A unified framework for Simplicial Kuramoto models

Simplicial Kuramoto models have emerged as a diverse and intriguing class of models describing oscillators on simplices rather than nodes. In this paper, we present a unified framework to describe different variants of these models, categorized into three main groups: "simple" models, "Hodge-coupled" models, and "order-coupled" (Dirac) models. Our framework is based on topology, discrete differential geometry as well as gradient flows and frustrations, and permits a systematic analysis of their properties. We establish an equivalence between the simple simplicial Kuramoto model and the standard Kuramoto model on pairwise networks under the condition of manifoldness of the simplicial complex. Then, starting from simple models, we describe the notion of simplicial synchronization and derive bounds on the coupling strength necessary or sufficient for achieving it. For some variants, we generalize these results and provide new ones, such as the controllability of equilibrium solutions. Finally, we explore a potential application in the reconstruction of brain functional connectivity from structural connectomes and find that simple edge-based Kuramoto models perform competitively or even outperform complex extensions of node-based models.Comment: 36 pages, 11 figure

Structure-Based Design and Optimization of Multitarget-Directed 2H-Chromen-2-one Derivatives as Potent Inhibitors of Monoamine Oxidase B and Cholinesterases

The multifactorial nature of Alzheimer’s disease calls for the development of multitarget agents addressing key pathogenic processes. To this end, by following a docking-assisted hybridization strategy, a number of aminocoumarins were designed, prepared, and tested as monoamine oxidases (MAOs) and acetyl- and butyryl-cholinesterase (AChE and BChE) inhibitors. Highly flexible N-benzyl-N-alkyloxy coumarins 2–12 showed good inhibitory activities at MAO-B, AChE, and BChE but low selectivity. More rigid inhibitors, bearing meta- and para-xylyl linkers, displayed good inhibitory activities and high MAO-B selectivity. Compounds 21, 24, 37, and 39, the last two featuring an improved hydrophilic/lipophilic balance, exhibited excellent activity profiles with nanomolar inhibitory potency toward hMAO-B, high hMAO-B over hMAO-A selectivity and submicromolar potency at hAChE. Cell-based assays of BBB permeation, neurotoxicity, and neuroprotection supported the potential of compound 37 as a BBB-permeant neuroprotective agent against H2O2-induced oxidative stress with poor interaction as P-gp substrate and very low cytotoxicity

Network-based kinetic models: Emergence of a statistical description of the graph topology

In this paper, we propose a novel approach that employs kinetic equations to describe the collective dynamics emerging from graph-mediated pairwise interactions in multi-agent systems. We formally show that for large graphs and specific classes of interactions a statistical description of the graph topology, given in terms of the degree distribution embedded in a Boltzmann-type kinetic equation, is sufficient to capture the collective trends of networked interacting systems. This proves the validity of a commonly accepted heuristic assumption in statistically structured graph models, namely that the so-called connectivity of the agents is the only relevant parameter to be retained in a statistical description of the graph topology. Then, we validate our results by testing them numerically against real social network data

Prediction of retention time in reversed-phase liquid chromatography as a tool for steroid identification

The untargeted profiling of steroids constitutes a growing research field because of their importance as biomarkers of endocrine disruption. New technologies in analytical chemistry, such as ultra highpressure liquid chromatography coupled with mass spectrometry (MS), offer the possibility of a fast and sensitive analysis. Nevertheless, difficulties regarding steroid identification are encountered when considering isotopomeric steroids. Thus, the use of retention times is of great help for the unambiguous identification of steroids. In this context, starting from the linear solvent strength (LSS) theory, quantitative structure retention relationship (QSRR) models, based on a dataset composed of 91 endogenous steroids and VolSurf þ descriptors combined with a new dedicated molecular fingerprint, were developed to predict retention times of steroid structures in any gradient mode conditions. Satisfactory performance was obtained during nested cross-validation with a predictive ability (Q2) of 0.92. The generalisation ability of the model was further confirmed by an average error of 4.4% in external prediction. This allowed the list of candidates associated with identical monoisotopic masses to be strongly reduced, facilitating definitive steroid identification

Computational Studies on Sirtuins from Trypanosoma cruzi: Structures, Conformations and Interactions with Phytochemicals

The silent-information regulator 2 proteins, otherwise called sirtuins, are currently considered as emerging anti-parasitic targets. Nicotinamide, a pan-sirtuin inhibitor, is known to cause kinetoplast alterations and the arrested growth of T. cruzi, the protozoan responsible for Chagas disease. These observations suggested that sirtuins from this parasite (TcSir2rp1 and TcSir2rp3) could play an important role in the regulation of the parasitic cell cycle. Thus, their inhibition could be exploited for the development of novel anti-trypanosomal compounds

Synthesis of a selective HDAC6 inhibitor active in neuroblasts

In recent years, the role of HDAC6 in neurodegeneration has been partially elucidated, which led some authors to propose HDAC6 inhibitors as a therapeutic strategy to treat neurodegenerative diseases. In an effort to develop a selective HDAC6 inhibitor which can cross the blood brain barrier (BBB), a modified hydroxamate derivative (compound 3) was designed and synthetized. This compound was predicted to have potential for BBB penetration based on in silico and in vitro evaluation of passive permeability. When tested for its HDAC inhibitory activity, the IC50 value of compound 3 towards HDAC6 was in the nM range in both enzymatic and cell-based assays. Compound 3 showed a cell-based selectivity profile close to that of tubastatin A in SH-SY5Y human neuroblastoma cells, and a good BBB permeability profile

Poultry biodiversity for alternative farming systems development

Poultry biodiversity represents a key factor to improve poultry resilience and promote sustainable and low input farming systems. The EU and member states promote protection of livestock biodiversity and the development of alternative farming through funding projects such as “Local Chicken Breeds in Alternative Production Chain: Welfare, Quality and Sustainability” (funded by the Italian Ministry of Research and University). The aim of the present research was to identify among five different poultry genotypes Bionda Piemontese (BP), Robusta Maculata (RM), RM x Sasso (RMxS), BP x Sasso (BPxS) and a commercial hybrid (Ross 308) the best suitable breed in terms of productivity and welfare for alternative housing system. A total of 300 (60 x genotype), 21 days old male birds were randomly allotted in two housing systems: 1) standard intensive farming (controlled environment, 33 kg/m2 and standard diet) and 2) free-range (“natural” environmental conditions, 21 kg/m2, access to outdoor area and low-input diet). Slaughtering was performed at 81 days of age. During the trial, the productive performance and behaviour of the animals were evaluated. The housing system, the genotype and their interaction significantly affected many of the studied variables, showing broiler not the ideal genotype for extensive farming system, which is more suited for low/medium performance strains