that characterize structural and behavioral shifts within the biofilm over time. In this context, protein folding may play a critical role in regulating both the establishment and dispersal of biofilms, as the conformational states of key structural and regulatory proteins can influence adhesion, matrix production, and the transition back to planktonic states.

Poster by J. Tember at the Protein Folding in Real Time conference, Stockholm, 11 March 2026

Comparison of anisotropic light-sheet microscopy data and super-resolved reconstruction, illustrating improved continuity and structural clarity of volumetric features. (Image by J. Tember.)
FIREFLY – Framework for Interactive Rendering, Exploration and Feature Extraction for Light-Sheet Microscopy
John Tember, Harshith Bachimanchi, Tsz Long Chu, Xin Tian, Andrei Chagin, Giovanni Volpe
Date: 11th March 2026
Time: 18:00 – 20:00
Place: Aula Medica, Karolinska Institute, Solna
Conference: Protein Folding in Real Time, 11-13 March 2026, Stockholm, Sweden

We present FIREFLY (Framework for Interactive Rendering, Exploration and Feature Extraction for Light-Sheet Microscopy), a platform for scalable computational tools. Modern 3D microscopy datasets are increasingly large and complex, posing challenges for efficient visualization, processing, and quantitative analysis. Our work focuses on developing tools and methods to support interactive and high-quality analysis workflows.

We are building a Unity-based application for real-time, multi-channel 3D rendering, enabling interactive inspection and quantitative analysis of large volumetric datasets. In parallel, we explore self-supervised machine learning approaches for enhancing anisotropic microscopy volumes and improving resolution without requiring additional training data.

Together, these efforts aim to provide an integrated and scalable pipeline for visualization and analysis in light-sheet microscopy.

Poster by N. C. Palmero Cruz at the Protein Folding in Real Time conference, Stockholm, 11 March 2026

3D model of the integrated setup combining optical tweezers, light-sheet microscopy, and microfluidics to manipulate the gut microbiome in vivo in zebrafish. (Image by N. C. Palmero Cruz.)
Optical Manipulation of Gut Microbiome and Neural Responses in Zebrafish
Norma Caridad Palmero Cruz
Date: 11 March 2026
Time: 18.00-20.00
Place: Aula Medica, Stockholm Sweden
Conference Protein Folding in Real Time, 11-13 March 2026, Stockholm, Sweden

The gut-brain axis is a complex, bidirectional network linking the microbiome to the central nervous system, significantly affecting physiological processes and neurological health, including conditions like autism and depression. Due to the genetic similarities between zebrafish and humans, the zebrafish serves as a valuable model for investigating the bidirectional relationship between the gut and brain, offering insights into how it compares with human behaviors. Research on the connection between gut and brain development typically involves using germ-free lab animals, where the microbiome is eliminated, and comparing them to those with restored microbiomes. However, this method does not capture the complexity of microbiome-nervous system communication due to its all-or-nothing approach. This work presents a setup that combines microfluidic techniques, optical tweezers, and light sheet microscopy to precisely manipulate the microbiome in larval zebrafish in situ and in vivo. This approach offers deeper insights into gut-brain connectivity and its impact on neurological health.

Poster by L. Viaene at the Protein Folding in Real Time conference, Stockholm, 11 March 2026

Heat-induced aggregates in Saccharomyces cerevisiae on Slimfield SMLM. Hsp104-mGFP binds to misfolded regions enabling aggregate visualisation for tracking. (Image by L. Viaene.)
A single-molecule approach to study the spatial protein quality control system
Linde Viaene
Date: 11 March 2026
Time: 18.00-20.00
Place: Aula Medica, Stockholm Sweden
Conference Protein Folding in Real Time, 11-13 March 2026, Stockholm, Sweden

Cell populations are inherently diverse, and averaging measurements across them can mask subtle or rare cellular behaviours. In this work, we use live Slimfield single-molecule microscopy to study the role of Hsp104 in clearing misfolded and aggregated proteins after stress. By analysing endogenously tagged Hsp104, we quantify molecular diffusion and stoichiometry before and after heat stress. Our results show a transition from faster, more mobile molecules to larger, more static assemblies following stress, consistent with Hsp104 functionally engaging with protein aggregates. These measurements provide molecular-level insight into how cells respond to proteotoxic stress.

International conference “Protein Folding in Real Time: From Molecules to Disease”, Aula Medica, KI, Stockholm, 11-13 March 2026

Giovanni Volpe opens the Protein Folding in Real Time conference. (Photo by A. Ciarlo)
The international conference Protein Folding in Real Time: From Molecules to Disease opened today, 11 March 2026, at Aula Medica, KI, Stockholm.

The conference brings together researchers from multiple disciplines, including biophysics, molecular biology, computational science, and medicine, to discuss recent advances in the study of protein folding. Proteins must fold into precise three-dimensional structures to perform their biological functions, and failures in this process are associated with several diseases, including neurodegenerative disorders and cancer.

During the three-day meeting, participants attend a series of lectures and discussions covering topics such as single-molecule biophysics, high-resolution experimental techniques for observing folding dynamics, advanced molecular simulations, and artificial intelligence approaches for predicting folding pathways. Particular attention is given to the challenge of observing protein folding in real time, capturing transient intermediate states that determine whether proteins reach their functional structure or misfold.

The event also highlights the interdisciplinary and international nature of the initiative. Representatives from the Embassies of Italy, Japan, and Spain, together with UNESCO, take part in the meeting, emphasizing the global interest in advancing research on protein folding and its biomedical implications. The initiative aims to integrate experimental measurements, computational modeling, and data-driven approaches to build a predictive framework for protein folding dynamics. By combining advanced imaging, force spectroscopy, and machine learning methods, the initiative seeks to better understand how folding processes occur inside living systems and how their disruption can lead to disease.

Overall, the conference provides an opportunity for scientists from different institutions to exchange ideas, establish collaborations, and shape future research directions in the field of protein folding and misfolding. The launch of this initiative represents an important step toward bridging molecular-level observations with biomedical applications, ultimately contributing to improved strategies for diagnosing and treating diseases related to protein misfolding.