Myoglobin-H(2)O(2) catalyzes the oxidation of beta-ketoacids to alpha-dicarbonyls: Mechanism and implications in ketosis

Acetoacetate (AA) and 2-methylacetoacetate (MAA) are accumulated in metabolic disorders such as diabetes and isoleucinemia. Here we examine the mechanism of AA and MAA aerobic oxidation initiated by myoglobin (Mb)/H(2)O(2). We propose a chemiluminescent route involving a dioxetanone intermediate whose thermolysis yields triplet alpha-dicarbonyl species (methylglyoxal and diacetyl). The observed ultraweak chemiluminescence increased linearly on raising the concentration of either Mb (10-500 mu M) or AA (10-100 mM). Oxygen uptake studies revealed that MAA is almost a 100-fold more reactive than AA. EPR spin-trapping studies with MNP/MAA revealed the intermediacy of an alpha-carbon-centered radical and acetyl radical. The latter radical, probably derived from triplet diacetyl, is totally suppressed by sorbate, a well-known quencher of triplet carbonyls. Furthermore, an EPR signal assignable to MNP-AA(center dot) adduct was observed and confirmed by isotope effects. Oxygen consumption and a-dicarbonyl yield were shown to be dependent on AA or MAA concentrations (1-50 mM) and on H(2)O(2) or tert-butOOH added to the Mb-containing reaction mixtures. That ferrylMb is involved in a peroxidase cycle acting on the substrates is suggested by the reaction pH profiles and immunospin-trapping experiments. The generation of radicals and triplet dicarbonyl products by Mb/H(2)O(2)/beta-ketoacids may contribute to the adverse health effects of ketogenic unbalance. (C) 2011 Elsevier Inc. All rights reserved.

Expression of human papillomavirus type 16 E7 oncoprotein alters keratinocytes expression profile in response to tumor necrosis factor-alpha

Acute expression of E7 oncogene from human papillomavirus (HPV) 16 or HPV18 is sufficient to overcome tumor necrosis factor (TNF)-alpha cytostatic effect on primary human keratinocytes. In the present study, we investigated the molecular basis of E7-induced TNF resistance through a comparative analysis of the effect of this cytokine on the proliferation and global gene expression of normal and E7-expressing keratinocytes. Using E7 functional mutants, we show that E7-induced TNF resistance correlates with its ability to mediate pRb degradation and cell transformation. On the other hand, this effect does not depend on E7 sequences required to override DNA damage-induced cell cycle arrest or extend keratinocyte life span. Furthermore, we identified a group of 66 genes whose expression pattern differs between normal and E7-expressing cells upon cytokine treatment. These genes are mainly involved in cell cycle regulation suggesting that their altered expression may contribute to sustained cell proliferation even in the presence of a cytostatic stimulus. Differential expression of TCN1 (transcobalamin I), IFI44 (Interferon-induced protein 44), HMGB2 (high-mobility group box 2) and FUS [Fusion (involved in t(12; 16) in malignant liposarcoma)] among other genes were further confirmed by western-blot and/or real-time polymerase chain reaction. Moreover, FUS upregulation was detected in HPV-positive cervical high-grade squamous intraepithelial lesions when compared with normal cervical tissue. Further evaluation of the role of such genes in TNF resistance and HPVassociated disease development is warranted.

Unsupervised learning to cluster the disease stages in parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder (after Alzheimer's disease) and directly affects upto 5 million people worldwide. The stages (Hoehn and Yaar) of disease has been predicted by many methods which will be helpful for the doctors to give the dosage according to it. So these methods were brought up based on the data set which includes about seventy patients at nine clinics in Sweden. The purpose of the work is to analyze unsupervised technique with supervised neural network techniques in order to make sure the collected data sets are reliable to make decisions. The data which is available was preprocessed before calculating the features of it. One of the complex and efficient feature called wavelets has been calculated to present the data set to the network. The dimension of the final feature set has been reduced using principle component analysis. For unsupervised learning k-means gives the closer result around 76% while comparing with supervised techniques. Back propagation and J4 has been used as supervised model to classify the stages of Parkinson's disease where back propagation gives the variance percentage of 76-82%. The results of both these models have been analyzed. This proves that the data which are collected are reliable to predict the disease stages in Parkinson's disease.

Classification of Parkinson’s Disease using MultiPass Lvq,Logistic Model Tree,K-Star for Audio Data set : Classification of Parkinson Disease using Audio Dataset

Parkinson's disease (PD) is a degenerative illness whose cardinal symptoms include rigidity, tremor, and slowness of movement. In addition to its widely recognized effects PD can have a profound effect on speech and voice.The speech symptoms most commonly demonstrated by patients with PD are reduced vocal loudness, monopitch, disruptions of voice quality, and abnormally fast rate of speech. This cluster of speech symptoms is often termed Hypokinetic Dysarthria.The disease can be difficult to diagnose accurately, especially in its early stages, due to this reason, automatic techniques based on Artificial Intelligence should increase the diagnosing accuracy and to help the doctors make better decisions. The aim of the thesis work is to predict the PD based on the audio files collected from various patients.Audio files are preprocessed in order to attain the features.The preprocessed data contains 23 attributes and 195 instances. On an average there are six voice recordings per person, By using data compression technique such as Discrete Cosine Transform (DCT) number of instances can be minimized, after data compression, attribute selection is done using several WEKA build in methods such as ChiSquared, GainRatio, Infogain after identifying the important attributes, we evaluate attributes one by one by using stepwise regression.Based on the selected attributes we process in WEKA by using cost sensitive classifier with various algorithms like MultiPass LVQ, Logistic Model Tree(LMT), K-Star.The classified results shows on an average 80%.By using this features 95% approximate classification of PD is acheived.This shows that using the audio dataset, PD could be predicted with a higher level of accuracy.

Kinetics and Adsorption Isotherms of Bisphenol A, Estrone, 17 beta-Estradiol, and 17 alpha-Ethinylestradiol in Tropical Sediment Samples

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Analysis of the Priestley-Taylor alpha parameter for a bean crop

This work deals with the Priestley-Taylor model for evapotranspiration in different grown stages of a bean crop. Priestley and Taylor derived a practical Formulation for energy partitioning between the sensible and latent heat fluxes through the a parameter. Bowen ratio energy balance (BREB) was carried out for daily sensible and latent heat flux estimations in three different crop stages. Mean daily values of Priestley-Taylor a parameter were determined for eleven days during the crop cycle. Diurnal variation patterns of a are presented for the growing, flowering and graining periods. The mean values of 1.13 +/- 0.33, 1.26 +/- 0.74, 1.22 +/- 0.55 were obtained for a day in the growing, in the flowering and for graining periods, respectively. Eleven days values of a are shown and gave a mean value of 1.23 +/- 0.10 which agree on the reported literature.

Effect of cationic micelles on the decomposition of alpha-aminophenyl cephalosporins

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Kinetics of interface state-limited hole injection in alpha-naphthylphenylbiphenyl diamine (alpha-NPD) thin layers

Injection-limited operation is identified in thin-film, alpha-NPD-based diodes. A detailed model for the impedance of the injection process is provided which considers the kinetics of filling/releasing of interface states as the key factor behind the injection mechanism. The injection model is able to simultaneously account for the steady-state, current-voltage (J-V) characteristics and impedance response. and is based on the sequential injection of holes mediated by energetically distributed surface states at the metal-organic interface. The model takes into account the vacuum level offset caused by the interface dipole, along with the partial shift of the interface level distribution with bias voltage. This approach connects the low-frequency (similar to 1 Hz) capacitance spectra, which exhibits a transition between positive to negative values, to the change in the occupancy of interface states with voltage. Simulations based on the model allow to derive the density of interface states effectively intervening in the carrier injection (similar to 5 x 10(12) cm(-2)), which exhibit a Gaussian-like distribution. A kinetically determined hole barrier is calculated at levels located similar to 0.4 eV below the contact work function. (C) 2008 Elsevier B.V. All rights reserved.

Evaluation of Carcinogenic Potential of Diuron in a Rat Mammary Two-Stage Carcinogenesis Model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Chronic ethanol intake promotes double gluthatione S-transferase transforming growth factor-alpha-positive hepatocellular lesions in male Wistar rats

The chronic ethanol intake influence on the gluthatione S-transferase (GST-P) and transforming growth factor alpha (TGF-alpha) expression in remodeling/persistent preneoplastic lesions (PNLs) was evaluated in the resistant hepatocyte model. Male Wistar rats were allocated into five groups: G1, non-treated, fed water and chow ad libitum; G2, non-treated and pair-fed chow (restricted to match that of G3 group) and a maltodextrin (MD) solution in tap water (matched ethanol-derived calories); G3, fed 5% ethanol in drinking water and chow ad libitum; G4, diethylnitrosamine (DEN, 200 mg/kg, body weight) plus 200 parts per million of 2-acetylaminofluorene (2-AAF) for 3 weeks and pair-fed chow (restricted to match that of G5 group) and an MD solution in tap water (matched ethanol-derived calories); G5, DEN/2-AAF treatment, fed ethanol 5% and chow ad libitum. All animals were subjected to 70% partial hepatectomy at week 3 and sacrificed at weeks 12 or 22, respectively. Liver samples were collected for histological analysis or immunohistochemical expression of GST-P, TGF-alpha and proliferating cell nuclear antigen or zymography for matrix metalloproteinases-2 and -9. At the end of ethanol treatment, there was a significant increase in the percentage of liver area occupied by persistent GST-P-positive PNLs, the number of TGF-alpha-positive PNLs and the development of liver tumors in ethanol-fed and DEN/2-AAF-treated groups (G5 versus G4, P < 0.001). In addition, ethanol feeding led to a significant increase in cell proliferation mainly in remodeling and persistent PNLs with immunoreactivity for TGF-alpha at week 22 (P < 0.001). Gelatinase activities were not altered by ethanol treatment. The results demonstrated that ethanol enhances the selective growth of PNL with double expression of TGF-alpha and GST-P markers.

Role of flanking sequences and phosphorylation in the recognition of the simian-virus-40 large T-antigen nuclear localization sequences by importin-alpha

The nuclear import of simian-virus-40 large T-antigen (tumour antigen) is enhanced via phosphorylation by the protein kinase CK2 at Ser(112) in the vicinity of the NLS (nuclear localization sequence). To determine the structural basis of the effect of the sequences flanking the basic cluster KKKRK, and the effect of phosphorylation on the recognition of the NLS by the nuclear import factor importin-alpha (Impalpha), we co-crystallized non-autoinhibited Impalpha with peptides corresponding to the phosphorylated and non-phosphorylated forms of the NLS, and determined the crystal structures of the complexes. The structures show that the amino acids N-terminally flanking the basic cluster make specific contacts with the receptor that are distinct from the interactions between bipartite NLSs and Impalpha. We confirm the important role of flanking sequences using binding assays. Unexpectedly, the regions of the peptides containing the phosphorylation site do not make specific contacts with the receptor. Binding assays confirm that phosphorylation does not increase the affinity of the T-antigen NLS to Impalpha. We conclude that the sequences flanking the basic clusters in NLSs play a crucial role in nuclear import by modulating the recognition of the NLS by Impalpha, whereas phosphorylation of the T-antigen enhances nuclear import by a mechanism that does not involve a direct interaction of the phosphorylated residue with Impalpha.

Structural Basis of Importin-alpha-Mediated Nuclear Transport for Ku70 and Ku80

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

GH overexpression causes muscle hypertrophy independent from local IGF-I in a zebrafish transgenic model

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Monitoring the positioning of short polycationic peptides in model lipid bilayers by combining hydrogen/deuterium exchange and electrospray ionization mass spectrometry

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Role of PKC and CaV1.2 in Detrusor Overactivity in a Model of Obesity Associated with Insulin Resistance in Mice

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)