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Background: Breast cancer requires evaluating treatment plans using dosimetric and biological parameters. Considering radiation dose distribution and tissue response, healthcare professionals can optimize treatment plans for better outcomes. Objective: This study aimed to evaluate the effects of the different Dose Calculation Algorithms (DCAs) and Biologically Model-Related Parameters (BMRPs) on the prediction of cardiopulmonary complications due to left breast radiotherapy. Material and Methods: In this practical study, the treatment plans of 21 female patients were simulated in the Monaco Treatment Planning System (TPS) with a prescribed dose of 50 Gy in 25 fractions. Dose distribution was extracted using the three DCAs [Pencil Beam (PB), Collapsed Cone (CC), and Monte Carlo (MC)]. Cardiopulmonary complications were predicted by Normal Tissue Complication Probability (NTCP) calculations using different dosimetric and biological parameters. The Lyman-Kutcher-Burman (LKB) and Relative-Seriality (RS) models were used to calculate NTCP. The endpoint for NTCP calculation was pneumonitis, pericarditis, and late cardiac mortality. The ANOVA test was used for statistical analysis. Results: In calculating Tumor Control Probability (TCP), a statistically significant difference was observed between the results of DCAs in the Poisson model. The PB algorithm estimated NTCP as less than others for all Pneumonia BMRPs. Conclusion: The impact of DCAs and BMRPs differs in the estimation of TCP and NTCP. DCAs have a stronger influence on TCP calculation, providing more effective results. On the other hand, BMRPs are more effective in estimating NTCP. Consequently, parameters for radiobiological indices should be cautiously used s to ensure the appropriate consideration of both DCAs and BMRPs.

Oleogels containing bioactive substances such as citral (CT) are used as functional food ingredients. However, little information is available on the influence of different oleogel network structure caused by CT addition and fatty acid distribution on its digestion behavior. Coconut oil, palm oil, high oleic peanut oil, safflower seed oil, and perilla seed oil were used in this study. The results showed that perilla seed oil-CT-based oleogels had the highest oil-holding capacity (99.03 ± 0.3), whereas CT addition higher than 10 wt% could lead to the morphology collapse of oleogels. Physical and thermodynamic analyses revealed that CT could reduce oleogel hardness and higher unsaturated fatty acid content is more likely to form oleogel with stable and tight crystalline network. Moreover, the dense structure of oleogels hinders the contact between oleogels and lipase, thus weakening triglyceride digestion. These findings provide valuable insights into the design of oleogels loading with CT., Competing Interests: Declaration of competing interest The authors declare that they have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Human dietary exposure to chemical compounds is a priority issue for public health authorities since it constitutes a key step in risk assessment, and food packaging could be an important source of contamination. In this study, the bioaccessibility of cyclodi-BADGE was evaluated in canned seafood samples using a standardized protocol of in vitro gastrointestinal digestion and an analytical method based on liquid chromatography coupled to tandem mass spectrometry. The impact of enzymes, different gastric pHs, and food-covering liquids on the bioaccessibility of cyclodi-BADGE was studied. The results highlighted that cyclodi-BADGE was available to be absorbed at the intestinal level (90.9-112.3%), and its bioaccessibility increased substantially in fat food samples. Finally, the estimated dietary exposure to cyclodi-BADGE in the Spanish adult population reached values of 14.26 μg/kg bw/day for tuna in tomato, exceeding the tolerable daily intake (1.5 μg/kg bw/day) recommended for chemicals with high toxicological risk., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Sunflower oil (SFO) and Flaxseed oil (FSO) were microencapsulated using simple and complex coacervation techniques with Opuntia (Cactaceae) mucilage (Mu) and with a combination of Mu with chitosan (Chit). The encapsulation efficiency (EE) of SFO and FSO in emulsions using Mu/Chit shells was 96.7% and 97.4%, respectively. Morphological studies indicated successful entrapment of oils in core shells with particle sizes ranging from 1396 ± 42.4 to 399.8 ± 42.3 nm. The thermogravimetric analyses demonstrated enhanced core protection with thermal stability noted for microcapsules regardless of encapsulation method. The stability of the microcapsules, during in vitro digestion was studied. The obtained results revealed that the microcapsules are intact in oral conditions and have a slow release of oil over stomach digestion and rapid release in the small intestine. The results showed that Mu and Mu/Chit coacervates can be used as effective carrier systems to encapsulate sensitive ingredients and functional oils., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Abstract: Nonadherence to direct oral anticoagulant (DOAC) pharmacotherapy may increase the risk of thromboembolism or bleeding, and delayed or missed doses are the most common types of nonadherence. Current recommendations from regulatory agencies or guidelines regarding this issue lack evidence and fail to consider individual differences. This study aimed to develop individual remedial dosing strategies when the dose was delayed or missed for DOACs, including rivaroxaban, apixaban, edoxaban, and dabigatran etexilate. Remedial dosing regimens based on population pharmacokinetic (PK)-pharmacodynamic (PD) modeling and simulation strategies were developed to expeditiously restore drug concentration or PD biomarkers within the therapeutic range. Population PK-PD characteristics of DOACs were retrieved from previously published literature. The effects of factors that influence PK and PD parameters were assessed for their impact on remedial dosing regimens. A web-based dashboard was established with R-shiny to recommend remedial dosing regimens based on patient traits, dosing schedules, and delay duration. Addressing delayed or missed doses relies on the delay time and specific DOACs involved. Additionally, age, body weight, renal function, and polypharmacy may marginally affect remedial strategies. The proposed remedial dosing strategies surpass current recommendations, with less deviation time beyond the therapeutic range. The online dashboard offers quick and convenient solutions for addressing missed or delayed DOACs, enabling individualized remedial dosing strategies based on patient characteristics to mitigate the risks of bleeding and thrombosis., (© 2024 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Background: Wolbachia incompatible insect technique (IIT) programs have been shown in field trials to be highly effective in suppressing populations of mosquitoes that carry diseases such as dengue, chikungunya, and Zika. However, the frequent and repeated release of Wolbachia-infected male mosquitoes makes such programs resource-intensive. While the need for optimization is recognized, potential strategies to optimize releases and reduce resource utilization have not been fully explored., Results: We developed a process-based model to study the spatio-temporal metapopulation dynamics of mosquitoes in a Wolbachia IIT program, which explicitly incorporates climatic influence in mosquito life-history traits. We then used the model to simulate various scale-down and redistribution strategies to optimize the existing program in Singapore. Specifically, the model was used to study the trade-offs between the intervention efficacy outcomes and resource requirements of various release program strategies, such as the total number of release events and the number of mosquitoes released. We found that scaling down releases in existing sites from twice a week to only once a week yielded small changes in suppression efficacy (from 87 to 80%), while requiring 44% fewer mosquitoes and release events. Additionally, redistributing mosquitoes from already suppressed areas and releasing them in new areas once a week led to a greater total suppressive efficacy (83% compared to 61%) while also yielding a 16% and 14% reduction in the number of mosquitoes and release events required, respectively., Conclusions: Both scale-down and redistribution strategies can be implemented to significantly reduce program resource requirements without compromising the suppressive efficacy of IIT. These findings will inform planners on ways to optimize existing and future IIT programs, potentially allowing for the wider adoption of this method for mosquito-borne disease control., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: We would like to declare that the primary author, Preston Lim, is an employee of Verily Life Sciences, which produces Wolbachia mosquitoes for mosquito control programs. However, he is pursuing this research in the capacity of his PhD studentship with the National University of Singapore. The opinions expressed in this article are those of the individual authors, and do not reflect those of the primary author’s employer (Verily Life Sciences LLC)., (© 2024. The Author(s).)

The hypothalamus senses the appetite-regulating hormones and also coordinates the metabolic function in alignment with the circadian rhythm. This alignment is essential to maintain the physiological conditions that prevent clinically important comorbidities, such as obesity or type-2 diabetes. However, a complete model of the hypothalamus that relates food intake with circadian rhythms and appetite hormones has not yet been developed. In this work, we present a computational model that accurately allows interpreting neural activity in terms of hormone regulation and sleep-wake cycles. We used a conductance-based model, which consists of a system of four differential equations that considers the ionotropic and metabotropic receptors, and the input currents from homeostatic hormones. We proposed a logistic function that fits available experimental data of insulin hormone concentration and added it into a short-term ghrelin model that served as an input to our dynamical system. Our results show a double oscillatory system, one synchronized by light-regulated sleep-wake cycles and the other by food-regulated feeding-fasting cycles. We have also found that meal timing frequency is highly relevant for the regulation of the hypothalamus neurons. We therefore present a mathematical model to explore the plausible link between the circadian rhythm and the endogenous food clock., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The merging of physiology and toxicokinetics, or pharmacokinetics, with computational modeling to characterize dosimetry has led to major advances for both the chemical and pharmaceutical research arenas. Driven by the mutual need to estimate internal exposures where in vivo data generation was simply not possible, the application of toxicokinetic modeling has grown exponentially in the past 30 years. In toxicology the need has been the derivation of quantitative estimates of toxicokinetic and toxicodynamic variability to evaluate the suitability of the tenfold uncertainty factor employed in risk assessment decision-making. Consideration of a host of physiologic, ontogenetic, genetic, and exposure factors are all required for comprehensive characterization. Fortunately, the underlying framework of physiologically based toxicokinetic models can accommodate these inputs, in addition to being amenable to capturing time-varying dynamics. Meanwhile, international interest in advancing new approach methodologies has fueled the generation of in vitro toxicity and toxicokinetic data that can be applied in in vitro-in vivo extrapolation approaches to provide human-specific risk-based information for historically data-poor chemicals. This review will provide a brief introduction to the structure and evolution of toxicokinetic and physiologically based toxicokinetic models as they advanced to incorporate variability and a wide range of complex exposure scenarios. This will be followed by a state of the science update describing current and emerging experimental and modeling strategies for population and life-stage variability, including the increasing application of in vitro-in vivo extrapolation with physiologically based toxicokinetic models in pharmaceutical and chemical safety research. The review will conclude with case study examples demonstrating novel applications of physiologically based toxicokinetic modeling and an update on its applications for regulatory decision-making. Physiologically based toxicokinetic modeling provides a sound framework for variability evaluation in chemical risk assessment., Competing Interests: Declarations. Competing interests: H.H.D. is a guest editor for this special issue. The other authors declare no potential conflicts of interest., (© 2024. The Author(s).)

Hypoxia is one of the main hallmarks of hepatocellular carcinoma (HCC) resulting from improper oxygenation and insufficient nourishment of the HCC microenvironment. The effect of hypoxia is mediated by hypoxia-inducible factor-1A (HIF-1A) via targeting various downstream pathways, including glycolysis, angiogenesis, and survival signaling. However, HCC cell lines in a 2-dimensional (2D) setting do not resemble the metabolic signature of HCC. Here we aim to overcome these limitations by developing an HCC organoid that recapitulates the HIF-1A metabolic shift. The enrichment analysis of the RNA-Seq data revealed that HIF-1A-driven glycolytic shift is of the significant pathways. The established organoid model, using xeno-free plasma-derived extracellular matrix (ECM) as a scaffold and nutritive biomatrix, maintained its structural integrity and viability for up to 14 days; the comparative analysis of the cobalt (II) chloride (CoCl 2 )-treated organoids to the untreated ones unveiled reduced size and proliferative capacity. Interestingly, our organoid model showed an elevated expression of HIF-1A and glycolysis enzymes compared to their counterparts in the CoCl 2 -treated organoids. HIF-1A molecular expression-translated biochemical signature is further assessed in our spontaneously growing organoids showing an increase in glucose uptake, intracellular pyruvate, extracellular lactate dehydrogenase expression, and extracellular lactate production, while hydrogen peroxide (H 2 O 2 ), a marker for oxidative metabolism, is reduced. Our data confirmed the potency of the established organoid model to mimic the molecular and biochemical HIF-1A-driven metabolism, which validates its potential use as an in vitro HCC model. Our model naturally simulates hypoxic conditions and simultaneous HIF-1A-dependent glycolysis within HCC rather than using of CoCl 2 -induced hypoxic conditions., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethics approval: This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the Institution Review Board (IRB) of the National Liver Institute (NLI), Menoufiya University (date: September 1st, 2018, number: 00140/2018). Consent to participate: Not applicable. Consent to publish: Not applicable., (© 2024. The Author(s).)

Phenotypic integration is often perceived as being able to produce convergent evolution in the absence of selection, but specific mechanisms for this process are lacking and a connection has never been empirically demonstrated. A new model of the effect of integration on convergence provides such a mechanism, along with other predictions about the influence of integration on evolutionary patterns. I use simulations and data from three empirical systems-turtle shells, characiform fish, and squirrel mandibles-to investigate the degree to which evolutionary integration is associated with high levels of convergent evolution. Levels of integration were varied in Brownian motion simulations and the resulting amounts of stochastic convergent evolution were quantified. Each empirical system was divided into modules, and the strength of integration, average amount of convergence, phenotypic disparity, and rate of evolution in each module were measured. Results from the simulations and from all three empirical systems converge on a common result: higher levels of phenotypic integration are indeed associated with higher levels of convergence. This is despite a lack of consistent association between the strength of phenotypic integration and evolutionary rate or disparity. The results here are only correlational. Further studies that more closely examine the influence of within-population drivers of evolutionary integration-for example, genetic or developmental integration-on convergence are required before it is possible to definitively establish when phenotypic integration can cause evolutionary convergence. Until then, however, the results of this study strongly suggest that phenotypic integration will often promote convergent evolution., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology.)

Whether walking, running, slithering, or flying, organisms display a remarkable ability to move through complex and uncertain environments. In particular, animals have evolved to cope with a host of uncertainties-both of internal and external origin-to maintain adequate performance in an ever-changing world. In this review, we present mathematical methods in engineering to highlight emerging principles of robust and adaptive control of organismal locomotion. Specifically, by drawing on the mathematical framework of control theory, we decompose the robust and adaptive hierarchical structure of locomotor control. We show how this decomposition along the robust-adaptive axis provides testable hypotheses to classify behavioral outcomes to perturbations. With a focus on studies in non-human animals, we contextualize recent findings along the robust-adaptive axis by emphasizing two broad classes of behaviors: (1) compensation to appendage loss and (2) image stabilization and fixation. Next, we attempt to map robust and adaptive control of locomotion across some animal groups and existing bio-inspired robots. Finally, we highlight exciting future directions and interdisciplinary collaborations that are needed to unravel principles of robust and adaptive locomotion., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology.)

Tree crown biomass is rarely assessed individually in forest monitoring, but when it is to be reported, standard conversion factors are commonly used for predicting crown biomass as a function of stem biomass. Further, in the conventional methods, the predicted total tree biomass is assigned exclusively to the stem position. In reality, however, tree and in particular crown biomass is spatially distributed over the entire crown projection area. In this study, we investigated the "Horizontal Biomass Distribution (HBD)" model, which serves to depict this biomass as a spatial distribution over the crown projection area: here, the individual tree crown biomass is modeled as a continuous distribution within the area defined by the crown projection. We examined two empirical HBD prediction models: (1) Weibull distribution; and (2) Segmented polynomial regression; which describe the biomass contained up to a given crown radius on the horizontal projection of individual trees, i.e., spatial distribution of crown biomass as a function of the horizontal distance from the stem. The approach was demonstrated using terrestrial laser scanning (TLS) on a sample of 33 urban trees from eight species. We found that (1) the segmented polynomial regression model revealed better performance in defining the HBD for various tree species; (2) a certain variability in HBD patterns was observed between the sample trees, with the variability being more pronounced between species groups than within species; and (3) the methodological approaches using TLS proxies are suitable and convenient to non-destructively assess the HBD, which would be otherwise impractical by direct measurements., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The onset of degenerative joint diseases such as post-traumatic osteoarthritis (PTOA) are associated with joint injury, biomechanical changes, and synovial biochemical anomalies. Sex and reproductive endocrinology have been emerging as potential risk factors, with epidemiological evidence revealing that female's exhibit higher PTOA risk and poorer outcomes post-injury compared to males. Sex hormones, including estradiol, progesterone, and testosterone, have been shown to regulate inflammatory signaling in immune and synovial cells, yet their collective impact on injury-induced joint inflammation and catabolism is poorly understood. Using an in silico kinetic model, we investigated the effects of sex-specific endocrine states on post-injury mechanisms in the human synovial joint. Our model results reveal that heightened estradiol levels in pre-menopausal females during the peri-ovulatory phase increase interleukin (IL)-1β expression and suppress IL-10 expression within the synovium after a simulated injury. Conversely, elevated testosterone levels in males decrease post-injury IL-1β, tumor necrosis factor alpha (TNF)-α, and stromelysin (MMP)-3 expression while increasing IL-10 production compared to females. Gaining insight into the effects of sex hormones on injury-induced inflammation and cartilage degradation provides a basis for designing future experimental and clinical studies to explore their effects on the synovial system, with a particular focus on the female sex., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

To understand the distribution of Atlas pistachio (Pistacia atlantica Desf.) in Algeria, we analyzed the environmental factors influencing its habitat. This study employs an ensemble modelling (EM) approach, a robust predictive technique in ecological niche modelling that enables us to identify critical environmental drivers affecting plant distributions across different ecosystems' focal species. The EM incorporated four prediction algorithms (generalized linear model, boosted regression trees, random forest, and maximum entropy algorithms); we modelled Atlas pistachio's niche with 2810 occurrence points and 32 environmental variables, including climatic, edaphic, topographic, and anthropogenic factors. The model demonstrated high accuracy, with an AUC of 0.97 and TSS of 0.88. Key factors influencing distribution were precipitation in the driest month (Bio14), soil bulk density (BD), cation exchange capacity (CEC), human modification, and average diurnal amplitude (Bio2), with a relative importance of 20.1%, 12.7%, 6.7%, 4.9%, and 3.1%, respectively. These findings underscore the utility of ensemble modelling to pinpoint specific environmental variables critical to the species' presence and ecological adaptability, which has broader implications for other plant species in arid landscapes. Notably, the probability of Atlas pistachio occurrence increased with BD and decreased with CEC and human influence. Our results emphasize the EM approach as a versatile tool in ecological modelling, facilitating species-specific analyses that contribute to broader ecological restoration efforts, especially in degraded arid and semi-arid regions. This study advances our understanding of Atlas pistachio's environmental requirements and highlights the importance of EM in developing targeted programs to restore degraded ecosystems., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Microorganisms have evolved sophisticated sensor-actuator circuits to perform taxis in response to various environmental stimuli. How any given circuit can select between different taxis responses in noisy vs. saturated stimuli conditions is unclear. Here, we investigate how Euglena gracilis can select between positive vs. negative phototaxis under low vs. high light intensities, respectively. We propose three general selection mechanisms for phototactic microswimmers, and biophysical modeling demonstrates their effectiveness. Perturbation and high-speed imaging experiments show that of these three mechanisms, the "photoresponse inversion mechanism" is implemented in E. gracilis : a fast, light-intensity-dependent switching between two flagellar beat states responsible for swimming and turning causes positive vs. negative phototaxis at low vs. high light intensity via run-and-tumble vs. helical klinotaxis strategies, respectively. This coordinated beat-switching mechanism then also accounts for a larger set of previously reported E. gracilis behaviors; furthermore, it suggests key design principles for other natural as well as synthetic microswimmers., Competing Interests: Competing interests statement:The authors declare no competing interest.

Gastrulation is a critical process during embryonic development that transforms a single-layered blastula into a multilayered embryo with distinct germ layers, which eventually give rise to all the tissues and organs of the organism. Studies across species have uncovered the mechanisms underlying the building blocks of gastrulation movements, such as localized in-plane and out-of-plane epithelial deformations. The next challenge is to understand dynamics on the scale of the embryo: this requires quantifying strain tensors, which rigorously describe the differences between the deformed configurations taken on by local clusters of cells at time instants of observation and their reference configuration at an initial time. We present a systematic strategy for computing such tensors from the local dynamics of cell clusters, which are chosen across the embryo from several regions whose morphogenetic fate is central to viable gastrulation. As an application of our approach, we demonstrate a strategy of identifying distinct Drosophila morphological domains using strain tensors., Competing Interests: Declaration of interests The author declares no competing interests., (Copyright © 2024 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Bacillus subtilis is an important industrial and environmental microorganism known to occupy many niches and produce many compounds of interest. Although it is one of the best-studied organisms, much of this focus including the reconstruction of genome-scale metabolic models has been placed on a few key laboratory strains. Here, we substantially expand these prior models to pan-genome-scale, representing 481 genomes of B. subtilis with 2,315 orthologous gene clusters, 1,874 metabolites, and 2,239 reactions. Furthermore, we incorporate data from carbon utilization experiments for eight strains to refine and validate its metabolic predictions. This comprehensive pan-genome model enables the assessment of strain-to-strain differences related to nutrient utilization, fermentation outputs, robustness, and other metabolic aspects. Using the model and phenotypic predictions, we divide B. subtilis strains into five groups with distinct patterns of behavior that correlate across these features. The pan-genome model offers deep insights into B. subtilis' metabolism as it varies across environments and provides an understanding as to how different strains have adapted to dynamic habitats., Importance: As the volume of genomic data and computational power have increased, so has the number of genome-scale metabolic models. These models encapsulate the totality of metabolic functions for a given organism. Bacillus subtilis strain 168 is one of the first bacteria for which a metabolic network was reconstructed. Since then, several updated reconstructions have been generated for this model microorganism. Here, we expand the metabolic model for a single strain into a pan-genome-scale model, which consists of individual models for 481 B. subtilis strains. By evaluating differences between these strains, we identified five distinct groups of strains, allowing for the rapid classification of any particular strain. Furthermore, this classification into five groups aids the rapid identification of suitable strains for any application., Competing Interests: The authors declare no conflict of interest.

The discrepancy between model predictions and actual processes, known as process-model mismatch (PMM), remains a substantial challenge in bioprocess optimization. We previously introduced a hybrid in silico/in-cell controller (HISICC) that combines model-based optimization with cell-based feedback to address this problem. Here, we extended this approach to regulate a key enzyme level using intracellular biosensing. The extended HISICC was implemented using an Escherichia coli strain engineered for fatty acid production (FA3). This strain contains a genetically encoded feedback controller that decelerates the expression of acetyl-CoA carboxylase (ACC) in response to malonyl-CoA synthesized through the enzymatic reaction. We modeled FA3 to allow the HISICC to optimize an inducer input that accelerates the enzyme expression. Simulations showed that the HISICC slowed the unexpectedly rapid accumulation of ACC resulting from PMMs before it reached cytotoxic levels, thereby improving fatty acid yields. These results highlight the potential of our approach, particularly in cases where monitoring intracellular biomolecules is required to handle PMMs., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Cellular networks realize their functions by integrating intricate information embedded within local structures such as regulatory paths and feedback loops. However, the precise mechanisms of how local topologies determine global network dynamics and induce bifurcations remain unidentified. A critical step in unraveling the integration is to identify the governing principles, which underlie the mechanisms of information flow. Here, we develop the cumulative linearized approximation (CLA) algorithm to address this issue. Based on perturbation analysis and network decomposition, we theoretically demonstrate how perturbations affect the equilibrium variations through the integration of all regulatory paths and how stability of the equilibria is determined by distinct feedback loops. Two illustrative examples, i.e., a three-variable bistable system and a more intricate epithelial-mesenchymal transition (EMT) network, are chosen to validate the feasibility of this approach. These results establish a solid foundation for understanding information flow across cellular networks, highlighting the critical roles of local topologies in determining global network dynamics and the emergence of bifurcations within these networks. This work introduces a novel framework for investigating the general relationship between local topologies and global dynamics of cellular networks under perturbations., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Human breathing is crucial for studying indoor environments and human health. Computational Fluid Dynamics (CFD) is a key tool for simulating human respiration. To enhance the accuracy of CFD simulations and reduce computation time, a new simulation strategy for human respiration is proposed in this paper. The effects of steady versus unsteady boundary conditions on simulation results were examined. For the unsteady boundary, sinusoidal exhalation velocities and non-inhalation gas were assumed, while the steady boundary involved constant velocities during both exhalation and inhalation phases. The jet center trajectory under different boundary conditions was analyzed and compared with experimental data. Additionally, variations in pollutant dispersion near the mouth under the two boundary conditions were discussed. Furthermore, the paper compared the calculation accuracy, calculation time and memory occupied by a single turbulence model or switching flow character models in human respiration simulation. Differences in exhaled gas vorticity and jet penetration depth across different flow models were identified. Finally, combined with the non-iterative algorithm, the optimal strategy of human respiration simulation was proposed. Results show that under the comprehensive consideration of calculation accuracy, calculation time and memory occupancy, using sinusoidal expiratory boundary conditions combined with the PISO algorithm, with the RNG k-ε model during expiratory phase, and switching into the laminar flow during inspiratory phase, is the optimal strategy of simulating human breathing., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Gao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

"The Strategy of Model Building in Population Biology" published by Richard Levins in 1966 has been cited over 2500 times. For a paper concerned with modeling approaches in population biology a surprisingly large part of the attention. The Strategy received comes from history and philosophy of biology, and specifically from accounts on model and model formulation. The Strategy is an unusual paper; it presents neither new data nor a new formal model; at times it reads like a manifesto for some modeling approach, without specifying which broader program that approach intends to support. When these peculiarities of The Strategy are even mentioned, the philosophical literature tends to explain them away by invoking Levins' Marxist commitments. In contrast, I argue that those peculiarities can be explained by examining the programmatic purpose of the paper; starting from his doctoral work, Levins was trying to establish a research program meant to account for the relations between fitness and environment in different terms than the prevalent lock-and-key view. My paper brings that program back to the discussion, explains its relation to competing approaches and examines Levins' approach to modeling in light of that context., (© 2024. The Author(s).)

Spontaneous locomotion is a common feature of most metazoan cells, generally attributed to the properties of actomyosin networks. This force-producing machinery has been studied down to the most minute molecular details, especially in lamellipodium-driven migration. Nevertheless, how actomyosin networks work inside contraction-driven amoeboid cells still lacks unifying principles. Here, using stable motile blebs from HeLa cells as a model amoeboid motile system, we imaged the dynamics of the actin cortex at the single filament level and revealed the co-existence of three distinct rheological phases. We introduce "advected percolation," a process where rigidity percolation and active advection synergize, spatially organizing the actin network's mechanical properties into a minimal and generic locomotion mechanism. Expanding from our observations on simplified systems, we speculate that this model could explain, down to the single actin filament level, how amoeboid cells, such as cancer or immune cells, can propel efficiently through complex 3D environments., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Both metabolism and growth scale sublinearly with body mass across species. Ecosystems show the same sublinear scaling between production and total biomass, but ecological theory cannot reconcile the existence of these nearly identical scalings at different levels of biological organization. We attempt to solve this paradox using marine phytoplankton, connecting individual and ecosystem scalings across three orders of magnitude in body size and biomass. We find that competitive interactions determined by biomass slow metabolism in a consistent fashion across species of different sizes. These effects dominate over species-specific peculiarities, explaining why community composition does not affect respiration and production patterns. The sublinear scaling of ecosystem production thus emerges from this metabolic density-dependence that operates across species, independently of the equilibrium state or resource regime. Our findings demonstrate the connection between individual and ecosystem scalings, unifying aspects of physiology and ecology to explain why growth patterns are so strikingly similar across scales., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Blood coagulation is a vital physiological process involving a complex network of biochemical reactions, which converge to form a blood clot that repairs vascular injury. This process unfolds in three phases: initiation, amplification, and propagation, ultimately leading to thrombin formation. Coagulation begins when tissue factor (TF) is exposed on an injured vessel's wall. The first step is when activated factor VII (VIIa) in the plasma binds to TF, forming complex TF:VIIa, which activates factor X. Activated factor X (Xa) is necessary for coagulation, so the regulation of its activation is crucial. Tissue Factor Pathway Inhibitor (TFPI) is a critical regulator of the initiation phase as it inhibits the activation of factor X. While previous studies have proposed two pathways-direct and indirect binding-for TFPI's inhibitory role, the specific biochemical reactions and their rates remain ambiguous. Many existing mathematical models only assume an indirect pathway, which may be less effective under physiological flow conditions. In this study, we revisit datasets from two experiments focused on activated factor X formation in the presence of TFPI. We employ an adaptive Metropolis method for parameter estimation to reinvestigate a previously proposed biochemical scheme and corresponding rates for both inhibition pathways. Our findings show that both pathways are essential to replicate the static experimental results. Previous studies have suggested that flow itself makes a significant contribution to the inhibition of factor X activation. We added flow to this model with our estimated parameters to determine the contribution of the two inhibition pathways under these conditions. We found that direct binding of TFPI is necessary for inhibition under flow. The indirect pathway has a weaker inhibitory effect due to removal of solution phase inhibitory complexes by flow., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Santiago et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Ventral furrow (VF) formation in Drosophila melanogaster is an important model of epithelial folding. Previous models of VF formation require cell volume conservation to convert apically localized constriction forces into lateral cell elongation and tissue folding. Here, we have investigated embryonic morphogenesis in anillin knockdown (scra RNAi) embryos, where basal cell membranes fail to form and therefore cells can lose cytoplasmic volume through their basal side. Surprisingly, the mesoderm elongation and subsequent folding that comprise VF formation occurred essentially normally. We hypothesized that the effects of viscous shear may be sufficient to drive membrane elongation, providing effective volume conservation, and thus driving tissue folding. Since this hypothesis may not be possible to test experimentally, we turned to a computational approach. To test whether viscous shear is a dominant force for morphogenesis in vivo, we developed a 3D computational model incorporating both accurate cell and tissue geometry, and experimentally measured material parameters. Results from this model demonstrate that viscous shear generates sufficient force to drive cell elongation and tissue folding in vivo., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2024. Published by The Company of Biologists Ltd.)

Evaluation of the CYP3A induction risk is important in early drug development stages. This study focused on 4 β -hydroxycholesterol (4 β -HC) as an endogenous biomarker of drug-drug interactions (DDIs) caused by CYP3A induction. We investigated a new approach using 4 β -HC for quantitative prediction of DDIs caused by CYP3A induction based on the mechanistic static pharmacokinetic (MSPK) model. The induction ratio, i.e., the ratio of plasma 4 β -HC or 4 β -HC/cholesterol (4 β -HC/C) with and without a coadministered CYP3A inducer, and the ratio of the area under the plasma concentration-time curve (AUCR), i.e., the ratio of the AUC of plasma CYP3A substrate drugs with and without a coadministered CYP3A inducer, were collected. The scaling factor ( d ) in the MSPK model was calculated from the induction ratio of 4 β -HC or 4 β -HC/C based on the systemic term in the MSPK model. The AUCR of 18 CYP3A substrates with and without coadministration of seven CYP3A inducers were then predicted by substituting the calculated d value into the MSPK model. This approach showed that approximately 84% of the predicted AUCR values were within a twofold range of the observed values, showing that this approach can be a good tool to quantitatively predict DDIs caused by CYP3A induction. SIGNIFICANCE STATEMENT: A concise approach to predict drug interactions with adequate accuracy is preferable in the early drug development stage. In this study, a new approach using 4 β -hydroxycholesterol for quantitative prediction of drug-drug interactions caused by CYP3A induction was investigated. The predictability was verified using seven CYP3A inducers and 18 substrates., (Copyright © 2024 by The American Society for Pharmacology and Experimental Therapeutics.)

The objectives of this study were to expand and implement a Computational Fluid Dynamics (CFD)-Dissolution, Absorption and Clearance (DAC)-Pharmacokinetics (PK) multi-physics modeling framework for simulating the transport of suspension-based nasal corticosteroid sprays. The mean CFD-predicted peak plasma concentration (C max ) and area under the curve (AUC) of the plasma concentration-time profile, based on three representative nasal airway models (capturing low, medium and high posterior spray deposition), were within one standard deviation of available in vivo PK data for a representative corticosteroid drug (triamcinolone acetonide). The relative differences in mean C max between predictions and in vivo data for low dose (110 µg) and high dose (220 µg) cases were 27.8% and 10.1%, respectively. The models confirmed the dose-dependent dissolution-limited behavior of nasally delivered triamcinolone acetonide observed in available in vivo data. The total uptake from the nasal cavity decreased from 68.3% to 51.3% for the medium deposition model as dose was increased from 110 to 220 µg due to concentration-limited dissolution. The modeling framework is envisioned to facilitate faster development and testing of generic locally acting suspension nasal spray products due to its ability to predict the impact of differences in spray characteristics and patient use parameters on systemic PK., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: With the coming era of digital medicine and healthcare technology, mathematical modeling of tumors has become a key step to optimize and realize precision radiation therapy. The purpose of this study was to develop a mathematical model for simulating the change of head and neck (HN) tumor volume during radiation therapy., Methods and Materials: A formula was developed to describe the dynamic change of oxygenated compartment within a tumor, which was combined with the lethal lesions model to describe various cell processes during radiation therapy, including potentially lethal lesion repair and misrepair, cell proliferation/loss, and tumor reoxygenation. Parameter sensitivity analysis was performed to evaluate the impacts of lesion- and repair-related biological factors on radiation therapy outcomes., Results: We tested our model on 14 available patients with HN cancer and compared the performance with 3 other models. The mean error of our model for the 12 good fit cases was 12.2%, which is considerably smaller than that of the linear quadratic model (19.7%), the generalized linear quadratic model (19.1%), and a 4-level cell population model (16.6%). Correlation analysis results revealed that for small tumors, there was a positive correlation (correlation coefficient r=0.9416) between hypoxic fraction (hf) and tumor volume, whereas the correlation became negative and not significant (r=-0.4365) for large tumors. It is demonstrated from sensitivity analysis that the production rate of lethal lesions (η l ) has a far greater impact on tumor volume than other parameters. The hf had an insignificant impact on tumor volume but had a notable influence on the volume of surviving cells. The final volume of surviving cells athf=0.5 was almost 8 ×10 2 times that of hf=0.01. The potentially lethal lesion-related parameters (the production rate of potentially lethal lessions per unit dose η pl , the rate of correct repair per unit time ε pl , and the rate of binary misrepair per unit time ε 2pl ) had rather small impacts (<1%) on both tumor volume and the volume of surviving cells, which indicates that the repaired and misrepaired sublethal cells only take up a small portion of the total cancer cell population., Conclusions: A population-based tumor-volume model for HN cancer during radiation therapy with a dynamic oxygenated compartment was developed in this study. Comprehensively considering the damage process of tumor cells caused by radiation therapy, the accurate prediction of the volume change of HN tumors during treatment was revealed. Meanwhile, various cell activities and their principles in the process of antitumor treatment were reflected, which has positive clinical reference significance for radiobiology., (Copyright © 2024 Elsevier Inc. All rights reserved.)

This paper employed a physiologically based pharmacokinetic model (PBPK) to investigate the transformations of folic acid and its metabolites in vivo. Additionally, an ultra-performance liquid chromatography (UPLC) method was developed to accurately measure the body's retention rate and conversion rate of folic acid, tetrahydrofolate, and 5-methyltetrahydrofolate. Furthermore, the bioavailability of folic acid in the body was assessed by combining this method with an evaluation technique for animal models. The study found that the gastric metabolism time was 2 h, while the small intestinal metabolism duration was 4 h. The maximum conversion rate was observed in plasma and liver after 6 h, and in the brain after 8 h. This serves as a framework for creating a model to assess the bioavailability of folic acid in living organisms, to enhance the safety and efficacy of folic acid intake., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Lichens have great potential as food, functional food additives or flavourings. The presence of specific substances with multiple biological activities is one of the characteristics of lichens. However, research on lichens as a food source or functional food additive is limited. The present study simulated, for the first time, the potential bioaccessibility of active compounds from 6 lichen species in simulated gastric and intestinal conditions. An in vitro digestion showed that the lichen substances had different bioaccessibility and stability during digestion. It was found that the application of some metabolic modulators significantly altered the accumulation of metabolites in most species. In addition, the study demonstrated the antimicrobial activity of the tested extracts as well as of 14 isolated lichen metabolites. These multi-directional studies demonstrate the potential of lichens in terms of their use as antimicrobial functional food additives., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

D-amino acids can affect the action of digestive enzymes, hence the protein digestion. In this work the behaviour of the main stomach and gut digestive enzymes (pepsin, trypsin, and chymotrypsin) in the presence of D-amino acids in the protein chain was monitored over time using a model peptide, Ac-LDAQSAPLRVYVE-NH 2 (belonging to β-lactoglobulin, position 48-60), where L-amino acids were systematically substituted by D-amino acids. The results showed several changes in the behaviour of digestive enzymes, not only when the D-amino acids are inserted at the specific cleavage sites (after Val-57), but in some cases also when in distant positions. The effect seemed more pronounced in the case of pepsin rather than the gut enzymes, possibly indicating a better resilience of the upper gut phase of digestion to racemization. These results demonstrated that racemization could impair nutritional value by slowing down digestibility and has different effects according to the enzyme/amino acids involved., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Nothing declared., (Copyright © 2024. Published by Elsevier Ltd.)

Musculoskeletal simulations are a useful tool for improving our understanding of the human body. However, the physiological validity of predicted kinematics and forces is highly dependent upon the correct calibration of muscle parameters and the structural integrity of a model's internal skeletal structure. In this study, we show how ill-tuned muscle parameters and unphysiological deformations of a model's skeletal structure can be detected by using muscle elements as sensors with which modelling and parameterization inconsistencies can be identified through muscle and tendon strain injury assessment. To illustrate our approach, two modelling issues were recreated. First, a model repositioning simulation using the THUMS AM50 occupant model version 5.03 was performed to show how internal model deformations can occur during a change of model posture. Second, the muscle material parameters of the OpenSim gait2354 model were varied to illustrate how unphysiological muscle forces can arise if material parameters are inadequately calibrated. The simulations were assessed for muscle and tendon strain injuries using previously published injury criteria and a newly developed method to determine tendon strain injury threshold values. Muscle strain injuries in the left and right musculus pronator teres were detected during the model repositioning. This straining was caused by an unphysiologically large gap (12.92 mm) that had formed in the elbow joint. Similarly, muscle and tendon strain injuries were detected in the modified right-hand musculus gastrocnemius medialis of the gait2354 model where an unphysiological reduction of the tendon slack length introduced large pre-strain of the muscle-tendon unit. The results of this work show that the proposed method can quantify the internal distortion behaviour of musculoskeletal human body models and the plausibility of Hill-type muscle parameter choice via strain injury assessment. Furthermore, we highlight possible actions to avoid the presented issues and inconsistencies in literature data concerning the material characteristics of human tendons., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Nölle et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study presents a stochastic model of seed dispersal based on a branching random walk (BRW) framework, incorporating both homogeneous and non-homogeneous Poisson point processes (PPP). Building on the model introduced by Coletti et al. (2023), we examine the effects of habitat reduction on seed dispersal dynamics. We analyze the phase transition behavior of the BRW model under varying conditions of habitat fragmentation, focusing on how these conditions influence the critical dispersal rate. Specifically, we study a BRW on the real line with a non-homogeneous PPP driven by a log-normal density, constrained between spatial barriers. Our simulations localize the critical dispersal rate with respect to barrier positions and compare this dependence between homogeneous and non-homogeneous models., Competing Interests: Declarations Competing of Interest The author declares no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

This study concentrated on determining the levels of uranium present in drinking water samples obtained from various locations throughout the Shahdol district in Madhya Pradesh, India. In this assessment a LED fluorimeter Quantalase (LF-2a) was utilized. Uranium, being a radioactive substance, can be hazardous to health when consumed in significant quantities over extended durations. The study found that the average uranium concentration was 167.91 µg/L. 82% of samples exceeded recommended limits, emphasizing the essential aspect of this study. The study utilizes the age-specific biokinetic model developed by the International Commission on Radiological Protection to examine uranium distribution across various organs. Using dosimetric model, the study provides a comprehensive health risk analysis by assessing the chemical toxicity and the radiation dosages received by particular organs. Longitudinal studies on uranium distribution across different organs and tissues showed that the kidneys, liver, non-exchangeable bone volume, and soft tissues are the primary locations where uranium accumulates., Competing Interests: Declarations Conflict of interest The authors declare no competing interests. The authors declare that none of the research presented in this publication has been influenced by any identifiable conflicting financial interests or personal relationships., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Chronic spontaneous urticaria (CSU) is a typical example of an intractable skin disease with no clear cause and significantly affects daily life of patients. Because CSU is a human-specific disease and lacks proper animal model, there are many questions regarding its pathophysiological dynamics. On the other hand, most clinical symptoms of urticaria are notable as dynamic appearance of skin eruptions called wheals. In this study, we explored dynamics of wheal by dividing it into three phases using a mathematical model: onset, development, and disappearance. Our results suggest that CSU onset is critically associated with endovascular dynamics triggered by basophils positive feedback. In contrast, the development phase is regulated by mast cell dynamics via vascular gap formation. We also suggest a disappearance mechanism of skin eruptions in CSU through an extension of the mathematical model using qualitative and quantitative comparisons of wheal expansion data of real patients with urticaria. Our results suggest that the wheal dynamics of the three phases and CSU development are hierarchically related to endovascular and extravascular pathophysiological networks., Competing Interests: Declarations Code availability Numerical code is made available online on GitHub (https://github.com/seirin-lee/urticaria-code) and all other data are available from the corresponding author (SSL) on reasonable request. Conflict of interest The authors declare no Conflict of interest., (© 2024. The Author(s).)

Bariatric surgery introduces significant changes in the gastrointestinal tract, which may affect oral drug absorption/bioavailability. Here we investigate the phosphodiesterase-5 inhibitor (PDE5i) tadalafil for potentially impaired post-bariatric solubility/dissolution and absorption. Solubility was studied in vitro in different pHs, and ex vivo in gastric content aspirated from patients pre/post-surgery. Dissolution was studied in conditions mimicking pre/post-surgery stomach. Finally, the experimental data were used in physiologically-based pharmacokinetic (PBPK) model (GastroPlus ® ) to simulate pre- vs. post-surgery tadalafil PK. Tadalafil demonstrated low and pH-independent solubility, both in vitro and ex vivo. Tadalafil release from all drug products and under all gastric conditions was incomplete, with particularly poor dissolution (2%) of the highest dose under post-bariatric conditions. PBPK simulations revealed altered tadalafil PK after gastric bypass-but not after sleeve gastrectomy-compared to unoperated individuals, with 44-48% decreased C max , 35-56% decreased AUC and 44% shorter T max . This mechanistic analysis suggests that tadalafil may be as effective after sleeve gastrectomy as before the procedure; meanwhile, results after gastric bypass raise concerns regarding the bioperformance of the drug. In addition, the drug's duration of action may be much shorter after gastric bypass. Thus, the effectiveness of tadalafil, widely regarded as the 'weekend pill', may be shorter than expected among gastric bypass patients., Competing Interests: Declarations Conflict of Interest None., (© 2024. The Author(s).)

Cell fate decision is crucial in biological development and plays fundamental roles in normal development and functional maintenance of organisms. By identifying key regulatory interactions and molecules involved in these fate decisions, we can shed light on the intricate mechanisms underlying the cell fates. This understanding ultimately reveals the fundamental principles driving biological development and the origins of various diseases. In this study, we present an overarching framework which integrates pseudo-trajectory inference and differential analysis to determine critical regulatory interactions and molecules during cell fate transitions. To demonstrate feasibility and reliability of the approach, we employ the differentiation networks of hepatobiliary system and embryonic stem cells as representative model systems. By applying pseudo-trajectory inference to biological data, we aim to identify critical regulatory interactions and molecules during the cell fate transition processes. Consistent with experimental observations, the approach can allow us to infer dynamical cell fate decision processes and gain insights into the underlying mechanisms which govern cell state decisions., Competing Interests: Declarations Ethical approval This article does not contain any studies with human participants or animals performed by the authors. Conflict of interest The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Fluctuations are inherent to biological systems, arising from the stochastic nature of molecular interactions, and influence various aspects of system behavior, stability, and robustness. These fluctuations can be categorized as intrinsic, stemming from the system's inherent structure and dynamics, and extrinsic, arising from external factors, such as temperature variations. Understanding the interplay between these fluctuations is crucial for obtaining a comprehensive understanding of biological phenomena. However, studying these effects poses significant computational challenges. In this study, we used an underexplored methodology to analyze the effect of extrinsic fluctuations in stochastic systems using ordinary differential equations instead of solving the master equation with stochastic parameters. By incorporating temperature fluctuations into reaction rates, we explored the impact of extrinsic factors on system dynamics. We constructed a master equation and calculated the equations for the dynamics of the first two moments, offering computational efficiency compared with directly solving the chemical master equation. We applied this approach to analyze a biological oscillator, focusing on the p53 model and its response to temperature-induced extrinsic fluctuations. Our findings underscore the impact of extrinsic fluctuations on the nature of oscillations in biological systems, with alterations in oscillatory behavior depending on the characteristics of extrinsic fluctuations. We observed an increased oscillation amplitude and frequency of the p53 concentration cycle. This study provides valuable insights into the effects of extrinsic fluctuations on biological oscillations and highlights the importance of considering them in more complex systems to prevent unwanted scenarios related to health issues., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Recently, vision-based unmanned aerial vehicle (UAV) swarming has emerged as a promising alternative that can overcome the adaptability and scalability limitations of distributed and communication-based UAV swarm systems. While most vision-based control algorithms are predicated on the detection of neighboring objects, they often overlook key perceptual factors such as visual occlusion and the impact of visual sensor limitations on swarm performance. To address the interaction problem of neighbor selection at the core of self-organizing UAV swarm control, a perceptually realistic finite perception visual (FPV) neighbor selection model is proposed, which is based on the lateral visual characteristics of birds, incorporates adjustable lateral visual field widths and orientations, and is able to ignore occluded agents. Based on the FPV model, a neighbor selection method based on the acute angle test (AAT) is proposed, which overcomes the limitation that the traditional neighbor selection mechanism can only interact with the nearest neighboring agents. A large number of Monte Carlo simulation comparison experiments show that the proposed FPV+AAT neighbor selection mechanism can reduce the redundant communication burden between large-scale self-organized UAV swarms, and outperforms the traditional neighbor selection method in terms of order, safety, union, connectivity, and noise resistance., (© 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Over the last two decades, robotics engineering has witnessed rapid growth in the exploration and development of soft robots. Soft robots are made of deformable materials with mechanical properties or other features that resemble biological structures. These robots are often inspired by living organisms or mimic their locomotion, such as crawling and swimming. This paper aims to assist researchers in robotics and engineering to design soft robots incorporating or inspired by biological systems with a more informed perspective on biological models and functions. We address the characteristics of fluidic soft robots inspired by or mimicking biological examples, establish a method to categorize soft robots from a functional biological perspective, and provide a wider range of organisms to inspire the development of soft robotics. The actuation mechanisms in bioinspired and biomimetic soft robotics would benefit from a clearer understanding of the underlying principles, organization, and function of biological structures., (Creative Commons Attribution license.)

In this research work, the authors have developed a mathematical model to examine the interaction between dystrophin protein and tumor. The authors formulated a system of ordinary differential equations to describe the dynamics of the dystrophin-tumor interaction system. Jacobian matrix and Routh-Hurwitz stability techniques were used to determine equilibrium points, perform stability and bifurcation analysis, and establish the conditions required for the stability of the proposed model. Numerical simulations are performed using Euler's method to investigate the temporal evolution of the proposed model under different parameter values, such as tumor growth rate and feedback strength of dystrophin protein. The numerical results are presented in tables, and corresponding to each table, a graphical analysis is done. The graphical analysis includes creating phase portraits to visually represent stability regions around the equilibrium points, bifurcation diagrams to identify critical points, and time series analysis to highlight the behavior of the proposed model. The authors explore how variations in dystrophin expression impact tumor progression, identifying potential therapeutic implications of maintaining higher dystrophin levels. This comprehensive analysis enhances our understanding of the dystrophin-tumor interaction, providing a basis for further experimental validation and potential therapeutic strategies., Competing Interests: Declarations Competing interests The authors declare no competing interests. Consent to participate Each author has approved of and agreed to submit the article., (© 2024. The Author(s).)

Background: The ventilatory physiopathology of patients with interstitial lung disease (ILD) remains poorly understood. We aimed to personalize a mechanical simulator to model healthy and ILD profiles ventilation, and to evaluate the effect of spontaneous breathing on respiratory mechanics at rest and during exercise., Methods: In a 2-compartment lung simulator (ASL 5000 ® ), we modeled 1 healthy and 3 ILD profiles, at rest and during exercise, based on physiological data from literature and patients. Measurements were: tidal volume, end-expiratory lung volume, driving pressure, transpulmonary driving pressure, dynamic alveolar strain, mechanical power, and time lag of inspiratory flow between compartments 1 and 2., Results: Healthy and ILD models were validated: maximum differences between real and simulated tidal volume were 5% (96 ml) and 6% (54 ml) at rest and during exercise respectively, considered clinically negligible. When we simulated lung inhomogeneity (compliance in compartment 1 > compartment 2), tidal volume, end-expiratory lung volume, driving pressure and mechanical power increased in compartment 1 and decreased in compartment 2. Driving transpulmonary pressure and dynamic alveolar strain increased in compartment 2 and decreased in compartment 1. Time lag of inspiratory flow between compartments 1 and 2 was positively correlated with a difference of compliance between compartments (r = 0.98, CI95% (0.9106; 0.9962), p < 0.0001)., Conclusion: In this bench study, we personalized a mechanical simulator thatmodels the lung inhomogeneity and spontaneous breathing of healthy subjects and ILD patients at rest and during exercise. Our results suggest that lung inhomogeneity could increase lung vulnerability to volo-atelec-trauma mechanisms in ILD. Further physiological studies are needed to evaluate the impact of this vulnerability on acute or chronic ILD worsening., Competing Interests: Declarations Ethics approval and consent to participate All included patients consented that their data were used. Consent for publication Not available. Competing interests The authors declare no competing interests.on research purpose. This study was approved by the Rouen university hospital.Ethics Committee (n° E2022-64). Informed consent was obtained from all the patients in this study., (© 2024. The Author(s).)

Fuzzy logic presents a promising approach for Species Distribution Modelling by generating a value that can be used for comparative purposes termed 'environmental favourability'. In contrast to 'presence probability', 'environmental favourability' remains robust regardless of species prevalence. This characteristic facilitates effective comparisons across species with varying levels of prevalence. In this study, presence probability was predicted using three commonly used Species Distribution Models: Generalised Linear Model, Generalised Additive Modelling, and Boosted Regression Trees for two beetle species, Euwallacea fornicatus and Euwallacea perbrevis in Australia. Fuzzy logic was then employed to derive environmental favourability values based on these models. Additionally, Maxent modelling was included to compare prediction outputs and facilitate a comprehensive analysis. Model performance was evaluated using standard metrics (Area under the receiver operating characteristic curve, True statistical skill, Correct classification rate), as well as Hosmer-Lemeshow test. The research explored fuzzy similarity, fuzzy intersection and potential biotic interaction of these closely related borers, and revealed a favourable distribution pattern for Euwallacea fornicatus across Australia. This study supports the efficacy of fuzzy logic in Species Distribution Modelling and highlights the value of environmental favourability function in enhancing the comparative analysis of the geographical relationship across species. This approach offers a more nuanced perspective on Species Distribution Modelling., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

The radiation adaptive response (or radioadaptation) effect is a biophysical and radiobiological phenomenon responsible for, e.g. the enhancement of repair processes, cell cycle and apoptosis regulation or enhancement of antioxidant production in cells/organisms irradiated by low doses and low dose-rates of ionising radiation. This phenomenon, however, is not always present, which creates many problems both for experimenters and theoreticians. Here we propose a comprehensive and complete theoretical model of radioadaptation grounded in mathematical concept of dose- and time-related probability function of the adaptive response appearance. This can be used in the context of two special cases of the adaptive response: the Raper-Yonezawa (priming dose) effect or constant low-dose-rate irradiation (e.g. for high natural background). This complete theoretical approach is supported by Monte Carlo simulations and real-experimental data used for model calibration and validation., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

This study developed a more universal tool for estimating the in vivo distribution of intake radionuclides. The biokinetic models and transfer rates for intake radionuclides were cited from the publications of the International Commission on Radiological Protection (ICRP), and the models were transformed into a series of linear differential equations and numerically solved using the Scipy algorithm in Python. The user interfaces for model selection, data input and in vivo distribution calculations were designed using PyQt5. The calculation results of the new tool are completely consistent with those of the data viewer released by the ICRP and are also very similar to other reported values. The new tool allows users to select and change the biokinetic models and transfer rates and display the in vivo distribution of radionuclides in an image format. It is much more user friendly., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Eukaryotic cells sense and follow electric fields during wound healing and embryogenesis - this is called galvanotaxis. Galvanotaxis is believed to be driven by the redistribution of "sensors" - potentially transmembrane proteins or other molecules - through electrophoresis and electroosmosis. Here, we update our previous model of the limits of galvanotaxis due to the stochasticity of sensor movements to account for cell shape and orientation. Computing the Fisher information shows that, in principle, cells have more information about the electric field direction when their long axis is parallel to the field. However, for weak fields, maximum-likelihood estimators may have lower variability when the cell's long axis is perpendicular to the field. In an alternate possibility, we find that if cells instead estimate the field direction by taking the average of all the sensor locations as its directional cue ("vector sum"), this introduces a bias towards the short axis, an effect not present for isotropic cells. We also explore the possibility that cell elongation arises downstream of sensor redistribution. We argue that if sensors migrate to the cell's rear, the cell will tend to expand perpendicular the field - as is more commonly observed - but if sensors migrate to the front, the cell will tend to elongate parallel to the field.

In recent years, the micro air vehicle (MAV) oscillations caused by thrust imbalances have received more attention. This paper proposes a dual-wing thrust balance model (DTBM) that can solve the above problem by iterating the modified rotation angle formula. The core control parameter of the DTBM model is the au angle, which refers to the angle between the wing surface and the stroke plane at the mid-stroke position during the upstroke. For each degree change in the au angle, the range of variation in the dimensionless average thrust coefficient is between 0.0225-0.0268. A thrust coefficient of 0.0225 causes the dragonfly to move forward by 9.037 cm in one second, which is equivalent to 1.29 times its body length. By using DTBM, the average thrust coefficient can be reduced to below 0.001 in just a few iterations. No matter how complex the motion pattern is, the DTBM can achieve thrust balance within 0.278 s. Through our research, when selecting the deviation angle motion of real dragonflies, the dual-wing au angles exhibit a highly linear correlation with wing spacing, called linear motion. In contrast, the nonlinear variation of the au angle appears in the hindwing of the no-deviation motion and the forewing of the elliptical deviation motion. All of the nonlinear changes are referred to as nonlinear motion. Nonlinear variation of the au angle arises from larger disturbances of the lateral force during the upstroke. The stronger lateral force is closely related to the flapping trajectory. When the flapping trajectory causes the dual-wing to closely approach each other in the mid-stroke, a continuous positive pressure zone forms between the dual-wing. The collision of the leading-edge vortex and the shedding of the trailing-edge vortex is the special flow field structure in the nonlinear motion. Guided by the DTBM, future designs of MAVs will be able to better achieve thrust balance during hovering flight, requiring only the embedding of the iteration algorithm and prediction function of the DTBM in the internal chip., (© 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Microbial processes operate at the microscale, which is not resolved by existing ecosystem models. Here, we present a novel model that simulates a 1 mL three-dimensional cube using a hybrid Lagrangian-Eulerian approach, at ecologically relevant timescales. The model simulates individual microbes, including three phytoplankton size classes with healthy, senescent, and dead lifecycle stages; copiotrophic and oligotrophic heterotrophic bacteria; and dissolved organic matter at 50 µm resolution. Diffusion, shear, sedimentation, chemotaxis, and attachment processes are explicitly resolved. The emerging quantitative representation of the ecosystem shows that (1) copiotrophs grow mostly attached to eukaryotic phytoplankters and get almost all of their carbon from them vs. oligotrophs that grow on exudates and lysates of cyanobacteria; (2) contrasting diel patterns in substrate appearance in the phycosphere vs. ambient water and growth of particle-associated copiotrophs vs. free-living oligotrophs; (3) attached bacteria reduce carbon flux from the phycosphere, lowering chemotactic efficiency toward eukaryotes below that toward cyanobacteria; (4) shear reduces chemotactic efficiency and fitness of the copiotroph; and (5) the main benefit of chemotaxis is to locate attachment partners. These patterns are consistent with available observations. Our study provides insights into the microscale ecology of marine bacteria, and the open-source code is a tool for further research in this area.IMPORTANCEA large amount of global CO 2 fixation is performed by marine phytoplankton, and a substantial fraction of that is released as dissolved organic carbon and further processed by heterotrophic bacteria. The interaction between phytoplankton and bacteria, i.e., the carbon flux between them, is therefore an important process in the global carbon and climate system. Some bacteria have developed specialized behavioral traits, like swimming and attachment, to increase their carbon acquisition. These interactions occur at the micrometer scale, for example, the immediate vicinity of phytoplankters (the phycosphere), but existing biogeochemical models typically only simulate down to the 1 meter vertical or ~100 kilometer horizontal scale. We present a new microscale model and use it to predict fluxes and other features in the surface ocean. The model makes important predictions about the fluxes between various types of phytoplankton and bacteria and the role of behavioral traits, and it provides a basis and tool for further research in this area., Competing Interests: The authors declare no conflict of interest.