The proteasome: A key modulator of nervous system function, brain aging, and neurodegenerative disease

The proteasome is a large multi-subunit protease responsible for the degradation and removal of oxidized, misfolded, and polyubiquitinated proteins. The proteasome plays critical roles in nervous system processes. This includes maintenance of cellular homeostasis in neurons. It also includes roles in long-term potentiation via modulation of CREB signaling. The proteasome also possesses roles in promoting dendritic spine growth driven by proteasome localization to the dendritic spines in an NMDA/CaMKIIα dependent manner. Proteasome inhibition experiments in varied organisms has been shown to impact memory, consolidation, recollection and extinction. The proteasome has been further shown to impact circadian rhythm through modulation of a range of ‘clock’ genes, and glial function. Proteasome function is impaired as a consequence both of aging and neurodegenerative diseases. Many studies have demonstrated an impairment in 26S proteasome function in the brain and other tissues as a consequence of age, driven by a disassembly of 26S proteasome in favor of 20S proteasome. Some studies also show proteasome augmentation to correct age-related deficits. In amyotrophic lateral sclerosis Alzheimer’s, Parkinson’s and Huntington’s disease proteasome function is impaired through distinct mechanisms with impacts on disease susceptibility and progression. Age and neurodegenerative-related deficits in the function of the constitutive proteasome are often also accompanied by an increase in an alternative form of proteasome called the immunoproteasome. This article discusses the critical role of the proteasome in the nervous system. We then describe how proteasome dysfunction contributes to brain aging and neurodegenerative disease

Mitochondrial thioredoxin reductase 2 is elevated in long‐lived primate as well as rodent species and extends fly mean lifespan

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137684/1/acel12596-sup-0001-SupInfo.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137684/2/acel12596.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137684/3/acel12596_am.pd

Extraversion and Reward-Processing: Consolidating Evidence from an Electroencephalographic Index of Reward-Prediction-Error

Trait extraversion has been theorized to emerge from functioning of the dopaminergic reward system. Recent evidence for this view shows that extraversion modulates the scalp-recorded Reward Positivity, a putative marker of dopaminergic signaling of reward-prediction-error. We attempt to replicate this association amid several improvements on previous studies in this area, including an adequately-powered sample (N = 100) and thorough examination of convergent-divergent validity. Participants completed a passive associative learning task presenting rewards and non-rewards that were either predictable or unexpected. Frequentist and Bayesian analyses confirmed that the scalp recorded Reward Positivity (i.e. the Feedback-Related-Negativity contrasting unpredicted rewards and unpredicted non-rewards) was significantly associated with three measures of extraversion and unrelated to other basic traits from the Big Five personality model. Narrower sub-traits of extraversion showed similar, though weaker associations with the Reward Positivity. These findings consolidate previous evidence linking extraversion with a putative marker of dopaminergic reward-processing

Natural genetic variation in transcriptome reflects network structure inferred with major effect mutations: insulin/TOR and associated phenotypes in Drosophila melanogaster

<p>Abstract</p> <p>Background</p> <p>A molecular process based genotype-to-phenotype map will ultimately enable us to predict how genetic variation among individuals results in phenotypic alterations. Building such a map is, however, far from straightforward. It requires understanding how molecular variation re-shapes developmental and metabolic networks, and how the functional state of these networks modifies phenotypes in genotype specific way. We focus on the latter problem by describing genetic variation in transcript levels of genes in the InR/TOR pathway among 72 <it>Drosophila melanogaster </it>genotypes.</p> <p>Results</p> <p>We observe tight co-variance in transcript levels of genes not known to influence each other through direct transcriptional control. We summarize transcriptome variation with factor analyses, and observe strong co-variance of gene expression within the dFOXO-branch and within the TOR-branch of the pathway. Finally, we investigate whether major axes of transcriptome variation shape phenotypes expected to be influenced through the InR/TOR pathway. We find limited evidence that transcript levels of individual upstream genes in the InR/TOR pathway predict fly phenotypes in expected ways. However, there is no evidence that these effects are mediated through the major axes of downstream transcriptome variation.</p> <p>Conclusion</p> <p>In summary, our results question the assertion of the 'sparse' nature of genetic networks, while validating and extending candidate gene approaches in the analyses of complex traits.</p

Mappings preserving locations of movable poles: a new extension of the truncation method to ordinary differential equations

The truncation method is a collective name for techniques that arise from truncating a Laurent series expansion (with leading term) of generic solutions of nonlinear partial differential equations (PDEs). Despite its utility in finding Backlund transformations and other remarkable properties of integrable PDEs, it has not been generally extended to ordinary differential equations (ODEs). Here we give a new general method that provides such an extension and show how to apply it to the classical nonlinear ODEs called the Painleve equations. Our main new idea is to consider mappings that preserve the locations of a natural subset of the movable poles admitted by the equation. In this way we are able to recover all known fundamental Backlund transformations for the equations considered. We are also able to derive Backlund transformations onto other ODEs in the Painleve classification.Comment: To appear in Nonlinearity (22 pages

Rapid Start-up and Loading of an Attached Growth, Simultaneous Nitrification/Denitrification Membrane Aerated Bioreactor

Membrane aerated bioreactors (MABR) are attached-growth biological systems used for simultaneous nitrification and denitrification to reclaim water from waste. This design is an innovative approach to common terrestrial wastewater treatments for nitrogen and carbon removal and implementing a biologically-based water treatment system for long-duration human exploration is an attractive, low energy alternative to physiochemical processes. Two obstacles to implementing such a system are (1) the "start-up" duration from inoculation to steady-state operations and (2) the amount of surface area needed for the biological activity to occur. The Advanced Water Recovery Systems (AWRS) team at JSC explored these two issues through two tests; a rapid inoculation study and a wastewater loading study. Results from these tests demonstrate that the duration from inoculation to steady state can be reduced to under two weeks, and that despite low ammonium removal rates, the MABRs are oversized

B\"acklund transformations for the second Painlev\'e hierarchy: a modified truncation approach

The second Painlev\'e hierarchy is defined as the hierarchy of ordinary differential equations obtained by similarity reduction from the modified Korteweg-de Vries hierarchy. Its first member is the well-known second Painlev\'e equation, P2. In this paper we use this hierarchy in order to illustrate our application of the truncation procedure in Painlev\'e analysis to ordinary differential equations. We extend these techniques in order to derive auto-B\"acklund transformations for the second Painlev\'e hierarchy. We also derive a number of other B\"acklund transformations, including a B\"acklund transformation onto a hierarchy of P34 equations, and a little known B\"acklund transformation for P2 itself. We then use our results on B\"acklund transformations to obtain, for each member of the P2 hierarchy, a sequence of special integrals.Comment: 12 pages in LaTeX 2.09 (uses ioplppt.sty), to appear in Inverse Problem