Evolution Of Signals Research Articles

Surviving the serenade: how conflicting selection pressures shape the early stages of sexual signal diversification.

Understanding how the early stages of sexual signal diversification proceed is critically important because these microevolutionary dynamics directly shape species trajectories and impact macroevolutionary patterns. Unfortunately, studying this is challenging because signals involve complex interactions between behavior, morphology, and physiology, much of which can only be measured in real-time. In Hawaii, male Pacific field cricket song attracts both females and a deadly parasitoid fly. Over the past two decades, there has been a marked increase in signal variation in Hawaiian populations of these crickets, including novel male morphs with distinct mating songs. We capitalize on this rare opportunity to track changes in morph composition over time in a population with three novel morphs, investigating how mate and parasitoid attraction (components of sexual and natural selection) may shape signal evolution. We find dramatic fluctuation in morph proportions over the three years of the study, including the arrival and rapid increase of one novel morph. Natural and sexual selection pressures act differently among morphs, with some more attractive to mates and others more protected from parasitism. Collectively, our results suggest that differential protection from parasitism among morphs, rather than mate attraction, aligns with recent patterns of phenotypic change in the wild.

Ancient Loss of Catalytic Selenocysteine Spurred Convergent Adaptation in a Mammalian Oxidoreductase.

Selenocysteine, the 21st amino acid specified by the genetic code, is a rare selenium-containing residue found in the catalytic site of selenoprotein oxidoreductases. Selenocysteine is analogous to the common cysteine amino acid, but its selenium atom offers physical-chemical properties not provided by the corresponding sulfur atom in cysteine. Catalytic sites with selenocysteine in selenoproteins of vertebrates are under strong purifying selection, but one enzyme, glutathione peroxidase 6 (GPX6), independently exchanged selenocysteine for cysteine <100 million years ago in several mammalian lineages. We reconstructed and assayed these ancient enzymes before and after selenocysteine was lost and up to today and found them to have lost their classic ability to reduce hydroperoxides using glutathione. This loss of function, however, was accompanied by additional amino acid changes in the catalytic domain, with protein sites concertedly changing under positive selection across distant lineages abandoning selenocysteine in glutathione peroxidase 6. This demonstrates a narrow evolutionary range in maintaining fitness when sulfur in cysteine impairs the catalytic activity of this protein, with pleiotropy and epistasis likely driving the observed convergent evolution. We propose that the mutations shared across distinct lineages may trigger enzymatic properties beyond those in classic glutathione peroxidases, rather than simply recovering catalytic rate. These findings are an unusual example of adaptive convergence across mammalian selenoproteins, with the evolutionary signatures possibly representing the evolution of novel oxidoreductase functions.

Research on Magnetic Memory Detection of Weld Fatigue Damage Based on Two-Dimensional Spectral Entropy

Abstract In light of the intrinsic relationship between weld fatigue damage and the characteristics of magnetic leakage signals, fatigue experiments were conducted on butt welds to analyze the evolution of magnetic leakage signal as fatigue cycles increased. The introduction of two-dimensional spectral entropy allowed for the construction of a fatigue stage division model based on the two-dimensional spectral entropy diagram. The results revealed that distinctions between magnetic leakage signal under loaded and unloaded conditions were solely evident in their magnitude, with consistent curve distribution trends observed across various fatigue cycles. Furthermore, the distribution pattern of magnetic leakage signal displayed significant fluctuations, characterized by a sharp gradient increase following the emergence of fatigue cracks. These distribution characteristics of magnetic leakage signal differed markedly from the magnetic field distribution at other fatigue stages, with a higher growth rate observed as fatigue cycles increased. The two-dimensional spectral entropy spectrum analysis of magnetic leakage signals at different fatigue stages indicated the disorder in the magnetic leakage signal distribution within the high fatigue zone, signifying the expansion of fatigue microcracks. To some extent, two-dimensional spectral entropy can serve as an early warning system for detecting fatigue cracks in welds and achieving early identification of fatigue microcracks.

Latent evolutionary signatures: a general framework for analysing music and cultural evolution.

Cultural processes of change bear many resemblances to biological evolution. The underlying units of non-biological evolution have, however, remained elusive, especially in the domain of music. Here, we introduce a general framework to jointly identify underlying units and their associated evolutionary processes. We model musical styles and principles of organization in dimensions such as harmony and form as following an evolutionary process. Furthermore, we propose that such processes can be identified by extracting latent evolutionary signatures from musical corpora, analogously to identifying mutational signatures in genomics. These signatures provide a latent embedding for each song or musical piece. We develop a deep generative architecture for our model, which can be viewed as a type of variational autoencoder with an evolutionary prior constraining the latent space; specifically, the embeddings for each song are tied together via an energy-based prior, which encourages songs close in evolutionary space to share similar representations. As illustration, we analyse songs from the McGill Billboard dataset. We find frequent chord transitions and formal repetition schemes and identify latent evolutionary signatures related to these features. Finally, we show that the latent evolutionary representations learned by our model outperform non-evolutionary representations in such tasks as period and genre prediction.

Emerging Trends in Magnetic Resonance Fingerprinting for Quantitative Biomedical Imaging Applications: A Review.

Magnetic resonance imaging (MRI) stands as a vital medical imaging technique, renowned for its ability to offer high-resolution images of the human body with remarkable soft-tissue contrast. This enables healthcare professionals to gain valuable insights into various aspects of the human body, including morphology, structural integrity, and physiological processes. Quantitative imaging provides compositional measurements of the human body, but, currently, either it takes a long scan time or is limited to low spatial resolutions. Undersampled k-space data acquisitions have significantly helped to reduce MRI scan time, while compressed sensing (CS) and deep learning (DL) reconstructions have mitigated the associated undersampling artifacts. Alternatively, magnetic resonance fingerprinting (MRF) provides an efficient and versatile framework to acquire and quantify multiple tissue properties simultaneously from a single fast MRI scan. The MRF framework involves four key aspects: (1) pulse sequence design; (2) rapid (undersampled) data acquisition; (3) encoding of tissue properties in MR signal evolutions or fingerprints; and (4) simultaneous recovery of multiple quantitative spatial maps. This paper provides an extensive literature review of the MRF framework, addressing the trends associated with these four key aspects. There are specific challenges in MRF for all ranges of magnetic field strengths and all body parts, which can present opportunities for further investigation. We aim to review the best practices in each key aspect of MRF, as well as for different applications, such as cardiac, brain, and musculoskeletal imaging, among others. A comprehensive review of these applications will enable us to assess future trends and their implications for the translation of MRF into these biomedical imaging applications.

Reconstruction of multi-phase parametric maps in 4D-magnetic resonance fingerprinting (4D-MRF) by optimization of local T1 and T2 sensitivities.

Time-resolved magnetic resonance fingerprinting (MRF), or 4D-MRF, has been demonstrated its feasibility in motion management in radiotherapy (RT). However, the prohibitive long acquisition time is one of challenges of the clinical implementation of 4D-MRF. The shortening of acquisition time causes data insufficiency in each respiratory phase, leading to poor accuracies and consistencies of the predicted tissues' properties of each phase. To develop a technique for the reconstruction of multi-phase parametric maps in four-dimensional magnetic resonance fingerprinting (4D-MRF) through the optimization of local T1 and T2 sensitivities. The proposed technique employed an iterative optimization to tailor the data arrangement of each phase by manipulation of inter-phase frames, such that the T1 and T2 sensitivities, which were quantified by the modified Minkowski distance, of the truncated signal evolution curve was maximized. The multi-phase signal evolution curves were modified by sliding window reconstruction and inter-phase frame sharing (SWIFS). Motion correction (MC) and dot product matching were sequentially performed on the modified signal evolution and dictionary to reconstruct the multi-parametric maps. The proposed technique was evaluated by numerical simulations using the extended cardiac-torso (XCAT) phantom with regular and irregular breathing patterns, and by in vivo MRF data of three health volunteers and six liver cancer patients acquired at a 3.0 T scanner. In simulation study, the proposed SWIFS approach achieved the overall mean absolute percentage error (MAPE) of 8.62%±1.59% and 16.2%±3.88% for the eight-phases T1 and T2 maps, respectively, in the sagittal view with irregular breathing patterns. In contrast, the overall MAPE of T1 and T2 maps generated by the conventional approach with multiple MRF repetitions were 22.1%±11.0% and 30.8%±14.9%, respectively. For in-vivo study, the predicted mean T1 and T2 of liver by the proposed SWIFS approach were 795ms±38.9ms and 58.3ms±11.7ms, respectively. Both simulation and in vivo results showed that the approach empowered by T1 and T2 sensitivities optimization and sliding window under the shortened acquisition of MRF had superior performance in the estimation of multi-phase T1 and T2 maps as compared to the conventional approach with oversampling of MRF data.

Polysulfide-mediated solvation shell reorganization for fast Li+ transfer probed by in-situ sum frequency generation spectroscopy

Understanding of interfacial Li+ solvation shell structures and dynamic evolution at the electrode/electrolyte interface is requisite for developing high-energy-density Li batteries. Herein, the reorganization of Li+ solvation shell at the sulfur/electrolyte interface along with the presence of a trace amount of lithium polysulfides is verified by in-situ sum frequency generation (SFG) spectroscopy together with density functional theory (DFT) calculations. Both the spectroelectrochemical and DFT calculation results reveal a strongly competitive anion adsorption of the polysulfide anion additive against the pristine electrolyte anion on the sulfur cathode surface, reorganizing the interfacial local solvation shell structure facilitating rapid Li ion transfer and conduction. Meanwhile, the evolution of the SFG signals along with the discharging/charging cycle exhibits improved reversibility, indicating the transformation of the inner Helmholtz plane layer into a stable molecular-layer polysulfide interphase rather than a dynamic diffusion layer. Consequently, applications in practical Li-S batteries reveal the capacity and cycling stability of the corresponding cells are significantly enhanced. Our work provides a methodology using in-situ SFG for probing solvation reorganization of charge carriers at electrochemical interfaces.

The origin and evolution of Wnt signalling.

The Wnt signal transduction pathway has essential roles in the formation of the primary body axis during development, cellular differentiation and tissue homeostasis. This animal-specific pathway has been studied extensively in contexts ranging from developmental biology to medicine for more than 40 years. Despite its physiological importance, an understanding of the evolutionary origin and primary function of Wnt signalling has begun to emerge only recently. Recent studies on very basal metazoan species have shown high levels of conservation of components of both canonical and non-canonical Wnt signalling pathways. Furthermore, some pathway proteins have been described also in non-animal species, suggesting that recruitment and functional adaptation of these factors has occurred in metazoans. In this Review, we summarize the current state of research regarding the evolutionary origin of Wnt signalling, its ancestral function and the characteristics of the primal Wnt ligand, with emphasis on the importance of genomic studies in various pre-metazoan and basal metazoan species.

A late burst of colour evolution in a radiation of songbirds (Passeriformes: Parulidae) suggests secondary contact drives signal divergence.

Evolutionary radiations provide important insights into species diversification, which is especially true of adaptive radiations. New World wood warblers (Parulidae) are a family of small, insectivorous, forest-dwelling passerine birds, often considered an exemplar of adaptive radiation due to their rapid diversification followed by a slowdown. However, they deviate from the expectations of an adaptive radiation scenario due to the lack of conspicuous morphological and ecological differentiation. We fitted several macroevolutionary models to trait data in 105 species of wood warblers. We tested whether morphological traits underwent an early burst of evolution (suggesting adaptation to new ecological niches in adaptive radiations) and whether song and colour underwent a diversity-dependent acceleration of trait evolutionary rate (consistent with reproductive interference driving signal evolution). Morphology and song evolved gradually under stabilizing selection, suggesting niche conservatism, with morphology possibly acting as a constraint on song evolution. In contrast, many feather colour traits underwent a diversity-dependent burst of evolution occurring late in the clade's history. We suggest that a two-step process has led to the remarkable diversification of wood warblers. First, their early diversification probably proceeded by allopatric speciation. Second, feather colour divergence likely occurred during secondary contact after range expansion. This diversification of signalling traits might have facilitated species coexistence, in combination with behavioural niche partitioning. Wood warblers seem to present characteristics of both adaptive and non-adaptive radiations.

Electro‐thermo‐mechanical characterization of shape memory alloy wires for actuator and sensor applications—Part 1: The effects of training

AbstractSo far shape memory alloys (SMA) are mostly characterized by their thermo‐mechanical behavior due to the underlying thermal effect. In technical applications however, where their benefits like low weight and compact design become relevant, they are activated electrically. This work presents methods for a thorough and systematic characterization of SMA wire samples under Joule heating with the focus on aspects relevant for applications. The goal is to achieve a precise understanding of the sensor and actuator properties of SMA wire samples with different trainings under varying loads. All experiments are conducted on a custom designed test bench with a commercially available NiTi wire with 72 μm diameter, which enables the direct comparisons of tensile tests to actuation tests. The characterization consists of tensile tests and actuator tests with varying load and heating power for differently trained wire samples. The results vividly represent the influence of heating power, training and changing loads on stroke output, working point and the functional stability of SMA actuator wires. Especially, the evolution of the resistance signal and the influence of the R‐phase on self‐sensing is discussed. The proposed method enables to compare and choose the best suitable alloy with a fitting training for a desired application.

Geography and ecology shape the phylogenetic composition of Amazonian tree communities

AbstractAimAmazonia hosts more tree species from numerous evolutionary lineages, both young and ancient, than any other biogeographic region. Previous studies have shown that tree lineages colonized multiple edaphic environments and dispersed widely across Amazonia, leading to a hypothesis, which we test, that lineages should not be strongly associated with either geographic regions or edaphic forest types.LocationAmazonia.TaxonAngiosperms (Magnoliids; Monocots; Eudicots).MethodsData for the abundance of 5082 tree species in 1989 plots were combined with a mega‐phylogeny. We applied evolutionary ordination to assess how phylogenetic composition varies across Amazonia. We used variation partitioning and Moran's eigenvector maps (MEM) to test and quantify the separate and joint contributions of spatial and environmental variables to explain the phylogenetic composition of plots. We tested the indicator value of lineages for geographic regions and edaphic forest types and mapped associations onto the phylogeny.ResultsIn the terra firme and várzea forest types, the phylogenetic composition varies by geographic region, but the igapó and white‐sand forest types retain a unique evolutionary signature regardless of region. Overall, we find that soil chemistry, climate and topography explain 24% of the variation in phylogenetic composition, with 79% of that variation being spatially structured (R2 = 19% overall for combined spatial/environmental effects). The phylogenetic composition also shows substantial spatial patterns not related to the environmental variables we quantified (R2 = 28%). A greater number of lineages were significant indicators of geographic regions than forest types.Main ConclusionNumerous tree lineages, including some ancient ones (&gt;66 Ma), show strong associations with geographic regions and edaphic forest types of Amazonia. This shows that specialization in specific edaphic environments has played a long‐standing role in the evolutionary assembly of Amazonian forests. Furthermore, many lineages, even those that have dispersed across Amazonia, dominate within a specific region, likely because of phylogenetically conserved niches for environmental conditions that are prevalent within regions.

Hematopoiesis Revolves Around the Primordial Evolutional Rhythm of Purinergic Signaling and Innate Immunity – A Journey to the Developmental Roots

A cell's most significant existential task is to survive by ensuring proper metabolism, avoiding harmful stimuli, and adapting to changing environments. It explains why early evolutionary primordial signals and pathways remained active and regulate cell and tissue integrity. This requires energy supply and a balanced redox state. To meet these requirements, the universal intracellular energy transporter purine nucleotide-adenosine triphosphate (ATP) became an important signaling molecule and precursor of purinergic signaling after being released into extracellular space. Similarly, ancient proteins involved in intracellular metabolism gave rise to the third protein component (C3) of the complement cascade (ComC), a soluble arm of innate immunity. These pathways induce cytosol reactive oxygen (ROS) and reactive nitrogen species (RNS) that regulate the redox state of the cells. While low levels of ROS and RNS promote cell growth and differentiation, supra-physiological concentrations can lead to cell damage by pyroptosis. This balance explains the impact of purinergic signaling and innate immunity on cell metabolism, organogenesis, and tissue development. Subsequently, along with evolution, new regulatory cues emerge in the form of growth factors, cytokines, chemokines, and bioactive lipids. However, their expression is still modulated by both primordial signaling pathways. This review will focus on the data that purinergic signaling and innate immunity carry on their ancient developmental task in hematopoiesis and specification of hematopoietic stem/progenitor cells (HSPCs). Moreover, recent evidence shows both these regulatory pathways operate in a paracrine manner and inside HSPCs at the autocrine level.Graphical

Evolution of sensitivity to warning cues from kin in plants with a structured population.

Plants exchange a variety of information intra- and interspecifically by using various mediating cues. For example, plant individuals that are injured by herbivores release volatile chemicals, which induce receiver plants to express anti-herbivore resistance. Remarkably, some plant species were known to represent kin specificity in the response, where cues from a damaged individual induce a higher level of resistance in a kin receiver than in a non-kin receiver. Such higher sensitivity to warning cues from kin could be advantageous via two mechanisms. If each herbivore tends to attack plants with a certain genotype, plants should be more sensitive to warning cues from kin that share genetic properties. In addition, if herbivores successively attack the neighboring plant with a high probability, and if related plants tend to grow in close proximity, plants may be more sensitive to warning cues from neighboring kin under the presence of a trade-off between sensitivity to kin and non-kin. In the present study, we constructed a mathematical model including those mechanisms to investigate the evolutionary process of the higher sensitivity to warning cues from kin than sensitivities to cues from non-kin. According to the analysis of evolutionary dynamics, we revealed that both mechanisms could contribute, although higher sensitivity to cues from kin is more likely to evolve when the spatial range of competition is greater than the range of effective alarm cues. This result highlights the importance of the competition regime in the evolution of signaling among kin.

Flower colour and size-signals vary with altitude and resulting climate on the tropical-subtropical islands of Taiwan.

The diversity of flower colours in nature provides quantifiable evidence for how visitations by colour sensing insect pollinators can drive the evolution of angiosperm visual signalling. Recent research shows that both biotic and abiotic factors may influence flower signalling, and that harsher climate conditions may also promote salient signalling to entice scarcer pollinators to visit. In parallel, a more sophisticated appreciation of the visual task foragers face reveals that bees have a complex visual system that uses achromatic vision when moving fast, whilst colour vision requires slower, more careful inspection of targets. Spectra of 714 native flowering species across Taiwan from sea level to mountainous regions 3,300 m above sea level (a.s.l.) were measured. We modelled how the visual system of key bee pollinators process signals, including flower size. By using phylogenetically informed analyses, we observed that at lower altitudes including foothills and submontane landscapes, there is a significant relationship between colour contrast and achromatic signals. Overall, the frequency of flowers with high colour contrast increases with altitude, whilst flower size decreases. The evidence that flower colour signaling becomes increasingly salient in higher altitude conditions supports that abiotic factors influence pollinator foraging in a way that directly influences how flowering plants need to advertise.

Abstract PR009: Tick tock trees: Reconstructing the evolutionary dynamics of human tissues using fluctuating methylation clocks

Abstract The development of cancer from healthy somatic cells is fundamentally an evolutionary process. Understanding this process is vital to improving its clinical management and developing new treatment strategies. Tracing individual human cells’ fates would simultaneously advance somatic evolutionary theory and our understanding of normal tissue function and its change through development, aging, and cancer progression. We cannot use human cell-labeling techniques in vivo. Still, population genetic and phylogenetic models can leverage the information recorded in heritable alterations to reconstruct the unobserved somatic cells’ history. Most such methods are limited by the few parameters they can estimate and restricted to neoplastic samples due to the lack of adequate evolutionary signal in healthy somatic cells. Gabbutt et al. recently ameliorated this limitation by introducing fluctuating methylation clocks (FMCs)—tissue-specific CpG sites that randomly change their methylation state—and a model that uses them to reconstruct the evolution of a clonal stem-cell population. In this application, all FMCs in a bulk sample are interrogated using a single standard methylation array to yield estimates of rates of methylation, demethylation and cell replacement, and the size of the stem-cell niche. This technique is especially suited to studying stem-cell niche dynamics in healthy or pre-malignant tissues organized in clonal cell populations where the whole population can be sampled together, like crypts (e.g., intestine, Barrett’s esophagus) and glands (e.g., endometrium). We have developed a multi-sample extension of this model that simultaneously reconstructs the evolutionary dynamics of stem cells within a niche and the niches within the tissue. This phylodynamic model produces additional estimates like ancestral relationships between sampled clonal populations, their calendar divergence times, the number of effective evolutionary niches, and how some of these parameters change over time. Here, we will present the method, demonstrate its validity, characterize its accuracy under a broad simulation parameter space, and showcase its application in analyzing human data from the following tissues: colon, small intestine, endometrium, and Barrett’s esophagus. We will also discuss the current model's limitations and future improvements that will discern between mechanisms of stem-cell-niche reproduction and incorporate geographical information. The stochastic nature of neoplastic progression makes it unlikely for any particular somatic alteration to be highly predictive of its outcome. This can explain why developing reliable traditional biomarkers has been so difficult. Alternatively, evolutionary biomarkers measure the characteristics of the process itself and thus should apply to all neoplasms. Parametric phylogenetic reconstruction models like the one introduced here will enable us to develop such universal biomarkers. Our ultimate goal is for evolutionary biomarkers to join evolutionary therapies in the revolution of the clinical management of cancer. Citation Format: Diego Mallo, Pablo Bousquets-Muñoz, Heather E. Grant, Darryl Shibata, Trevor A. Graham, Carlo C. Maley, Calum Gabbutt. Tick tock trees: Reconstructing the evolutionary dynamics of human tissues using fluctuating methylation clocks [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr PR009.

Sensory trap leads to reliable communication without a shift in nonsexual responses to the model cue.

The sensory trap model of signal evolution suggests that males manipulate females into mating using traits that mimic cues used in a nonsexual context. Despite much empirical support for sensory traps, little is known about how females evolve in response to these deceptive signals. Female sea lamprey (Petromyzon marinus) evolved to discriminate a male sex pheromone from the larval odor it mimics and orient only toward males during mate search. Larvae and males release the attractant 3-keto petromyzonol sulfate (3kPZS), but spawning females avoid larval odor using the pheromone antagonist, petromyzonol sulfate (PZS), which larvae but not males, release at higher rates than 3kPZS. We tested the hypothesis that migratory females also discriminate between larval odor and the male pheromone and orient only to larval odor during anadromous migration, when they navigate within spawning streams using larval odor before they begin mate search. In-stream behavioral assays revealed that, unlike spawning females, migratory females do not discriminate between mixtures of 3kPZS and PZS applied at ratios typical of larval versus male odorants. Our results indicate females discriminate between the sexual and nonsexual sources of 3kPZS during but not outside of mating and show sensory traps can lead to reliable sexual communication without females shifting their responses in the original context.

Residue coevolution and mutational landscape for OmpR and NarL response regulator subfamilies

DNA-binding response regulators (DBRRs) are a broad class of proteins that operate in tandem with their partner kinase proteins to form two-component signal transduction systems in bacteria. Typical DBRRs are composed of two domains where the conserved N-terminal domain accepts transduced signals and the evolutionarily diverse C-terminal domain binds to DNA. These domains are assumed to be functionally independent, and hence recombination of the two domains should yield novel DBRRs of arbitrary input/output response, which can be used as biosensors. This idea has been proved to be successful in some cases; yet, the error rate is not trivial. Improvement of the success rate of this technique requires a deeper understanding of the linker-domain and inter-domain residue interactions, which have not yet been thoroughly examined. Here, we studied residue coevolution of DBRRs of the two main subfamilies (OmpR and NarL) using large collections of bacterial amino acid sequences to extensively investigate the evolutionary signatures of linker-domain and inter-domain residue interactions. Coevolutionary analysis uncovered evolutionarily selected linker-domain and inter-domain residue interactions of known experimental structures, as well as previously unknown inter-domain residue interactions. We examined the possibility of these inter-domain residue interactions as contacts that stabilize an inactive conformation of the DBRR where DNA binding is inhibited for both subfamilies. The newly gained insights on linker-domain/inter-domain residue interactions and shared inactivation mechanisms improve the understanding of the functional mechanism of DBRRs, providing clues to efficiently create functional DBRR-based biosensors. Additionally, we show the feasibility of applying coevolutionary landscape models to predict the functionality of domain-swapped DBRR proteins. The presented result demonstrates that sequence information can be used to filter out bioengineered DBRR proteins that are predicted to be nonfunctional due to a high negative predictive value.

On the evolution of complex signals and structures in media without dispersion

The paper investigates the nonlinear evolution of complex signals and structures having two significantly different scales at the input: a high-frequency noise carrier and a regular modulating function. Consideration of the statistical characteristics of the velocity field is based on the asymptotic solution of the Burgers equation for a vanishingly small viscosity. This solution coincides with the weak solution of the Riemann equation (Hopf equation) and is known as the Oleinik-Laks absolute minimum principle. In this case, the solution of the partial differential equation is reduced to the procedure for finding the absolute minimum of some functional of the initial perturbation, which depends on the coordinate of the observation point and time. The problem of analyzing the statistical characteristics of the velocity and density fields of a one-dimensional flow of inelastically sticking particles is also considered on the basis of the global principle (E-Rykov-Sinai principle). In the special case of a constant initial density, this solution coincides with the Oleinik-Laks absolute minimum principle. In media without dispersion, the multiple interaction of harmonics leads to a strong distortion of the wave profile and the formation of discontinuities, and at long times the field is transformed into a sequence of triangular pulses with the same slope. It is shown that only a relative decrease in modulation occurs for a noise carrier, in contrast to a quasi-monochromatic wave, where, due to nonlinear effects, amplitude modulation is completely suppressed at the stage of developed discontinuities. The statistical characteristics of the velocity and density fields at long times are found, and the process of generating the mean field from a modulated signal perturbation with zero mean at the input is studied. It is shown that if the correlation scale of the noise filling is much smaller than the duration of the localized modulating function, then a practically deterministic signal is formed at large times. On the basis of the global principle, the problems of the escape of particles from a localized bunch with a random input field into free space and the evolution of a flow of particles with random velocities and harmonic modulation of the initial density are analytically considered. It is shown that at long times in both cases the average density field has a universal character. The analytical consideration is compared with the results of numerical simulation, which was carried out on the basis of the Fast Legendre transform algorithm.

Perceptual integration of bodily and facial emotion cues in chimpanzees and humans.

For highly visual species like primates, facial and bodily emotion expressions play a crucial role in emotion perception. However, most research focuses on facial expressions, while the perception of bodily cues is still poorly understood. Using a novel comparative priming eye-tracking design, we examined whether our close primate relatives, the chimpanzees (Pan troglodytes), and humans infer emotions from bodily cues through subsequent perceptual integration with facial expressions. In experiment 1, we primed chimpanzees with videos of bodily movements of unfamiliar conspecifics engaged in social activities of opposite valence (play and fear) against neutral control scenes to examine attentional bias toward succeeding congruent or incongruent facial expressions. In experiment 2, we assessed the same attentional bias in humans yet using stimuli showing unfamiliar humans. In experiment 3, humans watched the chimpanzee stimuli of experiment 1, to examine cross-species emotion perception. Chimpanzees exhibited a persistent fear-related attention bias but did not associate bodily with congruent facial cues. In contrast, humans prioritized conspecifics' congruent facial expressions (matching bodily scenes) over incongruent ones (mismatching). Nevertheless, humans exhibited no congruency effect when viewing chimpanzee stimuli, suggesting difficulty in cross-species emotion perception. These results highlight differences in emotion perception, with humans being greatly affected by fearful and playful bodily cues and chimpanzees being strongly drawn toward fearful expressions, regardless of the preceding bodily priming cue. These data advance our understanding of the evolution of emotion signaling and the presence of distinct perceptual patterns in hominids.

Genome-wide mining of diversity and evolutionary signatures revealed selective hotspots in Indian Sahiwal cattle

The Sahiwal cattle breed is the best indigenous dairy cattle breed, and it plays a pivotal role in the Indian dairy industry. This is due to its exceptional milk-producing potential, adaptability to local tropical conditions, and its resilience to ticks and diseases. The study aimed to identify selective sweeps and estimate intrapopulation genetic diversity parameters in Sahiwal cattle using ddRAD sequencing-based genotyping data from 82 individuals. After applying filtering criteria, 78,193 high-quality SNPs remained for further analysis. The population exhibited an average minor allele frequency of 0.221 ± 0.119. Genetic diversity metrics, including observed (0.597 ± 0.196) and expected heterozygosity (0.433 ± 0.096), nucleotide diversity (0.327 ± 0.114), the proportion of polymorphic SNPs (0.726), and allelic richness (1.323 ± 0.134), indicated ample genomic diversity within the breed. Furthermore, an effective population size of 74 was observed in the most recent generation. The overall mean linkage disequilibrium (r2) for pairwise SNPs was 0.269 ± 0.057. Moreover, a greater proportion of short Runs of Homozygosity (ROH) segments were observed suggesting that there may be low levels of recent inbreeding in this population. The genomic inbreeding coefficients, computed using different inbreeding estimates (FHOM, FUNI, FROH, and FGROM), ranged from −0.0289 to 0.0725. Subsequently, we found 146 regions undergoing selective sweeps using five distinct statistical tests: Tajima's D, CLR, |iHS|, |iHH12|, and ROH. These regions, located in non-overlapping 500 kb windows, were mapped and revealed various protein-coding genes associated with enhanced immune systems and disease resistance (IFNL3, IRF8, BLK), as well as production traits (NRXN1, PLCE1, GHR). Notably, we identified interleukin 2 (IL2) on Chr17: 35217075–35223276 as a gene linked to tick resistance and uncovered a cluster of genes (HSPA8, UBASH3B, ADAMTS18, CRTAM) associated with heat stress. These findings indicate the evolutionary impact of natural and artificial selection on the environmental adaptation of the Sahiwal cattle population.