Role of Piezo1 in modulating the RANKL/OPG ratio in mouse osteoblast cells exposed to Porphyromonas gingivalis lipopolysaccharide and mechanical stress.

AIMS: Excessive occlusal force with periodontitis leads to rapid alveolar bone resorption. However, the molecular mechanism by which inflammation and mechanical stress cause bone resorption remains unclear. We examined the role of Piezo1, a mechanosensitive ion channel expressed on osteoblasts, in the changes in the receptor activator of nuclear factor-kappa B ligand (RANKL)/osteoprotegerin (OPG) ratio in mouse MC3T3-E1 osteoblast-like cells under Porphyromonas gingivalis lipopolysaccharide (P.g.-LPS) and mechanical stress. METHODS: To investigate the effect of P.g.-LPS and mechanical stress on the RANKL/OPG ratio and Piezo1 expression, we stimulated MC3T3-E1 cells with P.g.-LPS. After 3 days in culture, shear stress, a form of mechanical stress, was applied to the cells using an orbital shaker. Subsequently, to investigate the role of Piezo1 in the change of RANKL/OPG ratio, we inhibited Piezo1 function by knockdown via Piezo1 siRNA transfection or by adding GsMTx4, a Piezo1 antagonist. RESULTS: The RANKL/OPG ratio significantly increased in MC3T3-E1 cells cultured in a medium containing P.g.-LPS and undergoing mechanical stress compared to cells treated with P.g.-LPS or mechanical stress alone. However, the expression of Piezo1 was not increased by P.g.-LPS and mechanical stress. In addition, phosphorylation of MEK/ERK was induced in the cells under P.g.-LPS and mechanical stress. MC3T3-E1 cells treated with P.g.-LPS and mechanical stress when cocultured with RAW264.7 cells induced their differentiation into osteoclast-like cells. The increased RANKL/OPG ratio was suppressed by either Piezo1 knockdown or the addition of GsMTx4. Furthermore, GsMTx4 inhibited the phosphorylation of MEK/ERK. CONCLUSION: These findings suggest that P.g.-LPS and Piezo1-mediated mechanical stress induce MEK/ERK phosphorylation and increase RANKL expression in osteoblasts. Consequently, this leads to the differentiation of osteoclast precursor cells into osteoclasts.

An evolutionary model of personality traits related to cooperative behavior using a large language model.

This study aims to demonstrate that Large Language Models (LLMs) can empower research on the evolution of human behavior, based on evolutionary game theory, by using an evolutionary model positing that instructing LLMs with high-level psychological and cognitive character descriptions enables the simulation of human behavior choices in game-theoretical scenarios. As a first step towards this objective, this paper proposes an evolutionary model of personality traits related to cooperative behavior using a large language model. In the model, linguistic descriptions of personality traits related to cooperative behavior are used as genes. The deterministic strategies extracted from LLM that make behavioral decisions based on these personality traits are used as behavioral traits. The population is evolved according to selection based on average payoff and mutation of genes by asking LLM to slightly modify the parent gene toward cooperative or selfish. Through experiments and analyses, we clarify that such a model can indeed exhibit evolution of cooperative behavior based on the diverse and higher-order representation of personality traits. We also observed repeated intrusion of cooperative and selfish personality traits through changes in the expression of personality traits. The words that emerged in the evolved genes reflected the behavioral tendencies of their associated personalities in terms of semantics, thereby influencing individual behavior and, consequently, the evolutionary dynamics.

Monitoring the courtship flight trajectory of Latham's snipe (Gallinago hardwickii) using microphone arrays.

This study is the first to quantitatively measure the courtship display flights of Latham's snipe (Gallinago hardwickii), which is a "near threatened" species as of 2022 (IUCN red list of threatened species). By using a 16-channel microphone array and 8-channel microphone arrays, we localized the fine-scale movements of courtship flights of one male performing at high altitude and high speed, and we estimated the direction from which each sound arrived using robot audition. Preliminary analyses of the azimuthal and elevation angles of the courtship flights partially revealed a fine-scale flight trajectory. First, a male Latham's snipe gradually gained altitude while vocalizing sharp and harsh repeating calls, until it reached the flight peak altitude, then dove down while producing winnowing sound to the ground along the wetland zones without tall vegetation. This observation method is methodologically useful to establish a better understanding of Latham's snipe courtship flight site selection. Furthermore, this method can be extended to investigate other rare nocturnal or crepuscular birds that are too timid to risk ringing or tagging.

Comprehensive Analyses of Intraviral Epstein-Barr Virus Protein-Protein Interactions Hint Central Role of BLRF2 in the Tegument Network.

Protein-protein interactions (PPIs) are crucial for various biological processes. Epstein-Barr virus (EBV) proteins typically form complexes, regulating the replication and persistence of the viral genome in human cells. However, the role of EBV protein complexes under physiological conditions remains unclear. In this study, we performed comprehensive analyses of EBV PPIs in living cells using the NanoBiT system. We identified 195 PPIs, many of which have not previously been reported. Computational analyses of these PPIs revealed that BLRF2, which is only found in gammaherpesviruses, is a central protein in the structural network of EBV tegument proteins. To characterize the role of BLRF2, we generated two BLRF2 knockout EBV clones using CRISPR/Cas9. BLRF2 knockout significantly decreased the production of infectious virus particles, which was partially restored by exogenous BLRF2 expression. In addition, self-association of BLRF2 protein was found, and mutation of the residues crucial for the self-association affected stability of the protein. Our data imply that BLRF2 is a tegument network hub that plays important roles in progeny virion maturation. IMPORTANCE EBV remains a significant public health challenge, causing infectious mononucleosis and several cancer types. Therefore, the better understanding of the molecular mechanisms underlying EBV replication is of high clinical importance. As protein-protein interactions (PPIs) are major regulators of virus-associated pathogenesis, comprehensive analyses of PPIs are essential. Previous studies on PPIs in EBV or other herpesviruses have predominantly employed the yeast two-hybrid (Y2H) system, immunoprecipitation, and pulldown assays. Herein, using a novel luminescence-based method, we identified 195 PPIs, most of which have not previously been reported. Computational and functional analyses using knockout viruses revealed that BLRF2 plays a central role in the EBV life cycle, which makes it a valuable target for drug development.

Auditory Survey of Endangered Eurasian Bittern Using Microphone Arrays and Robot Audition.

Bioacoustics monitoring has become increasingly popular for studying the behavior and ecology of vocalizing birds. This study aims to verify the practical effectiveness of localization technology for auditory monitoring of endangered Eurasian bittern (Botaurus stellaris) which inhabits wetlands in remote areas with thick vegetation. Their crepuscular and highly secretive nature, except during the breeding season when they vocalize advertisement calls, make them difficult to monitor. Because of the increasing rates of habitat loss, surveying accurate numbers and their habitat needs are both important conservation tasks. We investigated the feasibility of localizing their booming calls, at a low frequency range between 100-200 Hz, using microphone arrays and robot audition HARK (Honda Research Institute, Audition for Robots with Kyoto University). We first simulated sound source localization of actual bittern calls for microphone arrays of radii 10 cm, 50 cm, 1 m, and 10 m, under different noise levels. Second, we monitored bitterns in an actual field environment using small microphone arrays (height = 12 cm; width = 8 cm), in the Sarobetsu Mire, Hokkaido Island, Japan. The simulation results showed that the spectral detectability was higher for larger microphone arrays, whereas the temporal detectability was higher for smaller microphone arrays. We identified that false detection in smaller microphone arrays, which was coincidentally generated in the calculation proximate to the transfer function for the opposite side. Despite technical limitations, we successfully localized booming calls of at least two males in a reverberant wetland, surrounded by thick vegetation and riparian trees. This study is the first case of localizing such rare birds using small-sized microphone arrays in the field, thereby presenting how this technology could contribute to auditory surveys of population numbers, behaviors, and microhabitat selection, all of which are difficult to investigate using other observation methods. This methodology is not only useful for the better understanding of bitterns, but it can also be extended to investigate other rare nocturnal birds with low-frequency vocalizations, without direct ringing or tagging. Our results also suggest a future necessity for a robust localization system to avoid reverberation and echoing in the field, resulting in the false detection of the target birds.

Evolution of metamemory based on self-reference to own memory in artificial neural network with neuromodulation.

The ability of humans to self-monitor and control their memory processes is called metamemory and has been widely studied as a component of metacognition in cognitive psychology. Metamemory in non-human animals has also been investigated in recent years, although it had been regarded as a truly unique characteristic of human memory. We attempt to evolve artificial neural networks with neuromodulation, which have a metamemory function. Our constructive approach is expected to contribute, by introducing a novel dimension of evolutionary plausibility, to the discussion of animal experiments to detect metamemory. In this study, we demonstrate the evolution of neural networks that have a metamemory function based on the self-reference of memory, including the analysis of the evolved mechanism of metamemory. In addition, we discuss the similarity between the structure of the evolved neural network and the metamemory model defined by Nelson and Narens.

Effect of Low-intensity Pulsed Ultrasound on Healing of Bone Defects in Rat Tibia as Measured by Reconstructed Three-dimensional Analysis of Micro CT Images.

BACKGROUND/AIM: The aim of this study was to evaluate the effect of low-intensity pulsed ultrasound (LIPUS) on bone metabolism during the healing period in rat tibiae bone defects using micro-computed tomography (micro CT) imaging for three-dimensional morphological evaluation. MATERIALS AND METHODS: The right tibia received ultrasound exposure (US group) every day, whereas the opposite side served as a control (Control group). At 1, 2, and 3 weeks after the operation, micro CT was performed, and the volume and surface area of new bone formation in the bone defects was evaluated three-dimensionally. RESULTS: Bone volume (BV) and bone surface (BS) in the tibiae of both the US and Control groups demonstrated the highest values 1 week after the operation, with no significant differences between the groups. At 2 weeks after the operation, the BV and BS values in both groups had decreased, but the decrease was smaller in the US group than the Control group. At 3 weeks after the operation, the BV and BS values in the Control group were significantly lower than those in the US group. CONCLUSION: LIPUS stimulation can prevent bone loss during the healing of bone defects.

Evolution of Complex Niche-Constructing Behaviors and Ecological Inheritance of Adaptive Structures in a Physically Grounded Environment.

Niche construction is a process in which organisms modify the selection pressures on themselves and others through their ecological activities, and ecological inheritance is the consequence of niche construction inherited through generations. However, it is still unclear how such mutual interactions between robots or embodied agents and their physical environments can yield complex and divergent evolutionary processes or an open-ended evolution. Our purpose is to clarify what kind of complex and various niche-constructing behaviors evolve in a physically grounded environment under various conditions of ecological inheritance of constructed structures and spatial relationships. We focus on a predator-prey relationship, and constructed an evolutionary model in which a prey creature has to avoid predation through the construction of a structure composed of objects in a 2D physically simulated environment supported by a physics engine. We used a deep auto-encoder to extract the defining feature of adaptive structures automatically. The results in the case of no ecological inheritance revealed that the number of available resources can affect the diversity of emerging adaptive structures. Also, in the case with ecological inheritance, it was found that combinations of two types of ecological inheritance, which are the inheritance of adaptive structures and birthplace, can have strong effects on the diversity of emerging structures and the adaptivity of the population. We expect that findings in evolutionary simulations of niche-constructing behavior might contribute to evolutionary design of robotic builders or robot fabrication, especially when we assume physically simulated environments.

An integrated model of gene-culture coevolution of language mediated by phenotypic plasticity.

In this paper, we propose an agent-based model for investigating possible scenarios of genetic and cultural language evolution based on an integrated gene-culture coevolutionary framework. We focused on the following problems: (1) how communicative ability can evolve directionally under positive frequency-dependent selection and (2) how much of the directional effect there is between language and biological evolution. In our evolutionary experiments and analysis, we discovered a coevolutionary scenario involving the biological evolution of phenotypic plasticity and a cyclic coevolutionary dynamic between genetic and cultural evolution that is mediated by phenotypic plasticity. Furthermore, we discovered that the rates of cultural change are usually faster than the biological rates and fluctuate on a short time scale; on a long time scale, however, cultural rates tend to be slow. This implies that biological evolution can maintain the pace with language evolution. Finally, we analyzed the transfer entropy for a quantitative discussion of the directional effects between both evolutions. The results showed that biological evolution appears to be unable to maintain the pace with language evolution on short time scales, while their mutual directional effects are in the same range on long time scales. This implies that language and the relevant biology could coevolve.

A spatiotemporal analysis of acoustic interactions between great reed warblers (Acrocephalus arundinaceus) using microphone arrays and robot audition software HARK.

Acoustic interactions are important for understanding intra- and interspecific communication in songbird communities from the viewpoint of soundscape ecology. It has been suggested that birds may divide up sound space to increase communication efficiency in such a manner that they tend to avoid overlap with other birds when they sing. We are interested in clarifying the dynamics underlying the process as an example of complex systems based on short-term behavioral plasticity. However, it is very problematic to manually collect spatiotemporal patterns of acoustic events in natural habitats using data derived from a standard single-channel recording of several species singing simultaneously. Our purpose here was to investigate fine-scale spatiotemporal acoustic interactions of the great reed warbler. We surveyed spatial and temporal patterns of several vocalizing color-banded great reed warblers (Acrocephalus arundinaceus) using an open-source software for robot audition HARK (Honda Research Institute Japan Audition for Robots with Kyoto University) and three new 16-channel, stand-alone, and water-resistant microphone arrays, named DACHO spread out in the bird's habitat. We first show that our system estimated the location of two color-banded individuals' song posts with mean error distance of 5.5 ± 4.5 m from the location of observed song posts. We then evaluated the temporal localization accuracy of the songs by comparing the duration of localized songs around the song posts with those annotated by human observers, with an accuracy score of average 0.89 for one bird that stayed at one song post. We further found significant temporal overlap avoidance and an asymmetric relationship between songs of the two singing individuals, using transfer entropy. We believe that our system and analytical approach contribute to a better understanding of fine-scale acoustic interactions in time and space in bird communities.

Artificial Metamorphosis: Evolutionary Design of Transforming, Soft-Bodied Robots.

We show how the concept of metamorphosis, together with a biologically inspired model of multicellular development, can be used to evolve soft-bodied robots that are adapted to two very different tasks, such as being able to move in an aquatic and in a terrestrial environment. Each evolved solution defines two pairs of morphologies and controllers, together with a process of transforming one pair into the other. Animats develop from a single cell and grow through cellular divisions and deaths until they reach an initial larval form adapted to a first environment. To obtain the adult form adapted to a second environment, the larva undergoes metamorphosis, during which new cells are added or removed and its controller is modified. Importantly, our approach assumes nothing about what morphologies or methods of locomotion are preferred. Instead, it successfully searches the vast space of possible designs and comes up with complex, surprising, lifelike solutions that are reminiscent of amphibian metamorphosis. We analyze obtained solutions and investigate whether the morphological changes during metamorphosis are indeed adaptive. We then compare the effectiveness of three different types of selective pressures used to evolve metamorphic individuals. Finally, we investigate potential advantages of using metamorphosis to automatically produce soft-bodied designs by comparing the performance of metamorphic individuals with their specialized counterparts and designs that are robust to both environments.

Population and Evolutionary Dynamics based on Predator-Prey Relationships in a 3D Physical Simulation.

Recent studies have reported that population dynamics and evolutionary dynamics, occurring at different time scales, can be affected by each other. Our purpose is to explore the interaction between population and evolutionary dynamics using an artificial life approach based on a 3D physically simulated environment in the context of predator-prey and morphology-behavior coevolution. The morphologies and behaviors of virtual prey creatures are evolved using a genetic algorithm based on the predation interactions between predators and prey. Both population sizes are also changed, depending on the fitness. We observe two types of cyclic behaviors, corresponding to short-term and long-term dynamics. The former can be interpreted as a simple population dynamics of Lotka-Volterra type. It is shown that the latter cycle is based on the interaction between the changes in the prey strategy against predators and the long-term change in both population sizes, resulting partly from a tradeoff between their defensive success and the cost of defense.

Concurrent Bursty Behavior of Social Sensors in Sporting Events.

The advent of social media expands our ability to transmit information and connect with others instantly, which enables us to behave as "social sensors." Here, we studied concurrent bursty behavior of Twitter users during major sporting events to determine their function as social sensors. We show that the degree of concurrent bursts in tweets (posts) and retweets (re-posts) works as a strong indicator of winning or losing a game. More specifically, our simple tweet analysis of Japanese professional baseball games in 2013 revealed that social sensors can immediately react to positive and negative events through bursts of tweets, but that positive events are more likely to induce a subsequent burst of retweets. We confirm that these findings also hold true for tweets related to Major League Baseball games in 2015. Furthermore, we demonstrate active interactions among social sensors by constructing retweet networks during a baseball game. The resulting networks commonly exhibited user clusters depending on the baseball team, with a scale-free connectedness that is indicative of a substantial difference in user popularity as an information source. While previous studies have mainly focused on bursts of tweets as a simple indicator of a real-world event, the temporal correlation between tweets and retweets implies unique aspects of social sensors, offering new insights into human behavior in a highly connected world.

Emergent dynamics of fairness in the spatial coevolution of proposer and responder species in the ultimatum game.

While spatially local interactions are ubiquitous between coevolving species sharing recourses (e.g., plant-insect interactions), their effects on such coevolution processes of strategies involving the share of a resource are still not clearly understood. We construct a two-dimensional spatial model of the coevolution of the proposer and responder species in the ultimatum game (UG), in which a pair of proposer and responder individuals at each site plays the UG. We investigate the effects of the locality of interactions and the intensity of selection on the emergence of fairness between these species. We show that the lower intensity of selection favors fair strategies in general, and there are no significant differences in the evolution of fairness between the cases with local and global interactions when the intensity of selection is low. However, as the intensity of selection becomes higher, the spatially local interactions contribute to the evolution of fairer strategies more than the global interactions, even though fair strategies become more difficult to evolve. This positive effect of spatial interactions is expected to be due to the mutual benefit of fairness for both proposer and responder species in future generations, which brings about a dynamic evolution process of fairness.

Emergence of a dynamic resource partitioning based on the coevolution of phenotypic plasticity in sympatric species.

This paper investigates the coevolutionary dynamics of the phenotypic plasticity in the context of overlap avoidance behaviors of shared niches in sympatric species. Especially, we consider whether and how a differentiation of phenotypic plasticity can emerge under the assumption that there are no initial asymmetric relationships among coevolving species. We construct a minimal model where several different species participate in a partitioning of their shared niches, and evolve their behavioral plasticity to avoid an overlap of their niche use. By conducting evolutionary experiments with various conditions of the number of species and niches, we show that the two different types of asymmetric distributions of phenotypic plasticity emerge depending on the settings of the degree of congestion of the shared niches. In both cases, all species tended to obtain the similar amount of fitness regardless of such differences in their plasticity. We also show that the emerged distributions are coevolutionarily stable in general.

A simple computational model of the evolution of a communicative trait and its phenotypic plasticity.

We consider a simple computational model of the evolution of a quantitative trait and its phenotypic plasticity based on directional and positive frequency-dependent selection in order to explore whether and how leaning might facilitate evolution under the dynamics that arise from communicative interactions among individuals. In the model, each individual expresses, at many different times in its lifetime, its real-valued trait depending on the probability distribution determined by its own genotypes. In communicative interactions between two individuals, the contribution of an interaction to the fitness is high when their trait values are close to each other as well as large, which represents the positive frequency-dependent and directional components of selection, respectively. The iterative interactions allow individuals to acquire a more adaptive trait pair through trial and error. Under the stochastic evolution process with the limited number of individuals, we show that learning allows the population to avoid getting stuck in the global but low optimum of the innate and individual-level fitness landscape via both aspects of the components of selection, and brings about the successful evolution by increasing the genetic variation of the population. We also analyze how such an effect of learning can be realized by measuring the degree of the two different contributions for increasing the adaptivity and similarity of communicative traits, respectively. We show that this effect of learning arises from these different types of contributions depending on the biological and environmental conditions such as the mutation rate and the duration of communicative interactions. We further show the condition for the complete genetic assimilation to occur.

Heterochrony and artificial embryogeny: a method for analyzing artificial embryogenies based on developmental dynamics.

Artificial embryogenies are an extension to evolutionary algorithms, in which genotypes specify a process to grow phenotypes. This approach has become rather popular recently, with new kinds of embryogenies being increasingly reported in the literature. Nevertheless, it is still difficult to analyze and compare the available embryogenies, especially if they are based on very different paradigms. We propose a method to analyze embryogenies based on growth dynamics, and how evolution is able to change them (heterochrony). We define several quantitative measures that allow us to establish the variation in growth dynamics that an embryogeny can create, the degree of change in growth dynamics caused by mutations, and the degree to which an embryogeny allows mutations to change the growth of a genotype, but without changing the final phenotype reached. These measures are based on an heterochrony framework, due to Alberch, Gould, Oster, & Wake (1979 Size and shape in ontogeny and phylogeny, Paleobiology, 5(3), 296-317) that is used in real biological organisms. The measures are general enough to be applied to any embryogeny, and can be easily computed from simple experiments. We further illustrate how to compute these measures by applying them to two simple embryogenies. These embryogenies exhibit rather different growth dynamics, and both allow for mutations that changed growth without affecting the final phenotype.

Cyclic coevolution of cooperative behaviors and network structures.

This paper aims at understanding coevolutionary dynamics of cooperative behaviors and network structures of interactions. We constructed an evolutionary model in which each individual not only has a strategy for prisoner's dilemma to play with its neighboring members on the network, but also has a strategy for changing its neighboring structure of the network. By conducting evolutionary experiments with various settings of the payoff matrix, we found that the coevolutionary cycles of cooperative behaviors of individuals and their network structures repeatedly occurred when both the temptation to defect and the cost for playing a game were moderate.

The dynamic changes in roles of learning through the Baldwin effect.

The interaction between evolution and learning called the Baldwin effect is a two-step evolutionary scenario caused by the balances between benefit and cost of learning in general. However, little is known about the dynamic evolution of these balances in complex environments. Our purpose is to give a new insight into the benefit and cost of learning by focusing on the quantitative evolution of phenotypic plasticity under the assumption of epistatic interactions. For this purpose, we have constructed an evolutionary model of quantitative traits by using an extended version of Kauffman's NK fitness landscape. Phenotypic plasticity is introduced into our model; whether each phenotype is plastic or not is genetically defined, and plastic phenotypes can be adjusted by learning. The simulation results clearly show that drastic changes in roles of learning cause three-step evolution through the Baldwin effect and also cause the evolution of genetic robustness against mutations. We also conceptualize four different roles of learning by using a hill-climbing image of a population on a fitness landscape.

Interactions between learning and evolution: the outstanding strategy generated by the Baldwin effect.

The Baldwin effect is known as an possible interaction between learning and evolution, where individual lifetime learning can influence the course of evolution without using any Lamarckian mechanism. Our concern is to consider the Baldwin effect in dynamic environments, especially when there is no explicit optimal solution through generations and this solution depends only on interactions among agents. We adopted the iterated Prisoner's Dilemma as a dynamic environment, introduced phenotypic plasticity into its strategies, and conducted computational experiments, in which phenotypic plasticity is allowed to evolve. The Baldwin effect was observed in the experiments as follows: First, strategies with enough plasticity spread, which caused a shift from defect-oriented populations to cooperative populations. Second, these strategies were replaced by a strategy with a modest amount of plasticity generated by interactions between learning and evolution. By making three kinds of analysis, we have shown that this strategy provides outstanding performance in comparison with other deterministic strategies. Further experiments towards open-ended evolution have also been conducted so as to generalize our results.