45 resultados para signal detection theory
Resumo:
Two mutually exclusive hypotheses have been put forward to explain the evolution and adaptive function of melanin-based color traits. According to sexual selection theory melanism is a directionally selected signal of individual quality, whereas theory on the maintenance of genetic polymorphism proposes that alternative melanin-based variants achieve equal fitness. Alpine swift (Apus melba) males and females have a conspicuous patch of white feathers on the breast with their rachis varying continuously from white to black, and hence the breast varies from white to striated. If this trait is a sexually selected signal of quality, its expression should be condition dependent and the degree of melanism directionally selected. If variation in melanism is a polymorphism, its expression should be genetically determined and fitness of melanin-based variants equal. We experimentally tested these predictions by exchanging eggs or hatchlings between randomly chosen nests and by estimating survival and reproduction in relation to melanism. We found that breast melanism is heritable and that the environment and body condition do not significantly influence its expression. Between 5 and 50 days of age nestlings were heavier and their wings longer when breast feathers of their biological father were blacker, and they also fledged at a younger age. This shows that aspects of offspring quality covary positively with the degree of melanism. However, this did not result in directional selection because nestling survival and recruitment in the local breeding population were not associated with father breast melanism. Furthermore, adult survival, age at first reproduction and probability of skipping reproduction did not covary with the degree of melanism. Genetic variation in breast melanism is therefore maintained either because nonmelanic males achieve fitness similar to melanic males via a different route than producing fast-growing offspring, or because the advantage of producing fast-growing offspring is not sufficiently pronounced to result in directional selection.
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Contamination with arsenic is a recurring problem in both industrialized and developing countries. Drinking water supplies for large populations can have concentrations much higher than the permissible levels (for most European countries and the United States, 10 μg As per L; elsewhere, 50 μg As per L). Arsenic analysis requires high-end instruments, which are largely unavailable in developing countries. Bioassays based on genetically engineered bacteria have been proposed as suitable alternatives but such tests would profit from better standardization and direct incorporation into sensing devices. The goal of this work was to develop and test microfluidic devices in which bacterial bioreporters could be embedded, exposed and reporter signals detected, as a further step towards a complete miniaturized bacterial biosensor. The signal element in the biosensor is a nonpathogenic laboratory strain of Escherichia coli, which produces a variant of the green fluorescent protein after contact to arsenite and arsenate. E. coli bioreporter cells were encapsulated in agarose beads and incorporated into a microfluidic device where they were captured in 500 × 500 μm(2) cages and exposed to aqueous samples containing arsenic. Cell-beads frozen at -20 °C in the microfluidic chip retained inducibility for up to a month and arsenic samples with 10 or 50 μg L(-1) could be reproducibly discriminated from the blank. In the 0-50 μg L(-1) range and with an exposure time of 200 minutes, the rate of signal increase was linearly proportional to the arsenic concentration. The time needed to reliably and reproducibly detect a concentration of 50 μg L(-1) was 75-120 minutes, and 120-180 minutes for a concentration of 10 μg L(-1).
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Short-TE MRS has been proposed recently as a method for the in vivo detection and quantification of γ-aminobutyric acid (GABA) in the human brain at 3 T. In this study, we investigated the accuracy and reproducibility of short-TE MRS measurements of GABA at 3 T using both simulations and experiments. LCModel analysis was performed on a large number of simulated spectra with known metabolite input concentrations. Simulated spectra were generated using a range of spectral linewidths and signal-to-noise ratios to investigate the effect of varying experimental conditions, and analyses were performed using two different baseline models to investigate the effect of an inaccurate baseline model on GABA quantification. The results of these analyses indicated that, under experimental conditions corresponding to those typically observed in the occipital cortex, GABA concentration estimates are reproducible (mean reproducibility error, <20%), even when an incorrect baseline model is used. However, simulations indicate that the accuracy of GABA concentration estimates depends strongly on the experimental conditions (linewidth and signal-to-noise ratio). In addition to simulations, in vivo GABA measurements were performed using both spectral editing and short-TE MRS in the occipital cortex of 14 healthy volunteers. Short-TE MRS measurements of GABA exhibited a significant positive correlation with edited GABA measurements (R = 0.58, p < 0.05), suggesting that short-TE measurements of GABA correspond well with measurements made using spectral editing techniques. Finally, within-session reproducibility was assessed in the same 14 subjects using four consecutive short-TE GABA measurements in the occipital cortex. Across all subjects, the average coefficient of variation of these four GABA measurements was 8.7 ± 4.9%. This study demonstrates that, under some experimental conditions, short-TE MRS can be employed for the reproducible detection of GABA at 3 T, but that the technique should be used with caution, as the results are dependent on the experimental conditions. Copyright © 2013 John Wiley & Sons, Ltd.
Resumo:
PURPOSE: To determine the lower limit of dose reduction with hybrid and fully iterative reconstruction algorithms in detection of endoleaks and in-stent thrombus of thoracic aorta with computed tomographic (CT) angiography by applying protocols with different tube energies and automated tube current modulation. MATERIALS AND METHODS: The calcification insert of an anthropomorphic cardiac phantom was replaced with an aortic aneurysm model containing a stent, simulated endoleaks, and an intraluminal thrombus. CT was performed at tube energies of 120, 100, and 80 kVp with incrementally increasing noise indexes (NIs) of 16, 25, 34, 43, 52, 61, and 70 and a 2.5-mm section thickness. NI directly controls radiation exposure; a higher NI allows for greater image noise and decreases radiation. Images were reconstructed with filtered back projection (FBP) and hybrid and fully iterative algorithms. Five radiologists independently analyzed lesion conspicuity to assess sensitivity and specificity. Mean attenuation (in Hounsfield units) and standard deviation were measured in the aorta to calculate signal-to-noise ratio (SNR). Attenuation and SNR of different protocols and algorithms were analyzed with analysis of variance or Welch test depending on data distribution. RESULTS: Both sensitivity and specificity were 100% for simulated lesions on images with 2.5-mm section thickness and an NI of 25 (3.45 mGy), 34 (1.83 mGy), or 43 (1.16 mGy) at 120 kVp; an NI of 34 (1.98 mGy), 43 (1.23 mGy), or 61 (0.61 mGy) at 100 kVp; and an NI of 43 (1.46 mGy) or 70 (0.54 mGy) at 80 kVp. SNR values showed similar results. With the fully iterative algorithm, mean attenuation of the aorta decreased significantly in reduced-dose protocols in comparison with control protocols at 100 kVp (311 HU at 16 NI vs 290 HU at 70 NI, P ≤ .0011) and 80 kVp (400 HU at 16 NI vs 369 HU at 70 NI, P ≤ .0007). CONCLUSION: Endoleaks and in-stent thrombus of thoracic aorta were detectable to 1.46 mGy (80 kVp) with FBP, 1.23 mGy (100 kVp) with the hybrid algorithm, and 0.54 mGy (80 kVp) with the fully iterative algorithm.
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The CREB-binding protein (CBP) is a large nuclear protein that regulates many signal transduction pathways and is involved in chromatin-mediated transcription. The translocation t(8;16)(p11;p13.3) consistently disrupts two genes: the CBP gene on chromosome band 16p13.3 and the MOZ gene on chromosome band 8p11. Although a fusion of these two genes as a result of the translocation is expected, attempts at detecting the fusion transcript by reverse transcriptase polymerase chain reaction (RT-PCR) have proven difficult; to date, only one in-frame CBP/MOZ fusion transcript has been reported. We therefore sought other reliable means of detecting CBP rearrangements. We applied fluorescence in situ hybridization (FISH) and Southern blot analyses to a series of AML patients with a t(8;16) and detected DNA rearrangements of both the CBP and the MOZ loci in all cases tested. All six cases examined for CBP rearrangements have breakpoints within a 13 kb breakpoint cluster region at the 5' end of the CBP gene. Additionally, we used a MOZ cDNA probe to construct a surrounding cosmid contig and detect DNA rearrangements in three t(8;16) cases, all of which display rearrangements within a 6 kb genomic fragment of the MOZ gene. We have thus developed a series of cosmid probes that consistently detect the disruption of the CBP gene in t(8;16) patients. These clones could potentially be used to screen other cancer-associated or congenital translocations involving chromosome band 16p13.3 as well.
Resumo:
OBJECTIVE: Plasma adiponectin is strongly associated with various components of metabolic syndrome, type 2 diabetes and cardiovascular outcomes. Concentrations are highly heritable and differ between men and women. We therefore aimed to investigate the genetics of plasma adiponectin in men and women. METHODS: We combined genome-wide association scans of three population-based studies including 4659 persons. For the replication stage in 13795 subjects, we selected the 20 top signals of the combined analysis, as well as the 10 top signals with p-values less than 1.0 x 10(-4) for each the men- and the women-specific analyses. We further selected 73 SNPs that were consistently associated with metabolic syndrome parameters in previous genome-wide association studies to check for their association with plasma adiponectin. RESULTS: The ADIPOQ locus showed genome-wide significant p-values in the combined (p=4.3 x 10(-24)) as well as in both women- and men-specific analyses (p=8.7 x 10(-17) and p=2.5 x 10(-11), respectively). None of the other 39 top signal SNPs showed evidence for association in the replication analysis. None of 73 SNPs from metabolic syndrome loci exhibited association with plasma adiponectin (p>0.01). CONCLUSIONS: We demonstrated the ADIPOQ gene as the only major gene for plasma adiponectin, which explains 6.7% of the phenotypic variance. We further found that neither this gene nor any of the metabolic syndrome loci explained the sex differences observed for plasma adiponectin. Larger studies are needed to identify more moderate genetic determinants of plasma adiponectin.
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The knowledge of the relationship that links radiation dose and image quality is a prerequisite to any optimization of medical diagnostic radiology. Image quality depends, on the one hand, on the physical parameters such as contrast, resolution, and noise, and on the other hand, on characteristics of the observer that assesses the image. While the role of contrast and resolution is precisely defined and recognized, the influence of image noise is not yet fully understood. Its measurement is often based on imaging uniform test objects, even though real images contain anatomical backgrounds whose statistical nature is much different from test objects used to assess system noise. The goal of this study was to demonstrate the importance of variations in background anatomy by quantifying its effect on a series of detection tasks. Several types of mammographic backgrounds and signals were examined by psychophysical experiments in a two-alternative forced-choice detection task. According to hypotheses concerning the strategy used by the human observers, their signal to noise ratio was determined. This variable was also computed for a mathematical model based on the statistical decision theory. By comparing theoretical model and experimental results, the way that anatomical structure is perceived has been analyzed. Experiments showed that the observer's behavior was highly dependent upon both system noise and the anatomical background. The anatomy partly acts as a signal recognizable as such and partly as a pure noise that disturbs the detection process. This dual nature of the anatomy is quantified. It is shown that its effect varies according to its amplitude and the profile of the object being detected. The importance of the noisy part of the anatomy is, in some situations, much greater than the system noise. Hence, reducing the system noise by increasing the dose will not improve task performance. This observation indicates that the tradeoff between dose and image quality might be optimized by accepting a higher system noise. This could lead to a better resolution, more contrast, or less dose.
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Plants such as Arabidopsis thaliana respond to foliar shade and neighbors who may become competitors for light resources by elongation growth to secure access to unfiltered sunlight. Challenges faced during this shade avoidance response (SAR) are different under a light-absorbing canopy and during neighbor detection where light remains abundant. In both situations, elongation growth depends on auxin and transcription factors of the phytochrome interacting factor (PIF) class. Using a computational modeling approach to study the SAR regulatory network, we identify and experimentally validate a previously unidentified role for long hypocotyl in far red 1, a negative regulator of the PIFs. Moreover, we find that during neighbor detection, growth is promoted primarily by the production of auxin. In contrast, in true shade, the system operates with less auxin but with an increased sensitivity to the hormonal signal. Our data suggest that this latter signal is less robust, which may reflect a cost-to-robustness tradeoff, a system trait long recognized by engineers and forming the basis of information theory.
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Genomic approaches to the study of the expression of plant genes induced in response to disease and attack are now showing that there is an intimate association between pathogen perception and general stress detection.
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Glutamine has multiple roles in brain metabolism and its concentration can be altered in various pathological conditions. An accurate knowledge of its concentration is therefore highly desirable to monitor and study several brain disorders in vivo. However, in recent years, several MRS studies have reported conflicting glutamine concentrations in the human brain. A recent hypothesis for explaining these discrepancies is that a short T2 component of the glutamine signal may impact on its quantification at long echo times. The present study therefore aimed to investigate the impact of acquisition parameters on the quantified glutamine concentration using two different acquisition techniques, SPECIAL at ultra-short echo time and MEGA-SPECIAL at moderate echo time. For this purpose, MEGA-SPECIAL was optimized for the first time for glutamine detection. Based on the very good agreement of the glutamine concentration obtained between the two measurements, it was concluded that no impact of a short T2 component of the glutamine signal was detected.
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Remote sensing image processing is nowadays a mature research area. The techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics, and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, image coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This paper serves as a survey of methods and applications, and reviews the last methodological advances in remote sensing image processing.
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Detection of variations in blood glucose concentrations by pancreatic beta-cells and a subsequent appropriate secretion of insulin are key events in the control of glucose homeostasis. Because a decreased capability to sense glycemic changes is a hallmark of type 2 diabetes, the glucose signalling pathway leading to insulin secretion in pancreatic beta-cells has been extensively studied. This signalling mechanism depends on glucose metabolism and requires the presence of specific molecules such as GLUT2, glucokinase and the K(ATP) channel subunits Kir6.2 and SUR1. Other cells are also able to sense variations in glycemia or in local glucose concentrations and to modulate different physiological functions participating in the general control of glucose and energy homeostasis. These include cells forming the hepatoportal vein glucose sensor, which controls glucose storage in the liver, counterregulation, food intake and glucose utilization by peripheral tissues and neurons in the hypothalamus and brainstem whose firing rates are modulated by local variations in glucose concentrations or, when not protected by a blood-brain barrier, directly by changes in blood glucose levels. These glucose-sensing neurons are involved in the control of insulin and glucagon secretion, food intake and energy expenditure. Here, recent physiological studies performed with GLUT2-/- mice will be described, which indicate that this transporter is essential for glucose sensing by pancreatic beta-cells, by the hepatoportal sensor and by sensors, probably located centrally, which control activity of the autonomic nervous system and stimulate glucagon secretion. These studies may pave the way to a fine dissection of the molecular and cellular components of extra-pancreatic glucose sensors involved in the control of glucose and energy homeostasis.
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Combining bacterial bioreporters with microfluidics systems holds great promise for in-field detection of chemical or toxicity targets. Recently we showed how Escherichia coli cells engineered to produce a variant of green fluorescent protein after contact to arsenite and arsenate can be encapsulated in agarose beads and incorporated into a microfluidic chip to create a device for in-field detection of arsenic, a contaminant of well known toxicity and carcinogenicity in potable water both in industrialized and developing countries. Cell-beads stored in the microfluidics chip at -20°C retained inducibility up to one month and we were able to reproducibly discriminate concentrations of 10 and 50 μg arsenite per L (the drinking water standards for European countries and the United States, and for the developing countries, respectively) from the blank in less than 200 minutes. We discuss here the reasons for decreasing bioreporter signal development upon increased storage of cell beads but also show how this decrease can be reduced, leading to a faster detection and a longer lifetime of the device.
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In order to improve the efficacy and safety of treatments, drug dosage needs to be adjusted to the actual needs of each patient in a truly personalized medicine approach. Key for widespread dosage adjustment is the availability of point-of-care devices able to measure plasma drug concentration in a simple, automated, and cost-effective fashion. In the present work, we introduce and test a portable, palm-sized transmission-localized surface plasmon resonance (T-LSPR) setup, comprised of off-the-shelf components and coupled with DNA-based aptamers specific to the antibiotic tobramycin (467 Da). The core of the T-LSPR setup are aptamer-functionalized gold nanoislands (NIs) deposited on a glass slide covered with fluorine-doped tin oxide (FTO), which acts as a biosensor. The gold NIs exhibit localized plasmon resonance in the visible range matching the sensitivity of the complementary metal oxide semiconductor (CMOS) image sensor employed as a light detector. The combination of gold NIs on the FTO substrate, causing NIs size and pattern irregularity, might reduce the overall sensitivity but confers extremely high stability in high-ionic solutions, allowing it to withstand numerous regeneration cycles without sensing losses. With this rather simple T-LSPR setup, we show real-time label-free detection of tobramycin in buffer, measuring concentrations down to 0.5 μM. We determined an affinity constant of the aptamer-tobramycin pair consistent with the value obtained using a commercial propagating-wave based SPR. Moreover, our label-free system can detect tobramycin in filtered undiluted blood serum, measuring concentrations down to 10 μM with a theoretical detection limit of 3.4 μM. While the association signal of tobramycin onto the aptamer is masked by the serum injection, the quantification of the captured tobramycin is possible during the dissociation phase and leads to a linear calibration curve for the concentrations over the tested range (10-80 μM). The plasmon shift following surface binding is calculated in terms of both plasmon peak location and hue, with the latter allowing faster data elaboration and real-time display of the results. The presented T-LSPR system shows for the first time label-free direct detection and quantification of a small molecule in the complex matrix of filtered undiluted blood serum. Its uncomplicated construction and compact size, together with the remarkable performances, represent a leap forward toward effective point-of-care devices for therapeutic drug concentration monitoring.
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The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field.