4 resultados para X Window (Sistema informático)
em Université de Lausanne, Switzerland
Resumo:
The Fragile X mental retardation protein (FMRP) regulates neuronal RNA metabolism, and its absence or mutations leads to the Fragile X syndrome (FXS). The β-amyloid precursor protein (APP) is involved in Alzheimer's disease, plays a role in synapse formation, and is upregulated in intellectual disabilities. Here, we show that during mouse synaptogenesis and in human FXS fibroblasts, a dual dysregulation of APP and the α-secretase ADAM10 leads to the production of an excess of soluble APPα (sAPPα). In FXS, sAPPα signals through the metabotropic receptor that, activating the MAP kinase pathway, leads to synaptic and behavioral deficits. Modulation of ADAM10 activity in FXS reduces sAPPα levels, restoring translational control, synaptic morphology, and behavioral plasticity. Thus, proper control of ADAM10-mediated APP processing during a specific developmental postnatal stage is crucial for healthy spine formation and function(s). Downregulation of ADAM10 activity at synapses may be an effective strategy for ameliorating FXS phenotypes.
Resumo:
Introduction: Coronary magnetic resonance angiography (MRA) is a medical imaging technique that involves collecting data from consecutive heartbeats, always at the same time in the cardiac cycle, in order to minimize heart motion artifacts. This technique relies on the assumption that coronary arteries always follow the same trajectory from heartbeat to heartbeat. Until now, choosing the acquisition window in the cardiac cycle was based exclusively on the position of minimal coronary motion. The goal of this study was to test the hypothesis that there are time intervals during the cardiac cycle when coronary beat-to-beat repositioning is optimal. The repositioning uncertainty values in these time intervals were then compared with the intervals of low coronary motion in order to propose an optimal acquisition window for coronary MRA. Methods: Cine breath-hold x-ray angiograms with synchronous ECG were collected from 11 patients who underwent elective routine diagnostic coronarography. Twenty-three bifurcations of the left coronary artery were selected as markers to evaluate repositioning uncertainty and velocity during cardiac cycle. Each bifurcation was tracked by two observers, with the help of a user-assisted algorithm implemented in Matlab (The Mathworks, Natick, MA, USA) that compared the trajectories of the markers coming from consecutive heartbeats and computed the coronary repositioning uncertainty with steps of 50ms until 650ms after the R-wave. Repositioning uncertainty was defined as the diameter of the smallest circle encompassing the points to be compared at the same time after the R-wave. Student's t-tests with a false discovery rate (FDR, q=0.1) correction for multiple comparison were applied to see whether coronary repositioning and velocity vary statistically during cardiac cycle. Bland-Altman plots and linear regression were used to assess intra- and inter-observer agreement. Results: The analysis of left coronary artery beat-to-beat repositioning uncertainty shows a tendency to have better repositioning in mid systole (less than 0.84±0.58mm) and mid diastole (less than 0.89±0.6mm) than in the rest of the cardiac cycle (highest value at 50ms=1.35±0.64mm). According to Student's t-tests with FDR correction for multiple comparison (q=0.1), two intervals, in mid systole (150-200ms) and mid diastole (550-600ms), provide statistically better repositioning in comparison with the early systole and the early diastole. Coronary velocity analysis reveals that left coronary artery moves more slowly in end systole (14.35±11.35mm/s at 225ms) and mid diastole (11.78±11.62mm/s at 625ms) than in the rest of the cardiac cycle (highest value at 25ms: 55.96±22.34mm/s). This was confirmed by Student's t-tests with FDR correction for multiple comparison (q=0.1, FDR-corrected p-value=0.054): coronary velocity values at 225, 575 and 625ms are not much different between them but they are statistically inferior to all others. Bland-Altman plots and linear regression show that intra-observer agreement (y=0.97x+0.02 with R²=0.93 at 150ms) is better than inter-observer (y=0.8x+0.11 with R²=0.67 at 150ms). Discussion: The present study has demonstrated that there are two time intervals in the cardiac cycle, one in mid systole and one in mid diastole, where left coronary artery repositioning uncertainty reaches points of local minima. It has also been calculated that the velocity is the lowest in end systole and mid diastole. Since systole is less influenced by heart rate variability than diastole, it was finally proposed to test an acquisition window between 150 and 200ms after the R-wave.
Resumo:
BACKGROUND: Tests for recent infections (TRIs) are important for HIV surveillance. We have shown that a patient's antibody pattern in a confirmatory line immunoassay (Inno-Lia) also yields information on time since infection. We have published algorithms which, with a certain sensitivity and specificity, distinguish between incident (< = 12 months) and older infection. In order to use these algorithms like other TRIs, i.e., based on their windows, we now determined their window periods. METHODS: We classified Inno-Lia results of 527 treatment-naïve patients with HIV-1 infection < = 12 months according to incidence by 25 algorithms. The time after which all infections were ruled older, i.e. the algorithm's window, was determined by linear regression of the proportion ruled incident in dependence of time since infection. Window-based incident infection rates (IIR) were determined utilizing the relationship 'Prevalence = Incidence x Duration' in four annual cohorts of HIV-1 notifications. Results were compared to performance-based IIR also derived from Inno-Lia results, but utilizing the relationship 'incident = true incident + false incident' and also to the IIR derived from the BED incidence assay. RESULTS: Window periods varied between 45.8 and 130.1 days and correlated well with the algorithms' diagnostic sensitivity (R(2) = 0.962; P<0.0001). Among the 25 algorithms, the mean window-based IIR among the 748 notifications of 2005/06 was 0.457 compared to 0.453 obtained for performance-based IIR with a model not correcting for selection bias. Evaluation of BED results using a window of 153 days yielded an IIR of 0.669. Window-based IIR and performance-based IIR increased by 22.4% and respectively 30.6% in 2008, while 2009 and 2010 showed a return to baseline for both methods. CONCLUSIONS: IIR estimations by window- and performance-based evaluations of Inno-Lia algorithm results were similar and can be used together to assess IIR changes between annual HIV notification cohorts.
Resumo:
To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.