Murine models of colorectal cancer: studying the role of oncogenic K-<Emphasis Type="Italic">ras</Emphasis>

Cancers of the intestine are amongst the most frequent tumors in the Western countries. They arise through the stepwise, progressive disruption of cellular signalling cascades which control cell proliferation, survival and differentiation. The proto-oncogene K-ras functions as an important molecular switch linking several of these signalling pathways. Activating mutations of K-ras are found in about 50% of colorectal cancers, but their contribution to tumor initiation and progression is still poorly understood. Murine models provide excellent opportunities to identify and define the roles of genes involved in cancer formation and growth in the digestive tract. In this review, I will discuss the biological properties of oncogenic K-ras, its influence on cell signalling and its role in colorectal tumorigenesis based on recently established murine models.     

Evidence for mimicry by viral antigens in animal models of autoimmune disease including myocarditis

Molecular mimicry of viral antigens with self determinants has been proposed as one of the pathogenic mechanisms in autoimmune disease. Evidence of viral mimicry in animal models of autoimmunity is accumulating. Murine adenovirus, Semliki forest virus, lactate dehydrogenase-elevating virus, herpes simplex virus type-1, hepatitis B virus, encephalomyocarditis virus, Theiler's murine encephalomyelitis virus, Coxsackievirus and cytomegalovirus have been found to mimic physiologically important host proteins. However, epitope homology of a viral and self determinant is not in itself strong evidence for mimicry as a pathogenic mechanism. The mimicking determinant must also be capable of inducing disease in the absence of replicative virus. Animal models provide evaluation of the viral trigger, and development and therapy for autoimmune diseases. Identification of host proteins that can induce disease together with the knowledge of immune system dysregulation, genetic association and environmental factors may lead to improved immunotherapeutic strategies for human autoimmune diseases.     

Aneuploidy in the normal and diseased brain

The brain is remarkable for its complex organization and functions, which have been historically assumed to arise from cells with identical genomes. However, recent studies have shown that the brain is in fact a complex genetic mosaic of aneuploid and euploid cells. The precise function of neural aneuploidy and mosaicism are currently being examined on multiple fronts that include contributions to cellular diversity, cellular signaling and diseases of the central nervous system (CNS). Constitutive aneuploidy in genetic diseases has proven roles in brain dysfunction, as observed in Down syndrome (trisomy 21) and mosaic variegated aneuploidy. The existence of aneuploid cells within normal individuals raises the possibility that these cells might have distinct functions in the normal and diseased brain, the latter contributing to sporadic CNS disorders including cancer. Here we review what is known about neural aneuploidy, and offer speculations on its role in diseases of the brain. Received 13 April 2006; received after revision 2 June 2006; accepted 13 July 2006     

Explanation,understanding, and unrealistic models

How can false models be explanatory? And how can they help us to understand the way the world works? Sometimes scientists have little hope of building models that approximate the world they observe. Even in such cases, I argue, the models they build can have explanatory import. The basic idea is that scientists provide causal explanations of why the regularity entailed by an abstract and idealized model fails to obtain. They do so by relaxing some of its unrealistic assumptions. This method of ‘explanation by relaxation’ captures the explanatory import of some important models in economics. I contrast this method with the accounts that Daniel Hausman and Nancy Cartwright have provided of explanation in economics. Their accounts are unsatisfactory because they require that the economic model regularities obtain, which is rarely the case. I go on to argue that counterfactual regularities play a central role in achieving ‘understanding by relaxation.’ This has a surprising implication for the relation between explanation and understanding: Achieving scientific understanding does not require the ability to explain observed regularities.     

Cell culture models and animal models for studying the patho-physiological role of renal aquaporins

Aquaporins (AQPs) are key players regulating urinary-concentrating ability. To date, eight aquaporins have been characterized and localized along the nephron, namely, AQP1 located in the proximal tubule, thin descending limb of Henle, and vasa recta; AQP2, AQP3 and AQP4 in collecting duct principal cells; AQP5 in intercalated cell type B; AQP6 in intercalated cells type A in the papilla; AQP7, AQP8 and AQP11 in the proximal tubule. AQP2, whose expression and cellular distribution is dependent on vasopressin stimulation, is involved in hereditary and acquired diseases affecting urine-concentrating mechanisms. Due to the lack of selective aquaporin inhibitors, the patho-physiological role of renal aquaporins has not yet been completely clarified, and despite extensive studies, several questions remain unanswered. Until the recent and large-scale development of genetic manipulation technology, which has led to the generation of transgenic mice models, our knowledge on renal aquaporin regulation was mainly based on in vitro studies with suitable renal cell models. Transgenic and knockout technology approaches are providing pivotal information on the role of aquaporins in health and disease. The main goal of this review is to update and summarize what we can learn from cell and animal models that will shed more light on our understanding of aquaporin-dependent renal water regulation.     

How could models possibly provide how-possibly explanations?

One puzzle concerning highly idealized models is whether they explain. Some suggest they provide so-called ‘how-possibly explanations’. However, this raises an important question about the nature of how-possibly explanations, namely what distinguishes them from ‘normal’, or how-actually, explanations? I provide an account of how-possibly explanations that clarifies their nature in the context of solving the puzzle of model-based explanation. I argue that the modal notions of actuality and possibility provide the relevant dividing lines between how-possibly and how-actually explanations. Whereas how-possibly explanations establish claims of possible explanations, how-actually explanations establish claims of actual ones. Models, in turn, simply provide evidence for these claims.     

Metabolic circuits in neural stem cells

Metabolic activity indicative of cellular demand is emerging as a key player in cell fate decision. Numerous studies have demonstrated that diverse metabolic pathways have a critical role in the control of the proliferation, differentiation and quiescence of stem cells. The identification of neural stem/progenitor cells (NSPCs) and the characterization of their development and fate decision process have provided insight into the regenerative potential of the adult brain. As a result, the potential of NSPCs in cell replacement therapies for neurological diseases is rapidly growing. The aim of this review is to discuss the recent findings on the crosstalk among key regulators of NSPC development and the metabolic regulation crucial for the function and cell fate decisions of NSPCs. Fundamental understanding of the metabolic circuits in NSPCs may help to provide novel approaches for reactivating neurogenesis to treat degenerative brain conditions and cognitive decline.     

ARARMA models for time series analysis and forecasting

Methods of time series forecasting are proposed which can be applied automatically. However, they are not rote formulae, since they are based on a flexible philosophy which can provide several models for consideration. In addition it provides diverse diagnostics for qualitatively and quantitatively estimating how well one can forecast a series. The models considered are called ARARMA models (or ARAR models) because the model fitted to a long memory time series (t) is based on sophisticated time series analysis of AR (or ARMA) schemes (short memory models) fitted to residuals Y(t) obtained by parsimonious‘best lag’non-stationary autoregression. Both long range and short range forecasts are provided by an ARARMA model Section 1 explains the philosophy of our approach to time series model identification. Sections 2 and 3 attempt to relate our approach to some standard approaches to forecasting; exponential smoothing methods are developed from the point of view of prediction theory (section 2) and extended (section 3). ARARMA models are introduced (section 4). Methods of ARARMA model fitting are outlined (sections 5,6). Since‘the proof of the pudding is in the eating’, the methods proposed are illustrated (section 7) using the classic example of international airline passengers.     

Human heart disease: lessons from human pluripotent stem cell-derived cardiomyocytes

Technical advances in generating and phenotyping cardiomyocytes from human pluripotent stem cells (hPSC-CMs) are now driving their wider acceptance as in vitro models to understand human heart disease and discover therapeutic targets that may lead to new compounds for clinical use. Current literature clearly shows that hPSC-CMs recapitulate many molecular, cellular, and functional aspects of human heart pathophysiology and their responses to cardioactive drugs. Here, we provide a comprehensive overview of hPSC-CMs models that have been described to date and highlight their most recent and remarkable contributions to research on cardiovascular diseases and disorders with cardiac traits. We conclude discussing immediate challenges, limitations, and emerging solutions.     

Subjective intervention in formal models

Success in forecasting using mathematical/statistical models requires that the models be open to intervention by the user. In practice, a model is only one component of a forecasting system, which also includes the users/forecasters as integral components. Interaction between the user and the model is necessary to adequately cater for events and changes that go beyond the existing form of the model. In this paper we consider Bayesian forecasting models open to interventions, of essentially any form, to incorporate subjective information made available to the user. We discuss principles of intervention and derive theoretical results that provide the means to formally incorporate feedforward interventions into Bayesian models. Two example time series are considered to illustrate why and when such interventions may be necessary to sustain predictive performance.     

Animal models in burn research

Burn injury is a severe form of trauma affecting more than 2 million people in North America each year. Burn trauma is not a single pathophysiological event but a devastating injury that causes structural and functional deficits in numerous organ systems. Due to its complexity and the involvement of multiple organs, in vitro experiments cannot capture this complexity nor address the pathophysiology. In the past two decades, a number of burn animal models have been developed to replicate the various aspects of burn injury, to elucidate the pathophysiology, and to explore potential treatment interventions. Understanding the advantages and limitations of these animal models is essential for the design and development of treatments that are clinically relevant to humans. This review aims to highlight the common animal models of burn injury in order to provide investigators with a better understanding of the benefits and limitations of these models for translational applications. While many animal models of burn exist, we limit our discussion to the skin healing of mouse, rat, and pig. Additionally, we briefly explain hypermetabolic characteristics of burn injury and the animal model utilized to study this phenomena. Finally, we discuss the economic costs associated with each of these models in order to guide decisions of choosing the appropriate animal model for burn research.     

Models and the dynamics of theory-building in physics. Part I—Modeling strategies

A deeper understanding of models is sought in considering what models do, rather what they are. This distinction emphasizes how two different modeling strategies, as they pursue different purposes, do invest in different options, in particular in regard to rigor and immediate empirical relevance. The analysis focuses therefore on the services expected from models by the scientists who construct them: models are sought for how they contribute to exploring and testing the context in which they operate. In a forthcoming Part II these general considerations will be anchored in the presentation of specific case studies.     

Daily volatility forecasts: reassessing the performance of GARCH models

Volatility plays a key role in asset and portfolio management and derivatives pricing. As such, accurate measures and good forecasts of volatility are crucial for the implementation and evaluation of asset and derivative pricing models in addition to trading and hedging strategies. However, whilst GARCH models are able to capture the observed clustering effect in asset price volatility in‐sample, they appear to provide relatively poor out‐of‐sample forecasts. Recent research has suggested that this relative failure of GARCH models arises not from a failure of the model but a failure to specify correctly the ‘true volatility’ measure against which forecasting performance is measured. It is argued that the standard approach of using ex post daily squared returns as the measure of ‘true volatility’ includes a large noisy component. An alternative measure for ‘true volatility’ has therefore been suggested, based upon the cumulative squared returns from intra‐day data. This paper implements that technique and reports that, in a dataset of 17 daily exchange rate series, the GARCH model outperforms smoothing and moving average techniques which have been previously identified as providing superior volatility forecasts. Copyright © 2004 John Wiley & Sons, Ltd.     

Role of gut microbiota in aging-related health decline: insights from invertebrate models

Studies in mammals, including humans, have reported age-related changes in microbiota dynamics. A major challenge, however, is to dissect the cause and effect relationships involved. Invertebrate model organisms such as the fruit fly Drosophila and the nematode Caenorhabditis elegans have been invaluable in studies of the biological mechanisms of aging. Indeed, studies in flies and worms have resulted in the identification of a number of interventions that can slow aging and prolong life span. In this review, we discuss recent work using invertebrate models to provide insight into the interplay between microbiota dynamics, intestinal homeostasis during aging and life span determination. An emerging theme from these studies is that the microbiota contributes to cellular and physiological changes in the aging intestine and, in some cases, age-related shifts in microbiota dynamics can drive health decline in aged animals.     

Neuronal ciliary signaling in homeostasis and disease

Primary cilia are a class of cilia that are typically solitary, immotile appendages present on nearly every mammalian cell type. Primary cilia are believed to perform specialized sensory and signaling functions that are important for normal development and cellular homeostasis. Indeed, primary cilia dysfunction is now linked to numerous human diseases and genetic disorders. Collectively, primary cilia disorders are termed as ciliopathies and present with a wide range of clinical features, including cystic kidney disease, retinal degeneration, obesity, polydactyly, anosmia, intellectual disability, and brain malformations. Although significant progress has been made in elucidating the functions of primary cilia on some cell types, the precise functions of most primary cilia remain unknown. This is particularly true for primary cilia on neurons throughout the mammalian brain. This review will introduce primary cilia and ciliary signaling pathways with a focus on neuronal cilia and their putative functions and roles in human diseases.     

Regulation of oligodendrocyte precursor migration during development, in adulthood and in pathology

Oligodendrocytes are the myelin-forming cells in the central nervous system (CNS). These cells originate from oligodendrocyte precursor cells (OPCs) during development, and they migrate extensively from oligodendrogliogenic niches along the neural tube to colonise the entire CNS. Like many other such events, this migratory process is precisely regulated by a battery of positional and signalling cues that act via their corresponding receptors and that are expressed dynamically by OPCs. Here, we will review the cellular and molecular basis of this important event during embryonic and postnatal development, and we will discuss the relevance of the substantial number of OPCs existing in the adult CNS. Similarly, we will consider the behaviour of OPCs in normal and pathological conditions, especially in animal models of demyelination and of the demyelinating disease, multiple sclerosis. The spontaneous remyelination observed after damage in demyelinating pathologies has a limited effect. Understanding the cellular and molecular mechanisms underlying the biology of OPCs, particularly adult OPCs, should help in the design of neuroregenerative strategies to combat multiple sclerosis and other demyelinating diseases.     

How to form and close the brain: insight into the mechanism of cranial neural tube closure in mammals

The development of the embryonic brain critically depends on successfully completing cranial neural tube closure (NTC). Failure to properly close the neural tube results in significant and potentially lethal neural tube defects (NTDs). We believe these malformations are caused by disruptions in normal developmental programs such as those involved in neural plate morphogenesis and patterning, tissue fusion, and coordinated cell behaviors. Cranial NTDs include anencephaly and craniorachischisis, both lethal human birth defects. Newly emerging methods for molecular and cellular analysis offer a deeper understanding of not only the developmental NTC program itself but also mechanical and kinetic aspects of closure that may contribute to cranial NTDs. Clarifying the underlying mechanisms involved in NTC and how they relate to the onset of specific NTDs in various experimental models may help us develop novel intervention strategies to prevent NTDs.     

Variance estimation for multivariate dynamic linear models

The problem of estimating unknown observational variances in multivariate dynamic linear models is considered. Conjugate procedures are possible for univariate models and also for special very restrictive common components models but they are not generally applicable. However, for clarity of operation and in order to avoid numerical integration, it is desirable to have conjugacy or approximate conjugacy. Such an approximate procedure is proposed based upon a simple analytic approximation. It is exact for the sub-class of conjugate models and improves on a previous procedure based upon the Robust filter.     

Crosstalk between cerebral endothelium and oligodendrocyte

It is now relatively well accepted that the cerebrovascular system does not merely provide inert pipes for blood delivery to the brain. Cerebral endothelial cells may compose an embedded bunker of trophic factors that contribute to brain homeostasis and function. Recent findings suggest that soluble factors from cerebral endothelial cells nourish neighboring cells, such as neurons and astrocytes. Although data are strongest in supporting mechanisms of endothelial-neuron and/or endothelial-astrocyte trophic coupling, it is likely that similar interactions also exist between cerebral endothelial cells and oligodendrocyte lineage cells. In this mini-review, we summarize current advances in the field of endothelial-oligodendrocyte trophic coupling. These endothelial-oligodendrocyte interactions may comprise the oligovascular niche to maintain their cellular functions and sustain ongoing angiogenesis/oligodendrogenesis. Importantly, it should be noted that the cell–cell interactions are not static—the trophic coupling is disturbed under acute phase after brain injury, but would be recovered in the chronic phase to promote brain remodeling and repair. Oligodendrocyte lineage cells play critical roles in white matter function, and under pathological conditions, oligodendrocyte dysfunction lead to white matter damage. Therefore, a deeper understanding of the mechanisms of endothelial-oligodendrocyte trophic coupling may lead to new therapeutic approaches for white matter-related diseases, such as stroke or vascular dementia.     

The emerging link between O-GlcNAcylation and neurological disorders

O-linked β-N-acetylglucosaminylation (O-GlcNAcylation) is involved in the regulation of many cellular cascades and neurological diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and stroke. In the brain, the expression of O-GlcNAcylation is notably heightened, as is that of O-linked N-acetylglucosaminyltransferase (OGT) and β-N-acetylglucosaminidase (OGA), the presence of which is prominent in many regions of neurological importance. Most importantly, O-GlcNAcylation is believed to contribute to the normal functioning of neurons; conversely, its dysregulation participates in the pathogenesis of neurological disorders. In neurodegenerative diseases, O-GlcNAcylation of the brain’s key proteins, such as tau and amyloid-β, interacts with their phosphorylation, thereby triggering the formation of neurofibrillary tangles and amyloid plaques. An increase of O-GlcNAcylation by pharmacological intervention prevents neuronal loss. Additionally, O-GlcNAcylation is stress sensitive, and its elevation is cytoprotective. Increased O-GlcNAcylation ameliorated brain damage in victims of both trauma-hemorrhage and stroke. In this review, we summarize the current understanding of O-GlcNAcylation’s physiological and pathological roles in the nervous system and provide a foundation for development of a therapeutic strategy for neurological disorders.