IntroductionBiomedical applications of nanoparticles (NPs) as enzyme inhibitors have recently come to light. Oxides of metals native to the physiological environment (eg, Fe, Zn, Mg, etc.) are of particular interest—especially the functional consequences of their enzyme interaction.Materials and methodsHere, Fe2O3, zinc oxide (ZnO), magnesium oxide (MgO) and nickel oxide (NiO) NPs are compared to copper (Cu) and boron carbide (B4C) NPs. The functional impact of NP interaction to the model enzyme luciferase is determined by 2-dimensional fluorescence difference spectroscopy (2-D FDS) and 2-dimensional photoluminescence difference spectroscopy (2-D PLDS). By 2-D FDS analysis, the change in maximal intensity and in 2-D FDS area under the curve (AUC) is in the order Cu~B4C>ZnO>NiO>>Fe2O3>MgO. The induced changes in protein conformation are confirmed by tryptic digests and gel electrophoresis.ResultsAnalysis of possible trypsin cleavage sites suggest that cleavage mostly occurs in the range of residues 112–155 and 372–439, giving a major 45 kDa band. By 2-D PLDS, it is found that B4C NPs completely ablate bioluminescence, while Cu and Fe2O3 NPs yield a unique bimodal negative decay rate, −7.67×103 and −3.50×101 relative light units respectively. Cu NPs, in particular, give a remarkable 271% change in enzyme activity. Molecular dynamics simulations in water predicted that the surfaces of metal oxide NPs become capped with metal hydroxide groups under physiological conditions, while the surface of B4C becomes populated with boronic acid or borinic acid groups. These predictions are supported by the experimentally determined zeta potential. Thin layer chromatography patterns further support this conception of the NP surfaces, where stabilizing interactions were in the order ionic>polar>non-polar for the series tested.ConclusionOverall the results suggest that B4C and Cu NP functional dynamics on enzyme biochemistry are unique and should be examined further for potential ramifications on other model, physiological or disease-relevant enzymes.
Context: Athletic training students acquire clinical hours under the direct supervision of athletic training preceptors. Objective: The purpose of this project was to explore what characteristics preceptors desire in their athletic training students. Design and Setting: Online survey instrument. Patients or Other Participants: A total of 286 certified athletic trainers (128 male, 158 female; average years experience 10.58 ± 8.48). Participants were required to be current preceptors and have 1 or more years of preceptor experience. Main Outcome Measure(s): An instrument of 21 questions, including 7 demographics, 13 Likert-scale (1 = not important; 10 = strongly important), and 1 rank order item was developed. Validity of the instrument was established by a review of experts. An analysis of internal consistency revealed an α of .834. Data was analyzed with SPSS (version 20.0; IBM Inc, Chicago, IL). Basic descriptive statistics were calculated, and an analysis of variance was conducted to determine differences. Results: Top 3 characteristics seen amongst all settings were initiative (mean = 9.091 ± 1.166), communication skills (mean = 8.769 ± 1.241), and intelligence (mean = 8.723 ± 1.247). Gender differences were observed in 4 of the 13 characteristics. Conclusions: Findings demonstrated initiative, communication skills, and intelligence to be perceived as the most important athletic training student characteristics. These findings differ with previous literature and the preliminary focus group findings, where emotional intelligence and communication skills were reported to be of greater importance.
Nucleotide P2Y2 receptor (P2Y2R) plays important roles in inflammation. The leukocyte‐endothelium interaction is essential for leukocyte recruitment at the site of tissue damage or injury. Little is known about the role of P2Y2R in the regulation of in vivo leukocyte‐endothelium interaction. This study tested the hypothesis that P2Y2R mediates leukocyte‐endothelium interaction using the cremaster muscle. Leukocytes were labeled with Rhodamine 6G injected via tail vein. Leukocyte rolling and stable adhesion were analyzed using a semi‐automatic leukocyte tracking method. P2Y2R activation by UTP increased leukocyte rolling (EC50 = 4.7 ± 1.4 x 10−7 M) and adhesion (EC50= 4.3 ± 1.3 x 10−6 M) in a concentration‐dependent manner in C57BL/6 wild‐type (WT) mice (n=3). UTP (10−5 M) induced sustained increases in both leukocyte rolling and adhesion in WT mice (n=7–19, P<0.05) over 60 min. P2Y2R knockout (P2Y2R−/−) mice exhibited a 2‐fold increase in baseline leukocyte rolling (rolling fraction=37.8%, n=8, p < 0.001) compared to WT mice (rolling fraction=16.2%, n=12) and stayed at the high basal level without changes in rolling following stimulation of UTP (10−5 M) over 60 min. Baseline leukocyte adhesion in P2Y2R−/− mice was 1.5‐fold increase (15 ± 4 adherent cells.100 μm−1, n=12, p < 0.001) compared with WT mice (9 ± 4 adherent cells·100 μm−1; n=19). There was no change in leukocyte adhesion from the baseline in response to UPT (10−5 M) stimulation in P2Y2R−/− mice (n=5–12). We conclude that P2Y2R prevents in vivo leukocyte rolling and adhesion under resting condition while activation P2Y2R by UTP increases both leukocyte rolling and adhesion. Support or Funding Information Missouri State University
Subcutaneous tissue is frequently the target site for placement of continuous, real-time metabolic sensors. Since the 1960s, numerous research groups have developed needle-like sensor designs, patterned after the Clarke Electrode, to monitor glucose in subcutaneous tissue. These designs perform well in vitro but often fail in vivo due to sensor instability and tissue response. None of these studies focused on the mechanical properties of implanted sensors and how these properties may affect in vivo performance. To investigate the role of sensor stiffness on short term functionality we developed a low stiffness subcutaneous sensor patterned after the Clarke Electrode and tested it in rodents. The purpose of this study was two-fold. The first goal was to demonstrate the in vivo functionality of the flexible sensor. The second goal was to evaluate the effect of stiffness on functionality by co-implanting stiff and flexible sensors. In the first series of studies the low stiffness sensors provided glucose level measurements that fell within the A and B regions of the Clarke Error Grid 93.0% of the time. The results of the second study yielded similar accuracy; however, no performance difference was seen between the stiff and flexible sensors. We concluded that the flexible sensor works for at least 3days after implantation in the subcutaneous tissue of freely moving rats and that the key property of low stiffness has no differential effect on the accuracy of the sensor in the freely moving rodent model of these studies.
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