BioSystems

Phenotypic diversity is often thought to arise from the evolutionary modification of developmental processes. However, developmental processes are tightly coupled in space and time, with each process beginning from conditions set by the one before it. While we know from dynamical systems theory that initial conditions can significantly affect a systems out-come, their importance as a source of phenotypic evolvability has been largely overlooked. Here we show for the first time, that phenotypic evolution can proceed through changes in developmental initial conditions while the underlying developmental process remains conserved. Somitogenesis is the process by which vertebral precursors, known as somites, are periodically patterned in the pre-somitic mesoderm (PSM). Somitic count (total number of somites) is thought to diversify through the evolution of components of somitogenesis such as the tempo of the segmentation clock or the mechanisms driving axial morphogenesis. Using two closely related species of Lake Malawi cichlid fishes that differ in vertebral counts, we show that somite count evolution has happened without changes to somitogenesis itself, but instead, by altering the size of the PSM at the onset of this process. This work will expand what we consider developmental drivers of phenotypic evolution and highlight the importance of comparative studies to understand the diversification of phenotypes.

Animals sense and integrate complex external cues to make developmental decisions that help them better survive and adapt to their natural habitats. Under environmental adversity, nematodes can enter an alternative developmental pathway to form a diapautic and stress-resistant stage, termed the dauer larvae. While dauer formation has been well characterized in Caenorhabditis elegans, how environmental factors influence analogous stages in other nematode species remains largely unexplored. This study examines how symbiotic bacteria, temperature, and pheromones affect the formation of the infective juvenile (IJ), a dauer-like stage, of the insect-parasitic nematode Steinernema hermaphroditum. In contrast to C. elegans, where dauer entry is promoted by heat, IJ development in S. hermaphroditum development is enhanced by reduced temperature. Moreover, the presence and absence of live symbiotic bacterium Xenorhabdus griffiniae functions as an ON-and-OFF switch that regulates the host IJ formation. Crude pheromone extracts from S. hermaphroditum liquid culture do not robustly induce IJ formation in a dose-responsive manner, unlike the potent pheromone-driven dauer entry observed in C. elegans. Nutrient-rich liver-kidney media that mimics host insect environment showed IJ entry induction in a pheromone-dependent manner. These data suggest that external cues, such as temperature, microbial diet, and pheromone, are perceived differently by S. hermaphroditum in comparison to that of C. elegans, reflecting species-specific adaptations to distinct ecological niches and life history strategies.

Mass-conserved reaction-diffusion systems are used as mathematical models for various phenomena such as cell polarity. Numerical simulations of this system present transient dynamics in which multiple stripe patterns converge to spatially monotonic patterns. Previous studies indicated that the transient dynamics are driven by a mass conservation law and by variations in the amount of substance contained in each pattern, which we refer to as "pattern flux". However, it is challenging to mathematically investigate these pattern dynamics. In this study, we introduce a reaction-diffusion compartment model to investigate the pattern dynamics in view of the conservation law and the pattern flux. This model is defined on multiple intervals (compartments), and diffusive couplings are imposed on each boundary of the compartments. Corresponding to the transient dynamics in the original system, we consider the dynamics around stripe patterns in the compartment model. We derive ordinary differential equations describing the pattern dynamics of the compartment model and analyze the existence and stability of equilibria for the reduced ODE with respect to the boundary parameters. For a specific parameter setting, we obtained results consistent with previous studies. Moreover, we present that the stripe patterns in the compartment model are potentially stabilized by changing the parameter, which is not observed in the original system. We expect that the methodology developed in this paper is extendable to various directions, such as membrane-induced pattern control.

To achieve a stereotypic lineage, each embryo of Caenorhabditis elegans follows an invariant cell differentiation process arising from a combination of cell polarisation, asymmetric or symmetric divisions, combined with intercellular signalling processes. This pattern of embryonic cell differentiation is driven by regulated segregation of molecules occurring at each cell division, including polarity proteins or cell fate determinants, transcription factors, p-granules and mRNAs. These distribution patterns are coupled with a robust spatio-temporal orchestration of cortical actin dynamics, which also plays a crucial role in these processes. However, compared to other molecular contents, how the actin per se is segregated from the first asymmetric division onward remains poorly understood. This study presents a thorough quantification of the intracellular distribution from the zygote to the 4-cell stage of key actors related to actin polymerisation: two nucleators (a formin and the Arp2/3 complex), a capping protein and E-cadherin. We additionally developed a novel method to assess actin polymerisation capacities from single blastomere extracts. We found that actin-related signatures arise at these early stages and that differential mechanisms of protein segregation and homeostasis occur, depending both on the cell pair and on the protein considered. Notably, if asymmetric divisions correlated with unequal partitioning of actin-related contents in a process linked with embryonic polarity, differences were revealed between AB daughter cells upon their separation. Taken together, these actin-related asymmetric distributions are adding a layer to the complexity of cell fate acquisition mechanisms in the early embryo.

This retrospective study aims to explore the interactive effects of biological maturation and relative age effect (RAE) on talent identification. 56 male elite soccer players matched for chronological age (15.08{+/-}0.41 years) were studied. Test items included anthropometry (height, body mass, sitting height, leg length, BMI and Quetelet index), physiology (power, speed, agility, speed endurance and aerobic performance), soccer-specific skills (passing, shooting and dribbling), psychology (achievement motivation, orientation and resilience) and biological maturation (APHV) tests. The test results were analyzed independent sample t-test, Pearson correlation analysis, and stratified regression. Conclusion: Biological maturation significantly influences anthropometry (height, weight and Quetelet index), lower limb explosive, and speed (single-leg jump, standing triple jump, and 30-m sprint) in U16 male elite soccer players in Shanghai. The relative age effect shows no significant impact on talent selection indicators, which is attributed to the accumulated training load effect. The mechanisms of biological maturation and RAE in youth soccer talent selection are distinct and operate independently.

Voltage perturbations to a repetitively firing Hodgkin-Huxley (HH) model of neuronal spiking in the bistable regime with coexisting limit cycle and stable steady node can either lead to the spikes phase resetting or collapse to the stable steady state. The latter describes a non-firing hyperpolarized quiescent state of the neuron despite the presence of constant external current. Using asymptotic phase response curve (PRC), the impact of voltage perturbations on a repetitively firing HH model is studied here while it is diffusively coupled to another HH model under identical external stimulation. It is observed that the pre-perturbation state of synchronization and the coupling strength critically determine the PRC response of the perturbed HH dynamics. Higher coupling strengths of perfectly in-phase (anti-phase) synchronized HH models shrink (expand) the combinatorial space of perturbation strengths and the oscillation phases causing collapse to the quiescent state. This indicates reduced (enlarged) basin of attraction, viz. the null space, associated with the steady state in the HH phase space. The findings bear important implications to the spiking dynamics of diverse interneurons, as well as special cases of pyramidal neurons, coupled through electrical synapses via. gap junctions, and suggest the role of gap junction plasticity in tuning vulnerability to quiescent state in the presence of biological noise and spikelets.

Cancer cells in hypoxic environments often proliferate less but exhibit enhanced migration relative to their normoxic counterparts. Recent in vitro and in silico studies have characterized the role of hypoxic memory - the ability of cancer cells to retain their hypoxic phenotype even when reoxygenated - in tumor invasion. However, the observations have been limited either to exposing cancer cells to hypoxia for a fixed duration or by assuming a fixed-time persistence of the hypoxic state upon reoxygenation independent of the duration of hypoxia exposure. Thus, time-dependent cell-state changes during hypoxia and their impact on hypoxic memory remains unclear. Here, we first analyze transcriptomic data from breast cancer samples to show that the genes upregulated at transcriptional level and hypomethylated at epigenetic level are enriched in cell invasion, indicating hypoxic memory-driven process of tumor invasion. Next, we used a computational model to investigate how the spatial-temporal dynamics of oxygen levels in a tumor drive time-dependent changes in hypoxic memory and influence tumor invasion dynamics. Our simulation results show that such dynamic hypoxic memory can drive enhanced tumor invasion over a fixed hypoxic memory by a) enriching hypoxic cell density at the tumor front, b) reducing sensitivity of hypoxic cell state to fluctuations in oxygen supply, and c) enhancing effective diffusion of hypoxic cells. Our results highlight the crucial role of dynamic hypoxic memory in shaping tumor invasion dynamics, underscoring the need to elucidate its underlying mechanisms in future studies.

As social beings, humans make decisions partly based on social interaction. Observing the behavior of others can lead to learning from and about them, potentially increasing trust and prompting trust-based behavioral changes. Observation-based decision making involves different neural structures. The orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) are known as neural structures mainly involved in processing emotional and cognitive decision values, respectively, while the anterior cingulate cortex (ACC) plays a pivotal role as a social hub, integrating the afferent expectancy signals from OFC and LPFC. This paper presents a neurocomputational model of the interplay between observational learning and trust, as well as their role in individual decision-making. Our model elucidates and predicts the emotional and rational behavioral changes of an individual influenced by observing the action-outcome association of an alleged expert. We have modeled the neurodynamics of three cortical structures (OFC, LPFC, and ACC) and their interactions, where the neural oscillatory properties, modeled with Dynamic Bayesian Probability, represent the observers attitude towards the expert and the decision options. As an example of an everyday behavioral situation related to climate change, we use the choice of transportation between home and work. The EEG-like simulation outputs from our model represent the presumed brain activity of an individual making such a choice, assuming the decision-maker is exposed to social information.

Dauer larvae are a dormant developmental stage in nematodes that is induced by a range of environmental cues. The molecular mechanisms that transduce these cues to regulate dauer entry have been well characterized in Caenorhabditis elegans, whereas those in other nematode species remain unclear. The closest known sibling species of C. elegans, Caenorhabditis inopinata, occupies a distinct ecological niche and shows an extremely low frequency of dauer formation by starvation in laboratory conditions, suggesting that it could serve as a useful comparative model for analyzing dauer-inducing mechanisms. To support such analysis, we generated a fluorescent dauer reporter, Cin-col-183p::mCherry, in C. inopinata based on a previously reported dauer-specific reporter in C. elegans. This reporter showed fluorescence specifically in the pre-dauer and dauer stages, but not in other developmental stages, indicating that it functions as a dauer-specific marker in C. inopinata. Using these marker strains, we compared the responses to high temperature and RNAi-mediated knockdown of insulin/IGF-1 pathway genes (daf-2, age-1, and pdk-1), and found that dauer induction differs mechanistically between C. elegans and C. inopinata. This dauer-specific fluorescent strain will be a useful tool for investigating the diversity of dauer-inducing mechanisms across nematode species. Article SummaryDauer is a dormant developmental stage in nematodes induced by environmental stress. Although its regulation is well studied in Caenorhabditis elegans, the mechanisms in other species remain unclear. Here, we developed a fluorescent dauer reporter, Cin-col-183p::mCherry, in Caenorhabditis inopinata, a close relative of C. elegans. The reporter was specifically expressed in pre-dauer and dauer stages, confirming its usefulness as a dauer marker. Using this strain, we found that responses to high temperature and insulin/IGF-1 pathway gene knockdown differ between C. elegans and C. inopinata. This reporter will help reveal diversity in dauer-inducing mechanisms across nematode species.

Malaria is one of the deadliest diseases in sub-Saharan Africa and Southeast Asia. The majority of the fatalities occur mostly in children under 5 years and pregnant women and this is due to infection by Plasmodium spp, of which Plasmodium falciparum is the most virulent and is responsible for most of the morbidity and mortality. Despite various public health interventions such as use of insecticide-treated bed nets, spraying of homes with insecticides and use of WHO recommended artemisinin-based combination therapies (ACT), malaria prevention still faces major setback due to drug and insecticide resistance by P. falciparum and mosquitoes respectively. The study uses molecular docking and immunoinformatics to screen various Plasmodium spp antigens and evaluate their antigenicity and suitability as vaccine candidates. The P. falciparum antigens and T-cell receptor (TCR) structures were obtained from Protein Data Bank (PDB) based on a range of factors related to their role in the lifecycle of the parasite and their status as vaccine targets. Protein structures not available in the PDB were predicted using AlphaFold. The 3D structures of selected P. falciparum antigens and TCR structures were downloaded in PDB format then all water molecules, Hetatm, and bound ligands were deleted from the protein structures using BIOVIA Discovery Studio Visualizer. Subsequently, molecular docking was done using ClusPro v2.0 server and docked complexes were compared. The findings of this study gave valuable insights into the interaction of human immune response with P. falciparum antigens. The best three ranked antigen complexes are PfCyRPA, PfMSP10 and PfCSP and this confirm their use as potential candidates for vaccine development. This study highlights the usefulness of computational docking in identifying P. falciparum antigens of excellent immunogenic potential as vaccine candidates.

We describe an approach for analyzing biological networks using rows of the Krylov subspace of the adjacency matrix. Specifically, we explore the scenario where the Krylov subspace matrix is computed via power iteration using a non-random and potentially non-uniform initial vector that captures a specific biological state or perturbation. In this case, the rows the Krylov subspace matrix (i.e., Krylov trajectories) carry important functional information about the network nodes in the biological context represented by the initial vector. We demonstrate the utility of this approach for community detection and perturbation analysis using the C. Elegans neural network.

We explored processes within and orthogonal to the solution space (uncontrolled manifold, UCM) as superposition of fast random walk (RW) and slow drifts during multi-finger force production. Healthy participants performed two-hand (using the index and middle fingers per hand) accurate total force production task with different initial sharing of the force between the hand. After 5 s, visual feedback was manipulated - kept for both force and sharing, for only one of those variables, or turned off. The subjects tried to continue "doing what they have been doing" for 55 s. Trajectories both along and orthogonal to the UCM for total force showed fast RW and slow drifts. The diffusion plots confirmed persistent RW within the first 0.2 s and anti-persistent RW after 0.5 s. Persistent RW was similar across visual feedback conditions and larger orthogonal to the UCM. Its Hurst index correlated between the UCM and orthogonal to the UCM direction across participants. Anti-persistent RW depended strongly on visual feedback. Drift magnitude and characteristic time depended strongly on visual feedback, being similar along and orthogonal to the UCM. We conclude that RW destabilizes the state of the system thus encouraging exploration of nearby states over short time intervals and contributes to its stability over larger time intervals. Visual feedback plays a more important role in structuring stability of performance compared to the explicit task formulation. RW exploration promises new insights into the organization of stability in abundant systems and a potential biomarker for clinical studies. HighlightsO_LIStability during a multi-element action is structured in a feedback-specific way; C_LIO_LIRandom walk and drift characteristics of force depend not on the task but on salient feedback; C_LIO_LIRandom walk destabilizes steady state within a short range and stabilizes it within a long range; C_LIO_LIThe control of an action encourages exploration but limits its range. C_LI

At the fundamental conceptual level, two alternatives have traditionally been considered for how mutations arise and how evolution happens: 1) random mutation and natural selection, and 2) Lamarckism. Recently, the theory of Interaction-based Evolution (IBE) has been proposed, according to which mutations are neither random nor Lamarckian, but are influenced by information accumulating internally in the genome over generations. Based on the estimation-of-distribution algorithms framework, we present a simulation model that demonstrates nonrandom, non-Lamarckian mutation concretely while capturing indirectly several aspects of IBE: selection, recombination, and nonrandom, non-Lamarckian mutation interact in a complementary fashion; evolution is driven by the interaction of parsimony and fit; and random bits do not directly encode improvement but enable generalization by the manner in which they connect with the rest of the evolutionary process. Connections are drawn to Darwins observations that changed conditions increase the rate of production of heritable variation; to the causes of bell-shaped distributions of traits and how these distributions respond to selection; and to computational learning theory, where analogizing evolution to learning in accord with IBE casts individuals as examples and places the learned hypothesis at the population level. The model highlights the importance of incorporating internal integration of information through heritable change in both evolutionary theory and evolutionary computation.

Alzheimers disease (AD) is characterized by the accumulation of amyloid-{beta} (A{beta}), yet the specific link between plaque burden and cognitive decline remains a subject of intense investigation. This paper presents a mathematical model that simulates the coupled dynamics of A{beta} monomers, soluble oligomers, and fibrillar species in the brain tissue. By modifying existing moment equations to include a dedicated conservation equation for A{beta} monomers, the model explores how various microscopic processes, such as primary nucleation, surface-catalyzed secondary nucleation, fibril elongation, and fragmentation, contribute to macroscopic disease progression. Central to this study is the concept of "accumulated neurotoxicity" as a surrogate marker of biological age, defined as the time-integrated concentration of soluble A{beta} oligomers. Unlike plaque burden, accumulated neurotoxicity cannot be reversed, and the harm it causes depends critically on the sequence of events that produced it. Numerical results demonstrate that while plaque burden and neurotoxicity both increase over time, their relationship is non-linear and highly sensitive to the efficiency of protein degradation machinery. Specifically, impaired degradation leads to a rapid advancement of biological age relative to calendar age. The model further identifies oligomer dissociation and fibril fragmentation as potential protective mechanisms that can counterintuitively reduce neurotoxic burden by diverting monomers away from the soluble oligomer pool. These findings provide a quantitative framework for understanding why individuals with similar plaque burdens may experience vastly different cognitive outcomes, underscoring the importance of targeting soluble oligomers early in therapeutic interventions.

We introduce a spectral existence criterion for the evolution of cooperation in the form of the inequality{lambda} maxb > c, where{lambda} max is the leading eigenvalue of an interaction operator encoding population structure, and b and c represent benefit and cost tradeoffs, respectively. Nowaks five rules for the evolution of cooperation correspond to cases in which the cooperation condition reduces to a scalar assortment coefficient. These results follow from the Price equation, which sheds light on a long-standing debate on the role of inclusive fitness and evolutionary dynamics in explaining the evolution of cooperation.

The East Asian region, known for its high levels of human and fishery activities, experiences serious plastic pollution in the marine environment, especially in seawater and along coastlines. Wharf roaches (Ligia spp.) collected from the coast of western Japan frequently ingest expanded polystyrene (EPS), which is then excreted as microplastic through their feces. However, the impact of EPS exposure and ingestion on the gut microbiome of wharf roaches remains unclear. Thus, this study aimed to investigate the effects of EPS ingestion on the gut microbiota of wharf roaches by examining their gut microbiota and gene expression. The expression levels of more than 400 genes, including those associated with xenobiotic metabolism, and the abundance of gut microbial community were altered. Microbial analysis revealed that at least five archaeal types, two to four bacterial types, three to seven eukaryotic types, and three viral types were involved in a correlation network composed of strong associations. Among them, Haloquadratum, Halalkalicoccus, and Methanospirillum (archaea); Volvox (eukaryote); and Varicellovirus and T4-like viruses showed significantly increased abundance. Furthermore, covariance structure analysis indicated that the viruses and methanogens played key causal roles as characteristic factors related to EPS administration. In conclusion, EPS disrupts the intestinal environment of wharf roaches and serves as a potential material for viral activation and methane production. Building on our previous field study that identified wharf roaches as potential indicators of coastal EPS pollution, this study provides novel insights into the ecological impacts of EPS ingestion and consequences of plastic pollution.

We examined the overlap in the genes associated with daily rhythms and with behavioral plasticity in ants. We first investigated the daily rhythms of gene expression in the harvester ant, Pogonomyrmex barbatus, and how the rhythmic genes overlap with others previously shown to be associated with plasticity of foraging behavior. Then, to consider whether the overlap is conserved across ant species, we compared rhythms of gene expression in the diurnal, desert harvester ants with those previously reported for a distantly related nocturnal, subtropical carpenter ant, Camponotus floridanus. First, daily transcriptomes in P. barbatus showed that most genes were expressed in light-dark (LD) and constantly dark (DD) conditions at about the same levels; only 11 genes showed at least a two-fold change in expression. Network analysis identified eleven modules of P. barbatus genes under LD conditions. Of these 11 clusters, modules C1 and C2 seem to be central nodes of the gene expression network, because they are the most highly connected in LD, and show the strongest preservation in DD vs. LD, and contain core clock gene Period. Only one module, C2, showed significant overlap with P. barbatus genes that have 24h-rhythmic expression in both LD and DD. There was significant overlap between modules C1, C2, C10, C11, and P. barbatus genes found previously to be associated with plasticity in the regulation of foraging activity to manage water loss. A comparison of the daily transcriptome of P. barbatus with that of C. floridanus showed significant overlap of 24h-rhythmic genes in LD. Modules C1 and C2 of P. barbatus also overlap with C. floridanus genes previously shown to differ in expression rhythms in nurses and foragers. In combination, these results indicate that genes linking plasticity of the circadian clock and of behavior may be broadly conserved in ants.

The environments inhabited by flying insects demand a balance between flight efficiency and flight manoeuvrability. In structural oscillators such as the insect indirect flight motor, efficiency (arising from resonance) and manoeuvrability (arising from kinematic modulation) are typically quid pro quo, with modulation incurring penalties to efficiency. Band-type resonance is a phenomenon that offers, in theory, a strategy to lessen these penalties via careful navigation through a band of efficient kinematic states. However, identifying this band is challenging: no methods exist to identify the complete band in realistic motor models, involving elasticity distributed across thorax and wing. Nor are the effects of elasticity distribution on the band known. In this work, we address both open topics. We present a suite of numerical methods for identifying the complete resonance band in general systems. Applying them to models of the insect flight motor with distributed elasticity--thoracic and wing flexion--reveals that distributed elasticity is moderate-risk but high-reward morphological feature. Well-tuned distributions expand the resonance band over fourfold whereas poorly-tuned distributions completely extinguish the resonance band. These results indicate that distributing elasticity across the insect flight motor can have adaptive value, and motivate broader work identifying distributions across species.

Skeletal muscle regeneration is often impaired after acute muscle damage induced by viperid snake venoms, such as that of Bothrops asper, a medically-relevant species in Latin America. It has been shown that traces of venom that remain in the damaged muscle affect myogenic cells in culture, raising the possibility of inhibition of these toxins during the regenerative process as a way to improve regeneration. Using a mouse model of myonecrosis and regeneration, we evaluated the effects of Varespladib (a phospholipase A2 inhibitor) or Marimastat (a metalloproteinase inhibitor) on muscle regeneration when administered intravenously 24 h after the onset of myonecrosis, i.e., after muscle damage has occurred. The regenerative process was evaluated 14 and 28 days after venom injection. Results show that Marimastat, or a combination of both inhibitors, improved the extent of skeletal muscle regeneration and reduced the extent of tissue fibrosis when compared to tissue from mice receiving venom and no inhibitors, as judged by qualitative and quantitative histological assessment. Results underscore the deleterious role of traces of venom components in the damaged muscle during muscle regeneration and suggest that the administration of metalloproteinase inhibitors, or a combination of metalloproteinase and phospholipase A2 inhibitors, even when muscle damage has developed, may be a therapeutic alternative for improving the extent of muscle regeneration.

Sensorimotor learning and tool use involve synchronizing with external dynamics. Many everyday tools possess nonlinear hidden dynamics. Here we investigate how learning to synchronize with the complex dynamics of a tool depends on the degree of predictability and reciprocal coupling between user and tool. We introduce the concept of optimal coupling to measure adaptive user-tool coordination. Groups of participants practiced tracking an auditory stimulus in three conditions: 1) the tool was non-interactive and produced a periodic stimulus, 2) non-interactive and unstable stimulus, and 3) unstable but interactive stimulus which was coupled weakly to the participants movements and thus afforded control. Learning, retention, and transfer to visual modality were assessed using unpracticed test stimuli. Directional effective coupling was quantified using transfer entropy. Results showed that learning tended to be task-specific and there was no transfer to the visual modality. Interactive unstable practice exhibited some retention and generalization. We found a convergent reorganization of coupling during practice with the interactive unstable tool: stimulus-to-human coupling started high and decreased while human-to-stimulus coupling started low and increased. This suggests that embodiment of personalized rehabilitation technologies brings optimal reciprocal coupling in which sensorimotor-tool control is consistent with the minimal intervention principle postulated for within-body control.