What can we learn from atomistic simulations of bioactive glasses?

In the last decades, most experimental efforts have been devoted to design bioactive glasses (please consult the Editor’s note in order to clarify the usage of the terms bioglass, bioactive glass and biocompatible glasses) with enhanced biological and mechanical properties by adding specific ions to known bioactive compositions. Concurrently, computational research has been focused to the understanding of the relationships between bioactivity and composition by rationalization of the role of the doping ions. Thus, a deep knowledge of the structural organization of the constituent atoms of the bioactive glasses has been gained by the employment of ab initio and classical molecular dynamics simulations techniques. This chapter reviews the recent successes in this field by presenting, in a concise way, the structure–properties relationships of silicate, phospho-silicate and phosphate glasses with potential bioactive properties

Personalized Treatment Selection via Product Partition Models with Covariates

Precision medicine is an approach for disease treatment that defines treatment strategies based on the individual characteristics of the patients. Motivated by an open problem in cancer genomics, we develop a novel model that flexibly clusters patients with similar predictive characteristics and similar treatment responses; this approach identifies, via predictive inference, which one among a set of treatments is better suited for a new patient. The proposed method is fully model-based, avoiding uncertainty underestimation attained when treatment assignment is performed by adopting heuristic clustering procedures, and belongs to the class of product partition models with covariates, here extended to include the cohesion induced by the Normalized Generalized Gamma process. The method performs particularly well in scenarios characterized by considerable heterogeneity of the predictive covariates in simulation studies. A cancer genomics case study illustrates the potential benefits in terms of treatment response yielded by the proposed approach. Finally, being model-based, the approach allows estimating clusters' specific response probabilities and then identifying patients more likely to benefit from personalized treatment.Comment: 31 pages, 7 figure

Multiscale Molecular Dynamics Simulation of Multiple Protein Adsorption on Gold Nanoparticles

A multiscale molecular dynamics simulation study has been carried out in order to provide in-depth information on the adsorption of hemoglobin, myoglobin, and trypsin over citrate-capped AuNPs of 15 nm diameter. In particular, determinants for single proteins adsorption and simultaneous adsorption of the three types of proteins considered have been studied by Coarse-Grained and Meso-Scale molecular simulations, respectively. The results, discussed in the light of the controversial experimental data reported in the current experimental literature, have provided a detailed description of the (i) recognition process, (ii) number of proteins involved in the early stages of corona formation, (iii) protein competition for AuNP adsorption, (iv) interaction modalities between AuNP and protein binding sites, and (v) protein structural preservation and alteration

Nonlinear static procedures for state-dependent seismic fragility analysis of reinforced concrete buildings

This paper introduces a simplified methodology to develop state-dependent fragility relationships, based on nonlinear static analyses combined with the Cloud Capacity Spectrum Method. Capacity reduction factors for structural members are applied to simulate the attainment of a specific damage state under a mainshock. A cloud-based procedure is adopted to compute fragility analyses. The procedure is illustrated for a case-study building designed for gravity loads only. Results highlight the importance of considering the effect of cumulative damage in the fragility analysis of buildings. The proposed methodology may be used for seismic-risk assessment studies accounting for ground-motion sequences

Energy-based procedures for seismic fragility analysis of mainshock-damaged buildings

In recent decades, significant research efforts have been devoted to developing fragility and vulnerability models for mainshock-damaged buildings, i.e., depending on the attained damage state after a mainshock ground motion (state-dependent fragility/vulnerability relationships). Displacement-based peak quantities, such as the maximum interstory drift ratio, are widely adopted in fragility analysis to define both engineering demands and structural capacities at the global and/or local levels. However, when considering ground-motion sequences, the use of peak quantities may lead to statistical inconsistencies (e.g., fragility curves’ crossings) due to inadequate consideration of damage accumulation. In this context, energy-based engineering demand parameters (EDPs), explicitly accounting for cumulative damage, can help address this issue. This paper provides an overview of recent findings on the development of aftershock-fragility models of mainshock-damaged buildings. Particular focus is given to state-of-the-art frameworks for fragility analyses based on cumulative damage parameters. Moreover, a literature review on damage indices and energy-based concepts and approaches in earthquake engineering is reported to better understand the main advantages of the mostly adopted energy-based parameters, as well as their limitations. Different refinement levels of seismic response analyses to derive fragility relationships of mainshock-damaged buildings are also discussed. Finally, the benefits of adopting energy-based EDPs rather than, or in addition to, peak quantities in state-dependent fragility analyses are demonstrated on a reinforced concrete frame building. Specifically, a refined lumped plasticity modeling approach is adopted, and sequential cloud-based time-history analyses of a Multi-Degree-of-Freedom (MDoF) model are carried out. The results highlight that energy-based approaches for fragility analysis effectively capture damage accumulation during earthquake sequences without inconsistencies in the obtained statistical models. On the other hand, estimating global or local structural capacity in terms of cumulative EDPs is still challenging. Further experimental data are needed to better calibrate the quantification of energy-based damaged states

O2Activation over Ag-Decorated CeO2(111) and TiO2(110) Surfaces: A Theoretical Comparative Investigation

Periodic spin-polarized hybrid density functional theory calculations have been performed to investigate the reactivity of pristine, O-defective, and Ag-decorated CeO2(111) and TiO2(110) surfaces with a small Ag10 cluster toward O2. The adsorption of O2 and its subsequent dissociation have been studied in order to provide a better understanding of the role of the oxide, the metallic nanoparticle, and their interaction in the reactivity of composite metal/metal oxide materials toward O2, as potential catalysts to this reaction. Structural, energetic, electronic, and vibrational properties of all species involved in the different reaction paths considered have been fully characterized. On the stoichiometric surfaces, Ag10 is oxidized and reduces surface Ce4+/Ti4+ ions, while on the O-defective surfaces, the adhesion of silver is promoted only on CeO2 but unfavored on TiO2. On the other hand, on the silver-free supports, O2 strongly adsorbs at vacancies and preferentially reduces to peroxide. When no O vacancies are considered on the Ag10-decorated supports, the net positive charge on Ag10 actually prevents the adsorption and reduction of O2. Instead, when O vacancies are included, two reaction pathways are observed; oxygen molecules can weakly absorb on the silver cluster as a superoxide moiety or strongly adsorb at the vacancy as peroxide. The dissociation of the O-O bond of the peroxide is favored both from the thermodynamic and kinetic points of view in silver-decorated surfaces, in contrast with the silver-free cases. In addition, Ag10/CeO2 shows higher activity toward the O2 adsorption and dissociation than Ag10/TiO2, which can be related both to the higher ionicity and superior electron storage/release ability of ceria with respect to titania, thus leading to the weakening of the O-O bond and providing lower activation barriers for oxygen reduction. These results deepen the current understanding of the reactivity of metal/metal oxide composites toward O2, especially elucidating how the surface stoichiometry affects the charge state of the metal clusters, and hence the reactivity of these interfaces toward O2, with potential important consequences when such composites are considered for catalytic applications

Biasing crystallization in fused silica: An assessment of optimal metadynamics parameters

Metadynamics (MetaD) is a useful technique to study rare events such as crystallization. It has been only recently applied to study nucleation and crystallization in glass-forming liquids such as silicates, but the optimal set of parameters to drive crystallization and obtain converged free energy surfaces is still unexplored. In this work, we systematically investigated the effects of the simulation conditions to efficiently study the thermodynamics and mechanism of crystallization in highly viscous systems. As a prototype system, we used fused silica, which easily crystallizes to β-cristobalite through MetaD simulations, owing to its simple microstructure. We investigated the influence of the height, width, and bias factor used to define the biasing Gaussian potential, as well as the effects of the temperature and system size on the results. Among these parameters, the bias factor and temperature seem to be most effective in sampling the free energy landscape of melt to crystal transition and reaching convergence more quickly. We also demonstrate that the temperature rescaling from T > Tm is a reliable approach to recover free energy surfaces below Tm, provided that the temperature gap is below 600 K and the configurational space has been properly sampled. Finally, albeit a complete crystallization is hard to achieve with large simulation boxes, these can be reliably and effectively exploited to study the first stages of nucleation

Folding mechanisms steer the amyloid fibril formation propensity of highly homologous proteins

Significant advances in the understanding of the molecular determinants of fibrillogenesis can be expected from comparative studies of the aggregation propensities of proteins with highly homologous structures but different folding pathways. Here, we fully characterize, by means of stopped-flow, T-jump, CD and DSC experiments, the unfolding mechanisms of three highly homologous proteins, zinc binding Ros87 and Ml153-149 and zinc-lacking Ml452-151. The results indicate that the three proteins significantly differ in terms of stability and (un)folding mechanisms. Particularly, Ros87 and Ml153-149 appear to be much more stable to guanidine denaturation and are characterized by folding mechanisms including the presence of an intermediate. On the other hand, metal lacking Ml452-151 folds according to a classic two-state model. Successively, we have monitored the capabilities of Ros87, Ml452-151 and Ml153-149 to form amyloid fibrils under native conditions. Particularly, we show, by CD, fluorescence, DLS, TEM and SEM experiments, that after 168 hours, amyloid formation of Ros87 has started, while Ml153-149 has formed only amorphous aggregates and Ml452-151 is still monomeric in solution. This study shows how metal binding can influence protein folding pathways and thereby control conformational accessibility to aggregation-prone states, which in turn changes aggregation kinetics, shedding light on the role of metal ions in the development of protein deposition diseases

Naposomes: a new class of peptide-derivatized, target-selectivemultimodal nanoparticles for imaging and therapeutic applications

Modified supramolecular aggregates for selective delivery of contrast agents and/or drugs are examined with a focus on a new class of peptide-derivatized nanoparticles: naposomes. These nanoparticles are based on the co‑aggregation of two different amphiphilic monomers that give aggregates of different shapes and sizes (micelles, vesicles and liposomes) with diameters ranging between 10 and 300 nm. Structural properties and in vitro and in vivo behaviors are discussed. For the high relaxitivity values (12–19 mM-1s-1) and to detect for the presence of a surface exposed peptide, the new peptide-derived supramolecular aggregates are very promising candidates as targetselective MRI contrast agents. The efficiency of surface-exposed peptides in homing these nanovectors to a specific target introduces promising new opportunities for the development of diagnostic and therapeutic agents with high specificity toward the biological target and reduced toxic side effects on nontarget organs

Computational insights into the binding of monolayer-capped gold nanoparticles onto amyloid-\u3b2 fibrils

Amyloids-\u3b2 (A\u3b2) fibrils are involved in several neurodegenerative diseases. In this study, atomistic molecular dynamics simulations have been used to investigate how monolayer-protected gold nanoparticles interact with A\u3b2(1-40) and A\u3b2(1-42) fibrils. Our results show that small gold nanoparticles bind with the external side of amyloid-\u3b2 fibrils that is involved in the fibrillation process. The binding affinity, studied for both kinds of fibrils as a function of the monolayer composition and the nanoparticle diameter, is modulated by hydrophobic interactions and ligand monolayer conformation. Our findings thus show that monolayer-protected nanoparticles are good candidates to prevent fibril aggregation and secondary nucleation or to deliver drugs to specific fibril regions