Vegetation structure drives mosquito community composition in UK's largest managed lowland wetland.

PURPOSE: The rising burden of mosquito-borne diseases in Europe extends beyond urban areas, encompassing rural and semi-urban regions near managed and natural wetlands evidenced by recent outbreaks of Usutu and West Nile viruses. While wetland management policies focus on biodiversity and ecosystem services, few studies explore the impact on mosquito vectors. METHODS: Our research addresses this gap, examining juvenile mosquito and aquatic predator communities in 67 ditch sites within a South England coastal marsh subjected to different wetland management tiers. Using joint distribution models, we analyse how mosquito communities respond to abiotic and biotic factors influenced by wetland management. RESULTS: Of the 12 mosquito species identified, Culiseta annulata (Usutu virus vector) and Culex pipiens (Usutu and West Nile virus vector) constitute 47% of 6825 larval mosquitoes. Abundant predators include Coleoptera (water beetles) adults, Corixidae (water boatmen) and Zygoptera (Damselfy) larvae. Models reveal that tier 3 management sites (higher winter water levels, lower agricultural intensity) associated with shade and less floating vegetation are preferred by specific mosquito species. All mosquito species except Anopheles maculipennis s.l., are negatively impacted by potential predators. Culiseta annulata shows positive associations with shaded and turbid water, contrary to preferences of Corixidae predators. CONCLUSIONS: Tier 3 areas managed for biodiversity, characterised by higher seasonal water levels and reduced livestock grazing intensity, provide favourable habitats for key mosquito species that are known vectors of arboviruses, such as Usutu and West Nile. Our findings emphasise the impact of biodiversity-focused wetland management, altering mosquito breeding site vegetation to enhance vector suitability. Further exploration of these trade-offs is crucial for comprehending the broader implications of wetland management.

Phenotypic plasticity as a cause and consequence of population dynamics.

Predicting complex species-environment interactions is crucial for guiding conservation and mitigation strategies in a dynamically changing world. Phenotypic plasticity is a mechanism of trait variation that determines how individuals and populations adapt to changing and novel environments. For individuals, the effects of phenotypic plasticity can be quantified by measuring environment-trait relationships, but it is often difficult to predict how phenotypic plasticity affects populations. The assumption that environment-trait relationships validated for individuals indicate how populations respond to environmental change is commonly made without sufficient justification. Here we derive a novel general mathematical framework linking trait variation due to phenotypic plasticity to population dynamics. Applying the framework to the classical example of Nicholson's blowflies, we show how seemingly sensible predictions made from environment-trait relationships do not generalise to population responses. As a consequence, trait-based analyses that do not incorporate population feedbacks risk mischaracterising the effect of environmental change on populations.

A novel approach for predicting risk of vector-borne disease establishment in marginal temperate environments under climate change: West Nile virus in the UK.

Vector-borne diseases (VBDs), such as dengue, Zika, West Nile virus (WNV) and tick-borne encephalitis, account for substantial human morbidity worldwide and have expanded their range into temperate regions in recent decades. Climate change has been proposed as a likely driver of past and future expansion, however, the complex ecology of host and vector populations and their interactions with each other, environmental variables and land-use changes makes understanding the likely impacts of climate change on VBDs challenging. We present an environmentally driven, stage-structured, host-vector mathematical modelling framework to address this challenge. We apply our framework to predict the risk of WNV outbreaks in current and future UK climates. WNV is a mosquito-borne arbovirus which has expanded its range in mainland Europe in recent years. We predict that, while risks will remain low in the coming two to three decades, the risk of WNV outbreaks in the UK will increase with projected temperature rises and outbreaks appear plausible in the latter half of this century. This risk will increase substantially if increased temperatures lead to increases in the length of the mosquito biting season or if European strains show higher replication at lower temperatures than North American strains.

Eco-Epidemiological Uncertainties of Emerging Plant Diseases: The Challenge of Predicting Xylella fastidiosa Dynamics in Novel Environments.

In order to prevent and control the emergence of biosecurity threats such as vector-borne diseases of plants, it is vital to understand drivers of entry, establishment, and spatiotemporal spread, as well as the form, timing, and effectiveness of disease management strategies. An inherent challenge for policy in combatting emerging disease is the uncertainty associated with intervention planning in areas not yet affected, based on models and data from current outbreaks. Following the recent high-profile emergence of the bacterium Xylella fastidiosa in a number of European countries, we review the most pertinent epidemiological uncertainties concerning the dynamics of this bacterium in novel environments. To reduce the considerable ecological and socio-economic impacts of these outbreaks, eco-epidemiological research in a broader range of environmental conditions needs to be conducted and used to inform policy to enhance disease risk assessment, and support successful policy-making decisions. By characterizing infection pathways, we can highlight the uncertainties that surround our knowledge of this disease, drawing attention to how these are amplified when trying to predict and manage outbreaks in currently unaffected locations. To help guide future research and decision-making processes, we invited experts in different fields of plant pathology to identify data to prioritize when developing pest risk assessments. Our analysis revealed that epidemiological uncertainty is mainly driven by the large variety of hosts, vectors, and bacterial strains, leading to a range of different epidemiological characteristics further magnified by novel environmental conditions. These results offer new insights on how eco-epidemiological analyses can enhance understanding of plant disease spread and support management recommendations.[Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Sudden Cardiac Deaths in Adults with Congenital Heart Disease with Structural Abnormalities: A Retrospective Review of Cases in the Cook County Medical Examiner's Office.

Sudden cardiac death is a significant cause of mortality in adults with congenital heart disease (CHD). The Cook County Medical Examiner's Office database was queried for cases of CHD as a cause of death in the period between July 2008 and April 2019. Twenty-two cases were identified, including 11 decedents with simple defects and 10 decedents with complex defects. All of the subjects were in apparent good health at the time of death. In the absence of other obvious causes of death, simple defects were considered cases of sudden cardiac death. Significant cardiac morphological changes were common in complex defects. While 16 cases had known, diagnosed/treated CHD, 5 cases had no diagnosis prior to autopsy. In these cases, the ability to recognize CHD (sometimes subtle) helped in determining the causes of death. Therefore, forensic pathologists must be able to properly recognize various forms of CHD and request consultations, when needed.

Uncovering mechanisms behind mosquito seasonality by integrating mathematical models and daily empirical population data: Culex pipiens in the UK.

BACKGROUND: Many mosquito-borne diseases exhibit substantial seasonality, due to strong links between environmental variables and vector and pathogen life-cycles. Further, a range of density-dependent and density-independent biotic and abiotic processes affect the phenology of mosquito populations, with potentially large knock-on effects for vector dynamics and disease transmission. Whilst it is understood that density-independent and density-dependent processes affect seasonal population levels, it is not clear how these interact temporally to shape the population peaks and troughs. Due to this, the paucity of high-resolution data for validation, and the difficulty of parameterizing density-dependent processes, models of vector dynamics may poorly estimate abundances, which has knock-on effects for our ability predict vector-borne disease outbreaks. RESULTS: We present a rich dataset describing seasonal abundance patterns of each life stage of Culex pipiens, a widespread vector of West Nile virus, at a field site in southern England in 2015. Abundance of immature stages was measured three times per week, whilst adult traps were run four nights each week. This dataset is integrated with an existing delay-differential equation model predicting Cx. pipiens seasonal abundance to improve understanding of observed seasonal abundance patterns. At our field site, the outcome of our model fitting suggests interspecific predation on mosquito larvae and temperature-dependent larval mortality combine to act as the main sources of population regulation throughout the active season, whilst competition for resources is a relatively small source of larval mortality. CONCLUSIONS: The model suggests that density-independent mortality and interspecific predation interact to shape patterns of mosquito seasonal abundance in a permanent aquatic habitat and we propose that competition for resources is likely to be important where periods of high rainfall create transient habitats. Further, we highlight the importance of challenging population abundance models with data from across all life stages of the species of interest if reliable inferences are to be drawn from these models, particularly when considering mosquito control and vector-borne disease transmission.

Importance of Variant Interpretation in Whole-Exome Molecular Autopsy: Population-Based Case Series.

BACKGROUND: Potentially lethal cardiac channelopathies/cardiomyopathies may underlie a substantial portion of sudden unexplained death in the young (SUDY). The whole-exome molecular autopsy represents the latest approach to postmortem genetic testing for SUDY. However, proper variant adjudication in the setting of SUDY can be challenging. METHODS: From January 2012 through December 2013, 25 consecutive cases of SUDY from 1 to 40 years of age (average age at death 27±5.7 years; 13 white, 12 black) from Cook County, Illinois, were referred after a negative (n=16) or equivocal (n=9) conventional autopsy. A whole-exome molecular autopsy with analysis of 99 sudden death-susceptibility genes was performed. The predicted pathogenicity of ultrarare, nonsynonymous variants was determined using the American College of Medical Genetics guidelines. RESULTS: Overall, 27 ultrarare nonsynonymous variants were seen in 16/25 (64%) victims of SUDY. Among black individuals, 9/12 (75%) had an ultrarare nonsynonymous variant compared with 7/13 (54%) white individuals. Of the 27 variants, 10 were considered pathogenic or likely pathogenic in 7/25 (28%) individuals in accordance with the American College of Medical Genetics guidelines. Pathogenic/likely pathogenic variants were identified in 5/16 (31%) of autopsy-negative cases and in 2/6 (33%) victims of SUDY with equivocal findings of cardiomyopathy. Overall, 6 pathogenic/likely pathogenic variants in 4/25 (16%) cases were congruent with the phenotypic findings at autopsy and therefore considered clinically actionable. CONCLUSIONS: Whole-exome molecular autopsy with gene-specific surveillance is an effective approach for the detection of potential pathogenic variants in SUDY cases. However, systematic variant adjudication is crucial to ensure accurate and proper care for surviving family members.

Acute CD47 Blockade During Ischemic Myocardial Reperfusion Enhances Phagocytosis-Associated Cardiac Repair.

Our data suggest that, after a myocardial infarction, integrin-associated protein CD47 on cardiac myocytes is elevated. In culture, increased CD47 on the surface of dying cardiomyocytes impairs phagocytic removal by immune cell macrophages. After myocardial ischemia and reperfusion, acute CD47 inhibition with blocking antibodies enhanced dead myocyte clearance by cardiac phagocytes and also improved the resolution of cardiac inflammation, reduced infarct size, and preserved cardiac contractile function. Early targeting of CD47 in the myocardium after reperfusion may be a new strategy to enhance wound repair in the ischemic heart.

Mechanistic model for predicting the seasonal abundance of Culicoides biting midges and the impacts of insecticide control.

BACKGROUND: Understanding seasonal patterns of abundance of insect vectors is important for optimisation of control strategies of vector-borne diseases. Environmental drivers such as temperature, humidity and photoperiod influence vector abundance, but it is not generally known how these drivers combine to affect seasonal population dynamics. METHODS: In this paper, we derive and analyse a novel mechanistic stage-structured simulation model for Culicoides biting midges-the principle vectors of bluetongue and Schmallenberg viruses which cause mortality and morbidity in livestock and impact trade. We model variable life-history traits as functional forms that are dependent on environmental drivers, including air temperature, soil temperature and photoperiod. The model is fitted to Obsoletus group adult suction-trap data sampled daily at five locations throughout the UK for 2008. RESULTS: The model predicts population dynamics that closely resemble UK field observations, including the characteristic biannual peaks of adult abundance. Using the model, we then investigate the effects of insecticide control, showing that control strategies focussing on the autumn peak of adult midge abundance have the highest impact in terms of population reduction in the autumn and averaged over the year. Conversely, control during the spring peak of adult abundance leads to adverse increases in adult abundance in the autumn peak. CONCLUSIONS: The mechanisms of the biannual peaks of adult abundance, which are important features of midge seasonality in northern Europe and are key determinants of the risk of establishment and spread of midge-borne diseases, have been hypothesised over for many years. Our model suggests that the peaks correspond to two generations per year (bivoltine) are largely determined by pre-adult development. Furthermore, control strategies should focus on reducing the autumn peak since the immature stages are released from density-dependence regulation. We conclude that more extensive modelling of Culicoides biting midge populations in different geographical contexts will help to optimise control strategies and predictions of disease outbreaks.

Modelling the spread and control of Xylella fastidiosa in the early stages of invasion in Apulia, Italy.

Xylella fastidiosa is an important plant pathogen that attacks several plants of economic importance. Once restricted to the Americas, the bacterium, which causes olive quick decline syndrome, was discovered near Lecce, Italy in 2013. Since the initial outbreak, it has invaded 23,000 ha of olives in the Apulian Region, southern Italy, and is of great concern throughout Mediterranean basin. Therefore, predicting its spread and estimating the efficacy of control are of utmost importance. As data on this invasive infectious disease are poor, we have developed a spatially-explicit simulation model for X. fastidiosa to provide guidance for predicting spread in the early stages of invasion and inform management strategies. The model qualitatively and quantitatively predicts the patterns of spread. We model control zones currently employed in Apulia, showing that increasing buffer widths decrease infection risk beyond the control zone, but this may not halt the spread completely due to stochastic long-distance jumps caused by vector dispersal. Therefore, management practices should aim to reduce vector long-distance dispersal. We find optimal control scenarios that minimise control effort while reducing X. fastidiosa spread maximally-suggesting that increasing buffer zone widths should be favoured over surveillance efforts as control budgets increase. Our model highlights the importance of non-olive hosts which increase the spread rate of the disease and may lead to an order of magnitude increase in risk. Many aspects of X. fastidiosa disease invasion remain uncertain and hinder forecasting; we recommend future studies investigating quantification of the infection growth rate, and short and long distance dispersal.

A trait-based approach for predicting species responses to environmental change from sparse data: how well might terrestrial mammals track climate change?

Estimating population spread rates across multiple species is vital for projecting biodiversity responses to climate change. A major challenge is to parameterise spread models for many species. We introduce an approach that addresses this challenge, coupling a trait-based analysis with spatial population modelling to project spread rates for 15 000 virtual mammals with life histories that reflect those seen in the real world. Covariances among life-history traits are estimated from an extensive terrestrial mammal data set using Bayesian inference. We elucidate the relative roles of different life-history traits in driving modelled spread rates, demonstrating that any one alone will be a poor predictor. We also estimate that around 30% of mammal species have potential spread rates slower than the global mean velocity of climate change. This novel trait-space-demographic modelling approach has broad applicability for tackling many key ecological questions for which we have the models but are hindered by data availability.

Spreading speeds for plant populations in landscapes with low environmental variation.

Characterising the spread of biological populations is crucial in responding to both biological invasions and the shifting of habitat under climate change. Spreading speeds can be studied through mathematical models such as the discrete-time integro-difference equation (IDE) framework. The usual approach in implementing IDE models has been to ignore spatial variation in the demographic and dispersal parameters and to assume that these are spatially homogeneous. On the other hand, real landscapes are rarely spatially uniform with environmental variation being very important in determining biological spread. This raises the question of under what circumstances spatial structure need not be modelled explicitly. Recent work has shown that spatial variation can be ignored for the specific case where the scale of landscape variation is much smaller than the spreading population׳s dispersal scale. We consider more general types of landscape, where the spatial scales of environmental variation are arbitrarily large, but the maximum change in environmental parameters is relatively small. We find that the difference between the wave-speeds of populations spreading in a spatially structured periodic landscape and its homogenisation is, in general, proportional to ϵ(2), where ϵ governs the degree of environmental variation. For stochastically generated landscapes we numerically demonstrate that the error decays faster than ϵ. In both cases, this means that for sufficiently small ϵ, the homogeneous approximation is better than might be expected. Hence, in many situations, the precise details of the landscape can be ignored in favour of spatially homogeneous parameters. This means that field ecologists can use the homogeneous IDE as a relatively simple modelling tool--in terms of both measuring parameter values and doing the modelling itself. However, as ϵ increases, this homogeneous approximation loses its accuracy. The change in wave-speed due to the extrinsic (landscape) variation can be positive or negative, which is in contrast to the reduction in wave-speed caused by intrinsic stochasticity. To deal with the loss of accuracy as ϵ increases, we formulate a second-order approximation to the wave-speed for periodic landscapes and compare both approximations against the results of numerical simulation and show that they are both accurate for the range of landscapes considered.

The contrasting effects of genome size, chromosome number and ploidy level on plant invasiveness: a global analysis.

Understanding how species' traits relate to their status (e.g. invasiveness or rarity) is important because it can help to efficiently focus conservation and management effort and infer mechanisms affecting plant status. This is particularly important for invasiveness, in which proactive action is needed to restrict the establishment of potentially invasive plants. We tested the ability of genome size (DNA 1C-values) to explain invasiveness and compared it with cytogenetic traits (chromosome number and ploidy level). We considered 890 species from 62 genera, from across the angiosperm phylogeny and distributed from tropical to boreal latitudes. We show that invasiveness was negatively related to genome size and positively related to chromosome number (and ploidy level), yet there was a positive relationship between genome size and chromosome number; that is, our result was not caused by collinearity between the traits. Including both traits in explanatory models greatly increased the explanatory power of each. This demonstrates the potential unifying role that genome size, chromosome number and ploidy have as species' traits, despite the diverse impacts they have on plant physiology. It provides support for the continued cataloguing of cytogenetic traits and genome size of the world's flora.

Spreading speeds for stage structured plant populations in fragmented landscapes.

Landscape fragmentation has huge ecological and economic implications and affects the spatial dynamics of many plant species. Determining the speed of population spread in fragmented/heterogeneous landscapes is therefore of utmost importance to ecologists. Stage-structured integrodifference equations (IDEs) are deterministic models which accurately reflect the life cycles and dispersal patterns for numerous species. Existing approximations to wave-speeds consider only particular kernels, or landscapes in which the scale of variation is much smaller than the dispersal scale. We propose an analytical approximation to the wave-speeds of IDE solutions with periodic landscapes of alternating good and bad patches, where the dispersal scale is greater than the extent of each good patch and where the ratio of the demographic rates in the good and bad patches is given by a small parameter, denoted as ε. We formulate this approximation for the Gaussian and Laplace dispersal kernels and for stage structured and non-stage structured populations, and compare the results against numerical simulations. We find that the approximation is accurate for the landscapes considered, and that the type of dispersal kernel affects the relationship between landscape structure, as classified by landscape period and good patch size, and the spreading speed. This indicates that accurately fitting a kernel to data is important in determining the relationship between landscape structure and spreading speed.

Shox2 regulates the pacemaker gene program in embryoid bodies.

The pacemaker tissues of the heart are a complex set of specialized cells that initiate the rhythmic heartbeat. The sinoatrial node (SAN) serves as the primary pacemaker, whereas the atrioventricular node can serve as a subsidiary pacemaker in cases of SAN failure or block. The elucidation of genetic networks regulating the development of these tissues is crucial for understanding the mechanisms underlying arrhythmias and for the design of targeted therapies. Here we report temporal and spatial self-organized formation of the pacemaker and contracting tissues in three-dimensional aggregate cultures of mouse embryonic stem cells termed embryoid bodies (EBs). Using genetic marker expression and electrophysiological analyses we demonstrate that in EBs the pacemaker potential originates from a localized population of cells and propagates into the adjacent contracting region forming a functional syncytium. When Shox2, a major determinant of the SAN genetic pathway, was ablated we observed substantial slowing of spontaneous contraction rates and an altered gene expression pattern including downregulation of HCN4, Cx45, Tbx2, Tbx3, and bone morphogenetic protein 4 (BMP4); and upregulation of Cx40, Cx43, Nkx2.5, and Tbx5. This phenotype could be rescued by adding BMP4 to Shox2 knockout EBs in culture from days 6 to 16 of differentiation. When wild-type EBs were treated with Noggin, a potent BMP4 inhibitor, we observed a phenotype consistent with the Shox2 knockout EB. Altogether, we have generated a reproducible in vitro model that will be an invaluable tool for studying the molecular pathways regulating the development of cardiac pacemaker tissues.

Relating coupled map lattices to integro-difference equations: dispersal-driven instabilities in coupled map lattices.

Recently there has been a great deal of interest within the ecological community about the interactions of local populations that are coupled only by dispersal. Models have been developed to consider such scenarios but the theory needed to validate model outcomes has been somewhat lacking. In this paper, we present theory which can be used to understand these types of interaction when population exhibit discrete time dynamics. In particular, we consider a spatial extension to discrete-time models, known as coupled map lattices (CMLs) which are discrete in space. We introduce a general form of the CML and link this to integro-difference equations via a special redistribution kernel. General conditions are then derived for dispersal-driven instabilities. We then apply this theory to two discrete-time models; a predator-prey model and a host-pathogen model.

Applications of biological control in resistant host-pathogen systems.

Insect pest species can have devastating effects on crops. Control of these insect pests is usually achieved by using chemical insecticides. However, there has been much cause for concern with their overuse. Consequently, research has been carried out into alternative forms of control, in particular biological control methods. Recent laboratory studies have indicated that these natural forms of control can induce resistant strains of insect pest. In this paper we present a discrete-time host-pathogen model to describe the interaction between a host (insect species) that can develop a resistant strain and a pathogen (biological control) that can be externally applied to the system. For this model we use a single-state variable for the host population. We show that the proportion of resistance in the population impacts on the viability of the host population. Moreover, when the host population does persist, we explore the interaction between host susceptibility and host population levels. The different scenarios which arise are explained ecologically in terms of trade-offs in intrinsic growth rates, disease susceptibility and intraspecific host competition for the resistant subclass.

Embryonic stem cells form an organized, functional cardiac conduction system in vitro.

A functional pacemaking-conduction system is essential for maintaining normal cardiac function. However, no reproducible model system exists for studying the specialized cardiac pacemaking-conduction system in vitro. Although several molecular markers have been shown to delineate components of the cardiac conduction system in vivo, the functional characteristics of the cells expressing these markers remain unknown. The ability to accurately identify cells that function as cardiac pacemaking cells is crucial for being able to study their molecular phenotype. In differentiating murine embryonic stem cells, we demonstrate the development of an organized cardiac pacemaking-conduction system in vitro using the coexpression of the minK-lacZ transgene and the chicken GATA6 (cGATA6) enhancer. These markers identify clusters of pacemaking "nodes" that are functionally coupled with adjacent contracting regions. cGATA6-positive cell clusters spontaneously depolarize, emitting calcium signals to surrounding contracting regions. Physically separating cGATA6-positive cells from nearby contracting regions reduces the rate of spontaneous contraction or abolishes them altogether. cGATA6/minK copositive cells isolated from embryoid cells display characteristics of specialized pacemaking-conducting cardiac myocytes with regard to morphology, action potential waveform, and expression of a hyperpolarization-activated depolarizing current. Using the cGATA6 enhancer, we have isolated cells that exhibit electrophysiological and genetic properties of cardiac pacemaking myocytes. Using molecular markers, we have generated a novel model system that can be used to study the functional properties of an organized pacemaking-conducting contracting system in vitro. Moreover, we have used a molecular marker to isolate a renewable population of cells that exhibit characteristics of cardiac pacemaking myocytes.

Phosphatidylinositol 3-kinase inhibitors reveal a unique mechanism of enhancing insulin secretion in 832/13 rat insulinoma cells.

Hyperinsulinemia exists before the onset of overt type 2 diabetes mellitus. This response is at least partly due to enhanced insulin release from pancreatic beta-cells. Increased insulin secretion can be mimicked in vitro by acute culture of 832/13 rat insulinoma cells with phosphatidylinositol 3-kinase (PI-3K) inhibitors, a treatment that would theoretically simulate insulin resistance. We demonstrate in this study that while the PI-3K inhibitors Wortmannin and LY294002 both block Akt phosphorylation, only LY29002 significantly augments insulin secretion. LY294002 treatment potentiates insulin secretion over both basal and stimulatory glucose concentrations. This effect correlates with a significant increase in action potential duration. There was no change in resting or peak membrane potential under any of the treatment conditions, demonstrating that the cells remain healthy under the acute treatments used in this study. By contrast, Wortmannin has no effect on action potential duration. A partial explanation for these findings is that LY294002 potently inhibits voltage-dependent potassium channels, but does not affect voltage-gated calcium currents. We conclude that while PI-3K may play a role in regulating insulin secretion, there are diverse effects of the established inhibitors of this enzyme on beta-cell insulin secretory responses.

Cardiac physiology at the cellular level: use of cultured HL-1 cardiomyocytes for studies of cardiac muscle cell structure and function.

HL-1 cells are currently the only cardiomyocyte cell line available that continuously divides and spontaneously contracts while maintaining a differentiated cardiac phenotype. Extensive characterization using microscopic, genetic, immunohistochemical, electrophysiological, and pharmacological techniques has demonstrated how similar HL-1 cells are to primary cardiomyocytes. In the few years that HL-1 cells have been available, they have been used in a variety of model systems designed to answer important questions regarding cardiac biology at the cellular and molecular levels. Whereas HL-1 cells have been used to study normal cardiomyocyte function with regard to signaling, electrical, metabolic, and transcriptional regulation, they have also been used to address pathological conditions such as hypoxia, hyperglycemia-hyperinsulinemia, apoptosis, and ischemia-reperfusion. The availability of an immortalized, contractile cardiac cell line has provided investigators with a tool for probing the intricacies of cardiomyocyte function. In this review, we describe the culture and characterization of HL-1 cardiomyocytes as well as various model systems that have been developed using these cells to gain a better understanding of cardiac biology at the cellular and molecular levels.