Elucidating the Transport of Electrons and Molecules in a Solid Electrolyte Interphase Close to Battery Operation Potentials Using a Four-Electrode-Based Generator-Collector Setup.

In lithium-ion batteries, the solid electrolyte interphase (SEI) passivates the anode against reductive decomposition of the electrolyte but allows for electron transfer reactions between anode and redox shuttle molecules, which are added to the electrolyte as an internal overcharge protection. In order to elucidate the origin of these poorly understood passivation properties of the SEI with regard to different molecules, we used a four-electrode-based generator-collector setup to distinguish between electrolyte reduction current and the redox molecule (ferrocenium ion Fc+) reduction current at an SEI-covered glassy carbon electrode. The experiments were carried out in situ during potentiostatic SEI formation close to battery operation potentials. The measured generator and collector currents were used to calculate passivation factors of the SEI with regard to electrolyte reduction and with regard to Fc+ reduction. These passivation factors show huge differences in their absolute values and in their temporal evolution. By making simple assumptions about molecule transport, electron transport, and charge transfer reaction rates in the SEI, distinct passivation mechanisms are identified, strong indication is found for a transition during SEI growth from redox molecule reduction at the electrode | SEI interface to reduction at the SEI | electrolyte interface, and good estimates for the transport coefficients of both electrons and redox molecules are derived. The approach presented here is applicable to any type of electrochemical interphase and should thus also be of interest for interphase characterization in the fields of electrocatalysis and corrosion.

Elixhauser comorbidity method in predicting death of Spanish inpatients with asplenia and pneumococcal pneumonia.

BACKGROUND: Pneumococcal pneumonia (PP) is a serious infection caused by Streptococcus pneumoniae (pneumococcus), with a wide spectrum of clinical manifestations. The aim of this study was to analyze the comorbidity factors that influenced the mortality in patients with asplenia according to PP. METHODS: Discharge reports from the Spanish Minimum Basic Data Set (MBDS) was used to retrospectively analyze patients with asplenia and PP, from 1997 to 2021. Elixhauser Comorbidity Index (ECI) was calculated to predict in-hospital mortality (IHM). RESULTS: 97,922 patients with asplenia were included and 381 cases of PP were identified. The average age for men was 63.87 years and for women 65.99 years. In all years, ECI was larger for splenectomized than for non-splenectomized patients, with men having a higher mean ECI than women. An association was found between risk factors ECI, splenectomy, age group, sex, pneumococcal pneumonia, and increased mortality (OR = 0.98; 95% CI: 0.97-0.99; p < 0.001). The IHM increased steadily with the number of comorbidities and index scores in 1997-2021. CONCLUSIONS: Asplenia remain a relevant cause of hospitalization in Spain. Comorbidities reflected a great impact in patients with asplenia and PP, which would mean higher risk of mortality.

Complete Virion Simulated: All-Atom Model of an MS2 Bacteriophage with Native Genome.

For the first time, a complete all-atom molecular dynamics (MD) model of a virus, bacteriophage MS2, in its entirety, including a protein outer shell, native genomic RNA with necessary divalent ions, and surrounding explicit aqueous solution with ions at physiological concentration, was built. The model is based on an experimentally measured cryo-EM structure, which was substantially augmented by reconstructing missing or low-resolution parts of the measured density (where the atomistic structure cannot be fit unambiguously). The model was tested by a quarter of a microsecond MD run, and various biophysical characteristics are obtained and analyzed. The developed methodology of building the model can be used for reconstructing other large biomolecular structures when experimental data are fragmented and/or of varying resolution, while the model itself can be used for studying the biology of MS2, including the dynamics of its interaction with the host bacteria.

A biphasic model of lifespan in nematode Caenorhabditis elegans worm.

Ageing research focuses on identifying lifespan modifiers and understanding and appropriately interpreting their effects. One of the most relevant quantities being studied is the shape of the survival curve that can reveal crucial information on the mechanism of action. Here, we introduce a bilogistic model to describe the shape of the lifespan curves of Caenorhabditis elegans populations. Using the corrected Akaike information criterion and the RMSE as goodness-of-fit tests, we show that the bilogistic model provides a better fit to the experimental data from nematode worms than other mathematical models and can identify and confirm biphasic lifespan data. Our parametric model offers a method to interpret replicate experiments data in terms of the shape parameters of the lifespan curve and enables robust statistical analysis of intra- and inter-group variance. We apply the model to novel lifespan data from C. elegans and Drosophila melanogaster and provide a rational statistical analysis of lifespan modifiers such as temperature and daf-16/FOXO mutation.

Estimation of Nanoparticle's Surface Electrostatic Potential in Solution Using Acid-Base Molecular Probes. III. Experimental Hydrophobicity/Hydrophilicity and Charge Distribution of MS2 Virus Surface.

MS2 bacteriophage is often used as a model for evaluating pathogenic viruses' behavior in aqueous solution. However, the questions of the virus surface's hydrophilic/hydrophobic balance, the charge distribution, and the binding mechanism are open. Using the dynamic light scattering method and laser Doppler electrophoresis, the hydrodynamic diameter and the ζ-potential of the virus particles were measured at their concentration of 5 × 1011 particles per mL and ionic strength 0.03 M. The values were found to be 30 nm and -29 or -34 mV (by Smoluchowski or Ohshima approximations), respectively. The MS2 bacteriophage surface was also investigated using a series of acid-base indicator dyes of various charge type, size, and structure. Their spectral and acid-base properties (pKa) are very sensitive to the microenvironment in aqueous solution, including containing nanoparticles. The electrostatic potential of the surface Ψ was estimated using the common formula: Ψ = 59 × (pKai - pKa) in mV at 25 °C. The Ψ values were -50 and +10 mV, respectively, which indicate the "mosaic" way of the charge distribution on the surface. These data are in good agreement with the obtained ζ-potential values and provide even more information about the virus surface. It was found that the surface of the MS2 virus is hydrophilic in solution in contrast to the commonly accepted hypothesis of the hydrophobicity of virus particles. No hydrophobic interactions between various molecular probes and the capsid were observed.

Reconstruction and validation of entire virus model with complete genome from mixed resolution cryo-EM density.

It is very difficult to reconstruct computationally a large biomolecular complex in its biological entirety from experimental data. The resulting atomistic model should not contain gaps structurally and it should yield stable dynamics. We, for the first time, reconstruct from the published incomplete cryo-EM density a complete MS2 virus at atomistic resolution, that is, the capsid with the genome, and validate the result by all-atom molecular dynamics with explicit water. The available experimental data includes a high resolution protein capsid and an inhomogeneously resolved genome map. For the genomic RNA, apart from 16 hairpins with atomistic resolution, the strands near the capsid's inner surface were resolved up to the nucleic backbone level, and the innermost density was completely unresolved. As a result, only 242 nucleotides (out of 3569) were positioned, while only a fragmented backbone was outlined for the rest of the genome, making a detailed model reconstruction necessary. For model reconstruction, in addition to the available atomistic structure information, we extensively used the predicted secondary structure of the genome (base pairing). The technique was based on semi-automatic building of relatively large strands of RNA with subsequent manual positioning over the traced backbone. The entire virus structure (capsid + genome) was validated by a molecular dynamics run in physiological solution with ions at standard conditions confirming the stability of the model.

Oscillations, travelling fronts and patterns in a supramolecular system.

Supramolecular polymers, such as microtubules, operate under non-equilibrium conditions to drive crucial functions in cells, such as motility, division and organelle transport1. In vivo and in vitro size oscillations of individual microtubules2,3 (dynamic instabilities) and collective oscillations4 have been observed. In addition, dynamic spatial structures, like waves and polygons, can form in non-stirred systems5. Here we describe an artificial supramolecular polymer made of a perylene diimide derivative that displays oscillations, travelling fronts and centimetre-scale self-organized patterns when pushed far from equilibrium by chemical fuels. Oscillations arise from a positive feedback due to nucleation-elongation-fragmentation, and a negative feedback due to size-dependent depolymerization. Travelling fronts and patterns form due to self-assembly induced density differences that cause system-wide convection. In our system, the species responsible for the nonlinear dynamics and those that self-assemble are one and the same. In contrast, other reported oscillating assemblies formed by vesicles6, micelles7 or particles8 rely on the combination of a known chemical oscillator and a stimuli-responsive system, either by communication through the solvent (for example, by changing pH7-9), or by anchoring one of the species covalently (for example, a Belousov-Zhabotinsky catalyst6,10). The design of self-oscillating supramolecular polymers and large-scale dissipative structures brings us closer to the creation of more life-like materials11 that respond to external stimuli similarly to living cells, or to creating artificial autonomous chemical robots12.

In Situ Studies of Solid Electrolyte Interphase (SEI) Formation on Crystalline Carbon Surfaces by Neutron Reflectometry and Atomic Force Microscopy.

The solid electrolyte interphase (SEI) is a complex and fragile passivation layer with crucial importance for the functionality of lithium-ion batteries. Due to its fragility and reactivity, the use of in situ techniques is preferable for the determination of the SEI's true structure and morphology during its formation. In this study, we use in situ neutron reflectometry (NR) and in situ atomic force microscopy (AFM) to investigate the SEI formation on a carbon surface. It was found that a lithium-rich adsorption layer is already present at the open circuit voltage on the carbon sample surface and that the first decomposition products start to deposit close to this potential. During the negative potential sweep, the growth of the SEI can be observed in detail by AFM and NR. This allows precise monitoring of the morphology evolution and the resulting heterogeneities of individual SEI features. NR measurements show a maximum SEI thickness of 192 Å at the lower cutoff potential (0.02 V vs Li/Li+), which slightly decreases during the positive potential scan. The scattering length density (SLD) obtained by NR provides additional information on the SEI's chemical nature and structural evolution.

Mechanically Induced Homochirality in Nucleated Enantioselective Polymerization.

Understanding how biological homochirality may have emerged during chemical evolution remains a challenge for origin of life research. In keeping with this goal, we introduce and solve numerically a kinetic rate equation model of nucleated cooperative enantioselective polymerization in closed systems. The microreversible scheme includes (i) solution-phase racemization of the monomers, (ii) linear chain growth by stepwise monomer attachment, in both nucleation and elongation phases, and (iii) annealing or fusion of homochiral chains. Mechanically induced breakage of the longest chains maintains the system out of equilibrium and drives a breakage-fusion recycling mechanism. Spontaneous mirror symmetry breaking can be achieved starting from small initial enantiomeric excesses due to the intrinsic statistical fluctuations about the idealized racemic composition. The subsequent chiral amplification confirms the model's capacity for absolute asymmetric synthesis, without chiral cross-inhibition and without explicit autocatalysis.

Necessary conditions for the emergence of homochirality via autocatalytic self-replication.

We analyze a recent proposal for spontaneous mirror symmetry breaking based on the coupling of first-order enantioselective autocatalysis and direct production of the enantiomers that invokes a critical role for intrinsic reaction noise. For isolated systems, the racemic state is the unique stable outcome for both stochastic and deterministic dynamics when the system is in compliance with the constraints dictated by the thermodynamics of chemical reaction processes. In open systems, the racemic outcome also results for both stochastic and deterministic dynamics when driving the autocatalysis unidirectionally by external reagents. Nonracemic states can result in the latter only if the reverse reactions are strictly zero: these are kinetically controlled outcomes for small populations and volumes, and can be simulated by stochastic dynamics. However, the stability of the thermodynamic limit proves that the racemic outcome is the unique stable state for strictly irreversible externally driven autocatalysis. These findings contradict the suggestion that the inhibition requirement of the Frank autocatalytic model for the emergence of homochirality may be relaxed in a noise-induced mechanism.

Noise-induced standing waves in oscillatory systems with time-delayed feedback.

In oscillatory reaction-diffusion systems, time-delay feedback can lead to the instability of uniform oscillations with respect to formation of standing waves. Here, we investigate how the presence of additive, Gaussian white noise can induce the appearance of standing waves. Combining analytical solutions of the model with spatiotemporal simulations, we find that noise can promote standing waves in regimes where the deterministic uniform oscillatory modes are stabilized. As the deterministic phase boundary is approached, the spatiotemporal correlations become stronger, such that even small noise can induce standing waves in this parameter regime. With larger noise strengths, standing waves could be induced at finite distances from the (deterministic) phase boundary. The overall dynamics is defined through the interplay of noisy forcing with the inherent reaction-diffusion dynamics.

Efficient HIV-1 inhibition by a 16 nt-long RNA aptamer designed by combining in vitro selection and in silico optimisation strategies.

The human immunodeficiency virus type-1 (HIV-1) genome contains multiple, highly conserved structural RNA domains that play key roles in essential viral processes. Interference with the function of these RNA domains either by disrupting their structures or by blocking their interaction with viral or cellular factors may seriously compromise HIV-1 viability. RNA aptamers are amongst the most promising synthetic molecules able to interact with structural domains of viral genomes. However, aptamer shortening up to their minimal active domain is usually necessary for scaling up production, what requires very time-consuming, trial-and-error approaches. Here we report on the in vitro selection of 64 nt-long specific aptamers against the complete 5'-untranslated region of HIV-1 genome, which inhibit more than 75% of HIV-1 production in a human cell line. The analysis of the selected sequences and structures allowed for the identification of a highly conserved 16 nt-long stem-loop motif containing a common 8 nt-long apical loop. Based on this result, an in silico designed 16 nt-long RNA aptamer, termed RNApt16, was synthesized, with sequence 5'-CCCCGGCAAGGAGGGG-3'. The HIV-1 inhibition efficiency of such an aptamer was close to 85%, thus constituting the shortest RNA molecule so far described that efficiently interferes with HIV-1 replication.

Stabilization of standing waves through time-delay feedback.

Standing waves are studied as solutions of a complex Ginzburg-Landau equation subjected to local and global time-delay feedback terms. The onset is described as an instability of the uniform oscillations with respect to spatially periodic perturbations. The solution of the standing wave pattern is given analytically and studied through simulations.

Parametric pattern selection in a reaction-diffusion model.

We compare spot patterns generated by Turing mechanisms with those generated by replication cascades, in a model one-dimensional reaction-diffusion system. We determine the stability region of spot solutions in parameter space as a function of a natural control parameter (feed-rate) where degenerate patterns with different numbers of spots coexist for a fixed feed-rate. While it is possible to generate identical patterns via both mechanisms, we show that replication cascades lead to a wider choice of pattern profiles that can be selected through a tuning of the feed-rate, exploiting hysteresis and directionality effects of the different pattern pathways.

Chiral and chemical oscillations in a simple dimerization model.

We consider the APED model (activation-polymerization-epimerization-depolymerization) for describing the emergence of chiral solutions within a non-catalytic framework for chiral polymerization. The minimal APED model for dimerization can lead to the spontaneous appearance of chiral oscillations and we describe in detail the nature of these oscillations in the enantiomeric excess, which are the consequence of oscillations of the concentrations of the associated chemical species.

Topological structure of the space of phenotypes: the case of RNA neutral networks.

The evolution and adaptation of molecular populations is constrained by the diversity accessible through mutational processes. RNA is a paradigmatic example of biopolymer where genotype (sequence) and phenotype (approximated by the secondary structure fold) are identified in a single molecule. The extreme redundancy of the genotype-phenotype map leads to large ensembles of RNA sequences that fold into the same secondary structure and can be connected through single-point mutations. These ensembles define neutral networks of phenotypes in sequence space. Here we analyze the topological properties of neutral networks formed by 12-nucleotides RNA sequences, obtained through the exhaustive folding of sequence space. A total of 4(12) sequences fragments into 645 subnetworks that correspond to 57 different secondary structures. The topological analysis reveals that each subnetwork is far from being random: it has a degree distribution with a well-defined average and a small dispersion, a high clustering coefficient, and an average shortest path between nodes close to its minimum possible value, i.e. the Hamming distance between sequences. RNA neutral networks are assortative due to the correlation in the composition of neighboring sequences, a feature that together with the symmetries inherent to the folding process explains the existence of communities. Several topological relationships can be analytically derived attending to structural restrictions and generic properties of the folding process. The average degree of these phenotypic networks grows logarithmically with their size, such that abundant phenotypes have the additional advantage of being more robust to mutations. This property prevents fragmentation of neutral networks and thus enhances the navigability of sequence space. In summary, RNA neutral networks show unique topological properties, unknown to other networks previously described.

Motif frequency and evolutionary search times in RNA populations.

RNA molecules, through their dual identity as sequence and structure, are an appropriate experimental and theoretical model to study the genotype-phenotype map and evolutionary processes taking place in simple replicator populations. In this computational study, we relate properties of the sequence-structure map, in particular the abundance of a given secondary structure in a random pool, with the number of replicative events that an initially random population of sequences needs to find that structure through mutation and selection. For common structures, this search process turns out to be much faster than for rare structures. Furthermore, search and fixation processes are more efficient in a wider range of mutation rates for common structures, thus indicating that evolvability of RNA populations is not simply determined by abundance. We also find significant differences in the search and fixation processes for structures of same abundance, and relate them with the number of base pairs forming the structure. Moreover, the influence of the nucleotide content of the RNA sequences on the search process is studied. Our results advance in the understanding of the distribution and attainability of RNA secondary structures. They hint at the fact that, beyond sequence length and sequence-to-function redundancy, the mutation rate that permits localization and fixation of a given phenotype strongly depends on its relative abundance and global, in general non-uniform, distribution in sequence space.

Variable mutation rates as an adaptive strategy in replicator populations.

For evolving populations of replicators, there is much evidence that the effect of mutations on fitness depends on the degree of adaptation to the selective pressures at play. In optimized populations, most mutations have deleterious effects, such that low mutation rates are favoured. In contrast to this, in populations thriving in changing environments a larger fraction of mutations have beneficial effects, providing the diversity necessary to adapt to new conditions. What is more, non-adapted populations occasionally benefit from an increase in the mutation rate. Therefore, there is no optimal universal value of the mutation rate and species attempt to adjust it to their momentary adaptive needs. In this work we have used stationary populations of RNA molecules evolving in silico to investigate the relationship between the degree of adaptation of an optimized population and the value of the mutation rate promoting maximal adaptation in a short time to a new selective pressure. Our results show that this value can significantly differ from the optimal value at mutation-selection equilibrium, being strongly influenced by the structure of the population when the adaptive process begins. In the short-term, highly optimized populations containing little variability respond better to environmental changes upon an increase of the mutation rate, whereas populations with a lower degree of optimization but higher variability benefit from reducing the mutation rate to adapt rapidly. These findings show a good agreement with the behaviour exhibited by actual organisms that replicate their genomes under broadly different mutation rates.

Phenotypic effect of mutations in evolving populations of RNA molecules.

BACKGROUND: The secondary structure of folded RNA sequences is a good model to map phenotype onto genotype, as represented by the RNA sequence. Computational studies of the evolution of ensembles of RNA molecules towards target secondary structures yield valuable clues to the mechanisms behind adaptation of complex populations. The relationship between the space of sequences and structures, the organization of RNA ensembles at mutation-selection equilibrium, the time of adaptation as a function of the population parameters, the presence of collective effects in quasispecies, or the optimal mutation rates to promote adaptation all are issues that can be explored within this framework. RESULTS: We investigate the effect of microscopic mutations on the phenotype of RNA molecules during their in silico evolution and adaptation. We calculate the distribution of the effects of mutations on fitness, the relative fractions of beneficial and deleterious mutations and the corresponding selection coefficients for populations evolving under different mutation rates. Three different situations are explored: the mutation-selection equilibrium (optimized population) in three different fitness landscapes, the dynamics during adaptation towards a goal structure (adapting population), and the behavior under periodic population bottlenecks (perturbed population). CONCLUSIONS: The ratio between the number of beneficial and deleterious mutations experienced by a population of RNA sequences increases with the value of the mutation rate mu at which evolution proceeds. In contrast, the selective value of mutations remains almost constant, independent of mu, indicating that adaptation occurs through an increase in the amount of beneficial mutations, with little variations in the average effect they have on fitness. Statistical analyses of the distribution of fitness effects reveal that small effects, either beneficial or deleterious, are well described by a Pareto distribution. These results are robust under changes in the fitness landscape, remarkably when, in addition to selecting a target secondary structure, specific subsequences or low-energy folds are required. A population perturbed by bottlenecks behaves similarly to an adapting population, struggling to return to the optimized state. Whether it can survive in the long run or whether it goes extinct depends critically on the length of the time interval between bottlenecks.