p53-induced protein with a death domain (PIDD) isoforms differentially activate nuclear factor-kappaB and caspase-2 in response to genotoxic stress

Cells respond to DNA damage in a complex way and the fate of damaged cells depends on the balance between pro- and antiapoptotic signals. This is of crucial importance in cancer as genotoxic stress is implied both in oncogenesis and in classical tumor therapies. p53-induced protein with a death domain (PIDD), initially described as a p53-inducible gene, is one of the molecular switches able to activate a survival or apoptotic program. Two isoforms of PIDD, PIDD (isoform 1) and LRDD (isoform 2), have already been reported and we describe here a third isoform. These three isoforms are differentially expressed in tissues and cell lines. Genotoxic stress only affects PIDD isoform 3 mRNA levels, whereas isoforms 1 and 2 mRNA levels remain unchanged. All isoforms are capable of activating nuclear factor-kappaB in response to genotoxic stress, but only isoform 1 interacts with RIP-associated ICH-1/CED-3 homologous protein with a death domain and activates caspase-2. Isoform 2 counteracts the pro-apoptotic function of isoform 1, whereas isoform 3 enhances it. Thus, the differential splicing of PIDD mRNA leads to the formation of at least three proteins with antagonizing/agonizing functions, thereby regulating cell fate in response to DNA damage

Hometown architecture : changes in Central Iowa towns and farms,1981.

This book is a product of a two year project, the extensive surveys CIRALG and the Division of Historic Preservation undertook to identify culturally significant structures in central Iowa. It discloses the aspirations, tastes, building abilities and needs of earlier Iowans.

The CbrA-CbrB two-component regulatory system controls the utilization of multiple carbon and nitrogen sources in Pseudomonas aeruginosa.

A novel two-component system, CbrA-CbrB, was discovered in Pseudomonas aeruginosa; cbrA and cbrB mutants of strain PAO were found to be unable to use several amino acids (such as arginine, histidine and proline), polyamines and agmatine as sole carbon and nitrogen sources. These mutants were also unable to use, or used poorly, many other carbon sources, including mannitol, glucose, pyruvate and citrate. A 7 kb EcoRI fragment carrying the cbrA and cbrB genes was cloned and sequenced. The cbrA and cbrB genes encode a sensor/histidine kinase (Mr 108 379, 983 residues) and a cognate response regulator (Mr 52 254, 478 residues) respectively. The amino-terminal half (490 residues) of CbrA appears to be a sensor membrane domain, as predicted by 12 possible transmembrane helices, whereas the carboxy-terminal part shares homology with the histidine kinases of the NtrB family. The CbrB response regulator shows similarity to the NtrC family members. Complementation and primer extension experiments indicated that cbrA and cbrB are transcribed from separate promoters. In cbrA or cbrB mutants, as well as in the allelic argR9901 and argR9902 mutants, the aot-argR operon was not induced by arginine, indicating an essential role for this two-component system in the expression of the ArgR-dependent catabolic pathways, including the aruCFGDB operon specifying the major aerobic arginine catabolic pathway. The histidine catabolic enzyme histidase was not expressed in cbrAB mutants, even in the presence of histidine. In contrast, proline dehydrogenase, responsible for proline utilization (Pru), was expressed in a cbrB mutant at a level comparable with that of the wild-type strain. When succinate or other C4-dicarboxylates were added to proline medium at 1 mM, the cbrB mutant was restored to a Pru+ phenotype. Such a succinate-dependent Pru+ property was almost abolished by 20 mM ammonia. In conclusion, the CbrA-CbrB system controls the expression of several catabolic pathways and, perhaps together with the NtrB-NtrC system, appears to ensure the intracellular carbon: nitrogen balance in P. aeruginosa.

Regulatory roles of the GacS/GacA two-component system in plant-associated and other gram-negative bacteria.

The sensor kinase GacS and the response regulator GacA are members of a two-component system that is present in a wide variety of gram-negative bacteria and has been studied mainly in enteric bacteria and fluorescent pseudomonads. The GacS/GacA system controls the production of secondary metabolites and extracellular enzymes involved in pathogenicity to plants and animals, biocontrol of soilborne plant diseases, ecological fitness, or tolerance to stress. A current model proposes that GacS senses a still-unknown signal and activates, via a phosphorelay mechanism, the GacA transcription regulator, which in turn triggers the expression of target genes. The GacS protein belongs to the unorthodox sensor kinases, characterized by an autophosphorylation, a receiver, and an output domain. The periplasmic loop domain of GacS is poorly conserved in diverse bacteria. Thus, a common signal interacting with this domain would be unexpected. Based on a comparison with the transcriptional regulator NarL, a secondary structure can be predicted for the GacA sensor kinases. Certain genes whose expression is regulated by the GacS/GacA system are regulated in parallel by the small RNA binding protein RsmA (CsrA) at a posttranscriptional level. It is suggested that the GacS/GacA system operates a switch between primary and secondary metabolism, with a major involvement of posttranscriptional control mechanisms.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

c-Jun N-terminal kinase binding domain-dependent phosphorylation of mitogen-activated protein kinase kinase 4 and mitogen-activated protein kinase kinase 7 and balancing cross-talk between c-Jun N-terminal kinase and extracellular signal-regulated kinase pathways in cortical neurons

The c-Jun N-terminal kinase (JNK) is a mitogen-activated protein kinase (MAPK) activated by stress-signals and involved in many different diseases. Previous results proved the powerful effect of the cell permeable peptide inhibitor d-JNKI1 (d-retro-inverso form of c-Jun N-terminal kinase-inhibitor) against neuronal death in CNS diseases, but the precise features of this neuroprotection remain unclear. We here performed cell-free and in vitro experiments for a deeper characterization of d-JNKI1 features in physiological conditions. This peptide works by preventing JNK interaction with its c-Jun N-terminal kinase-binding domain (JBD) dependent targets. We here focused on the two JNK upstream MAPKKs, mitogen-activated protein kinase kinase 4 (MKK4) and mitogen-activated protein kinase kinase 7 (MKK7), because they contain a JBD homology domain. We proved that d-JNKI1 prevents MKK4 and MKK7 activity in cell-free and in vitro experiments: these MAPKK could be considered not only activators but also substrates of JNK. This means that d-JNKI1 can interrupt downstream but also upstream events along the JNK cascade, highlighting a new remarkable feature of this peptide. We also showed the lack of any direct effect of the peptide on p38, MEK1, and extracellular signal-regulated kinase (ERK) in cell free, while in rat primary cortical neurons JNK inhibition activates the MEK1-ERK-Ets1/c-Fos cascade. JNK inhibition induces a compensatory effect and leads to ERK activation via MEK1, resulting in an activation of the survival pathway-(MEK1/ERK) as a consequence of the death pathway-(JNK) inhibition. This study should hold as an important step to clarify the strong neuroprotective effect of d-JNKI1.

Option valuation as an expectation in the complex domain: The Black-Scholes case

It is very well known that the first succesful valuation of a stock option was done by solving a deterministic partial differential equation (PDE) of the parabolic type with some complementary conditions specific for the option. In this approach, the randomness in the option value process is eliminated through a no-arbitrage argument. An alternative approach is to construct a replicating portfolio for the option. From this viewpoint the payoff function for the option is a random process which, under a new probabilistic measure, turns out to be of a special type, a martingale. Accordingly, the value of the replicating portfolio (equivalently, of the option) is calculated as an expectation, with respect to this new measure, of the discounted value of the payoff function. Since the expectation is, by definition, an integral, its calculation can be made simpler by resorting to powerful methods already available in the theory of analytic functions. In this paper we use precisely two of those techniques to find the well-known value of a European call

Vacancy-driven ordering in a two-dimensional binary alloy

Domain growth in a system with nonconserved order parameter is studied. We simulate the usual Ising model for binary alloys with concentration 0.5 on a two-dimensional square lattice by Monte Carlo techniques. Measurements of the energy, jump-acceptance ratio, and order parameters are performed. Dynamics based on the diffusion of a single vacancy in the system gives a growth law faster than the usual Allen-Cahn law. Allowing vacancy jumps to next-nearest-neighbor sites is essential to prevent vacancy trapping in the ordered regions. By measuring local order parameters we show that the vacancy prefers to be in the disordered regions (domain boundaries). This naturally concentrates the atomic jumps in the domain boundaries, accelerating the growth compared with the usual exchange mechanism that causes jumps to be homogeneously distributed on the lattice.

Convergent genetic architecture underlies social organization in ants.

Complex adaptive polymorphisms are common in nature, but what mechanisms maintain the underlying favorable allelic combinations [1-4]? The convergent evolution of polymorphic social organization in two independent ant species provides a great opportunity to investigate how genomes evolved under parallel selection. Here, we demonstrate that a large, nonrecombining "social chromosome" is associated with social organization in the Alpine silver ant, Formica selysi. This social chromosome shares architectural characteristics with that of the fire ant Solenopsis invicta [2], but the two show no detectable similarity in gene content. The discovery of convergence at two levels-the phenotype and the genetic architecture associated with alternative social forms-points at general genetic mechanisms underlying transitions in social organization. More broadly, our findings are consistent with recent theoretical studies suggesting that suppression of recombination plays a key role in facilitating coordinated shifts in coadapted traits [5, 6].