Differential Gene Expression in the Liver of the African Lungfish,Protopterus annectens,after 6 Months of Aestivation in Air or 1 Day of Arousal from 6 Months of Aestivation

The African lungfish, Protopterus annectens, can undergo aestivation during drought. Aestivation has three phases: induction, maintenance and arousal. The objective of this study was to examine the differential gene expression in the liver of P. annectens after 6 months (the maintenance phase) of aestivation as compared with the freshwater control, or after 1 day of arousal from 6 months aestivation as compared with 6 months of aestivation using suppression subtractive hybridization. During the maintenance phase of aestivation, the mRNA expression of argininosuccinate synthetase 1 and carbamoyl phosphate synthetase III were up-regulated, indicating an increase in the ornithine-urea cycle capacity to detoxify ammonia to urea. There was also an increase in the expression of betaine homocysteine-S-transferase 1 which could reduce and prevent the accumulation of hepatic homocysteine. On the other hand, the down-regulation of superoxide dismutase 1 expression could signify a decrease in ROS production during the maintenance phase of aestivation. In addition, the maintenance phase was marked by decreases in expressions of genes related to blood coagulation, complement fixation and iron and copper metabolism, which could be strategies used to prevent thrombosis and to conserve energy. Unlike the maintenance phase of aestivation, there were increases in expressions of genes related to nitrogen, carbohydrate and lipid metabolism and fatty acid transport after 1 day of arousal from 6 months aestivation. There were also up-regulation in expressions of genes that were involved in the electron transport system and ATP synthesis, indicating a greater demand for metabolic energy during arousal. Overall, our results signify the importance of sustaining a low rate of waste production and conservation of energy store during the maintenance phase, and the dependence on internal energy store for repair and structural modification during the arousal phase, of aestivation in the liver of P. annectens.     

NSC666715 and Its Analogs Inhibit Strand-Displacement Activity of DNA Polymerase β and Potentiate Temozolomide-Induced DNA Damage,Senescence and Apoptosis in Colorectal Cancer Cells

Recently approved chemotherapeutic agents to treat colorectal cancer (CRC) have made some impact; however, there is an urgent need for newer targeted agents and strategies to circumvent CRC growth and metastasis. CRC frequently exhibits natural resistance to chemotherapy and those who do respond initially later acquire drug resistance. A mechanism to potentially sensitize CRC cells is by blocking the DNA polymerase β (Pol-β) activity. Temozolomide (TMZ), an alkylating agent, and other DNA-interacting agents exert DNA damage primarily repaired by a Pol-β-directed base excision repair (BER) pathway. In previous studies, we used structure-based molecular docking of Pol-β and identified a potent small molecule inhibitor (NSC666715). In the present study, we have determined the mechanism by which NSC666715 and its analogs block Fen1-induced strand-displacement activity of Pol-β-directed LP-BER, cause apurinic/apyrimidinic (AP) site accumulation and induce S-phase cell cycle arrest. Induction of S-phase cell cycle arrest leads to senescence and apoptosis of CRC cells through the p53/p21 pathway. Our initial findings also show a 10-fold reduction of the IC₅₀ of TMZ when combined with NSC666715. These results provide a guide for the development of a target-defined strategy for CRC chemotherapy that will be based on the mechanisms of action of NSC666715 and TMZ. This combination strategy can be used as a framework to further reduce the TMZ dosages and resistance in CRC patients.     

An Emerging Approach for Parallel Quantification of Intracellular Protozoan Parasites and Host Cell Characterization Using TissueFAXS Cytometry

Characterization of host-pathogen interactions is a fundamental approach in microbiological and immunological oriented disciplines. It is commonly accepted that host cells start to change their phenotype after engulfing pathogens. Techniques such as real time PCR or ELISA were used to characterize the genes encoding proteins that are associated either with pathogen elimination or immune escape mechanisms. Most of such studies were performed in vitro using primary host cells or cell lines. Consequently, the data generated with such approaches reflect the global RNA expression or protein amount recovered from all cells in culture. This is justified when all host cells harbor an equal amount of pathogens under experimental conditions. However, the uptake of pathogens by phagocytic cells is not synchronized. Consequently, there are host cells incorporating different amounts of pathogens that might result in distinct pathogen-induced protein biosynthesis. Therefore, we established a technique able to detect and quantify the number of pathogens in the corresponding host cells using immunofluorescence-based high throughput analysis. Paired with multicolor staining of molecules of interest it is now possible to analyze the infection profile of host cell populations and the corresponding phenotype of the host cells as a result of parasite load.     

Atorvastatin and Fluoxetine Prevent Oxidative Stress and Mitochondrial Dysfunction Evoked by Glutamate Toxicity in Hippocampal Slices

Atorvastatin has been shown to exert a neuroprotective action by counteracting glutamatergic toxicity. Recently, we have shown atorvastatin also exerts an antidepressant-like effect that depends on both glutamatergic and serotonergic systems modulation. Excitotoxicity is involved in several brain disorders including depression; thus, it is suggested that antidepressants may target glutamatergic system as a final common pathway. In this study, a comparison of the mechanisms involved in the putative neuroprotective effect of a repetitive atorvastatin or fluoxetine treatment against glutamate toxicity in hippocampal slices was performed. Adult Swiss mice were treated with atorvastatin (10 mg/kg, p.o.) or fluoxetine (10 mg/kg, p.o.), once a day during seven consecutive days. On the eighth day, animals were killed and hippocampal slices were obtained and subjected to an in vitro protocol of glutamate toxicity. An acute treatment of atorvastatin or fluoxetine was not neuroprotective; however, the repeated atorvastatin or fluoxetine treatment prevented the decrease in cellular viability induced by glutamate in hippocampal slices. The loss of cellular viability induced by glutamate was accompanied by increased D-aspartate release, increased reactive oxygen species (ROS) and nitric oxide (NO) production, and impaired mitochondrial membrane potential. Atorvastatin or fluoxetine repeated treatment also presented an antidepressant-like effect in the tail suspension test. Atorvastatin or fluoxetine treatment was effective in protecting mice hippocampal slices from glutamate toxicity by preventing the oxidative stress and mitochondrial dysfunction.     

Spind: a package for computing spatially corrected accuracy measures

Using an appropriate accuracy measure is essential for assessing prediction accuracy in species distribution modelling. Therefore, model evaluation as an analytical uncertainty is a challenging problem. Although a variety of accuracy measures for the assessment of prediction errors in presence/absence models is available, there is a lack of spatial accuracy measures, i.e. measures that are sensitive to the spatial arrangement of the predictions. We present ‘spind’, a new software package (based on the R software program) that provides spatial performance measures for grid‐based models. These accuracy measures are generalized, spatially corrected versions of the classical ones, thus enabling comparisons between them. Our method for evaluation consists of the following steps: 1) incorporate additional autocorrelation until spatial autocorrelation in predictions and actuals is balanced, 2) cross‐classify predictions and adjusted actuals in a 4 × 4 contingency table, 3) use a refined weighting pattern for errors, and 4) calculate weighted Kappa, sensitivity, specificity and subsequently ROC, AUC, TSS to get spatially corrected indices. To illustrate the impact of our spatial method we present an example of simulated data as well as an example of presence/absence data of the plant species Dianthus carthusianorum across Germany. Our analysis includes a statistic for the comparison of spatial and classical (non‐spatial) indices. We find that our spatial indices tend to result in higher values than classical ones. These differences are statistically significant at medium and high autocorrelation levels. We conclude that these spatial accuracy measures may contribute to evaluate prediction errors in presence/absence models, especially in case of medium or high degree of similarity of adjacent data, i.e. aggregated (clumped) or continuous species distributions.