The SARS-CoV-2 high infectivity is due to the functional polybasic furin cleavage site in the S protein. How it was acquired is unknown. There are two challenges to face: (i) an evolutionary model, to fit the origin of the coronavirus; and (ii) a molecular mechanism for the site acquisition. Here we show genomic fingerprints which are specific of Pangolin-CoVs, Bat-SARS-like (CoVZC45, CoVZXC21), bat RatG13 and human SARS-CoV-2 coronaviruses. This, along with phylogenetic analysis, we found that these species have the same evolutionary origin in the bat, including a genetic recombination of S gene between Pangolin-CoV (2017) and RatG13 ancestors. However, this does not explain why SARS-CoV-2 is the only of them with the furin site, which consists in four amino acid (PRRA) motif. The Arginine doublet is encoded by CGGCGG codons. Surprisingly, none of the Arginine doublet of other furin site of viral proteins from several type of viruses, are encoded by the CGGCGG codons. This makes it difficult to consider a virus recombination as mechanism for the PRRA acquisition. The origin of SARS-CoV-2, is the origin of the recognition cleavage site. The bat coronavirus RaTG13 appears to be the closest relative of the SARS-CoV-2, but was isolated in 2013. So, new RatG13 samples would provide insights into the acquisition of the polybasic motif.

The novel respiratory disease COVID-19 has reached the status of worldwide pandemic and large efforts are currently being undertaken in molecularly characterizing the virus causing it, SARS-CoV-2. The genomic variability of SARS-CoV-2 specimens scattered across the globe can underly geographically specific etiological effects. In the present study, we gather the 48,635 SARS-CoV-2 complete genomes currently available thanks to the collection endeavor of the GISAID consortium and thousands of contributing laboratories. We analyze and annotate all SARS-CoV-2 mutations compared with the reference Wuhan genome NC_045512.2, observing an average of 7.23 mutations per sample. Our analysis shows the prevalence of single nucleotide transitions as the major mutational type across the world. There exist at least three clades characterized by geographic and genomic specificity. In particular, the clade G, prevalent in Europe, carries a D614G mutation in the Spike protein, which is responsible for the initial interaction of the virus with the host human cell. Our analysis may drive local modulation of antiviral strategies based on the molecular specificities of this novel virus.

Chan and colleagues in their paper titled “Human origins in a southern African palaeo-wetland and first migrations” (https://www.nature.com/articles/s41586-019-1714-1) report 198 novel whole mitochondrial DNA (mtDNA) sequences and infer that ‘anatomically modern humans’ originated in the Makgadikgadi–Okavango palaeo-wetland of southern Africa around 200 thousand years ago. This claim relies on weakly informative data. In addition to flawed logic and questionable assumptions, the authors surprisingly disregard recent evidence and debate on human origins in Africa. As a result, the emphatic and high profile conclusions of the paper are unjustified.

Heart failure with preserved ejection fraction (HFpEF) is a leading form of human cardiovascular disease and commonly associated with systemic hypertension. Unique evolved adaptations in giraffe myocardia may be a natural animal model of resistance to HFpEF. In humans, pressure-overload induced left ventricular thickening (PLVT) impairs diastolic relaxation, elevates left atrial pressures and may progress to heart failure with symptoms including exercise intolerance. In healthy giraffe, the left ventricle thickens as developmental neck lengthening widens the vertical distance between the heart and head increasing pressures needed to maintain constant brain perfusion. Yet, diastolic relaxation and exercise capacity are unimpaired, a critical adaptation for prey species such as giraffe. The proximate mechanisms underlying this unique cardiovascular physiology are not yet characterized. Developmental PLVT in giraffe emerges as a species-specific evolved adaptation which offers a roadmap for identifying innovations in therapeutic and prevention strategies for HFpEF.

Kelly's Criterion is well known among gamblers and investors as a method for maximizing the returns one would expect to observe over long periods of betting or investing. These ideas are conspicuously absent from portfolio optimization problems in the financial and automation literature. This paper will show how Kelly's Criterion can be incorporated into standard portfolio optimization models. The model developed here combines risk and return into a single objective function by incorporating a risk parameter. This model is then solved for a portfolio of 10 stocks from a major stock exchange using a differential evolution algorithm. Monte Carlo calculations are used to verify the accuracy of the results obtained from differential evolution. The results show that evolutionary algorithms can be successfully applied to solve a portfolio optimization problem where returns are calculated by applying Kelly's Criterion to each of the assets in the portfolio.

A fundamental question in biology is whether phenotypes can be predicted by ecological or genomic rules. At least five cases of convergent evolution of the crab-like body plan (with a wide and flattened shape, and a bent abdomen) are known in decapod crustaceans, and have, for over 140 years, been known as ‘carcinization’. The repeated loss of this body plan has been identified as ‘decarcinization’. In reviewing the field, we offer phylogenetic strategies to include poorly known groups, and direct evidence from fossils, that will resolve the history of crab evolution and the degree of phenotypic variation within crabs. Proposed ecological advantages of the crab body are summarized into a hypothesis of phenotypic integration suggesting correlated evolution of the carapace shape and abdomen. Our premise provides fertile ground for future studies of the genomic and developmental basis, and the predictability, of the crab-like body form.

Biological invasions have reached an unprecedented level and the number of introduced species is still increasing worldwide. Despite major advances in invasion science, the determinants of success of introduced species, the magnitude and dimensions of their impact, and the mechanisms sustaining successful invasions are still debated. Empirical studies show divergent impacts of non-native populations on ecosystems and contrasting effects of biotic and abiotic factors on the dynamics of non-native populations; this is hindering the emergence of a unified theory of biological invasions. We propose a synthesis that merges perspectives from population, community, and ecosystem levels. Along a timeline of ecosystem transformation driven by non-native species, from historical to human-modified ecosystems, we order invasion concepts and theories to clarify their chaining and relevance during each step of the invasion process. This temporal sorting of invasion concepts shows that each concept is relevant at a specific stage of the invasion. Concepts and empirical findings on non-native species may appear contradictory. However, we suggest that, when mapped onto an invasion timeline, they may be combined in a complementary way. An overall scheme is proposed to summarise the theoretical dynamics of ecosystems subjected to invasions. For any given case study, this framework provides a guide through the maze of theories and should help choose the appropriate concepts according to the stage of invasion.

Efficient oxygen evolution reaction (OER) electrocatalysts are highly desired in the field of water electrolysis and rechargeable metal-air batteries. In this study, a chelate polymer, composed of copper (II) and dithiooxamide, was used to derive an efficient catalytic system for OER. Upon potential sweep in 1M KOH, copper (II) centers of the chelate polymer were transformed to CuO and Cu(OH)2. The carbon-dispersed CuO nanostructures formed a nanocomposite which exhibits an enhanced catalytic activity for OER in alkaline media. The nanocomposite catalyst has overpotential of 280 mV (at 1 mA/cm2) and a Tafel slope of 81 mV/dec in 1M KOH solution. It has a seven-fold higher current than IrO2/C electrode, per metal loading. A catalytic cycle is proposed, in which, CuO undergoes electrooxidation to Cu2O3 that further decomposes to CuO with releasing oxygen. This work reveals a new method to produce an active nanocomposite catalyst for OER in alkaline media using a non-noble metal chelate polymer and a porous carbon. This method can be applied to the synthesis of transition metal oxide nanoparticles used in the preparation of composite electrodes for water electrolyzers and can be used to derive cathode materials for aqueous-type metal-air batteries.

This paper presents the validation of the End Point Rate (EPR) tool for QGIS (EPR4Q), a tool built-in QGIS Graphical Modeler to calculate the shoreline change by End Point Rate method. The EPR4Q tries to fill the gap of user-friendly and free open-source tool for shoreline analysis in Geographic Information System environment, since the most used software - Digital Shoreline Analysis System (DSAS) - although is a free extension, is suited for commercial software. Besides, the best free open-source option to calculate EPR called Analyzing Moving Boundaries Using R (AMBUR), since it is a robust and powerful tool, the complexity and heavy processes can restrict the accessibility and simple usage. The validation methodology consists of applying the EPR4Q, DSAS, and AMBUR on different examples of shorelines found in nature, extracted from the U.S. Geological Survey Open-File. The obtained results of each tool were compared with Pearson correlation coefficient. The validation results indicate that the EPR4Q tool created acquired high correlation values with DSAS and AMBUR, reaching a coefficient of 0.98 to 1.00 on linear, extensive, and non-extensive shorelines, guarantying that the EPR4Q tool is ready to be freely used by the academic, scientific, engineering, and coastal managers communities worldwide.

Context: Code smells are associated with poor design and programming style that often degrades code quality and hampers code comprehensibility and maintainability. Goal: Identify reports from the literature that provide evidence of the influence of code smells on the occurrence of software bugs. Method: We conducted a Systematic Literature Review (SLR) to reach the~stated goal. Results: The SLR includes selected studies from July 2007 to September 2017 which analyzed the source code for open source and proprietary projects, as well, as several code smells and anti-patterns. The results of this SLR show that 24 code smells are more influential in the occurrence of bugs according to 16 studies. In contrast, three studies reported that at least 6 code smells are less influential in such occurrences. Evidence from the selected studies also point out tools, techniques and procedures applied to analyze the influence. Conclusion: To the best of our knowledge, this is the first SLR to target this goal. This study provides an up-to-date and structured understanding of the influence of code smells on the occurrence of software bugs based on findings systematically collected from a list of relevant references in the latest decade.

In this paper, we study the problem of controllability of impulsive neutral evolution integrodifferential equations with state dependent delay in Banach spaces. The main results are completely new and are obtained by using Sadovskii's fixed point theorem, theory of resolvent operators, and an abstract phase space. An example is given to illustrate the theory.

The most widespread intracellular bacteria in the animal kingdom are maternally-inherited endosymbionts of the genus Wolbachia. Their prevalence in arthropods and nematodes worldwide and a stunning arsenal of parasitic and mutualistic adaptations make these bacteria a biological archetype for basic studies of symbiosis and applied outcomes for curbing human and agricultural diseases. Here, we conduct a summative, centennial analysis of living in the Wolbachia world. We synthesize literature on Wolbachia’s host range, phylogenetic diversity, genomics, cell biology, and applications to filarial, arboviral, and agricultural diseases. We also review the mobilome of Wolbachia including phage WO and its essentiality to hallmark phenotypes in arthropods. Finally, the Wolbachia system is an exemplar for discovery-based science education using biodiversity, biotechnology, and bioinformatics lessons. As we approach a century of Wolbachia research, applications, and education, the interdisciplinary science and knowledge from this symbiosis stand as a model for consolidating and teaching the integrative rules of endosymbiotic life.

Currently there is little doubt left on the symbiogenetic nature of eukaryotes - genomes of archaeon and bacterium participated in shaping a genome of last eukaryotic common ancestor in equal albeit asymmetric manner, while a merger event itself indicated the advent of a new domain of life. The “symbiogenetic” framework of interaction of two partners is proposed, outlining similar steps essential for three major advents: the origin of life, the origin of complex life and the origin of humans. Given the immense importance of proper energy source for the evolution of life it seems plausible that for any principal increase in complexity, a partnership with a novel energy donor is required. Moreover, a “language” elaborated in the course of communication of partners might have been a prerequisite for a subsequent increase in complexity. Transitions, which led to RNA-protein world, eukaryotes and human brain, resulted in advent of complex languages via communication onsets between two entities in close partnership. Accordingly this further facilitated formation of first cells, multicellular organisms and human society.

Chironomus riparius is a well-established model organism in various fields such as ecotoxicology and ecology, and therefore environmental preferences, ecological interactions and metabolic traits are well-studied. With the recent publication of a high-quality draft genome, as well as different population genetic parameters such as mutation and recombination rate, the species can be used as an alternative to the Drosophila models in experimental population genomics or molecular ecology. To facilitate access to this promising experimental model species for a wider range of researchers, we describe experimental methods to first create and sustain long term cultures of C. riparius and then use them to perform repeatable and comparable experiments for various research questions.

The challenge posed by multi-drug resistance (MDR) of pathogenic organisms, spectacularly manifested in the 6 “ESKAPE” bacterium (two Gram-positive, four Gram-negative) species, should invoke new comprehensive strategies, and needs cooperation of scientists with medical, veterinary and natural science background. This review is aimed at informing newcomers, coming from the field of biology and genetics, about problems related to rapidly emerging, new multi-drug resistant, pathogenic, bacteria. Unlike persistence, the antibiotic resistance is inherited. A functioning “resistance gene” makes a susceptible organism resistant to a given antibiotic, encoding for polypeptides capable of acting either as decomposing enzymes, or acting as trans-membrane pumps, or membrane structure components capable of modifying the permeability implementing a «by pass» mechanism enabling the antibiotic molecule to reach its cellular target(s). A functioning “sensitivity gene” encode for a polypeptide, capable (directly or indirectly) of transferring toxic molecules into target cells, or of metabolizing non-transferable to transferable, or non-toxic molecules to toxic derivatives. A gene of a normal function could act as a “sensitivity” gene in the presence of antibiotics of chemical structures similar to the natural substrate of the gene product, (enzyme or binding/ trans-membrane protein). The Agrocin 84 story is a good example. Multi-drug resistance is a phenotypic consequence of the sequential accumulation of mutations, and/or up-take of plasmids or genomic islands carrying resistance genes from the environment via horizontal gene transfer, mediated by conjugative plasmid or bacteriophage carrying mobile genetic elements. Both multi-drug resistance and collateral sensitivity are evolutionary products. Some revealed evolutionary process and their Lamarckian and Darwinian interpretations are discussed. Toolkits of comparative full-genome sequencing, genomics, experimental evolution and population genetics may provide perspectives for overcoming the invincibility of multi-drug panresistance. The status of some recently emerging pathogenic bacterium species with zoonic features and of veterinary background is also discussed.

We propose a Gauss model (GM), a map from time to the bell-shaped Gauss function to model the deaths per day and country, as a quick and simple model to make predictions on the coronavirus epidemic. Justified by the sigmoidal nature of a pandemic, i.e. initial exponential spread to eventual saturation, we apply the GM to existing data, as of April 2, 2020, from 25 countries during first corona pandemic wave and study the model's predictions. We find that logarithmic daily fatalities caused by Covid-19 are well described by a quadratic function in time. By fitting the data to second order polynomials from a statistical chi2-fit with 95\% confidence, we are able to obtain the characteristic parameters of the GM, i.e. a width, peak height and time of peak, for each country separately, with which we extrapolate to future times to make predictions. We provide evidence that this supposedly oversimplifying model might still have predictive power and use it to forecast the further course of the fatalities caused by Covid-19 per country, including peak number of deaths per day, date of peak, and duration within most deaths occur. While our main goal is to present the general idea of the simple modeling process using GMs, we also describe possible estimates for the number of required respiratory machines and the duration left until the number of infected will be significantly reduced.

Brain metastases are highly evolved manifestations of breast cancer arising in a unique microenvironment, giving them exceptional adaptability in the face of new extrinsic pressures. The incidence is rising in line with population ageing, and use of newer therapies that stabilise metastatic disease burden with variable efficacy throughout the body. Historically, there has been a widely held view that brain metastases do not respond to circulating therapeutics because the blood-brain-barrier (BBB) restricts their uptake. However, emerging data are beginning to paint a far more complex picture where the brain acts as a sanctuary for dormant, subclinical proliferations that are initially protected by the BBB, but then exposed to dynamic selection pressures as tumours mature and vascular permeability increases. Here, we review key experimental approaches and landmark studies that have charted the genomic landscape of breast cancer brain metastases. These findings are contextualised with the factors impacting on clonal outgrowth in the brain: intrinsic breast tumour cell capabilities required for brain metastatic fitness, and the neural niche, which is initially hostile to invading cells but then engineered into a tumour-support vehicle by the successful minority. We also discuss how late detection, abnormal vascular perfusion and interstitial fluid dynamics underpin the recalcitrant clinical behaviour of brain metastases, and outline active clinical trials in the context of precision management.

Research in various fields of evolutionary biology has shown that divergence in gene expression is a key driver for phenotypic variation. An exceptional contribution of cis-regulatory evolution has for instance been found to contribute to morphological diversification. In the light of these findings, the analysis of genome-wide expression data has become one of the central tools to link genotype and phenotype information on a more mechanistic level. However, in many studies, especially if general conclusions are drawn from such data, a key feature of gene regulation is often neglected. With our article, we want to raise awareness that gene regulation and thus gene expression is highly context dependent. Genes show tissue- and developmental stage-specific expression. We argue that the regulatory context must be considered when studying evolution of gene expression.

Cannabis is among the oldest human domesticates and has been subjected to intensive artificial (human-mediated) selection throughout history to create a wide array of varieties and biotypes for diverse uses, including fibre, food, biofuel, medicine and drugs. This paper briefly reviews the available literature on the taxonomy, evolutionary origin and domestication of this plant, as well as its worldwide dispersal, in both its wild and cultivated forms. Emphasis is placed on Europe and especially on the Iberian Peninsula. Today, it is accepted that Cannabis is a monospecific genus with two subspecies, C. sativa subsp. sativa and C. sativa subsp. indica, originating in Europe and Asia, respectively, by allopatric differentiation after geographic isolation fostered by Pleistocene glacial-interglacial cycles. Palynological and phylogeographic evidence situates the Cannabis ancestor on the NE Tibetan Plateau during the mid-Oligocene. The timing and place of domestication is still a matter of debate between contrasting views that defend single or multiple Neolithic domestication centres situated in different parts of the Eurasian supercontinent, notably central/southeastern China and the Caucasus region. Recent meta-analyses have suggested that wild Cannabis may have already been spread across Europe in the Pleistocene, and its domestication could have occurred during the European Copper/Bronze ages. According to the available reviews and meta-analyses, pre-anthropic dispersal of Cannabis into the Iberian Peninsula seems to have occurred only in postglacial times, and the earlier signs of cultivation date to the Early Medieval Ages. However, the palynological and archaeological evidence used to date is insufficient for a sound assessment, and the development of thorough Iberian databases to address further meta-analysis is essential for more robust conclusions. Some clues are provided for these achievements to be fulfilled.

A basic problem in all postulated pathways of prebiotic chemistry is the low concentration which generally is expected for interesting reactants in fluid environments. Even though compounds like nucleobases, sugars or peptides principally may form spontaneously under environmental conditions, they will always be rapidly diluted in an aqueous environment. In addition, any such reaction leads to side products which often exceed the desired compound and generally hamper the first steps of a subsequent molecular evolution. Therefore, a mechanism of selection and accumulation of relevant prebiotic compounds seems to be crucial for molecular evolution. A very efficient environment for selection and accumulation can be found in the fluid continuum circulating in tectonic fault zones. Vesicles which form spontaneously at a depth of approximately 1 km present a selective trap for amphiphilic molecules, especially for peptides composed of hydrophilic and hydrophobic amino acids in a suitable sequence. The accumulation effect is shown in a numeric simulation on a simplified model. Further, possible mechanisms of a molecular evolution in vesicle membranes are discussed. Altogether, the proposed scenario can be seen as an ideal environment for constant, undisturbed molecular evolution in and on cell-like compartments, the latter offering preferential starting conditions for a subsequent RNA world.

Evolutionary convergence provides natural opportunities to investigate how, when, and why novel traits evolve. Many convergent traits are complex, highlighting the importance of explicitly considering convergence at different levels of biological organization, or ‘multi‐level convergent evolution’. To investigate multi‐level convergent evolution, we propose a holistic and hierarchical framework that emphasizes breaking down traits into several functional modules. We begin by identifying long‐standing questions on the origins of complexity and the diverse evolutionary processes underlying phenotypic convergence to discuss how they can be addressed by examining convergent systems. We argue that bioluminescence, a complex trait that evolved dozens of times through either novel mechanisms or conserved toolkits, is particularly well suited for these studies. We present an updated estimate of at least 94 independent origins of bioluminescence across the tree of life, which we calculated by reviewing and summarizing all estimates of independent origins. Then, we use our framework to review the biology, chemistry, and evolution of bioluminescence, and for each biological level identify questions that arise from our systematic review. We focus on luminous organisms that use the shared luciferin substrates coelenterazine or vargulin to produce light because these organisms convergently evolved bioluminescent proteins that use the same luciferins to produce bioluminescence. Evolutionary convergence does not necessarily extend across biological levels, as exemplified by cases of conservation and disparity in biological functions, organs, cells, and molecules associated with bioluminescence systems. Investigating differences across bioluminescent organisms will address fundamental questions on predictability and contingency in convergent evolution. Lastly, we highlight unexplored areas of bioluminescence research and advances in sequencing and chemical techniques useful for developing bioluminescence as a model system for studying multi‐level convergent evolution.

A novel coronavirus COVID-19 was first emerged in Wuhan city of Hubei Province in China in December 2019. The COVID-19, since then spreads to 213 countries and territories, and has become a pandemic. Genomic analyses have indicated that the virus, popularly named as corona, originated through a natural process and is probably not a purposefully manipulated laboratory construct. However, currently available data are not sufficient to precisely conclude the origin of this fearsome virus. Genome-wide annotation of thousands of genomes revealed that more than 1,407 nucleotide mutations and 722 amino acids replacements occurred at different positions of the SARS-CoV-2. The spike (S) glycoprotein of SARS-CoV-2 possesses a functional polybasic (furin) cleavage site at the S1-S2 boundary through the insertion of 12 nucleotides. It leads to the predicted acquisition of 3-O-linked glycan around the cleavage site. Although real-time RT-PCR methods targeting specific gene(s) have widely been used to diagnose the COVID-19 patients, however, recently developed more convenient, rapid, and specific diagnostic tools targeting IgM/IgG or newly developed plug and play methods should be available for resource-poor developing countries. Some drugs, vaccines and therapies have shown great promise in early trials, however, these candidates of preventive or therapeutic agents have to pass a long path of trials before being released for the practical application against COVID-19. This review updates current knowledge on origin, genomic evolution, development of the diagnostic tools and the preventive or therapeutic remedies of the COVID-19, and discusses on scopes for further research and effective management and surveillance of COVID-19.

The crucial stages in the geochemical evolution of the Earth’s crust, ocean, and atmosphere could be explained by the assumed low-energy nuclear reactions (LENR) that are triggered by seismic activity. LENR result in the fission of medium-weight elements accompanied by neutron emissions, involving Fe and Ni as starting elements, and C, N, O as resultants. Geochemical data and experimental evidences support the LENR hypothesis. A spectral analysis of the period 1955-2013 shows common cycles between interannual changes in atmospheric CO2 growth rate and global seismic-moment release, whereas the trending behavior of the atmospheric CO2 was in response to the anthropogenic emissions. Assuming a correlation between such seismic and atmospheric fluctuations, the latter could be explained by cycles of worldwide seismicity, which would trigger massively LENR in the Earth’s Crust. In this framework, LENR from active faults could be considered as a relevant cause of carbon formation and degassing of freshly-formed CO2 during seismic activity. However, further studies are necessary to validate the present hypothesis which, at the present time, mainly aims to stimulate debate on the models which regulates atmospheric CO2.

Bottom-up synthesis of porous NiMo alloy reduced by NiMoO₄ nanofibers was systematically investigated to fabricate non-noble metal porous electrodes for hydrogen production. The different annealing temperatures of NiMoO₄ nanofibers under hydrogen atmosphere reveal that the 950 °C annealing temperature is a key to produce bicontinuous porous NiMo alloy without oxide phases. The porous NiMo alloy as cathodes in electrical water splitting demonstrates not only almost identical catalytic activity with commercial Pt/C in 1.0 M KOH solution, but also superb stability for 12 days at an electrode potential of −200 mV (v.s. RHE).

Nervous systems evolved around 560 million years ago to coordinate and empower animal bodies. Ctenophores – one of the earliest-branching lineages – are thought to share few neuronal genes with bilaterians and may have evolved neurons convergently. Here we review our current understanding of the evolution of neuronal molecules in non-bilaterians. We also reanalyse single-cell sequencing data in light of new cell-cluster identities from a ctenophore and uncover evidence supporting the homology of one ctenophore neuron-type with neurons in Bilateria. The specific coexpression of the presynaptic proteins Unc13 and RIM with voltage-gated channels, neuropeptides and homeobox genes pinpoint a spiking sensory-peptidergic cell in the ctenophore mouth. Similar Unc13-RIM neurons may have been present in the first eumetazoans to rise to dominance only in stem Bilateria. We hypothesize that the Unc13-RIM lineage ancestrally innervated the mouth and conquered other parts of the body with the rise of macrophagy and predation during the Cambrian explosion.

Arthropods are the most abundant and diverse animals on earth. Among them, pancrustaceans are an ancient and morphologically diverse group, comprising a wide range of aquatic and semi-aquatic crustaceans as well as the insects, which emerged from crustacean ancestors to colonise most terrestrial habitats. Within insects, Drosophila stands out as one of the most powerful animal models, making major contributions to our understanding of development, physiology and behaviour. Given these attributes, crustaceans provide a fertile ground for exploring biological diversity through comparative studies. However, beyond insects, few crustaceans are developed sufficiently as experimental models to enable such studies. The marine amphipod Parhyale hawaiensis is currently the best established crustacean system, offering year-round accessibility to developmental stages, transgenic tools, genomic resources, and established genetics and imaging approaches. The Parhyale research community is small but diverse, investigating the evolution of development, regeneration, aspects of sensory biology, chronobiology, bioprocessing and ecotoxicology.

Information has been and will be a vital element for a person or department groups in an organization. That is why there are technologies that help us to give them the proper management of data; Business Intelligence is responsible for bringing technological solutions that correctly and effectively manage the entire volume of necessary and important information for companies. Among the solutions offered by Business Intelligence are Data Warehouses, Data Mining, among other business technologies that working together achieve the objectives proposed by an organization. It is important to highlight that these business technologies have been present since the 50's and have been evolving through time, improving processes, infrastructure, methodologies and implementing new technologies, which have helped to correct past mistakes based on information management for companies. There are questions about Business Intelligence. Could it be that in the not-too-distant future it will be used as an essential standard or norm in any organization for data management, since it provides many benefits and avoids failures at the time of classifying information. On the other hand, Cloud storage has been the best alternative to safeguard information and not depend on physical storage media, which are not 100% secure and are exposed to partial or total loss of information, by presenting hardware failures or security failures due to mishandling that can be given to such information.

Maximum entropy production principle (MEPP) has been formulated in the mid-twentieth century, and today it has acquired the status of an important principle of science, which is extremely effective in considering various non-equilibrium problems. In this study, for the first time, definition of life is based on an easily measurable physical quantity that is entropy production. Life and evolution are discussed from the point of view of MEPP and the Universe, but not a human

Nearly 50 years ago, Francis Crick propounded the frozen accident scenario for the evolution of the genetic code along with the hypothesis that the early translation system consisted primarily of RNA. Under the frozen accident perspective, the code is universal among modern life forms because any change in codon assignment would be highly deleterious. The frozen accident can be considered the default theory of code evolution because it does not imply any specific interactions between amino acids and the cognate codons or anticodons, or any particular properties of the code. The subsequent 49 years of code studies have elucidated notable features of the standard code, such as high robustness to errors, but failed to develop a compelling explanation for codon assignments. In particular, stereochemical affinity between amino acids and the cognate codons or anticodons does not seem to account for the origin and evolution of the code. Here I expand Crick’s hypothesis on RNA-only translation system by presenting evidence that this early translation already attained high fidelity that allowed protein evolution. I outline an experimentally testable scenario for the evolution of the code that combines a distinct version of the stereochemical hypothesis, in which amino acids are recognized via unique sites in the tertiary structure of proto-tRNAs, rather than by anticodons, expansion of the code via proto-tRNA duplication and the frozen accident.

To cope with a projected global population increase from 7.2 bn to 9.6 bn by 2050, many more cities must be built. Although there are great benefits to modern urban living, there also great costs, such as the seemingly unstoppable rise in Type 2 diabetes, obesity, coronary issues and various cancers. The new towns should be designed to contain or constrain the epidemic of those ‘Western Lifestyle Diseases’ that currently plagues today’s cities. But how might this be achieved? It is suggested here that a greater understanding of human evolution combined with the potency of the ‘Palaeolithic genome’ holds the key to our future urban wellbeing. Consequently, a new paradigm is suggested that underpins positive forward thinking on townplanning and city lifestyles to create healthier urban environments. This builds directly on the ‘Evolutionary Determinants of Health’ programme initiated at University College London (UCL). A four-stage model is proposed that integrates and develops both evolutionary-concordant personal and institutional health behaviours with appropriately reconfigured town-planning and building regulations. When integrated, these strands could deliver a healthier urban culture within greened, active townscapes by proactively constraining or eliminating some of the key underlying causes of the so-called ‘Western Lifestyle Diseases’.

Semi-solid feedstock of AZ80 magnesium alloy modified by minor rare-earth Y element (0, 0.2, 0.4, 0.8 wt.%) were fabricated by strain induces melting activated (SIMA) in the form of extrusion and partial remelting. The effect of Y addition on the microstructure evolution of extruded and isothermal treated alloy was observed by optical microscope (OM), scanning electron microscope (SEM), X-ray diffraction (XRD) and quantitative analysis. The results show that the Y addition can refine the microstructure and make the β-Mg17Al12 phases agglomerating. During the subsequent isothermal treatment at 570℃, the average solid grain size, shape factor and liquid fractions increased with prolonged soaking time. Smaller spheroidal solid grains and the larger shape factor were obtained due to Y addition. The coalescence and Ostwald ripening of solid grains operated the coarsening process simultaneously. The coarsening rate constants of AZ80M1 (0.2 wt.% Y addition) of 164.22 μm3s-1 was approximately four times less than the un-modified AZ80 alloy of 689.44 μm3s-1. In contrast, the desirable semi-solid structure featured by fine, well globular solid grains and appropriate liquid fractions and shape factor was achieved in AZ80M1 alloy treated at 570℃ for 20-30 min.

We tested the hypothesis that concatemers of ancestral tRNAs gave rise to the 16S ribosomal RNA. We built an ancestral sequence of proto-tRNAs that showed a significant identity of 51.69% and a percentage of structural identity of 0.941 with the 16S ribosomal molecule. We also propose a hypothesis for the emergence of translation.

The stele concept is one of the oldest enduring concepts in plant biology. This paper reviews the concept and its foundations, and builds an argument for an updated view of steles and their evolution. The history of studies of stelar organization has generated a widely ranging array of definitions of the stele that determine the way we classify steles and construct scenarios about the evolution of stelar architecture. Because at the level of the organism biological evolution proceeds by, and is reflected in, changes in development, concepts of structure need to be grounded in development in order to be relevant in an evolutionary perspective. For the stele, most of the traditional definitions that incorporate development have viewed it as the totality of tissues that either originate from procambium – currently the prevailing view – or are bordered by a boundary layer (e.g., endodermis). A definition of the stele that would bring consensus between these perspectives recasts the stele as a structural entity of dual nature. Here, I review briefly the history of the stele concept, basic terminology related to stelar organization, and traditional classifications of the steles. I then revisit boundary layers from the perspective of histogenesis as a dynamic mosaic of developmental domains. I use classic and recent anatomical and molecular data to reaffirm and explore the importance of boundary layers for stelar organization. Drawing on data from comparative anatomy, developmental regulation, and the fossil record, I offer a model for a stele concept that integrates both the boundary layer and the procambial perspective, consistent with a dual nature of the stele. The dual stele model posits that stelar architecture is determined in the apical meristem by two major cell fate specification events: a first one that specifies a provascular domain and its boundaries, and a second event that specifies a procambial domain (which will mature into conducting tissues) from cell subpopulations of the provascular domain. If the position and extent of the developmental domains defined by the two events are determined by different concentrations of the same morphogen (most likely auxin), then the distribution of this organizer factor in the shoot apical meristem, as modulated by changes in axis size and the effect of lateral organs, can explain the different stelar configurations documented among tracheophytes. This model provides a set of working hypotheses that incorporate assumptions and generate implications that can be tested empirically. The model also offers criteria for an updated classification of steles that is in line with current understanding of plant development. In this classification, steles fall into two major categories determined by the configuration of boundary layers – boundary protosteles and boundary siphonosteles, each with subtypes defined by the architecture of the vascular tissues. Validation the dual stele model and, more generally, in-depth understanding of the regulation of stelar architecture, will necessitate targeted efforts in two areas: (i) the regulation of procambium, vascular tissue, and boundary layer specification in all extant vascular plants, considering that most of the diversity in stelar architecture is hosted by seed-free plants, which are the least explored in terms of developmental regulation; (ii) the configuration of vascular tissues and, especially, boundary layers, in as many extinct species and lineages as possible.

Exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access network. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC). In this work, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research.

Polycystic ovary syndrome (PCOS) is increasingly recognized as a complex metabolic disorder that manifests in genetically susceptible women following a range of negative exposures to nutritional and environmental factors related to contemporary lifestyle. The hypothesis that PCOS phenotypes are derived from a mismatch between ancient genetic survival mechanisms and modern lifestyle practices is supported by a diversity of research findings. The proposed evolutionary model of the pathogenesis of PCOS incorporates evidence related to evolutionary theory, genetic studies, in-utero developmental epigenetic programming, transgenerational inheritance, metabolic features including insulin resistance, obesity and the apparent paradox of lean phenotypes, reproductive effects and subfertility, the impact of the microbiome and dysbiosis, endocrine disrupting chemical exposure, and the influence of lifestyle factors such as poor quality diet and physical inactivity. Based on these premises, the diverse lines of research are synthesized into a composite evolutionary model of the pathogenesis of PCOS. It is hoped that this model will assist clinicians and patients to understand the importance of lifestyle interventions in the prevention and management of PCOS and provide a conceptual framework for future research. It is appreciated that this theory represents a synthesis of the current evidence and that it is expected to evolve and change over time.

We show that low quality of all 427 Brazilian SARS-CoV-2 genomes recently published in Science (1) challenges their phylogenetic inference and may lead to incorrect typing of viral strains in clades with no statistical support. Absence of basecalling quality in genome assemblies and proper phylogeny parameter estimates preclude the assessment of signal-to-noise ratio in the data, downstream analysis and conclusions.

The present review provides an in-depth look into the complex topic of delimiting species in sea anemones. For most part of history this has been based on a small number of variable anatomic traits, many of which are used indistinctly across multiple taxonomic ranks. Early attempts to classify this group succeeded to comprise much of the diversity known to date, yet numerous taxa were mostly characterized by the lack of features rather than synapomorphies. Of the total number of species names within Actiniaria, about 77% are currently considered valid and more than half of them have several synonyms. Besides the nominal problem caused by large intraspecific variations and ambiguously described characters, genetic studies show that morphological convergences are also widespread among molecular phylogenies. On the contrary, spatial distribution has been emerging as a more reliable parameter to explain cryptic relationships among sea anemones. Integrative approaches and genome-wide data have been especially helpful to unveil the mechanisms behind the speciation process, which is typically marked by large genetic differences among populations, even from neighbouring localities. This paper further discusses current gaps in our knowledge and offers some future directions on how to address the issue of species delimitation in the extremely polymorphic group of sea anemones.

The electronic structure and the participation of the simplest azomethine imine (AI) in [3+2] cycloaddition (32CA) reactions have been analysed within the Molecular Electron Density Theory (MEDT) using DFT calculations at the MPWB1K/6-311G(d) level. Electron localisation function (ELF) topological analysis reveals that AI has a pseudoradical structure, while the conceptual DFT reactivity indices characterise this TAC as a moderate electrophile and a good nucleophile. The non-polar 32CA reaction of AI with ethylene takes place through a one-step mechanism with low activation energy, 5.3 kcal/mol-1. A bonding evolution theory (BET) study indicates that this reaction takes place through a non-concerted [2n+2τ] mechanism in which the C–C bond formation is clearly anticipated prior to the C–N one. On the other hand, the polar 32CA reaction of AI with dicyanoethylene takes place through a two-stage one-step mechanism. Now, the more favourable regioisomeric transition state structure (TS) is located 8.5 kcal•mol⁻¹ below the reagents, in complete agreement with the high polar character of the TS. The current MEDT study makes it possible to extend Domingo’s classification of 32CA reactions to a new pra-type of reactivity.

We report here a giant microfossil resembling the conidium of an ascomycete fungus (cf. Alternaria alternata). The specimen is preserved in stromatolitic black chert of the Gunflint Iron Formation (Paleoproterozoic Eon, Orosirian Period, ca. 1.9-2.0 Ga) of southern Ontario, Canada, and the rock that provided the thin section may have been collected by Elso Barghoorn as part of the original discovery of the Gunflint microbiota. The large size of the fossil sets it apart from other, tiny by comparison, Gunflint microfossils. The fossil is 200 microns in length and has cross walls. Individual cells are 30-46 microns in greatest dimension. The apical ‘spore’ is cap-shaped, and has partly separated from the rest of the structure. Cloulicaria gunflintensis gen. nov. sp. nov. may provide early evidence for eukaryotes (fungi) in the fossil record, and may also represent the earliest evidence for asexual reproduction in a eukaryote by means of mitospores.

Analysis of Fatigue Strain, Fatigue Modulus and Fatigue Damage for the modeling of concrete plays a vital role in the evolution material behaviour which is heterogeneous and anisotropic in nature. In this paper, the Level-S nonlinear fatigue strain curve, fatigue modulus curve, residual strain curve of concrete in compression, tension, flexure and torsional fatigue loading were proposed using strain life approach. The parameters such as physical meaning, the ranges, and the impact on the shape of the curve were discussed. Then, the evolution model of fatigue modulus was established based on the fatigue strain evolution model, fatigue modulus evaluation model, residual strain evaluation model, secondary strain evaluation model. The hypothesis of fatigue modulus is inversely related with the fatigue strain amplitude. The fatigue evolution of concrete damages the bond between material grains, changed the orientation of structure of molecules and affects the elastic properties resulting in the reduction of material stiffness and modulus by utilizing strain life analysis, regarding stiffness degradation and inelastic deformation by formation of microcracking, macro cracking, cracking which is heterogeneous and anisotropic in nature . This paper presents the Fatigue Strain Life Model and analyses of fatigue strain, fatigue modulus and damage parameters of concrete which is capable of predicting stiffness degradation, inelastic deformation, strength reduction under fatigue loading. Hence, the obtainable results were compared with experimental results for the validation of the proposed model.

The exponential growth of biomedical data in recent years urged the application of numerous machine learning techniques to address emerging problems in biology and clinical research. By enabling automatic feature extraction, selection and generation of predictive models, these methods can be used to efficiently study complex biological systems. Machine learning techniques are frequently integrated with bioinformatic methods, as well as curated databases and biological networks, to enhance training and validation, identify the best interpretable features, and enable feature and model investigation. Here, we review recently developed methods that incorporate machine learning within the same framework with techniques from molecular evolution, protein structure analysis, systems biology and disease genomics. We outline the challenges posed for machine learning, and in particular, deep learning in biomedicine and suggest unique opportunities for machine learning techniques integrated with established bioinformatics approaches to overcome some of these challenges.

Biological technologies are fundamentally unlike any other because biology evolves. Bioengineering therefore requires novel design methodologies with evolution at their core. Knowledge about evolution is currently applied to the design of biosystems ad hoc. Unless we have a unified engineering theory of evolution, we will neither be able to meet evolution’s potential as a design tool, nor understand or limit its unintended consequences on our designs. Our concept of the evotype offers a conceptual framework for engineering the evolutionary potential of biosystems. We show how a biosystem’s evolutionary properties might be rationally designed by engineering aspects of genetic variation, designed function, and natural selection. This idea could apply to all biosystems – from individual proteins to communities of whole-cells or even entire ecosystems – whether the goal is to direct evolution in the design process, or to limit its impacts during application. These principles could even be used beyond the realm of bioengineering to design entirely synthetic evolving auto-adaptive technologies.

Different factors seemingly account for the emergence of present-day languages in our species. Human self-domestication has been recently invoked as one important force favouring language complexity mostly via a cultural mechanism. As a consequence, evolutionary changes impacting on aggression levels are expected to have fostered this process. Here we hypothesise about a positive effect of dog-human interactions on aggression management and more generally, on our self-domestication, ultimately, contributing to aspects of language evolution. We review evidence of diverse sort (ethological mostly, but also archaeological, genetic, and physiological) supporting a positive feedback loop between dog domestication and human-self domestication that might have favoured the mechanisms promoting structural complexity in human languages.

Water electrolysis provides efficient and cost-effective production of hydrogen from renewable energy. Currently, the oxidation half-cell reaction relies on noble-metal catalysts, impeding widespread application. In order to adopt water electrolyzers as the main hydrogen production systems, it is critical to develop inexpensive and earth-abundant catalysts. This review discusses the proton exchange membrane (PEM) water electrolysis (WE) and the progress in replacing the noble-metal catalysts with earth-abundant ones. Researchers within this field are aiming to improve the efficiency and stability of earth-abundant catalysts (EACs), as well as to discover new ones. The latter is particularly important for the oxygen evolution reaction (OER) under acidic media, where the only stable and efficient catalysts are noble-metal oxides, such as IrO_x and RuO_x. On the other hand, there is significant progress on EACs for the hydrogen evolution reaction (HER) in acidic conditions, but how many of these EACs have been used in PEM WEs and tested under realistic conditions? What is the current status on the development of EACs for the OER? These are the two main questions this review addresses.

The evolution of manual grooming and its implications have received little attention in the quest to understand the origins of simian primates and their social and technical intelligence. All simians groom manually, whereas prosimians groom orally despite comparable manual dexterity between some members of the two groups. Simians also exhibit a variable propensity for the manipulation of inanimate, non-food objects, which has culminated in tool making and tool use in some species. However, lemuriform primates also seem capable of tool use with training. Furthermore, lemuriforms appear to understand the concept of a tool and use their own body parts as “tools”, despite not using inanimate objects. This suggests that prosimian primates are pre-adapted for proprioceptive object manipulation and tool use, but do not express these cognitive abilities by default. This essay explores the paleontological, anatomical, cognitive, ethological, and neurological roots of these abilities and attempts to explain this behavioural divide between simians and prosimians. Common misconceptions about early primate evolution and captive behaviours are addressed, and chronological inconsistencies with Machiavellian Intelligence are examined. A “licking to picking” hypothesis is also proposed to explain a potential link between manual grooming and object manipulation, and to reconcile the inconsistencies of Machiavellian Intelligence. Bayesian decision theory, the evolution of the parietal cortex and enhanced proprioception, and analogies with behavioural changes resulting from artificial selection may help provide new insights into the minds of both our primate kin and ourselves.

As a special class of “green” elastomers, thermoplastic vulcanizates (TPVs) have been widely used in industries due to the combination of the excellent resilience of conventional elastomers and the easy recyclability of thermoplastics. Here, the morphology evolution of TPVs based on polyamide 6/ethylene-propylene-diene rubber (PA6/EPDM) blends was investigated by varying the content of the curing agent, phenolic resin (PF). With the incorporation of 6 wt% PF, the gel content of the EPDM phase reaches a high value of 49.6wt% and a typical sea-island structure is formed with EPDM domain in a micro-nano size. The dynamic rheology behaviors of TPVs showed that with the curing degree of EPDM phase increasing, a denser network of EPDM particles is formed in PA6 matrix. Also, a lower crystal degree and crystal peak temperature are observed, indicating that the presence of a growth restriction of PA6 crystal plate induced by a thinner plastic layer between the adjacent EPDM particles. However, the crystal form of PA6 is not changed with the increasing curing degree of the EPDM phase. This study provides an effective strategy to realize a new kind of TPVs, which can be easily introduced into industrial applications.

Transposable elements (TEs) ubiquitously exist in the human genome, and some have the ability to copy and paste themselves to other locations, resulting in new insertions. Organisms have evolved with mechanisms and machineries to repress such activity. TEs are also co-opted for beneficial functions by the host and are thus maintained in the genome. During the lifetime of humans, aberrant TE activity might cause or contribute towards diseases including neurological conditions such as Alzheimers Disease (AD) and cancer. While inflammatory pathways linked to TEs may be a part of the disease pathology, on the other hand altered TE activity involving inflammatory pathways could be recognised by disease suppression mechanisms. For this reason, TEs could be targeted for therapeutic applications aiming to prevent TE activity or reduce initial inflammatory pathways as well as to activate disease suppression mechanisms. In this review, we describe the contributory and potential preventative roles of TEs in neurological conditions and cancer from a molecular and evolutionary perspective. Evolutionary paradigms both at the unicellular and organismal level aid understanding the role of TEs in disease. These observations could pave the way for the development of novel therapeutic approaches targeting TEs.

B chromosomes (B) are supernumerary elements found in many taxonomic groups. Most B chromosomes are rich in heterochromatin and composed of abundant repetitive sequences, especially transposable elements (TEs). Bs origin is generally linked to the A chromosome complement (A). The first report of a B chromosome in African cichlids was on Astatotilapia latifasciata, which can harbor 0, 1 or 2 B chromosomes. Classical cytogenetics studies found high TE content on the species B chromosome. In this study, we aim to understand TE composition and expression on A. latifasciata genome and its relation to the B chromosome. We use bioinformatics analysis to explore TEs genome organization and also their composition on the B chromosome. Bioinformatics findings were validated by fluorescent in situ hybridization (FISH) and real-time PCR (qPCR). A. latifasciata has a TE content similar to other cichlid fishes and several expanded elements on its B chromosome. With RNA sequencing data (RNA-seq) we showed that all major TE classes are transcribed in brain, muscle and male/female gonads. The evaluation of TE expression between B- and B+ individuals showed that few elements have differential expression among groups and expanded B elements were not highly transcribed. Putative silencing mechanisms may the acting on the B chromosome of A. latifasciata to prevent adverse consequences of repeat transcription and mobilization in the genome.

Socio-demography of statuses reflects the demographic and social roles and achievements of an individual(s) in a population. In the theoretical frameworks, little was known about the theory, analytical measures, and evolutionary mechanism of the socio-demographics of statuses of an individual(s). In this paper, three (3) methodological issues regarding the concept of socio-demographics were proposed, these are: (a) identified the basic features that clarify our understanding about the conception of the socio-demographic statuses of an individual(s) as common, universal, and desirable positions, achievements, and advantages every individual strives and competes to attain, achieve, maintain, update, and upgrade which are determined by biological and social environments, driven and regulated by a continuum of competitions and natural selections; (b) presented a new paradigm of analytical measures of an individual’s socio-demographic statuses and the established hierarchical transitions; (c) proposed theoretical assumptions for the evolution of a socio-demographically unique population. Seven (7) factors (the driving forces) and eight (8) conditions responsible for the evolution of socio-demographically unique populations were identified and explained. The evolutionary transitions were organized into six (6) socio-demographic ranks.

Proton exchange membrane water electrolyzers (PEMWEs) for water electrolysis have received tremendous attention due to their immediate response, high proton conductivity, low ohmic losses and gas crossover rate. However, design high activity, economical and long-term durable electrocatalysts in an acidic environment is still the bottleneck to realize the large-scale commercialization of PEMWEs. Iridium-based materials represent one of the most promising classes of oxygen evolution reaction (OER) catalysts due to their intrinsic stability in acid media over ruthenium-based counterparts. However, only a few innovative approaches have been developed to synthesizing iridium-based catalysts (IBCs) in the past decade, mainly due to achieving high activity may deteriorate the stability of IBCs. Accordingly, various engineering strategies of optimizing IBCs have been proposed to address this issue, including doping engineering, morphology engineering, crystal phase engineering and support engineering. Herein, a critical overview focusing on various synthesis and modulation strategies of IBCs is presented, based on an in-depth understanding of the relationship between electronic structures, charge redistribution and activity as well as stability of the electrocatalysts. In addition, the unprecedented achievements in PEMWEs are summarized. The reaction mechanisms and future perspectives are critically discussed to inspire more rational design of IBCs toward practical applications.

The extension of virology beyond its traditional medical, veterinary or agricultural applications, now called environmental virology, has shown that viruses are both the most numerous and diverse biological entities on earth. In particular, virus isolation studies involving unicellular eukaryotic hosts (heterotrophic and photosynthetic protozoans) revealed numerous viral types previously unexpected in terms of virion structure and morphology, genome size and gene content, or mode of replication. Complemented by large-scale metagenomic analyzes, these discoveries have rekindled interest in the enigma of the evolutionary origin of viruses, for which no simple definition encompassing all of their diversity is still unanimous. Several laboratories have repeatedly tackled the deep reconstruction of the evolutionary history of viruses, using various methods of molecular phylogeny applied to the few shared genes detected in certain virus groups (e.g. the Nucleocytoviricota). Beyond the practical difficulties of establishing reliable homology relationships from extremely divergent sequences, I present here purely conceptual arguments highlighting several fundamental limitations plaguing the reconstruction of the deep evolutionary history of viruses, and even more the identification of their unique of multiple origin (s). Those limitations are direct consequences of the particularly random mechanisms which govern the reductive evolution of obligate intracellular parasites.

Aptamers are versatile oligonucleotide ligands used for molecular recognition of diverse targets. However, application of aptamers to the field of amyloid β-protein (Aβ) has been limited so far. Aβ is an intrinsically disordered protein that exists in a dynamic conformational equilibrium, presenting time-dependent ensembles of short-lived, metastable structures and assemblies that have been generally difficult to isolate and characterize. Moreover, despite understanding of potential physiological roles of Aβ, this peptide has been linked to the pathogenesis of Alzheimer disease, and its pathogenic roles remain controversial. Accumulated scientific evidence thus far highlights undesirable or nonspecific interactions between selected aptamers and different Aβ assemblies likely due to metastable nature of Aβ or inherent affinity of RNA oligonucleotides to β-sheet-rich fibrillar structures of amyloidogenic proteins. Accordingly, lessons drawn from Aβ–aptamer studies emphasize that purity and uniformity of the protein target and rigorous characterization of aptamers’ specificity are important for realizing and garnering the full potential of aptamers selected for recongizing Aβ or other intrinsically disordered proteins. This review summarizes studies of aptamers selected for recognizing different Aβ assemblies and highlights controversies, difficulties, and limitations of such studies.

Cells occupy a prominent place in the history of life on planet Earth. The central role of cellular organization is observed by the fact that “cellular life” is often used as a synonym for life itself. Thus, most characteristics used to define cells overlap with the ones used to define life. Notwithstanding, new scenarios about the origin of life are bringing alternative views to describe how cells may have evolved from the open biological systems named progenotes. Here, using a logical and conceptual analysis, we re-evaluate the characteristics used to infer a single origin for cells. We argue that some evidences used to support cell monophyly, such as the presence of elements from both the translation mechanism and the universality of the genetic code, actually indicate a unique origin for all “biological systems”, a term used to define not only cells, but also virus and progenotes. Besides, we present evidence that at least two biochemical pathways as important as (i) DNA replication and (ii) lipid biosynthesis may not homologous between Bacteria and Archaea. The identities observed between the proteins involved in those pathways along representatives of these two ancestral Domains are too low to indicate common genic ancestry. Altogether these facts can be seen as an indication that cellular organization has possibly evolved two or more times and that LUCA (the Last Universal Common Ancestor) might not have existed as a cellular entity. Thus, we aim to consider the possibility that different strategies acquired by biological systems to exist, such as viral, bacterial and archaeal were originated independently from the evolution of different progenote populations.

Since its advent in the mid-twentieth century, the field of artificial intelligence (AI) has been heavily influenced by biology. From the structure of the brain to evolution by natural selection, core biological concepts underpin many of the fundamental breakthroughs in modern AI. Here, focusing specifically on artificial neural networks (ANNs) that have become commonplace in machine learning, we show the numerous connections between theories based on coevolution, multi-level selection, modularity and competition and related developments in ANNs. Our aim is to illuminate the valuable but often overlooked inspiration biologists have provided AI research and to spark future contributions at this intersection of biology and computer science. Although recent advances in AI have been swift, many significant challenges remain requiring innovative solutions. Thankfully, biology in all its forms still has a lot to teach us, especially when trying to create truly intelligent machines.

Thesis Statement: The consumption of externally fermented foods acted as the initial metabolic trigger enabling hominid brain expansion. Because brain tissue is metabolically expensive, it is thought that the evolution of humans’ large brains was only possible through a concomitant reduction in the size of another expensive organ system, the gut. However, this gut reduction must have itself been made possible by dietary changes, the nature of which are still unclear. Here, we propose that the initial metabolic trigger of hominid brain expansion may have been the consumption of externally fermented foods. We define “external fermentation” as occurring outside the body, as opposed to the internal fermentation that occurs through the gut microbiome. This practice could have begun accidentally and with limited understanding, but over time, fermentation technologies may have become increasingly intentional, socially-transmitted, and culturally-reinforced. We detail the mechanisms by which external fermentation can mediate the evolution of increased brain size, as well as a reduction in gut size, by increasing the bioavailability of macro- and micronutrients while reducing digestive energy expenditure. Importantly, we calculate that the reduction in human gut size relative to modern apes is mainly due to a reduction in the colon, the site of internal fermentation. We also discuss the explanatory power of our hypothesis relative to others, including realistic plausibility in hominids with brains roughly the size of modern chimpanzees. Finally, we survey external fermentation practices across human cultures to demonstrate its viability across a huge range of environments, temperatures, and food sources. We close with suggestions for empirical tests.

Most large fibers in central nervous system of vertebrates are decussated. The cause or the evolutionary force of this phenomenon is not convincingly described. Here we show a pattern for this nervous system property that simultaneously is found to a more basic rule in evolution.The idea here is the "function to anatomy" theorem. We claim that functions of physical, biochemical, enzymatic, etc., in lower scale of living organisms "emerge" to anatomy in larger scales. And reversely, the anatomy we see in multicelular organisms are/were functions in microscopic scales.We propose descriptions, predictions, and a probable road map to what this can implicate in biological and medical issues.

Montiaceae (Portulacineae) comprise a clade of at least 270 species primarily of western America and Australia. This work uses existing phylogenetic metadata to elaborate a new cladistic taxonomic synthesis, and clarifies morphological circumscriptions of several poorly known species. A total of 21 taxa are validated, seven new and 14 necessary nomenclatural recombinations). Hypotheses of Montiaceae historical biogeography and phenotypic evolution are evaluated in light of recent metadata.

In this paper, a multi-operator differential evolution algorithm (MODE) is proposed to solve the Optimal Power Flow (OPF) problem and is called MODE-OPF. The MODE-OPF utilizes the strengths of more than one differential evolution (DE) operator in a single algorithmic framework. Additionally, an adaptive method (AM) is proposed to update the number of solutions evolved by each DE operator based on both the diversity of population and quality of solutions. This adaptive method has the ability to maintain diversity at the early stages of the optimization process and boost convergence at the later ones. The performance of the proposed MODE-OPF is tested by solving OPF problems for both small and large IEEE bus systems (i.e., IEEE-30 and IEEE-118) while considering the intermittent solar and wind power generation. To prove the suitability of this proposed algorithm, its performance has been compared against several state-of-the-art optimization algorithms, where MODE-OPF outperforms other algorithms in all experimental results and thereby improving a network's performance with lower cost. MODE-OPF decreases the total generation cost up to 24.08%, the real power loss up to 6.80% and the total generation cost with emission up to 8.56%.

This research presents a solution to the problem of planning the optimum area for economic crops by developed mathematical models and developed an algorithm to solve the problem of planning the optimum area by considered economic value for the maximize profit of farmers. The data were collected from farmers in 8 provinces in the northeastern region of Thailand. The 3 economic crops studied were rice, cassava and sugarcane. The solving problem methods were 1) Created mathematical models and solved the problems with Lingo V.11. 2) Improved Differential Evolution algorithms (I-DE) to solve the problems, which had 3 local search methods included (Swap, Cyclic Move and K-variable moves). The results of this study showed that in the small and medium problems instances, Lingo V.11 and DE provided equal profit outcome but DE was faster but in the large size of test instances DE generated better solution than that of Lingo v.11 when Lingo simulation time is set to 250 hours and DE simulation time has set to maximum 21.82 minutes. 2) Comparing DE and I-DE , I-DE outperforms DE in finding the better solution for all size of test instances (small, medium and large).

The study of eco-evolutionary feedbacks is in clear recent expansion. However, most studies concern predator-prey and host-parasite interactions, while the analysis of eco-evolutionary feedbacks involving sexual interactions is lagging behind. This is at odds with the potential of these interactions to engage in such processes. Indeed, there is now ample evidence that sexual selection is affected by ecological change. There is also evidence that sexual selection traits evolve rapidly, which may modify the ecological context of species, and thus the selection pressures they will be exposed to. Here, we first set a clear distinction between processes in which ecology drives evolution and those in which the contemporary evolution of populations may change their ecology, depending on which traits act as drivers and objects of change. We then review evidence for these processes and discuss examples of closed eco-evolutionary feedbacks in an attempt to understand how we can tear this loop apart. We suggest that a better understanding of eco-evolutionary feedbacks of sexual selection may help us understand the effects of sexual selection on the rate of adaptation, speciation, and extinction, and thus foster future research in this area.

The microstructure of Al-5Fe-1.5Er alloy was characterized and analyzed by using XRD, SEM, TEM and EDS. The effect of microstructure on the behavior of crack initiation and propagation was investigated by in situ tensile testing. Results show that the microstructure consists of α-Al matrix, Al₃Fe, Al₄Er, eutectic phase Al₃Fe + Al₄Er, while the 1.5 wt.% Er was added in Al-5Fe alloy. The twin structure of the Al₃Fe phase was observed, and the twin plane is {001}. Moreover, a continuous concave and convex interface structure of the Al₄Er has been found. Al₃Fe is in the form of a sheet with a clear gap inside.In situ tensile tests of the alloy at room temperature show that the crack initiation occured mainly in the Al₃Fe phase, and that the crack propagation modes include intergranular and transgranular expansion. Crack transgranular expansion is due to the strong binding ability between Al₄Er phases and surrounding organization, and the continuous concave and convex interface structure of the Al₄Er provides a significant meshing effect on the matrix and eutectic structure.

With growing urbanisation the sustainability of cities has become increasingly important. Although cities have been using indicators for a long time it is only in the last decades that attempts have been made to collate indicators into indicator sets with the aim of reflecting the many different aspects that need to be covered to assess the sustainability of a city. The aim of this paper is to review how indicators for monitoring sustainable urban development have evolved over time and compare them to the indicators suggested by the UN Sustainable Development Goals (SDGs). The review reveals that previous indicator sets emphasised environmental sustainability, health and economic growth. It is also shown that indicator sets that pre-date the SDGs lacked dimensions such as gender equality and reduced inequalities. In all, the SDG indicators provide the possibility of a more balanced and integrated approach to urban sustainability monitoring. At the same time, a methodology is needed to facilitate the adaptation process of localising the SDGS, targets and indicators. Challenges of local application include their large number, their generic characteristics and the need to complement them with specific indicators that are more relevant at the city level.

When computers start to become a dominant part of technology around the 1950s, fundamental questions about reliable designs and robustness were of great relevance. Their development gave rise to the exploration of new questions such as what made brains reliable (since neurons can die) and how computers could get inspiration from neural systems. In parallel, the first Artificial Neural Networks came to life. Since then, the comparative view between brains and computers has been developed in new, sometimes unsuspected directions. With the rise of deep learning and the development of connectomics, an evolutionary look at how both hardware and neural complexity have evolved or designed is required. In this paper, we argue that important similarities have resulted both from convergent evolution (the inevitable outcome of architectural constraints) and inspiration of hardware and software principles guided by toy pictures of neurobiology. Moreover, dissimilarities and gaps originate from the lack of major innovations that have paved the way to biological computing (including brains) that are completely absent within the artificial domain. As it occurs within synthetic biocomputation, we can also ask whether alternative minds can emerge from A.I.\ designs. Here we take an evolutionary view of the problem and discuss the remarkable convergences between living and artificial designs and what are the pre-conditions to achieve artificial intelligence.

The energy crisis and environmental problems are becoming more and more severe due to the long-term consumption of fossil fuels. Therefore, energy conversion devices with high energy density and environmental friendliness (such as fuel cells, metal-air batteries, etc.) have been ex-pected to be reliable alternatives to traditional fossil energy. However, due to the inevitable use of precious metals as the electrode catalysts for these devices, the popularization of these alternatives is seriously hindered. Transition metal nitrides (TMNs) exhibit similar surface and adsorption properties to noble metals since the atomic distance between metal atoms increases and the d-band center of metal atoms downshift after the nitrogen atoms enter the metal lattice. TMNs have become one of the best electrode materials to replace noble metal electrocatalysts in energy storage and conversion devices. In this review, the latest development in the electrocatalytic ap-plication of TMNs nanocrystalline is covered. Firstly, we briefly discuss the structure and activity origin of TMNs and introduce the common physical and chemical methods for the preparation of TMNs. Subsequently, we illustrate the applications of unary TMNs and multivariate TMNs in oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Finally, we summarize the challenges and problems of TMNs encountered at the present stage, and expect its future de-velopment.

In this paper, we look at how Artificial Swarm Intelligence can evolve using evolutionary algorithms that try to minimize the sensory surprise of the system. We will show how to apply the free-energy principle, borrowed from statistical physics, to quantitatively describe the optimization method (sensory surprise minimization), which can be used to support lifelong learning. We provide our ideas about how to combine this optimization method with evolutionary algorithms in order to boost the development of specialized Artificial Neural Networks, which define the proprioceptive configuration of particular robotic units that are part of a swarm. We consider how optimization of the free-energy can promote the homeostasis of the swarm system, i.e. ensures that the system remains within its sensory boundaries throughout its active lifetime. We will show how complex distributed cognitive systems can be build in the form of hierarchical modular system, which consists of specialized micro-intelligent agents connected through information channels. We will also consider the co-evolution of various robotic swarm units, which can result in development of proprioception and a comprehensive awareness of the properties of the environment. And finally, we will give a brief outline of how this system can be implemented in practice and of our progress in this area.

Microbes have evolved many fascinating and complex ways of interacting with conspecifics. Perhaps one of the most interesting is aggregative multicellularity, wherein independent cells come together and adhere to one another in order to form a larger entity. The fundamental benefits of active aggregation into multicellular groups generally remain unclear, and there are many open questions about what selective pressures led to the evolution of this behavior in various eukaryotic and prokaryotic taxa, most notably the dictyostelids and the myxobacteria. Aggregative multicellularity can be partitioned into three main phases: coming together, staying together as a group, and disaggregation. Different selective pressures may have led to adaptations unique to each phase. While aggregative microbial systems generally form elevated multicellular structures such as fruiting bodies, these can vary in complexity and morphology even among closely related species. What evolutionary forces shaped such morphological diversification remains unknown. Strains that are not genetically identical can coaggregate, which can impact group-level function either positively through functional synergy or negatively through harmful exploitation. Such chimerism within aggregates is likely to have played important roles in shaping the evolution of microbial multicellularity. Much further research is needed into the evolutionary forces and processes leading to and shaping the many forms of microbial aggregation.

What is the potential for synthetic biology as a way of engineering, on a large scale, complex ecosystems? Can it be used to change endangered ecological communities and rescue them to prevent their collapse? What are the best strategies for such ecological engineering paths to succeed? Is it possible to create stable, diverse synthetic ecosystems capable of persisting in closed environments? Can synthetic communities be created to thrive on planets different from ours? These and other questions pervade major future developments within synthetic biology. The goal of engineering ecosystems is plagued with all kinds of technological, scientific and ethic problems. In this paper we consider the requirements for Terraformation, i. e. for changing a given environment to make it hospitable to some given class of life forms. Although the standard use of this term involved strategies for planetary terraformation, it has been recently suggested that this approach could be applied to a very different context: ecological communities within our own planet. As discussed here, this includes multiple scales, from the gut microbiome to the entire biosphere.

Understanding the evolutionary role of environmentally-induced phenotypic variation (i.e., environmental plasticity) is an important issue in developmental evolution. One of the major physiological responses to environmental changes is cellular stress, which is counteracted by a generic stress reaction that detoxifies the cell, refolds proteins, and repairs DNA damage. In this paper, we elaborate on a previous finding suggesting that the cell differentiation cascade of human decidual stromal cells, a cell type critical for embryo implantation and the maintenance of pregnancy, evolved from a cellular stress reaction. We hypothesize that the stress reaction in these cells was elicited ancestrally through the inflammation caused by embryo attachment and invasion. We describe a model, Stress-Induced Evolutionary Innovation (SIEI), whereby ancestral stress reactions and their corresponding pathways can be transformed into novel structural components of body plans, such as new cell types. After reviewing similarities and differences between SIEI and the “plasticity first hypothesis” (PFH) of evolution, we argue that SIEI is a distinct form of plasticity-based evolutionary change because it leads to the origin of novel structures rather than the adaptive transformation of a pre-existing character.

Fossils constitute the principal repository of data that allow for independent tests of hypotheses of biological evolution derived from observations of the extant biota. Traditionally, transformational series of structure, consisting of sequences of fossils of the same lineage through time, have been employed to reconstruct and interpret morphological evolution. More recently, a move toward an updated paradigm was fueled by the deliberate integration of developmental thinking in the inclusion of fossils in reconstruction of morphological evolution. The vehicle for this is provided by structural fingerprints – recognizable morphological and anatomical structures generated by (and reflective of) the deployment of specific genes and regulatory pathways during development. Furthermore, because the regulation of plant development is both modular and hierarchical in nature, combining structural fingerprints recognized in the fossil record with our understanding of the developmental regulation of those structures produces a powerful tool for understanding plant evolution. This is particularly true when the systematic distribution of specific developmental regulatory mechanisms and modules is viewed within an evolutionary (paleo-evo-devo) framework. Here, we discuss several advances in understanding the processes and patterns of evolution, achieved by tracking structural fingerprints with their underlying regulatory modules across lineages, living and fossil: the role of polar auxin regulation in the cellular patterning of secondary xylem and the parallel evolution of arborescence in lycophytes and seed plants; the morphology and life history of early polysporangiophytes and tracheophytes; the role of modularity in the parallel evolution of leaves in euphyllophytes; leaf meristematic activity and the parallel evolution of venation patterns among euphyllophytes; mosaic deployment of regulatory modules and the diverse modes of secondary growth of euphyllophytes; modularity and hierarchy in developmental regulation and the evolution of equisetophyte reproductive morphology. More generally, inclusion of plant fossils in the evo-devo paradigm has informed discussions on the evolution of growth patterns and growth responses, sporophyte body plans and their homology, sequences of character evolution, and the evolution of reproductive systems.

Considering that life on earth evolved about 3.7 billion years ago, vertebrates are young, appearing in the fossil record during the Cambrian explosion about 542 to 515 million years ago. Results from sequence analyses of genomes from bacteria, yeast, plants, invertebrates and vertebrates indicate that receptors for adrenal steroids (aldosterone, cortisol), and sex steroids (estrogen, progesterone, testosterone) also are young, with an estrogen receptor and a 3-ketosteroid receptor first appearing in basal chordates (cephalochordates: amphioxus), which are close ancestors of vertebrates. Through gene duplication and divergence of the 3-ketosteroid receptor, receptors that respond to androgens, glucocorticoids, mineralocorticoids and progestins evolved in vertebrates. Thus, an ancestral progesterone receptor and an ancestral corticoid receptor, the common ancestor of the glucocorticoid and mineralocorticoid receptors, evolved in jawless vertebrates (cyclostomes: lampreys, hagfish). This was followed by evolution of an androgen receptor, distinct glucocorticoid and mineralocorticoid receptors and estrogen receptor-α and -β in cartilaginous fishes (gnathostomes: sharks). Further evolution of mineralocorticoid signaling occurred with the evolution of aldosterone synthase in lungfish, a forerunner of terrestrial vertebrates. Adrenal and sex steroid receptors are not found in echinoderms: and hemichordates, which are ancestors in the lineage of cephalochordates and vertebrates. The evolution of steroid receptors at key nodes in the evolution of vertebrates, in which steroid receptors act as master switches to regulate differentiation, development, reproduction, immune responses, electrolyte homeostasis and stress responses, argues for an important role for steroid receptors in the evolutionary success of vertebrates, considering that the human genome contains about 22,000 genes, which is not much larger than genomes of invertebrates, such as Caenorhabditis elegans (~18,000 genes) and Drosophila (~14,000 genes).

Hydrogen evolution reaction (HER) is one of the most important reaction in electrochemistry. This is not only because it is the simplest way to produce high purity hydrogen and the fact that it is the side reaction in many other technologies. HER actually shaped current electrochemistry because it was in focus of active research for so many years (and it still is). The number of catalysts investigated for HER is immense, and it is impossible to overview them all. In fact, it seems that the complexity of the field overcomes the complexity of HER. The aim of this review is to point out some of the latest developments in HER catalysis, current directions and some of the missing links between a single crystal, nanosized supported catalysts and, recently emerging, single atom catalysts for HER

We propose the traditional goal of cancer therapists to develop a single drug or drug combination that can, by itself, eliminate all cancer cells within a host has neglected potential treatments that may achieve curative outcomes by strategically combining agents that are individually effective but non-curative. We derive basic principles for such an approach from the eco-evolutionary dynamics of background extinctions in which a “first strike” reduces the size and heterogeneity of the initial population and is followed immediately by demographic and ecological “second strikes” that push the population below an extinction threshold. This proposed strategy appears identical to the empirically-derived curative therapy in childhood Acute Lymphocytic Leukemia.

Simulation tools capturing the interactions of communication and electrical system operation represent a powerful support for fully assessing the potential benefits and impacts of ICT in future smart power distribution network. A strong interest is upon the possibility of exploiting the last generation communication systems for supporting the transition of distribution network towards a smart grid scenario. Having in mind the above, the authors propose a numerical co-simulation tool useful to thoroughly understand the impact of the communication networks on the performance of whole power system dynamics. The co-simulation tool has been purposely developed to simulate the highly time-critical smart grid application of fault management and network reconfiguration and permits reproducing and evaluating the behavior of the public mobile telecommunication system 4G Long Term Evolution (LTE), as communication technology for smart grid applications. Results of the paper demonstrates that LTE provides good performances for supporting the data communication required to perform fault location, extinction and a subsequent network reconfiguration in smart power distribution networks.

The Autopoiesis and Cognition Theory (ACT), by Maturana and Varela, based on the notions of Biological Closure and Structural Coupling, is a well-known theory on how to understand biological organization [1, 2, 3]. Although, for example, the Free Energy Principle framework evokes some entailments of autopoiesis in a more formal setting [4, 5]; and ACT has been used in many fields, its impact has been restricted because it lacks quantitative analysis. Here we present a theoretical framework grounded in accepted and well-developed ideas from Mathematics and Physics which advance the understanding of the Principles of Biological Organization under the guidance of Biological Closure and Structural Coupling. The disciplines of Differential Geometry/Topology, Mechanics and Complex Dynamical Systems provide a powerful, elegant, and well-established body of knowledge to support our Biological Organization Principles (BOP) framework. In particular, Stochastic Mechanics and KAM theory (from Kolmogorov, Arnold and Moser theorem) allow us to develop, using the notions of Biological Closure and Structural Coupling, a central core of BOP termed Dynamical Closure Mechanism. Under the proposed framework, a wide variety of bio- logical phenomena can be understood, shedding new light on biological explanations. However, an understanding of biological organization may require the re-evaluation of dogmas on how we think on biology as it seems inescapable that what is needed is an integration of analysis and notions derived from mathematics, physics, and biology to generate a new landscape of ideas.

The severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) viral genome is an RNA virus consisting of approximately 30,000 bases. As part of testing efforts, whole genome sequencing of human isolates has resulted in over 1,600 complete genomes publicly available from GenBank. We have performed a comparative phylogenetic analysis of the sequences, in order to detect common mutations within the population. Analysis of variants occurring within the assembled genomes yields 417 variants occurring in at least 1% of the completed genomes, including 229 within the 5’ untranslated region (UTR), 152 within the 3’UTR, 2 within intergenic regions and 34 within coding sequences.

This review describes major advances in the use of functionalized molecular metal oxides (polyoxometalates, POMs) as water oxidation catalysts under electrochemical conditions. The fundamentals of POM-based water oxidation are described together with a brief overview of general approaches to designing POM water oxidation catalysts. Next, the use of POMs for homogeneous, solution-phase water oxidation is described together with a summary of theoretical studies shedding light on the POM-WOC mechanism. This is followed by a discussion of heterogenization of POMs on electrically conductive substrates for technologically more relevant application studies. Stability of POM water oxidation catalysts are discussed on selected examples where detailed data is already available. The review finishes with an outlook on future perspective and emerging themes in electrocatalytic polyoxometalate-based water oxidation research.

This paper aims to provide an overall review of degradation, damage evolution and fatigue models in the literature of various engineering materials, mostly metals, and composites.

Currently, the use of numerical models for reproducing the landscape evolution of a river basin is part of the day-by-day research activities of fluvial engineers and geomorphologists. However, despite landscape modelling is based on a rather long tradition, and scientists and practitioners are trying to schematize the processes involved in the evolution of a landscape since decades, there is still the need for improving both the knowledge of the physical mechanisms and their numerical coding. The present review focuses on the first aspect, discussing the main components of a landscape evolution model and their more common schematizations, presenting possible open questions to be addressed towards an improvement of the reliability of such kind of models in describing the fluvial geomorphology.

Aggregative multicellularity occurs when dispersed cells join together to form a highly cooperative unit, in contrast to clonal multicellular organisms formed by cells that remain in contact after descent from a single cell. Because aggregative groups may include non-relatives, aggregative multicellular organisms should be particularly vulnerable to the rise of cheater cells that take advantage of social goods without paying the costs, reducing cooperation, and even threatening extinction. We review the key mechanisms by which aggregative multicellular organisms control cheaters with a focus on the best studied aggregative organisms, Myxococcus xanthus and Dictyostelium discoideum. These include various passive and active mechanisms to maintain high relatedness within aggregates, to enforce cooperation on aggregate members, and the costs of cheating on other key functions. Ultimately, aggregative multicellular organisms are not that different from clonal organisms descended from a single cell.

Viruses are the most numerically abundant biological entities on Earth. As ubiquitous replicators of information molecules and agents of community change, viruses have potent effects on life on Earth and may play a critical role in human spaceflight missions, life detection missions to other planetary bodies, and in planetary protection. However, major knowledge gaps constrain our understanding of the Earth’s virosphere: 1) the role viruses play in biogeochemical cycles, 2) the origin(s) of viruses, and 3) the involvement of viruses in the evolution, distribution, and persistence of life. As viruses are the only replicators that span all known types of nucleic acids, an expanded experimental and theoretical toolbox built for Earth’s viruses will be pivotal for detecting and understanding life on Earth and beyond. Only by filling in these knowledge and technical gaps will we obtain an inclusive assessment of how to distinguish and detect life on other planetary surfaces. Meanwhile, space exploration requires life-support systems for the needs of humans, plants, and their microbial inhabitants. Viral effects on microbes and plants are essential for Earth’s biosphere and human health, but virus-host interactions in spaceflight are poorly understood. Viral relationships with their hosts respond to environmental changes in complex ways which are difficult to predict by extrapolating from Earth-based proxies. These relationships must therefore be studied in space to fully understand how spaceflight will modulate viral impacts on human health and life-support systems, including microbiomes. This review addresses key questions that must be examined to incorporate viruses into Earth system models, life-support systems, and life detection. Further, the results of tackling these questions will help in our efforts to develop planetary protection protocols and further our understanding of viruses in astrobiology.

In order to understand the evolution of multicellularity, we must understand how and why selection favors the first steps in this process: the evolution of simple multicellular groups. Multicellularity has evolved many times in independent lineages with fundamentally different ecologies, yet no work has yet systematically examined these diverse selective drivers. Here we review recent developments in systematics, comparative biology, paleontology, synthetic biology, theory, and experimental evolution, highlighting ten selective drivers of simple multicellularity. Our survey highlights the many ecological opportunities available for simple multicellularity, and stresses the need for additional work examining how these first steps impact the subsequent evolution of complex multicellularity.

Polyploidy means having more than two basic sets of chromosomes. Polyploid plants may be artificially obtained through chemical, physical and biological (2n gametes) methods. This approach allows an increased gene scope and expression, thus resulting in phenotypic changes such as yield and product quality. Nonetheless, breeding new cultivars through induced polyploidy should overcome deleterious effects that are partly contributed by genome and epigenome instability after polyploidization. Furthermore, shortening the time required from early chromosome set doubling to the final selection of high yielding superior polyploids is a must. Despite these hurdles, plant breeders have successfully obtained polyploid bred-germplasm in broad range of forages after optimizing methods, concentration and time, particularly when using colchicine. These experimental polyploids are a valuable tool for understanding gene expression, which seems to be driven by dosage dependent gene expression, altered gene regulation and epigenetic changes. Isozymes and DNA-based markers facilitated the identification of rare alleles for particular loci when compared with diploids, and also explained their heterozygosity, phenotypic plasticity and adaptability to diverse environments. Experimentally induced polyploid germplasm could enhance fresh herbage yield and quality, e.g. leaf protein content, leaf total soluble solids, water soluble carbohydrates and sucrose content. Offspring of experimentally obtained hybrids should undergo selection for several generations to improve their performance and stability.

Three types of wakefulness appeared along the vertebrate’s phylogeny and ontogeny: spinal-rhombencephalic in fish, brainstem-diencephalic in reptiles and cortical in mammals, in which the paralyzed spinal-rhombencephalic wake and the brainstem-diencephalic wake remain as REMS and NREMS The spinal-rhombencephalic and cortical types of wake are inherently anti-homeostatic. Animals must forage, reproduce, and survive to predation disregarding the environmental circumstances, hence temporarily forgetting the homeostatic regulation. After fulfilling the vital functions, the brainstem-diencephalic wake recovers the homeostatic control. The phasic signs of REMS are adaptive in immature mammals, serving for demanding heat, milk and defense to their mother. These advantages outweigh the REMS' poikilostasis in infants. The adults’ poikilostasis of REMS is harmless in thermoneutral environments but is mal-adaptive in aquatic environments in which REMS is reduced or even disappears. These exceptions explain the anomalous examples of REMS. An on-off hypothalamic switch homeostatically regulates the entrance and exit from REMS. Furthermore, the vital phasic signs of REMS depend on a second pontine proportional homeostatic control. Altogether, they regulate the expression of REMS.

The newly established virus family Phenuiviridae in Bunyavirales harbors viruses infecting three kingdoms of host organisms (animals, plants, and fungi), which is rare in known virus families. Many phenuiviruses are arboviruses and replicate in two distinct hosts (e.g., insects and humans or rice). Multiple phenuiviruses, such as Dabie bandavirus, Rift Valley fever phlebovirus, and Rice stripe tenuivirus, are highly pathogenic to humans, animals, or plants. They impose heavy global burdens on human health, livestock industry, and agriculture and are research hotspots. In recent years the taxonomy of Phenuiviridae has been expanded greatly, and researches on phenuiviruses have made significant progress. With these advances, this review drew a novel panorama regarding the biomedical significance, distribution, morphology, genomics, taxonomy, evolution, replication, transmission, pathogenesis, and control of phenuiviruses, to aid researchers in various fields to recognize this highly adaptive and very important virus family.

What if oxygenic photosynthesis is a primordial process with roots at the origin of life? What would the impact of this change in perspective be on our understanding of the early Earth and of the emergence and diversification of life? In here, I will examine some of the historical context of the study of the evolution of photosynthesis, which led to the consolidation of the current notion that the origin of anoxygenic photosynthesis occurred before the origin of oxygenic photosynthesis. I will show with a few examples how the mainstream view on the evolution of photosynthesis traces back to Oparin’s ‘primordial soup’ scenario for the origin of life, fuelled by the century-old perception that oxygenic photosynthesis is a plant rather than a bacterial trait. However, it has become more evident than ever before that the mainstream view is not supported by the evolution of the photosystems. In other words, the origin of biological water oxidation appears to be the seed from where photosynthesis sprout. Somewhat troubling and contrary to all predictions that derive from the mainstream view, photosystem II—the water-splitting and oxygen-evolving enzyme—shows features that are better explained if photochemical reaction centres originated during the establishment of oxygenic photosynthesis. An urgent revision of the evolution of photosynthesis procured to be free from biases of interpretations and presuppositions is strongly encouraged from all angles of the Life and Earth Sciences.

Based on a new model of a possible origin of life, we establish an efficient and stable system undergoing structural reproduction, self-optimization and molecular evolution. This system is being formed under realistic conditions by the interaction of two cyclic processes, one of which offering vesicles as the structural environment, the other supplying peptides from a variety of amino acids as versatile building blocks. We demonstrate that structures growing in a combination of both cycles have the potential to support their own existence, to undergo chemical and structural evolution and to develop unpredicted functional properties. The key mechanism is the mutual stabilization of the peptides by the vesicles and of the vesicles by the peptides together with a constant production and selection of both. The development of the proposed system over time not only would represent one of the principles of life, but could also be a model for the formation of self-evolving structures ultimately leading to the first living cell. The experiment yields clear evidence on a vesicle-induced accumulation of membrane-interacting peptide which could be identified by liquid chromatography combined with high-resolution mass spectroscopy. We found that the selected peptide has an immediate effect on the vesicles, leading to i) reduced vesicle size, ii) increased vesicle membrane permeability, and iii) improved thermal vesicle stability.

Directed evolution methods are becoming increasingly popular, as they are extremely powerful toward developing new biomolecules with altered/novel activities, e.g., proteins with new catalytic functions or substrate specificities, and nucleic acids that recognize an intended target. Especially useful are systems that have incorporated continuous evolution, where the protein to be evolved undergoes continuous mutagenesis to evolve a desired trait with little to no input from the researcher once the system is started. However, continuous evolution methods can be challenging to implement in the lab and daunting for researchers to invest time and resources. Our intent is to provide basic information and helpful suggestions that we have gained from our experience with bacterial phage-assisted continuous evolution (PACE). Specifically, we review factors to consider before adopting PACE for a given evolution scheme, different types of selection circuits that can be utilized with particular focus on the PACE-B1H selection system, what optimization of a PACE selection circuit may look like using directed evolution of ME47 as a case study, and additional techniques that may be incorporated into a PACE experiment. With this information, researchers will be better equipped to determine if PACE is a valid strategy to use to evolve their proteins and how to set up a valid selection circuit.

The current SARS- CoV-2 pandemic underscores the importance of understanding the evolution of RNA genomes. While RNA is subject to the formation of similar lesions as DNA, the evolutionary and physiological impacts RNA lesions have on viral genomes are yet to be characterized. Lesions that may drive the evolution of RNA genomes can induce breaks that are repaired by recombination or can cause base substitution mutagenesis, also known as base editing. Over the past decade or so, base editing mutagenesis of DNA genomes has been subject to many studies, revealing that exposure of ssDNA is subject to hypermutation that is involved in the etiology of cancer. However, base editing of RNA genomes has not been studied to the same extent. Recently hypermutation of single-stranded RNA viral genomes have also been documented though its role in evolution and population dynamics. Here, we will summarize the current knowledge of key mechanisms and causes of RNA genome instability covering areas from the RNA world theory to the SARS- CoV-2 pandemic of today. We will also highlight the key questions that remain as it pertains to RNA genome instability, mutations accumulation, and experimental strategies for addressing these questions.

This article, we study the sufficient conditions for the controllability of second-order impulsive partial neutral evolution differential systems with infinite delay in Banach spaces by using the theory of cosine families of bounded linear operators and fixed point theorem.

For efficient electrode development in an electrolysis system, Fe₂O₃, MnO, and heterojunction Fe₂O₃-MnO materials were synthesized via a simple sol-gel method. These particles were coated on a Ni-foam electrode, and the resulting material was used as an electrode to be used during an oxygen evolution reaction (OER). A 1000-cycle OER test in a KOH alkaline electrolyte indicated that the heterojunction Fe₂O₃-MnO/NF electrode exhibited the most stable and highest OER activity: it exhibited a low overvoltage (n) of 370 mV and a small Tafel slope of 66 mV/dec. X-ray photoelectron spectroscopy indicated that the excellent redox performance contributed to the synergy of Mn and Fe, which enhanced the OER performance of the Fe₂O₃-MnO/NF electrode. Furthermore, the effective redox reaction of Mn and Fe indicated that the structure maintained stability even under 1000 repeated OER cycles.

There is an ongoing global pandemic of human respiratory syncytial virus (RSV) infection that results in substantial annual morbidity and mortality. In Australia, RSV is the major cause of acute lower respiratory tract infections (ALRI). Nevertheless, little is known about the extent and origins of genetic diversity of RSV in Australia, nor the factors that shape this diversity. We conducted a genome-scale analysis of RSV infections in New South Wales (NSW). RSV genomes were successfully sequenced for 144 specimens collected between 2010-2016. Of these, 64 belonged to the RSVA and 80 to the RSVB subtype. Phylogenetic analysis revealed a wide diversity of RSV lineages within NSW and that both subtypes evolved rapidly in a strongly clock-like manner, with mean rates of approximately 6-8 x 10^-4 nucleotide substitutions per site per year. There was only weak evidence for geographic clustering of sequences, indicative of fluid patterns of transmission within the infected population, and no evidence of any clustering by patient age such that viruses in the same lineages circulate through the entire host population. Importantly, we show that both subtypes circulated concurrently in NSW with multiple introductions into the Australian population in each year, and only limited evidence for multi-year persistence.

Genetic switches can be utilized for many purposes in synthetic biology including the assembly of complex genetic circuits to achieve sophisticated cellular systems and the construction of biosensors for real-time monitoring of intracellular metabolite concentrations. Although genetic switches have mainly been developed in prokaryotes to date, eukaryotic genetic switches are increasingly being reported as both rational and irrational engineering technologies mature. In this review, we describe genetic switches in yeast based on synthetic transcription factors and/or synthetic promoters. We also discuss directed evolution technologies for the rapid and robust construction of yeast genetic switches.

Antibiotic resistant Pseudomonas aeruginosa infections are the primary cause of mortality in people with cystic fibrosis (CF). Yet it has only recently become appreciated that resistance mutations can also increase P. aeruginosa virulence, even in the absence of antibiotics. Moreover, the mechanisms by which resistance mutations increase virulence are poorly understood. In this study we tested the hypothesis that mutations affecting efflux pumps can directly increase P. aeruginosa virulence. Using genetics, physiological assays, and model infections, we show that efflux pump mutations can increase virulence. Mutations of the mexEF efflux pump system increased swarming, rhamnolipid production, and lethality in a mouse infection model, while mutations in mexR that increased expression of the mexAB-oprM efflux system increased virulence during an acute murine lung infection without affecting swarming or rhamnolipid gene expression. Finally, we show that an efflux pump inhibitor, which represents a proposed novel treatment approach for P. aeruginosa, increased rhamnolipid gene expression in a dose-dependent manner. This finding is important because rhamnolipids are key virulence factors involved in dissemination through epithelial barriers and cause neutrophil necrosis. Together, these data show how current and proposed future anti-Pseudomonal treatments may unintentionally make infections worse by increasing virulence. Therefore, treatments that target efflux should be pursued with caution.

Nowadays genetic algorithm (GA) is greatly used in engineering pedagogy as an adaptive technique to learn and solve complex problems and issues. It is a meta-heuristic approach that is used to solve hybrid computation challenges. GA utilizes selection, crossover, and mutation operators to effectively manage the searching system strategy. This algorithm is derived from natural selection and genetics concepts. GA is an intelligent use of random search supported with historical data to contribute the search in an area of the improved outcome within a coverage framework. Such algorithms are widely used for maintaining high-quality reactions to optimize issues and problems investigation. These techniques are recognized to be somewhat of a statistical investigation process to search for a suitable solution or prevent an accurate strategy for challenges in optimization or searches. These techniques have been produced from natural selection or genetics principles. For random testing, historical information is provided with intelligent enslavement to continue moving the search out from the area of improved features for processing of the outcomes. It is a category of heuristics of evolutionary history using behavioral science-influenced methods like an annuity, gene, preference, or combination (sometimes refers to as hybridization). This method seemed to be a valuable tool to find solutions for problems optimization. In this paper, the author has explored the GAs, its role in engineering pedagogies, and the emerging areas where it is using, and its implementation.

Predation is a driving force of organismal ecology and evolution. Predator-prey interactions, constrained by other environmental factors and historical contingency, shape physical and behavioral phenotypes of organisms on both sides of the interaction arrow. Yet despite the universality of trophic interactions in biology, study of the ecology and evolution of anti-predator defense is challenging because these interactions tend to be brief and unpredictable, and thus gathering direct evidence requires patience and serendipity. The evolution of prey defenses can be studied by DNA sequencing followed by phylogenetic analysis, and the ecology can be studied by field observation and bringing tractable systems into the lab. However, animal models generally do not allow genetic manipulation, strict control of environmental variables, or detailed observation of evolution in real time, all of which are important for demonstrating evolutionary causes and consequences. Developing complementary microbial predator-prey systems can help overcome this hurdle. There is an extensive body of work on microbial experimental evolution, and many microbes come with well-characterized genomes and established methods for genetic manipulation. As understanding of microbial ecology and the mechanisms of their trophic interactions grows apace, these systems are poised to make valuable contributions to our understanding of how predator behaviors evolve, why certain anti-predator defenses evolve and not others, and how multiple defenses function together in a single defense portfolio. These systems will enable us to both test hypotheses formulated from the study of larger organisms and to propose new ones that can be tested in larger organisms with existing methods.

Reticulate evolution through the interchanging of genetic components across organisms can impact significantly on the fitness and adaptation of species. Bread wheat (Triticum aestivum subsp. aestivum) is one of the most important crops in the world. Allopolyploid speciation, frequent hybridization, extensive introgression, and occasional horizontal gene transfer (HGT) have been shaping a typical paradigm of reticulate evolution in bread wheat and its wild relatives, which is likely to have a substantial influence on phenotypic traits and environmental adaptability of bread wheat. In this review, we outlined the evolutionary history of bread wheat and its wild relatives with a highlight on the interspecific hybridization events, demonstrating the reticulate relationship between species/subspecies in the genera Triticum and Aegilops. Furthermore, we discussed the genetic mechanisms and evolutionary significance underlying the introgression of bread wheat and its wild relatives. An in-depth understanding of the evolutionary process of Triticum species should be beneficial to future genetic study and breeding of bread wheat.

B chromosomes are supernumerary chromosomes which are found in addition to the normal standard chromosomes (A chromosomes). B chromosomes are well known to accumulate several types of repeats. Although the evolution of B chromosomes has been subject of numerous studies, the mechanisms of accumulation and evolution of repetitive sequences is not fully understood. Recently, new genomic approaches have shed light on the origin and accumulation of different classes of repetitive sequences in the process of B chromosome formation and evolution. Here we discuss the impact of repetitive sequences accumulation on the evolution of plant B chromosomes.

External impact on the development of fluvial systems is generally exerted by changes in sea level, climate and tectonic movements. In this study it is shown that regional to local differentiation of fluvial response may be caused by semi-direct effects of climate change and tectonic movement, as for instance vegetation cover, frozen soil, snow cover and longitudinal gradient. Such semi-direct effects may be responsible for specific fluvial activity resulting in proper drainage patterns, sedimentation series and erosion-accumulation rates. These conclusions are exemplified by the study of the Tis(z)a catchment in the Pannonian Basin in Hungary and Serbia from the middle of the last glacial to the Pleistocene-Holocene transition. Previous investigations in that catchment are supplemented here by new geomorphological-sedimentological data and OSL-dating. Specific characteristics of this catchment in comparison with other regions are the preponderance of meandering systems during the last glacial and the presence of very large meanders in given time intervals.

Galls are characteristic plant structures formed by cell size enlargement and/or cell proliferation induced by parasitic or pathogenic organisms. Insects are a major inducer of galls, and insect galls can occur on plant leaves, stems, floral buds, flowers, fruits, or roots. Many of these exhibit unique shapes, providing shelter and nutrients to insects. To form unique gall structures, gall-inducing insects are believed to secrete certain effector molecules and hijack host developmental programs. However, the molecular mechanisms of insect gall induction and development remain largely unknown due to the difficulties associated with the study of non-model plants in the wild. Recent advances in next-generation sequencing have allowed us to determine the biological processes in non-model organisms, including gall-inducing insects and their host plants. In this review, we first summarize the adaptive significance of galls for insects and plants. Thereafter, we summarize recent progress regarding the molecular aspects of insect gall formation.

Scientific theories on the functioning and dysfunction of the human brain require a good understanding of both its development — before and after birth, and through maturation to adulthood — and its evolution from the ancestral primate brain. Adopting a complex-systems approach, here we propose that the apparent uniqueness of humans’ cognitive capacities might best be understood as emerging from multiple nested “virtuous cycles.” In particular, we propose that the intimate link that exists between oxygen metabolic loops, cortical expansion, and ultimately cognitive and social demands is a key driver of genetic developmental programs for the human brain. Overall, our proposed evolutionary model makes explicit mechanistic links between metabolism, molecular and cellular brain heterogeneity, and behaviour that may in time provide a clearer understanding of brain developmental trajectories and their disorders.