Scientific Publications
Evaluation of an engineered zika virus-like particle vaccine candidate in a mosquito-mouse transmission model
Abstract The primary route of Zika virus (ZIKV) transmission is through the bite of an infected Aedes mosquito, when it probes the skin of a vertebrate host during a blood meal. Viral particles are injected into the bite site together with mosquito saliva and a complex mixture of other components. Some of them are known to play a key role in the augmentation of the arbovirus infection in the host, with increased viremia and/or morbidity. This vector-derived contribution to the infection is not usually considered when vaccine candidates are tested in preclinical animal models. In this study, we performed a preclinical validation of a promising ZIKV vaccine candidate in a mosquito-mouse transmission model using both Asian and African ZIKV lineages. Mice were immunized with engineered ZIKV virus-like particles and subsequently infected through the bite of ZIKV-infected Aedes aegypti mosquitoes. Despite a mild increase in viremia in mosquito-infected mice compared to those infected through traditional needle injection, the vaccine protected the animals from developing the disease and strongly reduced viremia. In addition, during peak viremia, naive mosquitoes were allowed to feed on infected vaccinated and nonvaccinated mice. Our analysis of viral titers in mosquitos showed that the vaccine was able to inhibit virus transmission from the host to the vector. Authors Maria Vittoria Mancini, Rapeepat Tandavanitj, Thomas H Ant, Shivan M Murdochy, Daniel D Gingell, Chayanee Setthapramote, Piyatida Natsrita, Alain Kohl, Steven P Sinkins, Arvind H Patel, Giuditta De Lorenzo Journal Msphere Publication Date 20/04/2023 Consult the publication
The Interaction of Amines with Gold Nanoparticles
Abstract Here, we present an integrated ultra-high-vacuum (UHV) apparatus for the growth of complex materials and heterostructures. The specific growth technique is the Pulsed Laser Deposition (PLD) by means of a dual-laser source based on an excimer KrF ultraviolet and solid-state Nd:YAG infra-red lasers. By taking advantage of the two laser sources—both lasers can be independently used within the deposition chambers—a large number of different materials—ranging from oxides to metals, to selenides, and others—can be successfully grown in the form of thin films and heterostructures. All of the samples can be in situ transferred between the deposition chambers and the analysis chambers by using vessels and holders’ manipulators. The apparatus also offers the possibility to transfer samples to remote instrumentation under UHV conditions by means of commercially available UHV-suitcases. The dual-PLD operates for in-house research as well as user facility in combination with the Advanced Photo-electric Effect beamline at the Elettra synchrotron radiation facility in Trieste and allows synchrotron-based photo-emission as well as x-ray absorption experiments on pristine films and heterostructures. Authors Yanchao Lyu, Lucia Morillas Becerril, Mirko Vanzan, Stefano Corni, Mattia Cattelan, Gaetano Granozzi, Marco Frasconi, Piu Rajak, Pritam Banerjee, Fabrizio Mancin, Paolo Scrimin Journal Advanced Materials Date 23/03/2023 Consult the paper
Evidence of silicide at the Ni/ β-Si3N4(0001)/Si(111) interface
Abstract We present a study of a sub-nanometre interlayer of crystalline silicon nitride at the Ni/Si interface. We performed transmission electron microscopy measurements complemented by energy dispersive X-ray analysis to investigate to what extent the nitride layer act as a barrier against atom diffusion. The results show that discontinuous silicide areas can form just below the nitride layer, whose composition is compatible with that of the nickel disilicide. The Ni–Si reaction is tentatively attributed to the thermal strain suffered by the interface during the deposition of Ni at low temperature. Authors Piu Rajak, Regina Ciancio, Antonio Caretta, Simone Laterza, Richa Bhardwaj, Matteo Jugovac, Marco Malvestuto, Paolo Moras, Roberto Flammini Journal Applied Surface Science Date 13/03/2023 Consult the paper
Nd:YAG infrared laser as a viable alternative to excimer laser: YBCO case study
Abstract We report on the growth and characterization of epitaxial YBa2Cu3O7−δ (YBCO) complex oxide thin films and related heterostructures exclusively by Pulsed Laser Deposition (PLD) and using first harmonic Nd:Y3Al5O12 (Nd:YAG) pulsed laser source (λ = 1064 nm). High-quality epitaxial YBCO thin film heterostructures display superconducting properties with transition temperature ∼ 80 K. Compared with the excimer lasers, when using Nd:YAG lasers, the optimal growth conditions are achieved at a large target-to-substrate distance d. These results clearly demonstrate the potential use of the first harmonic Nd:YAG laser source as an alternative to the excimer lasers for the PLD thin film community. Its compactness as well as the absence of any safety issues related to poisonous gas represent a major breakthrough in the deposition of complex multi-element compounds in form of thin films. Authors Sandeep Kumar Chaluvadi, Shyni Punathum Chalil, Federico Mazzola, Simone Dolabella, Piu Rajak, Marcello Ferrara, Regina Ciancio, Jun Fujii, Giancarlo Panaccione, Giorgio Rossi & Pasquale Orgiani Journal Scientific Reports Date 08/03/2023 Consult the paper
Dual pulsed laser deposition system for the growth of complex materials and heterostructures
Abstract Here, we present an integrated ultra-high-vacuum (UHV) apparatus for the growth of complex materials and heterostructures. The specific growth technique is the Pulsed Laser Deposition (PLD) by means of a dual-laser source based on an excimer KrF ultraviolet and solid-state Nd:YAG infra-red lasers. By taking advantage of the two laser sources—both lasers can be independently used within the deposition chambers—a large number of different materials—ranging from oxides to metals, to selenides, and others—can be successfully grown in the form of thin films and heterostructures. All of the samples can be in situ transferred between the deposition chambers and the analysis chambers by using vessels and holders’ manipulators. The apparatus also offers the possibility to transfer samples to remote instrumentation under UHV conditions by means of commercially available UHV-suitcases. The dual-PLD operates for in-house research as well as user facility in combination with the Advanced Photo-electric Effect beamline at the Elettra synchrotron radiation facility in Trieste and allows synchrotron-based photo-emission as well as x-ray absorption experiments on pristine films and heterostructures. Authors Orgiani P.; Chaluvadi S.K.; Chalil, S. Punathum; Mazzola F.; Jana A.; Dolabella S.; Rajak P.; Ferrara M.; Benedetti D.; Fondacaro A.; Salvador F.; Ciancio R.; Fujii J.; Panaccione G.; Vobornik I.; Rossi G. Journal Review of Scientific Instruments Date 06/03/2023 Consult the paper
An Unsupervised Machine Learning Method Stratifies Chronic Lymphocytic Leukemia Patients in Novel Categories with Different Risk of Early Treatment
Abstract: Novel scoring systems have been developed in recent years to improve the accuracy of prognostication from historical clinical staging systems (Rai, Binet) for chronic lymphocytic leukemia (CLL). Most of them, however, rely on discretized and dichotomic values of the various biomarkers to infer prognosis. Here we analyzed the immunophenotypic and (immuno)genetic profiles in a wide CLL cohort by applying unsupervised machine learning methods elaborating prognostic factors as continuous variables, to identify novel relationships and interactions likely missed in conventional models. Authors Francesca Cuturello, Federico Pozzo, Edith Natalia Villegas Garcia, Francesca Maria Rossi, Massimo Degan, Paola Nanni, Ilaria Cattarossi, Eva Zaina, Paola Varaschin, Alessandra Braida, Michele Berton, Laura Zannier, Filippo Vit, Erika Tissino, Tamara Bittolo, Roberta Laureana, Giovanni D’Arena, Luca Laurenti, Agostino Tafuri, Jacopo Olivieri, Francesco Zaja, Annalisa Chiarenza, Maria Ilaria Del Principe, Riccardo Bomben, Antonella Zucchetto, Stefano Cozzini, Alessio Ansuini, Alberto Cazzaniga, Valter Gattei Journal Blood Publication date 15/11/2022 Consult the pubblication
Adversarial Attacks on Protein Language Models
Abstract: Deep Learning models for protein structure prediction, such as AlphaFold2, leverage Transformer architectures and their attention mechanism to capture structural and functional properties of amino acid sequences. Despite the high accuracy of predictions, biologically insignificant perturbations of the input sequences, or even single point mutations, can lead to substantially different 3d structures. On the other hand, protein language models are often insensitive to biologically relevant mutations that induce misfolding or dysfunction (e.g. missense mutations). Precisely, predictions of the 3d coordinates do not reveal the structure-disruptive effect of these mutations. Therefore, there is an evident inconsistency between the biological importance of mutations and the resulting change in structural prediction. Inspired by this problem, we introduce the concept of adversarial perturbation of protein sequences in continuous embedding spaces of protein language models. Our method relies on attention scores to detect the most vulnerable amino acid positions in the input sequences. Adversarial mutations are biologically diverse from their references and are able to significantly alter the resulting 3d structures. Authors Ginevra Carbone, Francesca Cuturello, Luca Bortolussi, Alberto Cazzaniga Journal Machine Learning for Structural Biology Workshop, NeurIPS 2022. Publication date 25/10/2022 Consult the pubblication
DPCfam: unsupervised protein family classification by Density Peak Clustering of large sequence datasets
Abstract: As the UniProt database approaches the 200 million entries’ mark, the vast majority of proteins it contains lack any experimental validation of their functions. In this context, the identification of homologous relationships between proteins remains the single most widely applicable tool for generating functional and structural hypotheses in silico. Although many databases exist that classify proteins and protein domains into homologous families, large sections of the sequence space remain unassigned. Authors Elena Tea Russo, Federico Barone, Alex Bateman, Stefano Cozzini, Marco Punta, Alessandro Laio Journal PLOS Computational Biology Publication date 19/10/2022 Consult the pubblication
Higher rank motivic Donaldson–Thomas invariants of 𝔸3 via wall-crossing, and asymptotics
Abstract We compute, via motivic wall-crossing, the generating function of virtual motives of the Quot scheme of points on 𝔸3, generalising to higher rank a result of Behrend–Bryan–Szendrői. We show that this motivic partition function converges to a Gaussian distribution, extending a result of Morrison. Authors Alberto Cazzaniga, Dimbinaina Ralaivaosaona, Andrea T. Ricolfi Journal Mathematical Proceedings Publication Date 05/05/2022 Consult the publication
Framed motivic Donaldson–Thomas invariants of small crepant resolutions
Abstract For an arbitrary integer 𝑟 ≥1, we compute r-framed motivic DT and PT invariants of small crepant resolutions of toric Calabi–Yau 3-folds, establishing a “higher rank” version of the motivic DT/PT wall-crossing formula. This generalises the work of Morrison and Nagao. Our formulae, in particular their relationship with the 𝑟 =1 theory, fit nicely in the current development of higher rank refined DT invariants. Authors Alberto Cazzaniga, Andrea T. Ricolfi Journal Mathematische Nachrichten Publication Date 12/04/2022 Consult the publication
Deep artificial neural network for prediction of atrial fibrillation through the analysis of 12‐leads standard ECG
Abstract Atrial Fibrillation (AF) is a heart’s arrhythmia which, despite being often asymptomatic, represents an important risk factor for stroke, therefore being able to predict AF at the electrocardiogram exam, would be of great impact on actively targeting patients at high risk. In the present work we use Convolution Neural Networks to analyze ECG and predict Atrial Fibrillation starting from realistic datasets, i.e. considering fewer ECG than other studies and extending the maximal distance between ECG and AF diagnosis. We achieved 75.5% (0.75) AUC firstly increasing our dataset size by a shifting technique and secondarily using the dilation parameter of the convolution neural network. In addition we find that, contrarily to what is commonly used by clinicians reporting AF at the exam, the most informative leads for the task of predicting AF are D1 and avR. Similarly, we find that the most important frequencies to check are in the range of 5-20 Hz. Finally, we develop a net able to manage at the same time the electrocardiographic signal together with the electronic health record, showing that integration between different sources of data is a profitable path. In fact, the 2.8% gain of such net brings us to a 78.6% (std 0.77) AUC. In future works we will deepen both the integration of sources and the reason why we claim avR is the most informative lead. Authors A. Scagnetto, G. Barbati, I. Gandin, C. Cappelletto, G. Baj, A. Cazzaniga, F. Cuturello, A. Ansuini, L. Bortolussi, A. Di Lenarda Journal Arxiv Preprint Publication Date 14/01/2022 Consult the publication
Framed sheaves on projective space and Quot schemes
Abstract: We prove that, given integers m≥3, r≥1 and n≥0, the moduli space of torsion free sheaves on Pm with Chern character (r,0,…,0,−n) that are trivial along a hyperplane D⊂Pm is isomorphic to the Quot scheme QuotAm(O⊕r,n) of 0-dimensional length n quotients of the free sheaf O⊕r on Am. The proof goes by comparing the two tangent-obstruction theories on these moduli s Authors Alberto Cazzaniga, Andrea T. Ricolfi Journal Mathematische Zeitschrift Publication date 28/06/2021 Consult the pubblication