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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.

This study investigated the effects of adding 4-20 % Tartary buckwheat protein (TBP, with a purity of 93.35 %) on the structural, thermal, and digestive properties of Tartary buckwheat starch (TBS) by high moisture (60 %) extrusion. The added TBP embedded and enwrapped the starch matrix, which formed protein-starch complexes. After adding 4 %-20 % TBP, the shear degradation of AP decreased. Conversely, the shear degradation of AM chains increased. The addition of TBP promoted the retrogradation of starch in extrudates, enhancing their short- and long-range ordered structures. Compared with extruded TBS, extrudates contained TBP showed a reduction of gelatinization enthalpy, a high content of resistant starch, and a lower starch digestibility. These findings provided an insight into the protein-starch interactions under high moisture extrusion, which would promote the advancement of starch-based foods with high TBP content., 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.)

Lactarius hatsudake Tanaka is a popular edible mushroom known for its delicious flavor and health benefits. Its polysaccharides (LHP) exhibit significant bioactivity, but their application is limited due to uncertainties in digestion. This study used in vitro simulated models to explore the dynamic changes of LHP during the digestive and fermentation process and validated them through mouse models. Results revealed that LHP cannot be digested by the simulated digestive system, but is primarily degraded into fatty acids by gut microbes, accompanied by reductions in molecular weight, carbohydrate content, and pH. Additionally, LHP promotes the proliferation of beneficial bacteria (Faecalibacterium, Bifidobacterium, Lactobacillus, etc.), while inhibiting harmful bacteria (Escherichia and Shigella). Metabolite analysis in serum indicated that LHP can regulate amino acid and lipid metabolism, enhancing overall health. These findings provide a theoretical foundation for developing LHP as a potential prebiotic, highlighting its considerable promise for disease prevention through improved intestinal health., 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. Published by Elsevier Ltd.)

Phenolic compounds are popular in screening novel hypoglycemic agents, but the impact of oxidative degradation on the determination of α-glucosidase inhibitory activity and bioavailability is unclear. Here we showed 12 phenolic compounds structure-dependently degraded during standard simulated digestion, while in physiological hypoxia their retention rates were all over 87.89 %. This enhancement of digestive stability resulted in the biggest drop of 31.72 % in IC 50 against α-glucosidase and a significant increase in bioavailability. Enzyme kinetic and multi-spectroscopic analysis confirmed oxygen weakened the affinity of compounds to α-glucosidase, but the mechanisms were not changed. Moreover, a two-chamber culture system was designed to meet conflicting demands for oxygen between epithelium and cavity, and better α-glucosidase inhibitory activities (51.61 % maximum reduction in glucose production) and absorption rates (up to 1.10 % from undetectable) were obtained than those of uncontrolled oxygen. Hence, the oxygen level should be monitored to assess the activities of phenolic compounds in vitro., 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. Published by Elsevier Ltd.)

Latency is the major obstacle in eradicating HIV from infected patients. Recent studies have shown that BET protein inhibitors can successfully reverse this latency by inhibiting the binding of BET proteins with positive cellular cofactor P-TEFb. Thus, availability of P-TEFbs plays an important role in HIV transactivation. However, in cells of our immune system which are primarily infected by the virus, number of P-TEFb is very low and is considered as one of the factors in inducing viral latency. At such small numbers of P-TEFb, the internal fluctuations can have a decisive role in the cell fate decision and fluctuations in the P-TEFb levels can switch the HIV to either a state of active replication or to a state of latency. Aimed at quantitative understanding of how BET inhibitors affect the statistics of P-TEFb level, we develop a coarse-grained stochastic model. However, the interaction between P-TEFb and BET proteins makes the problem analytically challenging. To address the nonlinearity arising due to such interactions, we use Langevin equation based approach to study the statistics of steady-state P-TEFb levels and explore the variations of some of the important quantities such as noise and fano factor associated with P-TEFb as well as correlations between BET and P-TEFb levels with model parameters. The analytic results derived exhibit that these quantities, in general, show non-monotonic response with respect to the parameters of the model. The results derived will be helpful in estimating the model parameters as well in identifying the pathways that can be intervened for effective HIV transactivation., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Coral reefs are critical ecosystems, fostering biodiversity and sustaining the livelihoods of millions globally. Nonetheless, they confront escalating threats, with infectious diseases emerging as primary catalysts for extensive damage, surpassing the impacts of other human-induced stressors. Disease transmission via biotic factors, particularly during fish predation, is a crucial yet often overlooked pathway. While their feeding can spread infectious diseases through spores, it also controls the growth of macroalgae, a major competitor for space on the reef. Given this dual effect, the precise impact of fish on coral disease remains ambiguous and requires additional investigation. In this study, we addressed this gap for the first time by employing a mathematical model. Our analyses unveil intricate interactions between fish predation and coral health, revealing potential benefits and drawbacks for coral reef ecosystems. Coral survival hinges on a delicate balance of fish predation, with extremes (both low and high) offering some protection against disease outbreaks compared to moderate predation, which can cause sudden die-offs. More specifically, as fish predation intensifies, the ecosystem undergoes a tipping point, transitioning from a disease-dominated state to a healthier one. Moreover, the interplay between transmission rate and virulence in coral populations is significantly shaped by fish predation rates. Specifically, the threshold ratio of transmission to virulence, signalling a regime shift from a healthy to a disease-dominated state, exhibits a linear increase with fish predation rate. Overall, our findings emphasize the importance of considering biotic interactions in coral disease ecology and offer insights essential for effective reef conservation strategies., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The dynamics unfolding during predator-prey interactions encapsulate a critical aspect of the natural world, dictating the survival and evolutionary trajectories of animal species. Underlying these complex dynamics, sensory-motor control strategies orchestrate the locomotory gates essential to guarantee survival or predation. While analytical models have been instrumental in understanding predator-prey interactions, dissecting sensory-motor control strategies remains a great challenge due to the adaptive and stochastic nature of animal behavior and the strong coupling of predator-prey interactions. Here, we propose a data-driven mathematical model describing the adaptive learning response of a dolphin while hunting a fish. Grounded in feedback control systems and stochastic differential equations theory, our model embraces the inherent unpredictability of animal behavior and sheds light on the adaptive learning strategies required to outmaneuver agile prey. The efficacy of our model was validated through numerical experiments mirroring crucial statistical properties of locomotor activity observed in empirical data. Finally, we explored the role of stochasticity in predator-prey dynamics. Interestingly, our findings indicate that varying noise levels can selectively favor either fish survival or dolphin hunting success., 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.)

An individual-based stochastic model was developed to simulate the spread of an infectious disease in an SEIR-type system on all possible contact-networks of size between six and nine nodes. We assessed systematically the impact of the change in the population contact structure on four important epidemiological quantities: i) the epidemic duration, ii) the maximum number of infected individuals at a time point during the epidemic, iii) the time at which the maximum number of infected individuals is reached, and iv) the total number of individuals that have been infected during the epidemic. We considered the potential relationship of these quantities as the network changes and identified the networks that maximise and minimise each of these in the case of an epidemic outbreak. Chain-like networks minimise the peak and final epidemic size, but the disease spread is slow on such contact structures which leads to the maximisation of the epidemic duration. Star-like networks maximise the time to the peak whereas highly connected networks lead to faster disease transmission, and higher peak and final epidemic size. While the pairwise relationship of most of the quantities becomes almost linear, or inverse linear, as the network connectivity increases and approaches the complete network, the relationships are non-linear towards networks of low connectivity. In particular, the pairwise relationship between the final epidemic size and other quantities is changed in a 'bow-shaped' manner. There is a strong inverse linear relationship between epidemic duration and peak epidemic size with increasing network connectivity. The (inverse) linear relationships between quantities are more pronounced in cases of high disease transmissibility. All the values of the quantities change in a non-linear way with the increase of network connectivity and are characterised by high variability between networks of the same degree. The variability decreases as network connectivity increases., 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.)

This study demonstrates the development and application of an ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) method for the rapid and sensitive identification of intact bovine milk proteins following simulated gastrointestinal infant digestion. The new method enables the differentiation between partially hydrolysed/modified and fully intact proteins. In the raw milk, intact α-lactalbumin was visible on SDS - PAGE until the end of the gastrointestinal digestion, while it was not detected with UHPLC-HRMS. Analysis of both raw and heated milk samples revealed that the method is applicable to various milk types. Interestingly, heated milk showed additional signals in the mass spectrum, indicating non-enzymatic post-translational modifications. The relative abundance of these proteoforms could be followed along digestion. These findings highlight the versatility and sensitivity of UHPLC-HRMS in elucidating protein structures and modifications, providing valuable insights into how simulated digestion affects milk protein composition., 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.)

Bovine whey contains bioactive proteins that could benefit consumer health, but their intact bioactivity depends on their ability to survive the digestive process and remain intact to their sites of action. Our study assessed whey protein degradation in the adult human jejunum after whey protein isolate ingestion and during static in vitro gastric and intestinal digestions, using LC-MS/MS-based proteomics and SDS-PAGE. We found that 53 % of the protein counts identified in the gastric digesta, including β-lactoglobulin and lactoferrin were stable under simulated gastric conditions. However, most proteins were degraded during both in vitro and in vivo intestinal digestion. The intact protein survival profiles were closely aligned between in vitro and in vivo digestion samples. Understanding the survival of specific whey proteins during digestion will help determine their biological relevancy in their intact forms within the gastrointestinal tract and may inspire strategies to enhance their stability for specific functions., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: David Dallas reports financial support was provided by BUILD Dairy. If there are other authors, they 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.)

Malnutrition is a global issue linked to energy or nutrient imbalances, often resulting in deficiencies or overweight. Dairy products, rich in macronutrients and micronutrients, are a potential solution. However, processing, storage, and digestion can lead to nutrient loss. To enhance nutritional value, functional ingredients like microencapsulated compounds are used. This study focused on assessing the bioaccessibility of microencapsulated ingredients in cottage cheese, their impact on sensory attributes, and shelf-life. Two microencapsulated ingredients were studied: high oleic palm oil (HOPO), encapsulated using spray drying (SD) and a refractive window (RW) drying technique. The bioaccessibility of these ingredients was evaluated using the INFOGEST in-vitro digestion model. Results showed that HOPO encapsulated via SD in cottage cheese (CSD) preserved oleic and linoleic acids best, and via RW in cottage cheese (CRW) preserve vitamins in 63 % and antioxidants in 96 %. This highlights the effectiveness of microencapsulation techniques in enhancing dairy product functionality and a 72 % of fatty acids release suggesting potential strategies for combating malnutrition through fortified dairy products., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Maria Ximena Quintanilla Carvajal reports equipment, drugs, or supplies was provided by Fasalact. If there are other authors, they 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.)

Composition and structure of oleogels significantly influence their digestive behaviour, impacting triacylglycerol breakdown and the bioavailability of incorporated compounds. Texture profile analysis showed that sterol-based oleogels (STOs) exhibited 20 times higher hardness than beeswax-based oleogels (BWOs), which showed stronger cohesion due to elasticity sustained by adhesive forces. Tribological assessments revealed similar initial coefficients of friction (COF) for both oleogels. However, fluctuations were observed in BWOs and a gradual decrease in STOs over time, enhancing lubrication, while BWOs recorded higher adhesion. These findings provide insights into their distinct digestive behaviour, with both oleogels undergoing structural disintegration and STOs displaying a higher lipolysis degree. Non-cytotoxicity was confirmed under Caco-2 cells. β-carotene bioaccessibility was influenced by the oleogels' structural modification and values of 4.0 ± 0.7 % for STOs and 2.6 ± 1.1 % for BWOs were recorded. Results highlight the need to optimize formulations to improve bioactive's bioavailability, emphasizing the role of structured gels in modulating digestion dynamics., 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.)

Most studies have primarily focused on the effects of individual sources of pectin or polyphenols on starch digestibility. However, the interactions between pectin and polyphenols in digestive fluids may influence their inhibitory capacity against starch digestion by modulating α-amylase activity (αAA), a relationship that remains poorly understood. This study aims to clarify how pectin affects starch digestion when combined with mulberry fruit powder (MFP), mulberry polyphenol extract (MPE), and rutin (the main phenolic compound in MPE). Results showed that the combination of pectin and MFP initially inhibited αAA but later enhanced it. The combination of pectin and MPE consistently showed stronger inhibition of αAA than MPE alone throughout digestion; similar results were observed for the pectin-rutin combination, though the pectin-MPE pairing exhibited greater inhibition than the latter. Pectin's enhanced inhibitory effect on starch digestion may arise from its interactions with α-amylase, starch, and polyphenols through hydrophobic interactions, hydrogen bonding, and non-covalent forces., 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.)

Powdered samples of guava pulp and processing by-products (single fraction containing crushed seeds, peels, and residual pulp) are rich sources of polyphenols with antidiabetic, anti-obesity, cardioprotective, and anticancer potential. However, post-digestion retention of these bioactivities remains unclear. Therefore, these samples were subjected to in vitro digestion simulating oral, gastric, small intestine, and large intestine phases. Phenolic bioaccessibility was highest upon large intestinal digestion for pulp (62.04 %) and waste (22.49 %), while the lowest occurred in the oral and small intestinal phases. Digestion reduced their antiradical activity and ability to inhibit α-glucosidase (42.42-55.84 %) but enhanced pancreatic lipase inhibition (up to 82.82 %). Digested samples could better suppress oxidative damage to LDL-cholesterol and supercoiled DNA. Phenolic acids and ellagitannins were released after gastric digestion, while proanthocyanidins predominated in intestinal phases. Digestion altered the phenolic composition of samples, positively affecting several bioactivities. Further research should investigate metabolization of polyphenols across intestinal cells to establish bioavailability., 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. Published by Elsevier Ltd.)

Time-dependent birth-death sampling models have been used in numerous studies to infer past evolutionary dynamics in different biological contexts, for example,  speciation and extinction rates in macroevolutionary studies, or effective reproductive number in epidemiological studies. These models are branching processes where lineages can bifurcate, die, or be sampled with time-dependent birth, death, and sampling rates, generating phylogenetic trees. It has been shown that in some subclasses of such models, different sets of rates can result in the same distributions of reconstructed phylogenetic trees, and therefore, the rates become unidentifiable from the trees regardless of their size. Here, we show that widely used time-dependent fossilized birth-death (FBD) models are identifiable. This subclass of models makes more realistic assumptions about the fossilization process and certain infectious disease transmission processes than the unidentifiable birth-death sampling models. Namely, FBD models assume that sampled lineages stay in the process rather than being immediately removed upon sampling. The identifiability of the time-dependent FBD model justifies using statistical methods that implement this model to infer the underlying temporal diversification or epidemiological dynamics from phylogenetic trees or directly from molecular or other comparative data. We further show that the time-dependent FBD model with an extra parameter, the removal after sampling probability, is unidentifiable. This implies that in scenarios where we do not know how sampling affects lineages, we are unable to infer this extra parameter together with birth, death, and sampling rates solely from trees., (© The Author(s) 2024. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.)

Reconstructing the evolutionary history of different groups of organisms provides insight into how life originated and diversified on Earth. Phylogenetic trees are commonly used to estimate this evolutionary history. Within Bayesian phylogenetics a major step in estimating a tree is in choosing an appropriate model of character evolution. While the most common character data used is molecular sequence data, morphological data remains a vital source of information. The use of morphological characters allows for the incorporation fossil taxa, and despite advances in molecular sequencing, continues to play a significant role in neontology. Moreover, it is the main data source that allows us to unite extinct and extant taxa directly under the same generating process. We therefore require suitable models of morphological character evolution, the most common being the Mk Lewis model. While it is frequently used in both palaeobiology and neontology, it is not known whether the simple Mk substitution model, or any extensions to it, provide a sufficiently good description of the process of morphological evolution. In this study we investigate the impact of different morphological models on empirical tetrapod datasets. Specifically, we compare unpartitioned Mk models with those where characters are partitioned by the number of observed states, both with and without allowing for rate variation across sites and accounting for ascertainment bias. We show that the choice of substitution model has an impact on both topology and branch lengths, highlighting the importance of model choice. Through simulations, we validate the use of the model adequacy approach, posterior predictive simulations, for choosing an appropriate model. Additionally, we compare the performance of model adequacy with Bayesian model selection. We demonstrate how model selection approaches based on marginal likelihoods are not appropriate for choosing between models with partition schemes that vary in character state space (i.e., that vary in Q-matrix state size). Using posterior predictive simulations, we found that current variations of the Mk model are often performing adequately in capturing the evolutionary dynamics that generated our data. We do not find any preference for a particular model extension across multiple datasets, indicating that there is no "one size fits all" when it comes to morphological data and that careful consideration should be given to choosing models of discrete character evolution. By using suitable models of character evolution, we can increase our confidence in our phylogenetic estimates, which should in turn allow us to gain more accurate insights into the evolutionary history of both extinct and extant taxa., (© The Author(s) 2024. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Skeletal muscle is the main actuator of various families of vertebrates (mammals, fish, reptiles). It displays remarkable robustness to micro-damage, that supposedly originates both from its redundant hierarchical structure and its nervous command. A bioinspired mock-up was designed and manufactured mimicking sarcomeres (micro-scale) and its series and parallel structure from fibre to muscle. First, the mechanical performances namely the force-velocity curve of the intact muscle mock-up were measured and modelled. Then, mimicking micro-damage by making some myosin heads inoperative, the mechanical performances were again measured to determine the resilience of the actuator. The mock-up is shown to be resilient: in the event of 10% damage of the mock-up, the mechanical performance of the mock-up was around 80% of the intact one. In this multi degrees of freedom actuator with hierarchical structure, the resilience is shown to be almost linear with the damage level for uniformly distributed damage (both maximal force and velocity decrease). Differently when micro-damage are clustered on a fibre, this decreases the maximal force with little effect on velocity., (© 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Purpose: Presented is the development of a workflow for end-to-end (e2e) in silico modelling of percutaneous absorption under a range of test conditions, integrating multiple calculation and analysis steps for in-silico simulation of dermal absorption. The aim is to achieve a digital twin that can be used by non-modelling experts to simulate transdermal permeation., Methods: A KNIME-based toolbox is used to create the workflow for the E2E in-silico model. The workflow first combines physicochemical property informatics (ChemAxon), molecular dynamics (MD) modelling, and quantitative structure-property relations (QSPRs) to calculate the diffusion and partition properties of permeants in heterogeneous skin layers and complex formulation vehicles. These are then set as input parameters to physiologically based pharmacokinetics (PBPK) model to simulate percutaneous absorption under complex in vitro testing or in vivo exposure conditions set by the end user. Integrated into the PBPK model is the evaporation of volatile permeants and solvents for in vitro unoccluded conditions. The workflow generates a report of the results and records the tested formulation in a database., Results: The workflow has been tested against several sets of published in vitro permeation test (IVPT) results of percutaneous absorption involving different formulation vehicles. The model predictions of formulation and evaporation effects on percutaneous absorption agreed well with experimental data., Conclusions: By automating multiple calculation steps from permeant property, diffusion-partition skin layers and formulation vehicles, to PBPK modelling of dermal absorption, the workflow provides a user-friendly means for non-modelling experts to conduct in-silico simulations of transdermal absorption under various conditions. The workflow is robust to simulate the impact of complex formulation and exposure conditions including evaporation of volatile permeants and solvents on the delivery into the skin., 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. Published by Elsevier B.V.)

Biology has become a highly mathematical discipline in which probabilistic models play a central role. As a result, research in the biological sciences is now dependent on computational tools capable of carrying out complex analyses. These tools must be validated before they can be used, but what is understood as validation varies widely among methodological contributions. This may be a consequence of the still embryonic stage of the literature on statistical software validation for computational biology. Our manuscript aims to advance this literature. Here, we describe, illustrate, and introduce new good practices for assessing the correctness of a model implementation with an emphasis on Bayesian methods. We also introduce a suite of functionalities for automating validation protocols. It is our hope that the guidelines presented here help sharpen the focus of discussions on (as well as elevate) expected standards of statistical software for biology., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society of Systematic Biologists.)

Gastroesophageal reflux (GER) is common in babies and infants and is characterized by effortless regurgitation (with or without vomiting), which is a common symptom of other infant conditions, including cow's milk protein allergy (CMPA). Various milk formulations are commercially available to help manage GER and CMPA symptoms (extensively hydrolyzed [eHF], partially hydrolyzed [pHF], and amino-acid formulas [AAF]). We aimed to understand if an alginate product (Gaviscon Infant powder) worked as intended in the presence of different milk formulations. A previously evaluated artificial infant stomach model simulated an internal pressure-inducing reflux event (five reflux events performed at 5 min intervals). Suppression activity of Gaviscon Infant combined with eHF, pHF, and AAF was assessed by measuring the height that the refluxate event traveled up a tube mimicking the infant esophagus, alongside a benchmark unhydrolyzed formulation (uHF) with Gaviscon Infant and a negative control without Gaviscon Infant. Each experiment was repeated six times per formulation in a random order. Gaviscon Infant combined with each milk formulation produced a lower height of refluxate versus the negative control. When formulations combined with Gaviscon Infant were grouped by category (eHF, pHF, AAF), two or more products from each category showed a lower refluxate height than the benchmark (uHF). There was a significant difference in median refluxate height (p = 0.0011 in Wilcoxon rank sum test) when comparing Gaviscon Infant combined with eHF against Gaviscon Infant combined with pHF, AAF, or uHF (benchmark). Refluxate height did not change significantly between events one and five for each milk formulation combined with Gaviscon Infant. In an artificial infant stomach model, Gaviscon Infant combined with different milk formulations (uHF, eHF, pHF, AAF) produced a lower refluxate height compared with a negative control (uHF without Gaviscon Infant), suggesting that Gaviscon Infant suppresses reflux as intended when used with different milk formulations., Competing Interests: Declarations. Competing interests: Cathal Coyle and Fiona McLaughlin are employees of the study sponsor, Reckitt Healthcare Ltd, UK. Jeanine Fisher and Mark Atherton are employees of Technostics Limited. Ethics approval: This was an in vitro study using an in vitro model. There were no patients or human tissue involved in this study; therefore, the requirement for ethical approval and informed consent were not applicable. Consent to participate: Not applicable as an in vitro model was used and no human tissue or patients were involved., (© 2025. The Author(s).)

Plasma pharmacokinetic (PK) profiles often do not resemble the PK within the central nervous system (CNS) because of blood-brain-border (BBB) processes, like active efflux by P-glycoprotein (P-gp). Methods to predict CNS-PK are therefore desired. Here we investigate whether in vitro apparent permeability (P app ) and corrected efflux ratio (ER c ) extracted from literature can be repurposed as input for the LeiCNS-PK3.4 physiologically-based PK model to confidently predict rat brain extracellular fluid (ECF) PK of P-gp substrates. Literature values of in vitro Caco-2, LLC-PK1-mdr1a/MDR1, and MDCKII-MDR1 cell line transport data were used to calculate P-gp efflux clearance (CL Pgp ). Subsequently, CL Pgp was scaled from in vitro to in vivo through a relative expression factor (REF) based on P-gp expression differences. BrainECF PK was predicted well (within twofold error of the observed data) for 2 out of 4 P-gp substrates after short infusions and 3 out of 4 P-gp substrates after continuous infusions. Variability of in vitro parameters impacted both predicted rate and extent of drug distribution, reducing model applicability. Notably, use of transport data and in vitro P-gp expression obtained from a single study did not guarantee an accurate prediction; it often resulted in worse predictions than when using in vitro expression values reported by other labs. Overall, LeiCNS-PK3.4 shows promise in predicting brainECF PK, but this study highlights that the in vitro to in vivo translation is not yet robust. We conclude that more information is needed about context and drug dependency of in vitro data for robust brainECF PK predictions., Competing Interests: Declarations. Conflict of interest: M.H. is an employee of Daiichi-Sankyo Co., Ltd. The other authors declare no conflicts of interest., (© 2025. The Author(s).)

In general, global attractors are composed of isolated invariant sets and the connections between them. This structure can possibly be highly complex, encompassing attraction basins, repeller sets and invariant sets that, collectively, form a dynamical landscape. Lotka-Volterra systems have long been pivotal as preliminary models for dynamics in complex networks exhibiting pairwise interactions. In scenarios involving Volterra-Lyapunov (VL) stable matrices, the dynamics is simplified in such a way that the positive solutions converge to a single, globally asymptotically stable stationary point as time tends to infinity, thereby excluding the existence of periodic solutions. In this work, we conduct a systematic study on the emergence of heteroclinic cycles within Lotka-Volterra systems characterized by Volterra-Lyapunov stable matrices. Although VL stability of the matrix implies that ω -limit sets of solutions are always stationary points, our analysis of α -limit sets reveals finite sets of stationary points interconnected by global trajectories, forming structures referred to as heteroclinic cycles. Our findings indicate that even within the framework of VL stable matrices, such structures are more prevalent than previously thought in literature, driven by the interplay between the symmetric and antisymmetric components of the model matrix. This understanding also reinforces our comprehension of the classical three-dimensional May-Leonard model, which is known to be the unique case exhibiting heteroclinic cycle within the VL framework in dimension three, while also pointing to a surprising richness in the dynamics of these structures in higher dimensions., Competing Interests: Declarations. Conflict of interest: The results in this work are original and have not been submitted elsewhere. Ethical approval: All authors agree with the content and all give explicit consent to submit and they obtained consent from the responsible authorities at the organization where the work has been carried., (© 2025. The Author(s).)

Among the components of a humanoid robot, a humanoid torso plays a vital role in supporting a humanoid robot to complete the desired motions. In this paper, a new LARMbot torso is developed to obtain better working performance based on biological features. By analyzing the anatomy of a human torso and spine, a parallel cable-driven mechanism is proposed to actuate the whole structure using two servo motors and two pulleys. Analysis is conducted to evaluate the properties of the proposed parallel cable-driven mechanism. A closed-loop control system is applied to control the whole LARMbot torso. Experiments are performed using the manufactured prototype in three modes to evaluate the characterizations of the proposed design. Results show that the proposed LARMbot can complete the desired motions properly, including two general human-like motions and a full rotation motion. When completing two general human-like motions, the maximum bending angle is 40 degrees. The maximum cable tension is 0.68 N, and the maximum required power is 18.3 W. In full rotation motion, the maximum bending angle is 30 degrees. The maximum cable tension is 0.75 N, and the maximum power required is 20.5 W. The proposed design is simplified and lightweight, with low energy consumption and flexible spatial motion performance that can meet the requirements of the humanoid robot torso's application in complex scenarios and commercial requirements., (Creative Commons Attribution license.)

Obtaining appropriate low-dimensional representations from high-dimensional sensory inputs in an unsupervised manner is essential for straightforward downstream processing. Although nonlinear dimensionality reduction methods such as t -distributed stochastic neighbor embedding ( t -SNE) have been developed, their implementation in simple biological circuits remains unclear. Here, we develop a biologically plausible dimensionality reduction algorithm compatible with t -SNE, which uses a simple three-layer feedforward network mimicking the Drosophila olfactory circuit. The proposed learning rule, described as three-factor Hebbian plasticity, is effective for datasets such as entangled rings and MNIST, comparable to t -SNE. We further show that the algorithm could be working in olfactory circuits in Drosophila by analyzing the multiple experimental data in previous studies. We lastly suggest that the algorithm is also beneficial for association learning between inputs and rewards, allowing the generalization of these associations to other inputs not yet associated with rewards.

We derive and test a CT-based biological age model for predicting longevity, using an automated pipeline of explainable AI algorithms that quantifies skeletal muscle, abdominal fat, aortic calcification, bone density, and solid abdominal organs. We apply these AI tools to abdominal CT scans from 123,281 adults (mean age, 53.6 years; 47% women; median follow-up, 5.3 years). The final weighted CT biomarker selection was based on the index of prediction accuracy. The CT model significantly outperforms standard demographic data for predicting longevity (IPA = 29.2 vs. 21.7; 10-year AUC = 0.880 vs. 0.779; p < 0.001). Age- and sex-corrected survival hazard ratio for the highest-vs-lowest risk quartile was 8.73 (95% CI,8.14-9.36) for the CT biological age model, and increased to 24.79 after excluding cancer diagnoses within 5 years of CT. Muscle density, aortic plaque burden, visceral fat density, and bone density contributed the most. Here we show a personalized phenotypic CT biological age model that can be opportunistically-derived, regardless of clinical indication, to better inform risk assessment., Competing Interests: Competing interests: P.J.P.: advisor to Bracco Diagnostics, GE HealthCare, Nanox-AI, and ColoWatch; stock options, ColoWatch; J.W.G.: Advisor to RadUnity, Shareholder in NVIDIA; R.M.S.: Royalties from iCAD, ScanMed, Philips, Translation Holdings, PingAn, MGB; research support through a CRADA with PingAn. The remaining authors declare no competing interests., (© 2025. The Author(s).)

A critical challenge for diseases spread is the development of effective prevention and control measures while minimizing costs, representing the foremost priority. Unfortunately, research in this crucial area remains inadequately explored. Consequently, this paper addresses the issue by leveraging an SI reaction-diffusion epidemic model incorporating a logistic birth rate and standard incidence rate. Employing vaccination as a control variable and integrating sparse optimal control theory, the study elucidates the achievement of epidemic prevention and control through the optimization of resource allocation, emphasizing a perspective rooted in pattern structure transformation. On the one hand, we theoretically prove the existence of the optimal solutions, first-order necessary optimality conditions, and the sparsity properties. On the other hand, we use numerical simulations to verify the rationality of the control method and the effectiveness of the control strategy from three aspects of control effect, control error and control cost. In addition, tailored targeting options are proposed based on the economic status of each region, specifying the required inoculum amount for each moment. Ultimately, the study demonstrates the effectiveness of input vaccination in controlling epidemics in a majority of areas. In summary, this work offers crucial insights into the prevention and control of a non-quasimonotonic reaction-diffusion epidemic model., 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.)

Using in-house computational tools, this work focuses on investigating how the combination of the electric field magnitude (E), bloodstream velocity (λinl) and pharmaco-kinetic profile (PK) impacts the reaction and transport mechanisms of drug (RTMs) arising in electro-chemotherapeutic treatments. The first step implies retrieving the ratios between extracellular, free intracellular, and bound intracellular concentrations from numerical simulations, employing a meshless code developed, calibrated and validated in a previous work. Subsequently, a Boolean model is developed to determine the presence, interaction and rates of RTMs based on the comparison of the spatio-temporal evolution of the drug concentration ratios, being this the main contribution of the present work to the comprehension of the phenomena involved in the systemic administration of chemotherapeutic drugs in cancer tumors. Different combinations of E (0 kV/m, 46 kV/m, 70 kV/m), λinl (1x10-4m/s, 1x10-3m/s, 1x10-2m/s) and PK (One-short tri-exponential, mono-exponential) are examined. In general, results show that both the presence and relative importance of RTMs can differ between both PKs for a given combination of E and λinl. Additionally, for a given PK, radial uniformity of transmembrane transport rate is aversively affected by the increase of E and λinl, whereas radial homogeneity of association/dissociation rate is monotonously affected only by E. Regarding the axial uniformity of transmembrane transport rate, this is benefited by the increase of λinl and, in a lower extent, by the reduction of E., Competing Interests: NO authors have competing interests., (Copyright: © 2025 Vélez Salazar, Patiño. 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.)

Albatrosses are increasingly drawing attention from the scientific community due to their remarkable flight capabilities. Recent studies suggest that grey-headed albatrosses (GHA) may be the fastest and most energy-efficient of the albatross species, yet no attempts have been made to replicate their wing design. A key factor in aircraft design is the airfoil, which remains uncharacterized for the GHA. Other critical aspects, such as wing twist and dihedral/anhedral, also remain unquantified for any albatross species. This study aimed to fill this gap in the current knowledge by extracting detailed morphological data from a GHA wing to recreate digitally. A well-preserved dried GHA wing was scanned in the presence of airflow in a wind tunnel, at conditions that represent a GHA in gliding flight. Wing cross-sections were extracted and smoothed to produce a series of airfoils along the wing span. The 3D properties such as wing dihedral/anhedral, sweep and twist were also extracted and used to build a CAD model of the wing. Variations in airfoil shape were observed along the wing span, with thicker, more cambered airfoils near the wing base. The model wing's camber was slightly higher, particularly in the arm section, but overall matched flight photographs. The body, tail, and bill were modelled based on available photographs and known dimensions from literature and merged with the wing to form the final bill-body-wing-tail model. This model is based on real GHA morphology under aerodynamic pressure, in gliding flight. Although geometric changes due to scanner interference remain a limitation of this method, the extracted geometric data still provide valuable insights into wing performance under varying conditions. The geometry can also be fully parameterized for complex simulations, aiding studies of GHA aerodynamics and engineering design, such as in aircraft or wind turbines at similar Reynolds numbers., (© 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Slowdowns in lineage accumulation are often observed in phylogenies of extant species. One explanation is the presence of ecological limits to diversity and hence to diversification. Previous research has examined whether and how species richness (SR) impacts diversification rates, but rarely considered the evolutionary relatedness (ER) between species, although ER can affect the degree of interaction between species, which likely sets these limits. To understand the influences of ER on species diversification and the interplay between SR and ER, we present a simple birth-death model in which the speciation rate depends on the ER. We use different metrics of ER that operate at different scales, ranging from branch/lineage-specific to clade-wide scales. We find that the scales at which an effect of ER operates yield distinct patterns in various tree statistics. When ER operates across the whole tree, we observe smaller and more balanced trees, with speciation rates distributed more evenly across the tips than in scenarios with lineage-specific ER effects. Importantly, we find that negative SR dependence of speciation masks the impact of ER on some of the tree statistics. Our model allows diverse evolutionary trajectories for producing imbalanced trees, which are commonly observed in empirical phylogenies but have been challenging to replicate with earlier models., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Blood clotting is an important physiological process to suppress bleeding upon injury, but when it occurs inadvertently, it can cause thrombosis, which can lead to life threatening conditions. Hence, understanding the microscopic mechanistic factors for inadvertent, spontaneous blood clotting, in absence of a vessel breach, can help in predicting and averting such conditions. Here, we present a minimal model - reminiscent of the SIR model - for the initiating stage of spontaneous blood clotting, the collective activation of blood platelets. This model predicts that in the presence of very small initial activation signals, collective activation of the platelet population is possible, but requires a sufficient degree of heterogeneity of platelet sensitivity. To propagate the activation signal and achieve collective activation of the bulk platelet population, it requires the presence of, possibly only few, hyper-sensitive platelets, but also a sufficient proportion of platelets with intermediate, yet higher-than-average sensitivity. A comparison with experimental results demonstrates a qualitative agreement for high platelet signalling activity., 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. Published by Elsevier Ltd.. All rights reserved.)

The endogenous circadian rhythm (approximately 24 h) allows plants to adapt to daily light and temperature variations. Although the mechanism of photoperiod entrainment has been studied extensively, entrainment to diurnal temperature rhythms remains poorly understood. Here we investigate the stochastic entrainment of the circadian clock in the model crop tomato, subject to different thermoperiods. We first proposed the deterministic model of the thermoresponsive circadian clock. The expressions of the circadian clock genes under constant warm temperature (29 ℃) were quantified by RT-qPCR for basal parameters estimation through minimizing the cost function. Model simulations by the stochastic simulation algorithm showed warm temperatures resulting in an advanced phase for approximately 3-4 h. A few hundred molecules for the system size of the stochastic model were sufficient to engage the robust oscillations. Multiple temperature inputs and abnormal temperature cycles similarly showed the invariant robustness of the oscillations. In addition, phases of the core circadian elements were remarkably correlated linearly with periods under temperature cycles. Whereas, the phases were correlated with the duration of daily warm temperature stimuli in a polynomial mode., 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.)

Norovirus, responsible for acute gastroenteritis and foodborne diseases in the United States, is influenced significantly by environmental factors. This study employs a hybrid approach to develop a foodborne disease model that incorporates indirect incidence to examine the correlation between norovirus outbreaks and environmental conditions, specifically focusing on the impact of temperature and humidity on virus transmission. By analyzing weekly average climate data and confirmed case data from four United States regions (Southern, Northeastern, Midwestern, and Western), we assess the mortality rates and estimate transmission rates using the inverse method. Our numerical results confirm that norovirus outbreaks predominantly occur in colder months. However, higher temperatures or increased humidity during warmer months appear to mitigate the spread of the virus. Utilizing climate data, this study also forecasts transmission rates and infection cases up to eight weeks in advance using a generalized boosting machine learning model., 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.)

Bacterial cell persistence, crucial for survival under adverse conditions like antibiotic exposure, is intrinsically linked to stochastic fluctuations in gene expression. Certain genes, while inhibiting growth under normal circumstances, confer tolerance to antibiotics at elevated expression levels. The occurrence of antibiotic events lead to instantaneous cellular responses with varied survival probabilities correlated with gene expression levels. Notably, cells with lower protein concentrations face higher mortality rates. This study aims to elucidate an optimal strategy for protein expression conducive to cellular survival. Through comprehensive mathematical analysis, we determine the optimal burst size and frequency that maximise cell proliferation. Furthermore, we explore how the optimal expression distribution changes as the cost of protein expression to growth escalates. Our model reveals a hysteresis phenomenon, characterised by discontinuous transitions between deterministic and stochastic optima. Intriguingly, stochastic optima possess a noise floor, representing the minimal level of fluctuations essential for optimal cellular resilience., 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.)

Tomopterids are mesmerizing holopelagic swimmers. They use two modes of locomotion simultaneously: drag-based metachronal paddling and bodily undulation. Tomopteris has two rows of flexible, leg-like parapodia positioned on opposite sides of its body. Each row metachronally paddles out of phase to the other. Both paddling behaviors occur in concert with a lateral bodily undulation. However, when looked at independently, each mode appears in tension with the other. The direction of the undulatory wave is opposite of what one may expect for forward (FWD) swimming and appears to actively work act against the direction of swimming initiated by metachronal paddling. To investigate how these two modes of locomotion synergize to generate effective swimming, we created a self-propelled, fluid-structure interaction model of an idealized Tomopteris . We holistically explored swimming performance over a 3D mechanospace comprising parapodia length, paddling amplitude, and undulatory amplitude using a machine learning framework based on polynomial chaos expansions. Although undulatory amplitude minimally affected FWD swimming speeds, it helped mitigate the larger costs of transport that arise from either using more mechanically expensive (larger) paddling amplitudes and/or having longer parapodia., (© 2025 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Understanding the thermal comfort and safety of diverse populations within indoor settings requires a quantitative understanding of the primary heat exchange pathways between occupants and their surroundings: radiation and free convection. Thus far, however, free convective heat transfer coefficients have only been determined for the average Western adult. To this end, we investigated how variation in body shape impacts free convection heat transfer using an experimentally validated numerical model. The multiphysics model was compared against experiments conducted using the thermal manikin ANDI ("Advanced Newton Dynamic Instrument") in a climate-controlled enclosure across five air-to-skin temperature differences ranging from 4.9 to 13.9°C. The difference between measured and simulated heat fluxes for the whole body, and per anatomical region, was typically <5%, occasionally reaching 15-20%, for some body regions due to physical features not modeled in the virtual ANDI model. Using the validated model, we simulated free convection around a family, or diverse group, of virtual manikins representing the 1st to 99th percentile body mass index (BMI) and height variation in the United States adult population. Our results show that the free convection heat transfer coefficient is independent of human sex and height but decreases slightly with increased BMI. However, the variation from the average manikin in the whole body and regional free convection coefficients with BMI was small, not exceeding 8% and 16%, respectively. Furthermore, our regression coefficients and exponents can be derived from the theorical correlation for free turbulent convection from a vertical plate, which also explains the observed independence of the heat transfer coefficient from the manikins' height. Overall, these findings demonstrate the general applicability of using an average body shape in indoor thermal audits and/or overheating risk assessments to understand thermal comfort and heat stress. The results and valid application of the model support critical insights for human health, productivity, and well-being connected to heat and cooling in buildings., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Viswanathan 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.)

In this issue of Cell Stem Cell, Pan et al. generated human induced pluripotent stem cell (iPSC)-derived venous endothelial cells (iVECs) by manipulating cell-cycle dynamics and Notch signaling and demonstrated that TIE2-mutant iVECs recapitulate the pathogenesis of venous malformations. 1 Their study provides a model for further mechanistic studies and drug discovery., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2025 Elsevier Inc. All rights reserved.)

Complex interactions between stromal cells, tumor cells and therapies can influence environmental factors that in turn impact anticancer treatment efficacy. Disentangling these phenomena is critical for understanding treatment response and designing effective dosing strategies. We propose a mathematical model for a common tumor-stromal interaction motif where stromal cells secrete factors that promote drug resistance. We demonstrate that the presence of this interaction modulates the therapeutic dose window of efficacy and can lead to nonmonotonic treatment response. We consider combination strategies that target stromal cells and their secretome, and identify strategies that constrain drug concentrations within the efficacious window for long-term response. We explore an experimental dataset from colorectal cancer cells treated with anti-EGFR targeting therapy, cetuximab, where cancer-associated fibroblasts increase epidermal growth factor secretion under treatment. We apply our general approach to identify a critical drug concentration threshold and study effective dosing regimens for single-drug and combination therapies., Competing Interests: Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Venous malformations (VMs) represent prevalent vascular anomalies typically attributed to non-inherited somatic mutations within venous endothelial cells (VECs). The lack of robust disease models for VMs impedes drug discovery. Here, we devise a robust protocol for the generation of human induced VECs (iVECs) through manipulation of cell-cycle dynamics via the retinoic signaling pathway. We introduce an L914F mutation into the TIE2 gene locus of induced pluripotent stem cells (iPSCs) and show that the mutated iVECs form dilated blood vessels after transplantation into mice, thereby recapitulating the phenotypic characteristics observed in VMs. Moreover, utilizing a deep neural network and a high-throughput digital RNA with perturbation of genes sequencing (DRUG-seq) approach, we perform drug screening and demonstrate that bosutinib effectively rescues the disease phenotype in vitro and in vivo. In summary, by leveraging genome editing and stem cell technology, we generate VM models that enable the development of additional therapeutics., Competing Interests: Declaration of interests K.W., Z.P., Weijing Kong, Xi Wang, X.P., Y.Y., and J.Q. have been granted a patent pertaining to the work in this manuscript (ZL2023113454514)., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

The concept of identifiability describes the possibility of inferring the parameters of a dynamic model by observing its output. It is common and useful to distinguish between structural and practical identifiability. The former property is fully determined by the model equations, while the latter is also influenced by the characteristics of the available experimental data. Structural identifiability can be determined by means of symbolic computations, which may be performed before collecting experimental data, and are hence sometimes called a priori analyses. Practical identifiability is typically assessed numerically, with methods that require simulations-and often also optimization-and are applied a posteriori. An approach to study structural local identifiability is to consider it as a particular case of observability, which is the possibility of inferring the internal state of a system from its output. Thus, both properties can be analysed jointly, by building a generalized observability matrix and computing its rank. The aim of this paper is to investigate to which extent such observability-based methods can also inform about practical aspects related with the experimental setup, which are usually not approached in this way. To this end, we explore a number of possible extensions of the rank tests, and discuss the purposes for which they can be informative as well as others for which they cannot., (© 2025. The Author(s).)

Feedback delay has been identified as a key ingredient in the quorum sensing synchronization of synthetic gene oscillators. While this influence has been evidenced at the theoretical level in a simplified system of degrade-and-fire oscillators coupled via a common activator protein, full mathematical certifications remained to be provided. Here, we prove from a rigorous mathematical viewpoint that, for the very same model, the synchronized degrade-and-fire oscillations are 1/ unstable with respect to out-of-sync perturbations in absence of delay, and 2/ are otherwise asymptotically stable in presence of delay, no matter how small is its amplitude. To that goal, we proceed to an extensive study of the population dynamics in this system, which in particular identifies the mechanisms of, and related criteria for, the delay-dependent stability of periodic orbits with respect to out-of-sync perturbations. As an additional outcome, the analysis also reveals that, depending on the parameters, multiple stable partially synchronized periodic orbits can coexist with the fully synchronized one., Competing Interests: Declarations. Conflict of interest: The authors have no Conflict of interest to declare. The data and graphs presented in this paper have illustrative purposes. No data were created or analysed during this study. Data sharing is not applicable to this article., (© 2025. The Author(s).)

The phase response curve (PRC) represents the time-dependent changes in circadian rhythm phase following internal or external stimuli. However, this time dependence complicates PRC measurement and quantification owing to its variable shape with changing stimulus intensity. Our previous work demonstrated that resetting a desynchronized circadian clock (singularity response, SR) simplifies the analysis by requiring only amplitude and phase parameters. In this study, we construct a comprehensive model for phase resetting in the mouse circadian clock by converting PRCs into SR parameters. We analyze single-cell PRCs and show that the SR amplitude parameters for different stimulus concentrations follow the Hill equation. Additionally, the model predicts the combined effects of multiple stimuli and pre-treatment (background) on phase response by simple addition or subtraction of individual SR parameters. Experimental validation using SR measurements in mouse cells and tissues confirms the model's accuracy. This study demonstrates that SRs facilitate PRC quantification and reveal simple rules governing phase resetting properties under various conditions using SR parameters., Competing Interests: Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Local stresses in a tissue, a collective property, regulate cell division and apoptosis. In turn, cell growth and division induce active stresses in the tissue. As a consequence, there is a feedback between cell growth and local stresses. However, how the cell dynamics depend on local stress-dependent cell division and the feedback strength is not understood. Here, we probe the consequences of stress-mediated growth and cell division on cell dynamics using agent-based simulations of a two-dimensional growing tissue. We discover a rich dynamical behavior of individual cells, ranging from jamming (mean square displacement, Δ( t ) ∼ t α with α less than unity), to hyperdiffusion ( α > 2) depending on cell division rate and the strength of the mechanical feedback. Strikingly, Δ( t ) is determined by the tissue growth law, which quantifies cell proliferation, measuring the number of cells N ( t ) as a function of time. The growth law ( N ( t ) ∼ t λ at long times) is regulated by the critical pressure that controls the strength of the mechanical feedback and the ratio between cell division-apoptosis rates. We show that λ ∼ α , which implies that higher growth rate leads to a greater degree of cell migration. The variations in cell motility are linked to the emergence of highly persistent forces extending over several cell cycle times. Our predictions are testable using cell-tracking imaging techniques.

This study presents a numerical model for incipient fibrin-clot formation that captures characteristic rheological and microstructural features of the clot at the gel point. Using a mesoscale-clustering framework, we evaluate the effect of gel concentration or gel volume fraction and branching on the fractal dimension, the gel time, and the viscoelastic properties of the clots. We show that variations in the gel concentration of our model can reproduce the effect of thrombin in the formation of fibrin clots. In particular, the model reproduces the fractal dimension's dependency on gel concentration and the trends in elasticity and gelation time with varying thrombin concentrations. This approach allows us to accurately recreate the gelation point of fibrin-thrombin gels, highlighting the intricate process of fibrin polymerization and gel network formation. This is critical for applications in the clinical and bioengineering fields where precise control over the gelation process is required.

An updated physiologically based pharmacokinetic (PBPK) model was developed for lamotrigine by incorporating a component of metabolism due to a UDP-glucuronyltransferase (UGT) 2B isozyme. This was assigned to UGT2B10 based on recent in vitro data in our laboratory demonstrating metabolism of lamotrigine by this isozyme (Tang et al. AAPS J 26:107, 2024). The PBPK model developed in this work was able to reasonably recapitulate the exposure of lamotrigine after single (IV and Oral) and multiple (Oral) doses. The predicted/observed maximal plasma concentration (C max ) ratio ranged from 0.8 to 1.4 across all simulated studies and for 16 out of 18 simulated studies was between 0.8 and 1.25. Similarly, the predicted/observed area under the curve (AUC) ratio ranged from 0.6 to 1.44 across all simulated studies and for 18 out of 26 of the simulated studies the ratio was between 0.8 and 1.25. There was a slight tendency to overpredict the lamotrigine AUC on multiple dosing. The median predicted fraction metabolised (fm) by UGT2B10 in the model was 60%. With this fm value, the in vivo clinical DDI between lamotrigine and valproate was reasonably recapitulated considering only UGT2B10 inhibition (Predicted/Observed AUC ratios ranged from 0.65 - 1.2). Information on the prevalence of UGT2B10 poor metabolizer phenotypes and longitudinal changes in UGT1A4 and UGT2B10 expression during pregnancy were incorporated into the PBPK model and the plasma concentrations in subjects with different UGT2B10 phenotypes and in different trimesters of pregnancy were simulated. The simulated concentrations in pregnant subjects were in line with those reported during pregnancy., Competing Interests: Declarations. Conflict of Interest: IG and ATH are employees of Certara Predictive Technologies and may own Certara Stock. LWTT, KL and TCG are employees of Pfizer Inc., New York, NY, USA and may own shares/stock options in Pfizer Inc., New York, NY, USA., (© 2025. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

Antiviral therapies can yield different outcomes depending on their scheduling: a highly effective drug may produce treatment results ranging from successful to inconsequential, depending on therapeutic timing, dosing intervals, and dosage. The effectiveness of antiviral therapies can be assessed using mathematical models that describe viral spread within a host. In this work, we conduct a study based on the dynamic characterization of a target-cell model to address a multi-objective control problem aimed at designing highly effective and host-customizable antiviral therapies. These therapies involve finite-time antiviral treatments that minimize the viral load peak and the infection final size until infection clearance, while simultaneously reducing the total amount of drug intake as much as possible. Two optimization-based control strategies are proposed: a fixed-dose and a variable-dose approach. The variable-dose strategy achieves superior performance by explicitly considering the system dynamics in the design of the control. Simulation results, based on an identified model for COVID-19 patients treated with Paxlovid, illustrate the potential benefits of the proposed strategies., Competing Interests: Declarations. Conflict of 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., (© 2025. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Development of antibodies often begins with the assessment and optimization of their physicochemical properties, and their efficient engagement with the target of interest. Decisions at the early optimization stage are critical for the success of the drug candidate but are constrained due to the limited knowledge of the antibody and target pharmacology. In the present work, we propose a machine learning-based target pharmacology assessment framework that utilizes minimal physiologically based pharmacokinetic (mPBPK) modeling and machine learning (ML) to infer optimal physicochemical properties of antibodies and their targets. We use a mPBPK model previously developed by our group that incorporates a multivariate quantitative relationship between antibodies' physicochemical properties such as molecular weight (MW), size, charge, and in silico + in vitro derived descriptors with their PK properties. In this study, we perform a high-throughput exploration of virtual antibody drug candidates with varying physicochemical properties (binding affinity, charge, etc.), and virtual target candidates with varying characteristics (baseline expression, half-life, etc.) to unravel rules for antibody drug candidate selection that achieve favorable drug-target interaction, which is defined by target occupancy (TO) percentage. We identified that variations in the antibody dose and dosing scheme, target form (soluble or membrane-bound), antibody charge, and site of action had a significant effect on the TO and selection criteria for antibody drug candidates. By unraveling new design rules for antibody drug properties that are dependent on ML-based TO assessment, we deliver a first-in-class ML-based target pharmacology assessment framework toward better understanding of the biology-specific PK and ADME processes of antibody drug candidate proteins and reduce the overall time for drug development., Competing Interests: Declarations. Competing interests: All authors were employed by Sanofi while the manuscript was written., (© 2025. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Accurate chromosome segregation in mitosis depends on proper connections of sister chromatids, through microtubules, to the opposite poles of the early mitotic spindle. Transiently, many inaccurate connections are formed and rapidly corrected throughout the mitotic stages, but a small number of merotelic connections, in which a chromatid is connected to both spindle poles, remain lagging at the spindle's equator in anaphase. Most of the lagging chromatids are eventually moved to one or the other pole, likely by a combination of microtubules' turnover and the brute force of pulling by the microtubules' majority from the one pole against the microtubules' minority from the other pole. We use computer simulations from two stochastic models (1D and full 3D CellDynaMo model) combining force balances and microtubules' dynamics for the lagging chromatids to investigate what maximizes the percentage of segregated laggards. We find that a) brute force tug-of-war with slow (< 0.0001 s -1 ) microtubules' detachment rate can move asymmetric laggards to the poles in limited time, b) rapid (> 0.01 s -1 ) microtubules' detachment rate leads to a significant loss of the laggards, and c) intermediate (~ 0.001 s -1 ) microtubules' detachment rate ensures higher than 90% accuracy of segregation. The simulations also shed light on the waiting time required to correct the merotelic errors in anaphase and on the roles of chromatid-attached microtubule number and Aurora B-mediated, spatially graded regulation of microtubule kinetics in anaphase., Competing Interests: Competing interests statement:The authors declare no competing interest.

This manuscript introduces a new Erlang-distributed SEIR model. The model incorporates asymptomatic spread through a subdivided exposed class, distinguishing between asymptomatic ( E a ) and symptomatic ( E s ) cases. The model identifies two key parameters: relative infectiousness, β SA , and the percentage of people who become asymptomatic after being infected by a symptomatic individual, κ . Lower values of these parameters reduce the peak magnitude and duration of the infectious period, highlighting the importance of isolation measures. Additionally, the model underscores the need for strategies addressing both symptomatic and asymptomatic transmissions., (© 2025. The Author(s).)