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The host-microbiota co-metabolite trimethylamine N-oxide (TMAO) is linked to increased cardiovascular risk but how its circulating levels are regulated remains unclear. We applied "explainable" machine learning, univariate, multivariate and mediation analyses of fasting plasma TMAO concentration and a multitude of phenotypes in 1,741 adult Europeans of the MetaCardis study. Here we show that next to age, kidney function is the primary variable predicting circulating TMAO, with microbiota composition and diet playing minor, albeit significant, roles. Mediation analysis suggests a causal relationship between TMAO and kidney function that we corroborate in preclinical models where TMAO exposure increases kidney scarring. Consistent with our findings, patients receiving glucose-lowering drugs with reno-protective properties have significantly lower circulating TMAO when compared to propensity-score matched control individuals. Our analyses uncover a bidirectional relationship between kidney function and TMAO that can potentially be modified by reno-protective anti-diabetic drugs and suggest a clinically actionable intervention for decreasing TMAO-associated excess cardiovascular risk. TMAO is known to be atherothrombotic. Here the authors show that i) kidney function is the main determinant of serum TMAO, ii) TMAO increases kidney scarring with TGF-β1 signalling and iii) anti-diabetic drugs with reno-protective properties such as GLP1R agonists reduce plasma TMAO. [ABSTRACT FROM AUTHOR]

This work aims to present an historical review of the ecosystem services provided by anadromous fish (i.e., species that migrate from the sea to the river to spawn) throughout Human time, as well as of the main related threats, focusing on the Iberian Peninsula region. Anadromous fish provide important provision, cultural, regulatory and supporting ecosystem services across their distribution range and have been extensively exploited by humans since prehistoric times. In the Iberian Peninsula, sea lamprey, allis and twaite shads, sea trout, Atlantic salmon and European sturgeon were once abundantly present in several river basins covering what is now Portuguese and Spanish territory. These species have suffered a severe decline across their distribution range, mainly due to habitat loss and overexploitation. Considered regal delicacies, these fishes were once a statement on the tables of the highest social classes, a much appreciated bounty for the poorer population and are still an important part of the local gastronomy and economy. Such high economic and cultural interest encouraged intensive fishing. Currently, management efforts are being implemented, pairing habitat rehabilitation (e.g., construction of fish passes in obstacles to migration such as weirs and dams) with sustainable fisheries. Considering the present climate change scenario, these species are bound to endure increased pressures, demanding novel management approaches to ensure population numbers that are able to secure their sustainable exploitation. [ABSTRACT FROM AUTHOR]

Leishmaniasis is a neglected disease caused by protozoan parasites of the Leishmania genus. Benzylamines are a class of compounds selectively designed to inhibit the squalene synthase (SQS) that catalyzes the first committed reaction on the sterol biosynthesis pathway. Herein, we studied seven new benzylamines (SBC 37–43) against Leishmania amazonensis. After the first screening of cell viability, two inhibitors (SBC 39 and SBC 40) were selected. Against intracellular amastigotes, SBC 39 and SBC 40 presented selectivity indexes of 117.7 and 180, respectively, indicating high selectivity. Analysis of the sterol composition revealed a depletion of endogenous 24-alkylated sterols such as episterol and 5-dehydroepisterol, with a concomitant accumulation of fecosterol, implying a disturbance in cellular lipid content. This result suggests a blockade of de novo sterol synthesis at the level of SQS and C-5 desaturase. Furthermore, physiological analysis and electron microscopy revealed three main alterations: (1) in the mitochondrion; (2) the presence of lipid bodies and autophagosomes; and (3) the appearance of projections in the plasma membrane. In conclusion, our results support the notion that benzylamines have a potent effect against Leishmania amazonensis and should be an exciting novel pharmaceutical lead for developing new chemotherapeutic alternatives to treat leishmaniasis. [ABSTRACT FROM AUTHOR]

Previous studies have highlighted the positive effects of Estradiol (E2) replacement therapy and physical exercise on skeletal muscle during menopause. However, the comparison effects of exercise training (ET) and estradiol replacement therapy during menopause on skeletal muscle have not been investigated to date. This study aimed to compare the effects of endurance exercise training versus E2 replacement therapy on mitochondrial density, redox status, and inflammatory biomarkers in the skeletal muscle of ovariectomized rats. Thirty female Wistar rats (12-week-old) were randomly assigned into three groups: Untrained ovariectomized rats (UN-OVX, n = 10); untrained ovariectomized rats treated with estradiol replacement therapy (E2-OVX); and, trained ovariectomized rats (TR-OVX). After ovariectomy, the E2-OVX rats were treated subcutaneously with E2 (implanted Silastic® capsule containing 360 μg of 17β-estradiol/mL) while the TR-OVX group performed an exercise training protocol (50–70% of maximal running speed on a treadmill, 60 min/day, 5 days/week for 8 weeks). After euthanasia, the soleus muscle was processed for histological and biochemical evaluations. Only exercise prevented the reduction of maximal oxygen consumption and increased mechanical efficiency (ME). While mitochondrial muscle density, total antioxidant capacity (FRAP), catalase (CAT) activity, and interleukin 10 levels were higher in TR-OVX, only OVX-E2 presented higher CAT activity and lower interleukin 6 levels. Endurance exercise training compared with E2 replacement therapy maintains the aerobic capacity improving the ME of OVX rats. In addition, only endurance exercise training raises the skeletal muscle mitochondrial content and tends to balance the redox and inflammatory status in the skeletal muscle of OVX rats. [ABSTRACT FROM AUTHOR]

Cold-adapted organisms, such as fishes, insects, plants and bacteria produce a group of proteins known as antifreeze proteins (AFPs). The specific functions of AFPs, including thermal hysteresis (TH), ice recrystallization inhibition (IRI), dynamic ice shaping (DIS) and interaction with membranes, attracted significant interest for their incorporation into commercial products. AFPs represent their effects by lowering the water freezing point as well as preventing the growth of ice crystals and recrystallization during frozen storage. The potential of AFPs to modify ice growth results in ice crystal stabilizing over a defined temperature range and inhibiting ice recrystallization, which could minimize drip loss during thawing, improve the quality and increase the shelf-life of frozen products. Most cryopreservation studies using marine-derived AFPs have shown that the addition of AFPs can increase post-thaw viability. Nevertheless, the reduced availability of bulk proteins and the need of biotechnological techniques for industrial production, limit the possible usage in foods. Despite all these drawbacks, relatively small concentrations are enough to show activity, which suggests AFPs as potential food additives in the future. The present work aims to review the results of numerous investigations on marine-derived AFPs and discuss their structure, function, physicochemical properties, purification and potential applications. [ABSTRACT FROM AUTHOR]

While metagenomic sequencing has become the tool of preference to study host-associated microbial communities, downstream analyses and clinical interpretation of microbiome data remains challenging due to the sparsity and compositionality of sequence matrices. Here, we evaluate both computational and experimental approaches proposed to mitigate the impact of these outstanding issues. Generating fecal metagenomes drawn from simulated microbial communities, we benchmark the performance of thirteen commonly used analytical approaches in terms of diversity estimation, identification of taxon-taxon associations, and assessment of taxon-metadata correlations under the challenge of varying microbial ecosystem loads. We find quantitative approaches including experimental procedures to incorporate microbial load variation in downstream analyses to perform significantly better than computational strategies designed to mitigate data compositionality and sparsity, not only improving the identification of true positive associations, but also reducing false positive detection. When analyzing simulated scenarios of low microbial load dysbiosis as observed in inflammatory pathologies, quantitative methods correcting for sampling depth show higher precision compared to uncorrected scaling. Overall, our findings advocate for a wider adoption of experimental quantitative approaches in microbiome research, yet also suggest preferred transformations for specific cases where determination of microbial load of samples is not feasible. Here, the authors use simulated quantitative gut microbial communities to benchmark the performance of 13 common data transformations in determining diversity as well as microbe-microbe and microbe-metadata associations, finding that quantitative approaches incorporating microbial load variation outperform computational strategies in downstream analyses, urging for a widespread adoption of quantitative approaches, or recommending specific computational transformations whenever determination of microbial load of samples is not feasible. [ABSTRACT FROM AUTHOR]

Transfer learning (TL) is the process by which some aspects of a machine learning model generated on a source task is transferred to a target task, to simplify the learning required to solve the target. TL in Genetic Programming (GP) has not received much attention, since it is normally assumed that an evolved symbolic expression is specifically tailored to a problem's data and thus cannot be used in other problems. The goal of this work is to present a broad and diverse study of TL in GP, considering a varied set of source and target tasks, and dealing with questions that have received little, or no attention, in previous GP literature. In particular, this work studies the performance of transferred solutions when the source and target tasks are from different domains, and when they do not share a similar input feature space. Additionally, the relationship between the success and failure of transferred solutions is studied, considering different source and target tasks. Finally, the predictability of TL performance is analyzed for the first time in GP literature. GP-based constructive induction of features is used to carry out the study, a wrapper-based approach where GP is used to construct feature transformations and an additional learning algorithm is used to fit the final model. The experimental work presents several notable results and contributions. First, TL is capable of generating solutions that outperform, in many cases, baseline methods in classification and regression tasks. Second, it is shown that some problems are good source problems while others are good targets in a TL system. Third, the transferability of solutions is not necessarily symmetric between two problems. Finally, results show that it is possible to predict the success of TL in some cases, particularly in classification tasks. [ABSTRACT FROM AUTHOR]

Microbiome community typing analyses have recently identified the Bacteroides2 (Bact2) enterotype, an intestinal microbiota configuration that is associated with systemic inflammation and has a high prevalence in loose stools in humans1,2. Bact2 is characterized by a high proportion of Bacteroides, a low proportion of Faecalibacterium and low microbial cell densities1,2, and its prevalence varies from 13% in a general population cohort to as high as 78% in patients with inflammatory bowel disease2. Reported changes in stool consistency3 and inflammation status4 during the progression towards obesity and metabolic comorbidities led us to propose that these developments might similarly correlate with an increased prevalence of the potentially dysbiotic Bact2 enterotype. Here, by exploring obesity-associated microbiota alterations in the quantitative faecal metagenomes of the cross-sectional MetaCardis Body Mass Index Spectrum cohort (n = 888), we identify statin therapy as a key covariate of microbiome diversification. By focusing on a subcohort of participants that are not medicated with statins, we find that the prevalence of Bact2 correlates with body mass index, increasing from 3.90% in lean or overweight participants to 17.73% in obese participants. Systemic inflammation levels in Bact2-enterotyped individuals are higher than predicted on the basis of their obesity status, indicative of Bact2 as a dysbiotic microbiome constellation. We also observe that obesity-associated microbiota dysbiosis is negatively associated with statin treatment, resulting in a lower Bact2 prevalence of 5.88% in statin-medicated obese participants. This finding is validated in both the accompanying MetaCardis cardiovascular disease dataset (n = 282) and the independent Flemish Gut Flora Project population cohort (n = 2,345). The potential benefits of statins in this context will require further evaluation in a prospective clinical trial to ascertain whether the effect is reproducible in a randomized population and before considering their application as microbiota-modulating therapeutics. A cross-sectional analysis of participants in the MetaCardis Body Mass Index Spectrum cohort finds that the higher prevalence of gut microbiota dysbiosis in individuals with obesity is not observed in those who take statin drugs. [ABSTRACT FROM AUTHOR]

Adherence to a low-gluten diet has become increasingly common in parts of the general population. However, the effects of reducing gluten-rich food items including wheat, barley and rye cereals in healthy adults are unclear. Here, we undertook a randomised, controlled, cross-over trial involving 60 middle-aged Danish adults without known disorders with two 8- week interventions comparing a low-gluten diet (2 g gluten per day) and a high-gluten diet (18 g gluten per day), separated by a washout period of at least six weeks with habitual diet (12 g gluten per day). We find that, in comparison with a high-gluten diet, a low-gluten diet induces moderate changes in the intestinal microbiome, reduces fasting and postprandial hydrogen exhalation, and leads to improvements in self-reported bloating. These observations suggest that most of the effects of a low-gluten diet in non-coeliac adults may be driven by qualitative changes in dietary fibres. [ABSTRACT FROM AUTHOR]

Current sequencing-based analyses of faecal microbiota quantify microbial taxa and metabolic pathways as fractions of the sample sequence library generated by each analysis. Although these relative approaches permit detection of disease-associated microbiome variation, they are limited in their ability to reveal the interplay between microbiota and host health. Comparative analyses of relative microbiome data cannot provide information about the extent or directionality of changes in taxa abundance or metabolic potential. If microbial load varies substantially between samples, relative profiling will hamper attempts to link microbiome features to quantitative data such as physiological parameters or metabolite concentrations. Saliently, relative approaches ignore the possibility that altered overall microbiota abundance itself could be a key identifier of a disease-associated ecosystem configuration. To enable genuine characterization of host-microbiota interactions, microbiome research must exchange ratios for counts. Here we build a workflow for the quantitative microbiome profiling of faecal material, through parallelization of amplicon sequencing and flow cytometric enumeration of microbial cells. We observe up to tenfold differences in the microbial loads of healthy individuals and relate this variation to enterotype differentiation. We show how microbial abundances underpin both microbiota variation between individuals and covariation with host phenotype. Quantitative profiling bypasses compositionality effects in the reconstruction of gut microbiota interaction networks and reveals that the taxonomic trade-off between Bacteroides and Prevotella is an artefact of relative microbiome analyses. Finally, we identify microbial load as a key driver of observed microbiota alterations in a cohort of patients with Crohn's disease, here associated with a low-cell-count Bacteroides enterotype (as defined through relative profiling). [ABSTRACT FROM AUTHOR]

The process of tuning the parameters that characterize evolutionary algorithms is difficult and can be time consuming. This paper presents a self-tuning algorithm for dynamically updating the crossover and mutation probabilities during a run of genetic programming. The genetic operators that are considered in this work are the geometric semantic genetic operators introduced by Moraglio et al. Differently from other existing self-tuning algorithms, the proposed one works by assigning a (different) crossover and mutation probability to each individual of the population. The experimental results we present show the appropriateness of the proposed self-tuning algorithm: on seven different test problems, the proposed algorithm finds solutions of a quality that is better than, or comparable to, the one achieved using the best known values for the geometric semantic crossover and mutation rates for the same problems. Also, we study how the mutation and crossover probabilities change during the execution of the proposed self-tuning algorithm, pointing out an interesting insight: mutation is basically the only operator used in the exploration phase, while crossover is used for exploitation, further improving good quality solutions. [ABSTRACT FROM AUTHOR]

Geometric semantic operators are new and promising genetic operators for genetic programming. They have the property of inducing a unimodal error surface for any supervised learning problem, i.e., any problem consisting in finding the match between a set of input data and known target values (like regression and classification). Thanks to an efficient implementation of these operators, it was possible to apply them to a set of real-life problems, obtaining very encouraging results. We have now made this implementation publicly available as open source software, and here we describe how to use it. We also reveal details of the implementation and perform an investigation of its efficiency in terms of running time and memory occupation, both theoretically and experimentally. The source code and documentation are available for download at . [ABSTRACT FROM AUTHOR]

Several methods to incorporate semantic awareness in genetic programming have been proposed in the last few years. These methods cover fundamental parts of the evolutionary process: from the population initialization, through different ways of modifying or extending the existing genetic operators, to formal methods, until the definition of completely new genetic operators. The objectives are also distinct: from the maintenance of semantic diversity to the study of semantic locality; from the use of semantics for constructing solutions which obey certain constraints to the exploitation of the geometry of the semantic topological space aimed at defining easy-to-search fitness landscapes. All these approaches have shown, in different ways and amounts, that incorporating semantic awareness may help improving the power of genetic programming. This survey analyzes and discusses the state of the art in the field, organizing the existing methods into different categories. It restricts itself to studies where semantics is intended as the set of output values of a program on the training data, a definition that is common to a rather large set of recent contributions. It does not discuss methods for incorporating semantic information into grammar-based genetic programming or approaches based on formal methods. The objective is keeping the community updated on this interesting research track, hoping to motivate new and stimulating contributions. [ABSTRACT FROM AUTHOR]

Bloat can be defined as an excess of code growth without a corresponding improvement in fitness. This problem has been one of the most intensively studied subjects since the beginnings of Genetic Programming. This paper begins by briefly reviewing the theories explaining bloat, and presenting a comprehensive survey and taxonomy of many of the bloat control methods published in the literature through the years. Particular attention is then given to the new Crossover Bias theory and the bloat control method it inspired, Operator Equalisation (OpEq). Two implementations of OpEq are described in detail. The results presented clearly show that Genetic Programming using OpEq is essentially bloat free. We discuss the advantages and shortcomings of each different implementation, and the unexpected effect of OpEq on overfitting. We observe the evolutionary dynamics of OpEq and address its potential to be extended and integrated into different elements of the evolutionary process. [ABSTRACT FROM AUTHOR]

Watershed land use in suburban areas can affect stream biota through degradation of instream habitat, water quality, and riparian vegetation. By monitoring stream biotic communities in various geographic regions, we can better understand and conserve our watershed ecosystems. The objective of this study was to examine the relationship between watershed land use and the integrity of benthic invertebrate communities in eight streams that were assessed over a 3-year period (2001–2003). Sites were selected from coastal Rhode Island watersheds along a residential land-use gradient (4–59%). Using the rapid bioassessment protocol, we collected biological, physicochemical, habitat, and nutrient data from wadeable stream reaches and compared metrics of structure and integrity. Principal component analyses showed significant negative correlation of indicators for stream physicochemical, habitat, and instream biodiversity with increasing residential land use (RLU) in the watershed. The physicochemical variables that were most responsive to percent RLU were conductivity, instream habitat, nitrate, and dissolved inorganic nitrogen (DIN). The positive correlation of DIN with percent RLU indicated an anthropogenic source of pollution affecting the streams. The biotic composition of the streams shifted from sensitive to insensitive taxa as percent RLU increased; the most responsive biological variables were percent Ephemeroptera, percent Scrapers, percent Insects, and the Hilsenhoff biotic index. These data show the importance of land management and conservation at the watershed scale to sustaining the biotic integrity of coastal stream ecosystems. [ABSTRACT FROM AUTHOR]

ATP-binding cassette (ABC) type I importers are widespread in bacteria and play a crucial role in its survival and pathogenesis. They share the same modular architecture comprising two intracellular nucleotide-binding domains (NBDs), two transmembrane domains (TMDs) and a substrate-binding protein. The NBDs bind and hydrolyze ATP, thereby generating conformational changes that are coupled to the TMDs and lead to substrate translocation. A group of multitask NBDs that are able to serve as the cellular motor for multiple sugar importers was recently discovered. To understand why some ABC importers share energy-coupling components, we used the MsmX ATPase from Bacillus subtilis as a model for biological and structural studies. Here we report the first examples of functional hybrid interspecies ABC type I importers in which the NBDs could be exchanged. Furthermore, the first crystal structure of an assigned multitask NBD provides a framework to understand the molecular basis of the broader specificity of interaction with the TMDs. [ABSTRACT FROM AUTHOR]

An introduction to this issue of the journal "Genetic Programming and Evolvable Machines" is presented.

RuvB-Like transcription factors function in cell cycle regulation, development and human disease, such as cancer and heart hyperplasia. The mechanisms that regulate adenosine triphosphate (ATP)-dependent activity, oligomerization and post-translational modifications in this family of enzymes are yet unknown. We present the first crystallographic structure of full-length human RuvBL2 which provides novel insights into its mechanistic action and biology. The ring-shaped hexameric RuvBL2 structure presented here resolves for the first time the mobile domain II of the human protein, which is responsible for protein-protein interactions and ATPase activity regulation. Structural analysis suggests how ATP binding may lead to domain II motion through interactions with conserved N-terminal loop histidine residues. Furthermore, a comparison between hsRuvBL1 and 2 shows differences in surface charge distribution that may account for previously described differences in regulation. Analytical ultracentrifugation and cryo electron microscopy analyses performed on hsRuvBL2 highlight an oligomer plasticity that possibly reflects different physiological conformations of the protein in the cell, as well as that single-stranded DNA (ssDNA) can promote the oligomerization of monomeric hsRuvBL2. Based on these findings, we propose a mechanism for ATP binding and domain II conformational change coupling. [ABSTRACT FROM AUTHOR]