995 resultados para second position
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Parameters of intrarectal pressure (surface area under pressure curve and peak pressure) recorded with a microsystem device during the second phase of labor showed no significant correlations with baby's weight or mode of delivery. AIM OF THE STUDY: Was to assess the biomechanical pressures delivered against pelvic floor structures during the second phase of labor in nulliparae women, and to correlate them with obstetrics parameters, i.e. baby'sweight and mode of delivery. MATERIAL: Using a microsystem device placed into the rectum at the beginning of the second phase of labor, two parameters were assessed during the bearing efforts in 59 nulliparae women: the surface area under the pressure curve and the peak pressure. RESULTS: During 11.5±9 bearing efforts of 99.1±16s duration, the mean value of surface area under the pressure curve was 32677±26058cm/s and the mean value of the peak pressure was 60.7±24cmH(2)O, exceeding 100cmH(2)O in 10% of women. These two parameters were not correlated with baby's weight (R: 0.19, P: 0.15 and R: 0.05, P: 0.71). In the same way, these two parameters were not correlated with the mode of delivery (spontaneous or forceps/vacuum-assisted). Furthermore, the individual values of these two parameters showed great variation from one woman to another. CONCLUSION: This study has showed that parameters of biomechanical pressures recorded into the rectum during second phase of labor had no significant correlations with obstetricals parameters, explaining why these latter have poor predicitive value of further pelvic floor problems.
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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.
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[Factum. Chirurgiens de Paris. 1748]
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The International Society for Clinical Densitometry (ISCD) and the International Osteoporosis Foundation (IOF) convened the FRAX(®) Position Development Conference (PDC) in Bucharest, Romania, on November 14, 2010, following a two-day joint meeting of the ISCD and IOF on the "Interpretation and Use of FRAX(®) in Clinical Practice." These three days of critical discussion and debate, led by a panel of international experts from the ISCD, IOF and dedicated task forces, have clarified a number of important issues pertaining to the interpretation and implementation of FRAX(®) in clinical practice. The Official Positions resulting from the PDC are intended to enhance the quality and clinical utility of fracture risk assessment worldwide. Since the field of skeletal assessment is still evolving rapidly, some clinically important issues addressed at the PDCs are not associated with robust medical evidence. Accordingly, some Official Positions are based largely on expert opinion. Despite limitations inherent in such a process, the ISCD and IOF believe it is important to provide clinicians and technologists with the best distillation of current knowledge in the discipline of bone densitometry and provide an important focus for the scientific community to consider. This report describes the methodology and results of the ISCD-IOF PDC dedicated to FRAX(®).
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The legislatives evolutions imply an important recourse to the psychiatric expertise in order to evaluate the potential dangerousness of a subject. However, in spite of the development of techniques and tools for this evaluation, the dangerousness assessment of a subject is in practice extremely complex and discussed in the scientific literature. The evolution of the concept of dangerousness to the risk assessment involved a technicisation of this evaluation which should not make forget the limits of these tools and the need for restoring the subject, the meaning and the clinic in this evaluation.
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As adult height is a well-established retrospective measure of health and standard of living, it is important to understand the factors that determine it. Among them, the influence of socio-environmental factors has been subjected to empirical scrutiny. This paper explores the influence of generational (or environmental) effects and individual and gender-specific heterogeneity on adult height. Our data set is from contemporary Spain, a country governed by an authoritarian regime between 1939 and 1977. First, we use normal position and quantile regression analysis to identify the determinants of self-reported adult height and to measure the influence of individual heterogeneity. Second, we use a Blinder-Oaxaca decomposition approach to explain the `gender height gap¿ and its distribution, so as to measure the influence on this gap of individual heterogeneity. Our findings suggest a significant increase in adult height in the generations that benefited from the country¿s economic liberalization in the 1950s, and especially those brought up after the transition to democracy in the 1970s. In contrast, distributional effects on height suggest that only in recent generations has ¿height increased more among the tallest¿. Although the mean gender height gap is 11 cm, generational effects and other controls such as individual capabilities explain on average roughly 5% of this difference, a figure that rises to 10% in the lowest 10% quantile.
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Objectives: Acetate brain metabolism has the particularity to occur specifically in glial cells. Labeling studies, using acetate labeled either with 13C (NMR) or 11C (PET), are governed by the same biochemical reactions and thus follow the same mathematical principles. In this study, the objective was to adapt an NMR acetate brain metabolism model to analyse [1-11C]acetate infusion in rats. Methods: Brain acetate infusion experiments were modeled using a two-compartment model approach used in NMR.1-3 The [1-11C]acetate labeling study was done using a beta scintillator.4 The measured radioactive signal represents the time evolution of the sum of all labeled metabolites in the brain. Using a coincidence counter in parallel, an arterial input curve was measured. The 11C at position C-1 of acetate is metabolized in the first turn of the TCA cycle to the position 5 of glutamate (Figure 1A). Through the neurotransmission process, it is further transported to the position 5 of glutamine and the position 5 of neuronal glutamate. After the second turn of the TCA cycle, tracer from [1-11C]acetate (and also a part from glial [5-11C]glutamate) is transferred to glial [1-11C]glutamate and further to [1-11C]glutamine and neuronal glutamate through the neurotransmission cycle. Brain poster session: oxidative mechanisms S460 Journal of Cerebral Blood Flow & Metabolism (2009) 29, S455-S466 Results: The standard acetate two-pool PET model describes the system by a plasma pool and a tissue pool linked by rate constants. Experimental data are not fully described with only one tissue compartment (Figure 1B). The modified NMR model was fitted successfully to tissue time-activity curves from 6 single animals, by varying the glial mitochondrial fluxes and the neurotransmission flux Vnt. A glial composite rate constant Kgtg=Vgtg/[Ace]plasma was extracted. Considering an average acetate concentration in plasma of 1 mmol/g5 and the negligible additional amount injected, we found an average Vgtg = 0.08±0.02 (n = 6), in agreement with previous NMR measurements.1 The tissue time-activity curve is dominated by glial glutamate and later by glutamine (Figure 1B). Labeling of neuronal pools has a low influence, at least for the 20 mins of beta-probe acquisition. Based on the high diffusivity of CO2 across the blood-brain barrier; 11CO2 is not predominant in the total tissue curve, even if the brain CO2 pool is big compared with other metabolites, due to its strong dilution through unlabeled CO2 from neuronal metabolism and diffusion from plasma. Conclusion: The two-compartment model presented here is also able to fit data of positron emission experiments and to extract specific glial metabolic fluxes. 11C-labeled acetate presents an alternative for faster measurements of glial oxidative metabolism compared to NMR, potentially applicable to human PET imaging. However, to quantify the relative value of the TCA cycle flux compared to the transmitochondrial flux, the chemical sensitivity of NMR is required. PET and NMR are thus complementary.
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Référence bibliographique : Weigert, 629
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Excessive speed is often cited as a primary driver factor in crashes, particularly rural two-lane crashes. It has also been suggested that speed plays a significant role in crashes on curves. However, the relationship between speed and crashes on curves is not well documented because it is difficult to determine driver speed after the fact when investigating a crash. One method to begin documenting this relationship is to explore the relationship between lateral position and speed as a crash surrogate. For this study, the researchers collected speed and lateral position data for three rural two-lane curves. The relationship between lateral position and speed was assessed by comparing the odds of a near-lane crossing for vehicles traveling 5 or more mph over the advisory speed to those for vehicles traveling below that threshold.
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Many species contain genetic lineages that are phylogenetically intermixed with those of other species. In the Sorex araneus group, previous results based on mtDNA and Y chromosome sequence data showed an incongruent position of Sorex granarius within this group. In this study, we explored the relationship between species within the S. araneus group, aiming to resolve the particular position of S. granarius. In this context, we sequenced a total of 2447 base pairs (bp) of X-linked and nuclear genes from 47 individuals of the S. araneus group. The same taxa were also analyzed within a Bayesian framework with nine autosomal microsatellites. These analyses revealed that all markers apart from mtDNA showed similar patterns, suggesting that the problematic position of S. granarius is best explained by an incongruent behavior by mtDNA. Given their close phylogenetic relationship and their close geographic distribution, the most likely explanation for this pattern is past mtDNA introgression from S. araneus race Carlit to S. granarius.
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This document summarizes the available evidence and provides recommendations on the use of home blood pressure monitoring in clinical practice and in research. It updates the previous recommendations on the same topic issued in year 2000. The main topics addressed include the methodology of home blood pressure monitoring, its diagnostic and therapeutic thresholds, its clinical applications in hypertension, with specific reference to special populations, and its applications in research. The final section deals with the problems related to the implementation of these recommendations in clinical practice.