Apoptosis rate and transcriptional response of pancreatic islets exposed to the PPAR gamma agonist Pioglitazone

To explore the molecular pathways underlying thiazolidinediones effects on pancreatic islets in conditions mimicking normo- and hyperglycemia, apoptosis rate and transcriptional response to Pioglitazone at both physiological and supraphysiological glucose concentrations were evaluated. Adult rat islets were cultured at physiological (5.6 mM) and supraphysiological (23 mM) glucose concentrations in presence of 10 μM Pioglitazone or vehicle. RNA expression profiling was evaluated with the PancChip 13k cDNA microarray after 24-h, and expression results for some selected genes were validated by qRT-PCR. The effects of Pioglitazone were investigated regarding apoptosis rate after 24-, 48- and 72-h. At 5.6 mM glucose, 101 genes were modulated by Pioglitazone, while 1,235 genes were affected at 23 mM glucose. Gene networks related to lipid metabolism were identified as altered by Pioglitazone at both glucose concentrations. At 23 mM glucose, cell cycle and cell death pathways were significantly regulated as well. At 5.6 mM glucose, Pioglitazone elicited a transient reduction in islets apoptosis rate while at 23 mM, Bcl2 expression was reduced and apoptosis rate was increased by Pioglitazone. Our data demonstrate that the effect of Pioglitazone on gene expression profile and apoptosis rate depends on the glucose concentration. The modulation of genes related to cell death and the increased apoptosis rate observed at supraphysiological glucose concentration raise concerns about Pioglitazone’s direct effects in conditions of hyperglycemia and reinforce the necessity of additional studies designed to evaluate TZDs effects on the preservation of β-cell function in situations where glucotoxicity might be more relevant than lipotoxicity.

Influence of INF-gamma gene polymorphism in HTLV-1 proviral load

Financial Support FAPESP, CNPq, CTC/FUNDHERP and INCTC.

Interferon-gamma and interleukin-10 production by mononuclear cells from patients with advanced head and neck cancer

OBJECTIVE: This study aims to evaluate the production of interferon-gamma and interleukin-10 by stimulated peripheral blood mononuclear cells isolated from patients with supraglottic laryngeal cancer before and after surgical treatment. METHODS: Fourteen patients with advanced supraglottic laryngeal cancer were studied. Cultures of peripheral blood mononuclear cells isolated during the preoperative and late postoperative periods were stimulated with concanavalin A and Bacille Calmette-Guerin, and the supernatant concentrations of interferon-gamma and interleukin-10 were measured. RESULTS: For non-stimulated cultures, the interferon-gamma levels produced by the preoperative period and the late postoperative period cultures were lower than the levels produced by the control group cultures. The interferon-gamma levels after stimulation with concanavalin A were higher in the late postoperative period cultures than in the preoperative evaluation cultures. Stimulation with Bacille Calmette-Guerin led to the production of similar levels of interferon-gamma and interleukin-10 by all cultures; thus, stimulation increased the levels of interferon-gamma produced by both the preoperative and postoperative cultures relative to the levels produced by the corresponding unstimulated cultures. CONCLUSION: Patients with advanced supraglottic laryngeal cancer exhibit an in vitro deficiency in interferongamma secretion by mononuclear cells. Stimulated cells seem to recover this function during the postoperative period.

Prospect on intergalactic magnetic field measurements with gamma-ray instruments

Observing high-energy gamma-rays from Active Galactic Nuclei (AGN) offers a unique potential to probe extremely tiny values of the intergalactic magnetic field (IGMF), a long standing question of astrophysics, astropa rticle physics and cosmology. Very high energy (VHE) photons from blazars propagating along the line of sight interact with the extragalactic background light (EBL) and produce e + e − pairs. Through inverse-Compton interaction, mainly on the cosmic microwave background (CMB), these pairs generate secondary GeV-TeV compo- nents accompanying the primary VHE signal. Such secondary components would be detected in the gamma-ray range as delayed “pair echos” for very weak IGMF ( B< 10 − 16 G ), while they should result in a spatially extended ga mma-ray emission around the source for higher IGMF values ( B> 10 − 16 G ). Coordinated observations with space (i.e. Fermi) and ground- based gamma-ray instruments, such as the pre sent Cherenkov experiments H.E.S.S., MAGIC and VERITAS, the future Cherenkov Telescope Array (CTA) Observatory, and the wide-field detectors such as HAWC and LHAASO, should allow to analyze and finally detect such echos, extended emission or pair halos, and to further characterize the IGMF.

Weighted Fourier–Laplace transforms in reproducing kernel Hilbert spaces on the sphere

We study the action of a weighted Fourier–Laplace transform on the functions in the reproducing kernel Hilbert space (RKHS) associated with a positive definite kernel on the sphere. After defining a notion of smoothness implied by the transform, we show that smoothness of the kernel implies the same smoothness for the generating elements (spherical harmonics) in the Mercer expansion of the kernel. We prove a reproducing property for the weighted Fourier–Laplace transform of the functions in the RKHS and embed the RKHS into spaces of smooth functions. Some relevant properties of the embedding are considered, including compactness and boundedness. The approach taken in the paper includes two important notions of differentiability characterized by weighted Fourier–Laplace transforms: fractional derivatives and Laplace–Beltrami derivatives.

Sharp estimates for eigenvalues of integral operators generated by dot product kernels on the sphere

We obtain explicit formulas for the eigenvalues of integral operators generated by continuous dot product kernels defined on the sphere via the usual gamma function. Using them, we present both, a procedure to describe sharp bounds for the eigenvalues and their asymptotic behavior near 0. We illustrate our results with examples, among them the integral operator generated by a Gaussian kernel. Finally, we sketch complex versions of our results to cover the cases when the sphere sits in a Hermitian space.

Radiación gamma natural en Gran Canaria

[ES]A raíz del accidente de Chernobyl en 1986 aumentó la preocupación por la vigilancia radIológica y se alentó el propósito de elaborar mapas de radiación gamma natural para poder evaluar los niveles de ral/iación y detectar así sus posibles incrementos. En España se ha piocedido a elaborar mapas de radiación gamma . . . natural. El presente trabajo contribuye a. completar dichos mapas, proporcionando datos s.obre la radiación natural en la isla deGran Canaria. Es Iruto de un convenio entre la Universidad de Las Palmas de . Gran Canaria, él Cabildo Insular de Gran Canaria Ji la Fundación Universitaria de Las Palmas. Se llevó a cabo en una campaña de medidas que se realizó desde el4 de mayo al10 de octubre de 1996, y aquí se presentan sus resultados

Kernel Methods for Tree Structured Data

Machine learning comprises a series of techniques for automatic extraction of meaningful information from large collections of noisy data. In many real world applications, data is naturally represented in structured form. Since traditional methods in machine learning deal with vectorial information, they require an a priori form of preprocessing. Among all the learning techniques for dealing with structured data, kernel methods are recognized to have a strong theoretical background and to be effective approaches. They do not require an explicit vectorial representation of the data in terms of features, but rely on a measure of similarity between any pair of objects of a domain, the kernel function. Designing fast and good kernel functions is a challenging problem. In the case of tree structured data two issues become relevant: kernel for trees should not be sparse and should be fast to compute. The sparsity problem arises when, given a dataset and a kernel function, most structures of the dataset are completely dissimilar to one another. In those cases the classifier has too few information for making correct predictions on unseen data. In fact, it tends to produce a discriminating function behaving as the nearest neighbour rule. Sparsity is likely to arise for some standard tree kernel functions, such as the subtree and subset tree kernel, when they are applied to datasets with node labels belonging to a large domain. A second drawback of using tree kernels is the time complexity required both in learning and classification phases. Such a complexity can sometimes prevents the kernel application in scenarios involving large amount of data. This thesis proposes three contributions for resolving the above issues of kernel for trees. A first contribution aims at creating kernel functions which adapt to the statistical properties of the dataset, thus reducing its sparsity with respect to traditional tree kernel functions. Specifically, we propose to encode the input trees by an algorithm able to project the data onto a lower dimensional space with the property that similar structures are mapped similarly. By building kernel functions on the lower dimensional representation, we are able to perform inexact matchings between different inputs in the original space. A second contribution is the proposal of a novel kernel function based on the convolution kernel framework. Convolution kernel measures the similarity of two objects in terms of the similarities of their subparts. Most convolution kernels are based on counting the number of shared substructures, partially discarding information about their position in the original structure. The kernel function we propose is, instead, especially focused on this aspect. A third contribution is devoted at reducing the computational burden related to the calculation of a kernel function between a tree and a forest of trees, which is a typical operation in the classification phase and, for some algorithms, also in the learning phase. We propose a general methodology applicable to convolution kernels. Moreover, we show an instantiation of our technique when kernels such as the subtree and subset tree kernels are employed. In those cases, Direct Acyclic Graphs can be used to compactly represent shared substructures in different trees, thus reducing the computational burden and storage requirements.

MoNET the Mobile Network Emulation Tool Modulo kernel per l’emulazione del canale wireless

MoNET e' un emulatore per reti wireless mobili, composto da una suite di software distribuiti. MoNET fornisce a ricercatori e sviluppatori un ambiente virtualizzato controllato per lo sviluppo e il test di applicazioni mobili e protocolli di rete per qualsiasi tipologia di hardware e piattaforma software che possa essere virtualizzata. La natura distribuita di questo emulatore permette di creare scenari di dimensione arbitraria. La rete wireless viene emulata in maniera trasparente, quindi la connettività percepita da ogni nodo virtuale, presenta le stesse caratteristiche di quella fisica emulata.

Transkriptionelle Regulation des humanen Interferon-gamma-Promotors in T-Lymphocyten

Interferon-gamma is mainly produced by activated T helper cells and cytotoxic T lymphocytes and sustains the immune-defense against viral and bacterial infections. For a better understanding of IFN-gamma promoter regulation in T cells, different DNA-binding motivs were examined. Hereby, a new motiv (-196 to -183) was identified, that binds to the transcription factor AP-1 in T helper cells and Jurkat T cells. This factor acts as an essential activator protein. Further investigation demonstrated that IL-12 and IL-18 induce different regulatory pathways. Both AP-1 and STAT-4 bindings at their cognate DNA elements (-196 to -183 and -224 to -215) are required for the IL-12 dependent activation whereas IL-18 causes direct activation via AP-1.Moreover, the TH2 cytokine IL-4 represses significantly the IFN-gamma promoter activity in CD4+ T cells. IL-4 induces GATA-3, that interacts with two DNA-motivs (-111 to -87) at the IFN-gamma promoter.Furthermore, transgenic mice were generated, yielding a human IFN-gamma promoter construct (410 bp) under the control of a luciferase reporter gene. The data demonstrated a specific IFN-gamma promoter activation by antiCD3 plus antiCD28 in CD4+ and CD8+ T cells. The luciferase activty in CD4+ T cells was reinforced by addition of IL-12 and IL-18 and repressed by IL-4.

Erste Untersuchungen zur Messung helizitätsabhängiger (gamma N)-Wirkungsquerschnitte für das GDH-Experiment am MAMI

Das experimentelle Studium der 1966 von Gerasimov, Drell undHearn unabhängig voneinander aufgestellten und als GDH-SummenregelbezeichnetenRelation macht die Vermessung totalerPhotoabsorptionswirkungsquerschnitte von zirkular polarisierten Photonen an longitudinalpolarisierten Nukleonen über einen weiten Energiebereich notwendig. Die im Sommer1998 erfolgte Messung am Mainzer Mikrotron stellt das erste derartigeExperiment mit reellen Photonen zur Messung des GDH-Integrals am Protondar. Die Verwendung eines Frozen-Spin-Butanoltargets, das eingesetzt wurde, umeinen möglichst hohen Proton-Polarisationsgrad zu erreichen, hat diezusätzliche experimentelle Schwierigkeit zur Folge, daß die imButanoltarget enthaltenen Kohlenstoffkerne ebenfalls Reaktionsprodukte liefern, diezusammen mit den am Proton erzeugten nachgewiesen werden.Ziel der Arbeit war die Bestimmung von Wirkungsquerschnittenam freien Proton aus Messungen an einem komplexen Target (CH2) wie esbeim polarisiertenTarget vorliegt. Die hierzu durchgeführten Pilotexperimentedienten neben der Entwicklung von Methoden zur Reaktionsidentifikation auchder Eichung des Detektorsystems. Durch die Reproduktion der schon bekanntenund vermessenen unpolarisierten differentiellen und totalenEin-Pion-Wirkungsquerschnitte am Proton (gamma p -> p pi0 und gamma p -> n pi+), die bis zueiner Photonenergievon etwa 400 MeV den Hauptbeitrag zum GDH-Integralausmachen, konnte gezeigt werden, daß eine Separation der Wasserstoff- vonKohlenstoffereignissen möglich ist. Die notwendigen Techniken hierzu wurden imRahmen dieser Arbeit zu einem allgemein nutzbaren Werkzeug entwickelt.Weiterhin konnte gezeigt werden, daß der vom Kohlenstoffstammende Anteil der Reaktionen keine Helizitätsabhängigkeit besitzt. Unterdieser Voraussetzung reduziert sich die Bestimmung der helizitätsabhängigenWirkungsquerschnittsdifferenz auf eine einfacheDifferenzbildung. Aus den erhaltenen Ergebnissen der intensiven Analyse von Daten, diemit einem unpolarisierten Target erhalten wurden, konnten so schnellerste Resultate für Messungen, die mit dem polarisierten Frozen-Spin-Targetaufgenommen wurden, geliefert werden. Es zeigt sich, daß sich dieseersten Resultate für polarisierte differentielle und totale (gammaN)-Wirkungsquerschnitte im Delta-Bereich in guter Übereinstimmung mit theoretischenAnalysen befinden.