Background: Hypoxia inducible factor-α (HIF-α) is the main transcription factor activated in low oxygen conditions.Results: Single cell imaging reveals pulses in nuclear levels of HIF-α.Conclusion: The transient nature of the HIF-α nuclear accumulation is required to avoid cell death.Significance: The duration of HIF-α response depends on cellular oxygenation, and can encode information and dictate cell fate.

Xenobiotic safety assessment is an area that impacts a multitude of different industry sectors such as medicinal drugs, agrochemicals, industrial chemicals, cosmetics and environmental contaminants. As such there are a number of well-developed in vitro, in vivo and in silico approaches to evaluate their properties and potential impact on the environment and to humans. Additionally, there is the continual investment in multidisciplinary scientists to explore non-animal surrogate technologies to predict specific toxicological outcomes and to improve our understanding of the biological processes regarding the toxic potential of xenobiotics. Here we provide a concise, critical evaluation of a number of in vitro systems utilised to assess the hepatotoxic potential of xenobiotics.

Many in vitro liver cell models, such as 2D systems, that are used to assess the hepatotoxic potential of xenobiotics suffer major limitations arising from a lack of preservation of physiological phenotype and metabolic competence. To circumvent some of these limitations there has been increased focus on producing more representative 3D models. Here we have used a novel approach to construct a size-controllable 3D hepatic spheroid model using freshly isolated primary rat hepatocytes (PRH) utilising the liquid-overlay technique whereby PRH spontaneously self-assemble in to 3D microtissues. This system produces viable spheroids with a compact in vivo -like structure for up to 21 days with sustained albumin production for the duration of the culture period. F-actin was seen throughout the spheroid body and P-glycoprotein (P-gp) and multidrug resistance-associated protein 2 (MRP2) transporters had polarised expression on the canalicular membrane of hepatocytes within the spheroids upon formation (day 3). The MRP2 transporter was able to functionally transport 5 μM 5-chloromethylfluorescein diacetate (CMFDA) substrates into these canalicular structures. These PRH spheroids display in vivo characteristics including direct cell-cell contacts, cellular polarisation, 3D cellular morphology, and formation of functional secondary structures throughout the spheroid. Such a well-characterised system could be readily exploited for pre-clinical and non-clinical repeat-dose investigations and could make a significant contribution to replace, reduce and refine the use of animals for applied research.

In early preclinical drug development, potential candidates are tested in the laboratory using isolated cells. These in vitro experiments traditionally involve cells cultured in a two-dimensional monolayer environment. However, cells cultured in three-dimensional spheroid systems have been shown to more closely resemble the functionality and morphology of cells in vivo . While the increasing usage of hepatic spheroid cultures allows for more relevant experimentation in a more realistic biological environment, the underlying physical processes of drug transport, uptake and metabolism contributing to the spatial distribution of drugs in these spheroids remain poorly understood. The development of a multiscale mathematical modelling framework describing the spatio-temporal dynamics of drugs in multicellular environments enables mechanistic insight into the behaviour of these systems. Here, our analysis of cell membrane permeation and porosity throughout the spheroid reveals the impact of these properties on drug penetration, with maximal disparity between zonal metabolism rates occurring for drugs of intermediate lipophilicity. Our research shows how mathematical models can be used to simulate the activity and transport of drugs in hepatic spheroids and in principle any organoid, with the ultimate aim of better informing experimentalists on how to regulate dosing and culture conditions to more effectively optimize drug delivery.

The development of improved, innovative models for the detection of toxicity of drugs, chemicals, or chemicals in cosmetics is crucial to efficiently bring new products safely to market in a cost-effective and timely manner. In addition, improvement in models to detect toxicity may reduce the incidence of unexpected post-marketing toxicity and reduce or eliminate the need for animal testing. The safety of novel products of the pharmaceutical, chemical, or cosmetics industry must be assured; therefore, toxicological properties need to be assessed. Accepted methods for gathering the information required by law for approval of substances are often animal methods. To reduce, refine, and replace animal testing, innovative organotypic in vitro models have emerged. Such models appear at different levels of complexity ranging from simpler, self-organized three-dimensional (3D) cell cultures up to more advanced scaffold-based co-cultures consisting of multiple cell types. This review provides an overview of recent developments in the field of toxicity testing with in vitro models for three major organ types: heart, skin, and liver. This review also examines regulatory aspects of such models in Europe and the UK, and summarizes best practices to facilitate the acceptance and appropriate use of advanced in vitro models.

Paracetamol (acetaminophen (APAP)) is one of the most commonly used analgesics in the United Kingdom and the United States. However, exceeding the maximum recommended dose can cause serious liver injury and even death. Promising APAP toxicity biomarkers are thought to add value to those used currently and clarification of the functional relationships between these biomarkers and liver injury would aid clinical implementation of an improved APAP toxicity identification framework. The framework currently used to define an APAP overdose is highly dependent upon time since ingestion and initial dose; information that is often highly unpredictable. A pharmacokinetic/pharmacodynamic (PK/PD) APAP model has been built in order to understand the relationships between a panel of biomarkers and APAP dose. Visualization and statistical tools have been used to predict initial APAP dose and time since administration. Additionally, logistic regression analysis has been applied to histology data to provide a prediction of the probability of liver injury.

The effect of climate change on the spatiotemporal dynamics of malaria transmission is studied using an unprecedented ensemble of climate projections, employing three diverse bias correction and downscaling techniques, in order to partially account for uncertainty in climate-driven malaria projections. These large climate ensembles drive two dynamical and spatially explicit epidemiological malaria models to provide future hazard projections for the focus region of eastern Africa. While the two malaria models produce very distinct transmission patterns for the recent climate, their response to future climate change is similar in terms of sign and spatial distribution, with malaria transmission moving to higher altitudes in the East African Community (EAC) region, while transmission reduces in lowland, marginal transmission zones such as South Sudan. The climate model ensemble generally projects warmer and wetter conditions over EAC. The simulated malaria response appears to be driven by temperature rather than precipitation effects. This reduces the uncertainty due to the climate models, as precipitation trends in tropical regions are very diverse, projecting both drier and wetter conditions with the current state-of-the-art climate model ensemble. The magnitude of the projected changes differed considerably between the two dynamical malaria models, with one much more sensitive to climate change, highlighting that uncertainty in the malaria projections is also associated with the disease modelling approach.

Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.