Mass detection on mammograms: influence of signal shape uncertainty on human and model observers.

We studied the influence of signal variability on human and model observers for detection tasks with realistic simulated masses superimposed on real patient mammographic backgrounds and synthesized mammographic backgrounds (clustered lumpy backgrounds, CLB). Results under the signal-known-exactly (SKE) paradigm were compared with signal-known-statistically (SKS) tasks for which the observers did not have prior knowledge of the shape or size of the signal. Human observers' performance did not vary significantly when benign masses were superimposed on real images or on CLB. Uncertainty and variability in signal shape did not degrade human performance significantly compared with the SKE task, while variability in signal size did. Implementation of appropriate internal noise components allowed the fit of model observers to human performance.

A semi-automatic computerized method to measure baroreflex-mediated heart rate responses that reduces interobserver variability

Arterial baroreflex sensitivity estimated by pharmacological impulse stimuli depends on intrinsic signal variability and usually a subjective choice of blood pressure (BP) and heart rate (HR) values. We propose a semi-automatic method to estimate cardiovascular reflex sensitivity to bolus infusions of phenylephrine and nitroprusside. Beat-to-beat BP and HR time series for male Wistar rats (N = 13) were obtained from the digitized signal (sample frequency = 2 kHz) and analyzed by the proposed method (PRM) developed in Matlab language. In the PRM, time series were low-pass filtered with zero-phase distortion (3rd order Butterworth used in the forward and reverse direction) and presented graphically, and parameters were selected interactively. Differences between basal mean values and peak BP (deltaBP) and HR (deltaHR) values after drug infusions were used to calculate baroreflex sensitivity indexes, defined as the deltaHR/deltaBP ratio. The PRM was compared to the method traditionally (TDM) employed by seven independent observers using files for reflex bradycardia (N = 43) and tachycardia (N = 61). Agreement was assessed by Bland and Altman plots. Dispersion among users, measured as the standard deviation, was higher for TDM for reflex bradycardia (0.60 ± 0.46 vs 0.21 ± 0.26 bpm/mmHg for PRM, P < 0.001) and tachycardia (0.83 ± 0.62 vs 0.28 ± 0.28 bpm/mmHg for PRM, P < 0.001). The advantage of the present method is related to its objectivity, since the routine automatically calculates the desired parameters according to previous software instructions. This is an objective, robust and easy-to-use tool for cardiovascular reflex studies.

In vivo brain macromolecule signals in healthy and glioblastoma mouse models: (1) H magnetic resonance spectroscopy, post-processing and metabolite quantification at 14.1 T.

In (1) H magnetic resonance spectroscopy, macromolecule signals underlay metabolite signals, and knowing their contribution is necessary for reliable metabolite quantification. When macromolecule signals are measured using an inversion-recovery pulse sequence, special care needs to be taken to correctly remove residual metabolite signals to obtain a pure macromolecule spectrum. Furthermore, since a single spectrum is commonly used for quantification in multiple experiments, the impact of potential macromolecule signal variability, because of regional differences or pathologies, on metabolite quantification has to be assessed. In this study, we introduced a novel method to post-process measured macromolecule signals that offers a flexible and robust way of removing residual metabolite signals. This method was applied to investigate regional differences in the mouse brain macromolecule signals that may affect metabolite quantification when not taken into account. However, since no significant differences in metabolite quantification were detected, it was concluded that a single macromolecule spectrum can be generally used for the quantification of healthy mouse brain spectra. Alternatively, the study of a mouse model of human glioma showed several alterations of the macromolecule spectrum, including, but not limited to, increased mobile lipid signals, which had to be taken into account to avoid significant metabolite quantification errors.

L’intégration de la prise de décision visuo-motrice et d’action motrice dans des conditions ambiguës

La prise de décision est un mécanisme qui fait intervenir les structures neuronales supérieures afin d’effectuer un lien entre la perception du signal et l’action. Plusieurs travaux qui cherchent à comprendre les mécanismes de la prise de décision sont menés à divers ni- veaux allant de l’analyse comportementale cognitive jusqu'à la modélisation computationnelle. Le but de ce projet a été d’évaluer d’un instant à l’autre comment la variabilité du signal observé («bruit»), influence la capacité des sujets humains à détecter la direction du mouvement dans un stimulus visuel. Dans ces travaux, nous avons éliminé l’une des sources potentielles de variabilité, la variabilité d’une image à l’autre, dans le nombre de points qui portaient les trois signaux de mouvements cohérents (gauche, droite, et aléatoire) dans les stimuli de Kinématogramme de points aléatoires (KPA), c’est-à-dire la variabilité d’origine périphérique. Les stimuli KPA de type « V6 » étaient des stimuli KPA standard avec une variabilité instantanée du signal, et par contre les stimuli KPA de type « V8 », étaient modifiés pour éliminer la variabilité stochastique due à la variabilité du nombre de pixels d’un instant à l’autre qui portent le signal cohérent. Si la performance des sujets, qui correspond à leur temps de réaction et au nombre de bonnes réponses, diffère en réponse aux stimuli dont le nombre de points en mouvement cohérent varie (V6) ou ne varie pas (V8), ceci serait une preuve que la variabilité d’origine périphérique modulerait le processus décisionnel. Par contre, si la performance des sujets ne diffère pas entre ces deux types de stimuli, ceci serait une preuve que la source majeure de variabilité de performance est d’origine centrale. Dans nos résultats nous avons constaté que le temps de réaction et le nombre de bonnes réponses sont modulés par la preuve nette du mouvement cohérent. De plus on a pu établir qu’en éliminant la variabilité d’origine périphérique définit ci-dessus, on n’observe pas réellement de modification dans les enregistrements. Ce qui nous à amené à penser qu’il n y a pas de distinction claire entre la distribution des erreurs et les bonnes réponses effectuées pour chacun des essais entre les deux stimuli que nous avons utilisé : V6 et V8. C’est donc après avoir mesuré la « quantité d’énergie » que nous avons proposé que la variabilité observée dans les résultats serait probablement d’origine centrale.

Análise de desempenho do Criptossistema Fuzzy Vault em aplicações reais

Pós-graduação em Ciência da Computação - IBILCE

Exploring copper nanostructures as highly uniform and reproducible substrates for plasmon-enhanced fluorescence

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Evidence for a climate signal in trends of global crop yield variability over the past 50 years

Low variability of crop production from year to year is desirable for many reasons, including reduced income risk and stability of supplies. Therefore, it is important to understand the nature of yield variability, whether it is changing through time, and how it varies between crops and regions. Previous studies have shown that national crop yield variability has changed in the past, with the direction and magnitude dependent on crop type and location. Whilst such studies acknowledge the importance of climate variability in determining yield variability, it has been assumed that its magnitude and its effect on crop production have not changed through time and, hence, that changes to yield variability have been due to non-climatic factors. We address this assumption by jointly examining yield and climate variability for three major crops (rice, wheat and maize) over the past 50 years. National yield time series and growing season temperature and precipitation were de-trended and related using multiple linear regression. Yield variability changed significantly in half of the crop–country combinations examined. For several crop–country combinations, changes in yield variability were related to changes in climate variability.

Evidence for a respiratory component, similar to mammalian respiratory sinus arrhythmia, in the heart rate variability signal from the rattlesnake, Crotalus durissus terrificus

Autonomic control of heart rate variability and the central location of vagal preganglionic neurones (VPN) were examined in the rattlesnake ( Crotalus durissus terrificus), in order to determine whether respiratory sinus arrhythmia (RSA) occurred in a similar manner to that described for mammals. Resting ECG signals were recorded in undisturbed snakes using miniature datalogging devices, and the presence of oscillations in heart rate (f(H)) was assessed by power spectral analysis (PSA). This mathematical technique provides a graphical output that enables the estimation of cardiac autonomic control by measuring periodic changes in the heart beat interval. At fH above 19 min(-1) spectra were mainly characterised by low frequency components, reflecting mainly adrenergic tonus on the heart. By contrast, at f(H) below 19 min(-1) spectra typically contained high frequency components, demonstrated to be cholinergic in origin. Snakes with a f(H) > 19 min(-1) may therefore have insufficient cholinergic tonus and/or too high an adrenergic tonus acting upon the heart for respiratory sinus arrhythmia ( RSA) to develop. A parallel study monitored f(Hd) simultaneously with the intraperitoneal pressures associated with lung inflation. Snakes with a fH < 19 min(-1) exhibited a high frequency (HF) peak in the power spectrum, which correlated with ventilation rate (f(V)). Adrenergic blockade by propranolol infusion increased the variability of the ventilation cycle, and the oscillatory component of the f(H) spectrum broadened accordingly. Infusion of atropine to effect cholinergic blockade abolished this HF component, confirming a role for vagal control of the heart in matching f(H) and f(V) in the rattlesnake. A neuroanatomical study of the brainstem revealed two locations for vagal preganglionic neurones (VPN). This is consistent with the suggestion that generation of ventilatory components in the heart rate variability (HRV) signal are dependent on spatially distinct loci for cardiac VPN. Therefore, this study has demonstrated the presence of RSA in the HRV signal and a dual location for VPN in the rattlesnake. We suggest there to be a causal relationship between these two observations.

Rainfall variability at decadal and longer time scales: signal or noise?

Rainfall variability occurs over a wide range of temporal scales. Knowledge and understanding of such variability can lead to improved risk management practices in agricultural and other industries. Analyses of temporal patterns in 100 yr of observed monthly global sea surface temperature and sea level pressure data show that the single most important cause of explainable, terrestrial rainfall variability resides within the El Nino-Southern Oscillation (ENSO) frequency domain (2.5-8.0 yr), followed by a slightly weaker but highly significant decadal signal (9-13 yr), with some evidence of lesser but significant rainfall variability at interclecadal time scales (15-18 yr). Most of the rainfall variability significantly linked to frequencies tower than ENSO occurs in the Australasian region, with smaller effects in North and South America, central and southern Africa, and western Europe. While low-frequency (LF) signals at a decadal frequency are dominant, the variability evident was ENSO-like in all the frequency domains considered. The extent to which such LF variability is (i) predictable and (ii) either part of the overall ENSO variability or caused by independent processes remains an as yet unanswered question. Further progress can only be made through mechanistic studies using a variety of models.

Influence of third-generation oral contraceptives on the complexity analysis and symbolic dynamics of heart rate variability

Objective To evaluate the influence of oral contraceptives (OCs) containing 20 mu mu g ethinylestradiol (EE) and 150 mu mu g gestodene (GEST) on the autonomic modulation of heart rate (HR) in women. Methods One-hundred and fifty-five women aged 24 +/-+/- 2 years were divided into four groups according to their physical activity and the use or not of an OC: active-OC, active-non-OC (NOC), sedentary-OC, and sedentary-NOC. The heart rate was registered in real time based on the electrocardiogram signal for 15 minutes, in the supine-position. The heart rate variability (HRV) was analysed using Shannon`s entropy (SE), conditional entropy (complexity index [CInd] and normalised CInd [NCI]), and symbolic analysis (0V%, 1V%, 2LV%, and 2ULV%). For statistical analysis the Kruskal-Wallis test with Dunn post hoc and the Wilcoxon test (p < 0.05 was considered significant) were applied. Results Treatment with this COC caused no significant changes in SE, CInd, NCI, or symbolic analysis in either active or sedentary groups. Active groups presented higher values for SE and 2ULV%, and lower values for 0V% when compared to sedentary groups (p < 0.05). Conclusion HRV patterns differed depending on life style; the non-linear method applied was highly reliable for identifying these changes. The use of OCs containing 20 mu mu g EE and 150 mu mu g GEST does not influence HR autonomic modulation.

Parallel programming in biomedical signal processing

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Genetic variability of the mTOR pathway and prostate cancer risk in the European Prospective Investigation on Cancer (EPIC)

The mTOR (mammalian target of rapamycin) signal transduction pathway integrates various signals, regulating ribosome biogenesis and protein synthesis as a function of available energy and amino acids, and assuring an appropriate coupling of cellular proliferation with increases in cell size. In addition, recent evidence has pointed to an interplay between the mTOR and p53 pathways. We investigated the genetic variability of 67 key genes in the mTOR pathway and in genes of the p53 pathway which interact with mTOR. We tested the association of 1,084 tagging SNPs with prostate cancer risk in a study of 815 prostate cancer cases and 1,266 controls nested within the European Prospective Investigation into Cancer and Nutrition (EPIC). We chose the SNPs (n = 11) with the strongest association with risk (p<0.01) and sought to replicate their association in an additional series of 838 prostate cancer cases and 943 controls from EPIC. In the joint analysis of first and second phase two SNPs of the PRKCI gene showed an association with risk of prostate cancer (ORallele = 0.85, 95% CI 0.78–0.94, p = 1.3×10−3 for rs546950 and ORallele = 0.84, 95% CI 0.76–0.93, p = 5.6×10−4 for rs4955720). We confirmed this in a meta-analysis using as replication set the data from the second phase of our study jointly with the first phase of the Cancer Genetic Markers of Susceptibility (CGEMS) project. In conclusion, we found an association with prostate cancer risk for two SNPs belonging to PRKCI, a gene which is frequently overexpressed in various neoplasms, including prostate cancer.

Inflammation and TCR Signal Strength Determine the Breadth of the T Cell Response in a Bim-Dependent Manner.

Generating a diverse T cell memory population through vaccination is a promising strategy to overcome pathogen epitope variability and tolerance to tumor Ags. The effector and memory pool becomes broad in TCR diversity by recruiting high- and low-affinity T cells. We wanted to determine which factors dictate whether a memory T cell pool has a broad versus focused repertoire. We find that inflammation increases the magnitude of low- and high-affinity T cell responses equally well, arguing against a synergistic effect of TCR and inflammatory signals on T cell expansion. We dissect the differential effects of TCR signal strength and inflammation and demonstrate that they control effector T cell survival in a bim-dependent manner. Importantly, bim-dependent cell death is overcome with a high Ag dose in the context of an inflammatory environment. Our data define the framework for the generation of a broad T cell memory pool to inform future vaccine design.

Waveform inversion of crosshole georadar data: influence of source wavelet variability and the suitability of a single wavelet assumption

Waveform-based tomographic imaging of crosshole georadar data is a powerful method to investigate the shallow subsurface because of its ability to provide images of electrical properties in near-surface environments with unprecedented spatial resolution. A critical issue with waveform inversion is the a priori unknown source signal. Indeed, the estimation of the source pulse is notoriously difficult but essential for the effective application of this method. Here, we explore the viability and robustness of a recently proposed deconvolution-based procedure to estimate the source pulse during waveform inversion of crosshole georadar data, where changes in wavelet shape with location as a result of varying near-field conditions and differences in antenna coupling may be significant. Specifically, we examine whether a single, average estimated source current function can adequately represent the pulses radiated at all transmitter locations during a crosshole georadar survey, or whether a separate source wavelet estimation should be performed for each transmitter gather. Tests with synthetic and field data indicate that remarkably good tomographic reconstructions can be obtained using a single estimated source pulse when moderate to strong variability exists in the true source signal with antenna location. Only in the case of very strong variability in the true source pulse are tomographic reconstructions clearly improved by estimating a different source wavelet for each transmitter location.

Correction for heart rate variability during 3D whole heart MR coronary angiography.

PURPOSE: To evaluate the effect of a real-time adaptive trigger delay on image quality to correct for heart rate variability in 3D whole-heart coronary MR angiography (MRA). MATERIALS AND METHODS: Twelve healthy adults underwent 3D whole-heart coronary MRA with and without the use of an adaptive trigger delay. The moment of minimal coronary artery motion was visually determined on a high temporal resolution MRI. Throughout the scan performed without adaptive trigger delay, trigger delay was kept constant, whereas during the scan performed with adaptive trigger delay, trigger delay was continuously updated after each RR-interval using physiological modeling. Signal-to-noise, contrast-to-noise, vessel length, vessel sharpness, and subjective image quality were compared in a blinded manner. RESULTS: Vessel sharpness improved significantly for the middle segment of the right coronary artery (RCA) with the use of the adaptive trigger delay (52.3 +/- 7.1% versus 48.9 +/- 7.9%, P = 0.026). Subjective image quality was significantly better in the middle segments of the RCA and left anterior descending artery (LAD) when the scan was performed with adaptive trigger delay compared to constant trigger delay. CONCLUSION: Our results demonstrate that the use of an adaptive trigger delay to correct for heart rate variability improves image quality mainly in the middle segments of the RCA and LAD.