Scientific Publications
Nickel-and/or iron-based ceria-supported catalysts for CO oxidation in combustion exhaust gases
Abstract We present a series of Ni, Fe, and mixed NiFe-based catalysts, deposited onto ceria prepared with either soft templated (with CTAB) or hard templated (with SBA-15) syntheses. The prepared materials were thoroughly characterized with SEM, HRTEM, EDX, ICP-MS, PXRD, and N2 adsorption techniques, to fully comprehend their physicochemical properties. All catalysts were then tested for carbon monoxide oxidation reaction at different temperatures, aiming to reach temperature and feed composition conditions typical of combustion exhausts from industrial and power plants (350–400 °C, in the presence of competitive species such as CO2 and H2O in the feed). Advanced reaction tests highlighted outstanding materials (especially NiFe catalyst deposited onto hard-templated ceria), displaying catalytic performances able to compete with those typical of noble metal–based catalysts. Such catalysts were further investigated by means of Raman, NEXAFS, H2–TPR, and CO@FT-IR, unraveling their surface and reduction properties, which make them excellent candidates for replacing more costly noble metal-based catalysts currently employed for CO oxidation reaction. Authors Andrea Lazzarini, Luciano Atzori, Matteo Signorile, Luca Braglia, Francesco Ferella, Maria Giorgia Cutrufello, Elisabetta Rombi, Marcello Crucianelli Journal Journal of Catalysis Date 24/01/2024 Consult the paper
Peptide Stereochemistry Effects from pKa-Shift to Gold Nanoparticle Templating in a Supramolecular Hydrogel
Abstract The divergent supramolecular behavior of a series of tripeptide stereoisomers was elucidated through spectroscopic, microscopic, crystallographic, and computational techniques. Only two epimers were able to effectively self-organize into amphipathic structures, leading to supramolecular hydrogels or crystals, respectively. Despite the similarity between the two peptides’ turn conformations, stereoconfiguration led to different abilities to engage in intramolecular hydrogen bonding. Self-assembly further shifted the pKa value of the C-terminal side chain. As a result, across the pH range 4–6, only one epimer predominated sufficiently as a zwitterion to reach the critical molar fraction, allowing gelation. By contrast, the differing pKa values and higher dipole moment of the other epimer favored crystallization. The four stereoisomers were further tested for gold nanoparticle (AuNP) formation, with the supramolecular hydrogel being the key to control and stabilize AuNPs, yielding a nanocomposite that catalyzed the photodegradation of a dye. Importantly, the AuNP formation occurred without the use of reductants other than the peptide, and the redox chemistry was investigated by LC–MS, NMR, and infrared scattering-type near field optical microscopy (IR s-SNOM). This study provides important insights for the rational design of simple peptides as minimalistic and green building blocks for functional nanocomposites. Authors Simone Adorinni, Serena Gentile, Ottavia Bellotto, Slavko Kralj, Evelina Parisi, Maria C. Cringoli, Caterina Deganutti, Giuliano Malloci, Federica Piccirilli, Paolo Pengo, Lisa Vaccari, Silvano Geremia, Attilio V. Vargiu, Rita De Zorzi, Silvia Marchesan Journal ACS Nano Publication date 18/01/2024 Consult the publication
Successful treatment of life-threatening mycobacteriosis using adjunctive gamma-interferon therapy with genetic analysis.
Abstract No abstract Authors Confalonieri P, Maiocchi S, Salton F, Ruaro B, Rizzardi C, Volpe MC, Licastro D, Braga L, Confalonieri M Journal IJTLD Open Date 01/01/2024 Consult the paper
Synthesis, characterization, functional testing and ageing analysis of bifunctional Zn-air battery GDEs, based on α-MnO2 nanowires and Ni/NiO nanoparticle electrocatalysts
Abstract Electrically rechargeable alkaline zinc air batteries (RZAB) – currently still at the R&D stage –, have great potential for stationary, as well as prospectively mobile, electrochemical energy storage applications. Their chief appeal is that they are made of abundant, environmentally friendly, intrinsically safe, and cheap materials, with established recycling concepts and auspicious life-cycle costs. One of the key weak points of present-generation RZAB programs is the air gas-diffusion electrode (GDE). In fact, on the one hand, GDE fabrication and testing are generally based on poorly understood protocols, and, on the other hand, performance is challenged by efficiency and durability issues. This work is centred on the fabrication of a novel bifunctional GDE for the air side of RZABs, on the assessment of its electrochemical performance and on the identification of factors impacting its efficiency and durability. The electrocatalysts for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are α-MnO2 nanowires and Ni/NiO nanoparticles, respectively. The composition of the active layer was optimized with rotating ring-disc electrode (RRDE) electrocatalysts tests. The GDEs were fabricated by spray-coating an ink, formulated with the electrocatalysts and the PTFE binder in an aqueous matrix. Fabrication and functional performance of GDEs – in pristine form and after ageing under realistic RZAB conditions – are rationalized on the basis of Scanning Electron Microscopy (SEM), Scanning Transmission X-ray SpectroMicroscopy (STXSM) at the Mn l-edge and Transmission Electron Microscopy (TEM) analyses. Imaging and spectral imaging disclosed the morphological and chemical-state evolution, brought about by electrochemical cycling. Special attention was devoted to the understanding of the role played by the presence of zincate in the electrolyte on the performance and ageing of the reversible air electrodes. Authors Salman Y., Waseem S., Alleva A., Banerjee P., Bonanni V., Emanuele E., Ciancio R., Gianoncelli A., Kourousias G., Li Bassi A., Macrelli A, Marini E., Rajak P., Bozzini B., Journal Electrochimica Acta Date 20/11/2023 Consult the paper
Phenotyping the virulence of SARS-CoV-2 variants in hamsters by digital pathology and machine learning
Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued to evolve throughout the coronavirus disease-19 (COVID-19) pandemic, giving rise to multiple variants of concern (VOCs) with different biological properties. As the pandemic progresses, it will be essential to test in near real time the potential of any new emerging variant to cause severe disease. BA.1 (Omicron) was shown to be attenuated compared to the previous VOCs like Delta, but it is possible that newly emerging variants may regain a virulent phenotype. Hamsters have been proven to be an exceedingly good model for SARS-CoV-2 pathogenesis. Here, we aimed to develop robust quantitative pipelines to assess the virulence of SARS-CoV-2 variants in hamsters. We used various approaches including RNAseq, RNA in situ hybridization, immunohistochemistry, and digital pathology, including software assisted whole section imaging and downstream automatic analyses enhanced by machine learning, to develop methods to assess and quantify virus-induced pulmonary lesions in an unbiased manner. Initially, we used Delta and Omicron to develop our experimental pipelines. We then assessed the virulence of recent Omicron sub-lineages including BA.5, XBB, BQ.1.18, BA.2, BA.2.75 and EG.5.1. We show that in experimentally infected hamsters, accurate quantification of alveolar epithelial hyperplasia and macrophage infiltrates represent robust markers for assessing the extent of virus-induced pulmonary pathology, and hence virus virulence. In addition, using these pipelines, we could reveal how some Omicron sub-lineages (e.g., BA.2.75 and EG.5.1) have regained virulence compared to the original BA.1. Finally, to maximise the utility of the digital pathology pipelines reported in our study, we developed an online repository containing representative whole organ histopathology sections that can be visualised at variable magnifications (https://covid-atlas.cvr.gla.ac.uk). Overall, this pipeline can provide unbiased and invaluable data for rapidly assessing newly emerging variants and their potential to cause severe disease. Authors Gavin R Meehan, Vanessa Herder, Jay Allan, Xinyi Huang, Karen Kerr, Diogo Correa Mendonca, Georgios Ilia, Derek W Wright, Kyriaki Nomikou, Quan Gu, Sergi Molina Arias, Florian Hansmann, Alexandros Hardas, Charalampos Attipa, Giuditta De Lorenzo, Vanessa Cowton, Nicole Upfold, Natasha Palmalux, Jonathan C Brown, Wendy S Barclay, Ana Da Silva Filipe, Wilhelm Furnon, Arvind H Patel, Massimo Palmarini Journal PLoS Pathogens Publication Date 17/11/2023 Consult the publication
Redundant representations help generalization in wide neural networks
Abstract Deep neural networks (DNNs) defy the classical bias-variance trade-off; adding parameters to a DNN that interpolates its training data will typically improve its generalization performance. Explaining the mechanism behind this ‘benign overfitting’ in deep networks remains an outstanding challenge. Here, we study the last hidden layer representations of various state-of-the-art convolutional neural networks and find that if the last hidden representation is wide enough, its neurons tend to split into groups that carry identical information and differ from each other only by statistically independent noise. The number of these groups increases linearly with the width of the layer, but only if the width is above a critical value. We show that redundant neurons appear only when the training is regularized and the training error is zero. Authors Diego Doimo, Aldo Glielmo, Sebastian Goldt, Alessandro Laio Journal Journal of Statistical Mechanics: Theory and Experiment Publication Date 15/11/2023 Consult the publication
SARS-CoV-2 variants evolve convergent strategies to remodel the host response
Abstract SARS-CoV-2 variants of concern (VOCs) emerged during the COVID-19 pandemic. Here, we used unbiased systems approaches to study the host-selective forces driving VOC evolution. We discovered that VOCs evolved convergent strategies to remodel the host by modulating viral RNA and protein levels, altering viral and host protein phosphorylation, and rewiring virus-host protein-protein interactions. Integrative computational analyses revealed that although Alpha, Beta, Gamma, and Delta ultimately converged to suppress interferon-stimulated genes (ISGs), Omicron BA.1 did not. ISG suppression correlated with the expression of viral innate immune antagonist proteins, including Orf6, N, and Orf9b, which we mapped to specific mutations. Later Omicron subvariants BA.4 and BA.5 more potently suppressed innate immunity than early subvariant BA.1, which correlated with Orf6 levels, although muted in BA.4 by a mutation that disrupts the Orf6-nuclear pore interaction. Our findings suggest that SARS-CoV-2 convergent evolution overcame human adaptive and innate immune barriers, laying the groundwork to tackle future pandemics. Authors Mehdi Bouhaddou, Ann-Kathrin Reuschl, Benjamin J Polacco, Lucy G Thorne, Manisha R Ummadi, Chengjin Ye, Romel Rosales, Adrian Pelin, Jyoti Batra, Gwendolyn M Jang, Jiewei Xu, Jack M Moen, Alicia L Richards, Yuan Zhou, Bhavya Harjai, Erica Stevenson, Ajda Rojc, Roberta Ragazzini, Matthew VX Whelan, Wilhelm Furnon, Giuditta De Lorenzo, Vanessa Cowton, Abdullah M Syed, Alison Ciling, Noa Deutsch, Daniel Pirak, Giulia Dowgier, Dejan Mesner, Jane L Turner, Briana L McGovern, M Luis Rodriguez, Rocio Leiva-Rebollo, Alistair S Dunham, Xiaofang Zhong, Manon Eckhardt, Andrea Fossati, Nicholas F Liotta, Thomas Kehrer, Anastasija Cupic, Magdalena Rutkowska, Ignacio Mena, Sadaf Aslam, Alyssa Hoffert, Helene Foussard, Charles Ochieng’Olwal, Weiqing Huang, Thomas Zwaka, John Pham, Molly Lyons, Laura Donohue, Aliesha Griffin, Rebecca Nugent, Kevin Holden, Robert Deans, Pablo Aviles, Jose A Lopez-Martin, Jose M Jimeno, Kirsten Obernier, Jacqueline M Fabius, Margaret Soucheray, Ruth Hüttenhain, Irwin Jungreis, Manolis Kellis, Ignacia Echeverria, Kliment Verba, Paola Bonfanti, Pedro Beltrao, Roded Sharan, Jennifer A Doudna, Luis Martinez-Sobrido, Arvind H Patel, Massimo Palmarini, Lisa Miorin, Kris White, Danielle L Swaney, Adolfo Garcia-Sastre, Clare Jolly, Lorena Zuliani-Alvarez, Greg J Towers, Nevan J Krogan Journal Cell Publication Date 12/10/2023 Consult the publication
The geometry of hidden representations of large transformer models
Abstract Large transformers are powerful architectures used for self-supervised data analysis across various data types, including protein sequences, images, and text. In these models, the semantic structure of the dataset emerges from a sequence of transformations between one representation and the next. We characterize the geometric and statistical properties of these representations and how they change as we move through the layers.By analyzing the intrinsic dimension (ID) and neighbor composition, we find that the representations evolve similarly in transformers trained on protein language taskand image reconstruction tasks. In the first layers, the data manifold expands, becoming high-dimensional, and then contracts significantly in the intermediate layers. In the last part of the model, the ID remains approximately constant or forms a second shallow peak. We show that the semantic information of the dataset is better expressed at the end of the first peak, and this phenomenon can be observed across many models trained on diverse datasets.Based on our findings, we point out an explicit strategy to identify, without supervision, the layers that maximize semantic content: representations at intermediate layers corresponding to a relative minimum of the ID profile are more suitable for downstream learning tasks. Authors Lucrezia Valeriani, Diego Doimo, Francesca Cuturello, Alessandro Laio, Alessio Ansuini, Alberto Cazzaniga Journal Advances in Neural Information Processing Systems 36 (NEURIPS 2023) Main Conference Track Publication Date 21/09/2023 Consult the paper
Shared metadata for data-centric materials science
Abstract The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data principles (Findable, Accessible, Interoperable, and Reusable) must not be too narrow. Besides, the wider materials-science community ought to agree on the strategies to tackle the challenges that are specific to its data, both from computations and experiments. In this paper, we present the result of the discussions held at the workshop on “Shared Metadata and Data Formats for Big-Data Driven Materials Science”. We start from an operative definition of metadata, and the features that a FAIR-compliant metadata schema should have. We will mainly focus on computational materials-science data and propose a constructive approach for the FAIRification of the (meta)data related to ground-state and excited-states calculations, potential-energy sampling, and generalized workflows. Finally, challenges with the FAIRification of experimental (meta)data and materials-science ontologies are presented together with an outlook of how to meet them. Authors Luca M. Ghiringhelli, Carsten Baldauf, Tristan Bereau, Sandor Brockhauser, Christian Carbogno, Javad Chamanara, Stefano Cozzini, Stefano Curtarolo, Claudia Draxl, Shyam Dwaraknath, Ádám Fekete, James Kermode, Christoph T. Koch, Markus Kühbach, Alvin Noe Ladines, Patrick Lambrix, Maja-Olivia Himmer, Sergey V. Levchenko, Micael Oliveira, Adam Michalchuk, Ronald E. Miller, Berk Onat, Pasquale Pavone, Giovanni Pizzi, Benjamin Regler, Gian-Marco Rignanese, Jörg Schaarschmidt, Markus Scheidgen, Astrid Schneidewind, Tatyana Sheveleva, Chuanxun Su, Denis Usvyat, Omar Valsson, Christof Wöll & Matthias Scheffler Journal Scientific Data Publication Date 14/09/2023 Consult the publication
Multiplexed biosensing of proteins and virions with disposable plasmonic assays
Abstract Our growing ability to tailor healthcare to the needs of individuals has the potential to transform clinical treatment. However, the measurement of multiple biomarkers to inform clinical decisions requires rapid, effective, and affordable diagnostics. Chronic diseases and rapidly evolving pathogens in a larger population have also escalated the need for improved diagnostic capabilities. Current chemical diagnostics are often performed in centralized facilities and are still dependent on multiple steps, molecular labeling, and detailed analysis, causing the result turnaround time to be over hours and days. Rapid diagnostic kits based on lateral flow devices can return results quickly but are only capable of detecting a handful of pathogens or markers. Herein, we present the use of disposable plasmonics with chiroptical nanostructures as a platform for low-cost, label-free optical biosensing with multiplexing and without the need for flow systems often required in current optical biosensors. We showcase the detection of SARS-CoV-2 in complex media as well as an assay for the Norovirus and Zika virus as an early developmental milestone toward high-throughput, single-step diagnostic kits for differential diagnosis of multiple respiratory viruses and any other emerging diagnostic needs. Diagnostics based on this platform, which we term “disposable plasmonics assays,” would be suitable for low-cost screening of multiple pathogens or biomarkers in a near-point-of-care setting. Authors Stephanie Wallace, Martin Kartau, Tarun Kakkar, Chris Davis, Agnieszka Szemiel, Iliyana Samardzhieva, Swetha Vijayakrishnan, Sarah Cole, Giuditta De Lorenzo, Emmanuel Maillart, Kevin Gautier, Adrian J Lapthorn, Arvind H Patel, Nikolaj Gadegaard, Malcolm Kadodwala, Edward Hutchinson, Affar S Karimullah Journal ACS sensors Publication Date 23/08/2023 Consult the publication
Unveiling the Electronic Structure of Pseudotetragonal WO3 Thin Films
Abstract WO3 is a 5d compound that undergoes several structural transitions in its bulk form. Its versatility is well-documented, with a wide range of applications, such as flexopiezoelectricity, electrochromism, gating-induced phase transitions, and its ability to improve the performance of Li-based batteries. The synthesis of WO3 thin films holds promise in stabilizing electronic phases for practical applications. However, despite its potential, the electronic structure of this material remains experimentally unexplored. Furthermore, its thermal instability limits its use in certain technological devices. Here, we employ tensile strain to stabilize WO3 thin films, which we call the pseudotetragonal phase, and investigate its electronic structure using a combination of photoelectron spectroscopy and density functional theory calculations. This study reveals the Fermiology of the system, notably identifying significant energy splittings between different orbital manifolds arising from atomic distortions. These splittings, along with the system’s thermal stability, offer a potential avenue for controlling inter- and intraband scattering for electronic applications. Authors Mazzola F., Hassani H., Amoroso D., Chaluvadi S.K., Fujii J., Polewczyk V., Rajak P., Koegler M. Ciancio R., Partoens B., Rossi G., Vobornik I., Ghosez P. and Orgiani P. Journal Journal of Physical Chemistry Letters Date 08/08/2023 Consult the paper
Antiviral evaluation of new synthetic bioconjugates based on GA-Hecate: a new class of antivirals targeting different steps of Zika Virus replication
Abstract Re-emerging arboviruses represent a serious health problem due to their rapid vector-mediated spread, mainly in urban tropical areas. The 2013–2015 Zika virus (ZIKV) outbreak in South and Central America has been associated with cases of microcephaly in newborns and Guillain–Barret syndrome. We previously showed that the conjugate gallic acid—Hecate (GA-FALALKALKKALKKLKKALKKAL-CONH2)—is an efficient inhibitor of the hepatitis C virus. Here, we show that the Hecate peptide is degraded in human blood serum into three major metabolites. These metabolites conjugated with gallic acid were synthesized and their effect on ZIKV replication in cultured cells was evaluated. The GA-metabolite 5 (GA-FALALKALKKALKKL-COOH) was the most efficient in inhibiting two ZIKV strains of African and Asian lineage at the stage of both virus entry (virucidal and protective) and replication (post-entry). We also demonstrate that GA-metabolite 5 does not affect cell growth after 7 days of continuous treatment. Thus, this study identifies a new synthetic antiviral compound targeting different steps of ZIKV replication in vitro and with the potential for broad reactivity against other flaviviruses. Our work highlights a promising strategy for the development of new antivirals based on peptide metabolism and bioconjugation. Authors Paulo Ricardo da Silva Sanches, Ricardo Sanchez-Velazquez, Mariana Nogueira Batista, Bruno Moreira Carneiro, Cintia Bittar, Giuditta De Lorenzo, Paula Rahal, Arvind H Patel, Eduardo Maffud Cilli Journal Molecules Publication Date 21/06/2023 Consult the publication