The effects of 17beta-estradiol and ethanol on zinc- or manganese-induced toxicity in SK-N-SH cells

Serious neurodegenerative disorders are increasingly prevalent in our society and excessive oxidative stress may be a key mediator of neuronal cell death in many of these conditions. A variety of metals, such as manganese and zinc, are essential trace elements but can reach localized toxic concentrations through various disease processes or environmental exposures and have been implicated as having a role in neurodegeneration. Both manganese and zinc exist as bivalent cations and are essential cofactors/activators for numerous enzymes. Evidence suggests one action of these metals, when concentrated beyond physiological levels, may be to inhibit cellular energy production, ultimately leading to increased radical formation. Our studies were undertaken to directly investigate the toxic effects of manganese and zinc in an immortalized neuronal-like cell line (SK-N-SH) by testing interactions with the antioxidant, 17beta-estradiol, and the neurotoxin, ethanol. Employing undifferentiated SK-N-SH cells, we found that these metals caused biphasic effects, enhancing cell proliferation at low doses and inducing cell death at higher doses. Zinc was both more efficacious and more potent than manganese in enhancing growth and in causing cell death. 17beta-Estradiol and ethanol enhanced the proliferative actions of zinc and manganese across a wide concentration range. Furthermore, co-treatment with either 17beta-estradiol or ethanol afforded protection against manganese-, but not zinc-induced toxicity. Finally, combined administration of 17beta-estradiol and ethanol to SK-N-SH cells resulted in both a loss of growth enhancement and protective properties that were observed when these substances were administered individually. We also noted that the toxic effects occurred more rapidly from zinc than manganese exposure. Taken together, these data suggest that oxidative stress likely has a role in cell death resulting from toxic exposure to either zinc or manganese, but there is a difference in the precise mechanism of their effects.     

<Emphasis Type="Italic">Scoredist</Emphasis>: A simple and robust protein sequence distance estimator

Background  

Distance-based methods are popular for reconstructing evolutionary trees thanks to their speed and generality. A number of methods exist for estimating distances from sequence alignments, which often involves some sort of correction for multiple substitutions. The problem is to accurately estimate the number of true substitutions given an observed alignment. So far, the most accurate protein distance estimators have looked for the optimal matrix in a series of transition probability matrices, e.g. the Dayhoff series. The evolutionary distance between two aligned sequences is here estimated as the evolutionary distance of the optimal matrix. The optimal matrix can be found either by an iterative search for the Maximum Likelihood matrix, or by integration to find the Expected Distance. As a consequence, these methods are more complex to implement and computationally heavier than correction-based methods. Another problem is that the result may vary substantially depending on the evolutionary model used for the matrices. An ideal distance estimator should produce consistent and accurate distances independent of the evolutionary model used.     

Improved profile HMM performance by assessment of critical algorithmic features in SAM and HMMER

Background  

Profile hidden Markov model (HMM) techniques are among the most powerful methods for protein homology detection. Yet, the critical features for successful modelling are not fully known. In the present work we approached this by using two of the most popular HMM packages: SAM and HMMER. The programs' abilities to build models and score sequences were compared on a SCOP/Pfam based test set. The comparison was done separately for local and global HMM scoring.     

Similarities and differences in the transcriptional regulation of the leptin gene promoter in gastric and adipose cells

The stomach was reported to synthesize and secrete leptin mainly in the gastric lumen. Gastric leptin release is markedly increased after food intake, by vagal cholinergic stimulation and by cholecystokinin and secretin. Here we show that human gastric MKN-74 cells produce leptin that increases upon challenge with cholecystokinin, insulin, glucocorticoids and all-trans retinoic acid through activation of the leptin gene promoter. In addition, we demonstrate that forskolin and BRL37344 which increased cAMP levels, fail to affect the activity of leptin gene promoter in MKN74 expressing beta(3)-adrenoceptor cells but, induce a 2-fold decrease in this activity in adipose 3T3-L1 cells. These data described for the first time, similarities and more interestingly, differences in the regulation of the leptin gene promoter in gastric cells as compared to adipocytes.