Retrospective evaluation of postoperative joint immobilization using a temporary calcaneotibial screw for medial or lateral tarsocrural joint instability in dogs.

OBJECTIVE: To evaluate the use of a temporary calcaneotibial screw (CTS) to immobilize medial or lateral tarsocrural joint instability (TCI) in dogs. STUDY DESIGN: Retrospective study. ANIMALS: Twelve dogs (including five active working farm dogs) with TCI. METHODS: Medical records (January 2015-June 2023) were retrospectively reviewed for cases of TCI managed surgically including temporary joint immobilization using a CTS and external coaptation. Clinical data consisted of medical records and an online survey completed by the owner. RESULTS: Surgical techniques to address TCI included primary ligamentous repair, synthetic ligament reconstruction, or malleolar fracture repair. Immobilization with a CTS was employed for 6-8 weeks postoperatively. The online survey was completed for 10 dogs. All dogs exhibited good-to-excellent functional outcomes at the follow-up (median, 31 months; range, 4-66). All working farm dogs (5) were able to return to normal or substantial levels of their work. Four distinct complications were reported in three dogs including one CTS breakage and three bandage-related soft-tissue injuries. CONCLUSION: This retrospective study represents the first report of employing a temporary CTS for TCI in dogs. CLINICAL SIGNIFICANCE: A temporary CTS was effective in immobilizing the tarsocrural joint for dogs with TCI and the postoperative complication rate in this study was relatively low. A CTS screw and external coaptation is a viable alternative to previously reported methods of tarsocrural joint stabilization.

Functional and multi-omics signatures of mitapivat efficacy upon activation of pyruvate kinase in red blood cells from patients with sickle cell disease.

Mitapivat, a pyruvate kinase (PK) activator, shows great potential as a sickle cell disease (SCD)- modifying therapy. Safety and efficacy of mitapivat as a long-term maintenance therapy is currently being evaluated in two open-label studies. Here we apply a comprehensive multi-omics approach to investigate the impact of activating PK on red blood cells (RBCs) from 15 SCD patients. HbSS patients were enrolled in one of the open label, extended studies (NCT04610866). Leuko-depleted RBCs obtained from fresh whole blood at baseline (visit 1, V1), prior to drug initiation and longitudinal time points over the course of the study were processed for multiomics through a stepwise extraction of metabolites, lipids and proteins. Mitapivat therapy had significant effects on the metabolome, lipidome and proteome of SCD RBCs. Mitapivat decreased 2,3-diphosphoglycerate (DPG) levels, increased adenosine triphosphate (ATP) levels, and improved hematologic and sickling parameters in patients with SCD. Agreement between omics measurements and clinical measurements confirmed the specificity of mitapivat on targeting late glycolysis, with glycolytic metabolites ranking as the top correlates to parameters of hemoglobin S (HbS) oxygen affinity (p50) and sickling kinetics (t50) during treatment. Mitapivat markedly reduced levels of proteins of mitochondrial origin within 2 weeks of initiation of drug treatment, with minimal changes in the reticulocyte counts. The first six months of treatment also witnessed transient elevation of lysophosphatidylcholines and oxylipins with depletion in free fatty acids, suggestive of an effect on membrane lipid remodeling. Multi-omics analysis of RBCs identified benefits for glycolysis, as well as activation of the Lands cycle.

Towards a future regulatory framework for chemicals in the European Union - Chemicals 2.0.

The body of EU chemicals legislation has evolved since the 1960s, producing the largest knowledge base on chemicals worldwide. Like any evolving system, however, it has become increasingly diverse and complex, resulting in inefficiencies and potential inconsistencies. In the light of the EU Chemicals Strategy for Sustainability, it is therefore timely and reasonable to consider how aspects of the system could be simplified and streamlined, without losing the hard-earned benefits to human health and the environment. In this commentary, we propose a conceptual framework that could be the basis of Chemicals 2.0 - a future safety assessment and management approach that is based on the application of New Approach Methodologies (NAMs), mechanistic reasoning and cost-benefit considerations. Chemicals 2.0 is designed to be a more efficient and more effective approach for assessing chemicals, and to comply with the EU goal to completely replace animal testing, in line with Directive 2010/63/EU. We propose five design criteria for Chemicals 2.0 to define what the future system should achieve. The approach is centered on a classification matrix in which NAMs for toxicodynamics and toxicokinetics are used to classify chemicals according to their level of concern. An important principle is the need to ensure an equivalent, or higher, protection level.

An Overview of Physiologically-Based Pharmacokinetic Models for Forensic Science.

A physiologically-based pharmacokinetic (PBPK) model represents the structural components of the body with physiologically relevant compartments connected via blood flow rates described by mathematical equations to determine drug disposition. PBPK models are used in the pharmaceutical sector for drug development, precision medicine, and the chemical industry to predict safe levels of exposure during the registration of chemical substances. However, one area of application where PBPK models have been scarcely used is forensic science. In this review, we give an overview of PBPK models successfully developed for several illicit drugs and environmental chemicals that could be applied for forensic interpretation, highlighting the gaps, uncertainties, and limitations.

Computational modelling and simulation for immunotoxicity prediction induced by skin sensitisers.

In many domains regulating chemicals and chemical products, there is a legal requirement to determine skin sensitivity to allergens. While many in vitro assays to detect contact hypersensitivity have been developed as alternatives to animal testing over the past ten years and significant progress has been made in this area, there is still a need for continued investment in the creation of techniques and strategies that will allow accurate identification of potential contact allergens and their potency in vitro. In silico models are promising tools in this regard. However, none of the state-of-the-art systems seems to function well enough to serve as a stand-alone hazard identification tool, especially in evaluating the possible allergenicity effects in humans. The Universal Immune System Simulator, a mechanistic computational platform that simulates the human immune system response to a specific insult, provides a means of predicting the immunotoxicity induced by skin sensitisers, enriching the collection of computational models for the assessment of skin sensitization. Here, we present a specific disease layer implementation of the Universal Immune System Simulator for the prediction of allergic contact dermatitis induced by specific skin sensitizers.

Use of New Approach Methodologies (NAMs) in regulatory decisions for chemical safety: Report from an EPAA Deep Dive Workshop.

New Approach Methodologies (NAMs) are considered to include any in vitro, in silico or chemistry-based method, as well as the strategies to implement them, that may provide information that could inform chemical safety assessment. Current chemical legislation in the European Union is limited in its acceptance of the widespread use of NAMs. The European Partnership for Alternative Approaches to Animal Testing (EPAA) therefore convened a 'Deep Dive Workshop' to explore the use of NAMs in chemical safety assessment, the aim of which was to support regulatory decisions, whilst intending to protect human health. The workshop recognised that NAMs are currently used in many industrial sectors, with some considered as fit for regulatory purpose. Moreover, the workshop identified key discussion points that can be addressed to increase the use and regulatory acceptance of NAMs. These are based on the changes needed in frameworks for regulatory requirements and the essential needs in education, training and greater stakeholder engagement as well the gaps in the scientific basis of NAMs.

A scheme to evaluate structural alerts to predict toxicity - Assessing confidence by characterising uncertainties.

Structure-activity relationships (SARs) in toxicology have enabled the formation of structural rules which, when coded as structural alerts, are essential tools in in silico toxicology. Whilst other in silico methods have approaches for their evaluation, there is no formal process to assess the confidence that may be associated with a structural alert. This investigation proposes twelve criteria to assess the uncertainty associated with structural alerts, allowing for an assessment of confidence. The criteria are based around the stated purpose, description of the chemistry, toxicology and mechanism, performance and coverage, as well as corroborating and supporting evidence of the alert. Alerts can be given a confidence assessment and score, enabling the identification of areas where more information may be beneficial. The scheme to evaluate structural alerts was placed in the context of various use cases for industrial and regulatory applications. The analysis of alerts, and consideration of the evaluation scheme, identifies the different characteristics an alert may have, such as being highly specific or generic. These characteristics may determine when an alert can be used for specific uses such as identification of analogues for read-across or hazard identification.

Accuracy of Lumbosacral Pedicle Screw Placement in Dogs: A Novel 3D Printed Patient-Specific Drill Guide versus Freehand Technique in Novice and Expert Surgeons.

OBJECTIVE: The aim of this study was to compare the accuracy of pedicle screw placement at the canine lumbosacral junction using a novel unilateral three-dimensional printed patient-specific guide (3D-PSG) versus a freehand drilling technique. Additionally, accuracy of screw placement between a novice and an experienced surgeon was determined. STUDY DESIGN: Preoperative computed tomography images from 20 lumbosacral cadaveric specimens were used to design a novel unilateral 3D-PSG for the L7 and sacral vertebrae which was printed in acryl-nitrile butadiene styrene plastic. A novice and an expert surgeon each placed 3.5mm cortical screws in 10 cadavers; on the left using the unilateral 3D-PSG and by the freehand (anatomic landmark) technique on the right. RESULTS: Sixty screws were placed using the unilateral 3D-PSG and 60 using the freehand technique. There was no statistical difference in accuracy for the comparison between methods performed by the expert (p = 0.679) and novice (p = 0.761) surgeon, nor between an expert and novice surgeon overall (p = 0.923). Unexpectedly, the use of a unilateral 3D-PSG increased variability for the expert surgeon in our study (p = 0.0314). CONCLUSION: Using a novel unilateral 3D-PSG did not improve the accuracy of screw placement for lumbosacral stabilization by a novice surgeon compared with an expert surgeon in lumbar spine surgery. This may reflect a suboptimal PSG design.

Translatability and transferability of in silico models: Context of use switching to predict the effects of environmental chemicals on the immune system.

Immunotoxicity hazard identification of chemicals aims to evaluate the potential for unintended effects of chemical exposure on the immune system. Perfluorinated alkylate substances (PFAS), such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persistent, globally disseminated environmental contaminants known to be immunotoxic. Elevated PFAS exposure is associated with lower antibody responses to vaccinations in children and in adults. In addition, some studies have reported a correlation between PFAS levels in the body and lower resistance to disease, in other words an increased risk of infections or cancers. In this context, modelling and simulation platforms could be used to simulate the human immune system with the aim to evaluate the adverse effects that immunotoxicants may have. Here, we show the conditions under which a mathematical model developed for one purpose and application (e.g., in the pharmaceutical domain) can be successfully translated and transferred to another (e.g., in the chemicals domain) without undergoing significant adaptation. In particular, we demonstrate that the Universal Immune System Simulator was able to simulate the effects of PFAS on the immune system, introducing entities and new interactions that are biologically involved in the phenomenon. This also revealed a potentially exploitable pathway for assessing immunotoxicity through a computational model.

Extension of the Virtual Cell Based Assay from a 2-D to a 3-D Cell Culture Model.

Prediction of chemical toxicity is very useful in risk assessment. With the current paradigm shift towards the use of in vitro and in silico systems, we present herein a theoretical mathematical description of a quasi-diffusion process to predict chemical concentrations in 3-D spheroid cell cultures. By extending a 2-D Virtual Cell Based Assay (VCBA) model into a 3-D spheroid cell model, we assume that cells are arranged in a series of concentric layers within the sphere. We formulate the chemical quasi-diffusion process by simplifying the spheroid with respect to the number of cells in each layer. The system was calibrated and tested with acetaminophen (APAP). Simulated predictions of APAP toxicity were compared with empirical data from in vitro measurements by using a 3-D spheroid model. The results of this first attempt to extend the VCBA model are promising - they show that the VCBA model simulates close correlation between the influence of compound concentration and the viability of the HepaRG 3-D cell culture. The 3-D VCBA model provides a complement to current in vitro procedures to refine experimental setups, to fill data gaps and help in the interpretation of in vitro data for the purposes of risk assessment.

A matter of trust: Learning lessons about causality will make qAOPs credible.

Toxicology in the 21st Century has seen a shift from chemical risk assessment based on traditional animal tests, identifying apical endpoints and doses that are "safe", to the prospect of Next Generation Risk Assessment based on non-animal methods. Increasingly, large and high throughput in vitro datasets are being generated and exploited to develop computational models. This is accompanied by an increased use of machine learning approaches in the model building process. A potential problem, however, is that such models, while robust and predictive, may still lack credibility from the perspective of the end-user. In this commentary, we argue that the science of causal inference and reasoning, as proposed by Judea Pearl, will facilitate the development, use and acceptance of quantitative AOP models. Our hope is that by importing established concepts of causality from outside the field of toxicology, we can be "constructively disruptive" to the current toxicological paradigm, using the "Causal Revolution" to bring about a "Toxicological Revolution" more rapidly.

Towards a qAOP framework for predictive toxicology - Linking data to decisions.

The adverse outcome pathway (AOP) is a conceptual construct that facilitates organisation and interpretation of mechanistic data representing multiple biological levels and deriving from a range of methodological approaches including in silico, in vitro and in vivo assays. AOPs are playing an increasingly important role in the chemical safety assessment paradigm and quantification of AOPs is an important step towards a more reliable prediction of chemically induced adverse effects. Modelling methodologies require the identification, extraction and use of reliable data and information to support the inclusion of quantitative considerations in AOP development. An extensive and growing range of digital resources are available to support the modelling of quantitative AOPs, providing a wide range of information, but also requiring guidance for their practical application. A framework for qAOP development is proposed based on feedback from a group of experts and three qAOP case studies. The proposed framework provides a harmonised approach for both regulators and scientists working in this area.

Probabilistic modelling of developmental neurotoxicity based on a simplified adverse outcome pathway network.

In a century where toxicology and chemical risk assessment are embracing alternative methods to animal testing, there is an opportunity to understand the causal factors of neurodevelopmental disorders such as learning and memory disabilities in children, as a foundation to predict adverse effects. New testing paradigms, along with the advances in probabilistic modelling, can help with the formulation of mechanistically-driven hypotheses on how exposure to environmental chemicals could potentially lead to developmental neurotoxicity (DNT). This investigation aimed to develop a Bayesian hierarchical model of a simplified AOP network for DNT. The model predicted the probability that a compound induces each of three selected common key events (CKEs) of the simplified AOP network and the adverse outcome (AO) of DNT, taking into account correlations and causal relations informed by the key event relationships (KERs). A dataset of 88 compounds representing pharmaceuticals, industrial chemicals and pesticides was compiled including physicochemical properties as well as in silico and in vitro information. The Bayesian model was able to predict DNT potential with an accuracy of 76%, classifying the compounds into low, medium or high probability classes. The modelling workflow achieved three further goals: it dealt with missing values; accommodated unbalanced and correlated data; and followed the structure of a directed acyclic graph (DAG) to simulate the simplified AOP network. Overall, the model demonstrated the utility of Bayesian hierarchical modelling for the development of quantitative AOP (qAOP) models and for informing the use of new approach methodologies (NAMs) in chemical risk assessment.

In Silico Models for Predicting Acute Systemic Toxicity.

In this chapter, we give a brief overview of the regulatory requirements for acute systemic toxicity information in the European Union, and we review structure-based computational models that are available and potentially useful in the assessment of acute systemic toxicity. Emphasis is placed on quantitative structure-activity relationship (QSAR) models implemented by means of a range of software tools. The most recently published literature models for acute systemic toxicity are also discussed, and perspectives for future developments in this field are offered.

Settling dynamics of nanoparticles in simple and biological media.

The biological response of organisms exposed to nanoparticles is often studied in vitro using adherent monolayers of cultured cells. In order to derive accurate concentration-response relationships, it is important to determine the local concentration of nanoparticles to which the cells are actually exposed rather than the nominal concentration of nanoparticles in the cell culture medium. In this study, the sedimentation-diffusion process of different sized and charged gold nanoparticles has been investigated in vitro by evaluating their settling dynamics and by developing a theoretical model to predict the concentration depth profile of nanoparticles in solution over time. Experiments were carried out in water and in cell culture media at a range of controlled temperatures. The optical phenomenon of caustics was exploited to track nanoparticles in real time in a conventional optical microscope without any requirement for fluorescent labelling that potentially affects the dynamics of the nanoparticles. The results obtained demonstrate that size, temperature and the stability of the nanoparticles play a pivotal role in regulating the settling dynamics of nanoparticles. For gold nanoparticles larger than 60 nm in diameter, the initial nominal concentration did not accurately represent the concentration of nanoparticles local to the cells. Finally, the theoretical model proposed accurately described the settling dynamics of the nanoparticles and thus represents a promising tool to support the design of in vitro experiments and the study of concentration-response relationships.

Combining in vitro assays and mathematical modelling to study developmental neurotoxicity induced by chemical mixtures.

Prenatal and postnatal co-exposure to multiple chemicals at the same time may have deleterious effects on the developing nervous system. We previously showed that chemicals acting through similar mode of action (MoA) and grouped based on perturbation of brain derived neurotrophic factor (BDNF), induced greater neurotoxic effects on human induced pluripotent stem cell (hiPSC)-derived neurons and astrocytes compared to chemicals with dissimilar MoA. Here we assessed the effects of repeated dose (14 days) treatments with mixtures containing the six chemicals tested in our previous study (Bisphenol A, Chlorpyrifos, Lead(II) chloride, Methylmercury chloride, PCB138 and Valproic acid) along with 2,2'4,4'-tetrabromodiphenyl ether (BDE47), Ethanol, Vinclozolin and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)), on hiPSC-derived neural stem cells undergoing differentiation toward mixed neurons/astrocytes up to 21 days. Similar MoA chemicals in mixtures caused an increase of BDNF levels and neurite outgrowth, and a decrease of synapse formation, which led to inhibition of electrical activity. Perturbations of these endpoints are described as common key events in adverse outcome pathways (AOPs) specific for DNT. When compared with mixtures tested in our previous study, adding similarly acting chemicals (BDE47 and EtOH) to the mixture resulted in a stronger downregulation of synapses. A synergistic effect on some synaptogenesis-related features (PSD95 in particular) was hypothesized upon treatment with tested mixtures, as indicated by mathematical modelling. Our findings confirm that the use of human iPSC-derived mixed neuronal/glial models applied to a battery of in vitro assays anchored to key events in DNT AOP networks, combined with mathematical modelling, is a suitable testing strategy to assess in vitro DNT induced by chemical mixtures.

Assessment of the predictive capacity of a physiologically based kinetic model using a read-across approach.

With current progress in science, there is growing interest in developing and applying Physiologically Based Kinetic (PBK) models in chemical risk assessment, as knowledge of internal exposure to chemicals is critical to understanding potential effects in vivo. In particular, a new generation of PBK models is being developed in which the model parameters are derived from in silico and in vitro methods. To increase the acceptance and use of these "Next Generation PBK models", there is a need to demonstrate their validity. However, this is challenging in the case of data-poor chemicals that are lacking in kinetic data and for which predictive capacity cannot, therefore, be assessed. The aim of this work is to lay down the fundamental steps in using a read across framework to inform modellers and risk assessors on how to develop, or evaluate, PBK models for chemicals without in vivo kinetic data. The application of a PBK model that takes into account the absorption, distribution, metabolism and excretion characteristics of the chemical reduces the uncertainties in the biokinetics and biotransformation of the chemical of interest. A strategic flow-charting application, proposed herein, allows users to identify the minimum information to perform a read-across from a data-rich chemical to its data-poor analogue(s). The workflow analysis is illustrated by means of a real case study using the alkenylbenzene class of chemicals, showing the reliability and potential of this approach. It was demonstrated that a consistent quantitative relationship between model simulations could be achieved using models for estragole and safrole (source chemicals) when applied to methyleugenol (target chemical). When the PBK model code for the source chemicals was adapted to utilise input values relevant to the target chemical, simulation was consistent between the models. The resulting PBK model for methyleugenol was further evaluated by comparing the results to an existing, published model for methyleugenol, providing further evidence that the approach was successful. This can be considered as a "read-across" approach, enabling a valid PBK model to be derived to aid the assessment of a data poor chemical.

Gaining acceptance in next generation PBK modelling approaches for regulatory assessments - An OECD international effort.

Physiologically Based Kinetic (PBK) models are valuable tools to help define safe external levels of chemicals based on internal doses at target organs in experimental animals, humans and organisms used in environmental risk assessment. As the toxicity testing paradigm shifts to alternative testing approaches, PBK model development has started to rely (mostly or entirely) on model parameters quantified using in vitro or in silico methods. Recently, the Organisation for Economic Cooperation and Development (OECD) published a guidance document (GD) describing a scientific workflow for characterising and validating PBK models developed using in vitro and in silico data. The GD provides an assessment framework for evaluating these models, with emphasis on the major uncertainties underlying model inputs and outputs. To help end-users submit or evaluate a PBK model for regulatory purposes, the GD also includes a template for documenting the model characteristics, and a checklist for evaluating the quality of a model. This commentary highlights the principles, criteria and tools laid out in the OECD PBK model GD, with the aim of facilitating the dialogue between model developers and risk assessors.

Current EU regulatory requirements for the assessment of chemicals and cosmetic products: challenges and opportunities for introducing new approach methodologies.

The EU Directive 2010/63/EU   on the protection of animals used for scientific purposes and other EU regulations, such as REACH and the Cosmetic Products Regulation advocate for a change in the way toxicity testing is conducted. Whilst the Cosmetic Products Regulation bans animal testing altogether, REACH aims for a progressive shift from in vivo testing towards quantitative in vitro and computational approaches. Several endpoints can already be addressed using non-animal approaches including skin corrosion and irritation, serious eye damage and irritation, skin sensitisation, and mutagenicity and genotoxicity. However, for systemic effects such as acute toxicity, repeated dose toxicity and reproductive and developmental toxicity, evaluation of chemicals under REACH still heavily relies on animal tests. Here we summarise current EU regulatory requirements for the human health assessment of chemicals under REACH and the Cosmetic Products Regulation, considering the more critical endpoints and identifying the main challenges in introducing alternative methods into regulatory testing practice. This supports a recent initiative taken by the International Cooperation on Alternative Test Methods (ICATM) to summarise current regulatory requirements specific for the assessment of chemicals and cosmetic products for several human health-related endpoints, with the aim of comparing different jurisdictions and coordinating the promotion and ultimately the implementation of non-animal approaches worldwide. Recent initiatives undertaken at European level to promote the 3Rs and the use of alternative methods in current regulatory practice are also discussed.