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ECCB 2026: the 25th European Conference on Computational Biology
Item type: Other Journal Item
Beerenwinkel, Niko; Bitbol, Anne-Florence; Gonzalez Gaarslev, Natalia; et al. (2026)
Scalable flame spray-derived bismuth catalysts enable efficient CO2 electrolysis revealed by FIB-SEM nano-tomography and ICP-MS EDX profiling
Item type: Journal Article
Rieder, Alain; Rabiee, Hesamoddin; Lorenzutti, Francesca; et al. (2026)
CO2 electrolysis is a promising route to convert CO2 into value-added chemicals. Here, we use flame spray pyrolysis (FSP) as a rapid and scalable method to synthesize Bi2O3 nanospheres and evaluate their formate production in a gas diffusion electrode flow electrolyzer. Under reaction conditions, Bi2O3 converts in situ into bismuth subcarbonate, delivering >90% formate Faradaic efficiency across −0.6 to −1.6 V vs. reversible hydrogen electrode (RHE), reaching a formate partial current density of −700 mA.cm−2 at −1.8 V. This performance is nearly twice that of electrochemically deposited dendritic Bi2O3. To elucidate the origin of this high performance, a combined tomography approach based on focused ion beam-scanning electron microscopy (FIB-SEM) nano-tomography and inductively coupled plasma-mass spectrometry (ICP-MS) EDX cross-sectional profiling was introduced to track catalyst layer morphology and electrolyte-induced flooding. The FSP-derived catalyst forms a compact layer near the microporous layer, confining flooding to the catalyst microporous interface and improving operational stability. This work provides mechanistic insight and characterization guidelines for designing durable, high-performance electrodes for CO2 electrolysis.
Chiron3D: an interpretable deep learning framework for understanding the DNA code of chromatin looping
Item type: Conference Paper
Hönig, Sebastian; Grover, Aayush; Neri, Piero; et al. (2026)
MOTIVATION: Three-dimensional folding of the genome into structures such as chromatin loops is essential for gene regulation. Current experimental methods for mapping these structures, like Hi-C and HiChIP, are labor-intensive and require repeated assays to test hypothesized mutation effects. This motivates the need for predictive approaches that reveal the sequence determinants of chromatin loops. RESULTS: In this work, we present a novel and interpretable computational pipeline for predicting CTCF-mediated chromatin loops. We propose Chiron3D, a DNA-only model trained in a cell-type specific manner to predict CTCF HiChIP contact maps. By leveraging pre-trained embeddings from a foundation model, our approach is competitive with baselines that take CTCF ChIP-seq as additional input, while enabling nucleotide-level attribution to the input DNA sequence. Using our framework, we provide likely mechanistic insights into the physical control of loop dynamics. Specifically, we find that the strength of the loop extrusion anchorage site is largely governed by the amount and binding affinity of CTCF sites at the boundaries. Furthermore, we reveal that loop stability is regulated by the amount of intra-loop CTCF binding sites, where fewer intra-loop sites are associated with greater loop stability. Using targeted, single-nucleotide edit simulations with Chiron3D, we show that both loop strength and stability can be precisely controlled. Together, these results provide novel mechanistic insights into the physical control of genome organization and highlight the potential of decoding the DNA sequence logic in silico. AVAILABILITY: The Chiron3D pipeline is made available at https://github.com/BoevaLab/Chiron3D.
Trace element partitioning for carbonated silicate melts generated in asthenospheric melting columns
Item type: Dataset
Schettino, Erwin; Schmidt, Max W. (2026)
Höper, Philipp; Zachmann, Lucca; Finger, Robert (2025)
This dataset contains survey responses from 489 Swiss grapevine growers collected in spring 2025. It covers production choices, pest and risk management, labour management, and behavioural factors. Key data include adoption of pesticide-reducing practices, farm and farmer characteristics, labour details, and environmental variables linked to disease risk.
This data provides an extensive resource for analysis on production, pest management, risk management, behavioural factors, and labour organization which could be used for meta-analysis or in a panel dataset with previous similar surveys. All personally identifiable data has been removed for confidentiality reasons.