The AF-1 Domain of the Orphan Nuclear Receptor NOR-1 Mediates Trans-activation, Coactivator Recruitment, and Activation by the Purine Anti-metabolite 6-Mercaptopurine

NOR-1/NR4A3 is an orphan member of the nuclear hormone receptor superfamily. NOR-1 and its close relatives Nurr1 and Nur77 are members of the NR4A subgroup of nuclear receptors. Members of the NR4A subgroup are induced through multiple signal transduction pathways. They have been implicated in cell proliferation, differentiation, T-cell apoptosis, chondrosarcomas, neurological disorders, inflammation, and atherogenesis. However, the mechanism of transcriptional activation, coactivator recruitment, and agonist-mediated activation remain obscure. Hence, we examined the molecular basis of NOR-1-mediated activation. We observed that NOR-1 trans-activates gene expression in a cell- and target-specific manner; moreover, it operates in an activation function (AF)-1-dependent manner. The N-terminal AF-1 domain delimited to between amino acids 1 and 112, preferentially recruits the steroid receptor coactivator (SRC). Furthermore, SRC-2 modulates the activity of the AF-1 domain but not the C-terminal ligand binding domain (LBD). Homology modeling indicated that the NOR-1 LBD was substantially different from that of hRORbeta, a closely related AF-2-dependent receptor. In particular, the hydrophobic cleft characteristic of nuclear receptors was replaced with a very hydrophilic surface with a distinct topology. This observation may account for the inability of this nuclear receptor LBD to efficiently mediate cofactor recruitment and transcriptional activation. In contrast, the N-terminal AF-1 is necessary for cofactor recruitment and can independently conscript coactivators. Finally, we demonstrate that the purine anti-metabolite 6-mercaptopurine, a widely used antineoplastic and anti-inflammatory drug, activates NOR-1 in an AF-1-dependent manner. Additional 6-mercaptopurine analogs all efficiently activated NOR-1, suggesting that the signaling pathways that modulate proliferation via inhibition of de novo purine and/or nucleic acid biosynthesis are involved in the regulation NR4A activity. We hypothesize that the NR4A subgroup mediates the genotoxic stress response and suggest that this subgroup may function as sensors that respond to genotoxicity.

Ectodysplasin has a dual role in ectodermal organogenesis: inhibition of Bmp activity and induction of Shh expression.

Ectodermal organogenesis is regulated by inductive and reciprocal signalling cascades that involve multiple signal molecules in several conserved families. Ectodysplasin-A (Eda), a tumour necrosis factor-like signalling molecule, and its receptor Edar are required for the development of a number of ectodermal organs in vertebrates. In mice, lack of Eda leads to failure in primary hair placode formation and missing or abnormally shaped teeth, whereas mice overexpressing Eda are characterized by enlarged hair placodes and supernumerary teeth and mammary glands. Here, we report two signalling outcomes of the Eda pathway: suppression of bone morphogenetic protein (Bmp) activity and upregulation of sonic hedgehog (Shh) signalling. Recombinant Eda counteracted Bmp4 activity in developing teeth and, importantly, inhibition of BMP activity by exogenous noggin partially restored primary hair placode formation in Eda-deficient skin in vitro, indicating that suppression of Bmp activity was compromised in the absence of Eda. The downstream effects of the Eda pathway are likely to be mediated by transcription factor nuclear factor-kappaB (NF-kappaB), but the transcriptional targets of Edar have remained unknown. Using a quantitative approach, we show in cultured embryonic skin that Eda induced the expression of two Bmp inhibitors, Ccn2/Ctgf (CCN family protein 2/connective tissue growth factor) and follistatin. Moreover, our data indicate that Shh is a likely transcriptional target of Edar, but, unlike noggin, recombinant Shh was unable to rescue primary hair placode formation in Eda-deficient skin explants.

Arteriovenous malformation in meningothelial meningioma: case report.

An unusual association of a meningioma and an arteriovenous malformation is reported. A 68-year-old man developed left homonymous hemianopsia, left hemiparesis, and gaze palsy. Magnetic resonance imaging showed a right occipital mass lesion containing multiple signal-void areas with tubular and honeycomb appearance, suggesting a marked vascular component. An angiogram showed abnormal vasculature in the mass supplied by the posterior cerebral artery and a dural arteriovenous malformation on the tentorium. Neuropathological examination after total removal of the mass revealed a meningothelial meningioma including major portions of an arteriovenous malformation that extended from the dura and leptomeninges, through the meningioma, and into the occipital lobe, where the tumor was located.

A hybrid feature selection approach for the early diagnosis of Alzheimer's disease

Objective. Recently, significant advances have been made in the early diagnosis of Alzheimer’s disease from EEG. However, choosing suitable measures is a challenging task. Among other measures, frequency Relative Power and loss of complexity have been used with promising results. In the present study we investigate the early diagnosis of AD using synchrony measures and frequency Relative Power on EEG signals, examining the changes found in different frequency ranges. Approach. We first explore the use of a single feature for computing the classification rate, looking for the best frequency range. Then, we present a multiple feature classification system that outperforms all previous results using a feature selection strategy. These two approaches are tested in two different databases, one containing MCI and healthy subjects (patients age: 71.9 ± 10.2, healthy subjects age: 71.7 ± 8.3), and the other containing Mild AD and healthy subjects (patients age: 77.6 ± 10.0; healthy subjects age: 69.4± 11.5). Main Results. Using a single feature to compute classification rates we achieve a performance of 78.33% for the MCI data set and of 97.56 % for Mild AD. Results are clearly improved using the multiple feature classification, where a classification rate of 95% is found for the MCI data set using 11 features, and 100% for the Mild AD data set using 4 features. Significance. The new features selection method described in this work may be a reliable tool that could help to design a realistic system that does not require prior knowledge of a patient's status. With that aim, we explore the standardization of features for MCI and Mild AD data sets with promising results.

Robust and fast vowel recognition using optimum-path forest

The applications of Automatic Vowel Recognition (AVR), which is a sub-part of fundamental importance in most of the speech processing systems, vary from automatic interpretation of spoken language to biometrics. State-of-the-art systems for AVR are based on traditional machine learning models such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), however, such classifiers can not deal with efficiency and effectiveness at the same time, existing a gap to be explored when real-time processing is required. In this work, we present an algorithm for AVR based on the Optimum-Path Forest (OPF), which is an emergent pattern recognition technique recently introduced in literature. Adopting a supervised training procedure and using speech tags from two public datasets, we observed that OPF has outperformed ANNs, SVMs, plus other classifiers, in terms of training time and accuracy. ©2010 IEEE.

A snoring classifier based on heart rate variability analysis

The effect of snoring on the cardiovascular system is not well-known. In this study we analyzed the Heart Rate Variability (HRV) differences between light and heavy snorers. The experiments are done on the full-whole-night polysomnography (PSG) with ECG and audio channels from patient group (heavy snorer) and control group (light snorer), which are gender- and age-paired, totally 30 subjects. A feature Snoring Density (SND) of audio signal as classification criterion and HRV features are computed. Mann-Whitney statistical test and Support Vector Machine (SVM) classification are done to see the correlation. The result of this study shows that snoring has close impact on the HRV features. This result can provide a deeper insight into the physiological understand of snoring. © 2011 CCAL.

Neural networks models for wear patterns recognition of single-point dresser

Grinding is a workpiece finishing process for advanced products and surfaces. However, the constant friction between workpiece and grinding wheel causes the latter to lose its sharpness, thereby impairing the result of the grinding process. When this occurs, the dressing process is essential to sharpen the worn grains of the grinding wheel. The dressing conditions strongly influence the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The purpose of this study was to classify the wear condition of a single-point dresser using intelligent systems whose inputs were obtained by digitally processing acoustic emission signals. Two multilayer perceptron (MLP) neural networks were compared for their classification ability, one using the root mean square (RMS) statistics and another the ratio of power (ROP) statistics as input. In this study, it was found that the harmonic content of the acoustic emission signal is influenced by the condition of the dresser, and that the condition of the tool under study can be classified by using the aforementioned statistics to feed a neural network. © IFAC.

Classificação de sinais acústicos utilizando a transformada wavelet discreta e a decomposição de modo empírico: aplicações na área de alimentos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Ultrasonic sensor signals and optimum path forest classifier for the microstructural characterization of thermally-aged inconel 625 alloy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Antennas for the detection of radio emission pulses from cosmic-ray induced air showers at the Pierre Auger Observatory

The Pierre Auger Observatory is exploring the potential of the radio detection technique to study extensive air showers induced by ultra-high energy cosmic rays. The Auger Engineering Radio Array (AERA) addresses both technological and scientific aspects of the radio technique. A first phase of AERA has been operating since September 2010 with detector stations observing radio signals at frequencies between 30 and 80 MHz. In this paper we present comparative studies to identify and optimize the antenna design for the final configuration of AERA consisting of 160 individual radio detector stations. The transient nature of the air shower signal requires a detailed description of the antenna sensor. As the ultra-wideband reception of pulses is not widely discussed in antenna literature, we review the relevant antenna characteristics and enhance theoretical considerations towards the impulse response of antennas including polarization effects and multiple signal reflections. On the basis of the vector effective length we study the transient response characteristics of three candidate antennas in the time domain. Observing the variation of the continuous galactic background intensity we rank the antennas with respect to the noise level added to the galactic signal.

Performance analysis of reconstruction algorithms for breast microwave imaging

The problem of localizing a scatterer, which represents a tumor, in a homogeneous circular domain, which represents a breast, is addressed. A breast imaging method based on microwaves is considered. The microwave imaging involves to several techniques for detecting, localizing and characterizing tumors in breast tissues. In all such methods an electromagnetic inverse scattering problem exists. For the scattering detection method, an algorithm based on a linear procedure solution, inspired by MUltiple SIgnal Classification algorithm (MUSIC) and Time Reversal method (TR), is implemented. The algorithm returns a reconstructed image of the investigation domain in which it is detected the scatterer position. This image is called pseudospectrum. A preliminary performance analysis of the algorithm vying the working frequency is performed: the resolution and the signal-to-noise ratio of the pseudospectra are improved if a multi-frequency approach is considered. The Geometrical Mean-MUSIC algorithm (GM- MUSIC) is proposed as multi-frequency method. The performance of the GMMUSIC is tested in different real life computer simulations. The performed analysis shows that the algorithm detects the scatterer until the electrical parameters of the breast are known. This is an evident limit, since, in a real life situation, the anatomy of the breast is unknown. An improvement in GM-MUSIC is proposed: the Eye-GMMUSIC algorithm. Eye-GMMUSIC algorithm needs no a priori information on the electrical parameters of the breast. It is an optimizing algorithm based on the pattern search algorithm: it searches the breast parameters which minimize the Signal-to-Clutter Mean Ratio (SCMR) in the signal. Finally, the GM-MUSIC and the Eye-GMMUSIC algorithms are tested on a microwave breast cancer detection system consisting of an dipole antenna, a Vector Network Analyzer and a novel breast phantom built at University of Bologna. The reconstruction of the experimental data confirm the GM-MUSIC ability to localize a scatterer in a homogeneous medium.

Compressed sensing based cyclic feature spectrum sensing for cognitive radios

Spectrum sensing is currently one of the most challenging design problems in cognitive radio. A robust spectrum sensing technique is important in allowing implementation of a practical dynamic spectrum access in noisy and interference uncertain environments. In addition, it is desired to minimize the sensing time, while meeting the stringent cognitive radio application requirements. To cope with this challenge, cyclic spectrum sensing techniques have been proposed. However, such techniques require very high sampling rates in the wideband regime and thus are costly in hardware implementation and power consumption. In this thesis the concept of compressed sensing is applied to circumvent this problem by utilizing the sparsity of the two-dimensional cyclic spectrum. Compressive sampling is used to reduce the sampling rate and a recovery method is developed for re- constructing the sparse cyclic spectrum from the compressed samples. The reconstruction solution used, exploits the sparsity structure in the two-dimensional cyclic spectrum do-main which is different from conventional compressed sensing techniques for vector-form sparse signals. The entire wideband cyclic spectrum is reconstructed from sub-Nyquist-rate samples for simultaneous detection of multiple signal sources. After the cyclic spectrum recovery two methods are proposed to make spectral occupancy decisions from the recovered cyclic spectrum: a band-by-band multi-cycle detector which works for all modulation schemes, and a fast and simple thresholding method that works for Binary Phase Shift Keying (BPSK) signals only. In addition a method for recovering the power spectrum of stationary signals is developed as a special case. Simulation results demonstrate that the proposed spectrum sensing algorithms can significantly reduce sampling rate without sacrifcing performance. The robustness of the algorithms to the noise uncertainty of the wireless channel is also shown.

Targeting the PI3K/AKT/mTOR signaling pathway in medulloblastoma

Medulloblastoma is the most common malignant childhood brain tumor and is associated with a poor outcome. There is an urgent need to develop novel targeted therapeutic approaches for medulloblastoma, which will arise from an enhanced understanding of the disease at the molecular level. Medulloblastoma has been recognized to be a heterogeneous disease, and no recurrent cancer gene mutations have been found, although many of the mutations described so far affect key intracellular signaling pathways, such as sonic hedgehog (SHH) and Wnt/β-catenin. The PI3K/AKT/mTOR (PAM) signaling pathway controls key cellular responses, such as cell growth and proliferation, survival, migration and metabolism. Over the last decades, it has been recognized that this intracellular signaling pathway is frequently activated by genetic and epigenetic alterations in malignant brain tumors, including medulloblastoma. Clinical trials have started to evaluate the safety and efficacy of agents targeting this pathway in malignant brain tumors. Due to the complexity of the PAM signaling pathway, there remain significant difficulties in the development of novel therapeutic approaches. The future challenges in developing effective treatments for cancer patients include the development of predictive biomarkers and combinatorial approaches to effectively target multiple signal transduction pathways. In this review article, we will summarize the current knowledge about the role of PAM signaling in medulloblastoma and discuss the strategies that are currently being evaluated with targeted agents against this pathway.

Novel mechanisms for PKC family enzymes to regulate PI3K signaling pathway

Phosphatidylinositol 3-kinase (PI3K) generates membrane phospholipids that serve as second messengers to recruit signaling proteins to plasma membrane consequently regulating cell growth and survival. PI3K is a heterodimer consisting of a catalytic p110 subunit and a regulatory p85 subunit. Association of the p85 with other signal proteins is critical for induced PI3K activation. Activated PI3K, in turn, leads to signal flows through a variety of PI3K effectors including PDK1, AKT, GSK3, BAD, p70 S6K and NFκB. The PI3K pathway is under regulation by multiple signal proteins representing cross-talk between different signaling cascades. In this study, we have evaluated the role of protein kinase C family kinases on signaling through PI3K at multiple levels. Firstly, we observed that the action of PKC specific inhibitors like Ro-31-8220 and GF109203X was associated with an increased AKT phosphorylation and activity, suggesting that PKC kinases might play a negative role in the regulation of PI3K pathway. Then, we demonstrated the stimulation of AKT by PKC inhibition was dependent on functional PI3K enzyme and able to be transmitted to the AKT effector p70 S6K. Furthermore, we showed an inducible physical association between the PKCζ isotype and AKT, which was accompanied by an attenuated AKT activity. However, a kinase-dead form of PKC failed to affect AKT. In the second part of our research we revealed the ability of a different PKC family member, PKCδ to bind to the p85 subunit of PI3K in response to oxidative stress, a process requiring the activity of src tyrosine kinases. The interaction was demonstrated to be a direct and specific contact between the carboxyl terminal SH2 domain of p85 and tyrosine phosphorylated PKCδ. Several different types of agonists were capable to induce this association including tyrosine kinases and phorbol esters with PKCδ tyrosine phosphorylation being integral components. Finally, the PKCδ-PI3K complex was related to a reduction in the AKT phosphorylation induced by src. A kinase-deficient mutant of PKCδ was equally able to inhibit AKT signal as the wild type, indicative of a process independent of PKCδ catalytic activity. Altogether, our data illustrate different PKC isoforms regulating PI3K pathway at multiple levels, suggesting a mechanism to control signal flows through PI3K for normal cell activities. Although further investigation is required for full understanding of the regulatory mechanism, we propose that complex formation of signal proteins in PI3K pathway and specific PKC isoforms plays important role in their functional linkage. ^

Requirement of the Jak2 tyrosine kinase in Bcr -Abl oncogenic transformation

Philadelphia chromosome (Ph)-positive chronic myeloid leukemia is caused by a clonal myeloproliferative expansion of malignant primitive hematopoietic progenitor cells. The Ph results from the reciprocal translocation of the ends of chromosome 9 and 22, which generate Bcr-Abl fusion proteins. The Bcr-Abl proteins possess a constitutively activated Abl tyrosine kinase, which is the driving force responsible for causing leukemia. The activated Bcr-Abl tyrosine kinase stimulates multiple signal transduction pathway affecting growth, differentiation and survival of cells. It is known that the Bcr-Abl tyrosine kinase activates several signaling proteins including Stat5, which is a member of the Jak/Stat pathway that is activated by cytokines that control the growth and differentiation of normal hematopoietic cells. Our laboratory was the first one to report that Jak2 tyrosine kinase is activated in a human Bcr-Abl positive hematopoietic cell line. In this thesis, we further investigated the activation of Jak2 by Bcr-Abl. We found that Jak2 is activated not only in cultured Bcr-abl positive cell lines but also in blood cells from CML blast crisis patients. We also demonstrated that SH2 domain of Bcr-Abl is required for efficient activation Jak2. We further showed that Jak2 binds to the C-terminal domain of Bcr-Abl; tyrosine residue 1007, which is critical for Jak2 activation, is phosphorylated by Bcr-Abl. We searched downstream targets of Jak2 in Bcr-Abl positive cells. We treated Bcr-Abl positive cells with a Jak2 kinase inhibitor AG490 and found that c-Myc protein expression is inhibited by AG490. We further demonstrated that Jak2 inhibitor AG490 not only inhibit C-MYC transcription but also protect c-Myc protein from proteasome-dependent degradation. We also showed that AG490 did not affect Bcr-Abl kinase activity and Stat5 activation and its downstream target Bcl-xL expression. AG490 also induced apoptosis of Bcr-Abl positive cells, similar to Bcr-Abl kinase inhibitor STI571 (also termed Gliveec, a very effective drug for CML), but unlike STI571 the apoptosis effects induced by AG490 can not be rescued by IL-3 containing WEHI conditioned medium. We further established several Bcr-Abl positive clones that express a kinase-inactive Jak2 and found that these clones had reduced tumor formation in nude mice assays. Taken together, these results establish that Jak2 is activated in Bcr-Abl positive CML cells and it is required for c-Myc induction and the oncogenic effects of Bcr-Abl. Furthermore, Jak2 and Stat5 are two independent targets of Bcr-Abl. ^