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Mucosal membranes with strong variability in their viscoelastic properties line numerous organs and are often targeted by mucoadhesive formulations, e.g., highly swellable hydroxypropylmethylcellulose (HPMC) and slightly cross-linked poly(acrylic acid) (PAA) tablets. Although the factors determining the strength of mucoadhesion are hierarchical and affected by both reversible and irreversible processes, the currently available strategies generally view mucoadhesion as the individual performance of the mucoadhesive excipient. We propose an integrated concept that considers the viscoelasticity and tensile properties of both the adhesive interphase and the bulk phases. To reduce the complexity of the mucosal membrane and eliminate the effect of specific macromolecular interactions, we studied the adhesion on mucosa-mimetic freeze/thawed (FT) poly(vinyl alcohol) (PVA) hydrogels. Their viscoelastic properties were controlled by the number of FT cycles and the polymer concentration. The adhesive strength of HPMC tablets displayed a pronounced dependence on the viscoelasticity of PVA gels, explained by the limited chain flexibility and interpenetration of HPMC, resulting in the formation of a thin the adhesive interphase compared to PAA. We recognized scaling laws between toughness and strength for tensile and adhesive properties as well as general correlations between viscoelastic and adhesive properties, which can aid the more rational design of both mucoadhesive formulations and mucosa-mimetic materials.

Abstract Biological reproduction rests ultimately on chemical autocatalysis. Autocatalytic chemical cycles are thought to have played an important role in the chemical complexification en route to life. There are two, related issues: what chemical transformations allow such cycles to form, and at what speed they are operating. Here we investigate the latter question for solitary as well as competitive autocatalytic cycles in resource-unlimited batch and resource-limited chemostat systems. The speed of growth tends to decrease with the length of a cycle. Reversibility of the reproductive step results in parabolic growth that is conducive to competitive coexistence. Reversibility of resource uptake also slows down growth. Unilateral help by a cycle of its competitor tends to favour the competitor (in effect a parasite on the helper), rendering coexistence unlikely. We also show that deep learning is able to predict the outcome of competition just from the topology and the kinetic rate constants, provided the training set is large enough. These investigations pave the way for studying autocatalytic cycles with more complicated coupling, such as mutual catalysis.

Abstract Gene regulatory networks (GRNs) fulfill the essential function of maintaining the stability of cellular differentiation states by sustaining lineage-specific gene expression, while driving the progression of development. However, accounting for the relative stability of intermediate differentiation stages and their divergent trajectories remains a major challenge for models of developmental biology. Here, we develop an empirical data-based associative GRN model (AGRN) in which regulatory networks store multilineage stage-specific gene expression profiles as associative memory patterns. These networks are capable of responding to multiple instructive signals and, depending on signal timing and identity, can dynamically drive the differentiation of multipotent cells toward different cell state attractors. The AGRN dynamics can thus generate diverse lineage-committed cell populations in a robust yet flexible manner, providing an attractor-based explanation for signal-driven cell fate decisions during differentiation and offering a readily generalizable modelling tool that can be applied to a wide variety of cell specification systems.

Large gas bubbles can reach the surface of pools of mud and lava where they burst, often through the formation and expansion of circular holes. Bursting bubbles release volatiles and generate spatter, and hence play a key role in volcanic degassing and volcanic edifice construction. Here, we study the ascent and rupture of bubbles using a combination of field observations at Pâclele Mici (Romania), laboratory experiments with mud from the Imperial Valley (California, USA), numerical simulations and theoretical models. Numerical simulations predict that bubbles ascend through the mud as elliptical caps that develop a dimple at the apex as they impinge on the free surface. We documented the rupture of bubbles in nature and under laboratory conditions using high-speed video. The bursting of mud bubbles starts with the nucleation of multiple holes, which form at a near-constant rate and in quick succession. The quasi-circular holes rapidly grow and coalesce, and the sheet evolves towards a filamentous structure that finally falls back into the mud pool, sometimes breaking up into droplets. The rate of expansion of holes in the sheet can be explained by a generalization of the Taylor–Culick theory, which is shown to hold independent of the fluid rheology.

Abstract Background Conventional wisdom in evolutionary theory considers aging as a non-selected byproduct of natural selection. Based on this, conviction aging was regarded as an inevitable phenomenon. It was also thought that in the wild organisms tend to die from diseases, predation and other accidents before they could reach the time when senescence takes its course. Evidence has accumulated, however, that aging is not inevitable and there are organisms that show negative aging even. Furthermore, old age does play a role in the deaths of many different organisms in the wild also. The hypothesis of programmed aging posits that a limited lifespan can evolve as an adaptation (i.e., positively selected for) in its own right, partly because it can enhance evolvability by eliminating “outdated” genotypes. A major shortcoming of this idea is that non-aging sexual individuals that fail to pay the demographic cost of aging would be able to steal good genes by recombination from aging ones. Results Here, we show by a spatially explicit, individual-based simulation model that aging can positively be selected for if a sufficient degree of kin selection complements directional selection. Under such conditions, senescence enhances evolvability because the rate of aging and the rate of recombination play complementary roles. The selected aging rate is highest at zero recombination (clonal reproduction). In our model, increasing extrinsic mortality favors evolved aging by making up free space, thereby decreasing competition and increasing drift, even when selection is stabilizing and the level of aging is set by mutation-selection balance. Importantly, higher extrinsic mortality is not a substitute for evolved aging under directional selection either. Reduction of relatedness decreases the evolved level of aging; chance relatedness favors non-aging genotypes. The applicability of our results depends on empirical values of directional and kin selection in the wild. Conclusions We found that aging can positively be selected for in a spatially explicit population model when sufficiently strong directional and kin selection prevail, even if reproduction is sexual. The view that there is a conceptual link between giving up clonal reproduction and evolving an aging genotype is supported by computational results.

The RNA world hypothesis proposes that during the early evolution of life, primordial genomes of the first self-propagating evolutionary units existed in the form of RNA-like polymers. Autonomous, non-enzymatic, and sustained replication of such information carriers presents a problem, because product formation and hybridization between template and copy strands reduces replication speed. Kinetics of growth is then parabolic with the benefit of entailing competitive coexistence, thereby maintaining diversity. Here, we test the information-maintaining ability of parabolic growth in stochastic multispecies population models under the constraints of constant total population size and chemostat conditions. We find that large population sizes and small differences in the replication rates favor the stable coexistence of the vast majority of replicator species (‘genes’), while the error threshold problem is alleviated relative to exponential amplification. In addition, sequence properties (GC content) and the strength of resource competition mediated by the rate of resource inflow determine the number of coexisting variants, suggesting that fluctuations in building block availability favored repeated cycles of exploration and exploitation. Stochastic parabolic growth could thus have played a pivotal role in preserving viable sequences generated by random abiotic synthesis and providing diverse genetic raw material to the early evolution of functional ribozymes.

Abstract Introduction The aim of our prospective study was to confirm validity and diagnostic accuracy of the modified Alvarado score, which was developed at the Department of Surgery, University of Szeged, on patients presenting with symptoms suggestive of acute appendicitis (right lower quadrant complaints) at the A&E department. Patient population, methods 138 patients were included in our study between 01.01.2019 and 01.01.2020. For patients attending A&E, the first medic calculated and recorded the modified Alvarado score before surgical consultation. The consulting surgeon decided on further treatment without knowing the score. Validation of the score was based on the pathology report of the removed appendix (whether the operation was warranted, and if the score also supported indication for surgery), if there was readmission or surgery due to worsening symptoms after discharge from A&E. We also examined if there was any connection between the value of the Alvarado score and the severity of inflammation. Our aim was to prove that using modified Alvarado score at the A&E Units helps to reduce patient’s waiting time and avoid unnecessary surgical consultations. Furthermore our study included measuring the diagnostic accuracy of the ultrasound examination (specificity, sensitivity). Results Based on the results, patients presenting at A&E had a mean modified Alvarado score of 6.5. Comparing the score to histological results showed that the specificity of the modified Alvarado score was 100%, and its sensitivity was 80.7%. Based on Spearman’s rank correlation (0.796) and ROC analysis (AUC 0.968), the modified Alvarado score has an excellent predictive value in diagnosing acute appendicitis. When comparing the patients’ waiting times with the use of modified Alvarado score and without it we found that there was a significant difference in group also in group under 4 points and in group over 7 points when using modified Alvarado score, so the diagnostic and therapeutic algorithm should be much quicker with the help of the score. We found a correlation between the severity of inflammation based on the Fisher’s exact test. Rank correlation of the same question also showed a significant connection. All patients had an US examination during their diagnostic course, its sensitivity was 82.6%, specificity was 87%. Based on this, we can conclude that the predictive value of the imaging method is good. Conclusions We can conclude according to our results that the predictive value of the modified score is excellent, and it can be safely applied by non-surgeons in urgent care in the differential diagnosis of acute appendicitis. The new score incorporates the results of an easily obtainable, ionising radiation free imaging method, the ultrasound, which was not included in previous scores. With the help of the new score, the number of unnecessary surgical referrals and waiting times for patients are reduced, excess examinations will become avoidable.

Protein homodimers have been classified as three-state or two-state dimers depending on whether a folded monomer forms before association, but the details of the folding–binding mechanisms are poorly understood. Kinetic transition networks of conformational states have provided insight into the folding mechanisms of monomeric proteins, but extending such a network to two protein chains is challenging as all the relative positions and orientations of the chains need to be included, greatly increasing the number of degrees of freedom. Here, we present a simplification of the problem by grouping all states of the two chains into two layers: a dissociated and an associated layer. We combined our two-layer approach with the Wako–Saito–Muñoz–Eaton method and used Transition Path Theory to investigate the dimer formation kinetics of eight homodimers. The analysis reveals a remarkable diversity of dimer formation mechanisms. Induced folding, conformational selection, and rigid docking are often simultaneously at work, and their contribution depends on the protein concentration. Pre-folded structural elements are always present at the moment of association, and asymmetric binding mechanisms are common. Our two-layer network approach can be combined with various methods that generate discrete states, yielding new insights into the kinetics and pathways of flexible binding processes.

There is increased awareness of the possibility of developmental memories resulting from evolutionary learning. Genetic regulatory and neural networks can be modelled by analogous formalism raising the important question of productive analogies in principles, processes and performance. We investigate the formation and persistence of various developmental memories of past phenotypes asking how the number of remembered past phenotypes scales with network size, to what extent memories stored form by Hebbian-like rules, and how robust these developmental "devo-engrams" are against networks perturbations (graceful degradation). The analogy between neural and genetic regulatory networks is not superficial in that it allows knowledge transfer between fields that used to be developed separately from each other. Known examples of spectacular phenotypic radiations could partly be accounted for in such terms.

Chromosomes are likely to have assembled from unlinked genes in early evolution. Genetic linkage reduces the assortment load and intragenomic conflict in reproducing protocell models to the extent that chromosomes can go to fixation even if chromosomes suffer from a replicative disadvantage, relative to unlinked genes, proportional to their length. Here we numerically show that chromosomes spread within protocells even if recurrent deleterious mutations affecting replicating genes (as ribozymes) are considered. Dosage effect selects for optimal genomic composition within protocells that carries over to the genic composition of emerging chromosomes. Lacking an accurate segregation mechanism, protocells continue to benefit from the stochastic corrector principle (group selection of early replicators), but now at the chromosome level. A remarkable feature of this process is the appearance of multigene families (in optimal genic proportions) on chromosomes. An added benefit of chromosome formation is an increase in the selectively maintainable genome size (number of different genes), primarily due to the marked reduction of the assortment load. The establishment of chromosomes is under strong positive selection in protocells harboring unlinked genes. The error threshold of replication is raised to higher genome size by linkage due to the fact that deleterious mutations affecting protocells metabolism (hence fitness) show antagonistic (diminishing return) epistasis. This result strengthens the established benefit conferred by chromosomes on protocells allowing for the fixation of highly specific and efficient enzymes.

Enzyme replacement therapies (ERT) have been of great help over the past 30 years in the treatment of various lysosomal storage disorders, including chronic pancreatitis and its common complication, exocrine pancreatic insufficiency. Research shows that difficulties in designing such drugs can be overcome by using appropriate additives and various enzyme immobilization techniques. Cyclodextrins (CDs) can be considered as a promising additive for enzyme replacement therapies, as they are known to enhance the activity of enzymes in a complex process due to their specific binding. In this study, we investigated the formulation of lipases (from Aspergillus oryzae and Burkholderia cepacia) paired with different cyclodextrins in poly(vinyl alcohol) (PVA) nanofibers by electrospinning technique. We examined the effect of the presence of cyclodextrins and nanoformulation on the lipase activity. The rheological and morphological characterizations of precursors and nanofibers were also performed using a viscometer as well as electron and Raman microscope. We found that by selecting the appropriate CD:lipase ratio, the activity of the investigated enzyme could be multiplied, and cyclodextrins can support the homogeneous dispersion of lipases inside the solid formula. In addition, the entrapment of lipases in PVA nanofibers led to a significant increase in activity compared to the preformulated precursor. In this way, the nanofibrous formulation of lipases combining CDs as additives can provide an efficient and sustainable possibility for designing novel solid medicines in ERT.

In order to explore how cucurbituril hosts accommodate an N-phenyl-pyridinium derivative guest, the complexation of the solvatochromic dye, 4-(4-(dimethylamino)styryl)-1-phenylpyridinium iodide (PhSt) with α,α′,δ,δ′-tetramethyl-cucurbit[6]uril (Me4CB6) and cucurbit[7]uril (CB7) was investigated by absorption spectroscopic, fluorescence and NMR experiments. In aqueous solutions, PhSt forms 1:1 complexes with both cucurbiturils, the complex with CB7 has a higher stability constant (Ka = 6.0 × 106 M−1) than the complex with Me4CB6 (Ka = 1.1 × 106 M−1). As revealed by NMR experiments and confirmed by theoretical calculations, CB7 encapsulates the whole phenylpyridinium entity of the PhSt cation guest, whereas the cavity of Me4CB6 includes only the phenyl ring, the pyridinium ring is bound to the carbonyl rim of the host. The binding of PhSt to cucurbiturils is accompanied by a strong enhancement of the fluorescence quantum yield due to the blocking of the deactivation through a twisted intramolecular charge transfer (TICT) state. The TICT mechanism in PhSt was characterized by fluorescence experiments in polyethylene glycol (PEG) solvents of different viscosities. The PhSt-CB7 system was tested as a fluorescence indicator displacement (FID) assay, and it recognized trimethyl-lysine selectively over other lysine derivatives.

The dual functionalization of magnetic nanoparticles with inert (methyl) and reactive (aminopropyl) groups enables efficient immobilization of synthetic metalloporphyrins (such as 5,10,15,20-tetrakis(2,3,4,5,6-pentafluorophenyl)iron(II) porphyrin and 5,10,15,20-tetrakis-(4-sulfonatophenyl)iron(II) porphyrin) via covalent or ionic interactions. The proportion of reactive function on the surface has significant effect on the biomimetic activity of metalloporphyrins. The optimized magnetic nanocatalyst containing porphyrin was successfully applied for biomimetic oxidation of antihypertensive drug Amlodipine in batch and continuous-flow reactors as well.

HIV superinfection (infection of an HIV positive individual with another strain of the virus) has been shown to result in a deterioration of clinical status in multiple case studies. However, superinfection with no (or positive) clinical outcome might easily go unnoticed, and the typical effect of superinfection is unknown. We analyzed mathematical models of HIV dynamics to assess the effect of superinfection under various assumptions. We extended the basic model of virus dynamics to explore systematically a set of model variants incorporating various details of HIV infection (homeostatic target cell dynamics, bystander killing, interference competition between viral clones, multiple target cell types, virus-induced activation of target cells). In each model, we identified the conditions for superinfection, and investigated whether and how successful invasion by a second viral strain affects the level of uninfected target cells. In the basic model, and in some of its extensions, the criteria for invasion necessarily entail a decrease in the equilibrium abundance of uninfected target cells. However, we identified three novel scenarios where superinfection can substantially increase the uninfected cell count: (i) if the rate of new infections saturates at high infectious titers (due to interference competition or cell-autonomous innate immunity); or when the invading strain is more efficient at infecting activated target cells, but less efficient at (ii) activating quiescent cells or (iii) inducing bystander killing of these cells. In addition, multiple target cell types also allow for modest increases in the total target cell count. We thus conclude that the effect of HIV superinfection on clinical status might be variable, complicated by factors that are independent of the invasion fitness of the second viral strain.

Parent-offspring communication remains an unresolved challenge for biologist. The difficulty of the challenge comes from the fact that it is a multifaceted problem with connections to life-history evolution, parent-offspring conflict, kin selection and signalling. Previous efforts mainly focused on modelling resource allocation at the expense of the dynamic interaction during a reproductive season. Here we present a two-stage model of begging where the first stage models the interaction between nestlings and parents within a nest and the second stage models the life-history trade-offs. We show in an asexual population that honest begging results in decreased variance of collected food between siblings, which leads to mean number of surviving offspring. Thus, honest begging can be seen as a special bet-hedging against informational uncertainty, which not just decreases the variance of fitness but also increases the arithmetic mean.

Serine proteases (SPs) are typically synthesized as precursors, termed proenzymes or zymogens, and the fully active form is produced via limited proteolysis by another protease or by autoactivation. The lectin pathway of the complement system is initiated by mannose-binding lectin (MBL)-associated SPs (MASP)-1, and MASP-2, which are known to be present as proenzymes in blood. The third SP of the lectin pathway, MASP-3, was recently shown to be the major activator, and the exclusive “resting blood” activator of profactor D, producing factor D, the initiator protease of the alternative pathway. Because only activated MASP-3 is capable of carrying out this cleavage, it was presumed that a significant fraction of MASP-3 must be present in the active form in resting blood. Here, we aimed to detect active MASP-3 in the blood by a more direct technique and to quantitate the active to zymogen ratio. First, MASPs were partially purified (enriched) from human plasma samples by affinity chromatography using immobilized MBL in the presence of inhibitors. Using this MASP pool, only the zymogen form of MASP-1 was detected by Western blot, whereas over 70% MASP-3 was in an activated form in the same samples. Furthermore, the active to zymogen ratio of MASP-3 showed little individual variation. It is enigmatic how MASP-3, which is not able to autoactivate, is present mostly as an active enzyme, whereas MASP-1, which has a potent autoactivation capability, is predominantly proenzymic in resting blood. In an attempt to explain this phenomenon, we modeled the basal level fluid-phase activation of lectin pathway proteases and their subsequent inactivation by C1 inhibitor and antithrombin using available and newly determined kinetic constants. The model can explain extensive MASP-3 activation only if we assume efficient intracomplex activation of MASP-3 by zymogen MASP-1. On the other hand, the model is in good agreement with the fact that MASP-1 and -2 are predominantly proenzymic and some of them is present in the form of inactive serpin–protease complexes. As an alternative hypothesis, MASP-3 activation by proprotein convertases is also discussed.

Background: The fact that surplus connections and neurons are pruned during development is well established. We complement this selectionist picture by a proof-of-principle model of evolutionary search in the brain, that accounts for new variations in theory space. We present a model for Darwinian evolutionary search for candidate solutions in the brain. Methods: We combine known components of the brain – recurrent neural networks (acting as attractors), the action selection loop and implicit working memory – to provide the appropriate Darwinian architecture. We employ a population of attractor networks with palimpsest memory. The action selection loop is employed with winners-share-all dynamics to select for candidate solutions that are transiently stored in implicit working memory. Results: We document two processes: selection of stored solutions and evolutionary search for novel solutions. During the replication of candidate solutions attractor networks occasionally produce recombinant patterns, increasing variation on which selection can act. Combinatorial search acts on multiplying units (activity patterns) with hereditary variation and novel variants appear due to (i) noisy recall of patterns from the attractor networks, (ii) noise during transmission of candidate solutions as messages between networks, and, (iii) spontaneously generated, untrained patterns in spurious attractors. Conclusions: Attractor dynamics of recurrent neural networks can be used to model Darwinian search. The proposed architecture can be used for fast search among stored solutions (by selection) and for evolutionary search when novel candidate solutions are generated in successive iterations. Since all the suggested components are present in advanced nervous systems, we hypothesize that the brain could implement a truly evolutionary combinatorial search system, capable of generating novel variants.

Biomimetic oxidation of drugs catalyzed by metalloporphyrins can be a novel and promising way for the effective and sustainable synthesis of drug metabolites. The immobilization of 5,10,15,20-tetrakis(2,3,4,5,6-pentafluorophenyl)iron(II) porphyrin (FeTPFP) and 5,10,15,20-tetrakis-(4-sulfonatophenyl)iron(II) porphyrin (FeTSPP) via stable covalent or rapid ionic binding on aminopropyl-functionalized magnetic nanoparticles (MNPs-NH2) were developed. These immobilized catalysts could be efficiently applied for the synthesis of new pharmaceutically active derivatives and liver related phase I oxidative major metabolite of an antiarrhythmic drug, amiodarone integrated in a continuous-flow magnetic chip reactor (Magnechip).

Background: The fact that surplus connections and neurons are pruned during development is well established. We complement this selectionist picture by a proof-of-principle model of evolutionary search in the brain, that accounts for new variations in theory space. We present a model for Darwinian evolutionary search for candidate solutions in the brain. Methods: We combine known components of the brain – recurrent neural networks (acting as attractors), the action selection loop and implicit working memory – to provide the appropriate Darwinian architecture. We employ a population of attractor networks with palimpsest memory. The action selection loop is employed with winners-share-all dynamics to select for candidate solutions that are transiently stored in implicit working memory. Results: We document two processes: selection of stored solutions and evolutionary search for novel solutions. During the replication of candidate solutions attractor networks occasionally produce recombinant patterns, increasing variation on which selection can act. Combinatorial search acts on multiplying units (activity patterns) with hereditary variation and novel variants appear due to (i) noisy recall of patterns from the attractor networks, (ii) noise during transmission of candidate solutions as messages between networks, and, (iii) spontaneously generated, untrained patterns in spurious attractors. Conclusions: Attractor dynamics of recurrent neural networks can be used to model Darwinian search. The proposed architecture can be used for fast search among stored solutions (by selection) and for evolutionary search when novel candidate solutions are generated in successive iterations. Since all the suggested components are present in advanced nervous systems, we hypothesize that the brain could implement a truly evolutionary combinatorial search system, capable of generating novel variants.

Randomized clinical trials (RCTs) demonstrated the equal efficacy of urinary human chorionic gonadotropin (uhCG) and recombinant hCG (rhCG) products in in vitro fertilisation (IVF). However, limitations inherent with RCTs necessitate the reinforcement of RCT results in real-life. We retrospectively analyzed pregnancies after treatment with rhCG and uhCG products (n=391, and 96, resp.). We found that laboratory-verified pregnancy occurred more frequently in rhCG patients than in those on uhCG (43% versus 30%, P=0.02). The association remains significant (P=0.002) after its adjustment for clinical characteristics. The prevalence of laboratory-verified pregnancies was higher with GnRH agonist use (P=0.012) and BMI under 30 kg/m2 (P=0.053) while decreased the age (P=0.014) and the number of previous failed attempts (P=0.08). Similar (but not significant) trends were observed with rates of pregnancy filled the 24th week. These results reinforce RCTs supporting the notion that rhCG is more efficient as uhCG during IVF.

Dry eye disease is a relatively common ocular problem, which causes eye discomfort and visual disorders leading to a decrease in the quality of life. The aim of this study was to find a possible excipient for eye drop formulations, which is able to stabilize the tear film. A cationic thiolated polyaspartamide polymer, poly[(N-mercaptoethylaspartamide)-co-(N-(N′,N′-dimethylaminoethyl)aspartamide)] (ThioPASP-DME), was used as a potential vehicle. Besides satisfying the basic requirements, the chemical structure of ThioPASP-DME is similar to those of ocular mucins as it is a protein-like polymer bearing a considerable number of thiol groups. The solution of the polymer is therefore able to mimic the physiological properties of the mucins and it can interact with the mucus layer via disulphide bond formation. The resultant mucoadhesion provides a prolonged residence time and ensures protective effect for the corneal/conjunctival epithelium. ThioPASP-DME also has an antioxidant effect due to the presence of the thiol groups. The applicability of ThioPASP-DME as a potential excipient in eye drops was determined by means of ocular compatibility tests and through examinations of the interactions with the mucosal surface. The results indicate that ThioPASP-DME can serve as a potential eye drop excipient for the therapy of dry eye disease.

As of today, the most credible scientific paradigm pertaining to the origin of life on Earth is undoubtedly the RNA World scenario. It is built on the assumption that catalytically active replicators (most probably RNA-like macromolecules) may have been responsible for booting up life almost four billion years ago. The many different incarnations of nucleotide sequence (string) replicator models proposed recently are all attempts to explain on this basis how the genetic information transfer and the functional diversity of prebiotic replicator systems may have emerged, persisted and evolved into the first living cell. We have postulated three necessary conditions for an RNA World model system to be a dynamically feasible representation of prebiotic chemical evolution: (1) it must maintain and transfer a sufficient diversity of information reliably and indefinitely, (2) it must be ecologically stable and (3) it must be evolutionarily stable. In this review, we discuss the best-known prebiotic scenarios and the corresponding models of string-replicator dynamics and assess them against these criteria. We suggest that the most popular of prebiotic replicator systems, the hypercycle, is probably the worst performer in almost all of these respects, whereas a few other model concepts (parabolic replicator, open chaotic flows, stochastic corrector, metabolically coupled replicator system) are promising candidates for development into coherent models that may become experimentally accessible in the future.

The RNA world is a very likely interim stage of the evolution after the first replicators and before the advent of the genetic code and translated proteins. Ribozymes are known to be able to catalyze many reaction types, including cofactor-aided metabolic transformations. In a metabolically complex RNA world, early division of labor between genes and enzymes could have evolved, where the ribozymes would have been transcribed from the genes more often than the other way round, benefiting the encapsulating cells through this dosage effect. Here we show, by computer simulations of protocells harboring unlinked RNA replicators, that the origin of replicational asymmetry producing more ribozymes from a gene template than gene strands from a ribozyme template is feasible and robust. Enzymatic activities of the two modeled ribozymes are in trade-off with their replication rates, and the relative replication rates compared to those of complementary strands are evolvable traits of the ribozymes. The degree of trade-off is shown to have the strongest effect in favor of the division of labor. Although some asymmetry between gene and enzymatic strands could have evolved even in earlier, surface-bound systems, the shown mechanism in protocells seems inevitable and under strong positive selection. This could have preadapted the genetic system for transcription after the subsequent origin of chromosomes and DNA.

The error threshold of replication limits the selectively maintainable genome size against recurrent deleterious mutations for most fitness landscapes. In the context of RNA replication a distinction between the genotypic and the phenotypic error threshold has been made; where the latter concerns the maintenance of secondary structure rather than sequence. RNA secondary structure is treated as a proxy for function. The phenotypic error threshold allows higher per digit mutation rates than its genotypic counterpart, and is known to increase with the frequency of neutral mutations in sequence space. Here we show that the degree of neutrality, i.e. the frequency of nearest-neighbour (one-step) neutral mutants is a remarkably accurate proxy for the overall frequency of such mutants in an experimentally verifiable formula for the phenotypic error threshold; this we achieve by the full numerical solution for the concentration of all sequences in mutation-selection balance up to length 16. We reinforce our previous result that currently known ribozymes could be selectively maintained by the accuracy known from the best available polymerase ribozymes. Furthermore, we show that in silico stabilizing selection can increase the mutational robustness of ribozymes due to the fact that they were produced by artificial directional selection in the first place. Our finding offers a better understanding of the error threshold and provides further insight into the plausibility of an ancient RNA world.

Models of competitive template replication, although basic for replicator dynamics and primordial evolution, have not yet taken different sequences explicitly into account, neither have they analyzed the effect of resource partitioning (feeding on different resources) on coexistence. Here we show by analytical and numerical calculations that Gause's principle of competitive exclusion holds for template replicators if resources (nucleotides) affect growth linearly and coexistence is at fixed point attractors. Cases of complementary or homologous pairing between building blocks with parallel or antiparallel strands show no deviation from the rule that the nucleotide compositions of stably coexisting species must be different and there cannot be more coexisting replicator species than nucleotide types. Besides this overlooked mechanism of template coexistence we show also that interesting sequence effects prevail as parts of sequences that are copied earlier affect coexistence more strongly due to the higher concentration of the corresponding replication intermediates. Template and copy always count as one species due their constraint of strict stoichiometric coupling. Stability of fixed-point coexistence tends to decrease with the length of sequences, although this effect is unlikely to be detrimental for sequences below 100 nucleotides. In sum, resource partitioning (niche differentiation) is the default form of competitive coexistence for replicating templates feeding on a cocktail of different nucleotides, as it may have been the case in the RNA world. Our analysis of different pairing and strand orientation schemes is relevant for artificial and potentially astrobiological genetics.

Background: The fact that surplus connections and neurons are pruned during development is well established. We complement this selectionist picture by a proof-of-principle model of evolutionary search in the brain, that accounts for new variations in theory space. We present a model for Darwinian evolutionary search for candidate solutions in the brain. Methods: We combine known components of the brain – recurrent neural networks (acting as attractors), the action selection loop and implicit working memory – to provide the appropriate Darwinian architecture. We employ a population of attractor networks with palimpsest memory. The action selection loop is employed with winners-share-all dynamics to select for candidate solutions that are transiently stored in implicit working memory. Results: We document two processes: selection of stored solutions and evolutionary search for novel solutions. During the replication of candidate solutions attractor networks occasionally produce recombinant patterns, increasing variation on which selection can act. Combinatorial search acts on multiplying units (activity patterns) with hereditary variation and novel variants appear due to (i) noisy recall of patterns from the attractor networks, (ii) noise during transmission of candidate solutions as messages between networks, and, (iii) spontaneously generated, untrained patterns in spurious attractors. Conclusions: Attractor dynamics of recurrent neural networks can be used to model Darwinian search. The proposed architecture can be used for fast search among stored solutions (by selection) and for evolutionary search when novel candidate solutions are generated in successive iterations. Since all the suggested components are present in advanced nervous systems, we hypothesize that the brain could implement a truly evolutionary combinatorial search system, capable of generating novel variants.