The role of NFI-C liver regeneration and its potential function as a general regulator of regenerative processes

Collectively, research aimed to understand the regeneration of certain tissues has unveiled the existence of common key regulators. Knockout studies of the murine Nuclear Factor I-C (NFI-C) transcription factor revealed a misregulation of growth factor signaling, in particular that of transforming growth factor ß-1 (TGF-ßl), which led to alterations of skin wound healing and the growth of its appendages, suggesting it may be a general regulator of regenerative processes. We sought to investigate this further by determining whether NFI-C played a role in liver regeneration. Liver regeneration following two-thirds removal of the liver by partial hepatectomy (PH) is a well-established regenerative model whereby changes elicited in hepatocytes following injury lead to a rapid, phased proliferation. However, mechanisms controlling the action of liver proliferative factors such as transforming growth factor-ßl (TGF-ß1) and plasminogen activator inhibitor-1 (PAI-1) remain largely unknown. We show that the absence of NFI-C impaired hepatocyte proliferation due to an overexpression of PAI-1 and the subsequent suppression of urokinase plasminogen (uPA) activity and hepatocyte growth factor (HGF) signaling, a potent hepatocyte mitogen. This indicated that NFI-C first acts to promote hepatocyte proliferation at the onset of liver regeneration in wildtype mice. The subsequent transient down regulation of NFI-C, as can be explained by a self- regulatory feedback loop with TGF-ßl, may limit the number of hepatocytes entering the first wave of cell division and/or prevent late initiations of mitosis. Overall, we conclude that NFI-C acts as a regulator of the phased hepatocyte proliferation during liver regeneration. Taken together with NFI-C's actions in other in vivo models of (re)generation, it is plausible that NFI-C may be a general regulator of regenerative processes. - L'ensemble des recherches visant à comprendre la régénération de certains tissus a permis de mettre en évidence l'existence de régulateurs-clés communs. L'étude des souris, dépourvues du gène codant pour le facteur de transcription NFI-C (Nuclear Factor I-C), a montré des dérèglements dans la signalisation de certains facteurs croissance, en particulier du TGF-ßl (transforming growth factor-ßl), ce qui conduit à des altérations de la cicatrisation de la peau et de la croissance des poils et des dents chez ces souris, suggérant que NFI-C pourrait être un régulateur général du processus de régénération. Nous avons cherché à approfondir cette question en déterminant si NFI-C joue un rôle dans la régénération du foie. La régénération du foie, induite par une hépatectomie partielle correspondant à l'ablation des deux-tiers du foie, constitue un modèle de régénération bien établi dans lequel la lésion induite conduit à la prolifération rapide des hépatocytes de façon synchronisée. Cependant, les mécanismes contrôlant l'action de facteurs de prolifération du foie, comme le facteur de croissance TGF-ßl et l'inhibiteur de l'activateur du plasminogène PAI-1 (plasminogen activator inhibitor-1), restent encore très méconnus. Nous avons pu montrer que l'absence de NFI-C affecte la prolifération des hépatocytes, occasionnée par la surexpression de PAI-1 et par la subséquente suppression de l'activité de la protéine uPA (urokinase plasminogen) et de la signalisation du facteur de croissance des hépatocytes HGF (hepatocyte growth factor), un mitogène puissant des hépatocytes. Cela indique que NFI-C agit en premier lieu pour promouvoir la prolifération des hépatocytes au début de la régénération du foie chez les souris de type sauvage. La subséquente baisse transitoire de NFI-C, pouvant s'expliquer par une boucle rétroactive d'autorégulation avec le facteur TGF-ßl, pourrait limiter le nombre d'hépatocytes qui entrent dans la première vague de division cellulaire et/ou inhiber l'initiation de la mitose tardive. L'ensemble de ces résultats nous a permis de conclure que NFI-C agit comme un régulateur de la prolifération des hépatocytes synchrones au cours de la régénération du foie.

Dynamic models of viral replication and latency.

PURPOSE OF REVIEW: HIV targets primary CD4(+) T cells. The virus depends on the physiological state of its target cells for efficient replication, and, in turn, viral infection perturbs the cellular state significantly. Identifying the virus-host interactions that drive these dynamic changes is important for a better understanding of viral pathogenesis and persistence. The present review focuses on experimental and computational approaches to study the dynamics of viral replication and latency. RECENT FINDINGS: It was recently shown that only a fraction of the inducible latently infected reservoirs are successfully induced upon stimulation in ex-vivo models while additional rounds of stimulation make allowance for reactivation of more latently infected cells. This highlights the potential role of treatment duration and timing as important factors for successful reactivation of latently infected cells. The dynamics of HIV productive infection and latency have been investigated using transcriptome and proteome data. The cellular activation state has shown to be a major determinant of viral reactivation success. Mathematical models of latency have been used to explore the dynamics of the latent viral reservoir decay. SUMMARY: Timing is an important component of biological interactions. Temporal analyses covering aspects of viral life cycle are essential for gathering a comprehensive picture of HIV interaction with the host cell and untangling the complexity of latency. Understanding the dynamic changes tipping the balance between success and failure of HIV particle production might be key to eradicate the viral reservoir.

The ciliary smooth muscle electrotransfer: basic principles and potential for sustained intraocular production of therapeutic proteins.

BACKGROUND: We have developed a nonviral gene therapy method based on the electrotransfer of plasmid in the ciliary muscle. These easily accessible smooth muscle cells could be turned into a biofactory for any therapeutic proteins to be secreted in a sustained manner in the ocular media. METHODS: Electrical conditions, design of electrodes, plasmid formulation, method and number of injections were optimized in vivo in the rat by localizing β-galactosidase expression and quantifying reporter (luciferase) and therapeutic (anti-tumor necrosis factor) proteins secretion in the ocular media. Anatomical measurements were performed via human magnetic resonance imaging to design a human eye-sized prototype that was tested in the rabbit. RESULTS: In the rat, transscleral injection of 30 µg of plasmid diluted in half saline (77 mM NaCl) followed by application of eight square-wave electrical pulses (15 V, 10 ms, 5.3 Hz) using two platinum/iridium electrodes, an internal wire and an external sheet, delivered plasmid efficiently to the ciliary muscle fibers. Gene transfer resulted in a long-lasting (at least 5 months) and plasmid dose-/injection number- dependent secretion of different molecular weight proteins mainly in the vitreous, without any systemic exposure. Because ciliary muscle anatomical measurements remained constant among ages in adult humans, an integrated device comprising needle-electrodes was designed and manufactured. Its usefulness was validated in the rabbit. CONCLUSIONS: Plasmid electrotransfer to the ciliary muscle with a suitable medical device represents a promising local and sustained protein delivery system for treating posterior segment diseases, avoiding repeated intraocular injections.

Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula.

The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system comprised two closely related species of Alpine Primula. We used species distribution models based on the extant distribution of the species and last glacial maximum (LGM) climate models to predict the distribution of the two species during the LGM. Phylogeographic data were generated using amplified fragment length polymorphisms (AFLPs). In Primula hirsuta, models of past distribution and phylogeographic data are partly congruent and support the hypothesis of widespread nunatak survival in the Central Alps. Species distribution models (SDMs) allowed us to differentiate between alpine regions that harbor potential nunatak areas and regions that have been colonized from other areas. SDMs revealed that diversity is a good indicator for nunataks, while rarity is a good indicator for peripheral relict populations that were not source for the recolonization of the inner Alps. In P. daonensis, palaeo-distribution models and phylogeographic data are incongruent. Besides the uncertainty inherent to this type of modeling approach (e.g., relatively coarse 1-km grain size), disagreement of models and data may partly be caused by shifts of ecological niche in both species. Nevertheless, we demonstrate that the combination of palaeo-distribution modeling with phylogeographical approaches provides a more differentiated picture of the distributional history of species and partly supports (P. hirsuta) and partly modifies (P. daonensis and P. hirsuta) hypotheses of Quaternary distributional history. Some of the refugial area indicated by palaeodistribution models could not have been identified with phylogeographic data.

Circadian regulation of renal function and potential role in hypertension.

PURPOSE OF REVIEW: Previous studies have shown that a variety of specific renal functions exhibit circadian oscillations. This review aims to provide an update on the molecular mechanisms underlying circadian rhythms in the kidney, and to discuss how dysregulation of circadian rhythms can interfere with kidney function. RECENT FINDINGS: The molecular mechanism responsible for generating and maintaining circadian rhythms has been unraveled in great detail. This mechanism, known as the circadian clock, drives circadian oscillation in expression levels of a large number of renal mRNA transcripts. Several proteins critically involved in renal homeostatic functions have been shown to exhibit significant circadian oscillation in their expression levels or in their posttranslational modifications. In transgenic mouse models, disruption of circadian clock activity results in dramatic changes in the circadian pattern of urinary sodium and potassium excretion and causes significant changes in arterial blood pressure. A growing amount of evidence suggests that dysregulation of circadian rhythms is associated with the development of hypertension and accelerated progression of chronic kidney disease and cardiovascular disease in humans. Chronotherapy studies have shown that the efficacy of antihypertensive medication is greatly dependent on the circadian time of drug administration. SUMMARY: Recent research points to the major role of circadian rhythms in renal function and in control of blood pressure.

Effects of alternative sets of climatic predictors on species distribution models and associated estimates of extinction risk: a test with plants in an arid environment

Aim To evaluate the effects of using distinct alternative sets of climatic predictor variables on the performance, spatial predictions and future projections of species distribution models (SDMs) for rare plants in an arid environment. . Location Atacama and Peruvian Deserts, South America (18º30'S - 31º30'S, 0 - 3 000 m) Methods We modelled the present and future potential distributions of 13 species of Heliotropium sect. Cochranea, a plant group with a centre of diversity in the Atacama Desert. We developed and applied a sequential procedure, starting from climate monthly variables, to derive six alternative sets of climatic predictor variables. We used them to fit models with eight modelling techniques within an ensemble forecasting framework, and derived climate change projections for each of them. We evaluated the effects of using these alternative sets of predictor variables on performance, spatial predictions and projections of SDMs using Generalised Linear Mixed Models (GLMM). Results The use of distinct sets of climatic predictor variables did not have a significant effect on overall metrics of model performance, but had significant effects on present and future spatial predictions. Main conclusion Using different sets of climatic predictors can yield the same model fits but different spatial predictions of current and future species distributions. This represents a new form of uncertainty in model-based estimates of extinction risk that may need to be better acknowledged and quantified in future SDM studies.

Anemia and chronic kidney disease are potential risk factors for mortality in stroke patients: a historic cohort study.

BACKGROUND: Chronic kidney disease (CKD) is associated to a higher stroke risk. Anemia is a common consequence of CKD, and is also a possible risk factor for cerebrovascular diseases. The purpose of this study was to examine if anemia and CKD are independent risk factors for mortality after stroke. METHODS: This historic cohort study was based on a stroke registry and included patients treated for a first clinical stroke in the stroke unit of one academic hospital over a three-year period. Mortality predictors comprised demographic characteristics, CKD, glomerular filtration rate (GFR), anemia and other stroke risk factors. GFR was estimated by means of the simplified Modification of Diet in Renal Disease formula. Renal function was assessed according to the Kidney Disease Outcomes Quality Initiative (K/DOQI)-CKD classification in five groups. A value of hemoglobin < 120 g/L in women and < 130 g/L in men on admission defined anemia. Kaplan-Meier survival curves and Cox models were used to describe and analyze one-year survival. RESULTS: Among 890 adult stroke patients, the mean (Standard Deviation) calculated GFR was 64.3 (17.8) ml/min/1.73 m2 and 17% had anemia. Eighty-two (10%) patients died during the first year after discharge. Among those, 50 (61%) had K/DOQI CKD stages 3 to 5 and 32 (39%) stages 1 or 2 (p < 0.001). Anemia was associated with an increased risk of death one year after discharge (p < 0.001). After adjustment for other factors, a higher hemoglobin level was independently associated with decreased mortality one year after discharge [hazard ratio (95% CI) 0.98 (0.97-1.00)]. CONCLUSIONS: Both CKD and anemia are frequent among stroke patients and are potential risk factors for decreased one-year survival. The inclusion of patients with a first-ever clinical stroke only and the determination of anemia based on one single measure, on admission, constitute limitations to the external validity. We should investigate if an early detection and management of both CKD and anemia could improve survival in stroke patients.

CD4+CD25+Foxp3+ regulatory T cells: from basic research to potential therapeutic use.

Regulatory T cells control immune responses to self- and foreign-antigens and play a major role in maintaining the balance between immunity and tolerance. This article reviews recent key developments in the field of CD4+CD25+Foxp3+ regulatory T (TREG) cells. It presents their characteristics and describes their range of activity and mechanisms of action. Some models of diseases triggered by the imbalance between TREG cells and effector pathogenic T cells are described and their potential therapeutic applications in humans are outlined.

Application of theoretical models to financial innovation

The present paper is aimed at providing a general strategic overview of the existing theoretical models that have applications in the field of financial innovation. Whereas most financialdevelopments have relied upon traditional economic tools, a new stream of research is defining a novel paradigm in which mathematical models from diverse scientific disciplines are being applied to conceptualize and explain economic and financial behavior. Indeed, terms such as ‘econophysics’ or ‘quantum finance’ have recently appeared to embrace efforts in this direction. As a first contact with such research, the project will present a brief description of some of the main theoretical models that have applications in finance and economics, and will try to present, if possible, potential new applications to particular areas in financial analysis, or new applicable models. As a result, emphasiswill be put on the implications of this research for the financial sector and its future dynamics.

Introduction of snow and geomorphic disturbance variables into predictive models of alpine plant distribution in the Western Swiss Alps

Indirect topographic variables have been used successfully as surrogates for disturbance processes in plant species distribution models (SDM) in mountain environments. However, no SDM studies have directly tested the performance of disturbance variables. In this study, we developed two disturbance variables: a geomorphic index (GEO) and an index of snow redistribution by wind (SNOW). These were developed in order to assess how they improved both the fit and predictive power of presenceabsence SDM based on commonly used topoclimatic (TC) variables for 91 plants in the Western Swiss Alps. The individual contribution of the disturbance variables was compared to TC variables. Maps of models were prepared to spatially test the effect of disturbance variables. On average, disturbance variables significantly improved the fit but not the predictive power of the TC models and their individual contribution was weak (5.6% for GEO and 3.3% for SNOW). However their maximum individual contribution was important (24.7% and 20.7%). Finally, maps including disturbance variables (i) were significantly divergent from TC models in terms of predicted suitable surfaces and connectivity between potential habitats, and (ii) were interpreted as more ecologically relevant. Disturbance variables did not improve the transferability of models at the local scale in a complex mountain system, and the performance and contribution of these variables were highly species-specific. However, improved spatial projections and change in connectivity are important issues when preparing projections under climate change because the future range size of the species will determine the sensitivity to changing conditions.

A critical evaluation of secondary cancer risk models applied to Monte Carlo dose distributions of 2-dimensional, 3-dimensional conformal and hybrid intensity-modulated radiation therapy for breast cancer.

The comparison of radiotherapy techniques regarding secondary cancer risk has yielded contradictory results possibly stemming from the many different approaches used to estimate risk. The purpose of this study was to make a comprehensive evaluation of different available risk models applied to detailed whole-body dose distributions computed by Monte Carlo for various breast radiotherapy techniques including conventional open tangents, 3D conformal wedged tangents and hybrid intensity modulated radiation therapy (IMRT). First, organ-specific linear risk models developed by the International Commission on Radiological Protection (ICRP) and the Biological Effects of Ionizing Radiation (BEIR) VII committee were applied to mean doses for remote organs only and all solid organs. Then, different general non-linear risk models were applied to the whole body dose distribution. Finally, organ-specific non-linear risk models for the lung and breast were used to assess the secondary cancer risk for these two specific organs. A total of 32 different calculated absolute risks resulted in a broad range of values (between 0.1% and 48.5%) underlying the large uncertainties in absolute risk calculation. The ratio of risk between two techniques has often been proposed as a more robust assessment of risk than the absolute risk. We found that the ratio of risk between two techniques could also vary substantially considering the different approaches to risk estimation. Sometimes the ratio of risk between two techniques would range between values smaller and larger than one, which then translates into inconsistent results on the potential higher risk of one technique compared to another. We found however that the hybrid IMRT technique resulted in a systematic reduction of risk compared to the other techniques investigated even though the magnitude of this reduction varied substantially with the different approaches investigated. Based on the epidemiological data available, a reasonable approach to risk estimation would be to use organ-specific non-linear risk models applied to the dose distributions of organs within or near the treatment fields (lungs and contralateral breast in the case of breast radiotherapy) as the majority of radiation-induced secondary cancers are found in the beam-bordering regions.

In vivo brain macromolecule signals in healthy and glioblastoma mouse models: (1) H magnetic resonance spectroscopy, post-processing and metabolite quantification at 14.1 T.

In (1) H magnetic resonance spectroscopy, macromolecule signals underlay metabolite signals, and knowing their contribution is necessary for reliable metabolite quantification. When macromolecule signals are measured using an inversion-recovery pulse sequence, special care needs to be taken to correctly remove residual metabolite signals to obtain a pure macromolecule spectrum. Furthermore, since a single spectrum is commonly used for quantification in multiple experiments, the impact of potential macromolecule signal variability, because of regional differences or pathologies, on metabolite quantification has to be assessed. In this study, we introduced a novel method to post-process measured macromolecule signals that offers a flexible and robust way of removing residual metabolite signals. This method was applied to investigate regional differences in the mouse brain macromolecule signals that may affect metabolite quantification when not taken into account. However, since no significant differences in metabolite quantification were detected, it was concluded that a single macromolecule spectrum can be generally used for the quantification of healthy mouse brain spectra. Alternatively, the study of a mouse model of human glioma showed several alterations of the macromolecule spectrum, including, but not limited to, increased mobile lipid signals, which had to be taken into account to avoid significant metabolite quantification errors.

Use of niche models in invasive species risk assessments.

Risk maps summarizing landscape suitability of novel areas for invading species can be valuable tools for preventing species' invasions or controlling their spread, but methods employed for development of such maps remain variable and unstandardized. We discuss several considerations in development of such models, including types of distributional information that should be used, the nature of explanatory variables that should be incorporated, and caveats regarding model testing and evaluation. We highlight that, in the case of invasive species, such distributional predictions should aim to derive the best hypothesis of the potential distribution of the species by using (1) all distributional information available, including information from both the native range and other invaded regions; (2) predictors linked as directly as is feasible to the physiological requirements of the species; and (3) modelling procedures that carefully avoid overfitting to the training data. Finally, model testing and evaluation should focus on well-predicted presences, and less on efficient prediction of absences; a k-fold regional cross-validation test is discussed.

Active strain and activation models in cardiac electromechanics

We present a model for mechanical activation of the cardiac tissue depending on the evolution of the transmembrane electrical potential and certain gating/ionic variables that are available in most of electrophysiological descriptions of the cardiac membrane. The basic idea consists in adding to the chosen ionic model one ordinary differential equation for the kinetics of the mechanical activation function. A relevant example illustrates the desired properties of the proposed model, such as delayed muscle contraction and correct magnitude of the muscle fibers' shortening.

Effects of sample size on the performance of species distribution models

A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.