Interactive effects of vascular risk burden and advanced age on cerebral blood flow.

Vascular risk factors and cerebral blood flow (CBF) reduction have been linked to increased risk of cognitive impairment and Alzheimer's disease (AD); however the possible moderating effects of age and vascular risk burden on CBF in late life remain understudied. We examined the relationships among elevated vascular risk burden, age, CBF, and cognition. Seventy-one non-demented older adults completed an arterial spin labeling MR scan, neuropsychological assessment, and medical history interview. Relationships among vascular risk burden, age, and CBF were examined in a priori regions of interest (ROIs) previously implicated in aging and AD. Interaction effects indicated that, among older adults with elevated vascular risk burden (i.e., multiple vascular risk factors), advancing age was significantly associated with reduced cortical CBF whereas there was no such relationship for those with low vascular risk burden (i.e., no or one vascular risk factor). This pattern was observed in cortical ROIs including medial temporal (hippocampus, parahippocampal gyrus, uncus), inferior parietal (supramarginal gyrus, inferior parietal lobule, angular gyrus), and frontal (anterior cingulate, middle frontal gyrus, medial frontal gyrus) cortices. Furthermore, among those with elevated vascular risk, reduced CBF was associated with poorer cognitive performance. Such findings suggest that older adults with elevated vascular risk burden may be particularly vulnerable to cognitive change as a function of CBF reductions. Findings support the use of CBF as a potential biomarker in preclinical AD and suggest that vascular risk burden and regionally-specific CBF changes may contribute to differential age-related cognitive declines

Attributing scientific and technical progress: the case of holography

Holography, the three-dimensional imaging technology, was portrayed widely as a paradigm of progress during its decade of explosive expansion 1964–73, and during its subsequent consolidation for commercial and artistic uses up to the mid 1980s. An unusually seductive and prolific subject, holography successively spawned scientific insights, putative applications and new constituencies of practitioners and consumers. Waves of forecasts, associated with different sponsors and user communities, cast holography as a field on the verge of success—but with the dimensions of success repeatedly refashioned. This retargeting of the subject represented a degree of cynical marketeering, but was underpinned by implicit confidence in philosophical positivism and faith in technological progressivism. Each of its communities defined success in terms of expansion, and anticipated continual progressive increase. This paper discusses the contrasting definitions of progress in holography, and how they were fashioned in changing contexts. Focusing equally on reputed ‘failures’ of some aspects of the subject, it explores the varied attributes by which success and failure were linked with progress by different technical communities. This important case illuminates the peculiar post-World War II environment that melded the military, commercial and popular engagement with scientific and technological subjects, and the competing criteria by which they assessed the products of science

Assessing Working Memory in Mild Cognitive Impairment with Serial Order Recall.

BACKGROUND: Working memory (WM) is often assessed with serial order tests such as repeating digits backward. In prior dementia research using the Backward Digit Span Test (BDT), only aggregate test performance was examined. OBJECTIVE: The current research tallied primacy/recency effects, out-of-sequence transposition errors, perseverations, and omissions to assess WM deficits in patients with mild cognitive impairment (MCI). METHODS: Memory clinic patients (n = 66) were classified into three groups: single domain amnestic MCI (aMCI), combined mixed domain/dysexecutive MCI (mixed/dys MCI), and non-MCI where patients did not meet criteria for MCI. Serial order/WM ability was assessed by asking participants to repeat 7 trials of five digits backwards. Serial order position accuracy, transposition errors, perseverations, and omission errors were tallied. RESULTS: A 3 (group)×5 (serial position) repeated measures ANOVA yielded a significant group×trial interaction. Follow-up analyses found attenuation of the recency effect for mixed/dys MCI patients. Mixed/dys MCI patients scored lower than non-MCI patients for serial position 3 (p \u3c 0.003) serial position 4 (p \u3c 0.002); and lower than both group for serial position 5 (recency; p \u3c 0.002). Mixed/dys MCI patients also produced more transposition errors than both groups (p \u3c 0.010); and more omissions (p \u3c 0.020), and perseverations errors (p \u3c 0.018) than non-MCI patients. CONCLUSIONS: The attenuation of a recency effect using serial order parameters obtained from the BDT may provide a useful operational definition as well as additional diagnostic information regarding working memory deficits in MCI

Characterization of a Novel Interaction between Bcl-2 Members Diva and Harakiri

Interactions within proteins of the Bcl-2 family are key in the regulation of apoptosis. The death-inducing members control apoptotic mechanisms partly by antagonizing the prosurvival proteins through heterodimer formation. Structural and biophysical studies on these complexes are providing important clues to understand their function. To help improve our knowledge on protein-protein interactions within the Bcl-2 family we have studied the binding between two of its members: mouse Diva and human Harakiri. Diva has been shown to perform both prosurvival and killing activity. In contrast, Harakiri induces cell death by interacting with antiapoptotic Bcl-2 members. Here we show using ELISA and NMR that Diva and Harakiri can interact in vitro. Combining the NMR data with the previously reported three-dimensional structure of Diva we find that Harakiri binds to a specific region in Diva. This interacting surface is equivalent to the known binding area of prosurvival Bcl-2 members from the reported structures of the complexes, suggesting that Diva could function at the structural level similarly to the antiapoptotic proteins of the Bcl-2 family. We illustrate this result by building a structural model of the heterodimer using molecular docking and the NMR data as restraints. Moreover, combining circular dichroism and NMR we also show that Harakiri is largely unstructured with residual (13%) α-helical conformation. This result agrees with intrinsic disorder previously observed in other Bcl-2 members. In addition, Harakiri constructs of different length were studied to identify the region critical for the interaction. Differential affinity for Diva of these constructs suggests that the amino acid sequence flanking the interacting region could play an important role in binding

Gene Set Enrichment in eQTL Data Identifies Novel Annotations and Pathway Regulators

Genome-wide gene expression profiling has been extensively used to generate biological hypotheses based on differential expression. Recently, many studies have used microarrays to measure gene expression levels across genetic mapping populations. These gene expression phenotypes have been used for genome-wide association analyses, an analysis referred to as expression QTL (eQTL) mapping. Here, eQTL analysis was performed in adipose tissue from 28 inbred strains of mice. We focused our analysis on “trans-eQTL bands”, defined as instances in which the expression patterns of many genes were all associated to a common genetic locus. Genes comprising trans-eQTL bands were screened for enrichments in functional gene sets representing known biological pathways, and genes located at associated trans-eQTL band loci were considered candidate transcriptional modulators. We demonstrate that these patterns were enriched for previously characterized relationships between known upstream transcriptional regulators and their downstream target genes. Moreover, we used this strategy to identify both novel regulators and novel members of known pathways. Finally, based on a putative regulatory relationship identified in our analysis, we identified and validated a previously uncharacterized role for cyclin H in the regulation of oxidative phosphorylation. We believe that the specific molecular hypotheses generated in this study will reveal many additional pathway members and regulators, and that the analysis approaches described herein will be broadly applicable to other eQTL data sets

Structural Basis of Response Regulator Dephosphorylation by Rap Phosphatases

Crystallographic, biochemical, and genetic studies reveal the mechanism of Rap protein phosphatase activity within the phosphorelay pathway leading to sporulation in Bacillus species

Axial and Radial Forces of Cross-Bridges Depend on Lattice Spacing

Nearly all mechanochemical models of the cross-bridge treat myosin as a simple linear spring arranged parallel to the contractile filaments. These single-spring models cannot account for the radial force that muscle generates (orthogonal to the long axis of the myofilaments) or the effects of changes in filament lattice spacing. We describe a more complex myosin cross-bridge model that uses multiple springs to replicate myosin's force-generating power stroke and account for the effects of lattice spacing and radial force. The four springs which comprise this model (the 4sXB) correspond to the mechanically relevant portions of myosin's structure. As occurs in vivo, the 4sXB's state-transition kinetics and force-production dynamics vary with lattice spacing. Additionally, we describe a simpler two-spring cross-bridge (2sXB) model which produces results similar to those of the 4sXB model. Unlike the 4sXB model, the 2sXB model requires no iterative techniques, making it more computationally efficient. The rate at which both multi-spring cross-bridges bind and generate force decreases as lattice spacing grows. The axial force generated by each cross-bridge as it undergoes a power stroke increases as lattice spacing grows. The radial force that a cross-bridge produces as it undergoes a power stroke varies from expansive to compressive as lattice spacing increases. Importantly, these results mirror those for intact, contracting muscle force production

Searching for DNA Lesions: Structural Evidence for Lower- and Higher-Affinity DNA Binding Conformations of Human Alkyladenine DNA Glycosylase

To efficiently repair DNA, human alkyladenine DNA glycosylase (AAG) must search the million-fold excess of unmodified DNA bases to find a handful of DNA lesions. Such a search can be facilitated by the ability of glycosylases, like AAG, to interact with DNA using two affinities: a lower-affinity interaction in a searching process and a higher-affinity interaction for catalytic repair. Here, we present crystal structures of AAG trapped in two DNA-bound states. The lower-affinity depiction allows us to investigate, for the first time, the conformation of this protein in the absence of a tightly bound DNA adduct. We find that active site residues of AAG involved in binding lesion bases are in a disordered state. Furthermore, two loops that contribute significantly to the positive electrostatic surface of AAG are disordered. Additionally, a higher-affinity state of AAG captured here provides a fortuitous snapshot of how this enzyme interacts with a DNA adduct that resembles a one-base loop.National Institutes of Health (U.S.) (grant no. P30-ES002109)National Institutes of Health (U.S.) (grant no. GM65337)National Institutes of Health (U.S.) (grant no. GM65337-03S2)National Institutes of Health (U.S.) (grant no. CA055042)National Institutes of Health (U.S.) (grant no. CA092584)Repligen Corporation (KIICR Graduate Fellowship

Structure-Based Design of Non-Natural Amino Acid Inhibitors of Amyloid Fibrillation

Many globular and natively disordered proteins can convert into amyloid fibers. These fibers are associated with numerous pathologies1 as well as with normal cellular functions2,3, and frequently form during protein denaturation4,5. Inhibitors of pathological amyloid fibers could serve as leads for therapeutics, provided the inhibitors were specific enough to avoid interfering with normal processes. Here we show that computer-aided, structure-based design can yield highly specific peptide inhibitors of amyloid formation. Using known atomic structures of segments of amyloid fibers as templates, we have designed and characterized an all D-amino acid inhibitor of fibrillation of the tau protein found in Alzheimer’s disease, and a non-natural L-amino acid inhibitor of an amyloid fiber that enhances sexual transmission of HIV. Our results indicate that peptides from structure-based designs can disrupt the fibrillation of full-length proteins, including those like tau that lack fully ordered native structures.We thank M.I. Ivanova, J. Corn, T. Kortemme, D. Anderson, M.R. Sawaya, M. Phillips, S. Sambashivan, J. Park, M. Landau, Q. Zhang, R. Clubb, F. Guo, T. Yeates, J. Nowick, J. Zheng, and M.J. Thompson for discussions, HHMI, NIH, NSF, the GATES foundation, and the Joint Center for Translational Medicine for support, R. Peterson for help with NMR experiments, E. Mandelkow for providing tau constructs, R. Riek for providing amyloid beta, J. Stroud for amyloid beta preparation. Support for JK was from the Damon Runyon Cancer Research Foundation, for HWC by the Ruth L. Kirschstein National Research Service Award, for JM from the programme for junior-professors by the ministry of science, Baden-Württemberg, and for SAS by a UCLA-IGERT bioinformatics traineeship

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods

Background: Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual aminoacids are systematically mutated to alanine and changes in free energy of binding (Delta Delta G) measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots") at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition.Results: We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which Delta Delta G >= 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%.Conclusion: We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been applied separately to biomolecular problems, the results of our investigation indicate that there are substantial benefits to be gained by their integration