2,347 research outputs found

    Contributions of Bcl-xL to acute and long term changes in bioenergetics during neuronal plasticity

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    Author Posting. © The Author(s), 2013. This is the author's version of the work. It is posted here by permission of Elsevier for personal use, not for redistribution. The definitive version was published in Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease 1842 (2014): 1168–1178, doi:10.1016/j.bbadis.2013.11.007.Mitochondria manufacture and release metabolites and manage calcium during neuronal activity and synaptic transmission, but whether long term alterations in mitochondrial function contribute to neuronal plasticity that underlies changes in organism behavior patterns is still poorly understood. Although normal neuronal plasticity may determine learning, in contrast a persistent decline in synaptic strength or neuronal excitability may portend neurite retraction and eventual somatic death. Anti-death proteins such as Bcl-xL provide neuroprotection at the neuronal soma during cell death stimuli, but also appear to enhance neurotransmitter release and synaptic growth and development. It is proposed that Bcl-xL performs these functions through its ability to regulate mitochondrial release of bioenergetic metabolites and calcium, its ability to rapidly alter mitochondrial positioning and morphology as well as its role in interacting with proteins that directly alter synaptic vesicle recycling. Bcl-xL translocates acutely to sub-cellular membranes during neuronal activity to achieve these changes. After stressful stimuli, pro-apoptotic cleaved delta N Bcl-xL (ΔN Bcl-xL)-induced mitochondrial ion channel activity leads to synaptic depression and this is regulated by caspase activation. During physiological states of decreased synaptic stimulation, loss of mitochondrial Bcl-xL and low level caspase activation occur prior to the onset of long term decline in synaptic efficacy. The degree to which Bcl-xL changes mitochondrial membrane permeability may control the direction of change in synaptic strength. The small molecule Bcl-xL inhibitor ABT-737 has been useful in defining the role of Bcl-xL in synaptic processes. Bcl-xL is crucial to the normal health of neurons and synapses and its malfunction may contribute to neurodegenerative disease

    Mitochondrial Regulators of Synaptic Plasticity in the Ischemic Brain

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    Synaptic plasticity is a process by which neurons adapt or alter the strength of information transfer, and it is known to play a role in memory formation, learning, and recovery after injury. In this chapter, we describe how ischemic insults alter neuronal intracellular mechanisms and signaling pathways, and we discuss how, after neuronal injury, synaptic plasticity is regulated prior to and during death or rehabilitation and recovery. In addition, recently described regulators of synaptic plasticity will be introduced

    DJ1 regulates Neuronal Mitochondrial Bioenergetic Efficiency

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    A multivariate prediction model for microarray cross-hybridization

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    BACKGROUND: Expression microarray analysis is one of the most popular molecular diagnostic techniques in the post-genomic era. However, this technique faces the fundamental problem of potential cross-hybridization. This is a pervasive problem for both oligonucleotide and cDNA microarrays; it is considered particularly problematic for the latter. No comprehensive multivariate predictive modeling has been performed to understand how multiple variables contribute to (cross-) hybridization. RESULTS: We propose a systematic search strategy using multiple multivariate models [multiple linear regressions, regression trees, and artificial neural network analyses (ANNs)] to select an effective set of predictors for hybridization. We validate this approach on a set of DNA microarrays with cytochrome p450 family genes. The performance of our multiple multivariate models is compared with that of a recently proposed third-order polynomial regression method that uses percent identity as the sole predictor. All multivariate models agree that the 'most contiguous base pairs between probe and target sequences,' rather than percent identity, is the best univariate predictor. The predictive power is improved by inclusion of additional nonlinear effects, in particular target GC content, when regression trees or ANNs are used. CONCLUSION: A systematic multivariate approach is provided to assess the importance of multiple sequence features for hybridization and of relationships among these features. This approach can easily be applied to larger datasets. This will allow future developments of generalized hybridization models that will be able to correct for false-positive cross-hybridization signals in expression experiments

    Serum profiling by MALDI-TOF mass spectrometry as a diagnostic tool for domoic acid toxicosis in California sea lions

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    <p>Abstract</p> <p>Background</p> <p>There are currently no reliable markers of acute domoic acid toxicosis (DAT) for California sea lions. We investigated whether patterns of serum peptides could diagnose acute DAT. Serum peptides were analyzed by MALDI-TOF mass spectrometry from 107 sea lions (acute DAT n = 34; non-DAT n = 73). Artificial neural networks (ANN) were trained using MALDI-TOF data. Individual peaks and neural networks were qualified using an independent test set (n = 20).</p> <p>Results</p> <p>No single peak was a good classifier of acute DAT, and ANN models were the best predictors of acute DAT. Performance measures for a single median ANN were: sensitivity, 100%; specificity, 60%; positive predictive value, 71%; negative predictive value, 100%. When 101 ANNs were combined and allowed to vote for the outcome, the performance measures were: sensitivity, 30%; specificity, 100%; positive predictive value, 100%; negative predictive value, 59%.</p> <p>Conclusions</p> <p>These results suggest that MALDI-TOF peptide profiling and neural networks can perform either as a highly sensitive (100% negative predictive value) or a highly specific (100% positive predictive value) diagnostic tool for acute DAT. This also suggests that machine learning directed by populations of predictive models offer the ability to modulate the predictive effort into a specific type of error.</p

    Most Common Single-Nucleotide Polymorphisms Associated With Rheumatoid Arthritis in Persons of European Ancestry Confer Risk of Rheumatoid Arthritis in African Americans

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    Objective. Large-scale genetic association studies have identified \u3e20 rheumatoid arthritis (RA) risk alleles among individuals of European ancestry. The influence of these risk alleles has not been comprehensively studied in African Americans. We therefore sought to examine whether these validated RA risk alleles are associated with RA risk in an African American population. Methods. Twenty-seven candidate single-nucleotide polymorphisms (SNPs) were genotyped in 556 autoantibody-positive African Americans with RA and 791 healthy African American control subjects. Odds ratios (ORs) and 95% confidence intervals (95% CIs) for each SNP were compared with previously published ORs for RA patients of European ancestry. We then calculated a composite genetic risk score (GRS) for each individual based on the sum of all risk alleles. Results. Overlap of the ORs and 95% CIs between the European and African American populations was observed for 24 of the 27 candidate SNPs. Conversely, 3 of the 27 SNPs (CCR6 rs3093023, TAGAP rs394581, and TNFAIP3 rs6920220) demonstrated ORs in the opposite direction from those reported for RA patients of European ancestry. The GRS analysis indicated a small but highly significant probability that African American patients relative to control subjects were enriched for the risk alleles validated in European RA patients (P = 0.00005). Conclusion. The majority of RA risk alleles previously validated for RA patients of European ancestry showed similar ORs in our population of African Americans with RA. Furthermore, the aggregate GRS supports the hypothesis that these SNPs are risk alleles for RA in the African American population. Future large-scale genetic studies are needed to validate these risk alleles and identify novel RA risk alleles in African Americans
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