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Abstract Understanding the genetic targets of natural selection is one of the most challenging goals of population genetics. Some of the earliest candidate genes were identified from associations between allozyme allele frequencies and environmental variation. One such example is the clinal polymorphism in the arginine kinase (Ak) gene in the marine snail Littorina fabalis. While other enzyme loci do not show differences in allozyme frequencies among populations, the Ak alleles are near differential fixation across repeated wave exposure gradients in Europe. Here, we use this case to illustrate how a new sequencing toolbox can be employed to characterize the genomic architecture associated with historical candidate genes. We found that the Ak alleles differ by nine nonsynonymous substitutions, which perfectly explain the different migration patterns of the allozymes during electrophoresis. Moreover, by exploring the genomic context of the Ak gene, we found that the three main Ak alleles are located on different arrangements of a putative chromosomal inversion that reaches near fixation at the opposing ends of two transects covering a wave exposure gradient. This shows Ak is part of a large (3/4 of the chromosome) genomic block of differentiation, in which Ak is unlikely to be the only target of divergent selection. Nevertheless, the nonsynonymous substitutions among Ak alleles and the complete association of one allele with one inversion arrangement suggest that the Ak gene is a strong candidate to contribute to the adaptive significance of the inversion.

Abstract Understanding population divergence that eventually leads to speciation is essential for evolutionary biology. High species diversity in the sea was regarded as a paradox when strict allopatry was considered necessary for most speciation events because geographical barriers seemed largely absent in the sea, and many marine species have high dispersal capacities. Combining genome‐wide data with demographic modelling to infer the demographic history of divergence has introduced new ways to address this classical issue. These models assume an ancestral population that splits into two subpopulations diverging according to different scenarios that allow tests for periods of gene flow. Models can also test for heterogeneities in population sizes and migration rates along the genome to account, respectively, for background selection and selection against introgressed ancestry. To investigate how barriers to gene flow arise in the sea, we compiled studies modelling the demographic history of divergence in marine organisms and extracted preferred demographic scenarios together with estimates of demographic parameters. These studies show that geographical barriers to gene flow do exist in the sea but that divergence can also occur without strict isolation. Heterogeneity of gene flow was detected in most population pairs suggesting the predominance of semipermeable barriers during divergence. We found a weak positive relationship between the fraction of the genome experiencing reduced gene flow and levels of genome‐wide differentiation. Furthermore, we found that the upper bound of the ‘grey zone of speciation’ for our dataset extended beyond that found before, implying that gene flow between diverging taxa is possible at higher levels of divergence than previously thought. Finally, we list recommendations for further strengthening the use of demographic modelling in speciation research. These include a more balanced representation of taxa, more consistent and comprehensive modelling, clear reporting of results and simulation studies to rule out nonbiological explanations for general results.

Approaches to both determine abdominal age and identify risk factors for accelerated abdominal age will help delay the onset of several diseases. Here, the authors build an abdominal age predictor by training convolutional neural networks to predict abdominal age from liver and pancreas MRIs.

Physical activity improves quality of life and protects against age-related diseases. With age, physical activity tends to decrease, increasing vulnerability to disease in the elderly. In the following, we trained a neural network to predict age from 115,456 one week-long 100Hz wrist accelerometer recordings from the UK Biobank (mean absolute error = 3.7±0.2 years), using a variety of data structures to capture the complexity of real-world activity. We achieved this performance by preprocessing the raw frequency data as 2,271 scalar features, 113 time series, and four images. We defined accelerated aging for a participant as being predicted older than one’s actual age and identified both genetic and environmental exposure factors associated with the new phenotype. We performed a genome wide association on the accelerated aging phenotypes to estimate its heritability (h_g2 = 12.3±0.9%) and identified ten single nucleotide polymorphisms in close proximity to genes in a histone and olfactory cluster on chromosome six (e.g HIST1H1C, OR5V1). Similarly, we identified biomarkers (e.g blood pressure), clinical phenotypes (e.g chest pain), diseases (e.g hypertension), environmental (e.g smoking), and socioeconomic (e.g income and education) variables associated with accelerated aging. Physical activity-derived biological age is a complex phenotype associated with both genetic and non-genetic factors. Author summary Physical activity improves quality of life and is also an important protective factor for prevalent age-related diseases and outcomes, such as diabetes and mortality. With age, physical activity tends to decrease, increasing vulnerability to disease in the elderly. Does physical activity measured from digital health devices predict one’s biological age? Biological age, as contrast to chronological age (the time that has elapsed since birth), is an indicator of the biological changes that accrue through time that are hypothesized to be one causal factor for age-related diseases. In the following, we trained machine learning models to predict age from 115,456 one week-long wrist accelerometer recordings from participants of the UK Biobank. We then found genetic, environmental, and behavioral factors associated with accelerated age, the difference between biological and chronological age, adding to the evidence of the biological plausibility of our new predictor. If reversable, summarizing complex physical activity into a biological age predictor may be a way of observing the effect of preventative efforts in real-time.

Abstract The correct immobilization and orientation of enzymes on nanosurfaces is a crucial step either for the realization of biosensors, as well as to guarantee the efficacy of the developed biomaterials. In this work we produced two versions of a chimeric protein, namely ArsC-Vmh2 and Vmh2-ArsC, which combined the self-assembling properties of Vmh2, a hydrophobin from Pleurotus ostreatus, with that of TtArsC, a thermophilic arsenate reductase from Thermus thermophilus; both chimeras were heterologously expressed in Escherichia coli and purified from inclusion bodies. They were characterized for their enzymatic capability to reduce As(V) into As(III), as well as for their immobilization properties on polystyrene and gold in comparison to the native TtArsC. The chimeric proteins immobilized on polystyrene can be reused up to three times and stored for 15 days with 50% of activity loss. Immobilization on gold electrodes showed that both chimeras follow a classic Langmuir isotherm model towards As(III) recognition, with an association constant (KAsIII) between As(III) and the immobilized enzyme, equal to 650 (± 100) L mol−1 for ArsC-Vmh2 and to 1200 (± 300) L mol−1 for Vmh2-ArsC. The results demonstrate that gold-immobilized ArsC-Vmh2 and Vmh2-ArsC can be exploited as electrochemical biosensors to detect As(III).

Abstract Sandeels are an ecologically important group of fishes; they are a key part of the food chain serving as food for marine mammals, seabirds and fish. Sandeels are further targeted by a large industrial fishery, which has led to concern about ecosystem effects. In the North Sea, the lesser sandeel Ammodytes marinus is by far the most prevalent species of sandeel in the fishery. Management of sandeel in the North Sea plus the Kattegat is currently divided into seven geographical areas, based on subtle differences in demography, population dynamics and results from simulations of larval dispersal. However, little is known about the underlying genetic population structure. In this study, we used 2,522 SNPs derived from restriction site‐associated DNA sequencing (RADseq) typed in 429 fish representing four main sandeel management areas. Our main results showed (a) a lack of a clear spatially defined genetic structure across the majority of genetic markers and (b) the existence of a group of at least 13 SNPs under strong linkage disequilibrium which together separate North Sea sandeel into three haplotype clusters, suggestive of one or more structural variants in the genome. Analyses of the spatial distribution of these putative structural variants suggest at least partial reproductive isolation of sandeel in the western management area along the Scottish coast, supporting a separate management. Our results highlight the importance of the application of a large number of markers to be able to detect weak patterns of differentiation. This study contributes to increasing the genetic knowledge of this important exploited species, and results can be used to improve our understanding of population dynamics and stock structure.

Summary: Background: Mortality risk stratification based on dichotomising a physiological indicator with a cutoff point might not adequately capture increased mortality risk and might not account for non-linear associations. We aimed to characterise the linear and non-linear relationships of 27 physiological indicators with all-cause mortality to evaluate whether the current clinical thresholds are suitable in distinguishing patients at high risk for mortality from those at low risk. Methods: For this observational cohort study of the US non-institutionalised population, we used data from adults (≥18 years) included in the 1999–2014 National Health and Nutrition Examination Survey (NHANES) linked with National Death Index mortality data collected from Jan 1, 1999, up until Dec 31, 2015. We used Cox proportional hazards regression models adjusted for age, sex, and race or ethnicity to assess associations of physiological indicators with all-cause mortality. We assessed non-linear associations by discretising the physiological indicator into nine quantiles (termed novemtiles) and by using a weighted sum of cubic polynomials (spline). We used ten-fold cross validation to select the most appropriate model using the concordance index, Nagelkerke R2, and Akaike Information Criterion. We identified the level of each physiological indicator that led to a 10% increase in mortality risk to define our cutoffs used to compare with the current clinical thresholds. Findings: We included 47 266 adults of 82 091 assessed for eligibility. 25 (93%) of 27 indicators showed non-linear associations with substantial increases compared with linear models in mortality risk (1·5–2·5-times increase). Height and 60 s pulse were the only physiological indicators to show linear associations. For example, participants with an estimated glomerular filtration rate (GFR) of less than 65 mL/min per 1·73 m2 or between 90–116 mL/min per 1·73 m2 are at moderate (hazard ratio 1–2) mortality risk. Those with a GFR greater than 117 mL/min per 1·73 m2 show substantial (hazard ratio ≥2) mortality risk. Both lower and higher values of cholesterol are associated with increased mortality risk. The current clinical thresholds do not align with our mortality-based cutoffs for fat deposition indices, 60 s pulse, triglycerides, cholesterol-related indicators, alkaline phosphatase, glycohaemoglobin, homoeostatic model assessment of insulin resistance, and GFR. For these indicators, the misalignment suggests the need to consider an additional bound when only one is provided. Interpretation: Most clinical indicators were shown to have non-linear associations with all-cause mortality. Furthermore, considering these non-linear associations can help derive reliable cutoffs to complement risk stratification and help inform clinical care delivery. Given the poor alignment with our proposed cutoffs, the current clinical thresholds might not adequately capture mortality risk. Funding: Ravitz Family Foundation, Forbes Institute for Cancer Discovery, and National Institutes of Health.

The immobilization of POXA1b laccase and its hydrophobin-fused chimera was performed at pristine Multiwalled Carbon Nanotube (MWCNT) and MWCNT-modified electrodes by electrografting of a 2-diazoniumanthraquinone salt. The influence of the hydrophobin domain and the MWCNT functionalization with anthraquinone groups towards immobilization of laccase was compared by direct electrochemistry under O2 and electrochemical biosensing of phenols. The hydrophobin domain affords the stable dispersion of MWCNT in water/ethanol, while being detrimental to the direct electron transfer between POXA1b and the electrode. On the contrary, the stronger hydrophobic interactions between anthraquinone and laccase affords direct electrochemistry of POXA1b and enabled the design of a highly sensitive phenol biosensor, reaching a limit-of-detection (LOD) of 2 pM and sensitivity of 23,600 mA L mmol−1 cm−2 for catechol, and a LOD of 15 nM and sensitivity of 0.053 mA L mmol−1 cm−2 for dopamine.

The microbiome is a new frontier for building predictors of human phenotypes. However, machine learning in the microbiome is fraught with issues of reproducibility, driven in large part by the wide range of analytic models and metagenomic data types available. We aimed to build robust metagenomic predictors of host phenotype by comparing prediction performances and biological interpretation across 8 machine learning methods and 4 different types of metagenomic data. Using 1,570 samples from 300 infants, we fit 7,865 models for 6 host phenotypes. We demonstrate the dependence of accuracy on algorithm choice and feature definition in microbiome data and propose a framework for building microbiome-derived indicators of host phenotype. We additionally identify biological features predictive of age, sex, breastfeeding status, historical antibiotic usage, country of origin, and delivery type. Our complete results can be viewed at http://apps.chiragjpgroup.org/ubiome_predictions/.

Massive genotyping of single nucleotide polymorphisms (SNP) has opened opportunities for analyzing the way in which selection shapes genomes. Artificial or natural selection usually leaves genomic signatures associated with selective sweeps around the responsible locus. Strong selective sweeps are most often identified either by lower genetic diversity than the genomic average and/or islands of runs of homozygosity (ROHi). Here, we conducted an analysis of selective sweeps in turbot (Scophthalmus maximus) using two SNP datasets from a Northeastern Atlantic population (36 individuals) and a domestic broodstock (46 individuals). Twenty-six families (∼ 40 offspring per family) from this broodstock and three SNP datasets applying differing filtering criteria were used to adjust ROH calling parameters. The best-fitted genomic inbreeding estimate (FROH) was obtained by the sum of ROH longer than 1 Mb, called using a 21,615 SNP panel, a sliding window of 37 SNPs and one heterozygous SNP per window allowed. These parameters were used to obtain the ROHi distribution in the domestic and wild populations (49 and 0 ROHi, respectively). Regions with higher and lower genetic diversity within each population were obtained using sliding windows of 37 SNPs. Furthermore, those regions were mapped in the turbot genome against previously reported genetic markers associated with QTL (Quantitative Trait Loci) and outlier loci for domestic or natural selection to identify putative selective sweeps. Out of the 319 and 278 windows surpassing the suggestive pooled heterozygosity thresholds (ZHp) in the wild and domestic population, respectively, 78 and 54 were retained under more restrictive ZHp criteria. A total of 116 suggestive windows (representing 19 genomic regions) were linked to either QTL for production traits, or outliers for divergent or balancing selection. Twenty-four of them (representing 3 genomic regions) were retained under stricter ZHp thresholds. Eleven QTL/outlier markers were exclusively found in suggestive regions of the domestic broodstock, 7 in the wild population and one in both populations; one (broodstock) and two (wild) of those were found in significant regions retained under more restrictive ZHp criteria in the broodstock and the wild population, respectively. Genome mining and functional enrichment within regions associated with selective sweeps disclosed relevant genes and pathways related to aquaculture target traits, including growth and immune-related pathways, metabolism and response to hypoxia, which showcases how this genome atlas of genetic diversity can be a valuable resource to look for candidate genes related to natural or artificial selection in turbot populations.

Nanomaterials have become essential components for the development of biosensors since such nanosized compounds were shown to clearly increase the analytical performance. The improvements are mainly related to an increased surface area, thus providing an enhanced accessibility for the analyte, the compound to be detected, to the receptor unit, the sensing element. Nanomaterials can also add value to biosensor devices due to their intrinsic physical or chemical properties and can even act as transducers for the signal capture. Among the vast amount of examples where nanomaterials demonstrate their superiority to bulk materials, the combination of different nano-objects with different characteristics can create phenomena which contribute to new or improved signal capture setups. These phenomena and their utility in biosensor devices are summarized in a non-exhaustive way where the principles behind these synergetic effects are emphasized.

Emerging research on followership has overwhelmingly been focused on for‐profit organizations. This research investigates four British congregations from different Christian denominations to explore how differing contexts shape the understanding of followership in nonprofit organizations. Using implicit followership theory, we analyze the value sets deriving from theological‐ideological, institutional, and local contexts and explore informants' perceptions of ideal followership attributes. By conducting 26 semi‐structured interviews with three different types of actors, we found that church members found themselves in a dialectic relationship between institutional norms and local settings, which shape the way followership is perceived. In terms of follower attributes, we identified faith‐related and ethical as well as relational attributes to be prevalent. With this research, we advance current understandings of how effective leader‐follower relationships in nonprofit organizations can be formed highlighting the importance of differing contexts for perceiving the role of followers. [ABSTRACT FROM AUTHOR]

The reduction of dioxygen to produce selectively H2O2 or H2O is crucial in various fields. While platinum‐based materials excel in 4H+/4e− oxygen reduction reaction (ORR) catalysis, cost and resource limitations drive the search for cost‐effective and abundant transition metal catalysts. It is thus of great importance to understand how the selectivity and efficiency of 3d‐metal ORR catalysts can be tuned. In this context, we report on a Co complex supported by a bisthiolate N2S2‐donor ligand acting as a homogeneous ORR catalyst in acetonitrile solutions both in the presence of a one‐electron reducing agent (selectivity for H2O of 93 % and TOFi=3 000 h−1) and under electrochemically‐assisted conditions (0.81 V <η<1.10 V, selectivity for H2O between 85 % and 95 %). Interestingly, such a predominant 4H+/4e− pathway for Co‐based ORR catalysts is rare, highlighting the key role of the thiolate donor ligand. Besides, the selectivity of this Co catalyst under chemical ORR conditions is inverse with respect to the Mn and Fe catalysts supported by the same ligand, which evidences the impact of the nature of the metal ion on the ORR selectivity. [ABSTRACT FROM AUTHOR]

Chromosomal rearrangements can lead to the coupling of reproductive barriers, but whether and how they contribute to the completion of speciation remains unclear. Marine snails of the genus Littorina repeatedly form hybrid zones between populations segregating for multiple inversion arrangements, providing opportunities to study their barrier effects. Here, we analyzed 2 adjacent transects across hybrid zones between 2 ecotypes of Littorina fabalis ("large" and "dwarf") adapted to different wave exposure conditions on a Swedish island. Applying whole-genome sequencing, we found 12 putative inversions on 9 of 17 chromosomes. Nine of the putative inversions reached near differential fixation between the 2 ecotypes, and all were in strong linkage disequilibrium. These inversions cover 20% of the genome and carry 93% of divergent single nucleotide polymorphisms (SNPs). Bimodal hybrid zones in both transects indicated that the 2 ecotypes of Littorina fabalis maintain their genetic and phenotypic integrity following contact. The bimodality reflects the strong coupling between inversion clines and the extension of the barrier effect across the whole genome. Demographic inference suggests that coupling arose during a period of allopatry and has been maintained for > 1,000 generations after secondary contact. Overall, this study shows that the coupling of multiple chromosomal inversions contributes to strong reproductive isolation. Notably, 2 of the putative inversions overlap with inverted genomic regions associated with ecotype differences in a closely related species (Littorina saxatilis), suggesting the same regions, with similar structural variants, repeatedly contribute to ecotype evolution in distinct species. [ABSTRACT FROM AUTHOR]

Purpose – This paper identifies the strategic changes and explores the solutions for talent development and leadership management to address the challenges faced by the funeral service industry in Hong Kong. Design/methodology/approach – In this study, semi-structured, in-depth interviews were conducted with seven key personnel (funeral director, salesperson, coffin shop owner, and mortuary transporter) engaged in the funeral service industry in Hong Kong. Thematic coding was used to identify and organize emerging themes from the data. Findings – Four overarching themes were identified: (1) Perception of the funeral service industry in Hong Kong; (2) Recruitment, retention, and talent development; (3) Prospects of the funeral service industry in Hong Kong; and (4) Other novel challenges. The findings reveal continuous, radical, and complex challenges that may exceed the capacity of any leader to develop workable solutions. Originality/value – The funeral service industry is facing radical challenges in modern times. A death-denying attitude is observed, which has severely undermined the study of the funeral service industry.