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Jantzie LL Talos DM Selip DB An L Jackson MC Folkerth RD Deng W Jensen FE 《Neuron glia biology》2010,6(4):277-288
Cerebral white matter injury in premature infants, known as periventricular leukomalacia (PVL), is common after hypoxia-ischemia (HI). While ionotropic glutamate receptors (iGluRs) can mediate immature white matter injury, we have previously shown that excitotoxic injury to premyelinating oligodendrocytes (preOLs) in vitro can be attenuated by group I metabotropic glutamate receptor (mGluR) agonists. Thus, we evaluated mGluR expression in developing white matter in rat and human brain, and tested the protective efficacy of a central nervous system (CNS)-penetrating mGluR agonist on injury to developing oligodendrocytes (OLs) in vivo. Group I mGluRs (mGluR1 and mGluR5) were strongly expressed on OLs in neonatal rodent cerebral white matter throughout normal development, with highest expression early in development on preOLs. Specifically at P6, mGluR1 and mGLuR5 were most highly expressed on GalC-positive OLs compared to neurons, axons, astrocytes and microglia. Systemic administration of (1S,3R) 1-aminocyclopentane-trans-1,3,-dicarboxylic acid (ACPD) significantly attenuated the loss of myelin basic protein in the white matter following HI in P6 rats. Assessment of postmortem human tissue showed both mGluR1 and mGluR5 localized on immature OLs in white matter throughout development, with mGluR5 highest in the preterm period. These data indicate group I mGluRs are highly expressed on OLs during the peak period of vulnerability to HI and modulation of mGluRs is protective in a rodent model of PVL. Group I mGluRs may represent important therapeutic targets for protection from HI-mediated white matter injury. 相似文献
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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. 相似文献7.
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. 相似文献8.
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