Association between objectively measured physical activity and opioid, hypnotic, or anticholinergic medication use in older people – data from the Physical Activity Cohort Scotland study

Background: Centrally acting medications cause cognitive slowing and incoordination, which could reduce older people’s physical activity levels. This association has not been studied previously.Objectives: To examine the association between opioid, hypnotic and anticholinergic medication, and objectively measured physical activity, in a cohort of older people.Methods: We used data from the Physical Activity Cohort Scotland, a representative cohort of community-dwelling older people aged 65 and over who were assessed at baseline and again 2-3 years later. Objective physical activity was measured using Stayhealthy RT3 accelerometers over 7 days. Baseline medication use (opioid use, hypnotic use, modified anticholinergic risk score [mARS]) was obtained from linked, routinely collected community prescribing records. Cross-sectional and longitudinal associations between baseline medication use and both baseline activity and change in activity over time were analysed using unadjusted and adjusted linear regression models.Results: 310 participants were included in the analysis; mean age 77 (SD 7) years. No association was seen between baseline use of any medication class and baseline physical activity levels in unadjusted or adjusted models. For change in activity over time, there was no difference between users and non-users of hypnotics or opioids. Higher anticholinergic burden was associated with a steeper decline in activity over the follow up period (mARS=0: -7051 counts/24h/yr; mARS=1-2 -15942 counts/24h/yr; mARS>=3 -19544 counts/24h/yr; p=0.03) and this remained robust to multiple adjustments.Conclusion: Anticholinergic burden is associated with greater decline in objectively measured physical activity over time in older people, a finding not seen with hypnotic or opioid use

Surface plasmon resonance imaging of cells and surface-associated fibronectin

<p>Abstract</p> <p>Background</p> <p>A critical challenge in cell biology is quantifying the interactions of cells with their extracellular matrix (ECM) environment and the active remodeling by cells of their ECM. Fluorescence microscopy is a commonly employed technique for examining cell-matrix interactions. A label-free imaging method would provide an alternative that would eliminate the requirement of transfected cells and modified biological molecules, and if collected nondestructively, would allow long term observation and analysis of live cells.</p> <p>Results</p> <p>Using surface plasmon resonance imaging (SPRI), the deposition of protein by vascular smooth muscle cells (vSMC) cultured on fibronectin was quantified as a function of cell density and distance from the cell periphery. We observed that as much as 120 ng/cm²of protein was deposited by cells in 24 h.</p> <p>Conclusion</p> <p>SPRI is a real-time, low-light-level, label-free imaging technique that allows the simultaneous observation and quantification of protein layers and cellular features. This technique is compatible with live cells such that it is possible to monitor cellular modifications to the extracellular matrix in real-time.</p

Prediction model of coal seam gas content based on ACSOA optimized BP neural network

For the problem of coal seam gas content prediction, the influencing factors of coal seam gas content were analyzed by taking No.2 coal seam of Chensilou Coal Mine as the research object. Based on the above, a prediction model of coal seam gas content was proposed based on adaptive chaotic seagull optimization algorithm (ACSOA) optimized BP neural network (ACSOA-BP). In the ACSOA, introducing chaos algorithm into SOA algorithm for chaos initialization, and adaptive algorithm and nonlinear convergence factor was proposed in SOA algorithm to improve the optimization ability. And the ACSOA-BP model was applied to the study area to verification. The results show that the relationship is nonlinear between gas content of No.2 coal seam and the influencing factors in Chensilou Coal Mine, and the geological structure is the main controlling factor of gas distribution. Compared with the BP model and the SOA-BP model, the ACSOA-BP model has a higher accuracy and stability