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3 figs., 3 tabs., Introduction: The quantification of knee range of motion is a clinically relevant measurement in the healthcare setting, as its decrease can alter activities of daily living. Collecting reliable measurements of the range of motion allows us to evaluate the reliability of interventions, or the severity of the pathology. The objective of this study was to obtain the intra- and inter- rater reliability of a protocol for the knee the range of joint motion, measured with an inertial sensor in asymptomatic subjects. Methods: The range of motion of 32 asymptomatic knees was measured. Two measurement sessions were performed by two different evaluators. A total of 8 measurements were made in each session: 2 measurements for flexion in supine decubitus position, 2 measurements for extension in supine decubitus, 2 measurements for flexion in standing position and 2 measurements for extension in standing position. Results: For inter-rater reliability, good results were achieved, with an ICC > 0.79 for all movements. The obtained data for intra-rater reliability in all the movements was excellent, with an ICC > 0.88. Conclusion: This study obtained excellent inter-rater and intra-rater reliability for healthy subjects.

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Chronic exposure of A(1) adenosine receptors (A(1)R) to A(1)R agonists leads to activation, phosphorylation, desensitization, and internalization to intracellular compartments of the receptor. Desensitization and internalization of A(1)R is modulated by adenosine deaminase (ADA), an enzyme that regulates the extracellular concentration of adenosine. ADA interacts with A(1)R on the cell surface of the smooth muscle cell line DDT1 MF-2, and both proteins are internalized following agonist stimulation of the receptor. The mechanism involved in A(1)R and ADA internalization upon agonist exposure is poorly understood in epithelial cells. In this report, we show that A(1)R and ADA interact in LLC-PK(1) epithelial cells. Exposure of LLC-PK(1) cells to A(1)R agonists induces aggregation of A(1)R and ADA on the cell surface and their translocation to intracellular compartments. Biochemical and cell biology assays were used to characterize the intracellular vesicles containing both proteins after agonist treatment. A(1)R and ADA colocalized together with the rafts marker protein caveolin. Filipin, a sterol-binding agent that disrupts rafts (small microdomains of the plasma membrane), was able to inhibit A(1)R internalization. In contrast, acid treatment of the cells, which disrupts internalization via clathrin-coated vesicles, did not inhibit agonist-stimulated A(1)R internalization. We demonstrated that A(1)R agonist N(6)-(R)-phenylisopropyl adenosine promotes the translocation of A(1)R into low-density gradient fractions containing caveolin. Furthermore, a direct interaction of the C-terminal domain of A(1)R with caveolin-1 was demonstrated by pull down experiments. These results indicate that A(1)R and ADA form a stable complex in the cell surface of LLC-PK(1) cells and that agonist-induced internalization of the A(1) adenosine receptor and ADA is mediated by clathrin-independent endocytosis.

The marker × environment interaction (M×E) genomic model can be used to generate predictions for untested individuals and identify genomic regions whose effects are stable across environments and others that show environmental specificity. The objectives of this study were: (1) to extend the M×E interaction model using priors that produce shrinkage and variable selection such as Bayesian Ridge Regression (BRR) and BayesB (BB), respectively, and (2) to evaluate the genomic prediction accuracy of M×E interaction, single-environment, and across-environment models using a multi-parental durum wheat population characterized for grain yield, grain volume weight, thousand-kernel weight and heading date in four environments. Breeding value predictions were generated for two prediction problems: cross-validation problem 1 (CV1) and cross-validation problem 2 (CV2). In general, results showed that the M×E interaction model performed better than the single-environment and across-environment models, in terms of minimization of the model residual variance, for both CV1 and CV2. The improved data-fitting gain over the other models was more evident for thousand-kernel weight and heading date (up to two-fold differences) as compared to grain yield and grain volume weight, which showed more complex genetic bases and smaller single-marker effects. Considering the Bayesian models used, BB showed better overall prediction accuracy than BRR. As proof-of-concept for the M×E interaction model, the major controllers of heading date, Ppd and FT on chromosomes 2A, 2B, and 7A, showed stable effects across environments as well as environment-specific effects. For GY, besides the regions on chromosomes 2B and 7A, additional chromosome regions with large marker effects were detected in all chromosome groups