Identification of CARDIAK, a RIP-like kinase that associates with caspase-1.

Members of the tumor necrosis factor receptor (TNFR) superfamily have an important role in the induction of cellular signals resulting in cell growth, differentiation and death. TNFR-1 recruits and assembles a signaling complex containing a number of death domain (DD)-containing proteins, including the adaptor protein TRADD and the serine/threonine kinase RIP, which mediates TNF-induced NF-kappa B activation. RIP also recruits caspase-2 to the TNFR-1 signaling complex via the adaptor protein RAIDD, which contains a DD and a caspase-recruiting domain (CARD). Here, we have identified a RIP-like kinase, termed CARDIAK (for CARD-containing interleukin (IL)-1 beta converting enzyme (ICE) associated kinase), which contains a serine/threonine kinase domain and a carboxy-terminal CARD. Overexpression of CARDIAK induced the activation of both NF-kappa B and Jun N-terminal kinase (JNK). CARDIAK interacted with the TNFR-associated factors TRAF-1 and TRAF-2, and a dominant-negative form of TRAF-2 inhibited CARDIAK-induced NF-kappa B activation. Interestingly, CARDIAK specifically interacted with the CARD of caspase-1 (previously known as ICE), and this interaction correlated with the processing of pro-caspase-1 and the formation of the active p20 subunit of caspase-1. Together, these data suggest that CARDIAK may be involved in NF-kappa B/JNK signaling and in the generation of the proinflammatory cytokine IL-1 beta through activation of caspase-1.

The prognostic value of health-related quality-of-life data in predicting survival in glioblastoma cancer patients: results from an international randomised phase III EORTC Brain Tumour and Radiation Oncology Groups, and NCIC Clinical Trials Group study.

This is one of the few studies that have explored the value of baseline symptoms and health-related quality of life (HRQOL) in predicting survival in brain cancer patients. Baseline HRQOL scores (from the EORTC QLQ-C30 and the Brain Cancer Module (BN 20)) were examined in 490 newly diagnosed glioblastoma cancer patients for the relationship with overall survival by using Cox proportional hazards regression models. Refined techniques as the bootstrap re-sampling procedure and the computation of C-indexes and R(2)-coefficients were used to try and validate the model. Classical analysis controlled for major clinical prognostic factors selected cognitive functioning (P=0.0001), global health status (P=0.0055) and social functioning (P<0.0001) as statistically significant prognostic factors of survival. However, several issues question the validity of these findings. C-indexes and R(2)-coefficients, which are measures of the predictive ability of the models, did not exhibit major improvements when adding selected or all HRQOL scores to clinical factors. While classical techniques lead to positive results, more refined analyses suggest that baseline HRQOL scores add relatively little to clinical factors to predict survival. These results may have implications for future use of HRQOL as a prognostic factor in cancer patients.

Imputation in data fusion of heterogeneous data sets a model-based numerical experiment

Given the very large amount of data obtained everyday through population surveys, much of the new research again could use this information instead of collecting new samples. Unfortunately, relevant data are often disseminated into different files obtained through different sampling designs. Data fusion is a set of methods used to combine information from different sources into a single dataset. In this article, we are interested in a specific problem: the fusion of two data files, one of which being quite small. We propose a model-based procedure combining a logistic regression with an Expectation-Maximization algorithm. Results show that despite the lack of data, this procedure can perform better than standard matching procedures.

Lifelong dynamics of human CD4+CD25+ regulatory T cells: insights from in vivo data and mathematical modeling.

Despite their limited proliferation capacity, regulatory T cells (T(regs)) constitute a population maintained over the entire lifetime of a human organism. The means by which T(regs) sustain a stable pool in vivo are controversial. Using a mathematical model, we address this issue by evaluating several biological scenarios of the origins and the proliferation capacity of two subsets of T(regs): precursor CD4(+)CD25(+)CD45RO(-) and mature CD4(+)CD25(+)CD45RO(+) cells. The lifelong dynamics of T(regs) are described by a set of ordinary differential equations, driven by a stochastic process representing the major immune reactions involving these cells. The model dynamics are validated using data from human donors of different ages. Analysis of the data led to the identification of two properties of the dynamics: (1) the equilibrium in the CD4(+)CD25(+)FoxP3(+)T(regs) population is maintained over both precursor and mature T(regs) pools together, and (2) the ratio between precursor and mature T(regs) is inverted in the early years of adulthood. Then, using the model, we identified three biologically relevant scenarios that have the above properties: (1) the unique source of mature T(regs) is the antigen-driven differentiation of precursors that acquire the mature profile in the periphery and the proliferation of T(regs) is essential for the development and the maintenance of the pool; there exist other sources of mature T(regs), such as (2) a homeostatic density-dependent regulation or (3) thymus- or effector-derived T(regs), and in both cases, antigen-induced proliferation is not necessary for the development of a stable pool of T(regs). This is the first time that a mathematical model built to describe the in vivo dynamics of regulatory T cells is validated using human data. The application of this model provides an invaluable tool in estimating the amount of regulatory T cells as a function of time in the blood of patients that received a solid organ transplant or are suffering from an autoimmune disease.

High-frequency linkage of co-expressing T-DNA in transgenic Arabidopsis thaliana transformed by vacuum-infiltration of Agrobacterium tumefaciens

The efficiency of co-expression and linkage of distinct T-DNAs present in separate Agrobacterium tumefaciens was analysed in Arabidopsis thaliana transformed by the vacuum infiltration method. Co-expression was monitored by the synthesis of three bacterial proteins involved in the production of polyhydroxybutyrate (PHB) in the plastids. Out of 80 kanamycin-resistant transgenic plants analysed, 13 plants were co-transformed with the two distinct T-DNAs and produced PHB. Of those, 7 lines had a kanamycin-resistance segregation ratio consistent with the presence of a single functional insert. Genetic linkage between the distinct T-DNAs was demonstrated for all 13 PHB-producing lines, while physical linkage between the distinct T-DNAs was shown for 12 out of 13 lines. T-DNAs were frequently linked in an inverted orientation about the left borders. Transformation of A. thaliana by the co-infiltration of two A. tumefaciens containing distinct T-DNAs is, thus, an efficient approach for the integration and expression of several transgenes at a single locus. This approach will facilitate the creation and study of novel metabolic pathways requiring the expression of numerous transgenes.

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Increased audiovisual integration in cochlear-implanted deaf patients: independent components analysis of longitudinal positron emission tomography data.

It has been demonstrated in earlier studies that patients with a cochlear implant have increased abilities for audio-visual integration because the crude information transmitted by the cochlear implant requires the persistent use of the complementary speech information from the visual channel. The brain network for these abilities needs to be clarified. We used an independent components analysis (ICA) of the activation (H2 (15) O) positron emission tomography data to explore occipito-temporal brain activity in post-lingually deaf patients with unilaterally implanted cochlear implants at several months post-implantation (T1), shortly after implantation (T0) and in normal hearing controls. In between-group analysis, patients at T1 had greater blood flow in the left middle temporal cortex as compared with T0 and normal hearing controls. In within-group analysis, patients at T0 had a task-related ICA component in the visual cortex, and patients at T1 had one task-related ICA component in the left middle temporal cortex and the other in the visual cortex. The time courses of temporal and visual activities during the positron emission tomography examination at T1 were highly correlated, meaning that synchronized integrative activity occurred. The greater involvement of the visual cortex and its close coupling with the temporal cortex at T1 confirm the importance of audio-visual integration in more experienced cochlear implant subjects at the cortical level.

What spatial data do we need to develop global mammal conservation strategies?

Spatial data on species distributions are available in two main forms, point locations and distribution maps (polygon ranges and grids). The first are often temporally and spatially biased, and too discontinuous, to be useful (untransformed) in spatial analyses. A variety of modelling approaches are used to transform point locations into maps. We discuss the attributes that point location data and distribution maps must satisfy in order to be useful in conservation planning. We recommend that before point location data are used to produce and/or evaluate distribution models, the dataset should be assessed under a set of criteria, including sample size, age of data, environmental/geographical coverage, independence, accuracy, time relevance and (often forgotten) representation of areas of permanent and natural presence of the species. Distribution maps must satisfy additional attributes if used for conservation analyses and strategies, including minimizing commission and omission errors, credibility of the source/assessors and availability for public screening. We review currently available databases for mammals globally and show that they are highly variable in complying with these attributes. The heterogeneity and weakness of spatial data seriously constrain their utility to global and also sub-global scale conservation analyses.

Lien entre durée de séjour et réadmissions en chirurgie et en obstétrique: étude de deux procédures à partir des données du PMSI = Using administrative data to assess the impact of length of stay on readmissions: study of two procedures in surgery and obstetrics

Position du problème: La mise en place de la tarification à l'activité pour les hôpitaux de court séjour pourrait entraîner une diminution des durées de séjour pour raisons financières. L'impact potentiel de ce phénomène sur la qualité des soins n'est pas connu. Les réadmissions identifiées à l'aide des données administratives hospitalières sont, pour certaines situations cliniques, des indicateurs de qualité des soins valides. Méthode: Étude rétrospective du lien entre la durée de séjour et la survenue de réadmissions imprévues liées au séjour initial, pour les cholécystectomies simples et les accouchements par voie basse sans complication, à partir des données du programme de médicalisation des systèmes d'information de l'Assistance publique-Hôpitaux de Paris des années 2002 à 2005. Résultats: Pour les deux procédures, la probabilité de réadmission suit une courbe en " J ". Après ajustement sur l'âge, le sexe, les comorbidités associées, l'hôpital et l'année d'admission, la probabilité de réadmission est plus élevée pour les durées de séjour les plus courtes : pour les cholécystectomies, odds ratio : 6,03 [IC95 % : 2,67-13,59] pour les hospitalisations d'un jour versus trois jours ; pour les accouchements, odds ratio : 1,74 [IC95 % : 1,05-2,91] pour les hospitalisations de deux jours versus trois jours. Conclusion: Pour deux pathologies communes, les durées de séjour les plus courtes sont associées à des probabilités de réadmission plus élevées. L'utilisation routinière des données du programme de médicalisation des systèmes d'information peut permettre d'assurer le suivi de la relation entre la réduction de la durée de séjour et les réadmissions. The prospective payment system for the French short-stay hospitals creates a financial incentive to reduce length of stay. The potential impact of the resulting decrease in length of stay on the quality of healthcare is unknown. Readmission rates are valid outcome indicators for some clinical procedures. Methods: Retrospective study of the association between length of stay and unplanned readmissions related to the initial stay, for two procedures: cholecystectomy and vaginal delivery. Data: Administrative diagnosis-related groups database of "Assistance publique-Hopitaux de Paris", a large teaching hospital, for years 2002 to 2005. Results: The risk of readmission according to length of stay, taking age, sex, comorbidity, hospital and year of admission into account, followed a J-shaped curve for both procedures. The probability of readmission was higher for very short stays, with odds ratios and 95% confidence intervals of 6.03 [2.67-13.59] for cholecystectomies (1- versus 3-night stays), and of 1.74 [1.05-2.91] for vaginal deliveries (2- versus 3-night stays). Conclusion: For both procedures, the shortest lengths of stay are associated with a higher readmission probability. Suitable indicators derived from administrative databases would enable monitoring of the association between length of stay and readmissions.

Use of variability in national and regional data to estimate the prevalence of lymphangioleiomyomatosis.

Background: Understanding the true prevalence of lymphangioleiomyomatosis (LAM) is important in estimating disease burden and targeting specific interventions. As with all rare diseases, obtaining reliable epidemiological data is difficult and requires innovative approaches.Aim: To determine the prevalence and incidence of LAM using data from patient organizations in seven countries, and to use the extent to which the prevalence of LAM varies regionally and nationally to determine whether prevalence estimates are related to health-care provision.Methods: Numbers of women with LAM were obtained from patient groups and national databases from seven countries (n = 1001). Prevalence was calculated for regions within countries using female population figures from census data. Incidence estimates were calculated for the USA, UK and Switzerland. Regional variation in prevalence and changes in incidence over time were analysed using Poisson regression and linear regression.Results: Prevalence of LAM in the seven countries ranged from 3.4 to 7.8/million women with significant variation, both between countries and between states in the USA. This variation did not relate to the number of pulmonary specialists in the region nor the percentage of population with health insurance, but suggests a large number of patients remain undiagnosed. The incidence of LAM from 2004 to 2008 ranged from 0.23 to 0.31/million women/per year in the USA, UK and Switzerland.Conclusions: Using this method, we have found that the prevalence of LAM is higher than that previously recorded and that many patients with LAM are undiagnosed.