2 resultados para Group interaction
em Digital Commons - Michigan Tech
Resumo:
Nearly 22 million Americans operate as shift workers, and shift work has been linked to the development of cardiovascular disease (CVD). This study is aimed at identifying pivotal risk factors of CVD by assessing 24 hour ambulatory blood pressure, state anxiety levels and sleep patterns in 12 hour fixed shift workers. We hypothesized that night shift work would negatively affect blood pressure regulation, anxiety levels and sleep patterns. A total of 28 subjects (ages 22-60) were divided into two groups: 12 hour fixed night shift workers (n=15) and 12 hour fixed day shift workers (n=13). 24 hour ambulatory blood pressure measurements (Space Labs 90207) were taken twice: once during a regular work day and once on a non-work day. State anxiety levels were assessed on both test days using the Speilberger’s State Trait Anxiety Inventory. Total sleep time (TST) was determined using self recorded sleep diary. Night shift workers demonstrated increases in 24 hour systolic (122 ± 2 to 126 ± 2 mmHg, P=0.012); diastolic (75 ± 1 to 79 ± 2 mmHg, P=0.001); and mean arterial pressures (90 ± 2 to 94 ± 2mmHg, P<0.001) during work days compared to off days. In contrast, 24 hour blood pressures were similar during work and off days in day shift workers. Night shift workers reported less TST on work days versus off days (345 ± 16 vs. 552 ± 30 min; P<0.001), whereas day shift workers reported similar TST during work and off days (475 ± 16 minutes to 437 ± 20 minutes; P=0.231). State anxiety scores did not differ between the groups or testing days (time*group interaction P=0.248), suggesting increased 24 hour blood pressure during night shift work is related to decreased TST, not short term anxiety. Our findings suggest that fixed night shift work causes disruption of the normal sleep-wake cycle negatively affecting acute blood pressure regulation, which may increase the long-term risk for CVD.
Resumo:
Many types of materials at nanoscale are currently being used in everyday life. The production and use of such products based on engineered nanomaterials have raised concerns of the possible risks and hazards associated with these nanomaterials. In order to evaluate and gain a better understanding of their effects on living organisms, we have performed first-principles quantum mechanical calculations and molecular dynamics simulations. Specifically, we will investigate the interaction of nanomaterials including semiconducting quantum dots and metallic nanoparticles with various biological molecules, such as dopamine, DNA nucleobases and lipid membranes. Firstly, interactions of semiconducting CdSe/CdS quantum dots (QDs) with the dopamine and the DNA nucleobase molecules are investigated using similar quantum mechanical approach to the one used for the metallic nanoparticles. A variety of interaction sites are explored. Our results show that small-sized Cd4Se4 and Cd4S4 QDs interact strongly with the DNA nucleobase if a DNA nucleobase has the amide or hydroxyl chemical group. These results indicate that these QDs are suitable for detecting subcellular structures, as also reported by experiments. The next two chapters describe a preparation required for the simulation of nanoparticles interacting with membranes leading to accurate structure models for the membranes. We develop a method for the molecular crystalline structure prediction of 1,2-Dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC), 1,2-Dimyristoyl-sn-glycero-3-phosphorylethanolamine (DMPE) and cyclic di-amino acid peptide using first-principles methods. Since an accurate determination of the structure of an organic crystal is usually an extremely difficult task due to availability of the large number of its conformers, we propose a new computational scheme by applying knowledge of symmetry, structural chemistry and chemical bonding to reduce the sampling size of the conformation space. The interaction of metal nanoparticles with cell membranes is finally carried out by molecular dynamics simulations, and the results are reported in the last chapter. A new force field is developed which accurately describes the interaction forces between the clusters representing small-sized metal nanoparticles and the lipid bilayer molecules. The permeation of nanoparticles into the cell membrane is analyzed together with the RMSD values of the membrane modeled by a lipid bilayer. The simulation results suggest that the AgNPs could cause the same amount of deformation as the AuNPs for the dysfunction of the membrane.