Objective The immune response arises from a fne balance of mechanisms that provide for surveillance, tolerance, and elimination of dangers. Sulfavant A (SULF A) is a sulfolipid with a promising adjuvant activity. Here we studied the mechanismof action of SULF A and addressed the identifcation of its molecular target in human dendritic cells (hDCs).Methods Adjuvant efect and immunological response to SULF A were assessed on DCs derived from human donors. Inaddition to testing various reporter cells, target identifcation and downstream signalling was supported by a reverse pharmacology approach based on antibody blocking and gene silencing, crosstalk with TLR pathways, use of human allogeneicmixed lymphocyte reaction.Results SULF A binds to the Triggering Receptor Expressed on Myeloid cells-2 (TREM2) and initiates an unconventionalmaturation of hDCs leading to enhanced migration activity and up-regulation of MHC and co-stimulatory molecules without release of conventional cytokines. This response involves the SYK-NFAT axis and is compromised by blockade orgene silencing of TREM2. Activation by SULF A preserved the DC functions to excite the allogeneic T cell response, andincreased interleukin-10 release after lipopolysaccharide stimulation.Conclusion SULF A is the frst synthetic small molecule that binds to TREM2. The receptor engagement drives diferentiation of an unprecedented DC phenotype (homeDCs) that contributes to immune homeostasis without compromising lymphocyte activation and immunogenic response. This mechanism fully supports the adjuvant and immunoregulatory activityof SULF A. We also propose that the biological p

Summary: ADViSELipidomics is a novel Shiny app for preprocessing, analyzing and visualizing lipidomics data. Ithandles the outputs from LipidSearch and LIQUID for lipid identification and quantification and the data fromthe Metabolomics Workbench. ADViSELipidomics extracts information by parsing lipid species (using LIPID MAPSclassification) and, together with information available on the samples, performs several exploratory and statisticalanalyses. When the experiment includes internal lipid standards, ADViSELipidomics can normalize the data matrix,providing normalized concentration values per lipids and samples. Moreover, it identifies differentially abundantlipids in simple and complex experimental designs, dealing with batch effect correction. Finally, ADViSELipidomicshas a user-friendly graphical user interface and supports an extensive series of interactive graphics.

The molecular programs involved in regulatory T (Treg) cell activation and homeostasis remain incompletely understood. Here, we show that T cell receptor (TCR) signaling in Treg cells induces the nuclear translocation of serine/threonine kinase 4 (Stk4), leading to the formation of an Stk4-NF-?B p65-Foxp3 complex that regulates Foxp3- and p65-dependent transcriptional programs. This complex was stabilized by Stk4-dependent phosphorylation of Foxp3 on serine-418. Stk4 deficiency in Treg cells, either alone or in combination with its homolog Stk3, precipitated a fatal autoimmune lymphoproliferative disease in mice characterized by decreased Treg cell p65 expression and nuclear translocation, impaired NF-?B p65-Foxp3 complex formation, and defective Treg cell activation. In an adoptive immunotherapy model, overexpression of p65 or the phosphomimetic Foxp3S418E in Stk3/4-deficient Treg cells ameliorated their immune regulatory defects. Our studies identify Stk4 as an essential TCR-responsive regulator of p65-Foxp3-dependent transcription that promotes Treg cell-mediated immune tolerance.

The dynamic behavior of a self-propelled semiflexible filament of length L is con- sidered under the action of a linear shear flow. The system is studied by using Brownian multi-particle collision dynamics. The system can be characterized in terms of the persistence length Lp of the chain, of the Peclet number, and of the Weissenberg number. The quantity Lp/L measures the bending rigidity of the polymer, the Peclet number Pe is the ratio of active force times L to thermal energy, and the Weissenberg number Wi characterizes the flow strength over thermal effects. In this presentation we will focus our attention to intermediate values of Pe corresponding to the weak spiral regime when no external flow is applied. The numerical results allow us to outline the main features of the physics underlying the considered system: o At low values of Wi, polymer is stretched by activity and aligned by shear along the flow direction. This effect is more marked in the case of more flexible chains. o At the intermediate values of Wi, polymer is prone to tumble due to shear and this promotes a contraction of the chain. o At very high values of Wi, activity sums up to shear enhancing polymer stretching and deformation.

The possibility to computationally prioritize candi- date disease genes capitalizing on existing information has led to a speedup in the discovery of new methods. Many gene discovery techniques exploit network data, like protein-protein interactions (PPIs), in order to extract knowledge from the network structure relying on several network metrics. We here present PROCONSUL, a method that builds on top of the concept of connectivity significance (CS) and exploits the idea of probabilistic exploration of the space of putative disease genes. We show that our methodology is able to outperform the state-of- the-art tool based on CS in several settings, and propose different, effective gene discovery strategies according to specific disease network properties.

The importance of faster drug development has never been more evident than in present time when the whole world is struggling to cope up with the COVID-19 pandemic. At times when timely development of effective drugs and treatment plans could potentially save millions of lives, drug repurposing is one area of medicine that has garnered much of research interest. Apart from experimental drug repurposing studies that happen within wet labs, lot many new quantitative methods have been proposed in the literature. In this paper, one such quantitative methods for drug repurposing is implemented and evaluated. DruSiLa (DRUg in-SIlico LAboratory) is an in-silico drug re- purposing method that leverages disease similarity measures to quantitatively rank existing drugs for their potential therapeutic efficacy against novel diseases. The proposed method makes use of available, manually curated, and open datasets on diseases, their genetic origins, and disease-related patho-phenotypes. DruSiLa evaluates pairwise disease similarity scores of any given target disease to each known disease in our dataset. Such similarity scores are then propagated through disease-drug associations, and aggregated at drug nodes to rank them for their predicted effectiveness against the target disease.

A classical Lotka-Volterra model with the logistical growth of prey-and-hunting coopera-tion in the functional response of predators to prey was extended by introducing advection terms,which included the velocities of animals. The effect of velocity on the kinetics of the problem wasanalyzed. In order to examine the band behavior of species over time, traveling wave solutions wereintroduced, and conditions for the coexistence of both populations and/or extinction were found.Numerical simulations illustrating the obtained results were performe

The dynamic behavior of a self-propelled semiflexible filament of length L is considered under the action of an external unbounded shear flow. The system is studied by using Brownian multi-particle collision dynamics. The system can be characterized in terms of the persistence length Lp of the chain, of the Peclet number, and of the Weissenberg number. The quantity Lp/L measures the bending rigidity of the polymer, the Peclet number Pe is the ratio of active force to thermal energy, and the Weissenberg number Wi characterizes the flow strength over thermal effects. In this presentation we will focus our attention to intermediate values of Pe corresponding to the weak spiral regime when no external flow is applied. The numerical results allow us to outline the main features of the physics underlying the considered system: o At low values of Wi, polymers are stretched by activity and aligned by shear along the flow direction. This effect is more marked in the case of more flexible chains. o At the intermediate values of Wi, polymers are prone to tumble due to shear and this promotes a contraction of the chain. o At very high values of Wi, activity sums up to shear enhancing polymer stretching and deformation.

In this paper we devise a microscopic (agent-based) mathematical model for reproducing crowd behavior in a specific scenario: a number of pedestrians, consisting of numerous social groups, flow along a corridor until a gate located at the end of the corridor closes. People are not informed about the closure of the gate and perceive the blockage observing dynamically the local crowd conditions. Once people become aware of the new conditions, they stop and then decide either to stay, waiting for reopening, or to go back and leave the corridor forever. People going back hit against newly incoming people creating a dangerous counter-flow. We run several numerical simulations varying parameters which control the crowd behavior, in order to understand the factors which have the greatest impact on the system dynamics. We also study the optimal way to inform people about the blockage in order to prevent the counter-flow. We conclude with some useful suggestions directed to the organizers of mass events.

In this paper, we describe some work aimed at upgrading the Alya code with up-to-date parallel linear solvers capable of achieving reliability, efficiency, and scalability in the computation of the pressure field at each time step of the numerical procedure for solving an LES formulation of the incompressible Navier-Stokes equations. We developed a software module in Alya's kernel to interface the libraries included in the current version of PSCToolkit, a framework for the iterative solution of sparse linear systems on parallel distributed-memory computers by Krylov methods coupled to Algebraic MultiGrid preconditioners. The Toolkit has undergone some extensions within the EoCoE-II project with the primary goal to face the exascale challenge. Results on a realistic benchmark for airflow simulations in wind farm applications show that the PSCToolkit solvers significantly outperform the original versions of the Conjugate Gradient method available in the Alya kernel in terms of scalability and parallel efficiency and represent a very promising software layer to move the Alya code towards exascale.

Models of networks play a major role in explaining and reproducing empirically observed patterns. Suitable models can be used to randomize an observed network while preserving some of its features, or to generate synthetic graphs whose properties may be tuned upon the characteristics of a given population. In the present paper, we introduce the Fitness-Corrected Block Model, an adjustable-density variation of the well-known Degree-Corrected Block Model, and we show that the proposed construction yields a maximum entropy model. When the network is sparse, we derive an analytical expression for the degree distribution of the model that depends on just the constraints and the chosen fitness-distribution. Our model is perfectly suited to define maximum-entropy data-driven spatial social networks, where each block identifies vertices having similar position (e.g., residence) and age, and where the expected block-to-block adjacency matrix can be inferred from the available data. In this case, the sparse-regime approximation coincides with a phenomenological model where the probability of a link binding two individuals is directly proportional to their sociability and to the typical cohesion of their age-groups, whereas it decays as an inverse-power of their geographic distance. We support our analytical findings through simulations of a stylized urban area.

In the context of hyperbolic systems of balance laws, the Shizuta-Kawashima coupling condition guarantees that all the variables of the system are dissipative even though the system is not totally dissipative. Hence it plays a crucial role in terms of sufficient conditions for the global in time existence of classical solutions. However, it is easy to find physically based models that do not satisfy this condition, especially in several space dimensions. In this paper, we consider two simple examples of partially dissipative hyperbolic systems violating the Shizuta-Kawashima condition (SK) in 3D, such that some eigendirections do not exhibit dissipation at all. We prove that if the source term is nonresonant (in a suitable sense) in the direction where dissipation does not play any role, then the formation of singularities is prevented, despite the lack of dissipation, and the smooth solutions exist globally in time. The main idea of the proof is to couple Green function estimates for weakly dissipative hyperbolic systems with the space-time resonance analysis for dispersive equations introduced by Germain, Masmoudi and Shatah. More precisely, the partially dissipative hyperbolic systems violating (SK) are endowed, in the nondissipative directions, with a special structure of the nonlinearity, the so-called nonresonant bilinear form for the wave equation (see Pusateri and Shatah, CPAM 2013).

A necessary and sucient condition for fractional Orlicz-Sobolev spaces to be continuously embedded into L1(Rn) is exhibited. Under the same assumption, any function from the relevant fractional-order spaces is shown to be continuous. Improvements of this result are also oered. They provide the optimal Orlicz target space, and the optimal rearrangement-invariant target space in the embedding in question. These results complement those already available in the subcritical case, where the embedding into L1(Rn) fails. They also augment a classical embedding theorem for standard fractional Sobolev spaces.

An optimal embedding theorem for fractional Orlicz-Sobolev spaces into Orlicz spaces will be surveyed. A new embedding for the same fractional spaces into generalized Campanato spaces will be also presented. This is a joint work, in progress, with Andrea Cianchi, Lubos Pick and Lenka Slavikova.

The optimal Orlicz target space and the optimal rearrangement- invariant target space are exhibited for embeddings of fractional-order Orlicz-Sobolev spaces. Both the subcritical and the supercritical regimes are considered. In particular, in the latter case the relevant Orlicz-Sobolev spaces are shown to be embedded into the space of bounded continuous functions in R^n. This is a joint work with Andrea Cianchi, Lubos Pick and Lenka Slavikova.

Digitization offers great opportunities as well as new challenges. Indeed, these opportunities entail increased cyber risks, both from deliberate cyberattacks and from incidents caused by inadvertent human error. Cyber risk must be mastered, and to this aim, its quantification is an urgent challenge. There is a lot of interest in this topic from the insurance community in order to price adequate coverage to their customers. A key first step is to investigate the frequency and severity of cyber incidents. On the grounds that data breaches seem to be the main cause of cyber incidents, the aim of this paper is to give further insights about the frequency and severity statistical distributions of malicious and negligent data breaches. For this purpose, we refer to a publicly available dataset: the Chronology of Data Breaches provided by the Privacy Rights Clearinghouse.

It has been observed in different kinds of networks, such as social or biological ones, a typical behavior inspired by the general principle 'similarity breeds connections'. These networks are defined as homophilic as nodes belonging to the same class preferentially interact with each other. In this work, we present HONTO (HOmophily Network TOol), a user-friendly open-source Python3 package designed to evaluate and analyze homophily in complex networks. The tool takes in input from the network along with a partition of its nodes into classes and yields a matrix whose entries are the homophily/heterophily z-score values. To complement the analysis, the tool also provides z-score values of nodes that do not interact with any other node of the same class. Homophily/heterophily z-scores values are presented as a heatmap allowing a visual at-a-glance interpretation of results.

Most financial signals show time dependency that, combined with noisy and extreme events, poses serious problems in the parameter estimations of statistical models. Moreover, when addressing asset pricing, portfolio selection, and investment strategies, accurate estimates of the relationship among assets are as necessary as are delicate in a time-dependent context. In this regard, fundamental tools that increasingly attract research interests are precision matrix and graphical models, which are able to obtain insights into the joint evolution of financial quantities. In this paper, we present a robust divergence estimator for a time-varying precision matrix that can manage both the extreme events and time-dependency that affect financial time series. Furthermore, we provide an algorithm to handle parameter estimations that uses the "maximization-minimization" approach. We apply the methodology to synthetic data to test its performances. Then, we consider the cryptocurrency market as a real data application, given its remarkable suitability for the proposed method because of its volatile and unregulated nature.

The SARS-CoV-2 non-structural protein 13 (nsp13) helicase is an essential enzyme for viral replication and has been identified as an attractive target for the development of new antiviral drugs. In detail, the helicase catalyzes the unwinding of double-stranded DNA or RNA in a 5? to 3? direction and acts in concert with the replication-transcription complex (nsp7/nsp8/nsp12). In this work, bioinformatics and computational tools allowed us to perform a detailed conservation analysis of the SARS-CoV-2 helicase genome and to further predict the druggable enzyme's binding pockets. Thus, a structure-based virtual screening was used to identify valuable compounds that are capable of recognizing multiple nsp13 pockets. Starting from a database of around 4000 drugs already approved by the Food and Drug Administration (FDA), we chose 14 shared compounds capable of recognizing three out of four sites. Finally, by means of visual inspection analysis and based on their commercial availability, five promising compounds were submitted to in vitro assays. Among them, PF-03715455 was able to block both the unwinding and NTPase activities of nsp13 in a micromolar range.

Tra novembre 2020 e giugno 2021, l'Istituto per le Applicazioni del Calcolo "Mauro Picone" (IAC) ha realizzato un ciclo di seminari dedicati al rapporto tra Intelligenza Artificiale e Matematica, denominato AIM - Artificial Intelligence and Mathematics - Fundamentlas and beyond. Nel presente lavoro si cercherà di sistematizzare i diversi contributi emersi durante il ciclo di seminari, realizzando una mappa concettuale che, a partire dalle collaborazioni già in essere e attraverso un'analisi ontologica delle parole chiave di ciascun seminario, evidenzi le possibili aree di contatto tra le diverse attività di ricerca presentate e le aree potenzialmente non ancora coperte. Ciò permetterà non solo di programmare un secondo ciclo di seminari, ma fornirà un utile spunto di riflessione per i ricercatori su future sinergie potenzialmente realizzabili.Inoltre, a partire dall'analisi dei dati di insight delle dirette streaming dal canale YouTube dell'IAC, incrociati con i dati degli Analytics dei canali social su cui è stata data rilevanza ai diversi appuntamenti del ciclo di seminari, si cercherà di trarre alcune conclusioni sulle possibilità di disseminazione di iniziative a carattere scientifico attraverso i social network, evidenziandone vantaggi e limiti. Infine, si promuoverà una riflessione sul possibile uso futuro di piattaforme online per le attività seminariali, anche quando l'emergenza pandemica sarà finalmente totalmente superata.