Oxidative stress modulates osteoblastic differentiation of vascular and bone cells

Oxidative stress may regulate cellular function in multiple pathological conditions, including atherosclerosis. One feature of the atherosclerotic plaque is calcium mineral deposition, which appears to result from the differentiation of vascular osteoblastic cells, calcifying vascular cells (CVC). To determine the role of oxidative stress in regulating the activity of CVC, we treated these cells with hydrogen peroxide (H(2)O(2)) or xanthine/xanthine oxidase (XXO) and assessed their effects on intracellular oxidative stress, differentiation, and mineralization. These agents increased intracellular oxidative stress as determined by 2,7 dichlorofluorescein fluorescence, and enhanced osteoblastic differentiation of vascular cells, based on alkaline phosphatase activity and mineralization. In contrast, H(2)O(2) and XXO resulted in inhibition of differentiation markers in bone osteoblastic cells, MC3T3-E1, and marrow stromal cells, M2-10B4, while increasing oxidative stress. In addition, minimally oxidized low-density lipoprotein (MM-LDL), previously shown to enhance vascular cell and inhibit bone cell differentiation, also increased intracellular oxidative stress in the three cell types. These effects of XXO and MM-LDL were counteracted by the antioxidants Trolox and pyrrolidinedithiocarbamate. These results suggest that oxidative stress modulates differentiation of vascular and bone cells oppositely, which may explain the parallel buildup and loss of calcification, seen in vascular calcification and osteoporosis, respectively.     

<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.     

Zooplankton in the Ligurian Sea: Part II. Exploration of their physical and biological forcing functions during summer 2000

A survey of the biological and physical oceanography of theLigurian Sea was conducted in the late summer of 2000. Forty-onestations were sampled for nutrients, oxygen, fluorescence andhydrographic information. Acoustic backscatter measurementswere used to estimate abundance of small (<5 mm) zooplanktonbiovolume versus depth and the distribution of northern krill,Meganyctiphanes norvegica. Net-tow and underwater video datawere collected to identify the zooplankton present. These datawere used to analyze the Ligurian Sea ecosystem for physicaland biological linkages that control zooplankton abundance anddistribution. Results are compared with those from a similarstudy conducted in 1999. Hydrographic sampling showed a domeof dense water in the southwestern middle of the basin. Thehighest chlorophyll a (Chl a) concentrations were measured inthis area, while small zooplankton biovolume was evenly distributedthroughout the survey. Integrated values of Chl a and smallzooplankton biovolume in 2000 were greater than in 1999. Meganyctiphanesnorvegica, siphonophores and salps were the dominant componentsof the macrozooplankton population in the upper 200 m. In thesampled depth strata, siphonophore abundance did not changeduring the day, while M. norvegica were only caught at night.Acoustic backscatter data show that higher densities of M. norvegicaoccurred in deeper water and in the western and southwesternareas of the Ligurian Sea.