291 research outputs found

    Gibbs distribution analysis of temporal correlations structure in retina ganglion cells

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    We present a method to estimate Gibbs distributions with \textit{spatio-temporal} constraints on spike trains statistics. We apply this method to spike trains recorded from ganglion cells of the salamander retina, in response to natural movies. Our analysis, restricted to a few neurons, performs more accurately than pairwise synchronization models (Ising) or the 1-time step Markov models (\cite{marre-boustani-etal:09}) to describe the statistics of spatio-temporal spike patterns and emphasizes the role of higher order spatio-temporal interactions.Comment: To appear in J. Physiol. Pari

    Adaptive cluster expansion for the inverse Ising problem: convergence, algorithm and tests

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    We present a procedure to solve the inverse Ising problem, that is to find the interactions between a set of binary variables from the measure of their equilibrium correlations. The method consists in constructing and selecting specific clusters of variables, based on their contributions to the cross-entropy of the Ising model. Small contributions are discarded to avoid overfitting and to make the computation tractable. The properties of the cluster expansion and its performances on synthetic data are studied. To make the implementation easier we give the pseudo-code of the algorithm.Comment: Paper submitted to Journal of Statistical Physic

    Stimulus-dependent maximum entropy models of neural population codes

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    Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. To be able to infer a model for this distribution from large-scale neural recordings, we introduce a stimulus-dependent maximum entropy (SDME) model---a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. The model is able to capture the single-cell response properties as well as the correlations in neural spiking due to shared stimulus and due to effective neuron-to-neuron connections. Here we show that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. As a result, the SDME model gives a more accurate account of single cell responses and in particular outperforms uncoupled models in reproducing the distributions of codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like surprise and information transmission in a neural population.Comment: 11 pages, 7 figure

    Dairy Consumption and the Incidence of Hyperglycemia and the Metabolic Syndrome: Results from a French prospective study, Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR)

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    International audienceOBJECTIVE: In the French Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR) cohort, cross-sectional analyses have shown that a higher consumption of dairy products and calcium are associated with a lower prevalence of the metabolic syndrome (MetS). We assess the influence of dairy products on 9-year incident MetS and on impaired fasting glycemia and/or type 2 diabetes (IFG/T2D). RESEARCH DESIGN AND METHODS: Men and women who completed a food frequency questionnaire at baseline and after 3 years were studied (n = 3,435). Logistic regression models were used to study associations between the average year 0 and year 3 consumption of milk and dairy products, cheese, dietary calcium density, and incident MetS and IFG/T2D after adjusting for 1) sex, age, alcohol, smoking, physical activity, fat intake and 2) additionally for BMI. Associations between dairy products and continuous variables were studied by repeated-measures ANCOVA, using the same covariates. RESULTS: Dairy products other than cheese, and dietary calcium density, were inversely associated with incident MetS and IFG/T2D; cheese was negatively associated with incident MetS. All three parameters were associated with lower diastolic blood pressure, and with a lower BMI gain. Higher cheese intake and calcium density were associated with a lower increase in waist circumference and lower triglyceride levels. Calcium density was also associated with a lower systolic blood pressure and a lower 9-year increase in plasma triglyceride levels. CONCLUSIONS: A higher consumption of dairy products and calcium was associated with a lower 9-year incidence of MetS and IFG/T2D in a large cohort drawn from the general population

    A polymorphism in the gene encoding carnosinase (CNDP1) as a predictor of mortality and progression from nephropathy to end-stage renal disease in type 1 diabetes mellitus

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    Aims/hypothesis Homozygosity for a five leucine repeat (5L-5L) in the carnosinase gene (CNDP1) has been found to be cross-sectionally associated with a low frequency of diabetic nephropathy (DN), mainly in type 2 diabetes. We prospectively investigated in patients with type I diabetes whether: (1) 5L-5L is associated with mortality; (2) there is an interaction of 5L-5L with DN or sex for prediction of mortality; and (3) 5L-5L is associated with progression to end-stage renal disease (ESRD). Methods In this prospective study in white European patients with type 1 diabetes, individuals with DN were defined by persistent albuminuria >= 300 mg/24 h. Controls without nephropathy were defined by persistent (>15 years) normoalbuminuria Results The study involved 916 patients with DN and 1,170 controls. During follow-up for 8.8 years, 107 patients (14%) with 5L-5L died compared with 182 patients (13.8%) with other genotypes (p=0.99). There was no significant interaction of 5L-5L with DN for prediction of mortality (p=0.57), but a trend towards interaction with sex (p=0.08). In patients with DN, HR for ESRD in 5L-5L vs other genotypes was not constant over time, with increased risk for 5L-5L beyond 8 years of follow-up (p=0.03). Conclusions/interpretation CNDP1 polymorphism was not associated with mortality, and nor was there an interaction of this polymorphism with DN for prediction of mortality in patients with type 1 diabetes. CNDP1 polymorphism predicts progression to ESRD in patients with DN, but only late after baseline measurements

    Low-frequency variants in HMGA1 are not associated with type 2 diabetes risk.

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    It has recently been suggested that the low-frequency c.136-14_136-13insC variant in high-mobility group A1 (HMGA1) may strongly contribute to insulin resistance and type 2 diabetes risk. In our study, we attempted to confirm that HMGA1 is a novel type 2 diabetes locus in French Caucasians. The gene was sequenced in 368 type 2 diabetic case subjects with a family history of type 2 diabetes and 372 normoglycemic control subjects without a family history of type 2 diabetes. None of the 41 genetic variations identified were associated with type 2 diabetes. The lack of association between the c.136-14_136-13insC variant and type 2 diabetes was confirmed in an independent French group of 4,538 case subjects and 4,015 control subjects and in a large meta-analysis of 16,605 case subjects and 46,179 control subjects. Finally, this variant had no effects on metabolic traits and was not involved in variations of HMGA1 and insulin receptor (INSR) expressions. The c.136-14_136-13insC variant was not associated with type 2 diabetes in individuals of European descent. Our study emphasizes the need to analyze a large number of subjects to reliably assess the association of low-frequency variants with the disease

    Evaluation of bacteriophage as an adjunct therapy for treatment of peri-prosthetic joint infection caused by Staphylococcus aureus

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    Phage therapy offers a potential alternate strategy for the treatment of peri-prosthetic joint infection (PJI), particularly where limited effective antibiotics are available. We undertook preclinical trials to investigate the therapeutic efficacy of a phage cocktail, alone and in combination with vancomycin, to reduce bacterial numbers within the infected joint using a clinically-relevant model of Staphylococcus aureus-induced PJI. Infected animals were randomised to 4 treatment groups, with treatment commencing 21-days post-surgery: bacteriophage alone, vancomycin alone, bacteriophage and vancomycin, and sham. At day 28 post-surgery, animals were euthanised for microbiological and immunological assessment of implanted joints. Treatment with phage alone or vancomycin alone, led to 5-fold and 6.2-fold reductions, respectively in bacterial load within peri-implant tissue compared to shamtreated animals. Compared to sham-treated animals, a 22.5-fold reduction in S. aureus burden was observed within joint tissue of animals that were administered phage in combination with vancomycin, corresponding with decreased swelling in the implanted knee. Microbiological data were supported by evidence of decreased inflammation within the joints of animals administered phage in combination with vancomycin, compared to sham-treated animals. Our findings provide further support for phage therapy as a tolerable and effective adjunct treatment for PJI
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