Substitution Model Research Articles

Substitution of physical activity for sedentary behaviour contributes to executive function improvement among young adults: a longitudinal study

BackgroundSedentary lifestyles may affect cognitive capacities which are essential for daily tasks. There is a lack of research on the effects of replacing sedentary behaviour with physical activity on executive function, as well as the dose–response relationship between physical activity and executive function among young adults, underscoring the critical need for prompt investigation.MethodsEmploying a longitudinal experimental design, the study conducted two assessments (baseline and at three months) on a cohort of participants. A total of 78 young adults with a mean age of 25 years old were recruited for the study. Physical activity and sedentary behaviour were measured using accelerometer, which provided objective data on the intensity and duration of the participants’ daily activity. Executive function was measured using the Trail Making Test (TMT). An isotemporal substitution model was employed to analyze the effects of replacing sedentary time with physical activity of different intensities. Additionally, mixed-effect models were used to explore the dose–response relationships between physical activity, sedentary behaviour, and executive function.ResultsThe reallocation of 30 min of daily time from sedentary behaviour (SED) to light physical activity (LPA) significantly reduced Trail Making Test (TMT) completion times, suggesting improvements in cognitive processing speed. Conversely, shifting the same duration from SED to moderate-to-vigorous physical activity (MVPA) enhanced the accuracy rate on the TMT. Sedentary time was associated with longer TMT completion times but did not significantly affect the accuracy rate. Additionally, a dose–response relationship was observed, with increases in MVPA, caloric expenditure, and step count correlating with shorter TMT completion times. In contrast, increases in LPA and caloric expenditure were associated with higher TMT correct response rates.ConclusionThe substitution of sedentary behaviour with physical activity may be a beneficial strategy to enhance executive function among young adults. These results underscore the importance of reducing sedentary time and promoting physical activity in the daily routine of young individuals to support cognitive development. Future research should explore the underlying mechanisms.

Risk ranking of mycotoxins in plant-based meat and dairy alternatives under protein transition scenarios

While reducing the consumption of animal-source foods is recommended for planetary and human health, potential emerging food safety risks associated with the transition to dietary patterns featuring plant-based meat (PBMA) and dairy alternatives (PBDA) remain unexplored. We assessed the exposure to mycotoxins and ranked the associated health risks related to the consumption of PBMA and PBDA. We simulated diets by replacing animal-source proteins with their plant-based alternatives. A risk ratio method, based on the hazard quotient (HQ), was applied to rank mycotoxin-related food safety risks. An aggregated dataset containing contamination data of 45 mycotoxins distributed over 182 PBDA and 131 PBMA samples, collected and analyzed in Europe, representing a convenience sample, was used as input in our risk assessment. The highest risk mycotoxins identified for PBMA in the lower bound scenario (LB) were the sum of aflatoxins (sum AF), alternariol monomethyl ether (AME), aflatoxin B1 (AFB1) and alternariol (AOH), with HQs for children of 121.3, 66.8, 24.0 and 4.3, respectively. In the milk substitution model (LB), HQs of 4.9 (sum AF) and 1.4 (AFB1) were calculated for children, indicating a potential food safety risk. Further analysis demonstrated that soy-based meat alternatives are the highest risk food products, in particular for sum AF, AME, AOH and AFB1. With regard to PBDA, highest HQs were found for sum AF in almond and oat drink, and AFB1 in oat drink. This research presents an approach to overcome the lack of data in the assessment of emerging risks associated with the shift to more sustainable dietary patterns.

Examining the molecular clock hypothesis for the contemporary evolution of the rabies virus.

The molecular clock hypothesis assumes that mutations accumulate on an organism's genome at a constant rate over time, but this assumption does not always hold true. While modelling approaches exist to accommodate deviations from a strict molecular clock, assumptions about rate variation may not fully represent the underlying evolutionary processes. There is considerable variability in rabies virus (RABV) incubation periods, ranging from days to over a year, during which viral replication may be reduced. This prompts the question of whether modelling RABV on a per infection generation basis might be more appropriate. We investigate how variable incubation periods affect root-to-tip divergence under per-unit time and per-generation models of mutation. Additionally, we assess how well these models represent root-to-tip divergence in time-stamped RABV sequences. We find that at low substitution rates (<1 substitution per genome per generation) divergence patterns between these models are difficult to distinguish, while above this threshold differences become apparent across a range of sampling rates. Using a Tanzanian RABV dataset, we calculate the mean substitution rate to be 0.17 substitutions per genome per generation. At RABV's substitution rate, the per-generation substitution model is unlikely to represent rabies evolution substantially differently than the molecular clock model when examining contemporary outbreaks; over enough generations for any divergence to accumulate, extreme incubation periods average out. However, measuring substitution rates per-generation holds potential in applications such as inferring transmission trees and predicting lineage emergence.

Substituting time spent in physical activity and sedentary time and its association with cardiovascular disease among northwest Chinese adults

ObjectivesTo examine the association between physical activity (PA) and leisure-time sedentary time and cardiovascular disease (CVD). MethodsThis cross-sectional study used baseline data from the Regional Ethnic Cohort Study in Northwest China from June 2018 to May 2019. PA and leisure-time sedentary time were self-reported. Logistic regression models analyzed the association of PA and leisure-time sedentary time with CVD prevalence individually and jointly. Restricted cubic spline analyses assessed dose-response relationships. Isotemporal substitution models were used to investigate substituting leisure-time sedentary time, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) with CVD prevalence. ResultsThe prevalence of CVD was 31.8 %. Compared to the lowest quartile, participants in the highest quartile of total PA had a 32 % lower CVD prevalence (odds ratio [OR]: 0.68, 95 % confidence interval [CI]: 0.62–0.74; P for trend <0.001). The fully adjusted OR for the highest quartile of leisure-time sedentary time compared to the lowest quartile was 1.09 (1.01–1.18; P for trend =0.04). An L-shaped dose-response relationship was observed between PA and CVD prevalence. An active lifestyle and reduced daily leisure-time sedentary time were associated with a 26 % (0.74 [0.63–0.86]) lower CVD prevalence. Additionally, substituting 30 min/day of leisure-time sedentary time with equivalent MVPA was associated with a 2 % (0.98 [0.97–0.99]) reduction in CVD prevalence. Substituting sedentary time with LPA was associated with a lower CVD prevalence in females. ConclusionsAn active lifestyle was associated with a lower prevalence of CVD in regional populations, suggesting a feasible strategy for CVD prevention and regional health promotion.

Delayed luminescence and thermoluminescence in laboratory-grown diamonds

The “blue-green” phosphorescence/thermoluminescence is most commonly observed in diamonds following excitation at or above the indirect band gap and has been explained by a substitutional nitrogen-boron donor-acceptor pair recombination model. “Orange” and “red” phosphorescence have also been frequently observed in laboratory-grown near-colorless high-pressure high-temperature diamonds following optical excitation and their luminescence mechanisms are shown to be different from that of the blue-green phosphorescence. The physics of the orange and red luminescence and phosphorescence bands including the optical-excitation dependency (UV-NIR), temperature dependency (20K–573K), and related charge transfer process are investigated by a combination of self-built time-resolved imaging/spectroscopic techniques. In this paper, an alternative model for long-lived phosphorescence based on charge trapping is proposed to explain the orange phosphorescence/thermoluminescence band. Additionally, the red phosphorescence band is attributed to point defect, which possibly has a three-level phosphorescence system. Published by the American Physical Society 2024

Assessing the impact of 24-hour activity behaviors on cardiorespiratory fitness in the older adult: a component analysis approach.

Cardiorespiratory fitness (CRF) serves as a critical measure of the cardiovascular system's efficiency in delivering oxygenated blood to tissues and organs. Understanding the relationship between various activity behaviors and CRF is essential for devising effective health interventions for the older adult population. This study aimed to investigate the association between 24-h activity behaviors and CRF in older adult individuals, utilizing compositional data analysis. We utilized baseline data from the "Fifth National Physical Fitness Monitoring Cohort Study in Tianjin, China," which included 540 older adult participants. Physical activity and sedentary behavior were objectively measured using a three-dimensional accelerometer, and CRF was assessed via a gas metabolism analyzer. Compositional data analysis was employed to examine the relationships between 24-h activity behaviors-specifically, moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary behavior (SB), and sleep (SLP)-and CRF. The analysis demonstrated that MVPA was significantly positively associated with CRF (βMVPA = 5.36, p < 0.01), whereas SB was significantly negatively associated (βSB = -3.97, p < 0.01). No significant associations were observed for LPA and SLP with CRF. The isochronous substitution model revealed that reallocating 15 min of MVPA to SB, LPA, or SLP significantly decreased CRF by 0.31, 0.27, and 0.23 mL/kg/min, respectively. Conversely, substituting 15 min of SB, LPA, or SLP with MVPA resulted in increases in CRF by 0.29, 0.22, and 0.17 mL/kg/min, respectively. Additionally, replacing SB with LPA or SLP led to improvements in CRF, though these changes were not significant, underscoring the potential benefits of reducing sedentary time and enhancing physical activity levels. These findings underscore the critical role of increasing MVPA and reducing SB in improving CRF among the older adult. This study provides a robust scientific foundation for health promotion and intervention strategies targeting older adults. Comprehensive modifications to daily activity patterns are imperative for optimizing cardiovascular health in this population.

An efficient deep learning method for amino acid substitution model selection.

Amino acid substitution models play an important role in studying the evolutionary relationships among species from protein sequences. The amino acid substitution model consists of a large number of parameters; therefore, it is estimated from hundreds or thousands of alignments. Both general models and clade-specific models have been estimated and widely used in phylogenetic analyses. The maximum likelihood method is normally used to select the best fit model for a specific protein alignment under the study. A number of studies have discussed theoretical concerns as well as computational burden of the maximum likelihood methods in model selection. Recently, machine learning methods have been proposed for selecting nucleotide models. In this paper, we propose a method to measure substitution rates among amino acids (called summary statistics) from protein alignments to efficiently train a deep learning network of so-called ModelDetector for detecting amino acid substitution models. The ModelDetector network was trained from 2,246,400 alignments on a computer with 8 cores (without GPU) in about 3.3 hours. Experiments on simulation data showed that the accuracy of the ModelDetector was comparable with that of the maximum likelihood method ModelFinder. It was orders of magnitude faster than the maximum likelihood method in inferring amino acid substitution models and able to analyze genome alignments with millions of sites in minutes. The results indicate that the deep learning network can play as a promising tool for amino acid substitution model selection.

Retraction Note: Polynomial cryptographic optical steganography substitution model for the telehealth system with multimedia data

Retraction Note: Polynomial cryptographic optical steganography substitution model for the telehealth system with multimedia data

Robustness of Divergence Time Estimation Despite Gene Tree Estimation Error: A Case Study of Fireflies (Coleoptera: Lampyridae).

Genomic data has become ubiquitous in phylogenomic studies, including divergence time estimation, but provide new challenges. These challenges include, amongst others, biological gene tree discordance, methodological gene tree estimation error, and computational limitations on performing full Bayesian inference under complex models. In this study, we use a recently published firefly (Coleoptera: Lampyridae) anchored hybrid enrichment dataset (AHE; 436 loci for 88 Lampyridae species and 10 outgroup species) as a case study to explore gene tree estimation error and the robustness of divergence time estimation. First, we explored the amount of model violation using posterior predictive simulations because model violations are likely to bias phylogenetic inferences and produce gene tree estimation error. We specifically focused on missing data (either uniformly distributed or systematically) and the distribution of highly variable and conserved sites (either uniformly distributed or clustered). Our assessment of model adequacy showed that standard phylogenetic substitution models are not adequate for any of the 436 AHE loci. We tested if the model violations and alignment errors resulted indeed in gene tree estimation error by comparing the observed gene tree discordance to simulated gene tree discordance under the multispecies coalescent model. Thus, we show that the inferred gene tree discordance is not only due to biological mechanism but primarily due to inference errors. Lastly, we explored if divergence time estimation is robust despite the observed gene tree estimation error. We selected four subsets of the full AHE dataset, concatenated each subset and performed a Bayesian relaxed clock divergence estimation in RevBayes. The estimated divergence times overlapped for all nodes that are shared between the topologies. Thus, divergence time estimation is robust using any well selected data subset as long as the topology inference is robust.

Screen time and obesity prevalence in adolescents: an isotemporal substitution analysis

BackgroundWe examined the associations between screen time and adolescent obesity and the associations of reallocating screen time to other activities using isotemporal substitution models. Understanding the association between screen time and obesity may provide additional insights into effective obesity prevention strategies in adolescents.MethodsWe conducted a cross-sectional analysis of 5,180 adolescents (4th and 7th grade students) from the Korean Children and Youth Panel Survey 2018. Participants reported their height, weight, and average time spent watching television, using computer, using smartphone, and other after-school activities. Obesity was defined as BMI-for-age and -sex ≥ 95th percentile based on the 2017 Korean National Growth Charts. We performed multivariable logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between screen time and obesity prevalence, adjusting for potential confounders.ResultsProlonged smartphone use (≥ 180 vs. <60 m/d: OR [95% CI] = 2.75 [2.06, 3.68]) was associated with a higher obesity prevalence. Television watching (≥ 120 vs. <60 min/d) was positively associated with obesity prevalence among 4th grade students (2.09 [1.51, 2.89]) but the association was not observed among 7th grade students (0.97 [0.63, 1.49]). One-hour increments of any non-screen time activities, with a simultaneous 1-hour decrease in combined screen time, were associated with a lower obesity prevalence (physical activity: 0.75 [0.65, 0.85]; sleeping: 0.69 [0.62, 0.78]; hanging out with friends: 0.80 [0.71, 0.89]; reading: 0.82 [0.69, 0.97]; studying: 0.84 [0.78, 0.90]; chatting with parents: 0.89 [0.88, 0.98]).ConclusionsOur data suggest that public health strategies that reduce screen time and increase time for non-screen time activities, such as physical activity, may be effective in lowering adolescent obesity prevalence.

Associations Between Childcare Physical Activity and Sedentary Time and Early Childhood Developmental Outcomes: A Compositional and Isotemporal Substitution Analysis.

Physical activity and sedentary time are independently associated with health and developmental outcomes in preschool children. However, the integrated nature of these behaviours on early life outcomes, particularly during childcare hours, is currently understudied. As such, the aim of this study was to examine the association between preschool children's physical activity and sedentary time during childcare and various developmental outcomes (psychosocial, cognitive and fundamental movement skills). A total of 107 preschool children (Mage: 41 ± 6 months) recruited from London, Canada, wore ActiGraph wGT3X-BT accelerometers during childcare hours to measure their sedentary time, light intensity physical activity (LPA) and moderate-to-vigorous intensity physical activity (MVPA). Developmental outcomes, including psychosocial health (internalising, externalising, prosocial behaviour), indicators of cognitive development (memory, inhibitory control) and fundamental movement skills (locomotor control, object control, total fundamental movement), were assessed using validated tools. Compositional regression and isotemporal substitution models were estimated to examine how movement compositions in childcare were associated with developmental outcomes. Engaging in more MVPA relative to LPA and sedentary time was associated with fewer internalising symptoms and better total fundamental movement skills and object control skills, whilst spending more time in LPA relative to MVPA and sedentary time was associated with more internalising symptoms and worse object control skills. Isotemporal substitution models suggested that theoretically increasing sedentary time or engaging in MVPA at the expense of time engaging in LPA during childcare is associated with lower internalising symptoms. The findings of this study provide preliminary evidence that engaging in MVPA during childcare, at the expense of time in LPA or sedentary time, is associated with children's fundamental movement skills and psychosocial development. Further longitudinal research is required, with larger samples of young children, to assess the mechanisms through which childcare movement behaviour compositions may interact with developmental outcomes, including contextualising both sedentary time and LPA. ClinicalTrials.gov identifier: NCT05359536.

Reallocating time between movement behaviors has implications for post-secondary students’ mental health and wellbeing

Objective: Examine the theoretical impact of reallocating time between self-reported moderate-to-vigorous physical activity (MVPA), recreational screen time, and sleep on psychological distress and mental wellbeing among post-secondary students. Participants: 24,742 post-secondary students (M age=24.3 ± 7.72 SD years; 66.4% women) from Cycle 1 of the Canadian Campus Wellbeing Survey. Methods: Cross-sectional isotemporal substitution modeling. Results: Replacing 20 min of screen time with either sleep or MVPA was associated with lower psychological distress, greater mental wellbeing, lower odds of reporting mild-to-severe psychological distress and low mental wellbeing, except for reallocating screen time to sleep among students who exceed the sleep guideline recommendations. Reallocating time between sleep and MVPA revealed noteworthy patterns: replacing sleep with MVPA was associated with greater mental wellbeing but not lower psychological distress. Conclusions: Findings highlight the potential mental health benefits of replacing screen time with sleep or MVPA as an integrative whole day approach to promote campus wellness.

Widespread adaptive evolution in angiosperm photosystems provides insight into the evolution of photosystem II repair.

Oxygenic photosynthesis generates the initial energy source that fuels nearly all life on Earth. At the heart of the process are the photosystems, which are pigment binding multi-protein complexes that catalyse the first step of photochemical conversion of light energy into chemical energy. Here, we investigate the molecular evolution of the plastid-encoded photosystem subunits at single-residue resolution across 773 angiosperm species. We show that despite an extremely high level of conservation, 7% of residues in the photosystems, spanning all photosystem subunits, exhibit hallmarks of adaptive evolution. Through in silico modelling of these adaptive substitutions, we uncover the impact of these changes on the predicted properties of the photosystems, focussing on their effects on co-factor binding and inter-subunit interface formation. By analyzing these cohorts of changes, we reveal that evolution has repeatedly altered the interaction between photosystem II and its D1 subunit in a manner that is predicted to reduce the energetic barrier for D1 turnover and photosystem repair. Together, these results provide insight into the trajectory of photosystem adaptation during angiosperm evolution.

A Molecular Temporal Evolutionary Framework of Land Plants and the Age of Angiosperms

A series of Bayesian molecular clock analyses with varying model combinations, parameters, and tree topologies were conducted to establish a temporal evolutionary framework of land plants and to estimate the age of angiosperms. The data consisted of five organellar and nuclear genes, 633 taxa, and 23 fossil calibration points (FCPs). The analyses were evaluated using an internal search thoroughness measure, effective sample sizes, and two external criteria: the consensus land plant phylogeny and a newly developed method that used the Hennigian reciprocal illumination principle to compare molecular age estimates of 21 nodes representing major land plant clades and the root split in green plants with those of their fossils in an a posteriori fashion. The results show that an analysis using a general time reversible (GTR) DNA substitution model, log normal branch-rate distribution, and Yule tree prior represented the best model combination, with the Birth-Death tree prior being equally optimal. This analysis estimated the age of the land plant crown group as 496.95 million years (MY), with a 95% highest posterior density (HPD) of 465.66–531.43 MY, and the age of the angiosperm crown group as 219.93 MY, with a 95% HPD of 184.09–256.82 MY. The former agrees with the fossil evidence, but the latter is significantly older than the fossil ages. A thorough examination of fossil evidence of angiosperms, as well as their evolutionary history in light of recent knowledge of morphology, physiology, and atmospheric CO2 concentration in the Mesozoic era, suggests that angiosperm radiation might have been delayed after their origin and that the current fossil record probably reflects only the products of that radiation, not the origin of angiosperms. Overall, the study shows that both molecular clock analyses and fossil studies, while agreeing on some aspects but disagreeing on others, can help develop a complete understanding of the temporal evolutionary history of land plants.

Inference of Phylogenetic Networks from Sequence Data using Composite Likelihood.

While phylogenies have been essential in understanding how species evolve, they do not adequately describe some evolutionary processes. For instance, hybridization, a common phenomenon where interbreeding between two species leads to formation of a new species, must be depicted by a phylogenetic network, a structure that modifies a phylogenetic tree by allowing two branches to merge into one, resulting in reticulation. However, existing methods for estimating networks become computationally expensive as the dataset size and/or topological complexity increase. The lack of methods for scalable inference hampers phylogenetic networks from being widely used in practice, despite accumulating evidence that hybridization occurs frequently in nature. Here, we propose a novel method, PhyNEST (Phylogenetic Network Estimation using SiTe patterns), that estimates binary, level-1 phylogenetic networks with a fixed, user-specified number of reticulations directly from sequence data. By using the composite likelihood as the basis for inference, PhyNEST is able to use the full genomic data in a computationally tractable manner, eliminating the need to summarize the data as a set of gene trees prior to network estimation. To search network space, PhyNEST implements both hill climbing and simulated annealing algorithms. PhyNEST assumes that the data are composed of coalescent independent sites that evolve according to the Jukes-Cantor substitution model and that the network has a constant effective population size. Simulation studies demonstrate that PhyNEST is often more accurate than two existing composite likelihood summary methods (SNaQ and PhyloNet) and that it is robust to at least one form of model misspecification (assuming a less complex nucleotide substitution model than the true generating model). We applied PhyNEST to reconstruct the evolutionary relationships among Heliconius butterflies and Papionini primates, characterized by hybrid speciation and widespread introgression, respectively. PhyNEST is implemented in an open-source Julia package and is publicly available at https://github.com/sungsik-kong/PhyNEST.jl.

Cyborging HRM theory: from evolution to revolution – the challenges and trajectories of AI for the future role of HRM

PurposeHuman Resource Management (HRM) is a critical organizational function, which has continued to evolve. We aim to explore how different HRM will be in the workplace of the future and why, from both strategic and practical perspectives. We present and discuss core HRM practices, such as recruitment, selection and training, as well as peripheral activities, such as monitoring health and safety, and diversity management, reflecting on how they may transform in the workplace of the future.Design/methodology/approachThis is a conceptual thought piece, building on the Substitution, Augmentation, Modification and Redefinition (SAMR) model, to offer a futuristic view of HRM in the era of AI.FindingsDiscussing the contemporary challenges of Artificial Intelligence, which we predict will lead to what we term Cyborging HRM.Practical implicationsThis study can help HR managers and practitioners to be prepared for AI-embedded HRM systems in the future. For academics, it offers an innovative framework to establish future writing on HRM in the AI era.Originality/valueAI is pushing HRM and the profession will have to undergo a revolutionary rather than evolutionary transformation in order to remain a necessary and valuable function for organizations. Our elaboration of the SAMR model and suggested implications for the future transformation of HRM should be worthwhile to organizations, management and the wider society.

A Case for First-Class Environments

Formalizations of programming languages typically adopt the substitution model from the lambda calculus. However, substitution creates notorious complications for reasoning and implementation. Furthermore, it is disconnected from practical implementations, which normally adopt environments and closures. In this paper we advocate for formalizing programming languages using a novel style of small-step environment-based semantics , which avoids substitution and is closer to implementations. We present a call-by-value statically typed calculus, called λ E , using our small-step environment semantics. With our alternative environment semantics programming language constructs for first-class environments arise naturally, without creating significant additional complexity. Therefore, λ E also adopts first-class environments, adding expressive power that is not available in conventional lambda calculi. λ E is a conservative extension of the call-by-value Simply Typed Lambda Calculus (STLC), and employs de Bruijn indices for its formalization, which fit naturally with the environment-based semantics. Reasoning about λ E is simple, and in many cases simpler than reasoning about the traditional STLC. We show an abstract machine that implements the semantics of λ E , and has an easy correctness proof. We also extend λ E with references. We show that λ E can model a simple form of first-class modules, and suggest using first-class environments as an alternative to objects for modelling capabilities. All technical results are formalized in the Coq proof assistant. In summary, our work shows that the small-step environment semantics that we adopt has three main and orthogonal benefits: 1) it simplifies the notorious binding problem in formalizations and proof assistants; 2) it is closer to implementations; and 3) additional expressive power is obtained from first-class environments almost for free.

Assessing the Adequacy of Morphological Models using Posterior Predictive Simulations.

Reconstructing the evolutionary history of different groups of organisms provides insight into how life originated and diversified on Earth. Phylogenetic trees are commonly used to estimate this evolutionary history. Within Bayesian phylogenetics a major step in estimating a tree is in choosing an appropriate model of character evolution. While the most common character data used is molecular sequence data, morphological data remains a vital source of information. The use of morphological characters allows for the incorporation fossil taxa, and despite advances in molecular sequencing, continues to play a significant role in neontology. Moreover, it is the main data source that allows us to unite extinct and extant taxa directly under the same generating process. We therefore require suitable models of morphological character evolution, the most common being the Mk Lewis model. While it is frequently used in both palaeobiology and neontology, it is not known whether the simple Mk substitution model, or any extensions to it, provide a sufficiently good description of the process of morphological evolution. In this study we investigate the impact of different morphological models on empirical tetrapod data sets. Specifically, we compare unpartitioned Mk models with those where characters are partitioned by the number of observed states, both with and without allowing for rate variation across sites and accounting for ascertainment bias. We show that the choice of substitution model has an impact on both topology and branch lengths, highlighting the importance of model choice. Through simulations, we validate the use of the model adequacy approach, posterior predictive simulations, for choosing an appropriate model. Additionally, we compare the performance of model adequacy with Bayesian model selection. We demonstrate how model selection approaches based on marginal likelihoods are not appropriate for choosing between models with partition schemes that vary in character state space (i.e., that vary in Q-matrix state size). Using posterior predictive simulations, we found that current variations of the Mk model are often performing adequately in capturing the evolutionary dynamics that generated our data. We do not find any preference for a particular model extension across multiple data sets, indicating that there is no 'one size fits all' when it comes to morphological data and that careful consideration should be given to choosing models of discrete character evolution. By using suitable models of character evolution, we can increase our confidence in our phylogenetic estimates, which should in turn allow us to gain more accurate insights into the evolutionary history of both extinct and extant taxa.

Higher Ultraprocessed Food Consumption Is Associated With Depression Persistence and Higher Risk of Depression Incidence in the Brazilian Longitudinal Study of Adult Health

BackgroundUltraprocessed foods (UPF) consumption has been associated with depression risk, but its association with depression persistence is unclear. ObjectiveThe objective of this study was to evaluate the association of UPF consumption with depression persistence and incidence. DesignThe Brazilian Longitudinal Study of Adult Health is a multicenter prospective cohort study with 3 waves (2008-2010, 2012-2014, and 2017-2019). Baseline percentage of energy from UPF, measured using a food frequency questionnaire, was divided into quartiles. Participants/settingCivil servants aged 35 to 74 years at baseline were included in the Brazilian Longitudinal Study of Adult Health. Participants with Parkinson disease, dementia, stroke history, extreme energy intake, and missing dietary or depression data at baseline were excluded. Main outcome measuresDepression was based on the Clinical Interview Schedule-Revised, depression persistence on depression status at each wave and depression incidence on time to first depression diagnosis. Statistical analyses performedClustering large applications algorithm, multinomial logistic regression, Cox proportional-hazard models, and partition substitution model were performed. ResultsAmong 13 870 participants free from depression at baseline, 731 (5.3%) had depression after 8 years of follow-up. Participants in Cluster 1 did not have depression in any wave, in Cluster 2 had depression in 1 wave, and in Cluster 3 had persistent depression in 2 or more waves. Compared with the first quartile of UPF consumption, participants in Quartiles 2, 3, and 4 had a 1.30 (95% CI 1.29 to 1.31), 1.39 (95% CI 1.38 to 1.40), and 1.58 (95% CI 1.56 to 1.60) higher odds of persistent depression (P = .019), respectively. Compared with the first UPF quartile, participants in Quartiles 3 and 4 had a 1.32 (95% CI 1.07 to 1.64) and 1.30 (95% CI 1.04 to 1.61) higher risk of incident depression (P = .017), respectively. Substituting 5%, 10%, and 20% of UPF with unprocessed/minimally processed foods and culinary ingredients was associated with a 6%, 11%, and 22% decreased depression incidence, respectively. ConclusionsHigher consumption of UPF at baseline was associated with higher odds of persistent depression and higher risk of incident depression over 8 years of follow-up.

Theoretical Behavior Substitutions during the 24-Hour Day in Pregnancy and Infant Growth Outcomes.

To assess associations of theoretically reallocating time from sleep, sedentary behavior, or light intensity physical activity (LPA) to moderate/vigorous intensity physical activity (MVPA) during pregnancy with infant growth outcomes. We used data from a cohort of pregnant individuals with overweight or obesity (n = 116). At 9-15 and 30-36 weeks gestation, waking movement was measured using wrist-worn accelerometers and sleep duration was self-reported. Outcomes were obtained from delivery electronic health records (birth) and study visits (12 months). We used compositional isotemporal substitution models. In early pregnancy, reallocating 10 minutes of sleep, sedentary behavior, or LPA to MVPA was associated with 20% (RR = 0.80; 95%CI: 0.75,0.85), 21% (RR = 0.79; 95%CI: 0.75,0.84), and 25% (RR = 0.75; 95%CI: 0.70,0.81) lower risk of large-for-gestational age (LGA) birthweight, respectively, and 17% (RR = 0.83; 95%CI: 0.75,0.91), 18% (RR = 0.82; 95%CI: 0.75,0.91), and 22% (RR = 0.78; 95%CI: 0.70,0.88) lower risk of rapid infant growth (birth to 12 months), respectively. In late pregnancy, reallocating 10 minutes to MVPA was associated with 18% to 22% lower risk of LGA birthweight, but was not associated with rapid infant growth. Reallocating time to MVPA in early or late pregnancy was not associated with high newborn body fat percent. Our findings suggest beneficial associations of theoretically reallocating time from sleep, sedentary behavior, or LPA to MVPA, especially during early pregnancy, for reducing LGA birthweight and rapid infant growth.