Bayesian modelling of time series data (BayModTS) - a FAIR workflow to process sparse and highly variable data.

MOTIVATION: Systems biology aims to better understand living systems through mathematical modelling of experimental and clinical data. A pervasive challenge in quantitative dynamical modelling is the integration of time series measurements, which often have high variability and low sampling resolution. Approaches are required to utilise such information while consistently handling uncertainties. RESULTS: We present BayModTS (Bayesian Modelling of Time Series data), a new FAIR (Findable, Accessible, Interoperable and Reusable) workflow for processing and analysing sparse and highly variable time series data. BayModTS consistently transfers uncertainties from data to model predictions, including process knowledge via parameterised models. Further, credible differences in the dynamics of different conditions can be identified by filtering noise. To demonstrate the power and versatility of BayModTS, we applied it to three hepatic datasets gathered from three different species and with different measurement techniques: (i) blood perfusion measurements by magnetic resonance imaging in rat livers after portal vein ligation, (ii) pharmacokinetic time series of different drugs in normal and steatotic mice, and (iii) CT-based volumetric assessment of human liver remnants after clinical liver resection. AVAILABILITY AND IMPLEMENTATION: The BayModTS codebase is available on GitHub at https://github.com/Systems-Theory-in-Systems-Biology/BayModTS. The repository contains a Python script for the executable BayModTS workflow and a widely applicable SBML (Systems Biology Markup Language) model for retarded transient functions. In addition, all examples from the paper are included in the repository. Data and code of the application examples are stored on DaRUS https://doi.org/10.18419/darus-3876. The raw MRI ROI voxel data were uploaded to DaRUS https://doi.org/10.18419/darus-3878. The steatosis metabolite data are published on FairdomHub 10.15490/fairdomhub.1.study.1070.1.

The simulation experiment description markup language (SED-ML): language specification for level 1 version 5.

Modern biological research is increasingly informed by computational simulation experiments, which necessitate the development of methods for annotating, archiving, sharing, and reproducing the conducted experiments. These simulations increasingly require extensive collaboration among modelers, experimentalists, and engineers. The Minimum Information About a Simulation Experiment (MIASE) guidelines outline the information needed to share simulation experiments. SED-ML is a computer-readable format for the information outlined by MIASE, created as a community project and supported by many investigators and software tools. Level 1 Version 5 of SED-ML expands the ability of modelers to define simulations in SED-ML using the Kinetic Simulation Algorithm Onotoloy (KiSAO). While it was possible in Version 4 to define a simulation entirely using KiSAO, Version 5 now allows users to define tasks, model changes, ranges, and outputs using the ontology as well. SED-ML is supported by a growing ecosystem of investigators, model languages, and software tools, including various languages for constraint-based, kinetic, qualitative, rule-based, and spatial models, and many simulation tools, visual editors, model repositories, and validators. Additional information about SED-ML is available at https://sed-ml.org/.

Quantifying fat zonation in liver lobules: an integrated multiscale in silico model combining disturbed microperfusion and fat metabolism via a continuum biomechanical bi-scale, tri-phasic approach.

Metabolic zonation refers to the spatial separation of metabolic functions along the sinusoidal axes of the liver. This phenomenon forms the foundation for adjusting hepatic metabolism to physiological requirements in health and disease (e.g., metabolic dysfunction-associated steatotic liver disease/MASLD). Zonated metabolic functions are influenced by zonal morphological abnormalities in the liver, such as periportal fibrosis and pericentral steatosis. We aim to analyze the interplay between microperfusion, oxygen gradient, fat metabolism and resulting zonated fat accumulation in a liver lobule. Therefore we developed a continuum biomechanical, tri-phasic, bi-scale, and multicomponent in silico model, which allows to numerically simulate coupled perfusion-function-growth interactions two-dimensionally in liver lobules. The developed homogenized model has the following specifications: (i) thermodynamically consistent, (ii) tri-phase model (tissue, fat, blood), (iii) penta-substances (glycogen, glucose, lactate, FFA, and oxygen), and (iv) bi-scale approach (lobule, cell). Our presented in silico model accounts for the mutual coupling between spatial and time-dependent liver perfusion, metabolic pathways and fat accumulation. The model thus allows the prediction of fat development in the liver lobule, depending on perfusion, oxygen and plasma concentration of free fatty acids (FFA), oxidative processes, the synthesis and the secretion of triglycerides (TGs). The use of a bi-scale approach allows in addition to focus on scale bridging processes. Thus, we will investigate how changes at the cellular scale affect perfusion at the lobular scale and vice versa. This allows to predict the zonation of fat distribution (periportal or pericentral) depending on initial conditions, as well as external and internal boundary value conditions.

Anti-rabies humoral immune response in cats after concurrent vs separate vaccination against rabies and feline leukaemia virus using canarypox-vectored vaccines.

OBJECTIVES: Some expert groups recommend that cats should be vaccinated with non-adjuvanted feline leukaemia virus (FeLV) and rabies vector vaccines, which, in the European Union, are currently not licensed for concurrent use and have to be administered at least 14 days apart (different from the USA) and thus at separate visits, which is associated with more stress for cats and owners. The aim of this study was to assess the anti-rabies antibody response in cats after vaccination against rabies and FeLV at concurrent vs separate (4 weeks apart) visits using two canarypox-vectored vaccines (Purevax Rabies and Purevax FeLV; Boehringer Ingelheim) and to evaluate the occurrence of vaccine-associated adverse events (VAAEs). METHODS: Healthy FeLV antigen-negative client-owned kittens (n = 106) were prospectively included in this randomised study. All kittens received primary vaccinations against rabies (week 0) and FeLV (weeks 4 and 8). After 1 year, the study group (n = 52) received booster vaccinations against rabies and FeLV concurrently at the same visit (weeks 50-52). The control group (n = 54) received booster vaccinations against rabies (weeks 50-52) and FeLV (weeks 54-56) separately. Anti-rabies virus antibodies (anti-RAV Ab) were determined by fluorescent antibody virus neutralisation assay at weeks 4, 50-52 and 54-56, and compared between both groups using a Mann-Whitney U-test. RESULTS: Four weeks after the first rabies vaccination, 87/106 (82.1%) kittens had a titre ⩾0.5 IU/ml and 19/106 (17.9%) had a titre <0.5 IU/ml. Four weeks after the 1-year rabies booster, all cats had adequate anti-RAV Ab according to the World Organisation for Animal Health (⩾0.5 IU/ml), and the titres of the study group (median = 14.30 IU/ml) and the control group (median = 21.39 IU/ml) did not differ significantly (P = 0.141). VAAEs were observed in 7/106 (6.6%) cats. CONCLUSIONS AND RELEVANCE: Concurrent administration of Purevax FeLV and Purevax Rabies vector vaccines at the 1-year booster does not interfere with the development of anti-RAV Ab or cause more adverse effects and thus represents a better option than separate vaccination visits for cats and owners.

Hyperspectral confocal imaging for high-throughput readout and analysis of bio-integrated microlasers.

Integrating micro- and nanolasers into live cells, tissue cultures and small animals is an emerging and rapidly evolving technique that offers noninvasive interrogation and labeling with unprecedented information density. The bright and distinct spectra of such lasers make this approach particularly attractive for high-throughput applications requiring single-cell specificity, such as multiplexed cell tracking and intracellular biosensing. The implementation of these applications requires high-resolution, high-speed spectral readout and advanced analysis routines, which leads to unique technical challenges. Here, we present a modular approach consisting of two separate procedures. The first procedure instructs users on how to efficiently integrate different types of lasers into living cells, and the second procedure presents a workflow for obtaining intracellular lasing spectra with high spectral resolution and up to 125-kHz readout rate and starts from the construction of a custom hyperspectral confocal microscope. We provide guidance on running hyperspectral imaging routines for various experimental designs and recommend specific workflows for processing the resulting large data sets along with an open-source Python library of functions covering the analysis pipeline. We illustrate three applications including the rapid, large-volume mapping of absolute refractive index by using polystyrene microbead lasers, the intracellular sensing of cardiac contractility with polystyrene microbead lasers and long-term cell tracking by using semiconductor nanodisk lasers. Our sample preparation and imaging procedures require 2 days, and setting up the hyperspectral confocal microscope for microlaser characterization requires <2 weeks to complete for users with limited experience in optical and software engineering.

Determination of Lactose in Lactose-Free and Low-Lactose Milk, Milk Products, and Products Containing Dairy Ingredients by the LactoSens®R Amperometry Method: Final Action 2020.01.

BACKGROUND: The LactoSens®R method was previously shown to have acceptable accuracy and repeatability precision as required by AOAC Standard Method Performance Requirements (SMPR®) 2018.009 for determination of lactose in low-lactose or lactose-free milk, milk products, and products containing dairy ingredients and was awarded Official Method of AnalysisSM (OMA) First Action status in 2020. OBJECTIVE: The method was subjected to a multilaboratory validation (MLV) study to evaluate the reproducibility precision of the method. METHODS: Fourteen validation materials were provided to 15 laboratories in seven countries as blind duplicates. The materials ranged from 0 to 173 mg/100 g lactose. Each laboratory analyzed the blind duplicates according to OMA 2020.01. The data were analyzed for repeatability and reproducibility precision. RESULTS: RSDr values varied from 2.81 to 8.76%, and RSDR values varied from 4.25 to 12.5%. When sorted by category and concentration range, these results met the repeatability and reproducibility criteria required by SMPR 2018.009. CONCLUSIONS: The data generated in the MLV support the adoption of OMA 2020.01 as Final Action status. HIGHLIGHTS: The LactoSensR method, as described by OMA 2020.01, provides an accurate and precise determination of lactose in a variety of low-lactose and lactose-free milk, milk products, and products containing dairy ingredients in minutes.

Eleven strategies for making reproducible research and open science training the norm at research institutions.

Reproducible research and open science practices have the potential to accelerate scientific progress by allowing others to reuse research outputs, and by promoting rigorous research that is more likely to yield trustworthy results. However, these practices are uncommon in many fields, so there is a clear need for training that helps and encourages researchers to integrate reproducible research and open science practices into their daily work. Here, we outline eleven strategies for making training in these practices the norm at research institutions. The strategies, which emerged from a virtual brainstorming event organized in collaboration with the German Reproducibility Network, are concentrated in three areas: (i) adapting research assessment criteria and program requirements; (ii) training; (iii) building communities. We provide a brief overview of each strategy, offer tips for implementation, and provide links to resources. We also highlight the importance of allocating resources and monitoring impact. Our goal is to encourage researchers - in their roles as scientists, supervisors, mentors, instructors, and members of curriculum, hiring or evaluation committees - to think creatively about the many ways they can promote reproducible research and open science practices in their institutions.

A pathway model of glucose-stimulated insulin secretion in the pancreatic ß-cell.

The pancreas plays a critical role in maintaining glucose homeostasis through the secretion of hormones from the islets of Langerhans. Glucose-stimulated insulin secretion (GSIS) by the pancreatic ß-cell is the main mechanism for reducing elevated plasma glucose. Here we present a systematic modeling workflow for the development of kinetic pathway models using the Systems Biology Markup Language (SBML). Steps include retrieval of information from databases, curation of experimental and clinical data for model calibration and validation, integration of heterogeneous data including absolute and relative measurements, unit normalization, data normalization, and model annotation. An important factor was the reproducibility and exchangeability of the model, which allowed the use of various existing tools. The workflow was applied to construct a novel data-driven kinetic model of GSIS in the pancreatic ß-cell based on experimental and clinical data from 39 studies spanning 50 years of pancreatic, islet, and ß-cell research in humans, rats, mice, and cell lines. The model consists of detailed glycolysis and phenomenological equations for insulin secretion coupled to cellular energy state, ATP dynamics and (ATP/ADP ratio). Key findings of our work are that in GSIS there is a glucose-dependent increase in almost all intermediates of glycolysis. This increase in glycolytic metabolites is accompanied by an increase in energy metabolites, especially ATP and NADH. One of the few decreasing metabolites is ADP, which, in combination with the increase in ATP, results in a large increase in ATP/ADP ratios in the ß-cell with increasing glucose. Insulin secretion is dependent on ATP/ADP, resulting in glucose-stimulated insulin secretion. The observed glucose-dependent increase in glycolytic intermediates and the resulting change in ATP/ADP ratios and insulin secretion is a robust phenomenon observed across data sets, experimental systems and species. Model predictions of the glucose-dependent response of glycolytic intermediates and biphasic insulin secretion are in good agreement with experimental measurements. Our model predicts that factors affecting ATP consumption, ATP formation, hexokinase, phosphofructokinase, and ATP/ADP-dependent insulin secretion have a major effect on GSIS. In conclusion, we have developed and applied a systematic modeling workflow for pathway models that allowed us to gain insight into key mechanisms in GSIS in the pancreatic ß-cell.

A proof of concept for matchete: an automated tool for matching effective theories.

Studying the impact of new-physics models on low-energy observables necessitates matching to effective field theories at the relevant mass thresholds. We introduce the first public version of Matchete, a computer tool for matching weakly-coupled models at one-loop order. It uses functional methods to directly compute all matching contributions in a manifestly gauge-covariant manner, while simplification methods eliminate redundant operators from the output. We sketch the workings of the program and provide examples of how to match simple Standard Model extensions. The package, documentation, and example notebooks are publicly available at https://gitlab.com/matchete/matchete.

Specifications of standards in systems and synthetic biology: status and developments in 2022 and the COMBINE meeting 2022.

This special issue of the Journal of Integrative Bioinformatics contains updated specifications of COMBINE standards in systems and synthetic biology. The 2022 special issue presents three updates to the standards: CellML 2.0.1, SBML Level 3 Package: Spatial Processes, Version 1, Release 1, and Synthetic Biology Open Language (SBOL) Version 3.1.0. This document can also be used to identify the latest specifications for all COMBINE standards. In addition, this editorial provides a brief overview of the COMBINE 2022 meeting in Berlin.

A Consensus Model of Glucose-Stimulated Insulin Secretion in the Pancreatic ß -Cell.

The pancreas plays a critical role in maintaining glucose homeostasis through the secretion of hormones from the islets of Langerhans. Glucose-stimulated insulin secretion (GSIS) by the pancreatic ß -cell is the main mechanism for reducing elevated plasma glucose. Here we present a systematic modeling workflow for the development of kinetic pathway models using the Systems Biology Markup Language (SBML). Steps include retrieval of information from databases, curation of experimental and clinical data for model calibration and validation, integration of heterogeneous data including absolute and relative measurements, unit normalization, data normalization, and model annotation. An important factor was the reproducibility and exchangeability of the model, which allowed the use of various existing tools. The workflow was applied to construct the first consensus model of GSIS in the pancreatic ß -cell based on experimental and clinical data from 39 studies spanning 50 years of pancreatic, islet, and ß -cell research in humans, rats, mice, and cell lines. The model consists of detailed glycolysis and equations for insulin secretion coupled to cellular energy state (ATP/ADP ratio). Key findings of our work are that in GSIS there is a glucose-dependent increase in almost all intermediates of glycolysis. This increase in glycolytic metabolites is accompanied by an increase in energy metabolites, especially ATP and NADH. One of the few decreasing metabolites is ADP, which, in combination with the increase in ATP, results in a large increase in ATP/ADP ratios in the ß -cell with increasing glucose. Insulin secretion is dependent on ATP/ADP, resulting in glucose-stimulated insulin secretion. The observed glucose-dependent increase in glycolytic intermediates and the resulting change in ATP/ADP ratios and insulin secretion is a robust phenomenon observed across data sets, experimental systems and species. Model predictions of the glucose-dependent response of glycolytic intermediates and insulin secretion are in good agreement with experimental measurements. Our model predicts that factors affecting ATP consumption, ATP formation, hexokinase, phosphofructokinase, and ATP/ADP-dependent insulin secretion have a major effect on GSIS. In conclusion, we have developed and applied a systematic modeling workflow for pathway models that allowed us to gain insight into key mechanisms in GSIS in the pancreatic ß -cell.

libRoadRunner 2.0: a high performance SBML simulation and analysis library.

MOTIVATION: This article presents libRoadRunner 2.0, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using the systems biology markup language (SBML). RESULTS: libRoadRunner is a self-contained library, able to run either as a component inside other tools via its C++, C and Python APIs, or interactively through its Python or Julia interface. libRoadRunner uses a custom just-in-time (JIT) compiler built on the widely used LLVM JIT compiler framework. It compiles SBML-specified models directly into native machine code for a large variety of processors, making it fast enough to simulate extremely large models or repeated runs in reasonable timeframes. libRoadRunner is flexible, supporting the bulk of the SBML specification (except for delay and non-linear algebraic equations) as well as several SBML extensions such as hierarchical composition and probability distributions. It offers multiple deterministic and stochastic integrators, as well as tools for steady-state, sensitivity, stability and structural analyses. AVAILABILITY AND IMPLEMENTATION: libRoadRunner binary distributions for Windows, Mac OS and Linux, Julia and Python bindings, source code and documentation are all available at https://github.com/sys-bio/roadrunner, and Python bindings are also available via pip. The source code can be compiled for the supported systems as well as in principle any system supported by LLVM-13, such as ARM-based computers like the Raspberry Pi. The library is licensed under the Apache License Version 2.0.

Factors Influencing Vertical Transmission of Psittacine Bornavirus in Cockatiels (Nymphicus hollandicus).

The transmission of parrot bornavirus is still not fully understood. Although horizontal transmission through wounds can be one route, vertical transmission is still discussed. PaBV RNA and PaBV antigen were detected in psittacine embryos, but isolation of the virus failed, raising doubts about this route. In this study, cockatiels were infected either as adults (adult group) or during the first 6 days after hatching (juvenile group) and raised until sexual maturity to breed and lay eggs. A total of 92 eggs (adult group: 49, juvenile group: 43) were laid and incubated until day 17. The embryos and yolk samples were examined by RT-PCR for PaBV RNA and by infectivity assay for infectious virus. In the adult group, 14/31 embryos (45.2%) and 20/39 (51%) of the yolk samples demonstrated PaBV RNA in the PCR. Isolation of PaBV was not possible in any embryo of this group, but it was achieved in six yolk samples from one female. Anti-PaBV antibodies were detected in the yolk samples after seroconversion of all female parents. In the juvenile group, 22/29 embryos (74.9%) were positive for PaBV RNA. In 9/21 embryos (42.9%), PaBV isolation was possible. PaBV RNA was detected in 100% and infectious virus in 41% of the yolk samples. Anti-PaBV antibodies were detected in all yolk samples. For the first time, successful vertical transmission of PaBV was proven, but it seems to depend on the age when the parent birds are infected. Therefore, the age of the bird at time of infection may be an important factor in the occurrence of vertical transmission.

Periportal steatosis in mice affects distinct parameters of pericentral drug metabolism.

Little is known about the impact of morphological disorders in distinct zones on metabolic zonation. It was described recently that periportal fibrosis did affect the expression of CYP proteins, a set of pericentrally located drug-metabolizing enzymes. Here, we investigated whether periportal steatosis might have a similar effect. Periportal steatosis was induced in C57BL6/J mice by feeding a high-fat diet with low methionine/choline content for either two or four weeks. Steatosis severity was quantified using image analysis. Triglycerides and CYP activity were quantified in photometric or fluorometric assay. The distribution of CYP3A4, CYP1A2, CYP2D6, and CYP2E1 was visualized by immunohistochemistry. Pharmacokinetic parameters of test drugs were determined after injecting a drug cocktail (caffeine, codeine, and midazolam). The dietary model resulted in moderate to severe mixed steatosis confined to periportal and midzonal areas. Periportal steatosis did not affect the zonal distribution of CYP expression but the activity of selected CYPs was associated with steatosis severity. Caffeine elimination was accelerated by microvesicular steatosis, whereas midazolam elimination was delayed in macrovesicular steatosis. In summary, periportal steatosis affected parameters of pericentrally located drug metabolism. This observation calls for further investigations of the highly complex interrelationship between steatosis and drug metabolism and underlying signaling mechanisms.

Physiologically based pharmacokinetic (PBPK) modeling of the role of CYP2D6 polymorphism for metabolic phenotyping with dextromethorphan.

The cytochrome P450 2D6 (CYP2D6) is a key xenobiotic-metabolizing enzyme involved in the clearance of many drugs. Genetic polymorphisms in CYP2D6 contribute to the large inter-individual variability in drug metabolism and could affect metabolic phenotyping of CYP2D6 probe substances such as dextromethorphan (DXM). To study this question, we (i) established an extensive pharmacokinetics dataset for DXM; and (ii) developed and validated a physiologically based pharmacokinetic (PBPK) model of DXM and its metabolites dextrorphan (DXO) and dextrorphan O-glucuronide (DXO-Glu) based on the data. Drug-gene interactions (DGI) were introduced by accounting for changes in CYP2D6 enzyme kinetics depending on activity score (AS), which in combination with AS for individual polymorphisms allowed us to model CYP2D6 gene variants. Variability in CYP3A4 and CYP2D6 activity was modeled based on in vitro data from human liver microsomes. Model predictions are in very good agreement with pharmacokinetics data for CYP2D6 polymorphisms, CYP2D6 activity as described by the AS system, and CYP2D6 metabolic phenotypes (UM, EM, IM, PM). The model was applied to investigate the genotype-phenotype association and the role of CYP2D6 polymorphisms for metabolic phenotyping using the urinary cumulative metabolic ratio (UCMR), DXM/(DXO + DXO-Glu). The effect of parameters on UCMR was studied via sensitivity analysis. Model predictions indicate very good robustness against the intervention protocol (i.e. application form, dosing amount, dissolution rate, and sampling time) and good robustness against physiological variation. The model is capable of estimating the UCMR dispersion within and across populations depending on activity scores. Moreover, the distribution of UCMR and the risk of genotype-phenotype mismatch could be estimated for populations with known CYP2D6 genotype frequencies. The model can be applied for individual prediction of UCMR and metabolic phenotype based on CYP2D6 genotype. Both, model and database are freely available for reuse.

Increase in Lower Limb Strength after Multimodal Pain Management in Patients with Low Back Pain.

Background and Objectives: The aim of the present study was to evaluate the efficacy of a multimodal pain therapy (MPM) regarding the objective parameter muscle strength of segment-dependent lower limb muscle groups before and after such a treatment. Materials and Methods: 52 patients with a history of low back pain and/or leg pain received standardized multimodal pain management. Strength of segment indicating lower limb muscles were assessed for each patient before and after ten days of treatment by handheld dynamometry. Results: Overall strength increased significantly from 23.6 kg ± 6.6 prior to treatment to 25.4 ± 7.3 after treatment, p ≤ 0.001. All muscle groups significantly increased in strength with exception of great toe extensors. Conclusions: Despite lower basic strength values at the beginning of treatment, all investigated muscle groups, except for the great toe extensors, showed a significant increase of overall strength after completion of the multimodal pain management concept. Increased overall strength could help with avoiding further need of medical care by supporting patients' autonomy in daily life activities, as well as maintaining working abilities. Thus, our study is the first to show a significant positive influence on lower limb strength in patients with low back pain after a conservative MPM program.

BioSimulators: a central registry of simulation engines and services for recommending specific tools.

Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations.

Differences in muscle synergies among recovery responses limit inter-task generalisation of stability performance.

Generalisation of adaptations is key to effective stability control facing variety of postural threats during daily life activity. However, in a previous study we could demonstrate that adaptations to stability control do not necessarily transfer to an untrained motor task. Here, we examined the dynamic stability and modular organisation of motor responses to different perturbations (i.e. unpredictable gait-trip perturbations and subsequent loss of anterior stability in a lean-and-release protocol) in a group of young and middle-aged adults (n = 57; age range 19-53 years) to detect potential neuromotor factors limiting transfer of adaptations within the stability control system. We hypothesized that the motor system uses different modular organisation in recovery responses to tripping and lean-and-release, which may explain lack in positive transfer of adaptations in stability control. After eight trip-perturbations participants increased their dynamic stability during the first recovery step (p < 0.001), yet they showed no significant improvement to the untrained lean-and-release transfer task compared to controls who did not undergo the perturbation exposure (p = 0.44). Regarding the neuromuscular control of responses, lower number of synergies (3 vs. 4) was found for the lean-and-release compared to the gait-trip perturbation task, revealing profound differences in both the timing and function of the recruited muscles to match the biomechanical specificity of different perturbations. Our results provide indirect evidence that the motor system uses different modular organisation in diverse perturbation responses, what possibly inhibits inter-task generalisation of adaptations in stability control.

The systems biology simulation core library.

SUMMARY: Studying biological systems generally relies on computational modeling and simulation, e.g., model-driven discovery and hypothesis testing. Progress in standardization efforts led to the development of interrelated file formats to exchange and reuse models in systems biology, such as SBML, the Simulation Experiment Description Markup Language (SED-ML) or the Open Modeling EXchange format. Conducting simulation experiments based on these formats requires efficient and reusable implementations to make them accessible to the broader scientific community and to ensure the reproducibility of the results. The Systems Biology Simulation Core Library (SBSCL) provides interpreters and solvers for these standards as a versatile open-source API in JavaTM. The library simulates even complex bio-models and supports deterministic Ordinary Differential Equations; Stochastic Differential Equations; constraint-based analyses; recent SBML and SED-ML versions; exchange of results, and visualization of in silico experiments; open modeling exchange formats (COMBINE archives); hierarchically structured models; and compatibility with standard testing systems, including the Systems Biology Test Suite and published models from the BioModels and BiGG databases. AVAILABILITY AND IMPLEMENTATION: SBSCL is freely available at https://draeger-lab.github.io/SBSCL/ and via Maven Central. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.