The role of mitochondrial DNA damage in the citotoxicity of reactive oxygen species

Mitochondria contain their own genome, a small circular molecule of around 16.5 kbases. The mitochondrial DNA (mtDNA) encodes for only 13 polypeptides, but its integrity is essential for mitochondrial function, as all 13 proteins are regulatory subunits of the oxidative phosphorylation complexes. Nonetheless, the mtDNA is physically associated with the inner mitochondrial membrane, where the majority of the cellular reactive oxygen species are generated. In fact, the mitochondrial DNA accumulates high levels of oxidized lesions, which have been associated with several pathological and degenerative processes. The cellular responses to nuclear DNA damage have been extensively studied, but so far little is known about the functional outcome and cellular responses to mtDNA damage. In this review we will discuss the mechanisms that lead to damage accumulation and the in vitro models we are establishing to dissect the cellular responses to oxidative damage in the mtDNA and to sort out the differential cellular consequences of accumulation of damage in each cellular genome, the nuclear and the mitochondrial genome.

PVP superabsorbent nanogels

Monomer free hydrogel nanoparticles (nanogels) were prepared by crosslinking preformed poly(N-vinyl-2-pyrrolidone) (PVP) entrapped in the aqueous pool of hexadecyltrimethylammonium bromide reverse micelles using the Fenton reaction. The PVP nanoparticles were spherical with a dry diameter of 27 nm. The diameter of the swollen particles was ten times higher, i.e., a swelling ratio, Q, above 900, characterizing this preparation as superabsorbent. PVP nanogel swelling was dependent on bound Fe(3+) and varied with pH and ionic strength. Nanogel deswelling by salt followed the anions lyotropic series, i.e., SCN(-) < HSO(3)(-) < NO(3)(-) < I(-) < Cl(-) < CH(3)COO(-) < CF(3)SO(3)(-). The value of Q reached 6,000 in iron-free PVP nanoparticles at low pH, making this nanogel one of the most efficient swelling systems so far described.

Copper hexacyanoferrate nanoparticles modified electrodes: A versatile tool for biosensors

Copper hexacyanoferrate nanoparticles of about 30 nm in size have been prepared by the sonochemical irradiation of a mixture of aqueous potassium ferricyanide and copper chloride solutions. The nanoparticles were immobilized onto fluorine doped tin oxide (FTO) electrodes by using the electrostatic deposition layer-by-layer technique (LbL), obtaining electroactive films with electrocatalytic properties towards H2O2 reduction, providing higher currents than those observed for electrodeposited bulk material, even in electrolytes containing NH4+, Na+ and K+. The nanoparticles assembly was used as mediator in a glucose biosensor by immobilizing glucose oxidase enzyme by both, cross-linking and LbL. techniques. Sensitivities obtained were dependent on the immobilization method ranging from 1.23 mu A mmol(-1) L cm(-2) for crosslinking to 0.47 mu A mmol(-1) L cm(-2) for LbL; these values being of the same order than those obtained with electrodes where the amount of enzyme used is much higher. Moreover, the linear concentration range where the biosensors can operate was 10 times higher for electrodes prepared with the LbL immobilization method than with the conventional crosslinking one. (C) 2008 Elsevier B.V. All rights reserved.

Studies on the resonance Raman spectra of polyaniline obtained with near-IR excitation

The effects of near-IR (NIR) laser power over the Raman spectra of poly(aniline) emeraldine salt (PANIES) and base (PANI-EB) were investigated. The reasons for the existence of several bands from 1324 to 1500 cm-1 in the Raman spectra of poly(aniline) obtained at NIR region were also studied. The bands from 1324 to 1375 cm-` were associated to vC-N of polarons with different conjugation lengths and the bands from 1450 to 1500 cm-1 in Raman spectra of PANI emeraldine and pernigraniline base forms were correlated to vC=N modes associated with quinoid units having different conjugation lengths. The increase of laser power at 1064.0 run causes the deprotonation of PANI-ES and the formation of cross-linking segments having phenazine and/or oxazine rings. For PANI-EB only a small spectral change is observed when the laser power is increased, owing to the low absorption of this form in the NIR region. Copyright (c) 2007 John Wiley & Sons, Ltd.

Spectroscopic characterization of the structural changes of polyaniline nanofibers after heating

The thermal behavior of PANI nanofibers doped with beta-naphthalenesulfonic acid (beta-NSA) was investigated and their morphological and structural changes after heating were monitored by SEM, XRD and Raman techniques, respectively. By using electron-scanning microscopy it is possible to verify that the nanofiber morphology is stable and no polymer degradation is observed in thermogravimetric (TG) data up to 200 degrees C. Nevertheless, the heating promotes the formation of cross-linking structures (phenazine and/or oxazine-like rings), that is clearly demonstrated by the presence of bands at ca. 578, 1398, and 1644 cm(-1) in resonance Raman spectra of heated PANI-NSA samples. The most important consequence of the formation of cross-linking structures in PANI-NSA samples is that these samples retain their nanofiber morphology upon HCl doping in contrast to PANI-NSA nanofibers without heating. (c) 2007 Elsevier Ltd. All rights reserved.

Cross-situational learning of object-word mapping using Neural Modeling Fields

The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have brought that issue to a central place in more applied research fields, such as computational linguistics and neural networks, as well. An attractive approach to learning an object-word mapping is the so-called cross-situational learning. This learning scenario is based on the intuitive notion that a learner can determine the meaning of a word by finding something in common across all observed uses of that word. Here we show how the deterministic Neural Modeling Fields (NMF) categorization mechanism can be used by the learner as an efficient algorithm to infer the correct object-word mapping. To achieve that we first reduce the original on-line learning problem to a batch learning problem where the inputs to the NMF mechanism are all possible object-word associations that Could be inferred from the cross-situational learning scenario. Since many of those associations are incorrect, they are considered as clutter or noise and discarded automatically by a clutter detector model included in our NMF implementation. With these two key ingredients - batch learning and clutter detection - the NMF mechanism was capable to infer perfectly the correct object-word mapping. (C) 2009 Elsevier Ltd. All rights reserved.

Three-dimensional quantitative structure-activity relationships for a large series of potent antitubercular agents

Comparative molecular field analysis (CoMFA) studies were conducted on a series of 100 isoniazid derivatives as anti-tuberculosis agents using two receptor-independent structural data set alignment strategies: (1) rigid-body fit, and (2) pharmacophore-based. Significant cross-validated correlation coefficients were obtained (CoMFA(1), q(2) = 0,75 and CoMFA(2), q(2) = 0.74), indicating the potential of the models for untested compounds. The models were then used to predict the inhibitory potency of 20 test set compounds that were not included in the training set, and the predicted values were in good agreement with the experimental results.

Cross-situational and supervised learning in the emergence of communication

Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two types of learning algorithms: cross-situational learning, in which the individuals determine the meaning of a word by looking for something in common across all observed uses of that word, and supervised operant conditioning learning, in which there is strong feedback between individuals about the intended meaning of the words. Despite the stark differences between these learning schemes, we show that they yield the same communication accuracy in the limits of large N and H, which coincides with the result of the classical occupancy problem of randomly assigning N objects to H words.