Reverse transcription quantitative real-time polymerase chain reaction reference genes in the spared nerve injury model of neuropathic pain: validation and literature search.

BACKGROUND: The reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a widely used, highly sensitive laboratory technique to rapidly and easily detect, identify and quantify gene expression. Reliable RT-qPCR data necessitates accurate normalization with validated control genes (reference genes) whose expression is constant in all studied conditions. This stability has to be demonstrated.We performed a literature search for studies using quantitative or semi-quantitative PCR in the rat spared nerve injury (SNI) model of neuropathic pain to verify whether any reference genes had previously been validated. We then analyzed the stability over time of 7 commonly used reference genes in the nervous system - specifically in the spinal cord dorsal horn and the dorsal root ganglion (DRG). These were: Actin beta (Actb), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal proteins 18S (18S), L13a (RPL13a) and L29 (RPL29), hypoxanthine phosphoribosyltransferase 1 (HPRT1) and hydroxymethylbilane synthase (HMBS). We compared the candidate genes and established a stability ranking using the geNorm algorithm. Finally, we assessed the number of reference genes necessary for accurate normalization in this neuropathic pain model. RESULTS: We found GAPDH, HMBS, Actb, HPRT1 and 18S cited as reference genes in literature on studies using the SNI model. Only HPRT1 and 18S had been once previously demonstrated as stable in RT-qPCR arrays. All the genes tested in this study, using the geNorm algorithm, presented gene stability values (M-value) acceptable enough for them to qualify as potential reference genes in both DRG and spinal cord. Using the coefficient of variation, 18S failed the 50% cut-off with a value of 61% in the DRG. The two most stable genes in the dorsal horn were RPL29 and RPL13a; in the DRG they were HPRT1 and Actb. Using a 0.15 cut-off for pairwise variations we found that any pair of stable reference gene was sufficient for the normalization process. CONCLUSIONS: In the rat SNI model, we validated and ranked Actb, RPL29, RPL13a, HMBS, GAPDH, HPRT1 and 18S as good reference genes in the spinal cord. In the DRG, 18S did not fulfill stability criteria. The combination of any two stable reference genes was sufficient to provide an accurate normalization.

Concepts of metastasis in flux: the stromal progression model.

The ability of tumor cells to leave a primary tumor, to disseminate through the body, and to ultimately seed new secondary tumors is universally agreed to be the basis for metastasis formation. An accurate description of the cellular and molecular mechanisms that underlie this multistep process would greatly facilitate the rational development of therapies that effectively allow metastatic disease to be controlled and treated. A number of disparate and sometimes conflicting hypotheses and models have been suggested to explain various aspects of the process, and no single concept explains the mechanism of metastasis in its entirety or encompasses all observations and experimental findings. The exciting progress made in metastasis research in recent years has refined existing ideas, as well as giving rise to new ones. In this review we survey some of the main theories that currently exist in the field, and show that significant convergence is emerging, allowing a synthesis of several models to give a more comprehensive overview of the process of metastasis. As a result we postulate a stromal progression model of metastasis. In this model, progressive modification of the tumor microenvironment is equally as important as genetic and epigenetic changes in tumor cells during primary tumor progression. Mutual regulatory interactions between stroma and tumor cells modify the stemness of the cells that drive tumor growth, in a manner that involves epithelial-mesenchymal and mesenchymal-epithelial-like transitions. Similar interactions need to be recapitulated at secondary sites for metastases to grow. Early disseminating tumor cells can progress at the secondary site in parallel to the primary tumor, both in terms of genetic changes, as well as progressive development of a metastatic stroma. Although this model brings together many ideas in the field, there remain nevertheless a number of major open questions, underscoring the need for further research to fully understand metastasis, and thereby identify new and effective ways of treating metastatic disease.

Determination of extreme floods using a distributed hydrological model

Hydrological models developed for extreme precipitation of PMP type are difficult to calibrate because of the scarcity of available data for these events. This article presents the process and results of calibration for a distributed hydrological model at fine scale developed for the estimation of probable maximal floods in the case of a PMP. This calibration is done on two Swiss catchments for two events of summer storms. The calculation done is concentrated on the estimation of the parameters of the model, divided in two parts. The first is necessary for the computation of flow speeds while the second is required for the determination of the initial and final infiltration capacities for each terrain type. The results, validated with the Nash equation show a good correlation between the simulated and observed flows. We also apply this model on two Romanian catchments, showing the river network and estimated flow.

Differential vulnerability of neurochemically identified subpopulations of retinal neurons in a monkey model of glaucoma.

The vulnerability of subpopulations of retinal neurons delineated by their content of cytoskeletal or calcium-binding proteins was evaluated in the retinas of cynomolgus monkeys in which glaucoma was produced with an argon laser. We quantitatively compared the number of neurons containing either neurofilament (NF) protein, parvalbumin, calbindin or calretinin immunoreactivity in central and peripheral portions of the nasal and temporal quadrants of the retina from glaucomatous and fellow non-glaucomatous eyes. There was no significant difference between the proportion of amacrine, horizontal and bipolar cells labeled with antibodies to the calcium-binding proteins comparing the two eyes. NF triplet immunoreactivity was present in a subpopulation of retinal ganglion cells, many of which, but not all, likely correspond to large ganglion cells that subserve the magnocellular visual pathway. Loss of NF protein-containing retinal ganglion cells was widespread throughout the central (59-77% loss) and peripheral (96-97%) nasal and temporal quadrants and was associated with the loss of NF-immunoreactive optic nerve fibers in the glaucomatous eyes. Comparison of counts of NF-immunoreactive neurons with total cell loss evaluated by Nissl staining indicated that NF protein-immunoreactive cells represent a large proportion of the cells that degenerate in the glaucomatous eyes, particularly in the peripheral regions of the retina. Such data may be useful in determining the cellular basis for sensitivity to this pathologic process and may also be helpful in the design of diagnostic tests that may be sensitive to the loss of the subset of NF-immunoreactive ganglion cells.

The optimal dividend barrier in the Gamma-Omega model

In the traditional actuarial risk model, if the surplus is negative, the company is ruined and has to go out of business. In this paper we distinguish between ruin (negative surplus) and bankruptcy (going out of business), where the probability of bankruptcy is a function of the level of negative surplus. The idea for this notion of bankruptcy comes from the observation that in some industries, companies can continue doing business even though they are technically ruined. Assuming that dividends can only be paid with a certain probability at each point of time, we derive closed-form formulas for the expected discounted dividends until bankruptcy under a barrier strategy. Subsequently, the optimal barrier is determined, and several explicit identities for the optimal value are found. The surplus process of the company is modeled by a Wiener process (Brownian motion).

A joint back calculation model for the imputation of the date of HIV infection in a prevalent cohort.

In studies of the natural history of HIV-1 infection, the time scale of primary interest is the time since infection. Unfortunately, this time is very often unknown for HIV infection and using the follow-up time instead of the time since infection is likely to provide biased results because of onset confounding. Laboratory markers such as the CD4 T-cell count carry important information concerning disease progression and can be used to predict the unknown date of infection. Previous work on this topic has made use of only one CD4 measurement or based the imputation on incident patients only. However, because of considerable intrinsic variability in CD4 levels and because incident cases are different from prevalent cases, back calculation based on only one CD4 determination per person or on characteristics of the incident sub-cohort may provide unreliable results. Therefore, we propose a methodology based on the repeated individual CD4 T-cells marker measurements that use both incident and prevalent cases to impute the unknown date of infection. Our approach uses joint modelling of the time since infection, the CD4 time path and the drop-out process. This methodology has been applied to estimate the CD4 slope and impute the unknown date of infection in HIV patients from the Swiss HIV Cohort Study. A procedure based on the comparison of different slope estimates is proposed to assess the goodness of fit of the imputation. Results of simulation studies indicated that the imputation procedure worked well, despite the intrinsic high volatility of the CD4 marker.

MORM--a Petri net based model for assessing OH&S risks in industrial processes: modeling qualitative aspects.

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.

Integrated methodologies to study human transcriptional regulation from functional genomics data

Abstract : The human body is composed of a huge number of cells acting together in a concerted manner. The current understanding is that proteins perform most of the necessary activities in keeping a cell alive. The DNA, on the other hand, stores the information on how to produce the different proteins in the genome. Regulating gene transcription is the first important step that can thus affect the life of a cell, modify its functions and its responses to the environment. Regulation is a complex operation that involves specialized proteins, the transcription factors. Transcription factors (TFs) can bind to DNA and activate the processes leading to the expression of genes into new proteins. Errors in this process may lead to diseases. In particular, some transcription factors have been associated with a lethal pathological state, commonly known as cancer, associated with uncontrolled cellular proliferation, invasiveness of healthy tissues and abnormal responses to stimuli. Understanding cancer-related regulatory programs is a difficult task, often involving several TFs interacting together and influencing each other's activity. This Thesis presents new computational methodologies to study gene regulation. In addition we present applications of our methods to the understanding of cancer-related regulatory programs. The understanding of transcriptional regulation is a major challenge. We address this difficult question combining computational approaches with large collections of heterogeneous experimental data. In detail, we design signal processing tools to recover transcription factors binding sites on the DNA from genome-wide surveys like chromatin immunoprecipitation assays on tiling arrays (ChIP-chip). We then use the localization about the binding of TFs to explain expression levels of regulated genes. In this way we identify a regulatory synergy between two TFs, the oncogene C-MYC and SP1. C-MYC and SP1 bind preferentially at promoters and when SP1 binds next to C-NIYC on the DNA, the nearby gene is strongly expressed. The association between the two TFs at promoters is reflected by the binding sites conservation across mammals, by the permissive underlying chromatin states 'it represents an important control mechanism involved in cellular proliferation, thereby involved in cancer. Secondly, we identify the characteristics of TF estrogen receptor alpha (hERa) target genes and we study the influence of hERa in regulating transcription. hERa, upon hormone estrogen signaling, binds to DNA to regulate transcription of its targets in concert with its co-factors. To overcome the scarce experimental data about the binding sites of other TFs that may interact with hERa, we conduct in silico analysis of the sequences underlying the ChIP sites using the collection of position weight matrices (PWMs) of hERa partners, TFs FOXA1 and SP1. We combine ChIP-chip and ChIP-paired-end-diTags (ChIP-pet) data about hERa binding on DNA with the sequence information to explain gene expression levels in a large collection of cancer tissue samples and also on studies about the response of cells to estrogen. We confirm that hERa binding sites are distributed anywhere on the genome. However, we distinguish between binding sites near promoters and binding sites along the transcripts. The first group shows weak binding of hERa and high occurrence of SP1 motifs, in particular near estrogen responsive genes. The second group shows strong binding of hERa and significant correlation between the number of binding sites along a gene and the strength of gene induction in presence of estrogen. Some binding sites of the second group also show presence of FOXA1, but the role of this TF still needs to be investigated. Different mechanisms have been proposed to explain hERa-mediated induction of gene expression. Our work supports the model of hERa activating gene expression from distal binding sites by interacting with promoter bound TFs, like SP1. hERa has been associated with survival rates of breast cancer patients, though explanatory models are still incomplete: this result is important to better understand how hERa can control gene expression. Thirdly, we address the difficult question of regulatory network inference. We tackle this problem analyzing time-series of biological measurements such as quantification of mRNA levels or protein concentrations. Our approach uses the well-established penalized linear regression models where we impose sparseness on the connectivity of the regulatory network. We extend this method enforcing the coherence of the regulatory dependencies: a TF must coherently behave as an activator, or a repressor on all its targets. This requirement is implemented as constraints on the signs of the regressed coefficients in the penalized linear regression model. Our approach is better at reconstructing meaningful biological networks than previous methods based on penalized regression. The method is tested on the DREAM2 challenge of reconstructing a five-genes/TFs regulatory network obtaining the best performance in the "undirected signed excitatory" category. Thus, these bioinformatics methods, which are reliable, interpretable and fast enough to cover large biological dataset, have enabled us to better understand gene regulation in humans.

Defective tumor necrosis factor-alpha-dependent control of astrocyte glutamate release in a transgenic mouse model of Alzheimer disease.

The cytokine tumor necrosis factor-alpha (TNFalpha) induces Ca2+-dependent glutamate release from astrocytes via the downstream action of prostaglandin (PG) E2. By this process, astrocytes may participate in intercellular communication and neuromodulation. Acute inflammation in vitro, induced by adding reactive microglia to astrocyte cultures, enhances TNFalpha production and amplifies glutamate release, switching the pathway into a neurodamaging cascade (Bezzi, P., Domercq, M., Brambilla, L., Galli, R., Schols, D., De Clercq, E., Vescovi, A., Bagetta, G., Kollias, G., Meldolesi, J., and Volterra, A. (2001) Nat. Neurosci. 4, 702-710). Because glial inflammation is a component of Alzheimer disease (AD) and TNFalpha is overexpressed in AD brains, we investigated possible alterations of the cytokine-dependent pathway in PDAPP mice, a transgenic model of AD. Glutamate release was measured in acute hippocampal and cerebellar slices from mice at early (4-month-old) and late (12-month-old) disease stages in comparison with age-matched controls. Surprisingly, TNFalpha-evoked glutamate release, normal in 4-month-old PDAPP mice, was dramatically reduced in the hippocampus of 12-month-old animals. This defect correlated with the presence of numerous beta-amyloid deposits and hypertrophic astrocytes. In contrast, release was normal in cerebellum, a region devoid of beta-amyloid deposition and astrocytosis. The Ca2+-dependent process by which TNFalpha evokes glutamate release in acute slices is distinct from synaptic release and displays properties identical to those observed in cultured astrocytes, notably PG dependence. However, prostaglandin E2 induced normal glutamate release responses in 12-month-old PDAPP mice, suggesting that the pathology-associated defect involves the TNFalpha-dependent control of secretion rather than the secretory process itself. Reduced expression of DENN/MADD, a mediator of TNFalpha-PG coupling, might account for the defect. Alteration of this neuromodulatory astrocytic pathway is described here for the first time in relation to Alzheimer disease.

Temperature-dependent turnovers in sex-determination mechanisms: a quantitative model.

Sex determination is often seen as a dichotomous process: individual sex is assumed to be determined either by genetic (genotypic sex determination, GSD) or by environmental factors (environmental sex determination, ESD), most often temperature (temperature sex determination, TSD). We endorse an alternative view, which sees GSD and TSD as the ends of a continuum. Both effects interact a priori, because temperature can affect gene expression at any step along the sex-determination cascade. We propose to define sex-determination systems at the population- (rather than individual) level, via the proportion of variance in phenotypic sex stemming from genetic versus environmental factors, and we formalize this concept in a quantitative-genetics framework. Sex is seen as a threshold trait underlain by a liability factor, and reaction norms allow modeling interactions between genotypic and temperature effects (seen as the necessary consequences of thermodynamic constraints on the underlying physiological processes). As this formalization shows, temperature changes (due to e.g., climatic changes or range expansions) are expected to provoke turnovers in sex-determination mechanisms, by inducing large-scale sex reversal and thereby sex-ratio selection for alternative sex-determining genes. The frequency of turnovers and prevalence of homomorphic sex chromosomes in cold-blooded vertebrates might thus directly relate to the temperature dependence in sex-determination mechanisms.

Gériatrie aiguë: un modèle d'unité intégree de soins aux seniors [How to prevent functional decline: an acute care unit model for the elderly].

Hospitalization in older patients is frequently associated with functional decline. Hospital factors and inadapted process of care are factors leading to this decline. Acute care units specifically developed for older patients can prevent functional decline. These units usually include a comprehensive geriatric evaluation, an interdisciplinary meeting, protocols for the treatment of geriatric syndromes and specific teaching for the care team. Globally, patients' cares are organized to preserve and improve functional performances. This article presents a pilot unit inspired by this model.

An active contour-based atlas registration model applied to automatic subthalamic nucleus targeting on MRI: method and validation.

This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.

Optimal dividend strategies for a compound Poisson risk process under transaction costs and power utility

We characterize the value function of maximizing the total discounted utility of dividend payments for a compound Poisson insurance risk model when strictly positive transaction costs are included, leading to an impulse control problem. We illustrate that well known simple strategies can be optimal in the case of exponential claim amounts. Finally we develop a numerical procedure to deal with general claim amount distributions.

Spinal cord T-cell infiltration in the spared nerve injury model of neuropathic pain: a time course study

Background : Numerous studies have shown that immune cells infiltrate the spinal cord after peripheral nerve injury and that they play a major contribution to sensory hypersensitivity in rodents. In particular, the role of monocyte-derived cells and T lymphocytes seems to be prominent in this process. This exciting new perspective in research on neuropathic pain opens many different areas of work, including the understanding of the function of these cells and how they impact on neural function. However, no systematic description of the time course or cell types that characterize this infiltration has been published yet, although this seems to be the rational first step of an overall understanding of the phenomenon. Objective : Describe the time course and cell characteristics of T lymphocyte infiltration in the spinal cord in the Spared Nerve Injury (SNI) model of neuropathic pain in rats. Methods : Collect of lumbar spinal cords of rats at days 2, 7, 21 and 40 after SNI or sham operation (n=4). Immunofluorescence detecting different proteins of T cell subgroups (CD2+CD4+, CD2+CD8+, Th1 markers, Th2 markers, Th17 markers). Quantification of the infiltration rate of the different subgroups. Expected results : First, we expect to see an infiltration of T cells in the spinal cord ipsilateral to nerve injury, higher in SNI rats than in sham animals. Second, we anticipate that different subtypes of T cells penetrate at different time points. Finally, the number of T lymphocytes are expected to decrease at the latest time point, showing a resolution of the process underlying their infiltrating the spinal cord in the first place. Impact : A systematic description of the infiltration of T cells in the spinal cord after peripheral nerve injury is needed to have a better understanding of the role of immune cells in neuropathic pain. The time course that we want to establish will provide the scientific community with new perspectives. First, it will confirm that T cells do indeed infiltrate the spinal cord after SNI in rats. Second, the type of T cells infiltrating at different time points will give clues about their function, in particular their inflammatory or anti-inflammatory profile. From there on, other studies could be lead, investigating the functional side of the specific subtypes put to light by us. Ultimately, this could lead to the discovery of new drugs targeting T cells or their infiltration, in the hope of improving neuropathic pain.

Group selection and kin selection: two concepts but one process.

In a recent paper, Traulsen and Nowak use a multilevel selection model to show that cooperation can be favored by group selection in finite populations [Traulsen A, Nowak M (2006) Proc Natl Acad Sci USA 103:10952-10955]. The authors challenge the view that kin selection may be an appropriate interpretation of their results and state that group selection is a distinctive process "that permeates evolutionary processes from the emergence of the first cells to eusociality and the economics of nations." In this paper, we start by addressing Traulsen and Nowak's challenge and demonstrate that all their results can be obtained by an application of kin selection theory. We then extend Traulsen and Nowak's model to life history conditions that have been previously studied. This allows us to highlight the differences and similarities between Traulsen and Nowak's model and typical kin selection models and also to broaden the scope of their results. Our retrospective analyses of Traulsen and Nowak's model illustrate that it is possible to convert group selection models to kin selection models without disturbing the mathematics describing the net effect of selection on cooperation.