Examining links between anxiety, reinvestment and walking when talking by older adults during adaptive gait

Falls by older adults often result in reduced quality of life and debilitating fear of further falls. Stopping walking when talking (SWWT) is a significant predictor of future falls by older adults and is thought to reflect age-related increases in attentional demands of walking. We examine whether SWWT is associated with use of explicit movement cues during locomotion, and evaluate if conscious control (i.e., movement specific reinvestment) is causally linked to falls-related anxiety during a complex walking task. We observed whether twenty-four older adults stopped walking when talking when asked a question during an adaptive gait task. After certain trials, participants completed a visual-spatial recall task regarding walkway features, or answered questions about their movements during the walk. In a subsequent experimental condition, participants completed the walking task under conditions of raised postural threat. Compared to a control group, participants who SWWT reported higher scores for aspects of reinvestment relating to conscious motor processing but not movement self-consciousness. The higher scores for conscious motor processing were preserved when scores representing cognitive function were included as a covariate. There were no group differences in measures of general cognitive function, visual spatial working memory or balance confidence. However, the SWWT group reported higher scores on a test of external awareness when walking, indicating allocation of attention away from task-relevant environmental features. Under conditions of increased threat, participants self-reported significantly greater state anxiety and reinvestment and displayed more accurate responses about their movements during the task. SWWT is not associated solely with age-related cognitive decline or generic increases in age-related attentional demands of walking. SWWT may be caused by competition for phonological resources of working memory associated with consciously processing motor actions and appears to be causally linked with fall-related anxiety and increased vigilance.This research was supported by The Royal Society (IE131576) and British Academy (SG132820)

In-vivo optical detection of cancer using chlorin e6 – polyvinylpyrrolidone induced fluorescence imaging and spectroscopy

<p>Abstract</p> <p>Background</p> <p>Photosensitizer based fluorescence imaging and spectroscopy is fast becoming a promising approach for cancer detection. The purpose of this study was to examine the use of the photosensitizer chlorin e6 (Ce6) formulated in polyvinylpyrrolidone (PVP) as a potential exogenous fluorophore for fluorescence imaging and spectroscopic detection of human cancer tissue xenografted in preclinical models as well as in a patient.</p> <p>Methods</p> <p>Fluorescence imaging was performed on MGH human bladder tumor xenografted on both the chick chorioallantoic membrane (CAM) and the murine model using a fluorescence endoscopy imaging system. In addition, fiber optic based fluorescence spectroscopy was performed on tumors and various normal organs in the same mice to validate the macroscopic images. In one patient, fluorescence imaging was performed on angiosarcoma lesions and normal skin in conjunction with fluorescence spectroscopy to validate Ce6-PVP induced fluorescence visual assessment of the lesions.</p> <p>Results</p> <p>Margins of tumor xenografts in the CAM model were clearly outlined under fluorescence imaging. Ce6-PVP-induced fluorescence imaging yielded a specificity of 83% on the CAM model. In mice, fluorescence intensity of Ce6-PVP was higher in bladder tumor compared to adjacent muscle and normal bladder. Clinical results confirmed that fluorescence imaging clearly captured the fluorescence of Ce6-PVP in angiosarcoma lesions and good correlation was found between fluorescence imaging and spectral measurement in the patient.</p> <p>Conclusion</p> <p>Combination of Ce6-PVP induced fluorescence imaging and spectroscopy could allow for optical detection and discrimination between cancer and the surrounding normal tissues. Ce6-PVP seems to be a promising fluorophore for fluorescence diagnosis of cancer.</p

Estimating cumulative pathway effects on risk for age-related macular degeneration using mixed linear models

BACKGROUND: Age-related macular degeneration (AMD) is the leading cause of irreversible visual loss in the elderly in developed countries and typically affects more than 10 % of individuals over age 80. AMD has a large genetic component, with heritability estimated to be between 45 % and 70 %. Numerous variants have been identified and implicate various molecular mechanisms and pathways for AMD pathogenesis but those variants only explain a portion of AMD’s heritability. The goal of our study was to estimate the cumulative genetic contribution of common variants on AMD risk for multiple pathways related to the etiology of AMD, including angiogenesis, antioxidant activity, apoptotic signaling, complement activation, inflammatory response, response to nicotine, oxidative phosphorylation, and the tricarboxylic acid cycle. While these mechanisms have been associated with AMD in literature, the overall extent of the contribution to AMD risk for each is unknown. METHODS: In a case–control dataset with 1,813 individuals genotyped for over 600,000 SNPs we used Genome-wide Complex Trait Analysis (GCTA) to estimate the proportion of AMD risk explained by SNPs in genes associated with each pathway. SNPs within a 50 kb region flanking each gene were also assessed, as well as more distant, putatively regulatory SNPs, based on DNaseI hypersensitivity data from ocular tissue in the ENCODE project. RESULTS: We found that 19 previously associated AMD risk SNPs contributed to 13.3 % of the risk for AMD in our dataset, while the remaining genotyped SNPs contributed to 36.7 % of AMD risk. Adjusting for the 19 risk SNPs, the complement activation and inflammatory response pathways still explained a statistically significant proportion of additional risk for AMD (9.8 % and 17.9 %, respectively), with other pathways showing no significant effects (0.3 % – 4.4 %). DISCUSSION: Our results show that SNPs associated with complement activation and inflammation significantly contribute to AMD risk, separately from the risk explained by the 19 known risk SNPs. We found that SNPs within 50 kb regions flanking genes explained additional risk beyond genic SNPs, suggesting a potential regulatory role, but that more distant SNPs explained less than 0.5 % additional risk for each pathway. CONCLUSIONS: From these analyses we find that the impact of complement SNPs on risk for AMD extends beyond the established genome-wide significant SNPs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0760-4) contains supplementary material, which is available to authorized users

A constructive approach for discovering new drug leads: Using a kernel methodology for the inverse-QSAR problem

<p>Abstract</p> <p>Background</p> <p>The inverse-QSAR problem seeks to find a new molecular descriptor from which one can recover the structure of a molecule that possess a desired activity or property. Surprisingly, there are very few papers providing solutions to this problem. It is a difficult problem because the molecular descriptors involved with the inverse-QSAR algorithm must adequately address the forward QSAR problem for a given biological activity if the subsequent recovery phase is to be meaningful. In addition, one should be able to construct a feasible molecule from such a descriptor. The difficulty of recovering the molecule from its descriptor is the major limitation of most inverse-QSAR methods.</p> <p>Results</p> <p>In this paper, we describe the reversibility of our previously reported descriptor, the vector space model molecular descriptor (VSMMD) based on a vector space model that is suitable for kernel studies in QSAR modeling. Our inverse-QSAR approach can be described using five steps: (1) generate the VSMMD for the compounds in the training set; (2) map the VSMMD in the input space to the kernel feature space using an appropriate kernel function; (3) design or generate a new point in the kernel feature space using a kernel feature space algorithm; (4) map the feature space point back to the input space of descriptors using a pre-image approximation algorithm; (5) build the molecular structure template using our VSMMD molecule recovery algorithm.</p> <p>Conclusion</p> <p>The empirical results reported in this paper show that our strategy of using kernel methodology for an inverse-Quantitative Structure-Activity Relationship is sufficiently powerful to find a meaningful solution for practical problems.</p

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.

This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.3448Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.We thank all participants of all the studies included for enabling this research by their participation in these studies. Computer resources for this project have been provided by the high-performance computing centers of the University of Michigan and the University of Regensburg. Group-specific acknowledgments can be found in the Supplementary Note. The Center for Inherited Diseases Research (CIDR) Program contract number is HHSN268201200008I. This and the main consortium work were predominantly funded by 1X01HG006934-01 to G.R.A. and R01 EY022310 to J.L.H